Genomic Medicine: A Decade of Successes, Challenges, and Opportunities

Abstract

Genomic medicine-an aspirational term 10 years ago-is gaining momentum across the entire clinical continuum from risk assessment in healthy individuals to genome-guided treatment in patients with complex diseases. We review the latest achievements in genome research and their impact on medicine, primarily in the past decade. In most cases, genomic medicine tools remain in the realm of research, but some tools are crossing over into clinical application, where they have the potential to markedly alter the clinical care of patients. In this State of the Art Review, we highlight notable examples including the use of next-generation sequencing in cancer pharmacogenomics, in the diagnosis of rare disorders, and in the tracking of infectious disease outbreaks. We also discuss progress in dissecting the molecular basis of common diseases, the role of the host microbiome, the identification of drug response biomarkers, and the repurposing of drugs. The significant challenges of implementing genomic medicine are examined, along with the innovative solutions being sought. These challenges include the difficulty in establishing clinical validity and utility of tests, how to increase awareness and promote their uptake by clinicians, a changing regulatory and coverage landscape, the need for education, and addressing the ethical aspects of genomics for patients and society. Finally, we consider the future of genomics in medicine and offer a glimpse of the forces shaping genomic medicine, such as fundamental shifts in how we define disease, how medicine is delivered to patients, and how consumers are managing their own health and affecting change.

Full text

GENOMICS
Genomic Medicine: A Decade of Successes, Challenges,
and Opportunities
Jeanette J. McCarthy,
1,2
Howard L. McLeod,
3
Geoffrey S. Ginsburg
1
*
Genomic medicine—an aspirational term 10 years ago—is gaining momentum across the entire clinical continuum
from risk assessment in healthy individuals to genome-guided treatment in patients with complex diseases. We
review the latest achievements in genome research and their impact on medicine, primarily in the past decade.
In most cases, genomic medicine tools remain in the realm of research, but some tools are crossing over into clinical
application, where they have the potential to markedly alter the clinical care of patients. In this State of the Art
Review, we highlight notable examples including the use of next-generation sequencing in cancer pharmaco-
genomics, in the diagnosis of rare disorders, and in the tracking of infectious disease outbreaks. We also discuss
progress in dissecting the molecular basis of common diseases, the role of the host microbiome, the identification
of drug response biomarkers, and the repurposing of drugs. The significant challenges of implementing genomic
medicine are examined, along with the innovative solutions being sought. These challenges include the difficulty in
establishing clinical validity and utility of tests, how to increase awareness and promote their uptake by clinicians, a
changing regulatory and coverage landscape, the need for education, and addressing the ethical aspects of ge-
nomics for patients and society. Finally, we consider the future of genomics in medicine and offer a glimpse of
the forces shaping genomic medicine, such as fundamental shifts in how we define disease, how medicine is
delivered to patients, and how consumers are managing their own health and affecting change.
INTRODUCTION
This year marks the 10th anniversary of the official completion of the
HumanGenomeProject,aprojectthatenabledthesystematicexplo-
ration of the molecular underpinnings of disease and generated expec-
tations of the transformation of medicine. Although the previous
decades were marked by improvements in overall health and longev-
ity, before completion of the Human Genome Project, the tools used
for diagnosis and treatment of disease were often blunt and imprecise.
Most diseases were defined by anatomical location and clinical symp-
toms and treated with one-size-fits-all therapies that failed to account
for the unique biological background of the individual. Despite the
development of rational drug design strategies, therapeutic efficacy
has remained unacceptably low (1).The Human Genome Project laid
the foundation for genomic medicine, offering a means of defining
disease at the molecular level. Along with advances in genotyping
and sequencing technologies, bioinformatics, systems biology, and
computational biology, the fruits of the Human Genome Project
have fueled important biological discoveries at an unprecedented
rate. Today, genomic medicine aims to build on this foundation,
translating these discoveries into clinical practice, with the ultimate
goal of personalized medicine.
This State of the Art Review highlights the latest achievements in
genome research and their impact on medicine, primarily in the past
decade. In some cases, genomic discoveries have led to marked changes
in the clinical care of patients. However, the transition to genomic med-
icine has not been smooth, and many challenges still exist. We explore
these challenges and discuss innovative solutions. Finally, we contem-
plate the future, offering a glimpse of the expected changes in health
care as genomic medicine takes hold.
GENOMIC MEDICINE SUCCESSES
The term “genomic medicine”was virtually absent from our lexicon
before 1995; now, it permeates the medical literature, the press, and
the economy. The Human Genome Project resulted in the launch of
thousands of biotechnology firms globally and the development of
faster and cheaper technologies for querying the genome, which have
fueled discoveries of disease biomarkers and drug targets. The phar-
maceutical industry has adopted genome-enabled drug discovery, and
the market for molecular diagnostics has grown rapidly. There are
now groundbreaking examples of the application of genomics across
the stages of disease, from risk stratification and screening to diagnosis
and prognosis to treatment (Table 1).Forsomediseaseslikebreast
cancer, HIV infection, and chronic hepatitis C virus (HCV) infection,
genome-based tools have been woven into clinical practice and disease
management (Fig. 1), but for most areas of medicine, the uptake of
genomics has been slow.
SEQUENCING TECHNOLOGY: THE DRIVER OF
GENOMIC MEDICINE
Technology has been an enabling force, providing transformative
tools for genomic research including genome-wide association studies
(GWAS) and next-generation sequencing (NGS). In 2005, GWAS
made their debut with the identification of a major susceptibility gene
for a complex trait. Through evaluation of hundreds of common ge-
netic variants, Klein et al. identified mutations in the complement
factor H gene as a genetic cause of age-related macular degeneration
1
Institute for Genome Sciences & Policy, Duke University, Durham, NC 27708, USA.
2
De-
partment of Epidemiology and Biostatistics, UCSF School of Medicine, San Francisco,
CA 94105, USA.
3
Institute for Pharmacogenomics and Individualized Therapy, Univer-
sity of North Carolina, Chapel Hill, NC 27599, USA.
*Corresponding author. E-mail: Geoffrey.ginsburg@duke.edu
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(2). Notwithstanding its limitations, including its restriction to com-
mon variants, incomplete genome coverage, and inherent challenge of
discerning the actual causal genetic variant, GWAS has been a trans-
formative technology, representing a major advance over the one-
gene-at-a-time candidate gene approach used for decades before.
Moreover, GWAS provided an indirect means of querying common
genetic variation across the entire human genome in an unbiased fash-
ion, offering an unprecedented opportunity to uncover new biological
pathways of disease.
From 2001 to 2012, the cost to sequence a human genome
dropped from $100 million to less than $10,000, and these costs con-
tinue to decline (3). Current sequencing machines can read about
250 billion bases in a week compared to only about 5 million in
2000 (4). NGS technology (also known as massively parallel se-
quencing) now allows direct measurement of not just common var-
iants but theoretically all variation in a genome (5). Data from the
1000 Genomes Project have confirmed previous estimates of the
population frequency of germline variants to be about 1 in every
1000 of the 3.2 billion nucleotide positions, giving rise to about
3 million variants in the human genome (6). The effect of genetic
variants in the ~1% of the genome that codes for genes is somewhat
predictable. The challenge lies in figuring out the meaning of var-
iants that occur in the vast remaining noncoding regions of the
genome, the so-called dark matter, whose function is largely unknown.
Consequently, the National Human Genome Research Institute
initiated project ENCODE, the Encyclopedia of DNA Elements,
whose goal is to functionally annotate noncoding regions of the
genome (7). This ongoing initiative will provide new insights into
the organization and regulation of genes throughout the genome,
enhancing the ability to annotate variants of unknown significance.
In the interim, researchers have focused on exome sequencing,
which examines variation in the coding sequence (genes), where
mutations have predictable effects on downstream protein struc-
ture. Individuals typically carry several hundred rare and potentially
deleterious coding region variants (6). For rare, Mendelian disorders,
those controlled by a single gene with a simple pattern of inheritance,
the variants found in as few as one or two affected individuals can
be compared to those found in unaffected individuals to pinpoint
disease-causing mutations. The first successful applications of exome
sequencing came in 2009 with the diagnosis of patients with Freeman-
Sheldon syndrome (8), Miller syndrome (9), and congenital chloride
diarrhea (10). These and other Mendelian disorders, with their rela-
tively simple genetic basis, are amenable to exome sequencing of their
DNA and the DNA of a small number of other affected or unaffected
individuals.
Today, GWAS and NGS are integral tools in basic genomic re-
search, but are increasingly being explored for clinical applications, in-
cluding the clinical diagnosis of rare genetic diseases (11), the selection
of cancer treatments based on molecular characterization of the tumor
(12), and the tracking of infectious disease outbreaks in real time (13).
Elucidating the genetic basis of common diseases has been more
challenging, but research in this area has broadened our understand-
ing of underlying disease mechanisms and has revealed new therapeu-
tic approaches through repurposing of existing drugs for treating
diseases they were not originally intended to treat (14–16).
