The Economic Impact and Functional Applications of Human

The Economic Impact and

Functional Applications of

Human Genetics and Genomics

Commissioned by the American Society of Human Genetics

Produced by TEConomy Partners, LLC.

Report Authors: Simon Tripp and Martin Grueber

May 2021

TEConomy Partners, LLC (TEConomy) endeavors at all times to produce work of the highest quality, consistent with our contract

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Acknowledgements

ASHG and the project authors wish to thank the following organizations for their generous support of this study.

Invitae Corporation, San Francisco, CA

Regeneron Pharmaceuticals, Inc., Tarrytown, NY

The project authors express their sincere appreciation to the following indi-

viduals who provided their advice and input to this project.

ASHG Government and Public Advocacy Committee

Lynn B. Jorde, PhD

ASHG Government and Public Advocacy Committee (GPAC) Chair, President (2011)

Professor and Chair of Human Genetics

George and Dolores Eccles Institute of Human Genetics

University of Utah School of Medicine

Katrina Goddard, PhD

ASHG GPAC Incoming Chair, Board of Directors (2018-2020)

Distinguished Investigator, Associate Director, Science Programs

Kaiser Permanente Northwest

Melinda Aldrich, PhD, MPH

Associate Professor, Department of Medicine, Division of Genetic Medicine

Vanderbilt University Medical Center

Wendy Chung, MD, PhD

Professor of Pediatrics in Medicine and

Director, Clinical Cancer Genetics

Columbia University

Mira Irons, MD

Chief Health and Science Ofﬁcer

American Medical Association

Peng Jin, PhD

Professor and Chair, Department of Human Genetics

Emory University

Allison McCague, PhD

Science Policy Analyst, Policy and Program Analysis Branch

National Human Genome Research Institute

Rebecca Meyer-Schuman, MS

Human Genetics Ph.D. Candidate, Antonellis Lab

University of Michigan

Charles Schwartz, PhD

Senior Research Scientist Emeritus

Greenwood Genetic Center

Wendy Uhlmann, MS, CGC

Clinical Professor of Internal Medicine and Clinical Professor of Human Genetics

Genetic Counselor and Clinic Coordinator, Medical Genetics Clinic

University of Michigan

David Wheeler, PhD

Director of Precision Genomics

Department of Computational Biology

St Jude Children’s Research Hospital

Advisors

Lawrence Brody, PhD

Director, Division of Genomics and Society

National Human Genome Research Institute

Eric D. Green, MD, PhD

Director

National Human Genome Research Institute

Cristina Kapustij, MS

Chief, Policy and Program Analysis Branch

National Human Genome Research Institute

Cynthia Casson Morton, PhD

ASHG President (2014)

Professor of Obstetrics, Gynecology and Reproductive Biology and Professor of Pathology

Harvard Medical School

Chair, Obstetrics and Gynecology, and Director of Cytogenetics

Brigham and Women’s Hospital

Heather C. Mefford, MD, PhD

ASHG Program Committee Chair (2018), Board of Directors (2021)

Associate Professor

Genetics, Epilepsy Program—Center for Integrative Brain Research

University of Washington and Seattle Children’s

Kiran Musunuru, MD, PhD, MPH, ML

ASHG Program Committee Chair (2019), Board of Directors (2021)

Professor of Medicine

Director, Genetic and Epigenetic Origins of Disease Program, Cardiovascular Institute

Perelman School of Medicine at the University of Pennsylvania

David L. Nelson, PhD

ASHG President (2018)

Professor

Molecular and Human Genetics

Baylor College of Medicine

Telephone and Email Interview Participants

Todd R. Golub, MD

Director, Founding Core Institute Member, Broad Institute of MIT and Harvard, and

Founding Core Member and Director of the Gerstner Center for Cancer Diagnostics, Broad Institute

Leroy Hood, MD, PhD

Senior Vice President and Chief Science Ofﬁcer

Providence St. Joseph Health, and

Chief Strategy Ofﬁcer and Professor, Institute for Systems Biology

Kathryn A. Phillips, PhD

Professor of Health Economics and Health Services Research, and

Founding Director, UCSF Center for Translational and Policy Research on Personalized Medicine

University of California, San Francisco

Philip Reilly, MD, JD

Venture Partner, Third Rock Ventures

David Veenstra, PharmD, PhD

Professor and Associate Director, Comparative Health Outcomes, Policy & Economics (CHOICE) Institute

School of Pharmacy, University of Washington

Carrie D. Wolinetz, PhD

Associate Director for Science Policy

National Institutes of Health

American Society of Human Genetics Staff

Mona Miller, MPP

Chief Executive Ofﬁcer

Derek Scholes, PhD

Senior Director, Policy and Advocacy

Lyly G. Luhachack, PhD

Policy and Advocacy Specialist

Contents

Executive Summary ......................................................................................................................................................ES-1

I. Introduction ........................................................................................................................................................................ 1

A. Science as a Driver of Economic and Social Advancement ................................................................................. 1

B. Funding and Supporting American Science ................................................................................................................ 2

C. Human Life Sciences .................................................................................................................................................................... 2

D. The Genome—Coding Life ....................................................................................................................................................... 3

E. Human Genetics and Genomics—Applications and Impacts............................................................................ 5

F. Purpose of the Study .................................................................................................................................................................... 7

G. Limitations of the Study ........................................................................................................................................................... 9

II. The Economic Impact of Human Genetics and Genomics ........................................................................... 11

A. Measuring Human Genetics and Genomics Economic Impacts .....................................................................11

B. Drivers of Economic Impacts: Methodology and Assumptions ......................................................................13

C. Economic Impact Analysis of Human Genetics and Genomics in the U.S. ............................................. 19

D. Healthcare Costs for Genetic Diseases .......................................................................................................................... 20

III. The Functional Impacts of Human Genetics and Genomics .................................................................... 23

A. The Structure of Functional Impacts (Application Domains of Human Genomics) .........................23

B. Fundamental Knowledge Advancement .................................................................................................................... 24

C. Functional Applications for Human Health .................................................................................................................26

D. Summary .......................................................................................................................................................................................... 65

IV. Into the Future ............................................................................................................................................................. 67

A. Ongoing Fundamental Discovery .................................................................................................................................... 68

B. Expanding the Clinical Application of Genomics ................................................................................................... 70

C. Educating and Updating Providers .................................................................................................................................. 71

D. Ethical Considerations .............................................................................................................................................................. 71

E. Conclusion .........................................................................................................................................................................................72

Glossary of Terms .............................................................................................................................................................. 75

Appendix—Additional Economic Impact Information ...................................................................................... 77

ES-1

Modern life sciences and associated advancements

in biopharmaceuticals, diagnostics, medical devices,

and healthcare services have enabled unprecedented

improvements in human health and longevity.

Executive Summary

Perhaps nowhere has life science research advanced

more in the modern age than through insights provid-

ed by genetics and genomics. This ﬁeld is both funda-

mental in biological research—elucidating the basic

code of life, DNA, upon which our form and function

depend—and in enabling applied and translational

discoveries across most diseases and health disorders.

This report examines and describes the positive im-

pacts that are derived from modern human genetics

and genomics science and its associated commercial

and clinical applications on the nation’s economy,

society, and the health and well-being of individuals.

Twenty years after the completion of the Human

Genome Project, there has been widespread expan-

sion and application of human genetics and genomics

technologies. Technologies for sequencing and for

genome analysis have advanced quite spectacularly—

to the extent that genome sequencing is now both

fast and affordable. The technologies of genetics

and genomics, and the research advancements they

have enabled scientists to make, have now brought

human genetics and genomics to a visible inﬂection

point—a point in time where scientiﬁc discoveries are

rapidly translating into clinical insights and signiﬁ-

cant human health and well-being advancements.

The Economic Impact

of the Human Genetics

and Genomics Sector

The U.S. economy has advanced on the back of sci-

entiﬁc progress—progress that has enabled national

leadership in diverse industries such as aerospace,

energy, agriculture, transportation, advanced ma-

terials, information technology, and biotechnology.

Continuing to strengthen the competitiveness of

the U.S. economy requires ongoing expansion of the

national capacity for innovation and the scientiﬁc and

technological research and development (R&D) upon

which innovation depends. Particularly important is

leveraging science and innovation to give rise to new,

fast-growing, advanced industries that spark econom-

ic growth and improved standards of living. Born out

of federal investment in the Human Genome Project,

the U.S. achieved early leadership in the genetics and

genomics industry—leadership that has resulted in the

growth of an important and dynamic economic sector.

Substantial U.S. economic activity, supporting a

large volume of high-paying jobs across the nation,

is generated from the performance of genetic and

genomic research, the development and manufactur-

ing of commercial genomic technologies, the broad

range of diagnostics products and therapeutics on the

ES-2

Figure ES-1: The Economic Impact of the Human Genetics

and Genomics Sector in the United States

Human Genetics &

Genomics Focused

Research Expenditures,

Services, and Corporate

Operations in the U.S.

Purchase of Secondary

Inputs & Services from U.S.

Suppliers and Vendors

Human Genetics &

Genomic Supported

Employees Spending

Disposable Income

in the U.S. Economy

Total Economic

Impacts of

Human Genetics

& Genomics

DIRECT EFFECT INDIRECT EFFECT INDUCED EFFECT

$3.3B

FEDERAL RESEARCH

Federal research funding, using a conservative deﬁnition of what constitutes human genetics

and genomics research, reached $3.3 billion in 2019, with most of this coming from NIH.

152,000

INDUSTRY JOBS

89,464 core private sector industry jobs and an estimated 62,710 additional extended

industry jobs (related employment share from major pharmaceutical and medical

testing/diagnostics companies).

850,000

TOTAL SUPPORTED JOBS

With a direct employment estimate of nearly 166,000 academic and industry jobs,

human genetics and genomics supports more than 850,000 total jobs. Each direct

human genetics and genomics job supports 4.12 additional jobs in the U.S. economy.

$265B

TOTAL ECONOMIC IMPACT

The direct economic activity generated by the human genetics and genomics industry

exceeds $108 billion in 2019 and ultimately supports a total of more than $265 billion across

the U.S. economy. Every $1.00 of direct human genetics and genomics activity generates

an additional $1.45 in the U.S. economy.

$5.2B

DIRECT FEDERAL TAX REVENUES

The federal tax revenues of $5.2 billion generated by the direct operations of the human

genetics and genomics domain alone surpasses the single year federal investment in human

genetics and genomics of approximately $3.3 billion across all federal agencies.

4.75:1.00

FEDERAL RETURN ON INVESTMENT

In the simplest of terms, from a federal investment and revenue perspective, the overall

economic impacts of U.S. human genetics and genomics generates a return on investment

(ROI) of more than 4.75 to 1.00 ($3.3 billion in federal investment in human genetics and

genomics – while the whole domain generates $15.5 billion in federal tax revenues).

Source: TEConomy Partners, LLC.

market that are derived from genomics knowledge

and have pharmacogenomic associations, and the

associated healthcare services that are delivered.

The economic impact of the human genetics and

genomics sector on the U.S. economy is assessed

using the standard regional economics methodology

of input-output analysis. The results demonstrate

the growth of a powerful economic sector across

the nation— a sector that has grown ﬁve-fold in

its annual economic impact since 2010. Even more

importantly, it is a sector that also generates robust

functional impacts in terms of human health and

well-being. Figure ES-1 summarizes some of the

topline ﬁndings from the economic impact analysis.

The sector also supports high wage jobs. Because it

requires a well-educated and technically skilled work-

force, direct jobs in the genetics and genomics sector

pay more than $130,000 in annual total compensation

(income and beneﬁts) per worker, while the total jobs

supported by human genetics and genomics eco-

nomic activity (direct + induced) average greater than

$81,000 in compensation per employee.

ES-3

The Functional Impacts of

Human Genetics and Genomics

The speed and affordability of gene sequencing

and advanced genomic data analytics have helped

produce deep biomedical insights and innovations,

which are being combined with advancements in

biopharmaceuticals, diagnostics, and other medical

technologies that leverage genomic information. An

evident tipping point has been achieved where the

utility of genomics and wide-spread use of sequencing

is clearly advantageous for signiﬁcantly enhancing

human health outcomes. As this report highlights,

the functional application of human genetics and

genomics to clinical healthcare is now a daily reality

in some medical ﬁelds (e.g., cancer diagnosis and

treatment) and is increasingly front-and-center in

neurological, psychiatric, gastrointestinal, immunolog-

ic, rheumatologic, dermatologic, pain management,

and other application areas of clinical medicine. It is

also fundamental to advancements being made in

the diagnosis and treatment of a wide range of rare

diseases and disorders—helping to end the diagnostic

odysseys of millions of patients afﬂicted with rare

diseases that have been difﬁcult to diagnose and

sparsely served in terms of available treatments.

In reviewing the functional applications of human

genetics and genomics, the authors ﬁnd that

the positive impacts being generated are highly

diverse—generated within eight major domains

Figure ES-2: Functional Biomedical Impact Domains

(Applications) of Human Genetics and Genomics

Minable Big Data

(Discovery Science)

Identifying Predisposition

to Diseases and Disorders

Diagnosing Diseases

and Disorders

Rational Drug

Development

Pharmacogenomics

(Personalized Medicine)

Gene Editing

and Gene Therapy

Human-Microbe

Interaction

Environmental Genomics

and Metagenomics

Analyzing sequencing

data from large and

diverse populations to

provide deep insights

into disease biology and

identify characteristics

associated with health.

Genetic and genomic

testing to identify

carrier status, and

identify predisposition

for genetic disease via

prenatal, newborn and

adult screening.

Using biomarkers

and gene signatures

to diagnose the

presence of diseases

or disorders that are

associated with

speciﬁc genes or

gene products.

Using genetic

information and gene

associated biomarkers

to inform molecular

targeting in drug design.

Using sequencing data

to enable the

prescription of drugs

best suited to the

patient’s genotype

(increasing efﬁcacy and

reducing adverse events)

Modifying the genes

associated with a

disease or disorder

to treat or cure the

disease

Biomedical

Application

Domains of

Human

Genetics

and

Genomics

Examining the human

genome’s impact

upon hosted microbial

populations, and

microbe impacts upon

the human genome

and gene expression

Examining the impact

of human interactions

with the environment

on the human genome,

gene regulation, muta-

tion, and disease

etiology.

Biomedical

Application

Domains of

Human Genetics

and Genomics

Source: TEConomy Partners, LLC.

ES-4

of activities impacting human health. These are

summarized and brieﬂy described in Figure ES-2.

The eight domains identiﬁed in Figure ES-2 are

already having profound impacts in advancing

clinical health sciences and health outcomes.

Each of these areas is proﬁled brieﬂy below and

detailed further in the full body of the report.

1. Minable Big Data (Discovery Science)

Advancements in high-speed gene sequencing

technologies have facilitated the assembly of exabytes

of genomic information that can be analyzed (assisted

by highly advanced and automated analytical systems)

for unique insights into genome structure and func-

tion and the association of gene variants with human

diseases and health disorders. It is anticipated that by

2025 more than 60 million patients will have had their

genome sequenced in a healthcare context.

Access to

extremely large volumes of sequenced individuals pro-

vides a rich platform for important scientiﬁc discovery

and for advancing the identiﬁcation and classiﬁcation

of genomic variant pathogenicity (variants associated

with causation of disease). Both science and techno-

logical capabilities are now at the point where the

analysis of genomic and phenomic big data provides

a powerful pathway forward for biomedical discovery

and clinical applications to improve human health.

2. Identifying Predisposition

to Diseases and Disorders

One of the primary research and clinical applications

of human genetics and genomics is identiﬁcation of

the potential predisposition for individuals to develop

speciﬁc diseases or health disorders. Modern genetic

screening for such predispositions divides into three

key categories: 1) carrier screening, which tests a

prospective parent for the presence of gene variants

that have been shown to be associated with risk of

passing down a hereditary disorder (thereby helping

 An exabyte =  bytes (,,,,,, bytes).

 Birney, Ewan. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. , no. , March-

April .

 National Center for Advancing Translational Sciences, Genetic and Rare Diseases Information Center. “FAQs About Rare Diseases.” https://

rarediseases.info.nih.gov/diseases/pages//faqs-about-rare-diseases. Accessed  May .

 Ibid.

to inform family planning and associated decisions);

2) pre-natal and post-natal testing, which focuses on

testing for genetic predisposition to disease in the

fetus or in newborns; and, 3) child and adult testing.

Information provided by predisposition screening

enables patients and their physicians to make in-

formed healthcare decisions, plan follow-up health

monitoring strategies, and identify strategies for

care using evidence-based clinical best practices.

3. Diagnosing Disease,

Rare Diseases, and Disorders

Whole genome and whole exome sequencing are

increasingly being used in clinical practice to facilitate

the diagnosis of diseases or health disorders. In addi-

tion to the many common chronic diseases (such as

heart disease, diabetes, cancer, etc.), approximately

7,000 rare diseases have been recognized

and have

historically been a signiﬁcant challenge to diagnose.

Rare diseases, by their inherent nature of being rare,

present diagnostic challenges because so few physi-

cians have encountered them. Often, these diseases

may present symptoms seen in other, more common

diseases, resulting in an understandable misdiagnosis

and inappropriate treatment strategies being adopt-

ed. Patients, and their families, may embark on long

“diagnostic odysseys”, seeing dozens of practitioners,

undergoing multiple tests and procedures, enduring

fruitless attempts at treatment over many years

without ever getting a deﬁnitive, accurate diagnosis.

Genetic and genomic testing provides a pathway

to solving this dilemma in multiple diseases and

disorders impacting many thousands of patients.

Collectively, rare diseases have a signiﬁcant population

impact, with approximately 1 in 10 individuals having

a rare disease (estimated at between 25-30 million pa-

tients in the U.S. and 350 million worldwide).

Modern

genetic and genomic diagnostic tools, informed by

ES-5

scientiﬁc advancements in identifying gene variants

associated with speciﬁc diseases, are providing clear

diagnostic beneﬁts. By deploying genetic and ge-

nomic testing, up to and including whole genome

sequencing, diagnostic odysseys may be ended for

many patients—not only providing a pathway to

appropriate treatment but also reducing signiﬁcant

waste in the healthcare system and the associated

costs of incorrect diagnosis. Even if no treatment is

available, peace of mind can result through simply

having an “answer” and being able to end the costly

hunt for diagnosis. It has been noted that “this is

clearly the most powerful diagnostic tool ever devel-

oped for the millions of children with rare diseases.”

4. Rational Drug Development

Rational drug development uses genetic and genomic

information to advance the development of new

biopharmaceuticals to treat diseases. Biomarkers

(genes or gene products) are providing molecular

targets for purposefully designed drugs that are engi-

neered to bind to targets. The application of genetics

and genomics to drug development has resulted in

multiple clinical successes, with speciﬁc examples

highlighted in this report. Biopharmaceutical com-

panies are now able to use genetic and genomic

information to target the trials of their pharma-

ceutical and biologic molecules to patients who

have been preselected through the presence of

biomarkers (often genetic). This has the potential to

advance more drugs successfully to market since

 Kingsmore, Stephen. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. , no. ,

March-April .

they are more likely to demonstrate efﬁcacy in

their trials by virtue of being rationally targeted.

It is also notable that progress in genetics and

genomics has enabled pharmaceutical research

to increasingly address rare diseases—helping to

rebalance biopharmaceutical research in terms of

work on chronic diseases versus rare diseases.

5. Precision Medicine and Targeted

Therapeutics (Pharmacogenetics)

Having an ability to sequence a patient’s whole

genome rapidly and cost-effectively has opened

the door to a new paradigm in healthcare termed

“precision medicine” whereby an individual’s genetic

proﬁle is used to guide decisions made in regard to

the prevention, diagnosis, and treatment of disease.

The discipline of “pharmacogenetics” (also “pharma-

cogenomics”) has developed as a ﬁeld of research

and, increasingly, clinical practice, that addresses the

genetically determined variation in how individuals re-

spond to speciﬁc drugs in terms of differences in dose

requirement, efﬁcacy, and the risk of adverse drug

reactions (ADRs). It is increasingly being employed to

help physicians select the “right drug and the right

dose” for a patient based on their genome (assuming

there is statistically signiﬁcant clinical information

linking a drug to speciﬁc gene variants in terms of efﬁ-

cacy and side effects). Currently, pharmacogenetics is

improving health outcomes along three primary paths:

The ability to tailor a drug regimen to a speciﬁc genetic code that is

truly personalized to that speciﬁc DNA double helix has been a dream of

researchers, physicians, and patients alike. Advances in precision medicine,

speciﬁcally around the genome…are making this dream a reality.”

Kristen Ciriello Pothier. Personalizing Precision Medicine. A Global Voyage from Vision to Reality. John Wiley & Sons, Inc., 2017.

ES-6

• Selection of the therapeutic (among multiple

choices) that is likely to prove most efﬁcacious

based on the patient’s genome and a drug’s

proven efﬁcacy for their speciﬁc genotype.

• Ruling-out a therapeutic (among multiple

choices) based on the patient’s genome and

a drug’s potential for unacceptable adverse

side effects given their speciﬁc genotype.

• Development of an optimized drug dosage for a

patient based on their genotype’s inﬂuence on

the rate at which they will metabolize the drug.

Cancer is perhaps the most well-recognized cluster

of disease for which genetic tests may impact drug

selection and dosing; however, analysis of U.S. Food

and Drug Administration (FDA) data shows that

pharmacogenetic associations are also in place for

multiple chronic diseases and conditions, covering

applications in major categories such as cardio-

vascular disease, gastroenterological diseases and

disorders, infectious diseases, neurological diseases

and disorders, psychiatric conditions, and rheuma-

tologic diseases. Pharmacogenetic associations

now span a range from relatively rare diseases, such

as Tourette’s syndrome and Tardive dyskinesia, to

common conditions, such as hypercholesterolemia

and depression. There are more than 100 drugs for

which the associations are now listed by the FDA.

6. Gene Editing and Gene Therapy

As noted above, genetic and genomic advancements

are elucidating gene variant associations with the

predisposition for disease, providing enhanced diag-

nosis of diseases, and providing increasingly effective

pathways for therapeutics and disease treatment.

Another developing approach is to use the expanding

knowledge of gene variants associated with disease

to provide targets for potential modiﬁcation of a

patient’s genes themselves—modiﬁcation that has

the goal of treating, and potentially curing, the target

 It should be noted that the discussion of gene editing and gene therapy pertains to modifying non-hereditable (somatic) genes—changes

to an individual’s genes that will only affect the individual being treated but not the genes of future generations. There is ongoing discussion

and public debate about the potential use of gene editing to make heritable genetic changes (changes to the germline). Such genome edits

would result in changes to an individual’s DNA being passed to their progeny and subsequent generations. At the present time, the general

consensus of leading organizations in medical genetics, genetics research, and genetic counseling is that genome editing which culminates

in human pregnancy should not be undertaken, and that further research is required into the scientiﬁc, clinical, and ethical implications of

germline editing.

disease through what is termed gene editing or gene

therapy. Ultimately, gene editing and gene therapy

represent new pathways to the treatment and curing

of diseases, but these approaches are still in the early

stages of clinical application.

Part of the caution in

clinical application arises from a need for further study

of the potential for off-target gene edits (mutagenesis)

to occur in non-targeted genes and for unintended

mosaicism to occur. Despite these challenges, there

are several important gene therapies that have suc-

cessfully advanced through clinical trials, helping to

treat a series of previously untreatable rare diseases.

It is a promising ﬁeld for ongoing advancement.

7. Human-Microbe Interactions

Each of us is host to communities of trillions of

microbes. Microbes serve important functions for

humans, for example aiding our digestion and the

breakdown of micronutrients, defending us from

pathogenetic microbes, and priming our immune

system. Recent research has shown that we have a

symbiotic two-way genetic interaction with microbes,

with microbes impacting our genes and gene expres-

sion, and human genotype impacting the make-up of

the microbial communities we host.

While microbes play an important positive role in

our health, many microbes are pathogenic, being

the causative agents for human infectious diseases.

Research is ﬁnding that individual genomes can

be associated with resistance or susceptibility to

certain infectious diseases, and the recent COVID-19

pandemic, coinciding with the current signiﬁcant

volumes of patients for which genome sequences

are available, has enabled signiﬁcant clinical study of

genome effects on viral susceptibility and resistance.

ES-7

8. Metagenomics and

Environmental Genomics

There exists a vast network of interactions between

individual genomes and other biological and environ-

mental systems. Each of us walks a slightly different

path through life, experiencing different inﬂuences

upon our physiology in terms of the food we eat, the

amount of sun we expose ourselves to, the environ-

ments we experience in our jobs, the pathogens that

we by chance encounter, etc. Any and all of these and

more may be subtly changing (mutating) letters in our

genome or periodically inﬂuencing gene regulation

or expression. Metagenomics is the ﬁeld of genomics

that investigates these interactions and their effects.

Obviously, the human genome is highly complex. Add

to that all the genomes in the environment with which

one may come into contact, and the enormity of the

subject comes into focus. Large-scale sequencing

programs are, however, providing a rich resource of

data for scientists to mine in metagenomic studies.

Genomics in the

COVID-19 Pandemic

Genomics rapidly assumed crucial roles in

COVID-19 research and clinical care in areas such

as: (1) the deployment of DNA and RNA sequenc-

ing technologies for diagnostics, tracking of viral

isolates, and environmental monitoring; (2) the

use of synthetic nucleic acid technologies for

studying SAR- CoV-2 virulence and facilitating vac-

cine development; (3) examination of how human

genomic variation inﬂuences infectivity, disease

severity, vaccine efﬁcacy, and treatment response;

(4) the adherence to principles and values relat-

ed to open science, data sharing, and consortia

based collaborations; and (5) the provision of

genomic data science tools to study COVID-19

pathophysiology. The growing adoption of ge-

nomic approaches and technologies into myriad

aspects of the global response to the COVID-19

pandemic serves as another important and highly

visible example of the integral and vital nature of

genomics in modern research and medicine.

Eric D. Green, et al. “Perspective: Strategic Vision for

Improving Human Health at the Forefront of Genomics.”

Nature, vol. 586, no. 29, October 2020.

ES-8

Conclusion

The ﬁelds of human genetics and genomics are

having profound positive impacts not only in terms

of biomedical discovery, but also in terms of the

clinical practice of medicine—working to improve

the lives for millions of patients and demonstrating

great promise for future highly positive contribu-

tions to human health and well-being worldwide.

As the eight functional domains for human health

application of genetics and genomics illustrate,

this ﬁeld of science (and the expanding industry

associated with it) generates a profound impact

on biomedical research and the practice of clinical

healthcare. In addition to applications in human

medicine and wellness, there are also several

non-medical human applications of genetics and

genomics, including forensic science, anthropology

and genealogy, evolutionary biology, and paternity

testing. These are also highlighted in the report.

It is readily evident that, as fundamental genomic

knowledge has expanded, the enhanced understand-

ing of genetic mechanisms generated, in concert with

access to rich whole exome and genome datasets

(and associated reference compendia of human gene

variants), has opened the door to a new era of discov-

ery and progress in medicine. The impacts of these

advancements are now increasingly reverberating

across medicine, a fact highlighted by Eric Green, the

Director of the National Human Genome Research

Institute (NHGRI), and colleagues who note that:”

With insights about the structure and function

of the human genome, and ever improving

laboratory and computational technologies,

genomics has become increasingly woven

into the fabric of biomedical research, medical

practice, and society. The scope, scale, and

pace of genomic advances so far were nearly

unimaginable when the human genome

project began; Even today, opportunities

 Green, Eric D., et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature, vol. ,  Oct. .

beyond their initial expectations, with many

more anticipated in the next decade.

While generating these positive functional impacts

is the raison d’etre for pursuing the advancement of

human genetics and genomics, it has also had the very

positive spillover effect of building a powerful science-

and technology-based economic sector for the U.S.—a

sector that supports over 850,000 jobs across the nation

and generates a $265 billion economic impact in terms

of U.S. economic output. The continued innovation in

human genetics and genomics is expanding the stock

of knowledge upon which our continued advancement

depends and shows great promise to continue to do

so long into the future. The ﬁeld represents a particu-

larly strong example of how investing in fundamental

and applied science generates robust economic,

social, and individual beneﬁts for humankind.

I. Introduction

A. Science as a Driver of Economic

and Social Advancement

Scientiﬁc research is of high importance not only be-

cause it reveals fundamental truths but also because it

increases the stock of human knowledge upon which

economic, societal, and technological progress de-

pends. The U.S. economy, in particular, has advanced

on the back of scientiﬁc progress that has enabled

national leadership in diverse industries such as aero-

space, energy, agriculture, transportation, materials,

digital technology, communications, and healthcare.

In the past two decades, scientiﬁc advancements

have seen new industries advanced, typically with the

U.S. being an early innovator in commercial applica-

tions of both science and associated technologies.

