Gail P. Jarvik, M.D., Ph.D.Arno G. Motulsky Endowed Chair Medicine and Genome Sciences

Professor and Head, Medical GeneticsUniversity of Washington, Seattle

Challenges in the implementation of genomic medicine

Genomic Medicine Obstacles  • Lack of practice guidelines / Lack of insurance coverage / reimbursement

• Need for evidence base• When it helps• How best to do it• What do all those variants mean?

• Regulatory climate / New legislation?• Lack of non-geneticist provider training• Patient/consent issues, family communication• Postmortem genome-sharing

Genomic medicine is another new technology

§ Study required to implement safely and effectively§ Harm of implementing both too fast and too slowly§ Need to evaluate best practices§ Understand economics (and convince insurers)

§ We have learned that evidence trumps “logic”p Think hormone replacement therapy

CSER Ongoing Outcomes Efforts: Steps to access to genomic medicine

Insurance Coverage

Practice Guidelines

Evidence baseResearch

Contemp Clin Trials. 2014. PMID: 24997220  

Genet Med.  2014.  PMID: 25394171

Next generation sequencing panels for the diagnosis of colorectal cancer and polyposis syndromes: a cost-effectiveness analysis.  Gallego, Shirts, Bennette,  et al.  J Clin Onc.

2015. in press

Regence Insurance Policy 64 effective (7/1/14)

§ “The following genetic panels are considered investigational because the current scientific evidence is not yet sufficient to establish how test results from panels which include a broad number of genes may be used to direct treatment decisions and improve health outcomes associated with all components of the panels.”

§ List of ALL panels, including cystic fibrosis 32 mutation panel

Exomes can save money without changing management: a case

• Patient in teens• Movement disorder early in life• Saw 12 experts in centers from Vancouver to Texas without a diagnosis

• PE: choreoathetosis and dystonia of limbs, most prominent at rest; progressed to include facial twitches and mild dysarthria

• Exome: de novo R418W (c.1252C>T) in ADCY5• Familial Dyskinesia with Facial Myokymia

• Ended diagnostic odysseyChen et al, Annals of Neurology. 

Twitter #hail_CSER

Explore, within an active clinical setting, the application of genomic sequence data to the care of patients.

> 200 clinicians involved

NHGRI’s Genomic Medicine Research ProgramProgram Goal Σ $M   Years

eMERGE II Use biorepositories with EMRs and GWA data to incorporate genomics into clinical research and care  31.1 FY11-14

eMERGE-PGx

Apply PGRN’s validated VIP array for discovery and clinical care in ~9,000 patients 9.0 FY12-14

CSER Explore infrastructure, methods, and issues for integrating genomic sequence into clinical care 66.5 FY12-16

RoR Investigate whether/when/how to return individual research results to pts in genomic research studies 5.7 FY11-13

ClinGen Develop and disseminate consensus information on variants relevant for clinical care 25.0 FY13-16

IGNITE Develop and disseminate methods for incorporating patients’ genomic findings into their clinical care  32.3 FY13-16

NSIGHT Explore possible uses of genomic sequence information in the newborn period 10.0 FY13-16

UDN Diagnose rare and new diseases by expanding NIH’s Undiagnosed Diseases Program 67.9 FY13-17

CSER U Award Study Populations

More interactive data-sets available online at 

http://cser-consortium.org/impact 

Enrollment & Germline Findings

Cases Path/LP VUS Other Yield

Cancer (Adult) 164 7 30 127 4%Cancer (Pediatric) 150 24 120 6 16%Dysmorphology 88 16 16 56 18%Heart Disease 117 27 44 46 23%Bilateral sensorineural hearing loss 34 8 12 14 24%Neurological Diagnosis 211 37 41 133 18%Retinal 55 18 13 24 33%Preconception (Carrier) 45 31 0 14 69%

Diagnostic Yield Varies by CSER Study Population

UW Randomized control trial

• N=220 over 3.5 years

Research Visit + 2 weeks+ 1 month, + 4 months, +7 months, +10 months

Various surveys 

Clinic Visit 2 

+ 2 weeks 2 Sets of Surveys

Clinic Visit 2 

+ 1 month 

1 Set of Surveys

 3 Sets of Surveys  

 