TUMOR SEQUENCING FOR CANCER PHARMACOGENOMICS
One of the most high-profile disease areas to benefit from NGS is
cancer. All cancers arise as a result of DNA mutations, which con-
fer a growth advantage upon the cells in which they have occurred,
giving rise to tumors. Comparison of the genetic profiles of tumors
and the surrounding normal tissue can reveal the acquired changes
driving growth that may be targets for treatment. Meanwhile, com-
parisons across patients and tumor types are changing how cancers
are classified and treated.
Targeted therapies for cancer
The idea of pairing medicines with specific tumor markers in a tar-
geted fashion to improve efficacy of cancer therapies is not new. In the
mid-1980s, detailed molecular studies of breast tumors led to the dis-
covery of HER-2, a biomarker overexpressed in about 30% of breast
tumors and associated with adverse outcomes (17). HER-2 typing of
primary breast tumors provided clinicians with a new tool that could
be used to guide adjuvant chemotherapy (18). The development of
trastuzumab (Herceptin) in 1998, a humanized monoclonal antibody
targeting HER-2, resulted in widespread adoption of the HER-2 test
Table 1. Examples of genomic tests used in clinical practice.
Susceptibility to common diseases
BRCA1/BRCA2 for breast and ovarian cancer predisposition
Lynch syndrome genetic screening in colorectal cancer families
Human leukocyte antigen (HLA) typing to aid in diagnosis of celiac disease
*NGS for Mendelian disorders and diagnostic dilemmas
*NGS for noninvasive prenatal screening/diagnosis
Preclinical diagnosis and prognosis
Oncotype DX: 21-gene RNA signature for breast tumors; 12-gene RNA
signature for colon tumors
MammaPrint: 70-gene RNA signature for breast tumors
OVA1: 5-protein signature for ovarian mass malignancy
AlloMap: 11-gene (blood RNA) signature for monitoring rejection after
cardiac transplant
Corus CAD: 23-gene (blood RNA) signature for coronary artery disease
Cancer pharmacogenomics
HER-2—trastuzumab
EGFR—gefitinib
KRAS—cetuximab and panitumumab
ALK—crizotinib
BRAF—vemurafenib
Pharmacogenomic dosing
CYP2D9/VKORC1—warfarin
Pharmacogenomic adverse events
HLA-B*5701—abacavir (HIV infection)
HLA-B*1502—carbamazepine (epilepsy, bipolar disorder)
Pharmacogenomic efficacy
CYP2C19—clopidogrel (coronary artery disease, peripheral vascular disease)
IL28B—pegylated interferon/ribavirin (HCV infection)
*NGS, next-generation sequencing.
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(19), now part of the standard workup and management of breast
cancer (20–22) (Fig. 2). During the following decade, other examples
of cancer therapies with companion diagnostics emerged (Table 1).
The introduction of EGFR mutation testing has markedly improved
the efficacy of gefitinib and erlotinib, small-molecule drugs for the
treatment of non–small cell lung cancer that target epidermal growth
factor receptor (EGFR) (23,24). In metastatic colorectal cancer, tu-
mors with mutated KRAS are almost always resistant to treatment with
cetuximab and panitumumab, leading the American Society of Clinical
Oncologists and the U.S. Food and Drug Administration (FDA) to
recommend withholding the drugs in these patients (25,26). With
the introduction of NGS, researchers and clinicians can now make a
comprehensive assessment of tumor markers, increasing the rate of
discovery of new targets, new therapeutic alternatives, and new clinical
management guidelines for cancer treatment. In 2011, two cancer
drugs received accelerated approval by the FDA for use with a com-
panion diagnostic test: crizotinib for the treatment of patients with lo-
cally advanced or metastatic non–small cell lung cancer with its
companion diagnostic designed to detect the EML4-ALK fusion gene
(27) and vemurafenib for the treatment of patients with metastatic or
unresectable melanoma positive for BRAF V600E mutations (28).
More recently, NGS of tumors has identified the existence of the
same mutations in distinct cancer types, prompting the expansion of
indications for some FDA-approved drugs. BRAF V600E mutations
not only are common in melanoma but also have been widely ob-
served in other cancers (29), especially hairy cell leukemia (30), leading
to the expanded use and ultimate demonstration of vemurafenib as a
viable treatment option for refractory hairy cell leukemia (31). Simi-
larly, early studies indicate that crizotinib, targeting EML4-ALK–positive
non–small cell lung cancers, is effective against other types of tumors
containing ALK alterations, such as aggressive forms of pediatric neu-
roblastoma and anaplastic large cell lymphoma (32). As the field pro-
gresses, the way tumors are classified is shifting away from tissue of
origin and toward molecular taxonomy, having a profound impact
on the manner in which treatment decisions are made.
Tumor genome analysis is also being explored in cancer patients to
identify new markers and mechanisms of drug sensitivity or resistance.
By sequencing the tumor of a patient with durable remission of meta-
static bladder cancer after treatment with everolimus, Iyer et al. identi-
fied a loss-of-function mutation in TSC1 as a marker of everolimus
sensitivity (33). Similarly, patients with non–small cell lung cancer
treated with crizotinib are prone to relapse, leading to the development
of next-generation ALK inhibitors to overcome crizotinib resistance.
Genomic alterations in resistant tumors were found to correlate with
response to these newer therapies, providing the rationale for pursuing
targeted combinatorial therapeutics to combat resistance (34).
NGS of tumors is not without its limitations (35). Tissue sampling
is problematic: The limited availability of tissue from a standard
biopsy, the need for fresh (as opposed to preserved) tissue, the inher-
ent heterogeneity within a tumor, the presence of aneuploidy, and the
contamination of tumor samples with surrounding normal tissue all
affect the ability to comprehensively characterize tumor mutations.
Further computational and experimental approaches are required to
distinguish those mutations responsible for cancerous growth (drivers)
from those that are inconsequential (passengers). The International
Cancer Genome Consortium (https://www.icgc.org/icgc) and the Cancer
Genome Atlas (http://cancergenome.nih.gov/) represent international
collaborative efforts to define the spectrum of mutations found in tumors,
mapping the genomic landscape of cancer. These efforts will provide a
foundation from which to develop therapeutic strategies against new tar-
gets, but this process is not trivial and, even when successful, may be short-
lived as therapeutic resistance evolves. Thus, whereas NGS is a promising
new tool, it is not a panacea for cancer genomic medicine.
Circulating tumor markers
Another noteworthy application of NGS is noninvasive cancer detec-
tion, either in the setting of primary diagnosis or in monitoring recur-
rence after treatment. Leary and colleagues have laid the groundwork
for this, demonstrating that chromosomal rearrangements, a hallmark
of cancerous tumors, can be detected in blood samples from cancer
patients using NGS (36). This method is successful at discriminating
samplesfromcancerpatientsfromthose of healthy controls, but the
sensitivity and specificity depend highly on the amount of tumor DNA
present in the sample and the detection limits of the sequencing technol-
ogy (37). This method shows promise for monitoring tumor burden to
determine response to treatment, providing an alternative to serial radio-
graphic imaging, which often fails to detect changes in tumor burden. In
metastatic breast cancer, Dawson and colleagues demonstrated marked
improvements in detection of chromosomal rearrangements as markers
of tumor burden, over and beyond specific cancer antigens or generic
circulating tumor DNA (38). Improvements in NGS technology will only
enhance the ability to detect and monitor cancer, with the potential to
markedly alter how the disease is managed.
HCV
HIV
Breast cancer
Disease burdenDisease burden Disease burden
BRCA1/2 Oncotype DX
MammaPrint HER-2: Herceptin
Viral RNA load HLA: Abacavir
Viral RNA load
Viral genotype
IL28B: PegIFN
efficacy and dosing
ITPA: Ribavirin
adverse events
BRCA
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Preclinical Clinical
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Fig. 1. Genomic medicine in action. Examples of three conditions where
genomic medicine tools and information have affected clinical management
at various stages of disease. (Top) In chronic HCV infection, several genomic
markers are used in disease management: viral RNA concentrations are used
for diagnosis and monitoring; the genotypeofthevirusisusedforprognosis
and treatment response; and host IL28B and ITPA genotypes are used as
pharmacogenomic markers for efficacy and dosing. (Middle) In patients in-
fected with HIV, viral RNA concentrations are used for diagnosis and monitoring,
and host HLA genotype is used as a pharmacogenomic marker of hypersen-
sitivity to abacavir treatment. (Bottom) In breast cancer, germline BRCA1/BRCA2
genotyping is used to determine susceptibility to breast and ovarian cancer;
analysis of tumors with Oncotype Dx or MammaPrint is used to predict like-
lihood of recurrence; and expression of the tumor marker HER-2 is used to
inform treatment with the monoclonal antibody Herceptin.