Developments in physics, chemistry, biology, and

mathematical and computational sciences have paved

the way for new industries in nanotechnology and

advanced materials, renewable energy, AI-powered

autonomous systems, biotechnology, and genetic

engineering. There has also been an observable trend

of “convergence,” whereby multiple science and

technological disciplines combine to advance new

opportunities. Advancements in computational and

digital analytics converging with large-scale data from

other sciences have helped accelerate this trend.

What has become clear is that continuing to strength-

en the competitiveness of the U.S. economy requires

ongoing expansion of national innovation capacity

and the scientiﬁc and technological research and

development (R&D) upon which that innovation

From Fundamental

to Applied Research

Public/Private and Market/

Non-Market Returns

Scientiﬁc research may produce both private and so-

cial returns. Research that leads to improved knowl-

edge, national security, public health, enhanced food

security, etc. provides social (public) returns. Research

generating a patented technology or improving the

productivity of a production process provides private

returns to those inventing and using the research-

based tool or knowledge for commerce. Often, re-

search leads to both forms of return at the same time.

For example, the development of a vaccine for an

infectious disease provides private monetary returns

to the vaccine developer and social returns through

enhanced public health. Both types of returns mo-

tivate investment in research. Research ﬁnds that

the rate of social return on R&D exceeds the rate of

private return (although both are strong). Despite the

large U.S. national investment in research, analysis

shows that optimal investment in research would be

more than four times actual investment.

The robust levels of social return on research un-

derpin the core rationale for public investment in

research. Indeed, without public support for research,

a wide-ranging and important suite of research topics

would go unaddressed. Because so much important

research is non-market (focused on phenomena or

subject matter without an immediate line-of-sight to

a market application) or focused on the generation of

social returns (beneﬁting society overall, but perhaps

not able to realize private returns to investment),

the public sector plays a critically important fund-

ing function in the R&D ecosystem. Further, private

sector investment in basic science is relatively scarce

because of the speculative nature of early fundamen-

tal research, the long time-horizons involved in the

performance of basic inquiry, the risk of experiment

failures, and, most importantly, the lack of immediate

line-of-sight to market.

What is critically important to understand is that the

U.S. economy, and the innovations and technologies

upon which it depends, is built upon a bedrock of

fundamental scientiﬁc advancements and an overly-

ing strata of applied and translational discoveries that

leverage fundamental knowledge.

depends. This requires funding for research and the

institutions that perform research, together with

funding for the education of the scientists, technol-

ogists, engineers, mathematicians, and other skilled

intellectual talent that innovates and produces the

products and services that result from innovation.

B. Funding and Supporting

American Science

The federal government has been and continues

to be an essential component of the U.S. research

ecosystem, funding research performed at univer-

sities, independent research institutions, and other

organizations and conducting research within na-

tional institutes and laboratories. Federal funding for

research has been especially important in supporting

fundamental science, which in turn represents the

platform upon which applied research may advance.

Federal funding also plays an important role in trans-

lating research into early-stage commercialization,

through translational research funding and dedicated

early-stage venture support through the federal

Small Business Innovation Research (SBIR) and Small

Business Technology Transfer (STTR) programs.

Support for scientiﬁc research in the U.S. comes from

both public and private sources. As noted in the prior

sidebar textbox, public resources focus primarily on

 “ Global R&D Funding Forecast”, R&D World, February , WTWH Media, LLC.

 Kochanek, Kenneth D., et al. “Mortality in the United States, .” NCHS Data Brief, No. , Dec. .

 Ibid.

supporting basic through applied research while

private (commercial) funding focuses primarily on

powering applied and translational research that

advances innovations into commercial application. In

total, the U.S. R&D enterprise spent $596.6 billion in

2019, representing 2.84% of GDP.

However, the extent

to which the economy is driven by and built upon the

innovative output of R&D makes the impact of R&D

on overall GDP many times larger and a dominant

factor in U.S. economic success. The economic future

of the U.S. hinges upon research and development.

C. Human Life Sciences

Scientiﬁc research produces many beneﬁts and

returns for society, but perhaps none are as important

as the preservation and extension of human life itself.

Modern life sciences and associated advancements

in biopharmaceuticals, diagnostics, medical devices,

and healthcare services have enabled unprecedented

improvements in human health and longevity. Today,

the average life expectancy for a newborn female

and male in the U.S. is 81.4 years and 76.3 years,

respectively.

In 1950, those same metrics were 71.1

and 65.6 years.

Average lifespans have expanded

by more than a decade in less than two generations

through advancements in health, hygiene, and safety.

Today, a powerful argument can be made for substantially

increased investment in research in the United States. Equally

great is the need to train the next generation of scientists and

citizens for what will be a very different world.”

National Academy of Sciences. 2021. “The Endless Frontier. The Next 75 Years in Science.”

“

The impact and importance of human life science

advancement have come sharply into focus during the

COVID-19 pandemic, where R&D-based innovation of

diagnostic tests, advanced therapeutics, and the rapid

development of vaccines has proven crucial in forg-

ing a path for a return to normal life and commerce.

As noted in a recent report: “the COVID-19 crisis has

vividly illustrated the critical importance of life science

research and innovation systems and the ecosystems

that support the advancement of innovations through

commercial deployment to address health needs.”

Scientiﬁc advancements in biology and medicine

contribute to our daily lives and are also unveiling the

incredibly complex physical mechanisms and human/

environment interactions that govern our develop-

ment and health. The Russian doll analogy appears

to hold, with the life sciences uncovering level upon

level of complexity and interrelationships in biological

structures, mechanisms of inﬂuence, and associated

health outcomes. While unveiled complexity may

confound easy solutions to questions and problems,

it also provides an expanding universe of potential for

discoveries, applications, and functional possibilities.

 Tripp, Simon, et al. Response and Resilience: Lessons Learned from Global Life Sciences Ecosystems in the COVID- Pandemic. TEConomy

Partners, LLC for Pﬁzer, Inc., Jan. .

Perhaps nowhere has life science research advanced

more in the modern age than through insights

provided by genetics and genomics. This ﬁeld is both

fundamental in biological research—elucidating the

basic code of life, DNA, upon which our form and func-

tion depend—and in enabling applied and translational

discoveries across most diseases and health disorders.

D. The Genome—Coding Life

Humans are complex. That is true on many levels,

and it is certainly true in terms of our biology. The

more biologists learn of our biological structure

and function, the more complex and intricate

the machinery of our biology is revealed to be.

We each comprise approximately 30 trillion indi-

vidual cells and over 200 different cell types. Our

development and ongoing biological function are

orchestrated by our DNA (deoxyribonucleic acid), a

linear molecule arranged in a double helix (a spiraling

ladder) comprising linked base pairs of the nucleo-

tides adenine (A) and cytosine (T), and guanine (G)

and thymine (T). Our DNA contains six billion base

pairs of these nucleotides, the sum of which is called

Investing in People

and Infrastructure

Science relies on an educated base of sci-

entists who make discoveries and is also

advanced through the development of new

tools and technologies that power experi-

ments and enable new insights into biolog-

ical processes. For example, advancements

in ultra-high resolution imaging technology,

functional imaging of real-time processes,

analytical chemistry instruments, computa-

tional systems, and gene sequencing equip-

ment have facilitated leaps forward in funda-

mental and applied scientiﬁc insights.

our “genome,” which is effectively the governing

instruction set and a regulatory “code” for our bodies.

The six billion base pairs of our genome are organized

into 46 chromosomes (23 inherited from our mother

and 23 from our father). A chromosome consists of

a long section of DNA containing up to 500 million

base pairs of DNA with thousands of genes. An

individual “gene” is deﬁned as a grouping of base

pairs that together perform a function, encoding the

synthesis of a gene product (either RNA or a protein).

We each have approximately 20,000 protein-coding

genes, which comprise circa 2% of our genome.

As genetics and genomics developed as scientiﬁc

disciplines, for a long time the standard hypothesis

was that the part of our genome that “mattered” is

the 2% comprising our protein-coding genes, because

proteins are the functional biomolecules performing

the vast majority of biological activities. It was com-

mon to consider the 98% majority of our DNA as “junk

DNA”, legacy base pairs accumulated over the huge

span of time in our evolution, but no longer relevant or

“functional” to our development and predominant bio-

logical functioning. We now know that is not the case.

 Parrington, John. The Deeper Genome: Why There Is More to the Human Genome than Meets the Eye. Oxford University Press, .

After the publishing of the draft human genome by

the Human Genome Project and Celera, an inter-

national team of 442 scientists from 32 institutions

embarked on a large-scale team research project

called ENCODE (the ENCyclopedia of DNA Elements),

which used leading edge approaches to measure

biochemical activity across the entire human genome,

not just protein coding genes. ENCODE revealed that

the non-protein coding regions are far from being

“junk” and primarily contain DNA with an active

biochemistry, even if the preliminary ﬁndings did not

elucidate the function of that activity. The results

indicate a far more complex and multifaceted func-

tionality to our genome than previously thought.

Complicating matters further is that while the genome

codes for our fundamental life processes it is not

deterministic. Other factors also inﬂuence our biology

and health, including a multitude of interactions

with external environmental factors and stimuli,

such as the foods we consume and the microbial

communities that inhabit us over our life journey.

We are all the same species, homo sapiens, but we

are all different. None of us have exactly the same

genome sequence nor the same environmental

interactions. A large number of the diseases and

health disorders we will face across our lifespan will

be similarly diverse and complex, many being found

to be associated with multiple genes and gene

variants in combination with wide-ranging external

factors—for example, prior infection with pathogens

or differential exposure to mutagenic factors such as

chemicals or radiation (causing genotoxic injury).

Numerous diseases and health disorders result

from single gene changes (known as monogenic

or Mendelian diseases), where a variant within a

single gene may code the wrong protein or a dys-

functional gene product. However, many diseases

with genetic engagement involve multiple genes

and interactions between various genes and ad-

ditional factors. Many diseases, including most of

We also are each host to trillions of

microorganisms found in our gut and

other parts of our anatomy, many of

which play an important symbiotic role

for us in digestion and immune system

function. Each of these microorganisms

has its own DNA. Collectively, all of

those microorganisms and their DNA

comprise our “microbiome.” Research in

epigenetics has found that microbiome

structure can inﬂuence and impact

human gene expression and regulation.

our large-scale chronic diseases, turn out to be a

complex soup of genetic, epigenetic, and envi-

ronmental factors interfacing with one another.

As individuals, our incredible complexity, and the

biologically inﬂuential environmental factors we

each uniquely encounter across our lives, explain

why the development of diagnostics and drugs

is such an intense, difﬁcult, and expensive chal-

lenge. Finding generic solutions to individually

variable disease causations and expressions is no

small task. It is further complicated by the fact

that genetic, and other factors, can inﬂuence how

we each respond to and metabolize a drug.

Biomarkers are one of the pathways by which the

complexity problem is resolved. At the highest level, a

“biomarker” is a measurable substance in an organism

whose presence is indicative of some phenomenon

such as disease, infection, or environmental exposure.

When a biomarker is discovered related to a disease,

it provides a target for further research, a potential

measure to be used in achieving diagnosis, and, if

found to be “druggable,” a target for a therapeutic.

In 1998, the National Institutes of Health Biomarkers

Deﬁnitions Working Group deﬁned a biomarker

as “a characteristic that is objectively measured

and evaluated as an indicator of normal biological

processes, pathogenic processes, or pharmacologic

responses to a therapeutic intervention.”

Genetics

and genomics advancements, including technolog-

ical advancements such as genome sequencing,

have provided an important modern pathway for

identifying genetic biomarkers, including diagnostic

and therapeutic targets. As extensive collections of

whole-genome or partial genome sequences build,

scientists can mine these sequences to identify

 Strimbu, Kyle, and Jorge A Tavel. “What are Biomarkers?” Current Opinion in HIV and AIDS vol. , (): -. doi:./

COH.beed

 National Human Genome Research Institute. “The Cost of Sequencing a Human Genome.” www.genome.gov/about-genomics/fact-sheets/

Sequencing-Human-Genome-cost. Accessed  May .

 Whole Genome Sequencing (WGS) is a term used to describe sequencing that at present does not provide full coverage of the entire

genome, where repeat sections in the genome still remain a challenge to resolve. As deﬁned by the National Cancer Institute, whole genome

sequencing is a laboratory process that is used to determine nearly all of the approximately  billion nucleotides of an individual’s complete

DNA sequence, including non-coding sequence.

 Nebula Genomics. “Did You Know that most DNA Tests Decode Only .% of Your DNA?” www.nebula.org/whole-genome-sequencing-dna-

test/. Accessed  May .

 National Human Genome Research Institute. “DNA Sequencing Costs: Data.” www.genome.gov/about-genomics/fact-sheets/DNA-

Sequencing-Costs-Data. Accessed  April .

genes and gene variants that stand out differently in

people with a disease or condition of interest. These

identiﬁed genes and variants can then be studied

to identify their gene products and the biochem-

istry involved in their regulation and expression.

E. Human Genetics and

Genomics—Applications

and Impacts

The applications and impacts of genetics and ge-

nomics in human biology and medicine have grown

in parallel with advancements in gene sequencing

technologies and digital analytics platforms for de-

riving meaning within the resulting large sequence

datasets. The Human Genome Project cost approx-

imately $2.7 billion resulting in publishing of the

reference genome.

The Human Genome Project

and subsequent genomics initiatives sparked the

advancement of commercial sequencing instruments

and processes that have dramatically increased the

speed of sequencing and decreased the price of

each sequence. In March 2021, Nebula Genetics was

providing whole genome sequencing (WGS)

with

30x resolution (meaning that each position is read

30 times to enhance accuracy) for less than $300, a

nearly 10,000 fold decrease in price versus the ﬁrst

sequenced human genomes.

NHGRI tracks costs

associated with DNA sequencing performed at the

sequencing centers funded by the Institute, and the

most recent NHGRI data (August 2020) place the cost

per genome at $689.

The pace of advancement in

gene sequencing has exceeded even the much-vaunt-

ed pace of Moore’s Law in computer processors.

The current speed and price of sequencing a hu-

man’s genome has led to the sequencing of patients

increasingly becoming a clinical reality in modern

healthcare systems. Barriers are less a factor of se-

quencing cost, and instead relate more to building

the capacity needed to analyze the huge volume

of data generated, to interpret the meaning of that

genetic code for the individual patient, and counsel

the patient as to implications for their health.

A developmental tipping point has been achieved in

which the utility of genomics and wide-spread use of

sequencing is clearly advantageous for signiﬁcantly

enhancing human health outcomes. As discussed

below, and in further detail within Chapter III, the

functional application of human genetics and ge-

nomics to clinical healthcare is now a daily reality

in some medical ﬁelds (e.g., cancer diagnosis and

treatment) and is increasingly front-and-center in

neurological, psychiatric, gastrointestinal, immunolog-

ic, rheumatologic, dermatologic, pain management,

and other application areas of clinical medicine. It is

 Note: the average cost of an MRI in the U.S. is $,. Source: Vanvuren, Christina. “What Can Affect the Cost of an MRI?” New Choice Health,

Inc., www.newchoicehealth.com/mri/cost. Accessed  May .

also fundamental to advancements being made in

the diagnosis and treatment of a wide range of rare

diseases and disorders—helping to end the diagnostic

odysseys of millions of patients afﬂicted with rare

diseases that have been difﬁcult to diagnose and

sparsely served in terms of available treatments.

TEConomy has divided this study of the impacts of

human genetics and genomics into two macro classes

of impacts: economic impacts (examining the impact

of human genetics and genomics on the U.S. econo-

my) and the functional (application) impact domains

in which genetics and genomics are affecting human

health and the clinical practice of medicine.

1. Economic Impacts

The performance of research, the development and

manufacturing of commercial genomics technology

platforms, the multitude of diagnostics products

and therapeutics on the market that is derived from

genomics knowledge, and the associated healthcare

services provided generate economic activity and

support a large volume of jobs across the nation—

these are economic impacts, that positively ripple

through the U.S. economy. Other economic impacts

are associated with lives saved, lives improved, and

impacts on people who would otherwise have to be

caregivers to loved ones. It is also the case that the

application of genetics and genomics to individual

healthcare needs costs money, and there is con-

siderable complexity in assessing the comparative

costs and beneﬁts of one therapy versus another, or

whole-genome sequencing (and what it may eluci-

date) versus other diagnostic tools and technologies.

Because genetics and genomics are such a rapidly

advancing ﬁeld of application and technology in

healthcare, cost/beneﬁt equations are continually

changing. No health insurer was going to pay $3 billion

to sequence a whole genome for a patient, but $689

(less than the average cost of a single MRI)

to gener-

ate a dataset with lifelong, and increasingly expanding

utility for the patient opens up a whole new ballgame.

Genomics in the

Mainstream of Human

Biological Research

The movement of genetics and genomics from a

niche in biomedical science into the mainstream

underpinning research across most biomedical

disciplines is evident in the expansion of genetics

and genomics content across the research sphere

funded by the National Institutes of Health (NIH).

In 1990, greater than 95% of human genomics

research funding ﬂowed, in a concentrated way,

through the National Human Genome Research

Institute (NHGRI) at NIH. By 2020, the vast majority

of human genomics research funding is provided

through twenty other individual NIH institutes,

indicative of the relevance of genomics across al-

most every domain of medical science and human

life science research.

2. Functional Applications

The functional impacts of human genetics and ge-

nomics are the impacts resulting from discoveries

via the advancement of research and the clinical

applications of genomics to beneﬁt human health.

The decoding of the human genome was a signature

inﬂection point for science and has been widely

acknowledged as a towering achievement for life sci-

ences. What it sparked, however, has been an ongoing

expanding universe of advancement in genetics and

genomics and incredibly wide-ranging elucidation

of biological processes, systems, and outcomes with

genetic connectivity that is now fundamental to

advancing human health and clinical medicine.

In reviewing applications of human genetics and ge-

nomics, functional impacts are generated within eight

major domains of activities impacting human health.

These are illustrated in Figure 1, and this structure

 Tripp, Simon, and Martin Grueber. Economic Impact of the Human Genome Project. Battelle Memorial Institute, May .

forms the foundation for discussion of functional im-

pacts of human genetics and genomics contained in

Chapter III. The study also brieﬂy describes non-med-

ical applications of human genetics and genomics.

F. Purpose of the Study

This study seeks to provide an accessible reporting of

the positive impacts for the economy, society, and in-

dividual health that are derived from modern human

genetics and genomics science and the associated

commercial and clinical application of advancements.

In 2011, the authors of this report (while at Battelle

Memorial Institute) conducted a detailed impact

analysis of the Human Genome Project. The result-

ing Battelle report

highlighted the growth of an

emerging industry in the application of genomics

that was born from the scientiﬁc and technological

Figure 1: Current Functional Impact Domains (Applications)

of Human Genetics and Genomics

Minable Big Data (Discovery Science)

Predisposition to Diseases and Disorders

Medical

Diagnosing Diseases and Disorders

Rational Drug Development

Pharmacogenomics (Personalized Medicine)

Gene Editing and Gene Therapy

Human-Microbe Interaction

Environmental Genomics, Metagenomics, & OneHealth

Carrier Screening

Pre-Natal Screening

Newborn Screening

Child and Adult Testing

Single Gene (Mendelian) Diseases & Disorders

Resolving Mystery Diseases

Polygenic Diseases & Disorders

Targeting to Increase Effectiveness

Reducing Adverse Events

FUNCTIONAL

IMPACT DOMAINS

APPLICATIONS OF

HUMAN GENETICS

AND GENOMICS

Forensic Science

Evolutionary Biology and Anthropology

Paternity Testing

Non-Medical

Source: TEConomy Partners, LLC.

momentum driven by the Human Genome Project

and Celera’s work to sequence a reference human

genome. It also highlighted some of the early appli-

cations occurring through genetics and genomics

advancements in healthcare and other life science-re-

lated challenges and needs. The 2011 report played a

role in highlighting not only the important scientiﬁc

impacts of federal government investment in “big

science” and genomics in particular, but also demon-

strated the robust return on public investment that

had occurred through economic growth in genom-

ics technologies and emerging applied genomics

application domains. The report continues to be

linked on the website of NHGRI at genome.gov.

Now, 20 years after the publication of the draft se-

quence, there has been a signiﬁcant and large-scale

expansion of the human genetics and genomics

universe. Technologies for sequencing and for genome

analysis have advanced signiﬁcantly—to the extent

that whole-genome sequencing is quite affordable

(certainly in comparison to many common medical

procedures and tests) and an entire genome may be

sequenced in less than one day.

Advanced analytics

and artiﬁcial intelligence systems are now available

that can simplify deriving actionable insights from

 Ibid.

 Genomics England. “Sequencing a Genome.” www.genomicsengland.co.uk/understanding-genomics/genome-sequencing/#:~:text=One%

human%genome%can%be,pieces %C%around%%letters%long. Accessed  May .

the sequencing data. Research discoveries in hu-

man genetics and genomics have compounded,

building upon one another in a virtuous network of

expanding information, knowledge, and application.

Today, this expansion has brought human genetics

and genomics to a rather visible inﬂection point.

The speed and affordability of gene sequencing,

in combination with deep insights into genomics

and -omic sciences more broadly, together with

advancing biopharmaceutical, diagnostics, and

other medical technologies that can leverage ge-

nomic information, have now made genomics a

part of the clinical practice of medicine across many

medical specializations and medical conditions.

This study seeks to provide a generalized overview

of human genetics and genomics achievements

and scan the current status of human genetics and

genomics in answering human health questions

and advancing clinical applications. The study also

seeks to highlight the economic contribution of the

expanding genetics and genomics sector. The U.S.

has been a pioneer in genomic sciences, leveraging

both public and private sector investment to build

an advanced industry that provides economic ex-

pansion and opportunities for further growth while

at the same time advancing human health and

well-being. This report characterizes those positive

impacts using quantitative analytics in conjunction

with a qualitative description of identiﬁed func-

tional impact domains and associated beneﬁts.

It is anticipated that this report will be useful to public

policymakers and those seeking an understanding of

the public and private, and monetary and non-mon-

etary, returns to investments in science broadly,

and speciﬁc to genomics. It may also be useful for

those seeking to gain a broad introduction into the

multi-faceted ways genetics and genomics are being

used to improve human health and clinical health

outcomes—helping to illustrate the power of a rapidly

expanding biomedical ﬁeld that is poised to advance

and transform many avenues of clinical medicine. It is

also hoped that the reader will be encouraged by the

promise of genomic medicine and the evident hope it

provides for improved health outcomes for humanity.

G. Limitations of the Study

The economic analysis deployed in this study provides

a one-year, point-in-time quantiﬁcation of the nation’s

genetics and genomics sector. One of the challenges

in measuring genetics and genomics impacts in the

economy is that the U.S. industry classiﬁcation sys-

tem does not contain a NAICS

code that covers the

industry speciﬁcally. Instead, it is a partial component

of many different industry sectors. Without having

access to data through NAICS codes, establishing a

baseline measure of the genetics and genomics indus-

try in aggregate within the U.S. economy requires the

development of a custom dataset (comprising data

on individual establishments and companies engaged

in human genetics and genomics research, technol-

ogy development, and application) that effectively

builds the data from the ground-up, establishment

by establishment (rather than relying on generally

available government summary sectoral statistics).

One of the principal challenges in developing estab-

lishment-level data in genetics and genomics is that

 NAICS is an abbreviation for the North American Industrial Classiﬁcation System.

while for some enterprises or organizations genetics

and genomics comprises the preponderance of their

business or institutional work (for example, gene

sequencer manufacturers, genetic testing companies,

genetic counselors), for many active in the sector, it is

only part of their business or work (for example drug

companies, large national diagnostic laboratories,

clinical care providers, etc.). Informed estimations have

to be made of the portion of revenues, expenditures,

and employment at organizations that are related

to the application of genetics and genomics. The

fact that estimates must be used this way to build

the overall dataset that drives the direct effect in the

input-output models used is a limitation (discussed

further in Chapter II). The study has endeavored to

err on the side of being conservative in developing

portioning estimates, and thus the resulting mea-

sures of impact are likely low rather than high.

The examination of functional impacts is, in many

respects, an even greater challenge. Part of this is evi-

dent in the very large volume of academic and indus-

try life science research studies in which genetics and

genomics are a component or focus. As a fast-moving

ﬁeld, there is ongoing evolution and expansion in

the applications of genomics in human healthcare,

and it is a signiﬁcant challenge to do justice to such a

wide-ranging ﬁeld. With thousands of diseases, many

hundreds of drugs, and a broad compendium of diag-

nostics tests having genetic associations, providing full

coverage of every application of genomics in health-

care would be an extremely challenging task and out-

of-date immediately upon completion, not to mention

a rather daunting read. This is not attempted in this

study, but rather the functional impact assessment

herein works to classify human genetics and genomics

advancements by broad application domain (disease

diagnostics, pharmacogenomics, gene therapy, etc.)

and then uses speciﬁc narrative examples of genetics

and genomics in action within these domains (to-

gether with some measures indicative of scale where

readily available). As such, the functional impact

section of this report should be viewed as providing

an overview of the broad areas in which genetics

and genomics are providing beneﬁts to human

health, not a formal quantiﬁcation of these impacts.

This report is also limited in that it focuses on human

genetics and genomics only, and this certainly under-

counts the wide economic and societal beneﬁts that

accrue to advancements in genetics and genomics

more broadly. While the application of genomics to

medicine is certainly an important area of use, the

ubiquity of DNA as the basis for all life on Earth means

that genomics ﬁnds application in many more ﬁelds of

science and commerce. Both the science of genomics

and the tools and technologies of genomics ﬁnd ap-

plication in multiple additional endeavors, including:

• Veterinary medicine

• Agriculture (in applications such as

crop improvement, crop protection,

animal science, and nutrition)

• Industrial biotechnology (in applications

using microbes with engineered genomes

to produce biochemical products), and

• Environmental and ecological services (in

applications using engineered microbes

in industrial waste cleanup, wastewater

treatment, and other applications).

These additional areas of genetics and ge-

nomics application have signiﬁcant impacts

that are not addressed in this report.

This report is primarily intended to highlight the

current status of human genetics and genomics

impacts, but it does contain a chapter that brieﬂy

discusses the frontiers and potential future advance-

ments that may occur in the foreseeable future. The

discussion in that chapter is, of course, speculative,

and thus subject to the usual limitations involved

when looking towards an uncertain future.

Readers should consider the beneﬁts of genomics

from both the economic and functional perspectives,

not just one or the other. Examining the ﬁeld through

the hard lens of economics must be tempered by the

fact that much that matters in life may not be readily

broken down into dollars and cents. The alleviation

of pain and discomfort from a medical condition, the

ending of a diagnostic odyssey of a patient with a

mystery disease, or the lifelong experiences of a child

and their parent made possible through that child

being effectively treated for a rare genetic condition,

are principally humanitarian beneﬁts. The other side

of the coin is that novel genetic tests, customized

medicines, and highly specialized care can come at

a signiﬁcant cost to individuals and those who pay

for healthcare, and it is important to understand the

economic implications of emerging clinical frontiers.

In this regard, we caution that because medical

genomics is an emerging ﬁeld, there is relatively

sparse literature on the monetary impacts and costs/

beneﬁts associated with genomic medicine. It is

anticipated that genomic medicine may increase

costs in many of its early applications, but these early

applications are part of a path that will lead to overall

cost savings as medicines are targeted and used

more effectively, chronic diseases better managed

(or perhaps cured), adverse reactions to medications

curbed, and the costs of lifelong care potentially

avoided by addressing genetic components in

diseases that may be attended to through gene

therapies and effective personalized therapeutics.

Chapter II provides an assessment of the eco-

nomic impact of sectors engaged in human

genetics and genomics R&D, the provision of

genetics and genomics tools, technologies, and

services, and associated economic activity.

Chapter III provides discussion of the multifaceted

functional impacts allocable to the key application do-

mains of human genetics and genomics in healthcare.

This follows the structure shown previously in Figure 1,

and also brieﬂy touches upon some of the non-med-

ical applications of human genetics and genomics.

Chapter IV looks to the future of human ge-

netics and genomics and introduces some of

the factors that need to be addressed to in-

crease the positive impacts of the sector.

A. Measuring Human Genetics and

Genomics Economic Impacts

As described in the previous chapter, the develop-

ment of the economic (expenditure) impacts within

this study is focused on and limited to estimating

those impacts stemming from the use of genetics

and genomics for human biomedical purposes.

1. Basics of Impact Modeling

The estimation of economic impact makes use of an

input-output (I-O) model to represent the interrela-

tionships among economic actors and sectors. Within

these models, the ﬂow of commodities (or the value

they represent) between industries, consumers, and

institutions in an economy are modeled through

a matrix representation allowing for the impact of

changes in employment, expenditures, or economic

output in one sector of the economy to be projected

onto other sectors of the economy. These transac-

tions continue under the premise that every dollar

spent in the economy (the direct effect) is re-spent

on the purchase of additional inputs, goods, or ser-

vices generating additional economic activity and

impacts. I-O analysis is the generally accepted “gold

standard” in economic impact measurement and

examines the relationships among economic sectors

(e.g., institutions or industries) and ﬁnal consumers.

