Heidi Rehm on behalf of ClinGen

ClinGen Clinical Genome Resource

Improving our knowledge of genomic variation will require a

massive effort in data sharing and collaborative curation

ClinGen NIH Groups and Funded Grants

NCBI ClinVar

Melissa Landrum Donna Maglott

Steve Sherry

NIH Programs Erin Ramos (NHGRI) Lisa Brooks (NHGRI)

Danuta Krotoski (NICHD) Sheri Schully (NCI)

U41 Grant – Partners/ Geisinger/UCSF David Ledbetter Christa Martin Bob Nussbaum

Heidi Rehm

U01 Grant - UNC/ ACMG/Geisinger

Jonathan Berg Jim Evans

David Ledbetter Mike Watson

U01 Grant - Stanford/Baylor

Carlos Bustamante Sharon Plon

www.clinicalgenome.org >200 people from >75 institutions

ClinGen Steering Committee Provides feedback to working groups on their progress and

serves as the voting body for ClinGen policy-and project-wide related matters.

IT Standards & Data Submission Facilitating the submission of data to public

repositories such as ClinVar.

Gene Curation Developing evidence-based methods for evaluating gene-disease associations to support gene curation

activities across the ClinGen project.

Education, Engagement, Access Fostering community engagement in all aspects of the ClinGen project through

education, outreach, and resource development

Consent and Disclosure Recommendations Committee

(CADRe) Exploring the ethical, legal, and social (ELSI) issues relating to reporting the actionability of particular genes and variants in the clinical care process.

Electronic Health Records (EHR) Integration

Ensuring that the ClinGen resource is designed to be accessible to providers and patients through electronic health

record and related systems.

Genomic Variation • Sequence Variant Interpretation

Approach • Gene Dosage Curation • Sequence Variant Conflict Resolution • Structural Variant Conflict Resolution

Standards & Data Collection

Phenotyping Supporting the collection and submission of

phenotypic data to ClinGen-related resources.

Data Modeling Providing a common set of definitions and

consistent representation of core concepts, attributes, and terminology to support ClinGen

and harmonize with relevant efforts.

Allele Registry

Individual Level Database

Machine Learning Algorithms

Education & Outreach

Curation & Consensus

Informatics & Analysis

ClinGen Portal NCBI & ClinVar Team

Actionability Identifying those human genes that, when

significantly altered, confer a high risk of serious disease that could be prevented or mitigated if the

risk were known.

Cardiovascular Disease

Somatic Cancer

Inborn Errors of Metabolism

Hereditary Cancer

Pharmacogenomics

Curation Pilots: • Noonan Spectrum Disorders • Developmental Delay, • Mowat-Wilson Syndrome • PKU, MCAD • Pheochromocytoma &

Paraganglioma, Pancreatic Cancer, PTEN

• Cardiomyopathy, Channelopathies

Curation Interface (Gene & Variant)

ClinGenKB

Clinical Domains Creating a comprehensive, standardized

knowledge base of genes and variants relevant for high-priority disease areas

ClinGen Working Groups

The Clinical Genome Resource

ClinGen Website: www.clinicalgenome.org

Key Principle of ClinGen Variant Sharing

• Enable immediate and unrestricted access to variant-level data (e.g. interpreted variants)

• Apply expert consensus approaches over time

ClinGen position statement of restricted access/licensed databases: http://www.clinicalgenome.org/site/assets/files/2235/position_statement_on_licensed_databases_formatted.pdf

ClinVar: ClinGen’s Variant Repository

Variant-level Data ClinVar

Linked Databases

Researchers Clinics Patients

Sharing Clinical Reports Project

Genome Connect and Free-the-Data

Patient Registries

Clinical Labs

Unpublished or Literature Citations

InSiGHT

CFTR2 OMIM

Expert Groups

>315 ClinVar submitters >172,000 submissions >118,000 unique interpreted variants

BIC

PharmGKB

M. Landrum D. Maglott J. Lee G. Riley

ClinVar submitters with >50 interpreted variants Submitter # of Variants

Expert Consortia and Professional Organizations International Society for Gastrointestinal Hereditary Tumours (InSiGHT) 2362 Clinical and Functional Translation of CFTR (CFTR2) 133 American College of Medical Genetics and Genomics (ACMG) 23