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CLINICAL SEQUENCING AND DIAGNOSTIC DILEMMAS
According to the Online Mendelian Inheritance in Man database
(http://omim.org/), about 3676 Mendelian disorders have a known
molecular basis. However, there are nearlyasmanysuspectedMendelian
traits for which the molecular basis remains to be identified. The
potential for clinical sequencing to find the underlying cause and iden-
tify treatment options for these rare, debilitating diseases has led to the
formation of various large national and international consortia. In the
United States, three Centers for Mendelian Genomics have been es-
tablished at the University of Washington, Yale University, and a joint
Center at Baylor College of Medicine and Johns Hopkins University
(39). Moreover, clinical sequencing is being offered to patients with
unknown yet suspected genetic diseases, the so-called diagnostic
Diagnosis: molecular taxonomy Treatment: tailored choices
Expanded definition of self
Host germline genome
Tumor genome Microbiome
Infectious agents
Targeting specific disease markers
Cancer cell
HER-2 protein
Herceptin
Improved likelihood of response
HCV patients: PegIFN treatment responders
IL28B genotype CT/TT 40%
80%IL28B genotype CC
Enhanced drug safety
Abacavir hypersensitive
Abacavir tolerant
HLA type
Patients (%)
0
80
HLA-B*5701 HLA-DR7 +
HLA-DQ3
HLA-B*5701 +
HLA-DR7 +
HLA-DQ3
Dosing optimization
iWarfarin app for iPhone
Earlier diagnosis
Clinical
Mendelian
sequencing
Expanded
newborn
screening
Noninvasive
prenatal
testing
Earlier diagnosis in human disease
Disease burden
BRCA1/2 testing
for breast
cancer risk
Health
Corus CAD
test for
heart disease
Time
Preclinical
Oncotype DX
test for ER+
breast cancer
diagnosis
Clinical
Fig. 2. Trends in genomic medicine. Several themes are emerging in
the diagnosis and treatment of disease. (Left) First, as the knowledge of
the genomic underpinnings of disease increases, the definition of “self”
is likewise expanding. This self includes not just the germline human
genome inherited from our parents but also somatic changes in the ge-
nomes of tumors, the genomes of commensal microbes that inhabit our
body, and the genomes of pathogenic organisms. Second, the influence
of genomics on medicine is moving the diagnosis of diseases toward
the earliest possible point in the course of disease, before clinical man-
ifestation. Third, genomic testing is occurring earlier in the life of a human,
moving from adulthood to childhood, the neonatal period, and even pre-
natally. (Right) Pharmacogenomic markers are being used in several ways:
to select targeted therapies exemplified by the breast cancer marker HER-2
and treatment with the monoclonal antibody Herceptin; to predict likeli-
hood of response, as in the case of the host IL28B genotype and response
to interferon therapy in HCV infection; to enhance drug safety, for example,
by testing for host HLA genotypes predictive of abacavir hypersensitivity in
humans infected with HIV; and to optimize dosing of drugs, such as war-
farin, based on genotypes indicative of rate of metabolism using, for exam-
ple, the iWarfarin app.
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dilemmas, at many major medical centers and through programs
such as the National Human Genome Research Institute’sUndiagnosed
Diseases Program (http://www.genome.gov/27544402). One notable
case from the Medical College of Wisconsin involved the use of clinical
exome sequencing to identify a gene variant in a child who presented
to the clinic with a severe, intractable form of inflammatory bowel dis-
ease for which physicians were unable to provide a diagnostic explana-
tion (40). The discovered variant in the XIAP gene defined a new form
of inflammatory bowel disease due to deficiency of an X-linked inhibitor
of apoptosis. Knowledge of the causal mutation led to a cure through
allogeneic bone marrow transplantation and demonstrated the power
of clinical NGS as a strategy for diagnosis and management of rare
diseases. Early results from a number of clinical sequencing programs
estimate the success rate of disease gene identification at about 50%,
offering hope to thousands of individuals with previously undiagnosed
or untreated rare disorders (41,42).
Newborn screening, prenatal diagnosis, and preconception
carrier testing
A natural outcome of identifying genes for rare Mendelian disorders
is the application of these findings to earlier detection, either at birth
(newborn screening), in utero (prenatal diagnosis), or preconception
(carrier testing). Newborn screening is a mandatory, state-supported
public health program meant to protect newborn children by screen-
ing them for rare, treatable (and thus preventable) disorders at birth.
The scope of diseases tested varies by state but has been steadily
increasing from an average of 5 conditions in 1995 to a uniform pan-
el of 31 core disorders and 26 secondary disorders currently recom-
mended by the U.S. Department of Health and Human Services
Secretary’s Advisory Committee on Heritable Disorders in New-
borns and Children (43). Some states evaluate additional conditions,
including diseases that affect children at a later stage in development
and others for which the benefits of early intervention are limited.
The number of conditions considered for newborn screening will
undoubtedly grow with genome sequencing, improving early diag-
nosis. A concern is that, as a consequence, expanded screening will
erode the ethical justification for this compulsory program and may
undermine one of the most successful public health programs in ex-
istence (44).
Prenatal diagnosis moves screening for genetic disorders even fur-
ther upstream by detecting genetic variation in the developing fetus.
Traditionally, fetal DNA is obtained invasively through amniocentesis
or chorionic villus sampling, but a potential alternative emerged in
1997 when it was demonstrated that cell-free fetal DNA circulates in
maternal blood and could be isolated, amplified, and sequenced non-
invasively through a sample of maternal plasma (45). In 2008, NGS
technologies were used successfully for the first time to identify fetal
aneuploidy from cell-free fetal DNA in maternal plasma (46,47). Clin-
ical trials of the new method rapidly followed, and by late 2011,
noninvasive prenatal testing of trisomy 21 by sequencing of maternal
plasma DNA was being offered on a clinical and commercial basis in
the United States and China (48). In the third quarter of 2012, Sequenom
Inc., one such company offering this test, had reached a 90,000 an-
nualized test volume run rate for the MaterniT21 PLUS test (49).
Noninvasive prenatal testing for disorders caused by large dele-
tions, single-nucleotide substitutions, and other types of genetic vari-
ation, as opposed to de novo chromosomal aneuploidies like trisomy
21, is more challenging due to the factthatmaternalplasmacontains
DNA from both the fetus and mother, who may share the same mu-
tation. However, progress has been made in this area as well (50,51).
Investigators at Stanford University applied noninvasive prenatal test-
ing to detect a large genetic deletion underlying DiGeorge syndrome
in a first-trimester fetus using only a blood sample from the mother
(52,53). Noninvasive prenatal testing eliminates the need for invasive
procedures while also greatly expanding the number of genetic var-
iants that have traditionally been detected in utero.
Even before conception, carrier screening enables couples who are
planning a family to assess their risk of having a child with a recessive
Mendelian disorder and use this information to guide their reproduc-
tive decisions. There are more than 1000 rare, recessive Mendelian dis-
orders for which the underlying genetic mutation is known (54). Although
individually rare, Mendelian disorders can have a sizable public health
impact. Population-based carrier screening for Tay-Sachs disease has
reduced the incidence of the disease in Jewish populations in the
United States and Canada by more than 90% (55). Considering that
each person is estimated to carry on average 2.8 mutations for known
severe recessive disorders (56), the impact of screening could be sizable
in terms of reduced disease morbidity and mortality in the population.
The impact could be particularly significant in populations such as
Ashkenazi Jewish, who are disproportionately affected by recessive
disorders. There may also be utility for screening in the setting of in vitro
fertilization, where preimplantation genetic analysis has the potential to
reduce the incidence of disease. Panels of tests for hundreds of child-
hood recessive illnesses with severe clinical manifestations have been
developed (56), and some are offered directly to patients through
companiessuchasCounsylInc.
Genetics of common complex diseases
Unlike rare Mendelian disorders, the genetic dissection of common,
complex diseases such as cancer, cardiovascular disease, and diabetes
has proven to be more difficult. These diseases by definition are due to
the complex interplay of many gene variants, both common and rare,
as well as nongenetic factors. GWAS, the current method used to find
these genes, has been carried out on large cohorts of patients and
controls across numerous traits and diseases, revealing hundreds of
common genetic variants associated with those traits (http://www.
genome.gov/gwastudies). Researchers are now turning to NGS to
identify rare genetic variants associated with complex diseases. For
example, exome sequencing in neurodevelopmental conditions has
identified de novo mutations linked to diseases like autism and schiz-
ophrenia (57). However, exome sequencing of large numbers of subjects
with a complex trait can be costly and experimentally challenging (58).
Often, thousands of patients are required to assign statistical significance
to rare variant associations with complex diseases. Innovative study
designs such as exome sequencing of patients with extreme phenotypes
have yielded some successes, including the identification of DCTN4
associated with clinical sequelae in cystic fibrosis patients infected with
Pseudomonas aeruginosa (59).