For the purposes of this study, the I-O analysis

models the “ripple effect” that originates from the

expenditures made for human genetics and genom-

ics research and direct company operations in the

economy, ﬂows through suppliers and vendors as

additional inputs are purchased, and through employ-

ees, faculty, staff, and related supplier workers who

spend their wages in the U.S. economy (Figure 2).

For modeling and estimating expenditure impacts,

TEConomy used a 2019 professional IMPLAN I-O

economic impact model of the U.S. Originally de-

veloped in 1976 by the U.S. Forest Service, IMPLAN

II. The Economic Impact of

Human Genetics and Genomics

Figure 2: Measuring Economic Impacts of Human Genetics and Genomics

Human Genetics &

Genomics Focused

Research Expenditures,

Services, and Corporate

Operations in the U.S.

Purchase of Secondary

Inputs & Services from U.S.

Suppliers and Vendors

Human Genetics &

Genomic Supported

Employees Spending

Disposable Income

in the U.S. Economy

Total Economic

Impacts of

Human Genetics

& Genomics

DIRECT EFFECT INDIRECT EFFECT INDUCED EFFECT

Source: TEConomy Partners, LLC.

is now the most widely used economic impact

modeling data and analysis tool in the nation.

IMPLAN models are built upon underlying federal

information including the U.S. Bureau of Economic

Analysis (BEA) national accounts data, supplement-

ed with state level employment data from the U.S.

Bureau of Labor Statistics (BLS) and other economic

data from the U.S. Bureau of the Census. Currently, the

IMPLAN model reﬂects and represents 546 sectors of

the U.S. economy. The core data and structures devel-

oped within an IMPLAN model can be used to analyze

the economic impacts of institutions, projects, or

entire industries. Employment and expenditure data

developed and estimated as part of this study provide

the direct impacts to drive the overall economic im-

pact models and estimations. Ultimately, the impact

model generates estimates of the additional indirect

 Note, the authors followed the same I-O methodology by using a prior year’s IMPLAN model to estimate the economic impacts of the Human

Genome Project.

and induced impacts (also known as the multiplier

effects) for employment, personal income, value add-

ed, output, and federal and state/local tax revenues.

2. Prior Human Genome Project

Economic Impact Results

For context both in terms of size and breadth,

values from the authors’ prior work on the

Economic Impact of the Human Genome Project

are provided in Table 2. These values reﬂect the

full breadth of genetic and genomic research and

the nascent involvement of industry as of 2010.

By comparison, the current study, to be described

and discussed in the following pages, focuses

solely on the human genetics and genomics

domain for a period one decade later, 2019.

Table 1: Impact Measures Included in the Analysis

Impact Measure Deﬁnition

Output

Also known as production, sales, or business volume, is the total value of goods

and services produced in the economy. For public/non-proﬁt entities, such as

universities, expenditures are often the truest measure of this economic activity.

Employment

The total number of jobs created; Includes the direct jobs paid for through salary

and beneﬁt expenditures and indirect/induced jobs generated through purchase

expenditures.

Labor Income

Also known as total compensation, is the total amount of income, including

salaries, wages and beneﬁts, received by employees, proprietors, and other

supplier workers in the economy;

Value Added

The difference between an industry’s total output and the cost of its intermediate

inputs; sometimes referred to as the industry’s “Contribution to GDP”.

Federal and State/Local

Government Tax

Revenues

Includes the estimated revenues to federal and state/local governments from all

sources as a result of the impacts estimated.

B. Drivers of Economic Impacts:

Methodology and Assumptions

Three types of economic inputs or “drivers” are used

to develop and estimate the impacts of human

genetics and genomics—research expenditures,

core industry employment, and extended industry

sales or employment. For this analysis, 2019 data

was captured to the extent practicable using the

ﬁscal year or calendar year. The following speciﬁes

the conservative methodology and assumptions

used in developing these economic impact drivers.

1. Research Drivers—

Investments in Research

A signiﬁcant driver of human genetics and genomics

economic impacts comes in the form of focused

research funding from federal agencies and other

non-proﬁt organizations. This section describes and

captures this funding mechanism for use in driving

the economic impact model. It captures the value

of human genetics and genomics research funded

by these organizations and ultimately performed

by universities, research institutes, federal agencies,

and other non-proﬁt research organizations.

National Institutes of Health

With the focus of this study speciﬁcally on human ge-

netics and genomics impacts, the National Institutes

 For the purposes of this study “NIH research funding” was limited to research-oriented grants or contracts (external and intramural) to U.S.

researchers. Grants to non-U.S. research performers, U.S. ﬁrms (via SBIR/STTR awards), or construction and training awards were excluded from

the analysis. For FY , this NIH total research funding reached $. billion. Note: grants to U.S. ﬁrms were excluded as individual ﬁrms

are typically captured in the core industry drivers analysis.

of Health (NIH) becomes the principal governmental

agency funding research in this domain. However,

even within NIH, the role of human genetics and

genomics in its research portfolio is subject to inter-

pretation and perspective—ranging from fundamental

research into human genetics and genomics to the

use of genetics and genomics as an enabling “tool” in

research focused on speciﬁc diseases or conditions.

To account for this, TEConomy established three

funding scenarios for NIH, each differentiated by

size and breadth of funding, developed through an

analytical approach that eliminates double count-

ing of funded research efforts and builds upon the

previous scenario. The structure of these scenarios

and the research funding that is captured within

each scenario is built using internal NIH classiﬁca-

tions and keywords.

These scenarios include:

• Core NIH Human Genetics and

Genomics Funding

• Includes all research funding from

NHGRI (524 projects, $416.3 million)

• Research reviewed and approved by spe-

ciﬁc genetic and genomic-related proposal

review study sections (e.g., Genetics of

Health and Disease Study Section and

others) (1,434 projects, $611.1 million)

Table 2. Core Metrics from Economic Impact of HGP Study

Impact Employment (Jobs) Output ($M)

Direct Effect 51,655 $22,627.5

Total Impact 310,360 $67,146.0

Source: Economic Impact of the Human Genome Project, Battelle Memorial Institute, May .

• Research classiﬁed in speciﬁc and relat-

ed NIH Research, Condition, and Disease

Categories (RCDC) EXCEPT the broadest

Genetics category (e.g., Cancer Genomics,

Gene Therapy, Gene Therapy Clinical Trials,

Genetic Testing, and Human Genome)

(5,424 projects, $2,107.3 million)

• Core + Additional Expanded NIH Funding

• Additional research within the speciﬁc

Genetics RCDC funding category, not cap-

tured above (10,493 projects, $3.884 billion)

• Core + Additional Expanded +

Additional Use as Tool Funding

• Additional research listing genetics or ge-

nomics as a Principal Investigator-provided

keyword in the funding information not cap-

tured above. A review of these awards showed

that most were non-genetics and genomics

focused yet were using genetics or genomics

as a key analytical approach or tool enabling

the research. (13,448 projects; $7.184 billion)

Table 3 shows the value and incremental additions

to each scenario and the share of total NIH research

funding.

A striking ﬁnding from this assessment of NIH

research funding is the pervasive nature of

genetics and genomics in human biomedical

research. Nearly half of all NIH research fund-

ing speciﬁes some connections with human

genetics and genomics, at least as an inves-

tigative tool to support other research.

To maintain a conservative perspective on the role

NIH research funding plays in the overall econom-

ic impact of human genetics and genomics, the

remainder of this chapter focuses on the impacts

generated with the inclusion of the smallest, core

funding scenario. Economic impact results estimated

using the additional more expansive NIH research

funding scenarios are included in the Appendix.

Other Federal Agencies

Beyond NIH, other federal agencies pro-

vide signiﬁcant human genetics and ge-

nomics-related research funding.

Department of Veterans Affairs

In FY 2019, the Department of Veterans Affairs (VA)

Ofﬁce of Research and Development invested a total

of $107.0 million in genomics research and infra-

structure. Of this, $26.0 million was towards funding

genomics research projects, $44.0 million towards the

Table 3: NIH Research Funding Captured by Each Scenario

NIH Human Genetics

and Genomics Funding

Scenario

2019 NIH Research

Investment

Component ($B)

2019 NIH Research

Scenario Value ($B)

Scenario Cumulative

Share of 2019 NIH

Research Funding

Core Funding $3.135 $3.135 10.8%

Core + Additional

Expanded Funding

$3.884 $7.018 24.2%

Core + Additional

Expanded + Additional

Use as Tool Funding

$7.184 $14.202 49.1%

Source: TEConomy analysis of NIH research awards using the RePORT website’s ExPORTER Project ﬁle for FY 

Million Veteran Program (MVP) core infrastructure

for recruitment, enrollment as well as clinical and

genomic data curation, and $37.0 million towards

genotyping and whole genome sequencing DNA

samples from the MVP. With over 830,000 Veterans

enrolled to date, MVP is one of the largest healthcare

system-based genomic cohorts in the world.

National Science Foundation

The National Science Foundation (NSF) funds substan-

tial research efforts within the broad context of genet-

ics and genomics through research programs in ge-

netic mechanisms, phylogenetic systematics, and the

large-scale Plant Genome Research Project. For the

purposes of this study, NSF awards that were active at

any time within FY 2019 were considered and exam-

ined to ﬁnd those that met the requirement of fund-

ing research primarily aimed at human genetics and

genomics understanding. Included in these awards

are signiﬁcant research funding for big data and/or

bioinformatics research that was primarily aimed at fa-

cilitating or enhancing the ability to manage and ana-

lyze human genetics and genomics data. The included

research reﬂects 212 awards funded at $19.3 million.

 For additional information on the Million Veteran Program see: www.mvp.va.gov.

 Multi-year awards that extended into FY  were weighted by the number of FY  days

as a share of the total project’s estimated duration.

Other Health and Human Services (HHS)

Undoubtedly, other HHS agencies beyond NIH in-

clude some level of human genetics and genomics

research and/or research funding. However, given

the limited detailed information upon which to

assess the connections to human genetics and

genomics, only within the National Institute for

Occupational Safety and Health (NIOSH) was this

information as well as funding information available.

For FY 2019, TEConomy identiﬁed nearly $384,000

in human genetics and genomics-related funding.

Voluntary Health Associations and

Other Non-Proﬁt Funding

An important funding stream for human genetics

and genomics research is provided by a wide variety

of voluntary health associations, patient groups,

and other non-proﬁt funders. Likely included with-

in this set of funders are many of the members of

National Organization for Rare Disorders that are

funding research efforts to understand the genet-

ic and genomic traits of these rare disorders.

The difﬁculty in including funding from these asso-

ciations and non-proﬁts is the limited information

on human genetics and genomics research within

their speciﬁc research grants and the requirement

to gather this information, if it exists, from liter-

ally hundreds of organizations across the U.S.

To reﬂect at least some level of funding from these

groups, TEConomy worked to develop a conservative

estimate. Building off of prior work, TEConomy ﬁrst

estimated a 2019 value for total research funding from

voluntary health associations.

An assumption is then

made that, at a minimum, these organizations fund

human genetics and genomics research at approxi-

mately the same “share” that NIH does. To stay most

conservative, the “core” percentage of NIH funding,

10.8% (see Table 3), is applied to the estimated FY 2019

voluntary health association total funding level of $1.56

billion to generate a human genetics and genomics

research funding estimate of $169.1 million in 2019.

The actual level of funding from these organizations

is likely to be considerably larger. Anecdotally and via

website information, it appears the cutting-edge re-

search funded by these groups is becoming more and

more engaged with genetic and genomic exploration.

Research Funding Summary

Combined, human genetics and genomics research

funding as captured from funding organizations

reaches $3.4 billion under the most conservative

estimate of NIH funding. Using the IMPLAN model

this level of research funding is estimated to directly

employ 13,800 researchers throughout the U.S.

2. Core Industry Drivers—Employment of

Core Human Genetics and Genomics Firms

The previous section captures the level of human

genetics and genomics research activity stem-

ming from federal and other sources of funding.

This section develops an employment-based

estimate of the size and scope of the core ﬁrms

operating primarily, if not exclusively, within

the human genetics and genomics domain.

 U.S. Investments in Medical and Health Research and Development  – . Research!America, Fall .

 Developing true employment values from these sources can be difﬁcult due to reasons such as outdated data, self-reported data, and the

effects of M&A activity. Conservative employment estimates were made, if required.

Following a similar approach to the authors’ prior

work analyzing the genetics and genomics industry,

a database of ﬁrms with their total employment was

developed. The database was initiated by starting with

the previous work’s 2010 database of ﬁrms, exclud-

ing those that were primarily in the plant/animal/

agricultural domain and determining whether these

ﬁrms were still in business in 2019, and correcting

for considerable mergers and acquisition activity

that has occurred within the industry over the past

decade. For the purposes of this study, ﬁrms that are

part of the important instrumentation (e.g., Illumina,

ThermoFisher) or bioinformatics subsectors are

included in this database even though their prod-

ucts and services may also be used outside of the

speciﬁc human genetics and genomics domain.

To supplement this existing ﬁrm database, lists of

ﬁrms from a variety of organizations, websites, and

market research publications were curated to gen-

erate an additional set of U.S. ﬁrms for review and

inclusion. These ﬁrms were then evaluated using

web-based research to determine their ﬁt within the

human genetics and genomics domain and whether

they were still in business. If they met these criteria, an

employment value was developed using third-party

databases such as Dun and Bradstreet and PitchBook

(a provider of angel and venture capital information)

and, at times, the ﬁrm’s website or LinkedIn pages.

The impacts are modeled as an aggregation of

IMPLAN sectors, as appropriate, to capture the extent

and variety of research and corporate activities by

using employment to drive the direct impacts of

the economic impact model. These ﬁrms and their

employment were classiﬁed into one of six human

genetics and genomics core industry subsectors

(Table 4). The employment ﬁgures reﬂect the total

employment of ﬁrms in each industry subsector.

Within this employment of more than 89,000, some

speciﬁc caveats and speciﬁcations are warranted. The

data only include small/mid-sized biopharmaceutical

focused ﬁrms’ employment—the impact of large bio-

pharmaceutical ﬁrms is captured via sales estimates

in the next section. Dun & Bradstreet and corporate

website information was used to determine whether

to include ﬁrms within the R&D/biotech ﬁrms’ catego-

ry versus small biopharma category. The core medical/

diagnostic laboratories category does not include

employment for Quest Diagnostics and Laboratory

Corporation of America (LabCorp); rather their role is

estimated in the next section. An assessment of the

list of genetic counselors available from the National

Society of Genetic Counselors was used to identify U.S.

ﬁrms. These ﬁrms were then classiﬁed into medical/

diagnostic laboratories or genetic counselor practices

as warranted as many medical/diagnostic laboratories

include genetic counselor employees. The speciﬁc

category for genetic counselor and other related

services was used to capture, as best as possible,

the employment of those ﬁrms operating without a

direct testing capability. It should be noted that the

ﬁnal economic impact assessment also included

1,752 individual counselors, including those practicing

within the VA’s Million Veteran Program, that are not

captured within the employment ﬁgures in Table 4.

Core Industry Drivers Summary

Across six industry subsectors, the economic im-

pact model is driven by direct employment within

the core industry drivers of 89,464 employees.

3. Extended Industry Drivers

Two subcomponents of the industry analysis ef-

forts required different approaches to estimating

their size and importance in driving the human

genetics and genomics economic impacts.

Pharmaceutical Manufacturing

The core industry employment analysis captured

small and/or nascent biopharmaceutical ﬁrms whose

sole focus is the development of pharmacogenetic/

genomics drugs (drugs associated with a genetic test)

and other genetic and genomic therapies. However,

larger pharmaceutical manufacturers with develop-

ment efforts ranging from small molecule chemistries

to large molecule biologics also are a signiﬁcant

component of human genetics and genomics-related

economic activities. For these ﬁrms, a different ap-

proach is used to apportion part of their operations

(sales) to the human genetics and genomics domain.

Table 4: Employment by Human Genetics and Genomics Core Industry Subsectors

Industry Subsector Est. of 2019 Employment

Core Analytical/Biomedical Instruments and Equipment Manufacturers 26,758

Core Small Biopharma Manufacturers 22,383

Core R&D/Biotech Firms 21,797

Core Medical/Diagnostic Laboratories 14,639

Core Software/IT/Bioinformatics Service Firms 3,729

Core Genetic Counselor and Other Related Services 158

Total Core Firms’ Employment 89,464

Sources: Lists of ﬁrms developed from various industry and professional websites. Employment estimates from corporate websites and Dun &

Bradstreet data. Additionally, LinkedIn information was used, at times, to update and correct some ﬁrms’ employment levels.

The original Economic Impact of the Human Genome

Project study also treated these large pharmaceutical

ﬁrms in a slightly different manner from core indus-

try employment. In the previous study, an estimate

of genetic and genomic research expenditures was

used to reﬂect these ﬁrms’ involvement in the human

genetics and genomics domain—one that was just

beginning to see the opportunities that genetics

and genomics would provide in the development of

modern medicines. In the decade since these esti-

mates were developed, the role of human genetics

and genomics in biopharmaceutical development

is still evolving. However, its use has extended its

impact on these large biopharmaceutical ﬁrms

beyond simply research and further into targeted drug

development and the labeling, use, and efﬁcacy of

existing products ultimately driving corporate sales.

Lists of the U.S.-based members of the Pharmaceutical

Research and Manufacturers Association (PhRMA)

and pharmaceuticals by sales for 2019 were exam-

ined.

Using a sales cut-off value of $1.5 billion to

represent the most active biopharmaceutical products

generates a list of 102 medicines. Of these, 26 are

currently listed in the FDA Table of Pharmacogenomic

 PhRMA. “Members.” www.phrma.org/en/About/Members. Accessed  May .

 PhRMALive and Outcomes LLC. “Top  Medicines Annual Report: Climbing Mount Humira.”

 U.S. Food & Drug Administration. “Table of Pharmacogenomic Biomarkers in Drug Labeling.”

www.fda.gov/media//download. December .

 Spitzer, Dan. Brand Name Pharmaceutical Manufacturing in the U.S. IBISWorld Industry Report a, August .

 Data obtained and calculated from corporate -K ﬁlings reﬂecting  performance.

 Curran, Jack. Diagnostic & Medical Laboratories in the U.S. IBISWorld Industry Report , November .

Biomarkers in Drug Labeling.

This subset of biomark-

er-labeled medicines account for 28% of global sales

of these 102 medicines. To generate a U.S. speciﬁc

estimate, this 28% was then applied to a market

study value of 2019 total U.S. prescription drug sales

of $177.7 billion yielding an estimated $49.5 billion in

U.S. prescription drug sales with one or more genetic

biomarkers.

This estimate is considered conservative

due to the higher usage rate of more expensive phar-

maceuticals within the U.S. Total global sales of these

26 medicines reached $96.5 billion, nearly twice the

value used to drive the U.S. economic impact estimate.

National Medical Testing Laboratories

Two medical/diagnostic laboratories, Laboratory

Corporation of America (LabCorp) and Quest

Diagnostics, together account for more than $16.5

billion in total U.S. sales and more than 90,000 U.S.

workers.

While human genetic and genomic testing

is becoming more common in U.S. healthcare, it is still

a smaller share of overall medical and diagnostic test-

ing. Using corporate websites and reporting as well

as third party market studies, TEConomy developed

estimates for these two ﬁrms’ human genetic and

genomic-related sales and employment.

Together,

these two ﬁrms are estimated to account for just un-

der 22,000 workers and more than $3.77 billion in sales

within the human genetics and genomics domain.

Extended Industry Drivers Summary

The revenue and employment size of the ﬁrms cap-

tured within the Extended Industry Drivers warrant

special and distinct attention. For both subcompo-

nents, the use of human genetics and genomics

technologies and techniques constitutes a relatively

small share of overall operations. However, due to

the sheer size of these corporate operations, these

two subcomponents directly add more than $53.3

billion and nearly 61,000 jobs to the U.S. economy.

C. Economic Impact Analysis

of Human Genetics and

Genomics in the U.S.

The combination of the three economic impact drivers

presented above—Research Drivers, Core Industry

Drivers, and Extended Industry Drivers—yields a signif-

icant direct economic presence in the U.S. economy.

Using the most conservative NIH research funding

levels and using the IMPLAN model to estimate

employment from sales (or research funding levels)

values, it is estimated that the U.S. human genetics

and genomics research and industrial domain

employs nearly 166,000 workers as a direct result

of these operations (Table 5). This number includes

human genetics researchers, medical geneticists,

and genetic counselors, as well as a large number of

workers in adjacent, corporate, or operational roles

in ﬁrms developing lab equipment and software,

performing clinical genetics and genomics testing,

or manufacturing pharmacogenomic drugs. Overall,

this combined set of drivers directly generate over

$108 billion within the U.S. economy. With this

set of direct drivers, the IMPLAN model is used to

estimate the total impacts of human genetics and

genomics domain on the U.S. economy (Table 5).

From an employment perspective, these impacts

show the U.S. human genetics and genomics do-

main supporting an additional 684,000 jobs (indirect

and induced effects) within the U.S. economy for

a total employment impact of more than 850,000

workers, reﬂecting an employment multiplier of

5.12. For every direct job in the human genetics and

genomics domain, 4.12 additional jobs are generated

throughout the U.S. economy. On average, due to

the higher technical and educational requirements,

Table 5: Economic (Expenditure) Impacts —

Core NIH Human Genetics and Genomics Funding Scenario (2019)

Impact Type Employment

Labor

Income

($B)

Value

Added

($B)

Output

($B)

State/

Local Tax

Revenues

($B)

Federal

Tax Reve-

nues ($B)

Direct Effect 165,973 $21.66 $52.59 $108.16 $2.90 $5.18

Indirect Effect 288,866 $24.81 $43.59 $87.04 $2.90 $5.38

Induced Effect 395,425 $22.40 $39.44 $70.15 $3.67 $4.95

Total Impacts 850,263 $68.88 $135.62 $265.35 $9.47 $15.51

Multiplier 5.12 3.18 2.58 2.45

Source: TEConomy analysis of Human Genetics and Genomics Input Dataset; IMPLAN  U.S. Impact Model.

the direct jobs generate more than $130,000 in

annual compensation (income and beneﬁts) per

worker while overall, the total jobs supported by the

human genetics and genomics domain still aver-

age over $81,000 in compensation per employee.

In terms of value added, or the contribution to U.S.

GDP, the human genetics and genomics domain

directly adds more than $50 billion to U.S. GDP, and

through the economic ripple effects these efforts

support, in total, nearly $136 billion of U.S. GDP.

The direct output also leads to considerable additional

economic activity in the U.S. For every $1 of output

(e.g., sales or research expenditures), $1.45 of additional

sales are generated in the U.S. economy leading to

an overall economic impact of U.S. human genetics

and genomics of more than $265 billion in 2019.

The federal tax revenues of $5.18 billion generated

by the direct operations of the human genetics and

genomics domain alone surpasses the single year fed-

eral investment in human genetics and genomics of

approximately $3.26 billion across all federal agencies.

In the simplest of terms, from a federal investment

perspective, the overall economic impacts of U.S.

human genetics and genomics generates a return

on investment (ROI) of more than 4.75 to 1.00.

Progress Over the Past Decade

At the outset of this chapter, the 2010 impact

estimates for the Human Genome Project were

provided. By comparison, this current analy-

sis shows the dramatic increase in impact over

the past decade that human genetics and

genomics has had on the U.S. economy.

Even though this current effort is focused solely on

“human” genetics and genomics, the size of the

workforce directly employed in these endeavors has

more than tripled over the decade from just under

52,000 workers in 2010 to nearly 166,000 in 2019.

Similarly, direct output has dramatically surpassed the

previous estimate as human genetics and genomics

developments are leading to actual and signiﬁcant

sales in 2019. Direct output was estimated to be $22.6

billion in 2010 compared to $108.2 billion in 2019.

The economic importance of U.S. human genet-

ics and genomics cannot be denied. The HGP

impact study found that the broader genetics

and genomics ﬁeld, for which the human do-

main is just one component, had an economic

impact of $67 billion in 2010. The growth of the

human genetics and genomics ﬁeld over the

past decade has been substantial, with this one

domain area now representing a total econom-

ic impact of more than $265 billion in 2019.

D. Healthcare Costs

for Genetic Diseases

The application of human genetics and genomics,

as discussed in the next chapter, is providing a wide

range of functional beneﬁts in healthcare in terms

of identiﬁcation of patient predisposition to genetic

disease, diagnosis of diseases, identiﬁcation of targets

for new drugs, precision drug dosing and limitation

of adverse drug events, and development of new

approaches to treatments and cures through gene

therapy and gene editing. As will be shown, human

genetics and genomics are very much at an inﬂection

point where many beneﬁts are now occurring as

research discoveries translate into clinical innovations.

Because the large-scale clinical application of

human genetics and genomics is a relatively new

phenomenon, there is relatively limited literature on

the economic impacts of its applications to clinical

care. Longitudinal studies tracking impacts over time

are particularly scarce and indeed are challenging

to interpret given that the cost of gene sequencing,

up to and including whole-genome sequencing,

has plummeted. Sequencing the genome was, just

a few years ago, prohibitively expensive. However,

advancements in technology mean that cost is

no longer a primary barrier to use in the clinic.

One way to evaluate the economic impacts of human

genetics and genomics is to examine the cost bur-

den of disease imposed on the economy by diseases

that are predominantly genetic in their etiology. The

majority of what is labelled “rare diseases and disor-

ders” falls into this category, often being single-gene

disorders. As such, the cost of these diseases can serve

as a surrogate for at least understanding the scale of

disease burden related to rare diseases, and by exten-

sion, provide intelligence on the kinds of economic

costs that may be ameliorated through advancements

in genetic and genomic diagnosis and treatments. A

recent study conducted by the Lewin Group for the

EveryLife Foundation for Rare Diseases makes an

important contribution to the literature and provides

robust evidence for the very substantial burden im-

posed by predominantly genetic rare disease.

The re-

search program, titled “The National Economic Burden

of Rare Disease Study,” uses data on medical care

costs, together with a detailed survey of rare disease

patients and caregivers, to derive estimates for the

burden of 379 rare diseases measured in terms of their

one year impact (2019). The study is conservative and

 . Yang, Grace, et al. The National Economic Burden of Rare Disease Study. Lewin Group for EveryLife Foundation for Rare Disease,  Feb. .

 Liu, Zhichao, et al. “Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic testing in Rare Diseases: Where Are We?”

Trends in Genetics, vol. , no. , Nov. .

only estimates the burden for 379 diseases for which

survey data were available (versus in excess of 7,000

rare diseases identiﬁed

)—but the results speak to the

large-scale costs of such disease to society, to patients,

and to patients’ families. The study ﬁnds the total

cost of the 379 assessed diseases to be $966 billion

for 2019. This total cost burden is shown in Table 6.

The Lewin authors do not choose to extrapolate their

ﬁndings for 379 rare diseases to the more than 7,000

such diseases that exist because they were unsure of

whether the 379 comprise a representative sample of

rare diseases extant. The measures shown in Table 6

are thus conservative. What they do provide, however,

is a window into the very large-scale cost of these (pre-

dominantly genetic) diseases—a cost that in just one

year in the U.S. imposed a burden of almost $1trillion.

The direct cost of the 379 rare disease impacts studied

by Lewin ($418 billion) can be put in context by exam-

ining total healthcare expenditure data maintained

Table 6: Economic Burden of 379 Rare Diseases in the United States (2019)

Cost Element Description 2019 Impact

Direct medical costs

Includes inpatient hospital or outpatient care,

physician visits, Rx medications, durable medical

equipment.

$418 billion

Indirect costs: productivity loss

Includes forced retirement, absenteeism,

presenteeism, and a reduction in community

participation and volunteer service.

$437 billion

Non-medical and uncovered

healthcare costs

Includes paid daily care, necessary home and vehicle

modiﬁcations, and transportation and education

costs. Also includes health care services not covered

by insurance: experimental treatments, medical

foods, and more.

$111 billion

$966 billion

Source: Lewin Group. “The National Economic Burden of Rare Disease Study.” Prepared for: EveryLife Foundation for Rare Diseases. February , .

by the Centers for Medicare and Medicaid Services

(CMS). CMS data for 2019 show total healthcare costs

for hospital, physician and other provider services,

medications, and durable medical equipment being

$2.4 trillion in 2019.

It is evident, therefore, that the

high amount of care required in diagnosing and

treating rare diseases comprises a signiﬁcant portion

of overall healthcare costs. At $418 billion (again,

just for 379 rare diseases), the direct care costs of

these diseases equate to 17.4% of total national direct

spending across equivalent expenditure categories.

Of course, many common diseases also have genetic

involvement. Cancer is fundamentally a genetic dis-

ease, whereby gene mutations cause uncontrolled cell

growth. Many more diseases, including cardiovascular

diseases, gastrointestinal diseases, autoimmune disor-

ders, psychiatric and neurological disorders, musculo-

skeletal disorders, etc., have genetic involvement, typi-

cally involving many genes (i.e., polygenic). Quantifying

the overall cost burden of these diseases, where

genetics is part of the equation, is particularly chal-

lenging. Still, just referencing cancer, the American

Cancer Society reports that “the Agency for Healthcare

 Centers for Medicare & Medicaid Services. “National Health Expenditures  Highlights.” www.cms.gov/ﬁles/document/highlights.pdf.