Clinical Laboratories International Standards for Cytogenomic Arrays (ISCA) Consortium 14440 Partners Healthcare Laboratory for Molecular Medicine 12040 GeneDx 11038 University of Chicago Genetic Services Laboratory 7158 Emory University Genetics Laboratory 6944 Ambry Genetics 4150 Sharing Clinical Reports Project for BRCA1 and BRCA2 2147 Laboratory Corporation of America (LabCorp) 1390 ARUP Laboratories 1374 InVitae 1134 Blueprint Genetics 651 U. Washington CSER Program with Northwest Clinical Genomics Laboratory 646 University of Washington Collagen Diagnostic Laboratory 411 Children's National Medical Center GenMed Metabolism Laboratory 317 Baylor College of Medicine 235 Pathway Genomics 189 Counsyl 112 Greenwood Genetic Center Diagnostic Laboratories 80 U. of Pennsylvania School of Medicine Genetic Diagnostic Laboratory 68

Research Programs and Locus-Specific Databases Breast Cancer Information Core (BIC) 3734 Royal Brompton Hospital Cardiovascular Biomedical Research Unit 1346 Muilu Laboratory, Institute for Molecular Medicine Finland 840 ClinSeq Project, National Human Genome Research Institute, NIH 425 Lifton Laboratory, Yale University 389 PALB2 Leiden Open Variation Database 242 Dept of Ophthalmology and Visual Sciences, Kyoto University Hospital 171 King Faisal Specialist Hospital and Research Centre Developmental Genetics 105 Dept Zoology, M.V. Muthiah Government College, India 58

Aggregate Databases Online Mendelian Inheritance in Man (OMIM) 25044 GeneReviews 4006

ClinVar Content Continues to Climb

10 Courtesy of Melissa Landrum

Expert Panel

Single Submitter – Criteria Provided

Single Submitter – No Criteria Provided

Multi-Source Consistency

Practice Guideline

No stars

No Assertion Not applicable

Assertion Levels in ClinVar

ACMG, CPIC

CFTR2, InSiGHT, PharmGKB, ENIGMA

Distinction Launching in June

11% (12,895/118,169) of variants have ≥2 submitters in ClinVar

17% (2229/12,895) are interpreted differently

ClinVar Variant Database

ClinVar Data from May 4th, 2015

ClinVar Variant View

Emory LMM Chicago

60 variants (3-Level)

22 variants (Confidencedifferences)

43 variants consistent

17 variants still discrepant

8 variants (Confidencedifferences)

14 variants (3-Level)

3 variants consistent

11 variants still discrepant

Discrepancy Identification

Variant Reassessment

Main reasons for discrepancies was variant classification rules • Novel silent: LB vs VUS • Missense (freq cut-offs; MOI)

Discussion between labs

1/104 differences need expert panel input

104 differences

28 differences

Work of: Birgit Funke Steven Harrison Melissa Kelly Lori Bean Amy Knight Madhuri Hegde

www.acmg.net

Genomic Variant WG

Gene Dosage Curation

Task Team

Sequence Variant Interpretation

Rules Task Team

Interlab Seq Var Discrepancy Resolution Task Team

Interlab Str Var Discrepancy Resolution Task Team

Noonan Spectrum

Pilot Project

Developmental Delay Pilot

Project

Mowat-Wilson Pilot Project

Congenital Muscular

Dystrophy Pilot Project

Swaroop Aradhya

Erik Thorland

Les Biesecker

Marc Greenblat

Steven Harrison

Jill Dolinsky

Lisa Vincent

Sherri Bale

Madhuri Hegde

Soma Das

Expert Curated Variants

ClinVar

Variants

Linked Databases

Clinics Patients

Sharing Clinical Reports Project

Genome Connect and Free-the-Data

Patient Registries

Clinical Labs

Unpublished or Literature Citations

InSiGHT

CFTR2 OMIM

Expert Groups

BIC

PharmGKB

Curation Interface

Cardiovascular Disease WG

Inborn Errors of Metabolism WG

Hereditary Cancer WG

PGx WG

Case-level data store

Somatic Cancer WG

Machine-learning algorithms Data resources

ClinGenKB

Researchers

Data Flows in ClinVar and ClinGenKB

ClinGen System Map Marc Williams

Infrastructure Development Allele Registry

Pathogenicity Calculator Curation Apps

ClinGenKB

Data Model WG

Allele information (from Allele Registry and other sources) Conclusions and rule-based justifications Evidence about the link between the allele and disease condition(s) 5/11/2015 CLINGEN INFORMATICS WG PRESENTATION BY ALEKS