Despite the unequivocally strong statistical associations between
genetic variants and complex diseases, their low sensitivity and spec-
ificity afford limited clinical value for disease predisposition testing.
Notable exceptions include genes underlying breast cancer (60), Lynch
syndrome (61), and celiac disease (62), where some variants have
enabled prophylactic treatment or screening of other family members,
which may provide cost-effective alternatives to standard disease man-
agement strategies.
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Amidst myriad technological advances and gene discoveries, a
simple family history continues to be advocated as a tool for identification
of common disease risk. For very common conditions with high heri-
tability, such as cardiovascular disease, family history is a much stronger
predictor of disease than any single or combination of genetic/genomic
markers (63). One model suggests that neither family history nor genetic
testing should be used as a standalone but that the real power for disease
prediction, risk assessment, and differential diagnosis comes from their
combined use (63).
Pharmacogenomic markers
GWAS approaches have also been used successfully in pharmaco-
genomics research. Several markers of efficacy, adverse events, and
dosing of therapeutics have been found, but their uptake into clinical
practice is variable, despite the clear actionability of these types of var-
iants. In some cases, such as with the HLA-B*5701 genotype for the
HIV drug abacavir (64)andHLA-B*1502 for the antiseizure drug car-
bamazepine (65), carriers of these genotypes should avoid the drug
entirely to eliminate a specific serious adverse event. In other cases, such
as TPMT for mercaptopurine (66)orCYP2C9/VKORC1 for warfarin
(67,68), adjusting the dose of drug based on genotype can help to avoid
toxicity and improve efficacy. Actionability is not enough to ensure
uptake of pharmacogenomic testing. Such is the case with the anti-
platelet drug clopidogrel, where despite having an FDA “black box
warning”for efficacy in individuals carrying the CYP2C19 genetic var-
iant, there is no clear consensus among physicians on its use (69). In
hepatitis C treatment, on the other hand, the IL28B genotype test
not only has proven to be highly predictive of response to pegylated
interferon/ribavirin used to treat chronic HCV infection but also has
seen rapid and widespread adoption in the clinic (70). Genetic markers
that predict reduced therapeutic efficacy may face a high hurdle for
established drugs, unless evidence supporting clinical validity and
utility of the test is indisputable.
Drug repurposing
Among the new programs at the National Center for Advancing Trans-
lational Sciences (http://www.ncats.nih.gov/research/reengineering/
rescue-repurpose/rescue-repurpose.html) is one aimed at using ge-
nomic information to determine whether drugs approved to treat
one disease may be effective in treating others. With 6% of the genome
already being pursued for targets of therapy development (14), addi-
tional investigations into the phenotypes associated with variation in
these targets may open the door to expanded indications. Indeed, two
different researchers recently demonstrated the feasibility of using ge-
nomic information to repurpose drugs. They used computational anal-
ysis to compare gene expression profiles characteristic of certain diseases
with profiles characteristic of specific drugs. By searching for comple-
mentary patterns of gene expression,theysuccessfullyidentifiednew
disease-drug matches, including a match between the antiulcer drug
(cimetidine) and lung cancer (15) and a match between the antiepileptic
drug (topiramate) and inflammatory bowel disease (16), and validated
their predicted use in vivo in rodent models.
Another group used GWAS data for drug repurposing (14). Dis-
ease genes uncovered through GWAS are 2.7-fold enriched for the
molecular targets being pursued by drug developers (14). Besides
the expected overlap in GWAS genes and drug targets for the same
clinical indication (trait), Sanseau and colleagues uncovered more than
100 drug targets that were associated with traits not considered as a
primary indication, opening the door for drug repurposing. In one
example, GWAS identified TNFSF11 variants associated with Crohn’s
disease. TNFSF11 is the target for the monoclonal antibody denosumab,
currently marketed for osteoporosis, but as a result of this research, it
may also be considered for Crohn’s disease. Repurposing of existing
FDA-approved drugs eliminates the need for lengthy clinical trials be-
cause formulation, dosing, and safety have already been worked out,
offering new avenues of treatment for these conditions in a short time
frame. Even for drugs in development, knowledge of potential expanded
indications may provide more impetus to push these drugs through de-
velopment. Nonetheless, the practicalities of renavigating the many safe-
ty and efficacy regulatory hurdles should not be underestimated.
Complex multimarker genomic tests for disease diagnosis
and prognosis
Beyond DNA sequence, measures of gene expression, proteins, metab-
olites, and epigenetic changes are being used to generate comprehen-
sive profiles of biological systems in health and disease. Many of the
computational challenges of analyzing these large complex data sets
are being addressed to yield next-generation biomarkers that are mul-
tianalyte, diagnostic, prognostic, and predictive. There are a growing
number of marketed tests that are in vitro diagnostic multivariate
index assays (IVDMIAs), which typically measure protein or RNA
levels, often with complex algorithms, enabling diagnosis and progno-
sis (Table 1) (71). One example is Oncotype Dx (Genomic Health Inc.),
a test that examines expression of 21 genes in tumor tissue to determine
the likelihood of disease recurrence in women with early-stage hormone
estrogen receptor–positive breast cancer (Fig. 2). The test analyzes ex-
pression levels and converts them to a recurrence risk score, which
has been shown to help guide treatment in patients, reduce overall
health care costs, and improve outcomes (72–75)andiscurrentlycov-
ered by many major insurance companies. Other examples include
MammaPrint (Agendia Inc.), which analyzes the expression of 70 genes
to determine whether patients are at high or low risk of breast cancer
recurrence, OVA1 (Vermillion Inc.), a five-protein test that gauges
whether a woman’s ovarian mass is malignant and requires surgery,
AlloMap (XDx Expression Diagnostics Inc.), an 11-gene blood RNA
signature for monitoring rejection after cardiac transplant, and Corus
CAD (CardioDx Inc.), a 23-gene blood RNA signature to screen for
obstructive coronary artery disease.
Despite their complexity, IVDMIAs like these are finding their way
to the market and to the clinic. According to 2007 draft guidance from
the FDA (76), IVDMIAs are being used to make critical health care
decisions and thus should be regulated by the FDA, leading some di-
agnostic developers to work with regulators preemptively. Some, but
not all, of the marketed IVDMIAs have demonstrated analytical and
clinical validity, but evidence of clinical utility is almost always lagging
(77,78). Moreover, the very nature of IVDMIAs presents challenges to
insurers, who grapple with not only limited data on clinical utility but
also how to reimburse such tests that are composed of both a labora-
tory component and an associated algorithm, used to score risk, the
latter part being integral to realizing the test’svalue(79).
The success of some IVDMIAs is a testament not only to the power
of computational biology but also to the importance of advocacy and
financial resources that the commercial developers of these tests bring to
the table. Companies developing IVDMIAs are able to finance pivotal
studies aimed at demonstrating clinical validity, navigate regulatory
hurdles, advocate for coverage by insurance companies, and disseminate
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their tests through marketing to health care providers. Their efforts
offer valuable lessons on the effective translation of genomic tests to
medicine.
Genomics to assess microbial friends and foes
Another exciting area of genomic medicine involves sequencing the
genomes of microorganisms, both the commensal bacteria that reg-
ularly inhabit our bodies (the human microbiome) (80) and the in-
fectious agents that cause acute and sometimes fatal diseases (81).
This past year, the Human Microbiome Project published the first
results of its study of the microbial populations inhabiting various
human body sites (82). Besides providing reference sequences for
many taxa, the major findings from the analysis of this healthy co-
hort included correlation of groups of organisms with host charac-
teristics including ethnicity, age, and body mass index. Further
research in this area has begun to uncover relationships between hu-
man microbial communities and diseases such as diabetes, asthma,
psoriasis, atherosclerosis, obesity, and others (83,84). In one exam-
ple, the gut microbiome has been linked to inflammatory bowel dis-
ease, with patients showing dysbiosis of their gut microbiome,
specifically an expansion of the Proteobacteria phylum that may lead
to inflammation (85). This study, along with others from GWAS
showing that patients with inflammatory bowel disease bear poly-
morphisms of genes conferring gastrointestinal innate immunity,
has led investigators to implicate host immune responses to Proteo-
bacteria in the etiology of inflammatory bowel disease (86). More-
over, strategies to modify the gut microbiome are being explored
as treatments for inflammatory bowel disease, including the use of
fecal microbiota transplantation or engraftment of microbiota from a
healthy donor into a recipient (87). The burgeoning study of the hu-
man microbiome holds tremendous promise for personalized med-
icine because microbial composition can be altered noninvasively
through diet or the use of probiotics or antibiotics.