Accessed  May .

 American Cancer Society. “Economic Impact of Cancer.”

www.cancer.org/cancer/cancer-basics/economic-impact-of-cancer.html. Accessed  May .

Research and Quality (AHRQ) estimates that the direct

medical costs (total of all health care costs) for cancer

in the U.S. in 2015 were $80.2 billion”

—with 52% of

this cost being for hospital outpatient or doctor ofﬁce

visits, and 38% of the cost for inpatient hospital stays.

While a deﬁnitive total cannot be calculated with

available data, there should be little doubt that the

economic burden of genetic and genomic-related

diseases in the U.S. reaches into the trillions of dollars

on an annual basis. However, as examined in the

next chapter, researchers and clinicians in research

institutes, universities, industry, and government

labs are making far-reaching contributions to re-

ducing the many burdens associated with genetic

and genomic diseases and disorders—making deep

progress in the clinical application of genetics sci-

ence and technology advancements to make a very

real difference in the lives of millions of patients.

The application of genetics and genomics advance-

ments to healthcare can certainly be viewed through

an economic lens, and the economic impact of this

dynamic science and technology-driven sector is

extremely large. However, the generation of busi-

ness income and jobs is not the raison d’etre for

medical genomics. Human genetics and genomics

are pursued for the scientiﬁc and clinical insights

they enable, and for their functional impacts,

these being the domains of application of the sci-

ence and technologies of genetics and genomics

to preserving and improving human health.

Genomics has become fundamental to advancement

of biomedical research, and the insights, tools, and

technologies provided by genetics and genomics are

now seeing increasingly widespread deployment in

clinical healthcare. This chapter seeks to provide a

broad overview of the key areas (domains) in which

human genetics and genomics are being applied

in clinical research and healthcare. The functional

impacts are divided into eight medical domains

(Figure 3): minable big data, whereby large data sets

of multi-patient data are providing deep insights

into disease biology (and also identifying charac-

teristics associated with health); identiﬁcation of

genetic predisposition to diseases and disorders;

diagnosis of diseases and disorders though genetic

signatures; rational drug development, whereby

genetics information informs molecular targeting

in drug design; pharmacogenomics, which enables

the personalized prescription of drugs best suited

to the person’s genetics (with a goal of increasing

effectiveness and reducing adverse events); gene

editing and gene therapy, whereby genes associ-

ated with disease are modiﬁed to treat or cure the

disease; and two more “emerging” areas in which

human-microbe genetic interactions and hu-

man-environmental metagenome interactions are

being examined for association with human gene

expression, regulation, mutation, and disease.

In addition to applications to human medicine,

there are also several additional human applica-

tion domains relevant for non-medical uses. These

are brieﬂy discussed herein, covering applications

in forensic science, anthropology and genealogy,

evolutionary biology, and paternity testing.

III. The Functional Impacts of

Human Genetics and Genomics

A. The Structure of Functional Impacts

(Application Domains of Human Genomics)

B. Fundamental Knowledge

Advancement

Before discussing the clinical impact domains

of human genetics and genomics, it is import-

ant to note that applied and clinical research

depends upon a healthy base of discoveries and

fundamental insights that are derived through

basic research, which may be deﬁned as:

Systematic study directed toward greater

knowledge or understanding of the

fundamental aspects of phenomena and of

observable facts without speciﬁc applications

towards processes or products in mind.

 Cornell Law School. “ CFR § . - Deﬁnition of Basic Research.” www.law.cornell.edu/cfr/text//.. Accessed  May .

Genetics can inform us of our past evolution, and

genetics and genomics as disciplines have themselves

been evolving. Fundamental scientiﬁc research,

facilitated by advancements in genomics technolo-

gies and analytics, has provided a stream of notable

discoveries, with just some highlighted below:

• The ENCODE project (ENCyclopedia of DNA

Elements) revealed that noncoding DNA, previ-

ously termed “junk DNA” because it was thought

to be a relic of evolution with little biological

function, instead has speciﬁc functionality in

transcription and translational regulation of

protein-coding. In other words, most of it is not

Figure 3: Functional Biomedical Impact Domains

(Applications) of Human Genetics and Genomics

Minable Big Data

(Discovery Science)

Identifying Predisposition

to Diseases and Disorders

Diagnosing Diseases

and Disorders

Rational Drug

Development

Pharmacogenomics

(Personalized Medicine)

Gene Editing

and Gene Therapy

Human-Microbe

Interaction

Environmental Genomics

and Metagenomics

Analyzing sequencing

data from large and

diverse populations to

provide deep insights

into disease biology and

identify characteristics

associated with health.

Genetic and genomic

testing to identify

carrier status, and

identify predisposition

for genetic disease via

prenatal, newborn and

adult screening.

Using biomarkers

and gene signatures

to diagnose the

presence of diseases

or disorders that are

associated with

speciﬁc genes or

gene products.

Using genetic

information and gene

associated biomarkers

to inform molecular

targeting in drug design.

Using sequencing data

to enable the

prescription of drugs

best suited to the

patient’s genotype

(increasing efﬁcacy and

reducing adverse events)

Modifying the genes

associated with a

disease or disorder

to treat or cure the

disease

Biomedical

Application

Domains of

Human

Genetics

and

Genomics

Examining the human

genome’s impact

upon hosted microbial

populations, and

microbe impacts upon

the human genome

and gene expression

Examining the impact

of human interactions

with the environment

on the human genome,

gene regulation, muta-

tion, and disease

etiology.

Biomedical

Application

Domains of

Human Genetics

and Genomics

Source: TEConomy Partners, LLC.

junk at all; it is central to life functions (although

not fully understood in terms of functionality).

• Basic research into gene silencing led to funda-

mental discoveries regarding RNA, messenger

RNA (mRNA), and development of techniques

for RNA interference that enabled human

genes to be disabled in a very precise man-

ner to better study their effect and function.

Further research has elucidated the presence

of multiple types of non-coding RNAs and

their impacts on gene expression, one class

of which, microRNAs (mnRNAs), may be reg-

ulating more than half of all human genes.

• Ongoing reﬁnement to the reference human

genome has occurred, closing many of the gaps

in the original sequences and uncovering previ-

ously uncharacterized parts of the human ge-

nome with potential for signiﬁcant discoveries.

• Recent studies have been elucidating “mo-

saicism”, which is the term used to describe

genomic variation among cells (both germline

and somatic) within an individual. Much still

 Miga, Karen H. “Human Genome: Bridging the Gaps.” Nature, vol. , no. , Feb. .

 Green, Eric D., et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature, vol. ,  Oct. .

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The New

England Journal of Medicine, vol., no. ,  Jan. .

 Pharmaphorum Connect. “The Future of Genomic Medicine: Can it Fulﬁl its Promises?” www.pharmaphorum.com/views-analysis-patients/the-

future-of-genomic-medicine-can-it-fulﬁl-its-promises/. Accessed  May .

remains to be studied in this area to better

understand “mosaic variation in both nuclear

and mitochondrial DNA, the mechanisms that

generate mosaicism, and the roles of mosa-

icism in physiology and human disease.”

• Recent work is focused on “studying patterns of

gene expression in individual cells, a step that

has been driven by new methods for single-cell

RNA sequencing and chromatin analysis. Tens

of millions of cells have been characterized

thus far on route to a complete cell Atlas of the

human body. This effort is revealing hundreds

of new cell types and characterizing the ways

in which cell types differ between healthy

people and people with various diseases.”

• Basic research has found that “not all genes

are expressed in all tissues and that not all

genes are expressed during all developmen-

tal stages.”

This has important downstream

implications in drug development, where, for

example, a research team developing a drug

for infantile epilepsy would need to know

The importance of basic science derives from its contribution to knowledge deeper within the tree

of information and, consequently, its greater potential for integration with other facts. In contrast,

the importance of translational science lies in its practicality. Hence, we do not view basic and

translational science as one being more important than the other but rather as complementary

areas of human endeavor, with the important distinction that basic science ﬁndings often precede

advances in translational science. We also note that observations in translational or applied science

can generate new questions for fundamental research, as illustrated from the fact that vaccination

preceded the ﬁeld of immunology. Hence, the epistemological ﬂow is bidirectional, and investments

in both types of science are needed.”

Ferric C. Fang and Arturo Casadevall. “Lost in Translation—Basic Science in the Era of Translational

Research.” Infection and Immunity, vol. 78, no. 2, Feb. 2010.

whether a drug target is “expressed in the

brain and also during early development.”

It should also be noted that the Human Genome

Project, and the ongoing development of genomic

tools and datasets, generated a rather seismic shift

in the way in which fundamental research is per-

formed. The big data, information mining approach

that gene sequencing enables has “transformed

the nature of medical discovery, enabling scien-

tists to undertake comprehensive and powerful

explorations rather than being conﬁned to testing

hypothesis focused on candidate pathways.”

What is clear is that the human genome is immensely

complex, and there is much still to be discovered

through fundamental research into its structure,

mechanisms of action, and its interface with biochem-

ical signals from non-genomic origin. In some diseas-

es, hundreds of individual genes are being found to

have an effect on disease development and progres-

sion, often in concert with multiple environmental

and physiological factors. Solving such multigenic

and multifactorial challenges is no small task, but

distinct progress is being made, aided by tremendous

technological advancements in sequencing and data

analytics platforms. Any scientist, or group of scien-

tists, embarking on ﬁnding solutions to individual

human diseases will typically recognize that the path

from question to discovery to therapy or cure is long

(sometimes spanning their career, if successful at all).

Modern genetics and genomics are, however, provid-

ing new, more brightly lit paths informed by quantita-

tive datasets that can be mined for insights and ther-

apeutic targets. As noted in NHGRI’s strategic vision:

…the past decade has brought the initial

realization of genomic medicine, as

research successes have been converted

into powerful tools for use in health care,

including somatic genome analysis for

 Ibid.

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The New

England Journal of Medicine, vol., no. ,  Jan. .

 Green, Eric D., et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature, vol. ,  Oct. .

 Ibid.

cancer (enabling development of targeted

therapeutic agents), noninvasive prenatal

genetic screening, and genomics-based

tests for a growing set of pediatric conditions

and rare disorders, among others.

For some diseases, especially those where a sin-

gle or only a few genes are involved, real break-

throughs are occurring. The section that follows

describes the domains of health sciences and

clinical care where these impacts are being felt.

C. Functional Applications

for Human Health

As fundamental genomic knowledge has expanded,

the enhanced understanding of genetic mecha-

nisms, in concert with access to rich whole exome

and genome datasets (and associated reference

compendia of human gene variants), has opened

the door to a new era of discovery and progress

in medicine. The impacts of these advancements

are now increasingly reverberating across medi-

cine, a fact highlighted by Eric Green, the Director

of the NHGRI, and colleagues who note that:

With insights about the structure and function

of the human genome, and ever improving

laboratory and computational technologies,

genomics has become increasingly woven

into the fabric of biomedical research, medical

practice, and society. The scope, scale, and

pace of genomic advances so far were nearly

unimaginable when the human genome

project began. Even today, such advances are

yielding scientiﬁc and clinical opportunities

beyond their initial expectations, with many

more anticipated in the next decade.

Much of the advancement being seen is enabled by

dramatic progress in genome sequencing technology

performance and cost effectiveness. A virtuous cycle

has occurred, whereby the speed increases and cost

decreases in sequencing have facilitated the assembly

of exabytes

of genomic information that can be

mined (assisted by highly advanced and automated

analytical systems) for unique insights into genome

structure and function.

As highlighted by Green:

Leading the signature advances has been

a greater than one million-fold reduction in

the cost of DNA sequencing. This decrease

has allowed the generation of innumerable

genome sequences, including hundreds of

thousands of human genome sequences (both

in research and clinical settings), and the

continuous development of assays to identify

and characterize functional genomic elements.

These new tools, together with increasingly

sophisticated statistical and computational

methods, have enabled researchers to create

rich catalogs of human genomic variants,

to gain an ever deepening understanding

of the functional complexities of the human

genome, and to determine the genomic

bases of thousands of human diseases.

This leads us to the ﬁrst functional impact domain of

genetics and genomics in human medicine, minable

big data, and what it enables, discovery science.

1. Minable Big Data (Discovery Science)

Laurence Hurst highlights the central role

that data are playing in advancing function-

al applications of genomics, noting that:

Genomics is in an age of exploration and

discovery. Whether we are discovering the

genomes of more species, the genomes

of more individuals in a species, or more

genomes within an individual (at single-cell

 An exabyte =  bytes (,,,,,, bytes).

 Stephens, Zachary D., et al. “Big Data: Astronomical or Genomical?” PLOS Biology, vol. ,  July . doi:./journal.pbio..

 Green, Eric D., et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature, vol. ,  Oct. .

 Cheifet, Barbara. “Editorial: Where is genomics going next?” Genome Biology, vol. , no. ,  Jan. . doi:./s---.

 Zielinski, Dina and Janiv Erlich. “Genetic Privacy in the Post-Covid Word.” Science, vol. , no. ,  Feb. .

 Birney, Ewan. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. , no. , March-

April .

 National Human Genome Research Institute. “Genetics vs. Genomics Fact Sheet.” www.genome.gov/about-genomics/fact-sheets/Genetics-vs-

Genomics#:~:text=All%human% beings%are%.,about%the%causes%of%diseases. Accessed  May .

resolution), we are very much in a phase

where we are letting the data lead.

Studying one person’s genome (or in the case of the

“reference” human genome, a composite of a few peo-

ple) has provided valuable information regarding the

structure of the human genome and the number of

protein-coding genes. It has also allowed for compar-

ison to an expanding library of reference genomes for

other organisms, helping to identify regions of similar-

ity and difference that could help illuminate function-

ality. At a time when whole-genome sequencing cost

many millions of dollars per genome, the ﬁeld was

limited to small volumes of sequenced genomes to

work with. As sequencing costs declined and sequenc-

ing speed increased, the ability to generate data from

a large number of individuals started to become real-

istic, and this has opened new horizons for research.

Currently, whole genome sequencing and whole

exome (the part of the genome formed from exons

that code proteins) sequencing is fast and affordable

(requiring just a day and $689 for whole genome

sequencing), and as affordability and speed have

increased, the number of sequenced individuals

has expanded exponentially. In a recent edition of

Science, it is noted that “today, more than 30 million

individuals have access to their detailed genomic

datasets,”

while Ewan Birney of the European

Bioinformatics Institute notes that “estimates show

that over 60 million patients will have their genome

sequenced in a healthcare context by 2025.”

Having access to an extremely large volume of se-

quenced individuals creates a dramatically enlarged

platform for discovery. Each of us has a unique

genome. While 99.9% of the genome between

individuals will be the same,

the 0.1% differenc-

es can add up to profoundly dissimilar physical

characteristics and differential predisposition to

disease, rates of metabolizing drugs, and other

factors. Identifying and understanding these differ-

ences becomes more feasible the more sequences

and data are available. The devil is in the details,

and more sequences provide more details.

Large-scale sequencing implementation is enabling

the ongoing assembly of robust, evidence-based

resources for the identiﬁcation and classiﬁcation of

genomic variant pathogenicity (variants associated

with causation of disease). To-date, the vast majority

of larger-scale whole genome sequences have been

produced in Western nations, with the result that

the available data skew quite signiﬁcantly in terms

of individuals of European ancestry. This bias in the

data is being addressed through multiple initiatives

worldwide that will contribute greatly to a broader

base of represented humanity. Recent research by

Table 7: Large Population Precision Medicine Initiatives

Country Project/program name Expected size

Common

diseases

Rare diseases

(and cancers)

Australia Genomics Health Futures Mission 200,000



Canada

Canadian Genomics Partnership

for Rare Diseases and Canadian

Longitudinal Study on Aging

Nationwide

 

China Precision Medicine Initiative

100,000–

100 million

 

Denmark Danish National Genome Center 60,000

 

Dubai Dubai Genomics Nationwide



Estonia Personalised Medicine Programme 150,000



European Union 1+ Million Genomes Initiative 1,000,000+



Finland FinnGen 500,000



France Genomic Medicine France 2025

235,000

each year

 

Hong Kong Hong Kong Genome Project 50,000



Italy SardiNIA Project 60,000



Japan GEnome Medical alliance Japan Nationwide

 

Saudi Arabia Saudi Human Genome Program 100,000

 

Singapore (And

International)

Genome Asia 100 K 100,000



Thailand Genomics Thailand 50,000

 

Turkey Turkish Genome Project

100,000–

1,000,000

 

United Kingdom 100,000 Genomes Project 100,000



United Kingdom Accelerating Detection of Disease 5,000,000



United States NHGRI Genomic-Medicine Nationwide

 

United States All of Us Research Program 1,000,000+



Source: Identiﬁed in Chung, B.H.Y., Chau, J.F.T. & Wong, G.KS. “Rare versus common diseases: a false dichotomy in precision medicine.” npj Genom.

Med. ,  ().

Brian Hon Yin Chung, Jeffrey Fong Ting Chau, and

Gane Ka-Shu Wong summarizes many of the larg-

er (>20,000 subject genomes) precision medicine

projects (for which sequencing is primarily a major

element), showing how in forthcoming years, the

richness of sequenced populations will be enhanced

signiﬁcantly.

The global distribution of these studies

(Table 7) holds promise for the development of reliable

genomic data on many different populations and

sub-populations, helping to build a more inclusive

atlas of genome variability across the human species.

The expanding diversity in the base of human

genome sequence data is further highlighted by

Rotimi, Callier, and Bentley who recently note that:

Growing prioritization of diverse populations

in genomics research has begun to respond

to these gaps. Programs, such as TOPMed,

All of Us, International Common Disease

Alliance, Human Heredity and Health in

Africa (H3Africa), Million Veteran Program,

GenomeAsia, and the COVID global consortium,

contribute to advances in diversity and

inclusion among research participants.

In the U.S., several large-scale sequencing initiatives

are ongoing. Among the largest is the NIH’s “All of Us”

program, which began in 2018 and is consolidating

 Chung, B.H.Y., et al. “Rare versus Common Diseases: a False Dichotomy in Precision Medicine.” npj Genomic Medicine, vol. , no. ,  Feb.

. doi.org/./s---x.

 Rotimi, Charles N., et al. “Lack of Diversity Hinders the Promise of Genome Science.” Science, vol. , no. ,  Feb. .

genetic, health, and environmental data for more than

one-million participants, providing a robust resource

for evaluating genotype-to-phenotype associations.

Another federally initiated program is the “Million Vets

Program” (MVP) that, similar to the NIH program, is

collecting deep data to allow the study of links be-

tween genes, lifestyle, and military exposures and their

associated impacts on health and illness. Since launch-

ing in 2011, over 825,000 veterans have signed up to

participate. The VA notes that “in addition to common

health conditions that affect everyone, such as cancer,

cardiovascular disease, and diabetes, MVP researchers

are also looking at conditions speciﬁc to Veterans. This

Increasing Sequenced

Population Diversity to Enhance

Studies of Genetic Variation.

Up until relatively recently the participants in-

volved in genomic research have largely been of

European ancestry.

Multiple initiatives are now underway to substan-

tially increase diversity in genomic datasets. For

example, the Human Heredity and Health in Africa

(H3Africa) initiative has enrolled more than 60,000

research participants and engaged more than 500

African scientists.

Research in genome biology is often descriptive in nature, sequencing genomes and metagenomes,

proﬁling epigenomes and transcriptomes, charting evolutionary history, and cataloging disease

linked risk loci. Thanks to major technological advances, we can now generate such descriptive

datasets using high throughput platforms.”

Christoph Bock, CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, quoted in Barbara

Cheifet. “Editorial: Where is Genomics Going Next?” Genome Biology, vol. 20, no. 17, 22 Jan. 2019.

includes PTSD [post-traumatic stress disorder], suicide

prevention, TBI [traumatic brain injury], and tinnitus.”

While advances in the technologies for gene se-

quencing are at the forefront in generating large

and deep datasets from diverse populations, equally

important, have been advancements in advanced

data analytics comprising the use of analytical

computer algorithms and statistical techniques

acting upon large-scale sets of structured and

unstructured data to derive actionable insight

(see sidebar deﬁnition for advanced analytics).

Genetic and genomic data, health record data, and

environmental data each provide important insights

on their own but promise far greater intelligence when

examined together. This presents the challenge of

analyzing extremely large-scale heterogenous data

compiled from multiple sources. Fortunately, as these

big data resources have been built, there has been

parallel advancement in the science and technology of

advanced data analytics, up to and including artiﬁcial

intelligence (AI) based systems. Advanced analytics

provides a pathway forward in terms of mining big

genome and genome-phenome datasets to provide

functional insights and impacts in broad areas such as:

biomarker discovery and identiﬁcation of druggable

 VA Million Veteran Program. “About the Million Veteran Program.” www.mvp.va.gov/webapp/mvp-web-participant/#/public/about. Accessed 

May .

 Liu, Zhichao, et al. “Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic testing in Rare Diseases: Where Are We?”

Trends in Genetics, vol. , no. , Nov. .

 Tripp, Simon, et al. Artiﬁcial Intelligence and Advanced Analytics in Indiana: An Initial Discussion of Industry Needs and University

Capabilities. TEConomy Partners, LLC for BioCrossroads, Jan. .

targets; multi-gene to disease associations; environ-

mental effects on gene regulation and expression;

gene expression effects of prior infectious diseases,

etc. The combination of genomics and phenomics

big data and advanced analytics provides a powerful

pathway forward for modern life science discovery

and healthcare improvement. This is highlighted

by Liu, Zhu, Roberts, and Tong who note that: “AI

is starting to realize its potential in augmenting

phenome-wide and genome-wide data proﬁles to

improve clinical utility and diagnostic power.”

Evidence for this technological convergence of bio-

medical big data and AI is seen in evident clusters

of new business ventures forming to pursue com-

mercialization of associated opportunities. Research

by TEConomy recently used machine learning to

identify clusters of U.S. activity focused on advanced

analytics applications.

Figure 4 illustrates three

distinct clusters of venture capital funded enter-

prises forming in this space, comprising: 1) drug

discovery and precision medicine, 2) healthcare

analytics, and 3) wearable health monitoring de-

vice analytics. The growth and interaction of these

clusters builds upon the promise of big data ana-

lytics using genome and phenome information to

derive clinical health insights and improvements.

Advanced Analytics is the autonomous or semi-autonomous examination of data or content using

sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI),

to discover deeper insights, make predictions, or generate recommendations. Advanced analytic

techniques include those such as data/text mining, machine learning, pattern matching, forecasting,

visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate

statistics, graph analysis, simulation, complex event processing, neural networks.”

Gartner. “Gartner Glossary.” www.gartner.com/en/information-technology/glossary/advanced-analytics.

Accessed 12 May 2021.

Figure 4: Biomedical-Related Clusters Identiﬁed in the Innovation Landscape Net-

work of U.S. AI Companies Receiving Signiﬁcant VC Investment, 2014-2018

Source: TEConomy Partners, LLC

New genetic and genomic analytical tools are also

in development and coming online, which promise

additional high-throughput analytical capabilities

and assessment. It is anticipated that new analytical

techniques such as CRISPR single cell sequencing

and single-cell RNA-seq (scRNAseq) will generate data

that provides new insights into biological function.

Case Study: Example of Minable Big Data (Discovery Science)

Geisinger is an integrated healthcare system headquartered in Pennsylvania integrating “primary care

and specialists, hospitals and trauma centers, insurance, medical education and research.”

Geising-

er has been at the forefront in terms of recognizing the clinical insights and utility that genomic data

and health record data that are mined together provide. Begun in 2007, Geisinger’s MyCode Commu-

nity Health Initiative has seen over 250,000 patients consent to participate in a research program that

has been performed in collaboration with Regeneron’s genetics research center. More than 100,000

whole exomes had been sequenced (as of reporting in April 2019). Motivated by the MyCode experience,

Geisinger launched a “clinical whole-exome population screening program in mid-2018 as part of rou-

tine clinical care in a variety of Geisinger clinics, developing an end to end implementation platform—

from patient engagement and consenting, to whole exome sequencing in a certiﬁed clinical laboratory,

to physician education, to genetic counseling at scale, and to integration of clinical results into the

electronic health record.”

The main focus of MyCode is ﬁnding and conﬁrming new disease-causing

variants (changes) in patient genes, with research programs directed at:

• Searching for changes in genes that protect against disease.

• Targeting new drug development.

• Researching and learning what are the best ways to share medically-actionable genetic results with

patient-participants, and then how to facilitate the sharing of that information with other potential-

ly affected family members.

• Translating the results into clinical care.

The CEO of Geisinger, Jaewon Ryu, notes that:

About 90 percent of the patients we ask let us look at their entire genomes. That’s huge trust; a typ-

ical rate is 15 percent. Our patients come from an unusually stable population—giving us volumes

of data from more than 15 years of electronic health records. MyCode therefore provides unprece-

dented opportunity for early diagnosis and developing new and tailored treatments, or precision

medicine. MyCode is already letting us help participants and their families prevent or mitigate the

impacts of some identiﬁed genetic risk factors, including cancer and heart disease.

Some of the results emanating from MyCode in terms of advancements in breast cancer genetics

have been called out as among the most signiﬁcant applications of medical genetics in the “Genomic

Medicine Year in Review.” BRCA1 and BRCA2 are genes associated with hereditary breast/ovarian cancer

syndrome. They have a high degree of sequence variation, but the population prevalence of “pathogen-

ic” and “more likely pathogenic” variance (P/LP) has not been known. The research team used 50,000+

whole exome sequences from MyCode to examine the frequency of P/LP variants, ﬁnding a frequency

signiﬁcantly higher than other estimates. Importantly, it was found that “almost half of all variant car-

riers did not meet current criteria for clinical testing, and of those meeting testing criteria, nearly half

had not undergone clinical testing. Thus, 3/4 of at-risk women were not identiﬁed as such and are not

beneﬁting from evidence based interventions; this is a signiﬁcant care gap with implications for popu-

lation health.”

This represents a prime example of how the assembly and analysis of big data enables

robust functional impacts to be generated in clinical care.

 Geisinger. “About Geisinger.” www.geisinger.org/about-geisinger. Accessed  May .

 Willard, Huntington. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine,

vol. , no. , March-April .

 Geisinger. “About Geisinger.” www.geisinger.org/about-geisinger. Accessed  May .

 Manolio, Teri A., et al. “Genomic Medicine Year in Review: .” The American Journal of Human Genetics, vol. .  December

. Reporting on ﬁndings from Manickam, K. et al. “What We’re Missing: Most BRCA and BRCA Variant Carriers are

Undetected.” JAMA Network Open.

2. Identifying Predisposition

to Diseases and Disorders

One of the primary research and clinical applica-

tions of human genetics and genomics is its use in

identifying potential predisposition to developing

diseases and health disorders. The BRCA gene ex-

ample from Geisinger is an example of this, where

the identiﬁcation of these genes in the patient

identiﬁes risk for breast cancer and guides clinical

decision making. The library of gene-disease as-

sociations has expanded rapidly, and as Figure 7

illustrates, there are genes within every human

chromosome associated with disease. Notably, all

but three of the diseases or disorders listed in Figure

5 now have a genetic test associated with them.

Figure 5: The human chromosome set, indicating examples of locations for patho-

genic gene variants causing hereditary diseases

Note: Conditions that can be diagnosed using DNA analysis are indicated by a red dot.

Source: By   - Own work, CC, https://commons.wikimedia.org/w/index.php?curid=

Figure 5 illustrates only a small sampling of the

diseases and health disorders that have genetic

associations. The number identiﬁed is growing, and

at the time of writing 4,395 genes are noted by the

Online Mendelian Inheritance in Man (OMIM) project

as being identiﬁed with a disease or disorder-causing

mutation (phenotype-causing mutation), and 6,828

diseases or disorders have a known genetic basis.

One of the key applications of this knowl-

edge, and an extremely valuable one, is the

development of genetic testing for predis-

position to disease. Genetic testing is:

The use of a laboratory test to look for genetic

variations associated with a disease. The

results of a genetic test can be used to conﬁrm

or rule out a suspected genetic disease or to

determine the likelihood of a person passing on

a mutation to their offspring. Genetic testing

may be performed prenatally or after birth.

The above deﬁnition from NHGRI implies two principal

uses for genetic tests: 1) diagnosis of present disease

(which was discuss previously), and 2) identiﬁcation

of the presence of a gene variant that may predispose

an individual or their offspring to the development

of a disease associated with that gene. This latter

use of genetic testing is becoming increasingly

deployed as more gene-disease associations are

established. Genetic testing for predisposition to

diseases or health disorders may be divided into

three categories: 1) carrier screening, which tests a

prospective parent for the presence of gene variants

that have been shown to be associated with risk of

passing down a hereditary disorder (thereby helping

to inform family planning and associated decisions);

2) pre-natal and post-natal testing, which focuses

on testing for genetic predisposition to disease in

the fetus or in newborns; and, 3) child and adult

testing. Each application is introduced below.