MILOSAVLJEVIC, BCM 21

Scope of CSER Variant Bakeoff Project

9 participating CSER labs

11 variants submitted by each lab = 99 variants total • One each for B/LB/VUS/LP/P; 6 variants of any category • Diversity of types of evidence and level of difficulty • Variants selected before evaluation by ACMG rules

9 variants (one from each site) were evaluated by all 9 labs - 81 unique interpretations 90 variants have each been reviewed by 3 labs - analysis pending

Intra-laboratory Classification Comparison

Laboratory class Total P LP VUS LB B

ACM

G c

lass

P 13 0 2 0 0 15 LP 3 18 2 0 0 23

VUS 0 3 14 7 1 25 LB 0 0 1 10 3 14 B 0 0 0 0 4 4

Total 16 21 19 17 8 81

0 10 20 30 40 50 60 70

ACMG 2 steps more certain

ACMG 1 step more certain

Concordant Lab 1 step more certain

Lab 2 steps more certain

ACMG rules slightly more conservative

Inter-laboratory Concordance

0

1

2

3

4

5

6

Complete concordance

Concordant except for confidence

(LP/P or LB/B)

1 step discordance (VUS/LB or

VUS/LP)

2 step discordance

(1 site)

2 step discordance (2 or more

sites)

3 step discordance

ACMG

Lab

ACMG rules lead to slightly more concordance

Cardiovascular Co-chairs

Birgit H. Funke, PhD, FACMG Assistant Professor, Harvard Medical School

Euan Ashley, MD, PhD Associate Professor of Cardiovascular Medicine, and of Genetics, Stanford University

Cardiomyopathy Channelopathies

Chris Semsarian, MD, PhD University of Sydney/Royal

Prince Alfred Hospital

Bill McKenna, MD University College London

Peter van Tintelen, MD, PhD University Medical Center Groningen

MFS/Aortopathies

Silvia Priori, MD, PhD NYU Langone Medical Center

Mike Gollob, MD University of Ottawa Heart Institute

Diana Milewicz, MD UT Medical School at Houston

Julie De Backer, MD, PhD Ghent University Hospital

Bart Loeys, MD University Hospital of Antwerp

Harry Dietz, MD Johns Hopkins School of Medicine

Ray Hershberger, MD Professor of Cardiovasc- ular Medicine, Director, Division of Human Genetics, The Ohio State University

Hereditary Cancer Co-chairs

Matthew Ferber, PhD Assistant Professor of Laboratory Medicine and Pathology Mayo Clinic

Sharon Plon, MD, PhD Professor of Pediatrics and of Molecular and Human Genetics Baylor College of Medicine

Ken Offit, MD Chief, Clinical Genetics Service Memorial Sloan Kettering Cancer Center

Fergus Couch, PhD Mayo Clinic

Marc Greenblatt, MD University of Vermont

Madhuri Hegde, PhD, FACMG Emory School of Medicine

Ludwine Messiaen, PhD University of Alabama

Katherine Nathanson, MD University of Pennsylvania

Working Group members

Sharon Savage, MD National Cancer Institute

Sheri Schully, PhD National Cancer Institute

Inborn Errors of Metabolism Co-Chairs

William J. Craigen, MD, PhD Baylor College of Medicine

Rong Mao, MD ARUP Laboratories, University of Utah

Robert D. Steiner, MD Marshfield Clinic Research Foundation

Jonathan Berg, MD, PhD University of North Carolina

Steven F. Dobrowolski, PhD University of Pittsburgh

Karen Eilbeck, PhD University of Utah

Gregory Enns, MD Stanford University

Uta Lichter-Konecki, MD Columbia University

Working Group members

Marzia Pasquali, PhD ARUP Laboratories, University of Utah

Elaine Lyon, PhD ARUP Laboratories,

University of Utah

Annette Feigenbaum, MD Rady Children’s Hospital

Pharmacogenomics Co-chairs

Working Group members

Teri Klein, PhD Co Principal Investigator, Stanford University Director, PharmGKB