In the area of infectious disease, NGS of pathogenic microor-
ganisms can supplant the need to first grow them in culture, previ-
ously a major impediment to pathogen identification. For example, in
2003, sequencing of samples from infected patients with the severe
acute respiratory syndrome (SARS) allowed investigators to identify
the causative agent as a coronavirus (88). Comparison of sequences
of multiple isolates of an organism from a single epidemic gives a pic-
ture of the organism’s evolution, allowing one to infer where the
outbreak began and how the infection spread. Sequencing was used
to determine the origins of historical outbreaks of cholera (89), tuber-
culosis (90), and the 2009 H1N1 influenza outbreak as well (91). Sim-
ilarly, the source of carbapenem-resistant Klebsiella pneumoniae in a
recent hospital outbreak was identified by sequencing isolates of the
bacteria from infected individuals and examining the genetic dif-
ferences (92). From these data, scientists were able to determine
the chronology of infection, the likely silent carriers who trans-
mitted the infection, and the hospital equipment that may have
acted as a reservoir for the bacteria, even after standard decontami-
nation procedures. The genomic analysis was also able to pinpoint
when resistance to carbapenem first developed. The ability to
sequence microorganisms in a clinically relevant timeframe means
that these methods can now be applied in real time. For example,
an outbreak of methicillin-resistant Staphylococcus aureus was re-
cently curtailed in a hospital after applying genome sequencing to
assess evolution of the epidemic (13).
CHALLENGES AND OPPORTUNITIES FOR GENOMICS
IN MEDICINE
In the past decade, applications of genome research have been pur-
sued across the spectrum of disease management, from risk assess-
ment through diagnosis, prognosis, and treatment. Several themes
in diagnosis and treatment are emerging (Fig. 2). First, as the knowl-
edge of the genomic underpinnings of disease increases, the definition
of self is likewise expanding. This self includes not just the germline
human genome inherited from our parents but also somatic changes
in the genomes of tumors, the genomes of commensal microbes that
regularly inhabit our body, and the genomes of pathogenic organisms.
Second, the influence of genomics on medicine is moving the diagno-
sis of diseases toward the earliest possible point in the course of dis-
ease, before clinical manifestation. Third, genomic testing is occurring
earlier in the life of a human, moving from adulthood to childhood,
the neonatal period, and even prenatally. Finally, pharmacogenomics
is providing a potential means of improving response to therapies, en-
hancing safety, optimizing dosing, and tailoring treatment to the mo-
lecular underpinnings of disease. Notwithstanding this progress,
significant barriers are impeding the rapid translation of genomic dis-
coveries into medical practice.
Whereas research continues on the development, validation, and
utility of genome-based biomarkers, attention is now appropriately
shifting to addressing the roadblocks in translational genomic medi-
cine, from discovery to clinical implementation (93). Here, we highlight
some of the most pressing challenges (Fig. 3) along with innovative so-
lutions. What is becoming clear as the field progresses is that integration
of genomic medicine into practice requires changes in the infrastruc-
ture, processes, and culture along the entire path from discovery to
health care delivery.
Evidentiary framework
Building the evidentiary framework needed to convince the FDA to
approve genomic tests, insurance companies to cover them, and phy-
sicians to use them is perhaps the biggest challenge facing the field of
genomic medicine. In this area, genomic medicine may benefit from
Test awareness
Reimbursement
Regulation
Ethical issues
Physician and
patient education
Clinical
implementation
Evidentiary
framework
Fig. 3. Challenges facing genomic medicine. Shown are the obstacles
on the path from genome discovery to clinical medicine. These obsta-
cles include test awareness (diffusion of innovation), building the evi-
dentiary framework needed to support the clinical validity and utility
of genomic tests, implementation of genomic medicine into the clinical
workflow, ethical issues surrounding genomic testing, regulatory and
reimbursement hurdles, and the education of health care workers and
patients alike.
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partnering with public health agencies, which have vast experience in
epidemiology and surveillance. The Office of Public Health Genomics
at the U.S. Centers for Disease Control and Prevention has developed
a framework for evaluating emerging genetic tests. Their ACCE model
encompasses four areas: analytic validity (how accurately and reliably
the test measures the genotype of interest), clinical validity (how con-
sistently and accurately the test detects or predicts the intermediate or
final outcomes of interest), clinical utility (how likely the test is to sig-
nificantly improve patient outcomes), and ethical, legal, and social im-
plications that may arise in the context of using the test (94). Analytic
validity is usually in the purview of the testing laboratory, which under-
takes a relatively straightforward process to ensure accurate detection
and reporting of the assay results. The bigger challenge is establishing
clinical validity and utility, a process that requires data curation from
the primary scientific literature and, ultimately, carrying out expensive
and time-consuming prospective randomized clinical trials.
The financial burden on a diagnostic developer to conduct random-
ized clinical trials is substantial. As a result, a number of public-
private consortia of stakeholders have emerged to pool resources and
validate genomic biomarkers. The Biomarker Consortium (http://
biomarkersconsortium.org) is one such example where government
and pharmaceutical companies are collaborating on the discovery
and qualification of new biomarkers. The Consortium can leverage
clinical trial data from multiple pharmaceutical companies, which,
when pooled, can markedly increase statistical power and, when
coupled with analytical and scientific expertise from academia, gov-
ernment, and the public sector partners, can accelerate and reduce
the cost of clinical validation.
In the case of rare diseases, which are the focus of clinical sequenc-
ing, or rare outcomes, which are the focus of pharmacogenomic tests
for therapeutic toxicities, enrolling adequate numbers of subjects in a
randomized clinical trial may not be possible. Moreover, randomized
clinical trials do not always represent real-world situations but rather
exemplify an ideal circumstance. To address these concerns, some
have proposed the use of a pragmatic clinical trial design instead
(95,96). In contrast to randomized clinical trials, with their strict pa-
tient eligibility criteria, narrow protocol-driven therapies, and pre-
scribed outcomes, pragmatic clinical trials are conducted in the real-
world medical setting, under best-practice conditions with diverse and
comorbid patient populations. Although less rigorous in design than
randomized clinical trials, the pragmatic clinical trial design could
provide an early indication of the value of pharmacogenomic test-
ing. Comparative effectiveness research is a similarly pragmatic approach
that uses systematic reviews of existing studies, evidence-quality ap-
praisal, and health outcomes research in real-world practice settings
to assess clinical utility. Rapid learning healthcare models are being
used for comparative effectiveness research, whereby diverse and in-
teroperable patient clinical and outcomes data are made available, ide-
ally in a robust and real-time fashion, to potentially support clinical
practice while simultaneously supporting comparative effectiveness
research (97). Coupled with biobanking of patient specimens, the clin-
ical utility of genomic tests can be evaluated in an efficient and cost-
effective manner (98).
Another consideration is that clinical utility conceived only as im-
proved morbidity and mortality fails to appreciate personal utility for
the patient, such as the financial and psychological benefits of resolu-
tion of an unknown diagnosis, changes in life-style leading to overall
improvements in health, or even family planning, all of which are in-
fluenced by knowledge of the genetic susceptibility of disease (99–102).
Some groups charged with evaluating genomic tests already recognize
that incorporating the concept of personal utility into assessments of clin-
ical utility will more accurately capture the value of these tests (101).
Through creative partnerships and study designs and a new appreciation
of personal utility, the evidence base for genomic medicine tests will ex-
pand and, in doing so, facilitate approval, coverage, and adoption by the
health care community.
Diffusion of innovation in genomics and medicine
The challenge of diffusion of innovationinhealthcareisnotuniqueto
genomic medicine, but the classical venues for disseminating informa-
tion to health care providers, such as grand rounds and conferences,
may be insufficient for capturing the breadth and depth of genomic
medicine. Passive approaches, including reading the primary scientific
and medical literature, can be time-consuming and overwhelming.
Consequently, several efforts are under way to track and make accessi-
ble the latest available information on genomic tests (Table 2). For drugs
on the market, recommendations for genomic testing can be found in
their labels and in a database of drug-test pairs, currently numbering
more than 100, maintained by the FDA (103). The Pharmacogenomics
Knowledge Base (PharmGKB) is another online resource that includes
information on 186 potentially clinically actionable gene-drug associa-
tions and genotype-phenotype relationships (104). Much of the
information is manually curated from the published literature and is
used to write evidence summaries and pharmacogenomic-based drug
dosing guidelines. Another resource is GeneTests (http://www.ncbi.
nlm.nih.gov/sites/GeneTests), a site focused on Mendelian disorders
that includes a directory of genetic testing laboratories and genetic
and prenatal diagnosis clinics as well as expert-authored peer-reviewed
disease descriptions in a standard format (GeneReviews). GeneTests is
slated to be phased out in 2013 and replaced with the National Institutes
of Health’s (NIH) Genetic Testing Registry, a repository for com-
prehensive genetic test information that is voluntarily submitted by
test providers (105). Currently, the site lists 2793 clinical tests, includ-
ing pharmacogenetic and other types of tests that are not in GeneTests.
Perhaps the most comprehensive list of non-Mendelian genomic tests
can be found in a series of Technology Assessment Reports generated
by the Tufts Medical Center Evidence-based Practice Center under
contract to the Agency for Healthcare Research and Quality. Through
horizon scanning of the scientific literature, news, laboratory and com-
mercial Web sites, databases, and other sources, researchers at Tufts
University have populated a database, Gene Test Tracker, with available
clinical genetic tests relevant to the Medicare population. The current
reports cite 154 cancer tests (106) and 127 noncancer genetic tests (107)
in development.