 OMIM®, Online Mendelian Inheritance in Man®. OMIM is a comprehensive, authoritative compendium of human genes and genetic

phenotypes that is freely available and updated daily. OMIM is authored and edited at the Johns Hopkins University School of Medicine. For

more information see: www.omim.org/statistics/geneMap.

 National Human Genome Research Institute. “Genetic Testing.” www.genome.gov/genetics-glossary/Genetic-Testing. Accessed  May .

 National Human Genome Research Institute. “Carrier Screening.” www.genome.gov/genetics-glossary/Carrier-Screening. Accessed  May

.

a. Carrier Screening

As noted by NHGRI:

Carrier screening is a type of genetic testing

performed on people who display no

symptoms for a genetic disorder but may

be at risk for passing it on to their children.

A carrier for a genetic disorder has inherited

one normal and one abnormal allele for a

gene associated with the disorder. A child

must inherit two abnormal alleles in order

for symptoms to appear. Prospective parents

with a family history of a genetic disorder

are candidates for carrier screening.

Carrier screening has generated signiﬁcant impacts

on decision making for potential parents. This particu-

larly comes into play when two individuals each carry

a single copy of a disease allele that, while harmless to

them, has a serious risk of manifesting into a serious

genetic disease in their offspring. Carrier screening

can be used by individuals, in advance of marriage or

long-term partnering, to assess genetic risks, and by

couples contemplating starting a family. The appli-

cation of carrier screening in some communities and

populations has had profound effects, limiting, for

example, the birth of children with devastating, often

fatal, diseases such as Tay-Sachs disease and highly

debilitating disorders such as Sickle Cell Anemia and

Beta-thalassemia. The rise of low cost, high accuracy

whole genome sequencing is greatly expanding the

potential to perform DNA-based carrier screening

across a broad range of autosomal recessive, sin-

gle-gene disorders. Carrier screening may also be used

by at-risk couples pursuing in vitro fertilization (IVF),

allowing their clinician to test for potential genetic

abnormalities before implantation of fertilized eggs

(this is termed “preimplantation genetic diagnosis”)

or to select embryos with normal chromosomes for

implantation (“preimplantation genetic screening”).

b. Pre-natal and Post-natal Testing

Not every potential parent is in a position to access

carrier screening and, of course, a great many preg-

nancies are unplanned. As a result, many (indeed

most) pregnancies occur without prior carrier screen-

ing. Once a pregnancy is underway, pre-natal screen-

ing provides the ability for clinicians to evaluate the

healthy development of the baby (through established

diagnostics such as ultrasounds and maternal blood

tests) and can also include genetic tests to screen for

whether the baby may be born with certain genetic

conditions and chromosomal disorders (such as

Down’s syndrome). Such genetic testing has tradition-

ally been reserved for mothers with a certain risk pro-

ﬁle (such as family history of genetic disease, mothers

who are older, or persons who know they carry certain

monogenic alleles that confer risk). Such genetic

prenatal testing has required invasive procedures,

such as amniocentesis, that carry a measure of risk

to the pregnancy. Increasingly, however, physicians

are able to order non-invasive prenatal screening (or

“cell-free DNA screening”) that uses cell-free placental

 A “trisomy” is a condition in which an extra copy of a chromosome is present in the cell nuclei, causing developmental abnormalities.

 Dondorp, Wybo, et.al. “Non-invasive Prenatal Testing for Aneuploidy and Beyond: Challenges of Responsible Innovation in Prenatal Screening.”

European Journal of Human Genetics, vol. , no. ,  Mar. .

DNA fragments in maternal blood to screen for fetal

genetic conditions, such as the common trisomies

(e.g., Down syndrome) and deletion or duplication

syndromes. A non-invasive prenatal screening (NIPS)

is more accurate, with fewer false positives for the

most common trisomies, than other screening

tests—leading to fewer invasive procedures.

NIPS can now test for:

• Trisomy 21 (Down’s syndrome)

• Trisomy 18 (Edwards syndrome)

• Trisomy 13 (Patau syndrome)

• XXY chromosome (Klinefelter syndrome)

• XO chromosome (Turner syndrome)

• Microdeletions in chromosomes

• Rh factor (positive or negative determination)

• Multiple other less common triso-

mies and single-gene disorders.

At the present time, these NIPS tests are not con-

sidered fully diagnostic, and follow-up testing is

recommended using other procedures if a posi-

tive result is achieved through NIPS. Ultimately,

pre-natal diagnostics can help mothers make

informed decisions regarding their pregnancy

and discuss options for care with their health-

care provider, help families prepare for a poten-

tial challenge to their baby’s health, and help

ensure that clinicians are ready to support any

special health needs of the resulting newborn.

Finally, post-natal testing is a suite of genetic and ge-

nomic tests that are employed to evaluate newborn

health and diagnose present or emerging health is-

sues. As noted by Holm, “the greatest opportunity for

lifelong impact of genomic sequencing is during the

newborn period.”

Having a whole-genome sequence,

or at least a whole-exome sequence, completed as

soon as possible after birth provides a broad spectrum

of genetic information for signiﬁcant immediate use

and expanding clinical utility across the lifespan. As

noted above, 6,828 diseases or disorders currently have

a known genetic basis, and a whole-genome se-

quence provides an increasingly accessible pathway to

evaluating common or rare genetic mutations associ-

ated with immediate health challenges or the devel-

opment or emergent health issues over a life span.

The most immediate beneﬁt of newborn screening is

as a contributor to achieving a diagnosis of a genetic

disease or disorder in the newborn—the advantages

of which are discussed in the diagnosis section.

 Holm, Ingrid A., et al. “The BabySeq Project: Implementing Genomic Sequencing in Newborns.” BMC Pediatrics, vol. , no. ,  July .

doi:./s---.

Newborn genetic screening represents a

highly visible and successful approach to

identiﬁcation of inherited health conditions.

c. Child and Adult Testing

The clinical reality of whole genome, or whole exome,

sequencing is a relatively new phenomenon. Thus,

the vast majority of the present U.S. population did

not beneﬁt from access to this valuable screening

and diagnostic tool at birth. Having sequencing

performed at any stage in life will, however, still

have potentially signiﬁcant clinical utility, with utility

obviously maximized the earlier in life the sequencing

is performed. With the expanding library of identiﬁed

gene-disease linkages and the assurance that this

library will continue to grow as more research ﬁndings

accumulate, it is only a matter of time before full

sequencing of everyone is a clinical reality and con-

sidered standard of care—with our genome sequence

ideally connected to a lifelong electronic health record.

The cost/beneﬁt ratio of such a data structure has

been consistently shifting in its favor as the cost of

sequencing dramatically declines and information

on gene-disease associations increases. Indeed, the

promise of universal sequencing in clinical application

is being realized in some health systems, as shown in

the Geisinger MyCode example. Multiple other health

systems have large-scale pilot projects underway, in-

cluding examples such as Mayo Clinic, Intermountain

Healthcare, Mount Sinai Healthcare System, Kaiser

Permanente, and the Veterans Administration. It is

also increasingly the case that “centers for person-

alized medicine” have been established at leading

healthcare centers that offer whole-genome or

whole-exome sequencing to selected patients, often

with an initial focus on cancers or rare disorders.

Today, with thousands of genes associated with

thousands of diseases, it is perhaps not surprising that

genetic and genomic tests are becoming increas-

ingly applied in medicine across the lifespan. A key

application is in determining the “risk” for patients in

developing a disease that is associated with particular

alleles. The previously mentioned BRCA gene tests

for risk of hereditary breast cancers are one example,

with the BRCA1 and BRCA2 genes accounting for

20-25% of hereditary breast cancers. Testing positive

for these gene variants allows a patient to enter into

informed discussions with their physicians regarding

potential risk reduction approaches, such as increased

screening frequency or prophylactic breast removal

surgery. Multiple cancers now have genetic tests

associated with them for risk evaluation, including

breast, colorectal, cutaneous melanoma, gastric,

ovarian, pancreatic, prostate, renal cell, thyroid, and

uterine cancers. Cardiovascular-related tests are also

available to evaluate risks for developing aortopathies,

arrhythmias, cardiomyopathies, genetic forms of high

blood pressure and high cholesterol, and thrombophil-

ia. The above are just some of the areas of disease in

which genetic testing for risk is seeing application, and

the library of available tests will continue to expand.

Because most common diseases have been found

to have associations with many individual genes (i.e.,

they are polygenic, as opposed to monogenic), a

new area of science and practice is in development

focused on determining potential risk based on

the presence of multiple gene variants. This testing

results in the generation of “polygenic risk scores”

 Ossorio, Pilar N. “Polygenic Risk in a Diverse World.” Science, vol. , no. ,  Feb. .

 Ibid.

 Worthy, Liz. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. , no. , March-

April .

(PRS), which are an “emerging technology for aggre-

gating the small effects of multiple polymorphisms

across a person’s genome into a single score.”

It has

been noted, “In medicine and public health, PRSs

could, in the future, be used for initiating additional

risk screening or motivating behavior change.”

is an area of research interest and potential prom-

ise. Writing in early 2019, Liz Worthy notes that:

Over the last 18 months we are seeing increased

application of polygenic risk score analysis

making use of large GWAS [genome wide

association studies] and WGS [whole genome

sequencing] data. PRS seeks to estimate an

individual’s propensity towards particular

phenotype… These methods have a variety of

uses including human disease risk assessment

in research settings and there is increased focus

on their application within healthcare settings.

For the patient, the advantages afforded through

the application of genetic tests for disease pre-

disposition are potentially signiﬁcant—providing

a pathway for adopting risk reduction lifestyle or

medicinal approaches, more frequent use of early

disease detection screenings, and prophylactic

surgeries in selected instances. It is important to

note that genetic and genomic testing for the

predisposition of disease is best performed in

consultation with a patient’s physician and with

genetic counselors—skilled personnel who can

interpret the results and provide recommendations

for health strategies rooted in evidence-based clinical

practice. While there are direct-to-consumer tests,

there is risk attached to non-professional test result

interpretation that could lead to unnecessary anxiety

or pursuit of unnecessary/unproven interventions.

3. Diagnosing Diseases,

Rare Diseases, and Disorders

Genetic or genomic tests can not only determine

potential risk for developing a disease, they can

also be highly informative in guiding the diagnosis

of a present disease or disorder. As noted by the

precision medicine program at Duke University:

Whole genome and whole exome sequencing

are increasingly being used in the clinic to aid

in the diagnosis of rare congenital disorders

and solve diagnostic dilemmas. One of the ﬁrst

and most high-proﬁle examples of using clinical

sequencing to end a diagnostic dilemma is

the case of 6 year old Nic Volker at the Medical

College of Wisconsin, who suffered from a

 Duke Center for Applied Genomics and Precision Medicine. “Clinical Whole Genome Sequencing.” https://precisionmedicine.duke.edu/

researchers/precision-medicine-programs/clinical-whole-genome-sequencing. Accessed  May .

mysterious severe bowel disease of unknown

origin. Searching for an explanation and

treatment, doctors turned to next-generation

DNA sequencing technology. They identiﬁed a

mutation in the XIAP gene as the likely cause of

his illness, knowledge that suggested a course

of treatment that led to his recovery, ending

his diagnostic odyssey. Early results from some

clinical sequencing programs estimate the

success rate of disease gene identiﬁcation at

about 25-30%, offering hope to thousands of

individuals with previously undiagnosed or

untreated rare disorders, while recognizing that

sequencing will not provide all of the answers.

Case Study in Genetic Screening: Detecting

At-Risk Carriers Not Detected Through Other Methods

Results from a large cohort study conducted at Renown Health in Nevada show how genetic carrier

testing results in the identiﬁcation of risk in patients where it was not previously suspected. Describing

the study, Manolio noted that:

The value of genetic screening in an unselected population for identifying individuals carrying P/

LP genomic variants for HBOC [Hereditary Breast and Ovarian Cancer], Lynch syndrome, and FH

[Familial Hypercholesterolemia] has not been widely explored. The Healthy Nevada Project at Re-

nown Health performed exome sequencing in 26,906 participants with available electronic med-

ical records and analyzed genomic variants in nine risk genes for these conditions. Roughly 1.3%,

90% of whom had not been previously identiﬁed, carried P/LP variance. Among carriers, 22%, 70%

of whom were diagnosed before age 65, were diagnosed with clinically relevant disease. Less than

20% of carriers had medical record documentation of inherited genetic disease risk or relevant

family history.

The researchers conclude that: “this suggests that genomic screening for inherited cancer and cardio-

vascular risk conditions can identify a signiﬁcant number of at-risk carriers who are not detected by

standard medical practice and who may beneﬁt from earlier clinical risk screening.”

 Manolio, Teri A., et al. “Genomic Medicine Year in Review: .” The American Journal of Human Genetics, vol. ,  December

. Reporting on ﬁndings from Grzymski, J.J. et al. “Population Genetic Screening Efﬁciently Identiﬁes Carriers of Autosomal

Dominant Diseases.” Nature Medicine, vol. ,  July .

 Ibid.

Genetic and genomic tests for disease diagnosis

are being deployed across a broad range of rare

and more common diseases and disorders.

a. Diagnosis of Rare Diseases and Disorders

Rare diseases, by their inherent nature, present

diagnostic challenges because so few physicians have

encountered them. Often these diseases may present

symptoms seen in other, more common diseases

resulting in an understandable misdiagnosis and

inappropriate treatment strategies being adopted.

Patients and their families may embark on long

“diagnostic odysseys”, seeing dozens of practitioners,

undergoing multiple tests and procedures, enduring

fruitless attempts at treatment over many years

without ever getting a deﬁnitive, accurate diagnosis.

Genetic and genomic testing has been a pathway

to solving this dilemma in multiple diseases and

disorders impacting many thousands of patients.

While individual rare diseases are, by deﬁnition, rare,

they collectively impact a large global and domestic

population. Liu, Zhu, Roberts, and Tong estimate that:

Approximately 7000 rare diseases have been

recognized, a substantial number of which

are life threatening or chronically debilitating.

Around 80% of rare diseases are genetic in

origin. A single rare disease affects a small

number of the population (deﬁned as <1/15,000

in the US and <1/2000 in Europe)… Most rare

disease patients (50 to 75%) show onset at

birth or in childhood. As many as 30% of

rare diseases patients die before the age of

ﬁve years. Furthermore, each rare disease

patient has been estimated to cost a total

of $5 million throughout their lifespan.

 Liu, Zhichao, et al. “Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic testing in Rare Diseases: Where Are We?”

Trends in Genetics, vol. , no. , Nov. .

 National Center for Advancing Translational Sciences, Genetic and Rare Diseases Information Center. “FAQs About Rare Diseases.” https://

rarediseases.info.nih.gov/diseases/pages//faqs-about-rare-diseases. Accessed  May .

 Liu, Zhichao, et al. “Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic testing in Rare Diseases: Where Are We?”

Trends in Genetics, vol. , no. , Nov. .

 Chung, B.H.Y., et al. “Rare versus Common Diseases: a False Dichotomy in Precision Medicine.” npj Genomic Medicine, vol. , no. ,  Feb.

. doi:./s---x.

The Genetic and Rare Diseases Information Center

reports that 25-30 million people in the U.S. have a

rare disease, and over 350 million people worldwide

are afﬂicted.

Approximately 1 in 10 individuals

has a rare disease, so collectively rare diseas-

es have a signiﬁcant population impact.

Liu, Zhu, Roberts, and Tong further report that:

An incomplete knowledge of the natural history

of each rare disease can make a substantial

proportion (~60%) of rare diseases intractable

and undiagnosable. Panel-based NGS or

targeted sequencing tests are designed to

reveal causal mutations for genes known to

be associated with a speciﬁc rare disease.

Since the NGS gene panel is predesigned or

expert-selected, ultradeep, uniform coverage

allows for high sensitivity and also for speciﬁc

variant calling for rare genetic variants.

By deploying genetic and genomic testing, up to

and including whole genome sequencing, diagnos-

tic odysseys may be ended for many patients—not

only providing a pathway to appropriate treatment

but also reducing signiﬁcant waste in the health-

care system and the associated costs of incorrect

diagnosis. Even if no treatment is available, peace of

mind can result through simply having an “answer”

and being able to end the costly hunt for diagnosis.

In discussing rare diseases and the application of

sequencing, Chung, Chau, and Wong report on

impressive results from sequencing adoption:

Affected individuals often endure years of

diagnostic odyssey, which is not only fruitless

but more expensive than sequencing their

genomes upfront

80,81

. For infants admitted

to intensive care within the ﬁrst 100 days of

life, sequencing produced diagnostic yields

of 36.7%; and in 52.0% of the diagnosed,

medical management was affected.

Results

improved to 50.8% and 71.9%, respectively,

when trio sequencing was conducted. Other

studies have given similar results.

Ranging from individual genetic tests through to

complete whole-genome sequencing, the full range

of genetic and genomic tools and technologies are

now being deployed in clinical diagnostic testing.

“Besides targeted sequencing, there are increasing

applications of whole-genome sequencing/whole-ex-

ome sequencing (WGS/WES) to detect complex

genetic variants and provide complete genetic

information in support of rare disease diagnosis.”

This statement recognizes that while many rare

diseases may be associated with a single gene (i.e.,

Mendelian), there are also many challenging diseases

where multiple genes come into play (polygenic).

 Tan, T. Y., et al. “Diagnostic Impact and Cost-effectiveness of Whole-exome Sequencing for Ambulant Children with Suspected Monogenic

Conditions.” JAMA Pediatrics, vol. , Sept. .

doi:./jamapediatrics...

 Farnaes, L., et al. “Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization.” npj Genomic Medicine, vol. , no.

,  Apr. . doi:./s---.

 Meng, L., et al. “Use of Exome Sequencing for Infants in Intensive Care Units: Ascertainment of Severe Single-gene Disorders and Effect on

Medical Management.” JAMA Pediatrics, vol. , no. ,  Dec. . doi:./jamapediatrics...

 Wright, C. F., et al. “Pediatric Genomics: Diagnosing Rare Disease in Children.” Nature Reviews Genetics, vol. , no. ,  Feb. .

doi:./nrg...

 Liu, Zichao, et al. “Editorial: Advancing Genomics for Rare Disease Diagnosis and Therapy Development.” Frontiers in Pharmacology, vol. , no.

,  September .

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The New

England Journal of Medicine, vol., no. ,  Jan. .

 Centers for Disease Control and Prevention. “Sickle Cell Disease.” www.cdc.gov/ncbddd/ sicklecell/data.html#:~:text=In%the%United%

States&text=It%is%estimated%that%A,every%%C%Hispanic%DAmerican%births. Accessed  May .

b. Diagnosing Single Gene (Mendelian)

Disease and Disorders

Mendelian, single-gene diseases represent an ex-

tremely large compendium of diseases and disorders.

As noted by Collins, Doudna, Lander, and Rotimi, “The

discovery of genes responsible for more than 5000 rare

mendelian diseases has facilitated genetic diagnostics

for many patients, pregnancy-related counseling, new

drug treatments, and in some cases, gene therapies.”

A number of these single gene-associated diseas-

es and disorders have a substantial impact across

populations and within certain sub-populations.

Some of the more widely known examples include:

• Cystic Fibrosis (CF)—a progressive, genetic

disease that causes persistent lung infections and

limits the ability to breathe over time. In people

with CF, mutations in the cystic ﬁbrosis trans-

membrane conductance regulator (CFTR) gene

cause the CFTR protein to become dysfunctional.

CF affects approximately 30,000 Americans.

• Alpha- and beta-thalassemias—inherited

genetic blood disorders causing the body to

Whole genomic sequencing and whole exome sequencing are eliminating the phenomenon of the

diagnostic odyssey for rare genetic disease: it’s realistic today to have a genome or exome test ordered at

ﬁrst subspecialist outpatient visit and to have a diagnosis by the time of the second visit . This is clearly

the most powerful diagnostic tool ever developed for the millions of children with rare diseases.”

Stephen Kingsmore. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics

Magazine, vol. 6, no. 2, March-April 2019.

make fewer healthy red blood cells and less

hemoglobin than normal. Beta-thalassemia

affects at least 1,000 people in the U.S.; how-

ever, the exact prevalence is not known.

• Sickle cell disease—an inherited group of dis-

orders in which red blood cells are misshapen

into a sickle shape. The cells die early, leaving

a shortage of healthy red blood cells (sickle

cell anemia), and can block blood ﬂow. The

Centers for Centers for Disease Control and

Prevention (CDC) estimate that the disease

affects approximately 100,000 Americans.

• Fragile X Syndrome (FXS)—a genetic disease

that causes mild to severe intellectual disability,

with typical associated symptoms including

delays in talking, anxiety, and hyperactive be-

havior. The exact number of people who have

FXS is unknown, but a review of research studies

estimated that about 1 in 7,000 males and about 1

in 11,000 females have been diagnosed with FXS.

• Huntington’s Disease—a fatal genetic disorder

that leads to progressive breakdown of nerve

 Challenge TDT. “Beta-Thalassemia Overview.” www.challengetdt.com/beta-thalassemia-overview. Accessed  May .

 Centers for Disease Control and Prevention. “Sickle Cell Disease.” www.cdc.gov/ncbddd/ sicklecell/data.html#:~:text=In%the%United%

States&text=It%is%estimated%that%A,every%%C%Hispanic%DAmerican%births. Accessed  May .

 Centers for Disease Control and Prevention. “Fragile X Syndrome.” www.cdc.gov/ncbddd/fxs/ data.html. Accessed  May .

 Yohrling, George, et al. “Prevalence of Huntington’s Disease in the US.” Neurology, vol. , no. , , Apr. .

cells in the brain. Huntington’s Disease is esti-

mated to affect more than 40,000 Americans.

The undiagnosed diseases network (UDN), a multidisciplinary collaboration evaluating patients

who have with complex presentations and have remained undiagnosed despite extensive clinical

investigation, performed in depth clinical evaluations along with exome and whole genome

sequencing, metabolomics testing, and studies in model organisms. From 2015 to 2017, the UDN

accepted 601 of 1519 patients referred for evaluation. Of the ﬁrst 382 patients with a completed

evaluation, 132 (35%) received a diagnosis; these included 31 (11%) with new syndromes. Among

diagnosed patients, the majority (58%) had medical care changes, such as changes in therapy or

shortening of the diagnostic odyssey.”

Teri A. Manolio et al. 2019. “Genomic Medicine Year in Review: 2019.” The American Journal of Human Genetics, vol. 105, 5

Dec. 2019. Reporting on original research by Splinter, K., et al. The New England Journal of Medicine, vol. 379, 2131-2139, 2018.

Case Study in Whole Genome Sequencing for Diagnosis: Project

Baby Bear, California

As noted in ClinicalOmics, a pilot program in California funded by the state “showed that precision

medicine for critically ill babies enrolled in California’s Medicaid program reduced their suffering and

yielded better health outcomes, while decreasing the cost of their healthcare, saving the Golden State

$2.5 million.”

The initiative, named Project Baby Bear, deployed rapid Whole Genome Sequencing

(rWGS) as the core approach. Stephen Kingsmore, the President and CEO of Rady Children’s Institute

for Genomic Medicine, which led the project, notes that:

For seriously ill children who are hospitalized in intensive care units, the most signiﬁcant advance

has been ultra-rapid whole-genome sequencing. It’s routinely possible now to examine nearly

every genetic disease and either make a diagnosis or rule out genetic disease, in 36 hours. That’s

fast enough to guide weighty management decisions in even the most seriously ill children. Where

rapid whole-genome sequencing is absolutely transformative is in seriously ill children in whom a

genetic disease was not suspected at test order. Those children were, with the best intentions in

the world, being treated for the wrong diagnosis.

In describing the results of the pilot project, Kingsmore reports that the project (which used WGS for Medi-

Cal-enrolled infants in intensive care units at ﬁve California children’s hospitals) had compelling results:

In 720 infants in intensive care units tested so far, one in three received the genetic disease di-

agnosis, and in about 1/3, we are able to exclude genetic disease as the course of illness. One in

four infants has a change in care as a result of rapid whole genome sequencing. One in ﬁve has a

change in outcome.

A recent review report on the results of Project Baby Bear shows that over 23 months, the project:

• Completed rWGS on 178 babies and families.

• Provided diagnoses for 76 babies (43%).

• Led to a change in the management of 55 babies (31%) that resulted in fewer hospital days, fewer

procedures or new therapies.

• Diagnosed 35 rare conditions that occur in less than one in one million births.

• Achieved a three-day turnaround time for provisional results.

The study also demonstrated that this clinical application of whole genome sequencing “reduced

healthcare costs and downstream spending, primarily by empowering doctors to eliminate unneces-

sary procedures and discharge babies sooner.”

In a retrospective analysis of the program’s economic

impacts, it is concluded that:

By introducing Medi-Cal babies into a coordinated system of care that included physicians trained

in identifying babies likely to beneﬁt from whole genome sequencing, lab interpretation scien-

tists, genetic counselors and others, the state of California saved millions of dollars in healthcare

expenses due to avoided procedures and shorter hospital stays… The avoided procedures and

reduced hospital time amounted to $2.5 million in cost savings. These cost savings stemmed from

changes in the medical management of just 29 babies who received signiﬁcant beneﬁt from ge-

nome sequencing.

 “Rady Children’s Helps California’s Project Baby Bear Improve Outcomes, Save $.M.” Clinical Omics Magazine,  June .

 Kingsmore, Stephen. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine,

vol. , no. , March-April .

 Ibid.

 Rady Children’s Hospital – San Diego. “Project Baby Bear Final Report: Period Covering July ,  – June , .” Report to the

State of California.

 Ibid.

 Ibid.

c. Diagnosing Complex (Polygenic)

Diseases and Disorders

Most common debilitating diseases are not caused by

mutation of a single gene, rather they are inﬂuenced

by combinations of mutations in many genes each

having a small effect (but combining to have the

potential for large effects). Complicating the situation

is that the expression, regulation, or products of these

genes may be a result of interactions with a multiplic-

ity of environmental factors. There is thus a complex

“soup” of genetic and environmental factors at play in

many common diseases. While these diseases have

a complex etiology that does not mean that progress

cannot be made. Indeed, with the sophisticated tools

of next generation sequencing and advanced compu-

tational analytics, signiﬁcant biological and mechanis-

tic insights are being produced. As noted in a recent

perspective in the New England Journal of Medicine:

The discovery of more than 100,000 robust

associations between genomic regions

and common diseases has pointed to new

biologic mechanisms, such as the role of

microglia in Alzheimer’s disease, autophagy

in inﬂammatory bowel disease, and synaptic

pruning in schizophrenia. It has also enabled

the development of polygenic risk scores

to identify patients at increased risk for

heart disease, breast cancer, and other

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The New

England Journal of Medicine, vol., no. ,  Jan. .

 Helbig, I. et al. “The ClinGen Epilepsy Gene Curation Expert Panel—Bridging the Divide Between Clinical Domain Knowledge and Formal Gene

Curation Criteria”. Human Mutation, vol. , no. , Nov. .

conditions, although additional rigorous

testing of such scores is needed, including

evaluation of clinical outcomes.

For many common diseases, the challenge of

identifying and characterizing genetic effects

is not insigniﬁcant. In the case of epilepsy, for

example, analysis of the ClinGen Epilepsy Gene

Curation Expert Panel indicates 2,702 genes as-

sociated with epilepsy, a disorder that affects

approximately 50 million people worldwide.

Multifactorial inheritance disorders are caused by a

combination of environmental factors and mu-

tations in multiple genes. For example, different

genes that inﬂuence breast cancer susceptibility

have been found on chromosomes 6, 11, 13, 14, 15, 17,

and 22. Some common chronic diseases are multi-

factorial disorders, with examples including:

• heart disease

• high blood pressure

• Alzheimer’s disease

• arthritis

• diabetes

• cancer, and

• obesity.

Eric D. Green, et al. “Perspective: Strategic Vision Medi-

cineNet. “Genetic Diseases (Disorder Deﬁnition, Types, and

Examples). www.medicinenet.com/genetic_disease/article.

htm. Accessed 12 May 2021.

Building on the recent successes of unraveling the genetic underpinnings of rare and undiagnosed

diseases, the ﬁeld is poised to gain a more comprehensive understanding of the genetic

architecture of all human diseases and traits. However, myriad complexities can be anticipated. For

example, any given genomic variant may affect more than one disease or trait; can confer disease

risk or reduce it; and connect additively, synergistically, and/or through intermediates.”

Eric D. Green, et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature,

vol. 586, 29 October 2020.

