Transcript The Ins and Outs of Gene Testing in Clinical Medicine

Clinical Applications of Whole
Genome/Whole Exome Sequencing
Robert L. Nussbaum, MD, FACMG
Division of Genomic Medicine, UCSF
AMA – November 11, 2012
Conflict of Interest Disclosures
Chair of Genomic Medicine Advisory
Board of Complete Genomics, Inc.
Mythical Scenario
A newborn blood spot undergoes whole
genome sequencing. It is analyzed for
• Personal risk for a Mendelian disorder (BRCA1)
• Pharmacogenetic variants that predict efficacy, side-effects,
adverse reactions (CYP2C19 and clopidogrel)
• Risk for carrying mutations that future children at risk (TaSachs carrier)
• Tissue-type and Blood type (HLA, ABO)
• Variants (rare and common) that increase risk for common
disorders (CFH and macular degeneration)
All the results are recorded in an EMR,
communicated to his health care providers, and
used to guide health care over the lifespan
Outline
• Whole Genome and Whole Exome Sequencing
• Factors Impeding Implementation of
WGS/WES sequencing
– Limits of the Technology
– Limits of Knowledge
– Limits of Genetic Determinism
Evaluating A Genetic Test
Patient Sample
Right result from the right
patient
Analytical Validity
Test has predictive value for
patient care
Clinical Validity
Results have value for the
patient and doctor
Clinical Utility
There is value to society in
generalizing the testing
Social Utility
(“Actionability”)
Whole Genome Sequencing (WGS)
CLIA ’88 Test Performance Metrics
Reportable Range:
Portion of the genome from which sequence
information can be reliably derived from WGS =
~96.5%
Reference Range:
•
•
•
Homopolymers, di- and tri-nucleotide repeats, microsatellites
Deletions and duplications ~ 100-500 bp
Single nucleotide variants sitting at the end of homopolymers
Are outside the typical Reference Range of WGS
Whole Exome Sequencing (WES) by
Exon Capture
Elute
Sequence
What Do You Miss With
Whole Exome Sequencing?
5’-UTR
Start
3’-UTR
Stop
~3-5% of Exons, Promoters, Untranslated
Regions, and the Bulk of Intron Sequences
are not Included in Exome Sequencing
Why Do WES Rather Than WGS?
• Because you only sequence ~2% of the
genome, what you do sequence is
covered to tremendous depth
• You are sequencing the part of the
genome we are better at interpreting
• Current cost of WES is ~$750-$1000
versus $4,000-$10,000 for WGS
HOWEVER………
How Good are WES and WGS at
Identifying Variants?
Because of False Positives, neither approach
provides stand-alone “clinical grade” sequencing
at the present time and Variants need to be
confirmed by conventional sequencing
Increases the cost tremendously
WES for research = $750
WES for Clinical Use = $8,000 -10,000
Variants in Whole Genome Sequence
~100
essential
splice site
SNVs
~430 premature
stops and frameshift Indels
~7,500 non-synonymous
SNV and in-frame Indels
in Exons
~3,400,000 SNV and Indels
85% are
rare
“The” Human Genome
• There is no such thing – there are only Human
Genomes
• There is a “Reference Genome” in databases
but it is incomplete
• Variants are defined as differences from the
Reference
• The more we learn, the more we realize that
there are alternative Reference Genomes
Evaluating A Genetic Test
Patient Sample
Right result from the right
patient
Analytical Validity
Test has predictive value
for patient care
Clinical Validity
Results have value for
the patient and doctor above
and beyond current practice
There is value to society in
generalizing the testing
Clinical Utility
(“Actionability”)
Social Utility
Clinical Validity
• Positive Predictive Value
Given a + test, how frequently does the patient
have, or how frequently will he develop the
disease? (“Penetrance”)
• Negative Predictive Value
Given a – test, how frequently is the patient
unaffected and will remain so?
The Reason for the Test Matters
“Screening” a healthy executive for variants
in her DNA that might be of interest
Versus
“Scanning” a child with a serious disorder
for variants in her DNA that might explain
the disease and suggest therapy
Genome-Wide Association Studies in
Eight Common Diseases
SNPS in a
Region on Chr 9
are associated
with CAD at
P < 10-15
Odds of Developing CAD
Depending on 9p21 Genotype
Palomaki et al.