~2 Months

~14 Months

Clinic Visit 1 (Baseline)

Clinical CRCP Genetic Counseling

Consent Discussion

Blood Draw

Randomize

 

~6 Weeks

Clinic Visit 2(WES)

 Clinical and exome CRCPGenetic Test Results

Clinic Visit 2(UC)

 Clinical CRCPGenetic Test Results 

Research Visit(WES)

Discuss Incidental Findings

  

Research Visit(UC)

Review Family History

  

Usual Care 

Exome 

 

Comparing whole exome sequencing to usual care for adult patients having clinical genetic testing for hereditary colorectal cancer/polyps

So many variants, so little time§ Average persons WGS has >3.5 million

variants from a reference sequence*§ 0.6 million are rare or novel§ 400 GENES have rare or novel,

nonsynonymous (coding) variants in conserved regions

§ Guessing < 10K variants with well established pathogenic role

§ Need annotations!§ Pathogenic, Likely pathogenic, VUS, Likely

benign, benign

*Kohane, Tsing, Kong, Genet Med 2012, PMID 22323072

ClinVar National Databaseof variants

http://www.clinvar.com/

Submitter Variants GenesExpert Consortia and Professional Organizations

International Society for Gastrointestinal Hereditary Tumours (InSiGHT) 2362 8

Clinical and Functional Translation of CFTR (CFTR2) 133 1

American College of Medical Genetics and Genomics (ACMG) 23 1

Clinical Laboratories

International Standards For Cytogenomic Arrays Consortium Laboratories 14441 >14000

Partners Healthcare Laboratory for Molecular Medicine 12133 222

University of Chicago Genetic Services Laboratory 7129 600

GeneDx 6757 574

Emory University Genetics Laboratory 5192 537

Ambry Genetics 4150 47

Sharing Clinical Reports Project for BRCA1 and BRCA2 2147 2

Laboratory Corporation of America (LabCorp) 1390 140

ARUP Laboratories 1304 7

InVitae 1102 35

U. Washington CSER Program with Northwest Clinical Genomics Laboratory 625 76

University of Washington Collagen Diagnostic Laboratory 411 1

Children's National Medical Center GenMed Metabolism Laboratory 317 1

Pathway Genomics 166 17

Baylor College of Medicine Medical Genetics Laboratories 155 12

BluePrint Genetics 123 56

Counsyl 112 2

University of Pennsylvania School of Medicine Genetic Diagnostic Laboratory 68 1

Research Programs and Locus-Specific DatabasesBreast Cancer Information Core (BIC) 3734 2

Royal Brompton Hospital Cardiovascular Biomedical Research Unit

1381 10

Muilu Laboratory, Institute for Molecular Medicine Finland  840 41

ClinSeq Project, National Human Genome Research Institute, NIH 425 36

Lifton Laboratory, Yale University 389 279

PALB2 Leiden Open Variation Database 242 2

Dept of Ophthalmology and Visual Sciences, Kyoto University Hospital 171 59Dept Zoology, M.V. Muthiah Government College, India 58 3

Aggregate DatabasesOnline Mendelian Inheritance in Man (OMIM) 24973 3606

GeneReviews 4035 459

Total variant submissions to ClinVar* 149354   

Total variant submissions to ClinVar with clinical assertions*  102418   

Total unique variant submissions to ClinVar with clinical assertions *  76606   

Total genes, in submissions with assertions, with variants in one gene*            6801Total genes, in submissions with assertions, with variants across multiple genes*   17763

 

Total unique variant submissions to ClinVar with clinical assertions = 76606  (Jan 20, 2015)http://www.ncbi.nlm.nih.gov/clinvar/submitters/