Besides databases for tracking available tests, there is a need for
curation, evaluation, and synthesis of evidence from published re-
search supporting clinical validity and utility of tests to guide clinicians.
Evaluation of Genomic Applications in Practice and Prevention (EGAPP)
(http://www.egappreviews.org/recommendations/index.htm), a group
formedin2004bytheOfficeofPublicHealthGenomics(108), synthesizes
scientific evidence and makes recommendations on appropriate use of
genetic tests in clinical practice. In 2009, PharmGKB and the NIH’s
Pharmacogenomics Research Network initiated a similar effort, the
Clinical Pharmacogenetics Implementation Consortium (CPIC) (http://
www.pharmgkb.org/page/cpicGeneDrugPairs) (109). CPIC provides
guidelines to help clinicians understand how available genetic test results
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should be used to optimize drug therapy. Currently, CPIC has published
recommendations for six gene-drug pairs, with eight more under way.
GAPPKB (http://www.hugenavigator.net/GAPPKB/home.do), an in-
tegrated, searchable knowledge base, is also attempting to fill this gap.
This online resource developed by the Office of Public Health Genomics
features the GAPP Finder, a continuously updated, searchable data-
base of genetic tests in transition to practice; Evidence Aggregator,
an application that facilitates searching for evidence reports, systematic
reviews, recommendations, or guidelines in genetic tests and genomic
applications; and PLoS Currents: Evidence on Genomic Tests, an on-
line, open-access journal publishing evidence reviews and recommenda-
tions on genomic tests. These early attempts at supporting diffusion of
innovation are a laudable first step, but a more sustainable means of
curating data on available tests, annotating the scientific literature,
and gathering evidence to support genomic tests in an efficient, dy-
namic, and timely manner needs to be developed.
Clinical implementation
Inorderforgenomicmedicinetobepracticed,itmustbewoveninto
current systems of healthcare delivery, with due consideration not on-
ly to the providers of healthcare but also to the organizations in which
they practice as well. Implementation scientists have outlined various
aspects that need to be considered in order for genomic medicine to
take hold in the clinical setting (110). Beyond the scientific soundness
of the genomic test, measured by a strong evidentiary base and regard
for potential benefits and harms, is consideration of how the new test
will integrate into the clinical workflow. Consideration should be given
to aspects such as access to a laboratory certified by the Clinical Labo-
ratory Improvement Amendments (CLIA) of 1988, methods for sample
preparation and transport, test ordering, receipt, and delivery of results.
Although these features are not unique to genomic testing, their imple-
mentation is complicated by issues of privacy, complex interpretation of
results, and the need to involve third parties for counseling in some
cases. These facets may require the development of new systems to ac-
commodate genomic tests (111). For example, surgical and interven-
tional radiology services are accustomed to fixing tissues in formalin
to preserve them for analysis at a later date, but NGS works best on
fresh tissues. Either adapting NGS technology to work within the con-
straints of current tissue handling procedures or modifying those pro-
cedures to allow collection of fresh or fresh-frozen tissues may be
necessary (112).
A robust means of integrating genomic data into electronic health
records will be required, with consideration of not only data storage
formats and privacy issues but also appropriate decision support tools
for prompting their use at the point of care and delivering results in an
easily interpretable format (113–115). To meet these needs, NGS
companies like Knome (http://www.knome.com) are developing their
own plug-and-play bioinformatic support tools, and commercial ven-
dors of electronic health records have begun to address genomic-
related applications as well (113). Some patients may opt to self-manage
their own genomic data in a personal health record such as Microsoft
Health Vault (http://www.microsoft.com/en-us/healthvault) or Dossia
Table 2. Genomic medicine’s address book. Shown are sites that curate available genomic tests and the evidence to support their use.
Web site URL Description
CPIC http://www.pharmgkb.org/page/cpic Provides freely available, peer-reviewed, updatable, and detailed gene/drug
clinical practice guidelines; 6 currently published, 8 under way
EGAPP http://www.egappreviews.org/ Synthesizes scientific evidence and makes recommendations on appropriate
use of genetic tests in clinical practice; 8 evidence reports and 6
recommendations currently available
Evidence aggregator http://www.hugenavigator.net/GAPPKB/
evidencerStartPage.do
Search engine for evidence reports, systematic reviews, recommendations, or
guidelines in genetic tests and genomic applications
FDA biomarkers http://www.fda.gov/drugs/scienceresearch/
researchareas/pharmacogenetics/
ucm083378.htm
List of pharmacogenomic biomarkers on drug labels (link to
drug labels provided); currently includes >100 biomarker-drug pairs
GAPP Finder http://www.hugenavigator.net/GAPPKB/
topicStartPage.do
A continuously updated, searchable database of genetic tests in transition to
practice; currently includes 519 tests
GeneTests http://www.ncbi.nlm.nih.gov/sites/GeneTests/ Information on genetic tests, mostly for rare Mendelian disorders. Site
includes directory of testing laboratories, genetic and prenatal diagnosis
clinics, and expert-authored peer-reviewed disease descriptions
(GeneReviews); currently includes >2900 disease entries; due to be phased
out in 2013
Genetic testing registry http://www.ncbi.nlm.nih.gov/gtr/ Central location for voluntary submission of genetic test information by
providers; includes information on test methodology, validity, evidence
of the test’s usefulness, and laboratory contacts and credentials;
currently includes >1200 fully registered tests for >500 conditions
PharmGKB http://www.pharmgkb.org Information on potentially clinically actionable gene-drug associations
and genotype-phenotype relationships; currently lists 186 well-known
pharmacogenomic associations and provides 46 summaries for very
important genes
PLoS currents: evidence
on genomic tests
http://currents.plos.org/genomictests/ Online, open-access journal publishing evidence reviews and recommendations
on genomic tests; currently has 23 genomic test reviews
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(http://www.dossia.org) as a safeguard. Currently, there are several
examples of decision support tools, such as Warfarin Dosing (http://
www.WarfarinDosing.org), but they are typically standalone tools and
not part of routine clinical workflow. To maximize their effectiveness,
such tools should be integrated into electronic health records. Tapping
into the collective knowledge and experience of various institutions
working in this space would greatly facilitate this effort. Ultimately, a na-
tional, standardized technical architecture for integrating clinical decision
support into electronic health records will be required. Notable efforts in
this space include those of Health Level 7 (http://www.hl7.org), an orga-
nization that provides interoperability standards for the exchange, integra-
tion, sharing, and retrieval of electronic health information. Through their
Clinical Genomics Workgroup, this organization has developed a stan-
dards guide for genetic testing that includes document templates to
support integration of genetic testing into electronic health records
(116). Appropriate clinical decision support, provided in the context of
the electronic health record, will greatly facilitate the diffusion and uptake
of genomic medicine.
Regulation of genomic tests
Regulationofgenomictestsisbothapublic health issue and, ultimate-
ly, an economic one. Physicians and patients alike look to government
regulators to assure them that the tests have been carefully scrutinized
for their safety, efficacy, and intrinsic value. Currently, two federal or-
ganizations are in charge of regulating genetic tests (117). A small per-
centage of genetic tests are sold as diagnostic devices, meaning that a
company makes and sells genetic test kits to a laboratory for testing,
and these are regulated by the FDA’s Office of In Vitro Diagnostics.
Before marketing, the analytical validity of the device must be assessed,
but in cases where clinical performance has not been well established,
the clinical validity is examined as well. The specific degree of regula-
tion of medical devices is currently tailored to their level of risk: class I
(low risk, few regulatory controls), class II (moderate risk), and class
III (high risk, more controls, including submission of a premarket ap-
proval application) (117). Many genomic tests will fall into class II, as
is the case with genetic tests for drug-metabolizing enzymes (118).
Some genomic tests will fall into class III, for example, those that alter
a therapeutic decision in such a way as to expose individuals to po-
tentially harmful treatments, such as radiation therapy in cancer. Re-
cent guidance from the FDA clarifies the principal factors it considers
when making benefit-risk determinations on medical devices (119).
Most genetic tests today are developed and offered by individual
laboratories as laboratory-developed tests, and these laboratories are
overseen by the Centers for Medicare and Medicaid Services (CMS).