PPV for 9p21 Genotype for CAD
Risk for Coronary Artery Disease
Events over the Next 10 Years
9p21Genotype
Unknown
65 year old male
No CAD risk factors
40 year old female
No CAD risk factors
Palomaki et al.
2 Risk
Alleles
0 Risk
Alleles
11%
13.2%
9.2%
2%
2.4%
1.7%
Combine 13 SNP Loci To Generate
Genetic Risk Score for CAD
Sipatti et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses,
The Lancet Volume 376, Issue 9750, Pages 1393-1400 (October 2010)
Fraction of the Population
Established Common Breast-Cancer
Susceptibility Alleles.
Pharoah PD et al. N Engl J Med 2008;358:2796-2803.
Distribution of Genetic Risk in the Population:
Seven Breast Cancer Risk Alleles
(Avg. risk allele freq. = ~0.35)
20,000 of 10M carry BRCA1/2 mutations
56 of 10M UK
women carry 14
low risk alleles
(0.00056%)
7 of 10M UK
women carry 14
high risk alleles
(0.00007%)
Assuming a multiplicative model for interaction between these alleles
Pharoah P et al., N Engl J Med 2008; 358:2796-803.
Evaluating A Genetic Test
Patient Sample
Right result from the right
patient
Analytical Validity
Test has predictive value
for patient care
Clinical Validity
Results have value for
the patient and doctor above
and beyond current practice
Clinical Utility
There is value to society in
generalizing the testing
Social Utility
(“Actionability”)
Clinical Utility of Genetic Testing
•
•
•
•
•
•
Explain why a disease occurs
Institute preventive measures
Anticipate and prevent complications
Affect choice of therapy
Avoid adverse reactions
Determine risk in other family members
or in future offspring
Clinical Pharmacogenetics
Implementation Consortium
Gene-Drug Pairs
TPMT - thiopurines
HLA-B - allopurinol
CYP2C19 - clopidogrel
G6PD - rasburicase
CYPC2C9, VKORC1 - warfarin
UGT1A1 - irinotecan
CYP2D6 - codeine
IL28B - pegintron
DPYD – 5FU/capecitabine
SLCO1B1 - simvastatin
HLA-B - abacavir
CYP2D6, CYP2C19 – TCAs
HLA-B - carbamazepine
CYP2D6 - SSRIs
HLA-B - phenytoin
Individuals with 1 or more CYP2C19 alleles
CYP2C19
not activity
associated
associatedgenotype
with lowerwas
enzyme
had
• lower
levels of active
clopidogrel
metabolites
with
modification
of the
effect of
• less platelet
clopidogrel
oninhibition
CVD end points or
• lower risk of bleeding
bleeding…Overall
there was no
significant association of genotype
with cardiovascular events
Clinical Validity ✔
Clinical Utility ?
Actionability: In the Eye of the Beholder
What is “Actionable Information”?
How does it differ from Clinical Utility?
• Information with high Clinical Validity
• Information that allows a medical decision to
be made or therapeutic action to be taken (or
not).
• Founded on evidence (A real problem in
genetics where diseases are rare)
• Information that informs an individual and
helps him/her make health decisions
“Actionability” Rating
Berg J. et al. Genetics IN Medicine • Volume 13, Number 6, June 2011
Conclusions
1. Genetic Testing is often not straightforward and
requires substantial interpretation
2. We do not know how to interpret a lot of
genetic information
3. Genetic Testing is not static and what a result
means can change over time.
WES/WGS only magnify the problems enormously
Barriers to the adoption of
pharmacogenetic tests in clinical practice
• Fragmentation of health-care systems that
preclude linking a “lifetime” genetic test result
with future medical care (exception: the VA)
• Limited use of electronic medical records vital to
linking test results with medication
prescribing/dispensing
• Health-care systems that do not reward the
prevention of disease (or adverse drug effects),
Barriers to the adoption of
pharmacogenetic tests in clinical practice
• Lack of sufficient awareness about genomics on
the part of many clinicians,
• Little of such testing is done preemptively and
therefore the results are not available when the
prescribing decision is made.
Some of these barriers will persist for
many years to come.