Cross-CSER Annotation of 6 Variants

Site MSH6c.2731C>T; p.Arg911*

RYR1c.1840C>T; p.Arg614Cys

FBN1c.4270C>G; p.Pro1424Ala

TSC2c.736A>G; p.Thr246Ala

TNNT2c.732G>T; p.Glu244Asp

LDLRc.967G>A; p.Gly323Ser

1 Pathogenic Likely pathogenic VUS VUS VUS VUS

2 Pathogenic PathogenicLikely

pathogenic/VUS

VUS VUS VUS

3 Pathogenic Pathogenic VUS VUS VUS VUS

4 Pathogenic Pathogenic VUS VUS Likely pathogenic VUS

5 Pathogenic Likely pathogenic

Likely pathogenic/

VUS

Likely pathogenic VUS VUS

6 Pathogenic Likely pathogenic

Pathogenic/Likely

pathogenic

Likely pathogenic VUS

Likely pathogenic/

VUS

Amendola et al, Genome Research, in press

Infrastructure Needs: Get annotations into ClinVar

§ UW has multiple molecular labs§ UW Exome Lab pipelines to ClinVar§ UW Lab Med molecular tests: 1000’s of cancer

variants not submitted§ UW Collage Diagnostic Lab: 1000 of variants not

submitted§ Outside lab reports to Clinical Service

§ Completed submitting BRCA1/2§ Hundreds more not submitted

§ Insufficient resources

What if the EHR pushed annotated variants to ClinVar?

Regulatory Changes: Data Sharing, FDA

Regulatory Changes: FDA Oversight of Lab developed tests

• Proposed FDA approval of tests • Freezes the test for each approval• Includes • Analysis pipeline • Which variants have clinical utility• Applies to research

• Response to non-genetic test failures• Amer Assoc for Cancer Research: “must

be FDA-approved”• Assoc for Molec Path: “Stifle innovation

and freeze tests in time”

FDA regulations?§ For genomics where is the public health

cost-benefit? § Is it reasonable for FDA to decide what

variants mean?§ Use ClinVar (now ~77K annotated variants)

§ Mostly research labs put in annotations§ Generally only few positives and limited phenotypes§ ~228,000 genomes sequenced by researchers (2014)§ In future most genomes will be done privately

§ Wrong/outdated tool?§ Premarket vs. postmarket

Bigger idea: database of all genomic data generated§ Similar to Sentinel System

§ drug safety data for 190 million Americans§ Post-market data

§ Genetic surveillance§ Collect whole genome data and broad

phenotype data§ Follow for new disorders§ Public health use overcomes HIPAA

•Goals• What is the chance that a random person having a genomic test will find a genetic change VERY likely to cause a preventable/actionable disease?• 6503 adults (4300 European Ancestry and 2203 African Ancestry) 

• Contribute to national databases of variants (ClinVar)

Anything important in my genome?

• Definition of “actionable” gene-disease pair:• Specific, evidence-based medical 

recommendations expected to improve health outcomes

• Sufficient benefit• e.g. Lynch syndrome variant -> screening

• Find all changes in 6503 people’s genomes with literature (~700)

• Read all the literature to see if they cause disease

Steps

MEMBER EXPERTISE(s)Arno Motulsky, MD Medical Genetics, pharmacogeneticsBenjamin Wilfond, MD Pediatrics, bioethicsBrian Shirts, MD PhD Molecular pathologyCarlos Gallego, MD Medical geneticsDebbie Nickerson, PhD GenomicsFuki Hisama, MD Medical Genetics, Neurology, Pediatrics, AdultGail Jarvik, MD PhD Medical genetics, Internal Medicine, genomics, bioethicsJames P Evans, MD PhD Medical genetics, Internal Medicine, genomicsJeff Murray, MD PhD Medical genetics, PediatricsJerry Kim, MD Anesthesiology, genetics Jonathan Berg, MD PhD Medical genetics, cancer and adult genetics Katherine Leppig, MD Medical genetics, cytogenetics, eMERGE RORC

 Laura Amendola, MS CGC Genetic counselor, cancer geneticsMichael Dorschner,  PhD Molecular diagnostics , GenomicsMitzi Murray, MD Medical genetics,  collagen/vascular, molecular diagnostics