CMS is primarily concerned with monitoring the laboratory’scompli-
ance with CLIA regulations in their testing procedures. For years, the
FDA has claimed enforcement discretion and opted not to regulate
laboratory-developed tests unless they were deemed “high risk,”as
in the case of IVDMIAs (76). However, the selective approach to reg-
ulate only a subset of high-risk laboratory-developed tests has led to
more confusion and created an uneven playing field. Moreover, the
rise of direct-to-consumer genetic testing companies, those that bypass
physicians and market their services directly to patients outside the med-
ical setting, has brought regulatory oversight of genomic tests in general
to the forefront (120). On the basis of a series of recommendations
by the U.S. Department of Health and Human Services Secretary’s
Advisory Committee on Genomics, Health, and Society to enhance
oversight (121), the FDA has responded with a 2010 notice stating that
they may actively regulate not just high-risk tests but all laboratory-
developed tests (122). Regulation of genomic tests is a moving target
that needs to strike a balance between commercial interests and pa-
tient safety to move genomic medicine forward.
Coverage and reimbursement
Although FDA approval of a genomic medicine test may improve the
likelihood of coverage by insurance companies, it is no guarantee.
Whether an insurance plan covers genetic testing depends on several
factors, including consumer demand, opinions of professional organi-
zations, integration into clinical guidelines, and, most importantly, the
strength of evidence supporting a test’s analytical and clinical validity
and clinical utility (123). Private insurance plans all make their own
decisions regarding whether to cover and how much to reimburse for
a genomic test, and it can vary on a case-by-case basis within those
plans. Nonetheless, private insurers often mimic the coverage decisions
of Medicare, as the largest provider of health insurance in the United
States. Medicare decisions are made by CMS, which has a policy of
reimbursing tests that are reasonable and necessary for diagnosis or
treatment of an illness or injury. However, CMS does not typically re-
imburse screening tests, including genetic predisposition tests, except
in the presence of signs and symptoms of disease. CMS’s Medical
Evidence Development and Coverage Advisory Committee met in 2009
to discuss what types of evidence will be needed to evaluate screen-
ing genetic tests for Medicare coverage (124). This information should
helpguidefuturedevelopmentofgenomicteststoimprovetheirlike-
lihood of coverage.
In a further sign that the field is moving forward, the American
Medical Association issued a new coding system for molecular diag-
nostics, and the CMS has been deliberating on how to reimburse these
tests (125).Oneofthekeychallengeswillbeobtainingreimbursement
not just for the pathology laboratories that are running the tests but
also for the physicians or other health care workers who are interpret-
ing the tests. Coverage and reimbursement of genomic tests is evolving,
but in the current system of healthcare delivery, it remains an essential
component that needs to be addressed to see widespread uptake of ge-
nomic medicine.
Ethical, legal, and social issues
Many of the ethical, legal, and social issues related to genomic medicine—
such as patient privacy, selective termination of pregnancies based on
genetic information, and patentability of DNA—have existed since the
arrival of genetic testing. In a current landmark case sparked by con-
troversy over the BRCA1 gene patent held by Myriad Genetics—
Association for Molecular Pathology, et al. v. U.S. Patent and Trade-
mark Office, et al.—the U.S. Supreme Court is hearing arguments on
the patentability of genes (126). The ruling will have implications for
diagnostic use of gene patents, affecting developers of diagnostics and
patients alike. Privacy is another issue that has been reignited by the
introduction of NGS and fueled by an atmosphere of collaborative,
open-access public data sharing. Studies of publicly available sequence
data have shown that patients in research studies can be identified by
their genome sequences (127,128). These findings demonstrate the
potential for sequence data to expose patient identities, with significant
implications for not only the individual but also their family members
and possibly the larger community to which they belong. The 2008
Genetic Information Nondiscrimination Act is a U.S. federal law
that bars insurers and employers from discriminating on the basis
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of genetic information, but it does not pertain to long-term disability
or life insurance, nor does it protect against stigmatization. The
application of NGS to noninvasive prenatal testing has also rekindled
an old concern over the misuse of genetic information to perform se-
lective abortion, already an ethically and politically contentious issue.
Fear that decisions will be made on the basis of trivial genetic traits has
reopened the debate about which health conditions, if any, are suffi-
cient grounds to justify abortion (129).
The ability to uncover all genetic variants in a subject through
NGS also raises a new dilemma: whether to disclose to patients poten-
tially clinically meaningful variants unrelated to the primary indication
for sequencing, so-called secondary or incidental findings (128,130).
On average, every human has several hundred coding region variants
in their genomes, most of which have unknown health consequences
(6). Who decides which of the discovered mutations are clinically rel-
evant and under what circumstances the incidental findings of NGS,
of either known or unknown health significance, should be shared
with patients are hotly debated topics. The American College of Med-
ical Genetics advocates for clear policies related to return of results,
stating that patients should be informed of those policies and under-
stand what types of information might be reported back to them and
under what circumstances, as well as recommending that patients
should be able to opt out of receiving certain findings (131). In their
recently published position statement, the American College of Med-
ical Genetics recommends that laboratories conducting exome and ge-
nome sequencing for clinical use should notify physicians about their
patients’status for a number of specific conditions, genes, and variants
that are found during the sequencing (132). This position has been
controversial because it is seen to be at odds with patient autonomy
and the rights of children to not learn about genetic predisposition to
adult-onset conditions. This has led the American College of Medical
Genetics to release a statement clarifying their position (133).
The limited understanding of the health implications of genetic
variation uncovered through NGS is concerning. In 2011, the National
Human Genome Research Institute sponsored a workshop, ClinAction,
to devise a plan for systematically evaluating and cataloguing genetic
variants based on their clinical actionability (134). The experts in attend-
ance proposed storing data on actionable variants in a new database,
ClinVar (http://www.ncbi.nlm.nih.gov/clinvar), which could be integrated
into the clinical workflow. Initially, the database will be populated with
existing variants catalogued in the Online Mendelian Inheritance in Man
database (http://www.omim.org), GeneReviews (http://www.ncbi.nlm.nih.
gov/sites/GeneTests/review), Locus-Specific Mutation Databases (http://
www.hgvs.org/dblist/glsdb.html), and other sources, but will grow as
new discoveries are made. An important aspect of this effort is the need
to guard against false-positive results that can occur in NGS studies based
on single patients or families, and for which very strict peer review of the
scientific evidence linking the genetic variant to disease is warranted. For-
tunately, discourse on incidental genetic findings as well as other ethical
issues is occurring in parallel with development of genomic medicine as
the research community strives to balance innovation with responsible
use of new technologies.
Education
There is a growing sentiment that uptake of genomic medicine is slow
becausehealthcareproviderslackadequate training in genomics. One
study found that describing a test as genetic (versus nongenetic) sig-
nificantly decreased a physician’s likelihood of offering the test (135).
Primary healthcare providers will likely assume prominent roles at the
front lines of genomic medicine, taking responsibility for administer-
ing new tests and fielding questions from informed patients. Hence,
they will not only need to be armed with practical information on
what tests are available, when and how to use them, where to get them
done, and what to tell patients, but also require a conceptual founda-
tion on which to build their capacitytoevaluateanddelivergenomics
in the course of clinical care. Although most physicians have heard of
pharmacogenomics (136), few are aware of direct-to-consumer genetic
testing (137), and with the rapid pace of discovery, staying on top
of the latest available genomic medicine tools will be a daunting task. Re-
search has shown that few primary care providers feel comfortable or-
dering genomic tests or explaining test results to patients (136,137),
and most feel an urgent need for genetics education (138).
In their report on genetics education, the U.S. Department of
Health and Human Services Secretary’s Advisory Committee on Ge-
nomics, Health, and Society highlighted factors that contribute to the
limited genetics education of healthcare professionals, including issues
such as a crowded curricula, lack of knowledgeable faculty, lack of
evidence-based guidelines in genetics, and misconceptions about the
nature of genomic medicine (139). The committee recommended
modifications in medical, dental, nursing, public health, and pharmacy
school curricula and in medical residencytrainingprogramstoensure
that healthcare professionals entering the workforce are well trained in
genetics. These recommendations prompted the National Coalition
for Health Professional Education in Genetics to develop specific core
competencies for all health care professionals on knowledge, skills, and
attitudes needed to effectively deliver genomic medicine (140).
But still unresolved are the best methods to educate health care
providers. In the last few years, several university medical schools have
made significant efforts to fill the genomics education gap (141–144).
These efforts include targeting curriculum to medical students and res-
idents in training and continuing medical education for practicing
professionals. There is a push to introduce topics related to genomic
medicine even earlier, during undergraduate training. However, improv-
ing overall genomics literacy of health care providers is only one piece
of the puzzle, and keeping pace with this rapidly evolving field will be
a continuous challenge.
Enhanced genomic education not only is key for health care pro-
viders but also extends to all professions that genomic medicine touches
upon. Policy-makers, regulators, lawyers, investors, insurance under-
writers, and others will need some understanding of genomics to
move genomic medicine forward. It remains unclear how these pro-
fessionals will receive this information. Moreover, acceptance of ge-
nomics ultimately may require a level of comfort on the part of the
patient, who may be concerned about privacy and discrimination or
confused about the implications of a particular genetic test result. This
may be especially problematic for patients obtaining genomic data
through direct-to-consumer test providers. Studies find that more
than one-third of U.S. adults have limited health literacy (145), which
in turn affects understanding of print and oral communications about
genetic and genomic information (146). Historically, genetic counsel-
ors have been responsible for putting genetic information into context
for patients undergoing genetic testing, but these situations have
mainly involved Mendelian traits with clear inheritance and strong
effects and have occurred in the domain of specialty genetics clinics.