4. Rational Drug Development

Pharmaceuticals (drugs) are a fundamental part of the

armamentarium of medicine, providing the means

to treat and ameliorate the symptoms of disease, and

in some cases, cure the disease. Pharmaceuticals

bring relief to millions worldwide and have greatly

extended the average human lifespan and quality of

life across that lifespan. Traditionally, drug discovery

has used a trial-and-error approach whereby a library

of chemical substances is tested on cultured cells or

animals and evaluated for its effects. Molecules gen-

erating an apparent positive effect are then brought

forward into clinical trials to evaluate effectiveness

on a disease in humans. Rational drug development,

however, takes a different approach, one in which

biomarkers or preidentiﬁed druggable targets that

are present in, or generated by, a disease may serve

as molecular targets for purposefully designed drugs

designed to bind to the target. Human genetics and

genomics assist in this approach in multiple ways:

• Helping to identify biomarkers, protein targets,

etc. through comparative analysis of disease

affected patients versus healthy individuals.

• Identifying genetic variations across indi-

viduals impacted by the disease that may

inﬂuence the effectiveness of a designed

drug (often related to differences in metab-

olism) and potential adverse side effects.

• As noted by Dugger, Platt and Goldstein,

sequencing can inform understanding of “the

phenotypic effects of a spectrum of rare muta-

tions ranging from loss-of-function to gain-of-

function mutations within a single gene” and can

provide “information on the putative efﬁcacy and/

or toxic effects resulting from the modulation

of that particular gene product in humans. This

knowledge thereby builds conﬁdence in the

rationale for targeting that gene product for the

 Dugger, Sarah A., et al. “Drug Development in the Era of Precision Medicine.” Nature Reviews Drug Discovery, vol. , no. ,  Dec. .

 Ibid.

 The PCSK gene provides instructions for making a protein that helps regulate the amount of cholesterol in the bloodstream.

 Dugger, Sarah A., et al. “Drug Development in the Era of Precision Medicine.” Nature Reviews Drug Discovery, vol. , no. ,  Dec. .

 Ciriello Pothier, Kristen. Personalizing Precision Medicine. A Global Voyage from Vision to Reality. John Wiley & Sons, Inc., .

treatment of a more common human disease,

rather than relying on information gained from

less predictive animal or cellular models.”

100

The application of genetics and genomics to drug

development has resulted in multiple clinical success-

es. Monoclonal antibodies for the treatment of various

immune-mediated conditions (targeting the protein

interleukin-23 for example, produced by the IL23R

gene) are already used clinically. Similarly, mutations

in the PCSK9

101

gene were identiﬁed in families with

autosomal dominant hypercholesterolemia, and

pursuing PCSK9 as a drug target resulted in the FDA

“approving two monoclonal antibodies (alirocumab

and evolocumab) for the treatment of high cholesterol

not adequately controlled by statins or diet.”

102

Put

simply, since genes code for proteins, and proteins

(and nucleic acids) are typical biomolecular targets

for drugs, understanding the relationship between

genes and disease provides potential for rationally

identifying drug targets. Kalydeco, a targeted drug for

cystic ﬁbrosis, approved by FDA in 2012, resulted from

rational drug development informed by genomics.

Cystic ﬁbrosis is characterized by physical responses

to the abnormal ﬂow of salt and ﬂuids in and out

of the cells in different parts of the body. Kalydeco

speciﬁcally “acts on the gating defect associated

with the CFTR protein [coded by the CFTR gene],

helping to open up the blocked chloride channels.”

103

It is interesting to note that, in some regards, ge-

netics and genomics advancements have helped

to rebalance pharmaceutical research in terms of

work on chronic diseases versus rare diseases. Given

the prior trial-and-error model, it was in the best

interests of the industry to concentrate resources

on major chronic conditions in search of blockbust-

er drugs. Costly and with a high failure rate, drug

companies had to triage their funds towards areas

with the most promise for ﬁnancial return. Modern

genomics, however, and the large-scale identiﬁcation

of gene-disease associations has provided a more

target-rich environment to address rarer, typically

monogenic, disorders

104

—while at the same time

showing that many of the more common diseases are

highly complex genetically, with sometimes hundreds

and even thousands of genes engaged. The result is

noted in a recent 2021 study by the Biotechnology

Innovation Organization (BIO), which reports that:

Throughout the last decade, industry investment

and drug development have pivoted towards

rare, congenital diseases. Speciﬁc examples

of clinical and commercial successes have

encouraged this transition. Drivers of these

successes include targeting molecularly deﬁned

causes of disease, regulatory incentives, and

favorable reimbursement environments.

105

The BIO report provides a review of two longitudinal

datasets on drug development, and notes that:

One large difference between this 2011–2020

dataset and the previous 2006–2015 iteration

is the intensifying focus on rare diseases. Our

latest analysis includes 1,256 phase transitions

within rare diseases, a considerable increase over

the 521 noted in the previous study. This spans

685 different lead developers (not including

those listed solely as partners). This indicates

that companies view pivoting to rare disease

clinical development as a sound strategy.

106

The BIO authors note that drug development for

rare disorders has had “notably more successful

than industry averages—and in particular chronic,

highly prevalent diseases.” They also note that:

A greater understanding of human disease—

whether at the molecular or genomic

level—ultimately leads to the investigation

 Rare diseases have often been termed “orphan diseases” in that they represent a class of disease that had not been “adopted” by the

pharmaceutical industry.

 Thomas, David. Clinical Development Success Rates and Contributing Factors –. BIO, Informa Pharma Intelligence, and QLS, Feb.

.

 Ibid.

 Ibid.

 Ibid.

of personalized medicine. Indications are

increasingly segmented by biomarkers in

order to match patients with the treatments

most likely to show the greatest beneﬁt,

according to the underlying drug mechanism

and disease pathophysiology. We identiﬁed

767 phase transitions out of 12,728 (6%) that

incorporated patient preselection biomarkers

in their corresponding clinical trial design.

This was accomplished by mapping Informa

Pharma Intelligence’s Biomedtracker

and Trialtrove databases, to provide the

supplemental level of clinical trial detail.

107

This later statement is important—showing that phar-

maceutical companies are now able to use genetic

and genomic information to target the trials of their

biopharmaceutical molecules to patients who have

been preselected through the presence of biomarkers

(often genetic). This has the potential to advance

more drugs successfully towards market since they

are more likely to demonstrate efﬁcacy in their trials

by virtue of being rationally targeted. The BIO authors

conclude that the data they have reviewed “builds

conﬁdence in the pursuit of drug development

programs targeted at biomarker-enriched patient

populations. Such assets are likely to advance through

clinical development with lower levels of attrition and

should in theory improve patient outcomes via the

advent of increasingly personalized medicine.”

108

What

is evident is that advancements in human genetics

and genomics are not only delivering deﬁnitive

diagnoses for patients, guiding their care; they

are also highly contributory to the development of

new therapeutics to treat identiﬁed conditions.

Case Study: Genomics and Rational Drug Development in Cancer

As noted by Collins, Doudna, Lander, and Rotimi: “Studies of cancer genomes have revealed hundreds of genes in

which somatic mutations propelled tumor initiation and growth, information that has fueled the development of

new drugs.”

109

Two long-standing cancer drugs, developed with the help of genetics and genomics, are illustrative:

• Approved by the FDA in 1998, Herceptin is a drug that targets metastatic breast cancer cells that overproduce

the HER2 protein (a product of the HER2 gene). It was the ﬁrst approved targeted drug based on an individu-

al’s genetics, and also came with development of an FDA approved companion diagnostic called HercepTest.

Herceptin has had robust results in achieving improved outcomes in patients. Pothier reports that an October

2014 study showed the overall 10-year survival rate for patients to be 84% for those treated with Herceptin and

chemotherapy, versus 75% for patients treated with chemotherapy only.

110

• Another example of rational drug development for cancer is Gleevec (imatinib). Chronic myeloid leukemia

(CML) is fundamentally a genetic disease caused by mutations in a patient’s DNA that translocate genes be-

tween chromosomes 9 and 22. The translocated genes generate a hybrid gene that produces a novel protein

that causes greatly accelerated production of white blood cells in bone marrow (i.e., a cancer, as deﬁned by

uncontrolled cell proliferation). According to the American Cancer Society, CML comprises circa 15% of leuke-

mias in adults. Without a cure, a diagnosis of CML used to mean a best-case survival of 5 years post diagnosis

through aggressive cytotoxic chemotherapy with severe side effects. The discovery of the gene translocation

causation of CML provided scientists with a target for therapeutic development. Oncologist Brian Druker de-

veloped a targeted drug, Gleevec (imatinib) and collaborated with Novartis to bring the drug forward through

clinical trials. The drug was a success, effectively blocking the effect of the translocated genes. For the great

majority of CML patients, Gleevec is a highly effective treatment—providing a pathway to normal life expec-

tancy through a pill taken once a day with only mild side effects. Gleevec is not a “cure”, because the mutated

genes are still present, but the drug is highly effective at stopping these genes from causing leukemia. In up to

30% of cases, patients start to develop resistance to Gleevec, but ongoing research has resulted in the develop-

ment of two alternative drugs aimed at the hybrid gene, Sprycel (dasatinib) and Tasigna (nilotinib) enabling

a patient to switch between drugs if resistance develops. Through increasingly sensitive diagnostic tests of

BCR-ABL gene expression and blood analysis, clinicians are able to monitor the effect of the administered drug,

modify dosage, and switch drugs if resistance development is detected. In effect, the treatment of CML became

one of the pioneers in a personalized approach to genetic medicine.

Other examples are Tarceva (erlotinib) and Iressa (geﬁtinib) both of which restrict activation of a protein (epidermal

growth factor, or EGFR) which is abnormally active in a subset of lung cancers due to mutations in the protein.

111

The National Cancer Institute (NCI) reports that “as a result of research into the genomic changes associated with

cancer, drugs have been developed to ﬁght the disease in several ways:

• Inhibiting enzymes that trigger the abnormal growth and survival of cancer cells.

• Blocking aberrant gene expression characteristic of cancer cells.

• Halting molecular signaling pathways that are in overdrive in cancer cells.

112

The NCI notes that “these “targeted therapies” speciﬁcally combat characteristics of cancer cells that are different

from normal cells of the body. This makes them less likely to be toxic for patients compared to other treatments

such as chemotherapy and radiation that can kill normal cells.”

113

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The

New England Journal of Medicine, vol., no. ,  Jan. .

 Ciriello Pothier, Kristen. Personalizing Precision Medicine. A Global Voyage from Vision to Reality. John Wiley & Sons, Inc., .

 National Cancer Institute. “Cancer Genomics Overview.” www.cancer.gov/about-nci/organization/ccg/cancer-genomics-overview.

Accessed  May .

 Ibid.

 Ibid.

5. Precision Medicine and Targeted

Therapeutics (Pharmacogenetics)

Having an ability to sequence a patient’s whole ge-

nome rapidly and cost-effectively has opened the door

to a new paradigm in healthcare termed “precision

medicine” whereby an individual’s genetic proﬁle is

used to guide decisions made in regard to the preven-

tion, diagnosis, and treatment of disease. As noted by

NHGRI, “knowledge of a patient’s genetic proﬁle can

help doctors select the proper medication or therapy

and administer it using the proper dose or regimen.”

114

The discipline of “pharmacogenomics” (also “phar-

macogenetics”) has grown to be able to deploy

genetic and genomic knowledge and tools to help

physicians select the “right drug and the right dose”

for a patient based on their genome (assuming

there is statistically signiﬁcant clinical information

linking a drug to speciﬁc gene variants in terms of

efﬁcacy and side effects). Pharmacogenetics is an

area of research and, increasingly, clinical practice,

that addresses the genetically determined varia-

tion in how individuals respond to speciﬁc drugs in

terms of differences in dose requirement, efﬁcacy,

and the risk of adverse drug reactions (ADRs).

David Khan, in the Journal of Allergy and

Clinical Immunology, notes that:

At its most basic, the term pharmacogenetics

describes any inﬂuence that genetics

can have on drug therapy. The newer

 National Human Genome Research Institute. “ Glossary of Genetic Terms: Personalized Medicine.” www.genome.gov/genetics-glossary/

Personalized-Medicine. Accessed  May .

 Khan, David A. “Pharmacogenomics and Adverse Drug Reactions: Primetime and Not Ready for Primetime Tests.” Journal of Allergy and

Clinical Immunology, vol. , no. , Oct. . doi:./j.jaci....

term pharmacogenomics is often used

interchangeably with pharmacogenetics,

but there are some subtle differences.

Pharmacogenetics mainly deals with

single drug-gene interactions. In contrast,

pharmacogenomics incorporates genomics

and epigenetics to look at the effect of multiple

genes on drug responses. Pharmacogenomics

is considered the future of drug therapy

and is a rapidly growing ﬁeld in the area

of precision (personalized) medicine.

115

Pharmacogenetics and pharmacogenom-

ics enable three principal pathways to the

improvement of clinical outcomes:

1. Selection of the therapeutic (among multiple

choices) that is likely to prove most efﬁcacious

based on the patient’s genome and a drug’s

proven efﬁcacy for their speciﬁc genotype.

2. Ruling-out a therapeutic (among multiple

choices) based on the patient’s genome and

a drug’s potential for unacceptable adverse

side effects given their speciﬁc genotype.

3. Development of an optimized drug dosage for a

patient based on their genotype’s inﬂuence on

the rate at which they will metabolize the drug.

In terms of this last beneﬁt, Namandie

Bumpus notes that:

Owing to genetics, people can be categorized

as poor, intermediate, extensive, or ultrarapid

The ability to tailor a drug regimen to a speciﬁc genetic code that is truly personalized to that

speciﬁc DNA double helix has been a dream of researchers, physicians, and patients alike. Advances

in precision medicine, speciﬁcally around the genome…are making this dream a reality.”

Kristen Ciriello Pothier. 2017. Personalizing Precision Medicine. A Global Voyage from Vision to Reality. John Wiley &

Sons, Inc., 2017.

metabolizers of certain drugs. For example, in

the case of a drug that is pharmacologically

active and its metabolites inactive, a drug may

accumulate in the body of a poor metabolizer

and toxicity could occur as a result. By contrast,

someone who is an ultrarapid metabolizer of

the same drug may not achieve concentrations

of the drug in their blood that are high enough

to be effective. For prodrugs, where the parent

drug is inactive or substantially less active

than its metabolite, genetically encoded

variation in drug metabolism could affect the

ability of a person to activate the drug.

116

In regard to adverse drug reactions,

David Khan points out that:

Medications are a cornerstone of the therapeutic

armamentarium for most clinicians. The goal of

pharmacotherapy is to cure or control a speciﬁc

condition or disease without causing adverse

effects. Unfortunately, adverse drug effects are

common and not always predictable. Adverse

drug reactions (ADRs) have been deﬁned as

reactions that are noxious and unintended

 Bumpus, Namandje N. “For Better Drugs, Diversity Clinical Trials.” Science, vol. , no. ,  Feb. . doi:./science.abe.

 Khan, David A. “Pharmacogenomics and Adverse Drug Reactions: Primetime and Not Ready for Primetime Tests.” Journal of Allergy and

Clinical Immunology, vol. , no. , Oct. . doi:./j.jaci....

 Ibid.

 Relling, Mary. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. , no. , March-

April .

and occur at doses normally used in human

subjects. ADRs can be related to a number of

factors, including known pharmacologic activity

of a drug, drug interactions, drug toxicity, and

drug hypersensitivity. ADRs are a relatively

common cause of morbidity and mortality.

117

He further notes that “genetic factors can play a role

in pharmacokinetics, pharmacodynamics, and sus-

ceptibility to hypersensitivity responses. The degree

to which genetics contributes to ADRs is not entirely

clear and varies by drug, as well as the type of ADR.”

118

Keeping up with the research literature in regard to

pharmacogenetics and pharmacogenomics ﬁndings

regarding speciﬁc drugs has been an expanding

challenge for clinicians. However, several leading

organizations have been collaborating, and reliable

peer-reviewed compendia resources for recom-

mendations have come online. This is highlighted

by Mary Relling, who reports that the application of

pharmacogenomics to improving healthcare is being

codiﬁed through “a number of users converging

on key peer reviewed, nonproﬁt curated genomic

medicine resources to guide clinical actions, such

as ClinVar, ClinGen, the Clinical Pharmacogenetics

Implementation Consortium (CPIC), and PharmGKB.”

119

a. Targeting to Increase Effectiveness

When a healthcare provider is considering prescribing

a drug the knowledge of the patient’s genotype can

now be used in many cases to guide the therapeutic

strategy, identify the most effective drug, determine

appropriate dosing, and assess the risk of toxicity or

other negative side effects. The U.S. Food and Drug

Administration (FDA) provides a list of pharmaco-

genetic associations that it has evaluated and for

which it considers there to be “sufﬁcient evidence

to suggest that subgroups of patients with certain

genetic variants, or genetic variant-inferred pheno-

types, are likely to have altered drug metabolism,

In cancer, tumor proﬁling is typically

performed for patients: with cancer with

an unknown primary; with cancer that has

not responded to standard treatments;

and, to help guide decision-making when

there are multiple treatment options. De-

pending on the clinical situation, the test-

ing method may be a single gene, a gene

panel, whole exome, or less commonly,

whole genome sequencing.

Table 8: Analysis of FDA Recognized Pharmacogenetic Associations

A1 = Data support therapeutic management recommendations

A2 = Data indicate a potential impact on safety or response

A3 = Data demonstrate a potential impact on pharmacokinetic properties only

Macro Category Disease or Condition A1 A2 A3 Sum

Cancer Cancer - Breast

2 1 3

Cancer Cancer - Leukemia

2 1 3

Cancer Cancer - Colon

2 2

Cancer Cancer - Lung

2 2

Cancer Cancer - Peripheral T-Cell Lymphoma

1 1

Cancer Cancer - Rectal

1 1

Cancer Cancer - Bladder

1 1

Cancer Cancer - Skin

1 1

Cancer Cancer - Kidney

1 1

Cancer Cancer - Soft Tissue Sarcoma

1 1

Cardiovascular Heart Attack or Stroke (blood thinners)

2 2

Cardiovascular Hypertension (high blood pressure)

1 1 2

Cardiovascular Cardiac Arrythmia

1 1 2

Cardiovascular Hypercholesterolemia

1 1

Dermatologic Eczema

1 1

Gastroenterological Nausea and Vomiting (antiemetics)

3 3

Gastroenterological GERD/Acid Reﬂux

2 1 3

Gastroenterological Ulcerative Colitis

1 1 2

Hematologic Thrombocytopenia

1 1

Immunologic Transplant Rejection (immune suppression)

1 1

Infectious Disease HIV/AIDS

2 1 1 4

Infectious Disease Tuberculosis

1 1

Infectious Disease Bacterial Infections

1 1

Metabolic Obesity

1 1

Metabolic Gaucher’s Disease

1 1

Muscle Rare Muscle Disorders

2 2

Muscle Muscle Relaxation for Surgery/Intubation

2 2

Neurologic Convulsions/Seizures

3 2 1 6

Neurologic Pain (treated by anti-inﬂammatories, narcotics, etc.)

3 1 1 5

Neurologic Nerve Pain (treated by antidepressants)

4 4

Macro Category Disease or Condition A1 A2 A3 Sum

Neurologic Tourette’s Syndrome

2 2

Neurologic Huntington’s Disease (Chorea)

2 2

Neurologic Narcolepsy

1 1

Neurologic Opioid Withdrawal

1 1

Neurologic Multiple Sclerosis

1 1

Neurologic Tardive Dyskinesia

1 1

Neurologic Alzheimer’s Disease/Dementia

1 1

Neurologic Insomnia

1 1

Psychiatric Depression

5 5 10

Psychiatric Schizophrenia

6 1 7

Psychiatric ADHD

2 2

Psychiatric Bipolar Disorder

2 2

Psychiatric Obsessive Compulsive Disorder

1 1

Psychiatric Anxiety

1 1

Psychiatric Female Hypoactive Sexual Desire Disorder

1 1

Rheumatologic Rheumatoid Arthritis

2 1 3

Rheumatologic Osteoarthritis

2 2

Rheumatologic Gout

1 1

Rheumatologic Dry Mouth in Sjogren’s Syndrome

1 1

Urologic Overactive Bladder/Incontinence

1 1 2

Urologic Kidney Stones

1 1

Note: An individual drug may have more than one disease or condition for which it has application. For example, the drug Irinotecan is used for both

colon cancer and small cell lung cancer, and the UGTA gene is associated with the metabolism of the drug and thus is of effect for both types of

cancers for which Irinotecan may be prescribed.

Source: TEConomy Partners analysis of FDA Table of Pharmacogenetic Associations.

and in certain cases, differential therapeutic effects,

including differences in risk of adverse events.”

120

While cancer is perhaps the most well recognized

cluster of disease for which genetic tests may impact

drug selection and dosing, analysis of FDA data

(Table 8) shows that pharmacogenetic associations

are in place for multiple chronic diseases and con-

ditions, covering applications in major categories

such as cardiovascular disease, gastroenterological

 U.S. Food & Drug Administration. “Table of Pharmacogenomic Associations.” www.fda.gov/ medical-devices/precision-medicine/table-

pharmacogenetic-associations.  Feb. .

diseases and disorders, infectious diseases, neuro-

logical diseases and disorders, psychiatric conditions,

and rheumatologic disease. Pharmacogenetic

associations now span a range from relatively rare

diseases such as Tourette’s syndrome and Tardive

dyskinesia to common conditions such as hy-

percholesterolemia and depression (with over 50

listed in Table 8). There are more than 100 drugs for

which the associations are now listed by the FDA.

Case Study: Pharmacogenetics/Pharmacogenomics

and Cancer Treatment Efficacy

Cancer is a genetic disease. As noted by the National Cancer Institute (NCI):

Cancer is a group of diseases caused by changes in DNA that alter cell behavior, causing uncon-

trolled growth and malignancy. These abnormalities can take many forms including DNA muta-

tions, rearrangements, deletions, ampliﬁcations, and the additional removal of chemical marks.

These changes can cause cells to produce abnormal amounts of particular proteins or make

misshapen proteins that do not work as they should. Oftentimes a combination of several genomic

alterations work together to promote cancer . Genetic alterations can be inherited from one’s par-

ents, caused by environmental factors, or occur during natural processes such as cell division. The

changes that accumulate over one’s lifetime are called acquired or somatic changes and account

for 90 to 95% of all cases of cancer. The ﬁeld of cancer genomics is a relatively new research area

that takes advantage of recent technological advances to study the human genome, meaning our

full set of DNA. By sequencing the DNA and RNA of cancer cells and comparing the sequences to

normal tissues such as blood, scientists identify genetic differences that may cause cancer. This

approach, called structural genomics, may also measure the activity of genes encoded in our DNA

in order to understand which proteins are abnormally active or silenced in cancer cells, contribut-

ing to their uncontrolled growth.

121

The NCI reports that “genomic information about cancer is leading to better diagnosis and treatment

strategies that are tailored to patients’ tumors, an approach called precision medicine. As a result of

research into the genomic changes associated with cancer, drugs have been developed to ﬁght the

disease in several ways:

• inhibiting enzymes that trigger the abnormal growth and survival of cancer cells

• blocking aberrant gene expression characteristics of cancer cells, and

• halting molecular signaling pathways that are in overdrive in cancer cells.”

122

It should also be noted that terms such as breast cancer, pancreatic cancer, or lung cancer, for example,

denote the location in which the cancer presents in the body, but that does not mean that every occur-

rence of these cancers is the same. Each form of cancer is typically characterized by there being many

cancer subtypes that can vary considerably between patients. The NCI notes that genetics and genom-

ics are proving to be an effective tool in characterizing cancer types and subtypes and elucidating their

comparative response to different therapeutic approaches. The NCI reports, for example, that:

Cancer genomics research also contributes to precision medicine by deﬁning cancer types and

subtypes based on their genetics. This molecular taxonomy of cancer can provide patients with

more precise diagnosis, and therefore a more personalized treatment strategy. There are several

ways in which the molecular deﬁnition of cancer already beneﬁts patients:

• Breast cancer is classiﬁed based on molecular characteristics into distinct subgroups—Lumi-

nal A, Luminal B, triple-negative/basal-like, and HER2 type—that vary in their aggressiveness

and respond differently to therapies. Breast cancer patients may beneﬁt from diagnosis and

treatment guided by knowledge of their tumor’s molecular subtype.

• Diffuse large B cell lymphoma can be divided into the ABC and GCB subtypes by genomic

proﬁling, identifying patients who respond differently to current chemotherapy regimens and

molecularly targeted therapies.

 National Cancer Institute. “Cancer Genomics Overview.” www.cancer.gov/about-nci/organization/ccg/cancer-genomics-overview.

Accessed  May .

 Ibid.

• In 2013, The Cancer Genome Atlas project identiﬁed four subtypes of endometrial cancer—

POLE ultramutated, microsatellite instability (MSI) hypermutated, copy-number (CN) low,

and CN high—that correlate with patient survival. This research has already given rise to new

clinical trials and investigation of how these subtypes can improve the future of endometrial

cancer care.

• Lung cancer patients who have a gene fusion involving the ROS1 gene often respond well to

treatment with a targeted therapy called crizotinib. In these cases the disease is best deﬁned and

treated based on its unique genetic change.

123

Elaine Mardis reviewing major advancements in omics sciences notes that:

In my opinion, the most signiﬁcant advances are the increasing numbers of FDA-approved tar-

geted and immunotherapies in cancer, most of which can be correlated to genomic aspects of

cancers including speciﬁc genes/mutations of known cancer driver genes, and immunogenomic

metrics such as increased neoantigen load, microsatellite instability in the setting of mismatch

repair defects that predict sensitivity to immune checkpoint blockade inhibitors, or sensitivity to

PARP inhibitors in the setting of homologous repair defects.

124

Because of its nature as a “genetic disease”, cancer has long been on the frontlines in the clinical appli-

cation of advanced genetics and genomics. This has paid off considerably, such that “today, biomarkers

directly connected to drugs, or to crucial outcomes in the human body, allow physicians to identify

drugs that are most likely to help a patient, and those drugs can be used to target cancerous cells only,

which reduces the side effects that the patient experiences.”

125

 Ibid.

 Mardis, Elaine. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Magazine, vol. ,

no. , March-April .

 Ciriello Pothier, Kristen. Personalizing Precision Medicine. A Global Voyage from Vision to Reality. John Wiley & Sons, Inc., .

b. Reducing Drug Side Effects

According to the U.S. Department of Health and

Human Services (DHHS), an “adverse drug event (ADE)

is an injury resulting from medical intervention related

to a drug. This includes medication errors, adverse

drug reactions, allergic reactions, and overdoses.”

126

inpatient settings, the DHHS reports that adverse drug

events account for an estimated 1 in 3 of all hospital

adverse events, affecting about 2 million hospital stays

each year and prolonging hospital stays by 1.7 to 4.6

days. In outpatient settings, adverse drug events each

year account for over 3.5 million physician ofﬁce visits,

 U.S. Department of Health and Human Services. “Adverse Drug Events.” https://health.gov/our-work/health-care-quality/adverse-drug-events.

Accessed  May .

 Ibid.

an estimated 1 million emergency department visits,

and approximately 125,000 hospital admissions.

127

Variations in individual genomes have been found

to have signiﬁcant impact on risk for adverse drug

reactions, and there is increasing evidence helping

to guide physician decisions regarding which drugs

to prescribe, which to avoid, and what dosing should

be used to lessen the risk of an adverse event. The

previously cited data for FDA pharmacogenetic

associations lists several drugs for which genetic tests

can identify patients at higher risk for adverse drug

reactions. Examples are shown on Tables 9 and 10.

Table 9: Examples of Drugs with Pharmacogenetic Associations with Adverse Reactions

Drug Disease or Disorder Treated Gene Affected Subgroups

Abacavir HIV/AIDS HLA-B *57:01 allele positive

Carbamazepine

Seizures (anticonvulsant), also used in

peripheral neuropathy and bipolar disorder

HLA-B *15:02 allele positive

Lapatinib Breast cancer HLA-DRB1 *07:01 allele positive

Simvastatin Hypercholesterolemia and high triglycerides SLC01B1

521 TC or 521 CC

(intermediate or poor

function transporters)

Warfarin

Blood thinner used in patients with risk of

heart attack or stroke

CYP4F2 V433M variant carriers

Source: TEConomy Partners analysis of FDA Table of Pharmacogenetic Associations.

Table 10: Examples of Drugs with Pharmacogenetic Associations

with Poor Drug Metabolism which may Result in High Systemic

Concentration and Associated Adverse Reactions

Drug Disease or Disorder Treated Gene Affected Subgroups

Amifampridine Rare muscle diseases NAT2 Poor metabolizers

Amphetamine ADHD, Narcolepsy, Obesity CYP2D6 Poor metabolizers

Fluorouracil Skin cancer and actinic keratosis DPYD

Intermediate and

poor metabolizers

Iloperidone Schizophrenia CYP2D6 Poor metabolizers

Tolterodine Overactive bladder CYP2D6 Poor metabolizers

Source: TEConomy Partners analysis of FDA Table of Pharmacogenetic Associations.