Peter Byers, MD PhD Medical genetics, collagen/vascular, molecular diagnostics

Robin Bennett, MS CGC Genetic counselor, cancer geneticsRon Scott, MD Medical genetics, biochemical geneticsS. Malia Fullerton, PhD Bioethics, eMERGE RORCThomas Bird, MD Neurogenetics, NeurologyVirginia Sybert, MD Medical & Dermatological Genetics, Turner syndromeWendy Raskind, MD PhD Medical Genetics, General Int. Med, cancerWilliam Grady, MD Gastroenterology, Cancer, geneticsWylie Burke, MD PhD Medical genetics, internal medicine, bioethics

ROR committeeNEXT Medicine Return of Results Committee, September 2012

Genes with Actionable Variants relevant to Adults

=112 TotalGenes

(a)Highlighted genes are recommended for return by the American College of Medical Genetics and Genomics guidelines.

Dominant X-LinkedACTA2a KCNQ1 RBM20 DMDACTC1 KIT RET EMDACVRL1 LDLR RYR1 GLAAPC LMNA RYR2 OTC

BMPR1A MAX SCN5A  BRCA1 MEN1 SDHAF2 RecessiveBRCA2 MET SDHB ATP7B

CACNA1C MLH1 SDHC BCHECACNA1S MLH3 SDHD BLMCACNB2 MSH2 SERPINC1 CASQ2CDC73 MSH6 SGCD COQ2CDH1 MUTYH SMAD3 COQ9CNBP MYBPC3 SMAD4 CPT2

COL3A1 MYH11 SMARCB1 F5DMPK MYH7 STK11 GAADSC2 MYL2 TGFB2 HAMPDSG2 MYL3 TGFB3 HFEDSP MYLK TGFBR1 HFE2ENG NF2 TGFBR2 IDUA

EPCAM PDGFRA TMEM127 LDLRAP1FBN1 PKP2 TMEM43 PAHFH PLN TNNI3 PCBD1

FLCN PMS2 TNNT2 PTSGCH1 PRKAG2 TP53 QDPRHMBS PRKAR1A TPM1 SERPINA1KCNE1 PROC TSC1 SLC25A13KCNE2 PROS1 TSC2 SLC37A4KCNH2 PTCH1 VHL SLC7A9KCNJ2 PTEN  

Pathogenic

Segregation* in >= 2 unrelated familiesOR2 of 3:1. Segregation * in 1 family2. Identified in >= 3 unrelated individual3. De novo event in trioORProtein truncation known to cause diseaseANDBelow allele frequency cut off

Likely pathogenicIdentified in >= 3 unrelated individualsORSegregation*  in 1 familyOR De novo event in trioANDBelow allele frequency cut off

Classification criteria  (strict for IFs)

*1/16 probability cut-off to define segregation

Expected rate of actionable variants:Exome Variant Server (EVS) Results by Ancestry Group

Participants with classification

European ancestry*N=4300

African ancestryN=2203

Disease causing variants (known) 30 (0.7%) 6 (0.3%)Likely disease causing variants (known) 52 (1.2%) 13 (0.6%)

Disease causing variants (novel disruptive) 

6 (0.1%) 6 (0.3%)

Total (Includes LP) 88 (2.0%) 25 (1.2%)

*Caveats:  No CNV included; only 3% AshkenaziAmendola et al, Genome Research, 2015. PMID: 25637381

§ Blind double/triple review for QC.

§ Step 1: Random 25% of 615: § 83/156 (53%) of all variants discrepant

§ Step 2: All pathogenic & likely pathogenic variants: § 44/79 (56%) discordant; § 42/44 (95%) overcalled (final call VUS) 

§ Of 52 reviewers, a few made systematic errors -> all recalled. Errors at all expertise levels.