As genomics spreads from specialty clinics to more mainstream medi-
cine where primary care physicians will be utilizing genomic information
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for clinical decision-making, the demand for genetic counselors may
far outstrip the supply, making this model impractical. Alternative so-
lutions, including additional training, and perhaps certification, of
primary health care providers in the delivery of genomic medicine will
need to be considered. In addition, improvement in the formal primary
and secondary education of consumers in the areas of scientific and
health literacy will enhance informed decision-making (93).
FUTURE EXPECTATIONS
The late 1990s marked what many consider to be the dawn of the era
of personalized medicine, when the full human genome was being re-
vealed for the first time and scientists were beginning to explore the
many ways that this information could be used to improve medicine
(147). Today, genome research has delivered promising new tools for
disease management, and early signs of uptake at academic medical
centers are encouraging. To be sure, the pace of implementation has
been slower than anticipated, and genomic medicine is far from
mainstream. Nonetheless, the challenges that prevent more widespread
uptake are not intractable but will require a concerted effort by the
many stakeholders in the field to overcome.
Moving forward, technological advances will continue to drive
discovery. New applications of NGS are on the horizon, including
profiling of immune cell repertoires (5) for monitoring hematological
malignancies (148,149) and responses to vaccines (150), and detecting
solid transplant rejection (151), just to name a few. Third-generation
sequencing platforms are expected to provide longer read lengths,
chromosome phasing, and reduced time and cost, increasing the ac-
curacy, capacity, and turnaround time for genome sequencing (152).
Not only will future research efforts lead to new markers and tools to
predict and manage disease at an increasing rate, but we also may see
fundamental shifts in how we define disease, how medicine is de-
livered to patients, and how consumers manage their own health
and affect change.
Creative partnerships and a rise in consumer-driven
genomic research
Thepaceofgenomicbiomarkerdiscovery will continue to accelerate
through creative research and funding partnerships. Large disease-
centered consortia are already bringing together investigators to col-
laborate and pool data and resources. For example, the International
Cancer Genome Consortium (153) involves 51 project teams contribut-
ing genomic data from 24,000 tumors across a wide spectrum of
cancers (http://icgc.org). The open-access movement will continue to
promote data sharing through portals such as Gene Expression Omnibus
(http://www.ncbi.nlm.nih.gov/geo) and dbGaP (http://www.ncbi.nlm.
nih.gov/gap), where any qualified investigator can generate hypotheses
and analyze data. Educated patients are also becoming a driving force
behind personalized medicine. The movement toward consumer-driven
health care has empowered patients, leading them to seek information
on medical conditions through the Internet, track their own health
history through personal health records, and obtain genomic data
through direct-to-consumer genetic testing companies. The downside
of this trend is that, without a medical professional to help with the inter-
pretation of the information, patients may misinterpret their genetic in-
formation, which could lead to unnecessary stress or misinformed health
decisions. Patients are now networked through social media, sharing
information on health conditions through sites like PatientsLikeMe
(http://www.patientslikeme.com) and, in some cases, bypassing the
medical establishment altogether. Crowd-sourcing, crowd-funding,
and participant-driven research are also on the rise. The direct-to-
consumer genetics company 23andMe has proven the feasibility of
web-based collection of self-reported data from an engaged cohort
of research participants that can beusedforgenomicresearchinsome
cases (154). Although these efforts are not without their caveats, in-
cluding the potential for bias and confounding leading to spurious
results (155,156), and will not replace carefully designed epidemiological
studies, they represent an innovative approach to overcoming some of
the financial and logistical constraints inherent in genomic research.
Another example of this trend is the newly launched American Gut
project (http://humanfoodproject.com/american-gut), an open-source,
community-driven effort to characterize the microbial diversity of the
American public where study subjects are recruited online and not
only participate in research but also help to fund it.
New taxonomy for disease
In the coming years, we will likely see a fundamental shift in how
disease is classified. Currently, diseases are classified on the basis of
subjective clinical signs and symptoms and, in some cases, objective
laboratory or image-based tests. Absent from this framework in
most cases is a measure of the perturbed molecular pathways that
characterize the disease. Genomics is poised to deliver molecular-
level definitions of the physiological processes underlying diseases,
suggesting treatments targeted at the molecular lesions instead of
thesymptoms.Nowhereisthismoreevidentthanincancer,where
subclassification of disease is having a tangible effect on treatment
and where tissue of origin is secondary to the molecular profile of the
tumor. The current disease classification system used in the health care
industry as a basis for diagnosis and reimbursement is the International
Statistical Classification of Diseases and Related Health Problems (ICD),
currently in its 10th revision (ICD-10) (157). The ICD-10 for oncology
already incorporates genomic factors to distinguish subtypes of can-
cer (158–160). ICD-11, the next revision, due to be published in 2015,
promises to expand this theme. Momentum on creating a new disease
taxonomy is growing, as evidenced by an extensive report on devel-
opment of precision medicine by the National Research Council of the
U.S. National Academies of Science (161) and the prioritization of
precision and personalized medicine this year by the World Economic
Forum (162).
New methods for delivering genomic medicine preemptively
Because the cost of sequencing continues to decline and the analyt-
ical issues abate, it is conceivable that individuals will have their ge-
nome sequenced at some point in their lives, perhaps even at birth.
Health systems will likely incorporate all or part of one’s genomic in-
formation into their electronic medical record. Thus, critical informa-
tion on pharmacogenetic markers of toxicity or drug response, for
example, would be available preemptively, before prescribing a drug.
This model is already being piloted in the NIH’seMERGEprogram
(163) at Vanderbilt University as part of their PREDICT initiative
(164) and at other institutions as well (165). Compared to current test-
ing practices, such an approach could provide a more cost-effective
means to capture and treat rare, preventable genetic diseases missed
by the current health care system, aid in future family planning, and
improve safety and efficacy of therapies.
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Point-of-care diagnostics and digital medicine
New ways of delivering personalized medicine are being developed for
use at the bedside and beyond. Point-of-care diagnostic tests will facil-
itate rapid diagnosis at the patient’s bedside, physicians’offices, emer-
gency rooms, and at home (166). We will see a rise in the use of digital
medicine, where patients monitor their own vital statistics at home
through sensors and handheld devices and send data directly to their
doctor (167). One day, this monitoring may include dynamic measures
of the genome including longitudinal, integrated personal “omics”pro-
files (168)orgeneexpressionchangesindicativeofexposuretoinfec-
tiousagents(169).
Rise in third-party genomic information brokers
Genome interpretive services will emerge to assist clinicians in under-
standing the meaning and actionability of genome information, much
the same way as radiologists assist in the interpretation of imaging.
This nascent field currently includes startup companies like Knome
(http://www.knome.com), Personalis (http://www.personalis.com),
Omicia (http://www.omicia.com), Genomatix (http://www.genomatix.
de), Cypher Genomics (http://cyphergenomics.com), Silicon Valley
Biosystems (http://www.svbio.com), and GenomeQuest (http://www.
genomequest.com), who are offering software, computer infrastruc-
ture, and services required to process, analyze, and store patient sequence
data and, in some cases, even produce tailored diagnostic reports.
CONCLUSION
Genomic medicine—only an aspiration 10 years ago—is beginning
to emerge across the entire clinical continuum from risk assessment in
healthy individuals to genome-guided treatment of complex diseases
in patients. Technology continues to propel the field forward, but
translating discovery into routine use is complex, requiring changes
in the fundamental processes of regulation, reimbursement, and clin-
ical practice. Progress is tempered by consideration of ethical issues
and the need to fill the education gap that exists for health care pro-
viders and consumers alike, which makes it difficult to keep pace with
advances in the field. External forces from social networking to digital
and information technologies are enabling consumers to take health
matters into their own hands, generating momentum like never before.
Today, we are on a path toward implementation of genomic medicine,
but that path is long, mired with obstacles, and potentially perilous.
Moreover, it remains to be seen whether genomic medicine will actually
improve health, when efforts to implement simpler clinical and preven-
tive strategies have failed. Nonetheless, the movement toward improv-
ing disease diagnosis and treatment with genomics is unlikely to halt
and there is reason to be optimistic. How will we know when we have
arrived? When we stop talking about genomic medicine, and refer to it
simply as medicine.
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Submitted 25 January 2013
Accepted 24 May 2013
Published 12 June 2013
10.1126/scitranslmed.3005785
Citation: J. J. McCarthy, H. L. McLeod, G. S. Ginsburg, Genomic medicine: A decade of
successes, challenges, and opportunities. Sci. Transl. Med. 5, 189sr4 (2013).
STATE OF THE ART REVIEW
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