Case Study: Avoiding Adverse Drug Events in HIV Treatment

Ziagen (abacavir) is a frequently prescribed antiviral for HIV patients. It is an example of an important

medication that, unfortunately, has signiﬁcant adverse effects for a proportion of patients taking it. Ap-

proximately 3-5% of patients taking Ziagen are hypersensitive to it and may have signiﬁcant reactions

(including potentially fatal reactions). In the early 2000s, a family of genes were discovered to be asso-

ciated with Ziagen hypersensitivity (those with the HLA-B*57:01 gene variant). Genetic testing deﬁni-

tively identiﬁes whether an HIV positive patient has the gene variant, and it has been found that those

patients without the variant will be free of the hypersensitivity.

As noted by David Khan:

Approximately 3% to 5% of patients treated with abacavir have a hypersensitivity syndrome that

typically appears within the ﬁrst 6 weeks of therapy and rarely can be fatal. Multiorgan symptoms,

including fever, rash, gastrointestinal symptoms, respiratory symptoms, and hypotension, can occur

along with liver and renal involvement.”… “A landmark study was performed to determine whether

screening patients with HIV-1 for HLA-B*5701 before treatment with abacavir would reduce the inci-

dence of the hypersensitivity reaction. This study was the ﬁrst to show in a very rigorous manner the

beneﬁts of pharmacogenetic testing in reducing the risk of hypersensitivity reactions. In 2008, the US

Food and Drug Administration issued an alert recommending that all patients should be screened

for the HLA-B*5701 allele before starting or restarting therapy with abacavir or abacavir-containing

medications.

128

 Khan, David A. “Pharmacogenomics and Adverse Drug Reactions: Primetime and Not Ready for Primetime Tests.” Journal of Allergy

and Clinical Immunology, vol. , no. , Oct. . doi:./j.jaci....

6. Gene Editing and Gene Therapy

Much of the important work of genetics and genomics

has come in the form of identifying gene variants that

are associated with a disease. The identiﬁcation of a

gene variant that codes for a malformed protein, or

fails to produce an important protein, or otherwise

effects disease etiology, provides potential biomarkers,

or targets, for developing diagnostics and, hopefully,

therapeutic drugs—very useful tools in the clinical

toolkit. But what if instead of treating the effects of

a miscoded gene, we could instead correct (edit) the

gene itself? If we could do that, then the application

of genetics and genomics would not just be to treat

the symptoms of a disease, it would potentially cure

it (particularly in the case of a monogenic disease or

disorder). This is the basis of the development of the

ﬁeld of gene therapy, which the FDA describes as:

A technique that modiﬁes a person’s genes

to treat or cure disease. Gene therapies can

work by several mechanisms: replacing a

disease-causing gene with a healthy copy

of the gene; inactivating a disease-causing

gene that is not functioning properly, [or]

introducing a new or modiﬁed gene into

the body to help treat a disease.

129

Ultimately, gene editing and gene therapy repre-

sent new pathways to the treatment and curing of

diseases, but these approaches are still in the early

stages of clinical application. Part of the caution in

clinical application currently arises from a need for

further study of the potential for off-target gene

edits (mutagenesis) to occur in non-targeted genes

and for unintended mosaicism to occur. Researchers

note, however, that the utility of gene editing is not

only in its potential clinical application, but also

as a powerful tool for investigating gene variation,

function, and linkages to diseases and disorders:

Advances in DNA synthesis and genome

editing allow the ﬁeld of genomics to progress

 U.S. Food & Drug Administration. “What is Gene Therapy.” www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/what-gene-

therapy. Accessed  May .

 Green, Eric D., et al. “Perspective: Strategic Vision for Improving Human Health at the Forefront of Genomics.” Nature, vol. ,  Oct. .

from a largely observational (‘reading DNA’)

to more experimental (‘writing’ and ‘editing’

DNA) approaches. Enabling true synthetic

genomics (that is the synthesis modiﬁcation and

perturbation of nucleic acid sequences at any

scale) will allow for more powerful experimental

testing of hypothesis about genome variation

and function and improve opportunities for

linking genotype to phenotypes. Genome

editing is increasingly being used for practical

applications in medicine such as in gene

therapy, biotechnology and agriculture.

130

There are a variety of types

of gene therapy products,

including:

• Plasmid DNA: Circular DNA molecules can be

genetically engineered to carry therapeutic

genes into human cells.

• Viral vectors: Viruses have a natural ability to

deliver genetic material into cells, and therefore

some gene therapy products are derived from vi-

ruses. Once viruses have been modiﬁed to remove

their ability to cause infectious disease, these

modiﬁed viruses can be used as vectors (vehicles)

to carry therapeutic genes into human cells.

• Bacterial vectors: Bacteria can be modiﬁed to

prevent them from causing infectious disease

and then used as vectors (vehicles) to carry ther-

apeutic genes into human tissues.

• Human gene editing technology: The goals of

gene editing are to disrupt harmful genes or to

repair mutated genes.

• Patient-derived cellular gene therapy prod-

ucts: Cells are removed from the patient, genet-

ically modiﬁed (often using a viral vector) and

then returned to the patient.

U.S. Food & Drug Administration. “What is Gene Therapy.”

www.fda.gov/vaccines-blood-biologics/cellular-gene-thera-

py-products/what-gene-therapy. Accessed 12 May 2021.

For research, the key advantage of modern gene

editing is the ability to precisely change a gene to

experimentally examine the effect of the change.

Modern technology using CRISPR-Cas9 provides

a highly reﬁned way to silence genes and insert

genes, and even modify a single letter in the ge-

nome. In describing it, Nessa Carey highlights that:

A breakthrough in 2012 ripped open the

genetic fabric of every organism on this

planet, from humans to ants and from rice

to butterﬂies. It’s giving every biologist in the

world the tools to answer in a few months

questions that some scientists have spent

half their careers trying to address.

131

As a result of both technological and scientiﬁc

advancement, the application of gene editing has

progressed from the benchtop, through animal

models, and onwards into human clinical trials and

approved clinical therapeutics. Gene editing is still

in its early days in terms of clinical use, with issues

remaining to be resolved in terms of risk of unintend-

ed off-target changes that may happen along with

intended changes. More work needs to be done before

the full promise of this technology can be realized,

but emerging application areas point to gene editing

and gene therapies’ potential to become import-

ant additional clinical tools for addressing genetic

diseases and disorders. Collins, Doudna, Lander,

and Rotimi capture this optimism, writing that:

After years of ups and downs, some dramatic

successes of gene therapy are emerging, such

as for spinal muscular atrophy and hemophilia.

The pace of this research could increase

dramatically in the future; precisely targeted

genome editing technologies (e.g., CRSPR-Cas9)

now provide new avenues to therapeutics…

as these technologies continue to mature,

it will become increasingly possible to alter

cellular genomes efﬁciently and accurately.

132

 Carey, Nessa. Hacking the Code of Life. How Gene Editing Will Rewrite our Futures. Icon Books, Ltd., .

 Collins, Francis S., et al. “Perspective: Human Molecular Genetics and Genomics – Important Advances and Exciting Possibilities.” The New

England Journal of Medicine, vol., no. ,  Jan. .

The thousands of rare monogenic diseases and

disorders may particularly lend themselves to gene

therapy approaches. However, the development of

such therapies will, at least early on, be limited to

those diseases and disorders that meet some fairly

stringent criteria, which are noted by Carey as follows:

There is a whole list of key factors. Can you be

100% certain that patients you have diagnosed

with the condition all have the same disease?

This rules out disorders like schizophrenia where

there are probably many different forms of the

illness. Do you know exactly how the disease

is caused in your patients? This rules out type

2 diabetes where it isn’t clear which is the key

step in the development of the condition. Do you

know what genetic change you need to create?

This rules out multiple sclerosis, where we think

multiple minor genetic variations interact with

the environment to trigger the condition. Can

you be sure that making the speciﬁc edit you

have in mind will prevent or reverse pathology?

This rules out Alzheimer’s disease. Drug trials

A Key Consideration

It should be noted that the discussion of gene edit-

ing and gene therapy pertains to changing non-he-

reditable (somatic) genes—that is changes to an

individual’s genes that will impact the individual but

not then be passed to any children they may subse-

quently have.

There is also ongoing discussion and public debate

about the potential use of gene editing for making

heritable genetic changes (changes to the germ-

line). Such genome edits would result in changes to

an individual’s DNA being passed to their progeny

and subsequent generations. At the present time,

the general consensus of leading organizations in

medical genetics, genetics research, and genetic

counseling is that genome editing that culminates

in human pregnancy should not be currently un-

dertaken and that further research is required into

the scientiﬁc, clinical, and ethical implications of

germline editing.

targeting what we thought was the key pathway

failed spectacularly recently, and the companies

involved have probably lost billions of dollars as

a consequence. Can you get the gene editing

reagents to the tissues where they are most

needed, in high enough levels? This probably

excludes Parkinson’s disease as the brain is

quite a difﬁcult tissue to access. … Many of the

most common and debilitating conditions aren’t

likely to be good candidates for gene editing

anytime soon, because they are too challenging

in one or more of these problem areas.

133

Even with the above challenges, biomedical research-

ers and clinicians have identiﬁed many diseases and

disorders that meet the criteria. Signiﬁcant prog-

ress has been made in advancing gene therapies

through clinical trials, with examples including:

• Metachromatic leukodystrophy (MLD)—a rare

storage disorder caused by mutations in the

gene coding for arylsulfatase A that results in

affected children failing to develop motor skills,

typically leading to their death by age 10.

• Lipoprotein lipase deﬁciency—a rare disor-

der in which “patients as young as two have

extremely high levels of cholesterol and suffer

recurring, life-threatening bouts of pancreati-

tis.”

134

The drug Glybera resulted and is the ﬁrst

approved gene therapy product in clinical use.

• Childhood X-linked adrenoleukodystro-

phy (CCALD)—is a genetically determined

metabolic disorder. Those affected typically

experience “normal development until they

reach 4–10 years of age, at which time behav-

ioral changes including memory impairment

and emotional instability manifest to varying

 Carey, Nessa. Hacking the Code of Life. How Gene Editing Will Rewrite our Futures. Icon Books, Ltd., .

 Reilly, Philip R. Orphan: The Quest to Save Children with Rare Genetic Disorders. Cold Spring Harbor Laboratory Press, .

 Kim, Ji Hyung and Hyon J. Kim. “Childhood X-linked Adrenoleukodystrophy: Clinical-Pathologic Overview and MR Imaging Manifestations at

Initial Evaluation and Follow-up.” RadioGraphics, vol. , no. ,  May .

 National Organization for Rare Disorders. “Rare Disease Database.” www.rarediseases.org/rare-diseases/leber-congenital-amaurosis/. Accessed

 May .

 The American Society of Hematology. “Gene Therapy for Hemophilia B Found Safe and Effective in First Phase III Trial.” American Society of

Hematology,  Dec. , www.hematology.org/newsroom/press-releases//gene-therapy-for-hemophilia-b-found-safe-and-effective-in-

ﬁrst-phase-iii-trial. Accessed  May .

degrees, followed by progressive deterioration

of vision, hearing, and motor function.”

135

• Leber congenital amaurosis (LCA)—is a rare

genetic eye disorder. Affected infants are of-

ten blind at birth, and other symptoms may

include crossed eyes; rapid, involuntary eye

movements; unusual light sensitivity; cataracts;

and/or, keratoconus. In 2017, the gene therapy

Luxturna (voretigene neparvovec-rzyl) was

approved by the FDA to treat children and

adults with two mutations in the RPE65 gene

which includes a type of LCA called LCA2.

136

• Beta-thalassemia—is a rare genetic blood

disorder that reduces the production

of hemoglobin, leading to severe ane-

mia and the need for transfusions.

• Spinal muscular atrophy—is a genetic de-

generative disorder that starts in the central

nervous system and progressively affects all the

muscles in the body. The therapy Spinraza is an

FDA-approved synthetic antisense oligonucle-

otide that binds to RNA, which corrects splicing

errors in the causative genes. Gene therapy with

Zolgensma adds a functional version of the gene.

• Hemophilia B—is a rare genetic bleeding

disorder in which affected individuals have

insufﬁcient levels of a blood protein called factor

IX. “The gene therapy etranacogene dezapar-

vovec substantially increased production of

the blood-clotting protein factor IX among

52 patients in the largest and most inclusive

hemophilia B gene therapy trial to date.”

137

Gene-based therapies are also being successfully

applied in the treatment of selected cancers. An

approach proving successful is CAR-T therapy, which

is an abbreviation for chimeric antigen receptor (CAR)

T-cell therapy. The process is described as follows:

First, T cells, a type of immune cell, are taken

from a person’s blood. Then, in the laboratory,

gene replacement therapy is used to add a new

gene to T cells. This new gene adds a special

receptor, called a chimeric antigen receptor

(CAR), to T cells to make CAR-T cells. CAR-T cells

are able to bind to and attack certain cancer

cells. Large numbers of the CAR-T cells are

made in the laboratory, and once a sufﬁcient

amount has been produced, the cells are put

back into the body to ﬁght certain cancers.

138

At its heart, CAR-T cell therapy uses genet-

ics to change a person’s own immune cells

to recognize and ﬁght cancer cells inside the

body. Currently, there are two FDA approved

CAR-T therapies used in clinical oncology:

• CAR-T Lentiviral vector, ex vivo, used

for acute lymphoblastic leukemia.

 Explore Gene Therapy. “Get to Know the Different Types of Gene-Based Therapies.” AveXis, Inc. www.exploregenetherapy.com/how-gene-

replacement-therapy-is-different. Accessed  Feb. .

 Yong, Ed. I Contain Multitudes: The Microbes Within us and a Grander View of Life. Ecco, .

• CAR-T Retroviral vector, ex vivo, used for re-

lapsed or refractory large B-cell lymphoma.

7. Human-Microbe Interactions

None of us go through life truly alone. Each of us

is host to communities of trillions of microbes,

an amount that is considerably larger than the

total count of human cells in our bodies. Ed Yong

highlights this fact quite effectively in the title of

his book I Contain Multitudes and notes: “how

ubiquitous and vital microbes are: they sculpt our

organs, defend us from disease, break down our

food, educate our immune systems, guide our

behavior, bombard our genomes with their genes,

and grant us incredible abilities.”

139

As Yong’s quote

highlights, there is signiﬁcant biological interaction

between the human genome and microbes.

a. The Human Microbiome

Even though our microbiome has a considerable effect

on our health, for a report focused on human genetics

and genomics it might be asked why one would con-

sider microbes to be within the bounds of this study.

Each microbe has its own unique genome, but this re-

port is focused on the human genome. It is a fair point,

but two very interesting ﬁndings from recent research

into our microbial passengers points to a distinct hu-

man genome effect—with impacts going in two direc-

tions (microbes impacting our genes and gene expres-

sion, and human genotype impacting the make-up of

the microbial communities humans’ host). In effect,

it has been found that humans are, loosely speaking,

genetic symbiotes. It is a difﬁcult subject matter to

research, requiring access to human sequencing and

metagenomic sequencing of the human microbiome,

but the data collected by the Human Microbiome

Project (HMP) can now be referenced to completed

human genome sequences to make important ﬁnd-

ings. Providing a signpost to potentially interesting

genetic interactions is the fact that the gut microbi-

omes of monozygotic (“identical”) twins are found to

be signiﬁcantly more similar than those of dizygotic

(non-identical) twins. The ﬁndings in human twins

conﬁrm ﬁndings in mouse models that show that

the host (the mouse) genome inﬂuences microbiota

composition and that host genotype explains a signif-

icant proportion of variation in the gut microbiome.

140

Additional research on whole genome sequencing and

microbiome metagenome sequencing of participants

in the HMP are compelling, showing that “most mi-

crobes are correlated to genetic principal components,

especially in stool, but also in oral samples.”

141

The au-

thors note that they “identiﬁed associations between

high level genetic features and various microbiome

features; however, the mechanistic forces of those

associations remain unclear.”

142

It is a very interesting,

albeit nascent area of human genomics research, but

given the sheer complexity of microbiota and the im-

pact on health of human microbiomes, interesting and

clinically relevant future ﬁndings are to be anticipated.

 Benson, Andrew K., et al. “Individuality in Gut Microbiota Composition is a Complex Polygenic Trait Shaped by Multiple Environmental and Host

Genetic Factors.” Proceedings of the National Academy of Sciences, vol. , no. , Oct. . doi:./pnas..

 Kolde, Raivo, et al. “Host Genetic Variation and its Microbiome Interactions within the Human Microbiome Project.” Genome Medicine, vol. ,

no. ,  Jan. . doi: ./s---.

 Ibid.

b. Infectious Diseases

While many microbes serve important positive life

functions for humans, for example aiding digestion

and the breakdown of micronutrients, many are

pathogenic—the viruses and bacteria that cause

infectious diseases. For 2020 and into 2021, COVID-19

has been very much on the minds of all. Clearly,

understanding the genetic structure of the SARS-

CoV-2 virus has been highly important in the global

mission to control the pandemic, and genetics and

genomics as disciplines have been on the front-

lines contributing to many areas (see sidebar).

In terms of advancing understanding of the effect of

the human genome on infectious disease response

and susceptibility, it has been serendipitous that the

Genomics in the

COVID-19 Pandemic

“Genomics rapidly assumed crucial roles in COVID-19

research and clinical care in areas such as: (1) the

deployment of DNA and RNA sequencing technol-

ogies for diagnostics, tracking of viral isolates, and

environmental monitoring; (2) the use of synthetic

nucleic acid technologies for studying SARS-CoV-2

virulence and facilitating vaccine development;

(3) examination of how human genomic variation

inﬂuences infectivity, disease severity, vaccine efﬁ-

cacy, and treatment response; (4) the adherence to

principles and values related to open science, data

sharing, and consortia based collaborations; and (5)

the provision of genomic data science tools to study

COVID-19 pathophysiology. The growing adoption of

genomic approaches and technologies into myriad

aspects of the global response to the COVID-19 pan-

demic serves as another important and highly visible

example of the integral and vital nature of genomics

in modern research and medicine.”

Eric D. Green, et al. “Perspective: Strategic Vision for Improv-

ing Human Health at the Forefront of Genomics.” Nature,

vol. 586, 29 Oct. 2020.

pandemic hit at a time when widespread human

genetic sequencing is relatively inexpensive. While se-

quencing the virus itself is not “human” genomics, the

discipline has been contributing important research

that may inﬂuence future approaches to diagnosis and

treatment of infectious disease. The COVID-19 Host

Genetics Initiative, for example, has brought together

multiple stakeholders in the human genetics’ commu-

nity to “generate, share, and analyze data to learn the

genetic determinants of COVID-19 susceptibility, sever-

ity, and outcomes.”

143

The Initiative formed to help ad-

vance research that could lead to potential discoveries

that “could help to generate hypotheses for drug re-

purposing, identify individuals at unusually high or low

risk, and contribute to global knowledge of the biology

of SARS-CoV-2 infection and disease.”

144

Worldwide

engagement in the Initiative has been considerable,

with participation of “over 2000 scientists from over

54 countries working collaboratively to share data,

ideas, recruit patients and disseminate ﬁndings.”

145

Another example is the COVID Human Genetic

Effort, which is an international consortium aiming

to “discover the human genetic and immunological

bases of the various clinical forms of SARS-CoV-2

infection.”

146

In particular, the COVID Human

Genetic Effort is directing work to search for:

• “Monogenic or digenic inborn errors of im-

munity (IEI), rare or common, underlying

severe forms of COVID-19 in previously healthy

individuals, including severe pneumonia,

multisystem inﬂammatory syndrome in chil-

dren (MIS-C), Long COVID, COVID Toes, etc.

• Phenocopies of these monogenic IEI, such

as auto-antibodies neutralizing gene prod-

ucts of loci whose variants underlie these

IEI (e.g., auto-antibodies to type I IFNs

mimicking inborn errors of type I IFNs).

 COVID- Host Genetics Initiative. “About.” www.covidhg.org/about/. Accessed  May .

 Ibid.

 Ibid.

 COVID Human Genetic Effort. “Our Mission.” www.covidhge.com/. Accessed  May .

 Ibid.

 Supriya, Lakshmi, Ph. D. “Study Finds Protective Genetic Associations with Mild COVID-.” News Medical,  Jan. , Life Sciences sec.

 Ibid.

• Single-gene variants, rare or common, which

make certain individuals resistant to the infec-

tion by the SARS-CoV2 itself, despite repeated

exposure, or resistant to the development of

clinical manifestations despite infection.”

147

Multiple U.S. research centers and labs are

active participants in both of the above

referenced international consortia.

Some interesting research contributions have

also been made as a result of the growth of di-

rect-to-consumer genetic testing, where the service

of AncestryDNA has built a deep repository of DNA

information for its participants. There have been

separate genome-wide association studies (GWAS),

performed in hospitals with COVID-19 patients that

indicated hereditary genetic associations with higher

levels of disease impact and infection. However, as

noted in a news article by Lakshmi Supriya,

148

these

studies have the inherent bias of examining those who

are infected, typically with a more severe case (since

they are hospitalized). AncestryDNA took a different

approach. Recognizing that their deep resource of

customer DNA may contain clues to COVID-19 ge-

netic protection or susceptibility associations, they

surveyed their customers to capture self-reported

information on “exposure, risk factors, symptoms and

demographics, most of whom had mild disease.”

149

With a large sample of over 700,000 respondents, the

AncestryDNA research team had a deep resource to

work with, ultimately ﬁnding gene associations related

to immunity and others associated with susceptibil-

ity and disease severity—some of which represent

new ﬁndings, and some conﬁrming associations

identiﬁed by other researchers. As Supriya notes, “the

study provides a complementary analysis to stud-

ies focusing on severe disease, which is promising

for ﬁnding new genetic associations, in particular

those that provide protection against the virus.”

150

The degree of susceptibility or immunity to various

infectious disease organisms has shaped the human

genome throughout our evolution as a species.

Historic pandemics, involving large-scale deaths due

to smallpox, plague, or inﬂuenza, for example, have

been “natural selection” events, favoring ongoing

reproduction of genotypes with disease resistance

traits and down selecting genotypes with high

susceptibility to the disease. It is also the case that

some of the protective genotypes may serve to help

an individual resist certain pathogens, but then be

related to negative repercussions also.

151

This has been

found to be the case with sickle cell disease where the

genes that are associated with the disease also appear

to be associated with a positive immunity to Malaria.

Another area of important research at the inter-

face between the human genome and infectious

disease is the affect that infection can have on

the human genome and upon gene regula-

tion and expression. As noted by the National

Institute of General Medical Sciences (NIGMS):

When viruses infect us, they can embed

small chunks of their genetic material in our

DNA. Although infrequent, the incorporation

of this material into the human genome

has been occurring for millions of years.

As a result of this ongoing process, viral

genetic material comprises nearly 10 percent

of the modern human genome.

152

Interestingly, recent research at the University of

Colorado Cancer Center by Sharon Kuss-Duerkop and

Dohun Pyeon ﬁnds that viruses are not just cutting

and pasting code within DNA; they are also engaged

in “suppressing gene expression via DNA methylation,

speciﬁcally by targeting DNA methyltransferases

 Ibid.

 Pittman, Kelly J., et al. “The Legacy of Past Pandemics: Common Human Mutations That Protect against Infectious Disease.” PLOS Pathogens,

vol. , no. ,  July .

 NIH, National Institute of General Medical Sciences (NIGMS). “Our Complicated Relationship with Viruses.” ScienceDaily,  November .

 University of Colorado Anschutz Medical Campus. “Here’s How Viruses Inactivate the Immune System, Causing Cancer.” ScienceDaily,  March

.

 Ibid.

(DNMTs).”

153

They note that “viruses elect to turn off

genes like interferon-b that the immune system

regularly enlist to ﬁght foreign pathogens which

allows them to replicate quickly and run rampant.

This could lead to cancer development.”

154

Human genetics and genomics as a discipline has

much more to discover regarding the complex relation-

ship between the human genome and the pathogenic,

and potentially positive, effects of microbial infections.

8. Metagenomics and

Environmental Genomics

All the above discussion of genetics and genomics

research, clinical application, and impacts will have

hopefully resulted in an appreciation for the incred-

ible complexity of not just the human genome but

the vast network of interfaces between the genome

and other biological and environmental systems.

Each of us walks a slightly different path through

life, experiencing different inﬂuences upon our

physiology in terms of the food we eat, the amount

of sun we expose ourselves to, the environments we

are exposed to in our jobs, the pathogens that we

by chance encounter, etc. Any and all of these and

more may be subtly changing (mutating) letters

in our genome or periodically inﬂuencing gene

regulation or expression. If you want a challenging

career, working on unravelling genome-environment

interactions and effects would have to be high on

the list. There is a speciﬁc area of research inquiry

in genetics and genomics that provides perspective

on the subject—it is termed “metagenomics”

Rob Knight, in considering the future of

human genetics and genomics, notes that:

Genomics is a key underpinning for

metagenomics. This is the case because

reference-based approaches are dramatically

faster and more accurate than reference-free

approaches whenever the reference database

is complete and correct. However, with a few

exceptions (such as bacteria in the human

gut of healthy western adults), we are far from

having adequate reference data. Sequencing

efforts such as the Genomic Encyclopedia of

Bacteria and Archaea (GEBA) projects have

been extremely valuable in ﬁlling in missing

branches of the tree of life, but projects such as

microbial earth which seeks to sequence all type

strains, and 1000 fungal genomes project remain

under-resourced. Building these references and

augmenting them with new clinical isolates and

with isolates from remote human populations

and from a panel of diverse environmental

samples, such as those provided by the Earth

Microbiome Project, could dramatically

accelerate progress in all metagenomic studies,

whether targeted at human or animal health or

at the environment. The beneﬁts that could be

achieved would greatly outweigh the modest

investment required to complete these studies.

155

There are countless research questions that

metagenomics will be used to pursue, and each

will beneﬁt from the speed, accuracy, and afford-

ability of gene sequencing in combination with

ongoing advancement in bioinformatics and

artiﬁcial intelligence-based approaches to the

mining of genomic and metagenomic big data.

 Cheifet, Barbara. “Editorial: Where is genomics going next?” Genome Biology, vol. , no. ,  Jan. . doi:./s---.

 Phillips, Melissa Lee. “Crime Scene Genetics: Transforming Forensic Science through Molecular Technologies.” BioScience, vol. , no. , June

. doi:./B.

9. Non-Medical Applications

of Human Genomics

Each of the functional impact domains of human

genetics and genomics discussed above (domains 1

through 8) have been viewed through the primary

lens of medical science—the application of genetics

and genomics to understanding genomic struc-

tures and mechanisms and their effect on human

health and pathology. There are, however, multiple

other areas of scientiﬁc research and functional

application of human genetics and genomics that

are not principally directed at medical questions.

Three such applications are highlighted brieﬂy

below, focused on: forensic science, anthropology

and evolutionary biology, and paternity testing.

a. Forensic Science

Genetics, and more recently genomics, has become

an essential tool for forensic scientists in criminal

justice systems. In the late 1980s, genetic analysis

entered forensic use through examination of non-cod-

ing region repeats in DNA that are highly variable

among individuals. This became known as DNA

“ﬁngerprinting,” helping to identify crime suspects.

The technology was revolutionary for forensic science

in that, as noted by Melissa Lee Phillips, “for the ﬁrst

time, forensic scientists could create genetic proﬁles

so speciﬁc that the only people who share them are

identical twins.”

156

Phillips notes that “DNA ﬁngerprint

techniques evolved subtly over the next several years,

until the polymerase chain reaction (PCR), developed

by Kary Mullis, was introduced into forensic work. By

Metagenomics. Also known as environmental genomics or community genomics, metagenomics

investigates the communal genome contained within an environmental sample. It enables

the study of the symbiosis and interactions of organismal genomes and genetic products as a

biological system.”

Simon Tripp and Martin Grueber. Economic Impact of the Human Genome Project. Battelle Memorial Institute, May 2011.

allowing the selective ampliﬁcation of any desired

stretch of DNA, PCR ushered in unprecedented sen-

sitivity in low-level DNA detection at crime scenes.”

157

Analysis of DNA provides a pathway to deﬁnitively

identify the individual associated with DNA evidence

at a crime scene, and also may be used to establish

the identity of human remains. Forensic genetics is

an evolving discipline, with new technologies en-

abling varied use in criminal justice applications:

 Ibid.

Forensic genetics is slowly transitioning into

forensic genomics… Genomic, transcriptomic,

and epigenomic principles, data, and

technologies are applied to identify and analyze

useful DNA and RNA markers to address

various forensic questions that cannot be

answered, or only in a limited way, via genetic

or other approaches. Human genome data

produced with SNP microarray technologies,

and increasingly whole exome and whole

genome data established via massively

parallel sequencing (MPS) technologies, are

used to identify DNA markers for individual

identiﬁcation, as well as for appearance and

ancestry prediction. The latter is forensically

relevant for ﬁnding unknown perpetrators of

crime who are unidentiﬁable with standard DNA

proﬁling. Human transcriptome data of various

tissues generated with expression microarray

technologies, and increasingly with whole

transcriptome sequencing via MPS technologies,

are used to identify RNA markers to determine

the cellular source of crime scene sample. This

is forensically relevant for reconstructing the

course of events that may have happened at the

Identifying the

“Golden State Killer”

For decades, police sought to identify the individ-

ual responsible for 12 murders and 45 rapes across

California between 1976 and 1986. The police had

DNA evidence from crime scenes, but the DNA did

not match any individuals in existing criminal DNA

databases, and without a suspect there was no way

to identify the offender.