Variant Classification QC: Overcalling

P & LP Variants Double Reviewed

79

DiscordantClassification

44

ConcordantClassification

35

VUS42

P2

Revised Classification

Final CSER calls match other experts

§ 45/45 (100%) match with Sharing Clinical Reports Project (SCRP)

§ 97/99 (98%) match with Partners Laboratory for Molecular Medicine (LMM)

CADDKircher et al. Nat Genet 2014, PMID 24487276

GERP++  Davydov et al. Plos Comput Biol 2010, PMID 21152010

GERP vs. CADD scores of pathogenic & likely pathogenic dominant variants 

(excluding disruptive variants) 

Expected rate of actionable variants:6503 Exome Variant Server (EVS) Results by Ancestry 

GroupParticipants with classification

European ancestry*N=4300

African ancestryN=2203

Disease causing variants (known) 30 (0.7%) 6 (0.3%)Likely disease causing variants (known) 52 (1.2%) 13 (0.6%)

Disease causing variants (novel disruptive) 

6 (0.1%) 6 (0.3%)

Total 88 (2.0%) 25 (1.2%)

*Caveats:  No CNV included, HIGHER in AshkenaziAmendola et al, Genome Research, in press

Physician Education Vignette§ CYP2C9 c.430C>T warfarin sensitivity result returned

to a research participant (affects starting dose)

§ Email ~1 month after return “The NEXT study indicated I have a moderate sensitivity to Warfarin, the generic Coumadin.  With that information, I switched to Rivaroxaban (Xarelto), one of the new blood thinner drugs, to mitigate that sensitivity. The NEXT  study provided this useful information that I acted on…I feel very fortunate to have been able to have been  able to be a part of the NEXT study and benefit from its results”

§ Plan: interview primary care physician re experience

Patient/Consent issues

§ Explain test / Incidental findings§ EHR communication§ Family communication

Why is a genetic test different?§ The genetic results on 1 family member can affect the medical care of other family members

§ Other family members may share the same genetic alterations

§ You may be able to show that the other family members do NOT share concerning alleles

§ Need to test affected person§ Most benefit if information is shared

A real case§ Patient with >1 cancer at early age seen by genetics (large family, but no kids)

§ Genetic test agreed to and ordered for next blood draw

§ Patient unexpectedly decompensates, is not conscious, and not expected to survive > 24 hrs

§ 7 siblings and 2 geneticists converge in hospital§ Family meeting:  Do test?  Who do you tell?

A real case (continued)§ Large family meeting + 2 geneticists + nurse

§ >>1 hour§ Genetics communicates patient desire to share this information with family

§ Family uniformly interested§ Family elects single representative to interact with genetics

§ Blood drawn hours before  patient died without gaining consciousness

§ Test results shared with contact member

What is good about this case?§ Everyone knew the patient had a bad disease§ Most knew it might be genetic (no family history)§ We could educate most of the family on what we were doing and why

§ General consensus to test§ General consensus on who should be the main point of contact

§ Each of these could have gone the other way

Why ask about preferences?

Everyone is different and its not easy to predict their wishes

Wide Range of Preferences (for IFs)§ Some wanted to know all information

§ “I’d want to know everything. I’d want no sugar coating at all.”§ Other interested in findings that are ‘actionable’ (broadly construed) or certain§ “I think if I could be treated I would want to know, but if it’s

something that they may not be able to treat or if it’s something that they can’t guarantee that I’m going to get or the percentage is like 50/50, then I have to just live wondering about this.”

§ Others wary of genomic information§ “I just think you could go nuts treating all these little

possibilities. I mean it just seems like there would be no end to, I don’t know, trying to research what you should be eating or not eating for this condition. I would go crazy.”

§ Preferences dependent on prior test results?

Consent form languageResearch Participant’s  Authorization: I am a participant in the NEXT (New ExomeTechnology in) Medicine study. I authorize the Principal Investigator, Gail P. Jarvik, MD to allow for the disclosure of my genetic research results to the named person below in the event that I should die or become incapacitated before receiving all genetic research results myself. I understand that my genetic records may contain DNA test results related to my risk to develop genetic conditions and/or may explain why I have a genetic disease. The results are termed “genetic incidental findings” that derive from whole exome sequencing of my DNA. Genetic results information is important for my blood relatives to learn as we share similar genetic material.This form will be destroyed when all study related genetic results from the NEXT Medicine study are given to me personally. I give my specific authorization for my genetic results derived from usual care tests or whole exome sequencing tests to be released to the recipient named below: Yes___ No___ (initial your choice) This authorization is valid until _________  ( date) OR until the end of the NEXT Medicine study___________ 

Should we return genomic results to someone if you are deceased? 