The recent growth of ancestral DNA databases

provided a pathway to a breakthrough in the case.

Police analyzed one of the databases and were able

to narrow the DNA to a particular family. Standard

investigative procedures were then able to be used

to narrow the family members down to one suspect

The U.S. Department of Justice – resulting in a con-

fession and conviction.

The U.S. Department of Justice

on Advancing Justice Through

DNA Technology

DNA can be used to identify criminals with incredi-

ble accuracy when biological evidence exists. By the

same token, DNA can be used to clear suspects and

exonerate persons mistakenly accused or convicted

of crimes. In all, DNA technology is increasingly vital

to ensuring accuracy and fairness in the criminal

justice system.

For example, in 1999, New York authorities linked

a man through DNA evidence to at least 22 sexual

assaults and robberies that had terrorized the city.

In 2002, authorities in Philadelphia, Pennsylvania,

and Fort Collins, Colorado, used DNA evidence

to link and solve a series of crimes (rapes and a

murder) perpetrated by the same individual. In the

2001 “Green River” killings, DNA evidence provided

a major breakthrough in a series of crimes that had

remained unsolved for years despite a large law en-

forcement task force and a $15 million investigation.

DNA is generally used to solve crimes in one of

two ways. In cases where a suspect is identiﬁed, a

sample of that person’s DNA can be compared to

evidence from the crime scene. The results of this

comparison may help establish whether the sus-

pect committed the crime. In cases where a suspect

has not yet been identiﬁed, biological evidence

from the crime scene can be analyzed and com-

pared to offender proﬁles in DNA databases to help

identify the perpetrator. Crime scene evidence can

also be linked to other crime scenes through the

use of DNA databases.

The United States Department of Justice. “Advancing Justice

Through DNA Technology: Using DNA to Solve Crimes.”

www.justice.gov/archives/ag/advancing-justicethrough- dna-

technology-using-dna-solve-crimes. Updated 7 March 2017.

scene of crime and to support the use of DNA at

the activity level of evidence interpretation.

158

Genetics and genomics are also being used by

researchers in the ﬁeld of criminology to examine

genetic correlates to offenders, drawing upon ad-

vancements in understanding genetic factors that

inﬂuence human behavior. An example of this is the

work of Eric Connolly and Kevin Beaver that incorpo-

rated behavioral genetic methods to “assess gene-en-

vironment interplay between anger, family conﬂict,

and violence using a subsample of kinship pairs

drawn from the Child and Young Adult Supplement

of the National Longitudinal Survey of Youth.”

159

Their

analysis reveals “a signiﬁcant shared genetic liability

for anger and exposure to family conﬂict indicating

gene-environment correlation” and they conclude

that ﬁndings from the study “underscore the impor-

tance of using genetically informed methodologies

to identify underlying risk factors involved in both

exposure and response to different forms of strain.”

160

b. Anthropology and Evolutionary Biology

Our DNA codes for us as individuals in the present,

but it is also a molecular historical record of our

ancestry—providing coded documentation of our

lineage (ancestry) and our evolution as a species.

Advancements in human genetics and genomics

have provided important scientiﬁc capabilities that

 Kayser, Manfred and Walther Parson (Editors). “Special Issue: Forensic Genomics.” Gene, .

 Connolly, Eric and Kevin Beaver. “Assessing the Salience of Gene–Environment Interplay in the Development of Anger, Family Conﬂict, and

Fhysical Violence: A Biosocial Test of General Strain Theory.” Journal of Criminal Justice, vol. , no. , November–December .

 Ibid.

 FridovichKeil, Judith. “Human Genome Project.” Encyclopedia Britannica Scientiﬁc Project.

 andMe. “Your DNA is Amazing!” www.andme.com/about. Accessed  May .

have enabled researchers in evolutionary biology,

physical anthropology, archaeology, and associated

disciplines to answer many questions regarding

our evolutionary biology, our genetic linkages to

other species, our population migrations, and our

genealogy. Modern genetics and genomics have,

for example, enabled substantial advancement in

anthropology such that Judith FridovichKeil writes:

“comparative DNA sequence analyses of samples

representing distinct modern populations of humans

have revolutionized the ﬁeld of anthropology.”

161

While genetics and genomics are proving funda-

mental to advancements in the above-cited aca-

demic research disciplines, they have also enabled

the development of commercial services that offer

genetic ancestry testing (genetic genealogy) to the

general population—providing insights regarding

ancestry that supplement traditional methods of

review of family records and historical documentation.

Interest levels have been high, to the extent that two

private companies 23andMe and Ancestry now have

among the largest repositories of human genetic

data in the world. 23andMe, for example, reports

that it has “more than 12,000,000 customers.”

162

Consumer interest in these services has created a

rather rich resource of genetic data that is being

used now to advance research, with 23andMe, for

Information about the relationships amongst species or populations within species and the time

of their divergence from each other can be found in the DNA. It is the job of the evolutionary

geneticist to interpret this information from DNA. A subset of anthropology—anthropological

genetics—uses the evolutionary geneticist’s tool kit to infer human evolutionary history from our

and our closest relative’s DNA.”

Jason Hodgson & Todd Disotell. “Anthropological Genetics: Inferring the History of Our Species Through the Analysis of

DNA.” Evolution: Education and Outreach, vol. 3, Sept. 2010.

example, noting that it has published more than

150 peer-reviewed studies in scientiﬁc journals.

163

c. Paternity testing

While connecting a baby to his or her mother is rather

easily accomplished, by the obvious nature of birth—

the question of paternity is less obvious. Before genet-

ic tests were available, blood tests and other methods

were deployed, but they were less than fully conclu-

sive. Today, however, as noted by the Cleveland Clinic:

A DNA paternity test is nearly 100% accurate at

determining whether a man is another person’s

biological father. DNA tests can use cheek

swabs or blood tests. You must have the test

done in a medical setting if you need results

for legal reasons. Prenatal paternity tests can

determine fatherhood during pregnancy.

164

Determining paternity may be performed simply to

inform a father and parenting decisions, but it may

also be required as part of a legal process—providing a

determinative path to legal rights in child support cas-

es and child custody cases, and also for determining

 Ibid.

 The Cleveland Clinic. “DNA Paternity Test.” https://my.clevelandclinic.org/health/diagnostics/ -dna-paternity-test. Accessed  May .

legal rights to Social Security beneﬁts and inheritance.

Some applications of paternity testing could also

be listed under the previous discussion of medical

applications of human genomics because there

is utility in establishing paternity for identiﬁcation

of links to genetic conditions and for determining

potential compatibility for organ or tissue donation.

D. Summary

Whether for medical or non-medical applications,

it is clear that human genetics and genomics

advancements provide extremely large-scale ben-

eﬁts across a broad variety of functional impact

domains. Genetics and genomics are considered

fundamental within modern biological science,

providing answers to basic biological research

questions, and they underpin a diverse range

of applied innovations and applications that are

greatly enhancing human health and well-being.

Since the authors ﬁrst wrote the impact study for

the Human Genome Project on its 10th anniver-

sary, genetics and genomics technologies, and

the cost-effectiveness of their application, have

advanced astonishingly quickly. The literature of

fundamental and applied research discoveries

in genetics and genomics has expanded equally

rapidly, and the application of human genetics

and genomics is evident in almost every branch of

human medicine and modern biological science.

While the accomplishments of genetics and ge-

nomics scientists have been many and varied, with

key categories of application highlighted herein, an

overused analogy still applies. We are probably just

looking at the “tip of the iceberg” in terms of the

future of human genomics. There are still multiple

large outstanding areas to pursue, including:

• Understanding of the full structure of

the human genome and the biologi-

cal activity it produces or inﬂuences.

• Developing additional knowledge regarding

the functional relationships between genotype

and phenotype and the inﬂuence that environ-

mental interactions have on gene expression,

regulation, and mutation over lifespans.

• Advancing knowledge of gene-disease

relationships, especially (but not exclu-

sively) in regard to common complex,

polygenic diseases and disorders.

• Overcoming the current skewing of genomic

data towards northern European genotypes by

supporting the concerted effort to build more

diversity of data across humanity worldwide.

This is an important effort to help ensure health

disparities are better understood and addressed,

and an equitable future secured in the appli-

cation of genetic medicine advancements.

• There is signiﬁcant need to translate the research

and innovation advancements already being

made into much more widespread clinical appli-

cation, and a distinct need to connect patient ge-

nome data to medical records and family history.

Generating predictions for the future of ﬁelds of

science, technology, and their application is no

easy task, especially in areas as large and diverse

as those driven by human genetics and genomics.

The frontiers of genetics knowledge are constantly

expanding, and it is impossible to predict in advance

the breakthroughs that may occur that will open-up

new pathways to discovery, innovation, and applica-

tion. CRISPR is a recent example that quite suddenly

IV. Into the Future

The primary purpose of this report is to provide a current overview, or

point-in-time snapshot, of the economic impact of human genetics

and genomics in the U.S., and to provide a useful overview of the

principal application domains of human genetics and genomics that are

generating positive advancements in human health and well-being.

and unexpectedly is making available to scientists an

exquisitely precise and ﬂexible tool for gene editing

that is greatly accelerating progress in both research

inquiry and practical application. Similarly, the con-

tinued convergence of genetics and genomics with

the rapidly advancing ﬁeld of advanced analytics and

artiﬁcial intelligence promises a dynamic future.

Researchers have regularly unveiled increasing

complexity in human genome functionality and

its interactions with other biological systems, and

that tendency makes it somewhat challenging

to fully predict future status. That said, there are

certain observable trends—in sequencing speed,

in emerging areas of inquiry, in expanding clinical

applications—that point to near-term directionality

with some degree of conﬁdence. Several anticipated

future areas of advancement are highlighted below.

A. Ongoing Fundamental

Discovery

The population of fully sequenced human genomes

already encompasses millions of individuals, and

further rapid expansion of this universe is to be an-

ticipated. As this report highlights, there are many

large-scale sequencing projects presently being

conducted around the world. As these datasets are

built, they increase opportunities to identify inter-

esting variation across human genomes enabling

fundamental questions to be pursued with higher

resolution regarding gene functions and the impact of

genetic variation on diseases and disorders (many of

which are particularly endemic in certain geographic

regions and associated regional population subtypes).

One of the key advances to be anticipated is devel-

opment of an enhanced understanding of genomic

variation among diverse population groups spread

across the world. The limitations imposed by current

data being skewed to genotypes associated with

European ancestry will be overcome as sequencing

programs in Africa (where the most genetically

diverse population is located) and Asia, for example,

expand signiﬁcantly. It may be anticipated that more

diversity in the data will reveal interesting ﬁndings,

as was the case in genes for sickle cell disease being

associated with protection against malaria. More

diversity in sequenced populations will also be im-

portant for further advancing precision medicine,

likely unveiling many more mutations associated

with drug efﬁcacy and adverse drug reactions.

Computational data sciences are also progressing

rapidly, with signiﬁcant progress being made in

advancing automated analysis tools rooted in artiﬁcial

intelligence advancements. It is likely that computa-

tional and analytical sciences will be as important as

biological sciences in contributing to a rich discovery

environment. A challenge area that will need to be

addressed, given the importance of data analytics, is

data access and data interoperability. The ability to

analyze data and make discoveries can only occur if

scientists have access to data, and there is still much

that needs to be done to provide access to health

records and other non-genomic data that can be

matched to genomic data for analysis. There are

also issues in terms of data needing to be format-

ted and archived in ways that facilitate analysis.

It should also be anticipated that signiﬁcant ad-

vancements in fundamental knowledge will be

advanced though studies at a single-cell resolution,

assisted by recent advancements in technology

and techniques. As noted by Olivier Harismendy:

DNA sequencing at deep coverage or at

single-cell resolution is revealing a vast genetic

heterogeneity of normal or dysplastic tissues.

At present these insights are mostly at the

stage of observations, but future studies will

address the consequences of such heterogeneity

in tissue homeostasis and function. The new

information that is provided will provide a better

understanding of diseases and conditions

 Cheifet, Barbara. “Editorial: Where is genomics going next?” Genome Biology, vol. , no. ,  Jan. . doi:./s---.

 Ibid.

associated with aging, genotoxic injuries, and

the accumulation of such mosaic mutations.

165

This is also echoed by Jernej Ule, noting that “we

will be able to move beyond the static picture of

genomic data towards studies of the dynamic

transitions that cells make on a genomic scale

in response to external and internal cues.”

166

It should also be anticipated that fundamental and ap-

plied research in genetics and genomics will increas-

ingly uncover linkages not just between gene varia-

tions and disease but also gene variations and health.

Some institutions are already focusing on this oppor-

tunity. For example, the Institute for Systems Biology

(ISB) in Seattle is a proponent of medicine that can be

predictive, preventive, personalized, and participatory

(termed P4 medicine), and is working on quantifying

wellness—integrating genomics as a component in

helping individuals improve their health, longevity, and

quality of life. As Lee Hood, the cofounder of ISB notes:

Systems biology will revolutionize the practice

of health care in the coming decades. Today,

medicine is largely reactive. It waits until a

person is sick and then treats a disease with

One of the biggest challenges is most health care systems are not built to prevent adverse

events, but mostly to treat adverse events. Another is the lack of a centralized, organized health

care system designed to support life-long results such as genomic testing. For example, we can

conduct a preemptive screen for pharmacogenetic tests in a single test, and these results are

more likely to be applicable as the patient grows older and is exposed to more high-risk drugs. But

we don’t have a good system for making these results available when needed. There is no uniform

electronic health record. At any one time, patients may have multiple prescribers and pharmacies

with little to no coordination, much less with common access to genetic test results that can

inform prescribing and capitalize on the availability of clinical decision support. The lack of logical

prescribing based on laboratory tests is just one small example of the disconnectedness and lack

of computationally informed medicine that impacts all levels of our healthcare.”

Mary Relling. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics

Magazine, vol. 6, no. 2, March-April 2019.

varying levels of success. The revolution will

emerge from the convergence of systems

biology and the digital revolution’s ability to

create consumer devices, generate and analyze

“big data” sets and deploy this information

through business and social networks. By

providing an understanding of disease at

the molecular level, systems medicine will

eventually be able to predict when an organ will

become diseased or when a perturbation in a

biological network could progress to disease.

167

B. Expanding the Clinical

Application of Genomics

It is safe to predict that the application of genetics

and genomics in clinical medicine will continue

to expand substantially. Currently, there is a large

observable difference between genetics and ge-

nomics having ubiquitous use in biological research

versus a far less uniform application of discoveries

and advancements into actual clinical practice.

In the U.S., a key challenge is imposed by the hetero-

geneous structure of the nation’s healthcare system.

Rather than a single system, the U.S. comprises a

patchwork quilt of individual health systems, to-

gether with intermediate insurance organizations

and third-party payers, that inﬂuence the adoption

 Institute for Systems Biology. “Scientiﬁc Wellness.” https://isbscience.org/research/ scientiﬁcwellness/. Accessed  May .

 National Academies of Sciences, Engineering, and Medicine. Implementing and Evaluating Genomic Screening Programs in Health Care

Systems: Proceedings of a Workshop. Washington, DC: The National Academies Press, . doi:./.

of established genomics tools and practice ad-

vancements. In some locations (for example, central

Pennsylvania within the Geisinger health system),

genomics is becoming integral to the management of

the healthcare of covered patient populations; how-

ever, this is far from the norm. There is a long way to

go before all patients across the nation have access to

state-of-the-art genomics and the personalized med-

icine and the improved outcomes they enable. The dis-

connected nature of the U.S. health system structure

also hampers effective cascade screening since pa-

tients move and their records do not follow-them, and

family members may reside in different health systems

across the nation. As the National Academies note

“the beneﬁts of screening will be multiplied if systems

for affective cascade screening can be implemented,

but there is currently no roadmap for such testing.”

168

It should also be anticipated that new classes of

medicines, developed through synthetic biology

and gene editing, will expand in clinical use. At the

present time, gene therapies and gene editing see

limited clinical application. However, the degree of

editing precision provided by CRISPR technology will

lead to more widespread therapeutic applications

developed using gene editing procedures, which

themselves cause editing within the patient’s genome.

Now that the sequencing technology has advanced to the point where delivering high quality,

cheap, and rapid genomes is a commodity – and where robust, reproducible, and accessible

methods exist for analysis and interpretation of these datasets – it is clear that the largest hurdle

relates to the integration of these types of methods into clinical practice. Tools, methods, and

processes need to be developed in order to deliver this information in ways that care providers can

digest it and use it for the treatment of their patients.”

Liz Worthy. “Luminaries Share Their Thoughts on Advances in ‘Omics Over the Past Five Years.” Clinical Omics Maga-

zine, vol. 6, no. 2, March-April 2019.

C. Educating and

Updating Providers

Part of the widespread clinical adoption challenge

with genomic medicine relates to the education of

medical professionals. Genetics and genomics are

complex and fast-moving ﬁelds, rendering it difﬁcult to

keep physicians up-to-speed in the latest ﬁndings and

clinical practice implications and recommendations.

It remains to be seen what model for the practice of

genomic medicine will predominate. For example:

• There may be development and adoption of

computational clinical decision support tools

that assist primary care and other physicians in

interpreting the results of genetic and genomic

tests and guide clinical decision making.

• Physicians may simply be expected to adapt and

to educate themselves regarding genomics simi-

lar to how they have to access information on new

drugs and new practice procedures. Education

here would occur via continuing professional

education courses, through visits by company

representatives, and other traditional pathways.

• Genetics and genomics counselors may become

increasingly embedded in large clinical prac-

tices as a localized resource, working to keep

pace with expanding genetics and genomics

advancements and to provide consultation

with physicians and other clinical providers.

Because the ﬁeld is moving quite fast, there will be a

need to not only relay new discoveries and advance-

ments to clinicians, but also to revise their knowledge

since it is likely that reinterpretation of variant results

will occur under evolving evidence and study.

More widespread use of testing for predisposition

for disease, and the growth in polygenic risk score

systems and other tools, will require physicians to

become comfortable in working with patients to in-

terpret results and develop preventive care regimens.

 Center for Genetics and Society. “Other Countries.” www.geneticsandsociety.org/topics/other-countries. Accessed  May .

D. Ethical Considerations

Particularly in biological sciences, the frontiers of sci-

ence may raise ethical considerations. Such is certainly

the case in human genetics and genomics where

abilities to edit the genome, up to and including

hereditary germline DNA, present challenges requir-

ing ethical debate. Should we edit carrier genomes to

prevent passing down of genetic disease to progeny,

and if so, which diseases should qualify? Some dis-

eases are relatively easily managed with medicines,

while some have no treatments at all. Should we

reserve gene editing as a last resort for these cur-

rently intractable diseases, or should it only be used

in diseases that dramatically shorten lives, involve

great pain in those afﬂicted, or impose large-scale

economic burdens on society? We will not presume to

guess how such issues will be resolved, but it is clear

that they are presenting and will require addressing.

Since germline editing impacts our evolution as a

species, it is a particularly contentious issue, and

it needs to be globally addressed. Currently, more

than 40 countries ban germline editing, but there

are 195 countries in the world.

169

Somatic gene

editing holds signiﬁcant promise for helping peo-

ple who are sick and presents less of an ethical

challenge (although there are still issues relating

to the potential for unforeseen consequences

in editing a not fully understood genome).

The widespread collection of individual genetic

data also presents privacy issues and potential for

genetic discrimination (for example, the risk of a

person being treated differently by their employer or

insurance company because they have a gene vari-

ant that causes or increases the risk of an inherited

disorder). The NHGRI sought to identify potential

ethical and legal issues pertaining to human genet-

ics as a component of the original Human Genome

Project, establishing the Ethical, Legal, and Social

Implications of Human Genetics Research (ELSI)

program to “examine these issues and assist in

the development of policy recommendations and

guidelines to ensure that genetic information is used

appropriately.”

170

The ELSI program continues to study

and address these issues, and NHGRI notes that:

As the ELSI program has evolved, four high pri-

ority areas have emerged from its work that

serve to categorize domains of ethical, legal,

public policy, and societal education that will

need to be further addressed. These include:

1. Privacy and Fairness in the Use and

Interpretation of Genetic Information

• Privacy

• Discrimination/Stigmatization

• Philosophical/Conceptual Assumptions

• Public Policy Issues

2. Clinical Integration of Genetic Technologies

• Clinical Ethical Issues

• Genetic Testing/Counseling

• Professional Issues and Standards

3. Issues Surrounding Genetics Research

• Informed Consent

• Other Philosophical and Ethical Issues

• Legal Issues

• Ethnocultural Issues

• Other

4. Education

• Professional-Health

• Professional-Other

• Public-K through 12

• Public-College

• Public-Consumer

• Combination Professional/Public.

Equitable access to the beneﬁts of modern human

genetics and genomics advancements also rep-

resents a challenge to be addressed. As noted in

this report, there are concerted efforts underway

to increase the diversity of sequencing human

 National Human Genome Research Institute. “Review of the Ethical, Legal and Social Implications Research Program and Related Activities

(-).” www.genome.gov/ /elsi-program-review-#:~:text=The%original%issues% identiﬁed %

in,impact%of%genetic%information%on. Accessed  May .

 ASHG Survey Finds Americans Strongly Support Human Genetics Research. Research!America and American Society of Human Genetics, 

Jan. .

sub-populations with multiple large-scale genome

sequencing projects taking place in areas of the globe

whose populations have been underrepresented

in current genomic data. Increasing diversity in the

data is important to advancing equitable research

and, ultimately, for equity in the clinical applica-

tions of genetic and genomic medical innovations

that can beneﬁt the full spectrum of humanity.

E. Conclusion

What is absolutely clear is that human genetics

and genomics will be in the vanguard in terms of

contributing to advancements in medical science

and enhancing the practice of clinical medicine.

Expanding understanding of the human genome,

variations in genomes, external factors that interface

with the genome, and genetic relationships to health

and disease will provide improved health, quality of

life, and large-scale beneﬁts to society (both economic

and social). Indeed, as this report ﬁnds, it already has.

It is heartening to note that a survey of the general

public in the U.S. found that people generally share

an optimistic view of genetics and genomics and

the promise it holds for a better future. A study re-

leased by the American Society of Human Genetics

in partnership with Research!America found that

the “large majority of Americans agree that genetic

knowledge will be important to their own health

and their families’ health.”

171

The study also found

that “a strong majority of Americans (77%) indicate

positive feelings about human genetic research”.

Figure 6 summarizes other topline survey ﬁndings.

Based on the economic and functional impacts

of human genetics and genomics detailed herein,

the public is right to feel optimistic about human

genetics research. The ﬁelds of human genetics

and genomics are having profound positive impacts

both in terms of biomedical discovery as well as

within the clinical practice of medicine—working

to improve outcomes for millions of patients and

demonstrating great promise for future highly

positive contributions to human health and well-be-

ing worldwide. While generating these positive

functional impacts is the raison d’etre for pursuing

the advancement of human genetics and genomics,

the ﬁelds have also had the very positive spillover

effect of building a powerful science- and technol-

ogy-based economic sector for the U.S.—a sector

that supports 850,263 jobs across the nation and

generates $265.4 billion in economic output. Human

genetics and genomics innovation is expanding

the stock of knowledge upon which the nation’s

continued advancement depends and shows great

promise to continue to do so long into the future.

Figure 6: U.S. Adults Attitudes Regarding Human Genetics Research – Survey Findings

Source: American Society of Human Genetics and Research!America . “ASHG Survey Finds Americans Strongly Support Human Genetics Research.”

Glossary of Terms

Term Deﬁnition

Allele

A variant of a gene inherited from one parent. An allele’s frequency in a population

can change due to four forces: mutation, natural selection, random genetic drift,

and gene ﬂow.

Biomarker

Any substance, structure, or process that can be measured in the body or its

products that inﬂuence or predict the incidence of outcome or disease

Cancer Genomics

The study of the DNA sequence and gene expression in tumor cells as they compare

to normal host cells.

Clinical

The observation and treatment of actual patients rather than theoretical or

laboratory studies.

DNA

Deoxyribonucleic acid, the molecule that carries genetic instructions in all living

things. The DNA molecule consists of two strands that wind around one another

to form a double helix. Each strand has a backbone made of alternating sugar

(deoxyribose) and phosphate groups. Attached to each sugar is one of four bases:

adenine (A), cytosine (C), guanine (G), and thymine (T). The sequence of the bases

along the backbones serves as instructions for assembling protein and RNA

molecules.

Functional Genomics The study of how elements in the genome contribute to biological processes.

Gene

The basic physical and functional unit of heredity. Technically a distinct sequence

of nucleotides forming part of a chromosome, the order of which determines the

order of monomers in a polypeptide or nucleic acid molecule which a cell (or virus)

may synthesize.

Genotype The genetic constitution of an individual organism.

Germline Cells

Germline cells pass on their genetic material to the progeny. These include sperm

and egg cells.

Microbiome

The collective genomes of the microbes (composed of bacteria, bacteriophage,

fungi, protozoa, and viruses) that live inside and on the human body

Mosaicism

Mosaicism is when a person has two or more genetically different sets of cells in his

or her body

Pharmacogenomics

The study of the role of the genome, or multiple genes, in predicting drug

metabolism and response.

Term Deﬁnition

Protein

A molecule made up of amino acids. Proteins are needed for the body to function

properly. They are the basis of body structures and of other substances such as

enzymes, cytokines, and antibodies.

Somatic Cells All cells in the body that are not germline cells

Synthetic Biology

An interdisciplinary ﬁeld that involves the application of engineering principles to

biology. It aims at the (re-)design and fabrication of biological components and

systems that do not already exist in the natural world.

Systems Biology

The holistic study of the interactions and behavior of the components of biological

entities, including molecules, cells, organs, and organisms.

Whole Exome

Sequencing (WES)

Identiﬁcation of the sequence of base-pairs in the protein-coding regions of the

genome.

Whole Genome

Sequencing

Identiﬁcation of the sequence of base-pairs across the full genome, including

protein-coding and regulatory regions.

Appendix—

Additional Economic Impact Information

Table 11: Listing of NIH Genetic and Genomic-Related Proposal Review Study Sections

• Behavioral Genetics and Epidemiology Study Section [BGES]

• Cancer Genetics Study Section [CG]

• Gene and Drug Delivery Systems Study Section [GDD]

• Genes, Genomes, and Genetics [F08]

• Genetic Variation and Evolution Study Section [GVE]

• Genetics of Health and Disease Study Section [GHD]

• Genomics, Computational Biology and Technology Study Section [GCAT]

• Molecular Genetics A Study Section [MGA]

• Molecular Genetics B Study Section [MGB]

• Molecular Neurogenetics Study Section [MNG]

• Therapeutic Approaches to Genetic Diseases Study Section [TAG]

Table 12: Economic (Expenditure) Impacts—

Additional Expanded NIH Funding Scenario ($7.018 billion)

Impact Type Employment

Labor

Income

($B)

Value

Added

($B)

Output

($B)

State/

Local Tax

Revenues

($B)

Federal

Tax Reve-

nues ($B)

Direct Effect 181,595 $23.31 $54.78 $112.04 $2.95 $5.48

Indirect Effect 303,139 $25.83 $45.15 $89.86 $3.00 $5.59

Induced Effect 418,167 $23.69 $41.71 $74.18 $3.88 $5.23

Total Effect 902,902 $72.84 $141.64 $276.08 $9.83 $16.31

Multiplier 4.97 3.12 2.59 2.46

Source: TEConomy Partners analysis of Human Genetics and Genomics Input Dataset; IMPLAN  U.S. Impact Model

Table 13: Economic (Expenditure) Impacts—

Additional Use as Tool NIH Funding Scenario ($14.202 billion)

Impact Type Employment

Labor

Income

($B)

Value

Added

($B)

Output

($B)

State/

Local Tax

Revenues

($B)

Federal

Tax Reve-

nues ($B)

Direct Effect 210,493 $26.37 $58.85 $119.23 $3.05 $6.04

Indirect Effect 329,541 $27.72 $48.03 $95.07 $3.16 $5.98

Induced Effect 460,234 $26.07 $45.91 $81.64 $4.27 $5.76

Total Effect 1,000,268 $80.16 $152.78 $295.93 $10.48 $17.78

Multiplier 4.75 3.04 2.60 2.48

Source: TEConomy Partners analysis of Human Genetics and Genomics Input Dataset; IMPLAN  U.S. Impact Model

ASHG and the project authors wish to thank the following organizations

for their generous support of this study.