§ 75 enrolled, 44 male, 31 female

§ 69 yes ( 92%) vs. 6 no return

§ If no: p 4 no biological family or contact

p 2 (3% of 75) want to decide after results are returned (TRUE NO)

Who to return genomic results to, if not me?

Participant

Return to spouseN (%)

Return to male 

relativeN (%)

Return to female relativeN (%)

TotalN 

Female         16 (61.5%)  2 (7.7%) 8 (30.8%)  26

Male 29 (67.4%) 3 (7.0%) 11 (26.6%) 43

Total 45 (65.2%)  5 (7.3%) 19 (27.5%) 69

Who should we return to?§ Of yes: 45/69 (65%) to spouse, 24/69 (35%) to first/second degree relatives

§ Of those 45 selecting spouse 

p 24 had kids age <=25 yo

p 6 no kids 

p 11 at least 1 kid > 25 yo

p 4 data pending

p Spouse: could ‘handle’ the information best and make sure it gets to the right person(s), although it has no impact on the spouses person’s health

p Spouse can manage information for children

Return to non-spouse§ Of 24 naming a first/second-degree relative

§ 19 named women (p=0.0025)

p 10 sister, 6  daughter, 2 mother, 1 grandmother

§ 9 had spouses/partners—all selected women

§ 5 named a man (2 brother, 3 son)

p 2 of 5 are women

p 4 of 5 did not have a daughter

p 4 of 5 had deceased mothers

p 2 of 5 selected men over women (son v. daughter, brother v. sister)

§ Most but not all want to share§ Usual medical care rarely seeks out family members to share information-genetics may differ§ Next of kin CAN access medical records, but may not know there is valuable information there.  

§ They may not have access to research data.

§ May not be selecting legal next-of-kin or executor

Postmortem return implications

Genomic Medicine Obstacles • Lack of practice guidelines / Lack of

insurance coverage• Need for evidence base• When it helps• How best to do it• What do all those variants mean?

• Regulatory climate / New legislation?• Lack of non-geneticist provider training• Patient/consent issues, family

communication• Address postmortem return

Gail JarvikDebbie NickersonDavid VeenstraWylie BurkeMalia FullertonMichael DorschnerDonald PatrickPeter ByersDean RegierFuki HisamaPeter Tarczy-HornochPatrick HeagertyBrian BrowningBarbara Evans, JDCarlos GallegoChris NefcyClinical review committee

Thank you, UW Next Medicine Team Laura AmendolaMartha Horike-PyneSue TrinidadBryan Comstock Amber BurtDavid Crosslin Jerry KimDaniel Kim Sara CarlsonJane Ranchalis Emily TurnerJosh Smith Brian Shirts Robin Bennett Adam GordonSara Goering Carrie BennetteElizabeth HopleyBryon PaeperJeff FurlongPeggy Robertson Katie IgartuaDebbie Olson

Funded by NIH,NHGRI & NCI (U01HG006507, U01HG006375, 5T32GM007454), WA State Life Sciences Discovery Fund (265508, NWIGM); EVS data supported by NHLBI

Elisabeth RosenthalKelly Jones Mari TokitaJimmy Bennett Colin Pritchard Tom Walsh Wendy Raskind

Learning Health Care System, e.g.

• UW Return of Results Committee• How to classify challenging variants• What IFs are returned (Gene-dz pairs)• EHR report formatting• EHR clinical decision support• Content• Usage

• All variant classifications pushed to ClinVar

e.g. (in packet) Dorschner MO, Amendola LM, Shirts BH, Kiedrowski L, Salama J, Gordon AS, Fullerton SM, Tarczy‐Hornoch P, Byers PH, Jarvik GP. 2014. Refining the structure and content of clinical genomic reports. Am J Med Genet Part C Semin Med Genet 166C:85–92.