Howard McLeod, PharmD Director, DeBartolo Family Personalized Medicine Institute Moffitt Cancer Center

Uli Broeckel, MD Medical College of Wisconsin

Josh Denny, MD, MS Vanderbilt University

Mary Relling, PharmD St. Jude Children’s Hospital

Stuart Scott, PhD Mt. Sinai School of Medicine

Gillian Bell, PharmD Moffitt Cancer Center

Marc Williams, MD Geisinger Health System

Michelle Whirl-Carrillo, PhD Stanford University

Somatic Cancer Co-chairs Working Group members

Shashi Kulkarni, PhD Washington University

School of Medicine

Subha Madhavan, PhD Georgetown University

Eli Van Allen, MD Dana-Farber

Cancer Institute

Barbara Conley, MD National Cancer

Institute

Carolyn Hutter, PhD NHGRI

John Iafrate, MD Mass General

Hospital

Marilyn Li, MD Baylor College of

Medicine

Peter McGarvey, PhD Georgetown

University

Howard McLeod, PharmD

Moffitt Cancer Center

Christine Micheel, PhD

Vanderbilt

Vincent Miller, MD Foundation Medicine

Will Parsons, MD, PhD

Texas Children’s

Nirali Patel, MD University of

North Carolina

Angshumoy Roy, PhD, Baylor College of

Medicine

Sameek Roychowdhury, MD, PhD, OSU

Richard Schilsky, MD

ASCO

Sheri Schully, PhD National

Cancer Institute

Christine Walko, PharmD

Moffitt Cancer Center

Mike Watson, PhD ACMG

Not Pictured: Annette

Meredith, PhD, MPL

Jason Merker, MD, PhD, Stanford

Clinical Domain WG Charges

• Define the genes with valid association to a human disease

• Define variants with valid evidence for pathogenicity and those with benign impact

• Define rules for interpreting novel variants

Birgit Funke will present progress of the Cardiovascular Clinical Domain WG

Gene-Disease Validity Classification*

31

*Detailed criteria available online: http://www.clinicalgenome.org/knowledge-curation/gene-curation/

Co-Chairs Jonathan Berg

Christa Martin

Assertion criteria Definition 0 1 2 3 4 5

# of case or case-control studies

# of Independent publications identifying human mutations in the gene in association with disease (Functional data is not required to be in the publication)

0 1 2 3 4 5+

# Probands Total # of unrelated probands with convincing pathogenic variants across all curated literature 0 2 4-6 7-9 10-12 13+

# Functional studies/assays

# Functional studies/assays that support gene-disease association at the gene level (one publication can provide more than one level of functional evidence. ie mouse model AND biochemical interactions in a pub can count as “2”)

0 1 2 3 4 5

COLUMN TOTAL 0 3 0 0 4 0

Refuting Evidence Is there Valid evidence that refutes the association? Y/N? N

TOTAL 7 Assertion: LIMITED

Strength of Evidence

Example: WRAP53: Dyskeratosis Congenita

Classification Total Score Limited: 0-8 Moderate: 9-12 Strong: 13-16 Definitive: 17-20

Gene-Level Evidence Collection Published Clinical Information

~50% of genes on clinical multigene panels for hereditary pheochromocytoma /paraganglioma demonstrate only limited

evidence for association with the disease.

Courtesy of Sharon Plon and the Hereditary Cancer WG

Ahmad Abou Tayoun

HL OtherACTG1 3 AD M X3 X2 Postlingual, progressive sloping SNHL Baraitser-Winter syndrome

ATP6V1B1 3 AR M, LOF X Childhood onset, progressive sloping SNHL Distal renal tubular acidosisBSND 3 AR M, LOF X1 X3 Prelingual, severe to profound, flat SNHL Bartter SyndromeCABP2 2 AR LOF X Prelingual, moderate to sever, cookie-bite SNHL

CACNA1D 2 AR LOF X Congenital, severe to profound, flat SNHL Bradycardia and deafnessCCDC50 2 AD LOF X Postlingual, progressive, moderate to profound SNHLCDH23 3 AR M, LOF X3 X3 Congenital, moderate to profound SNHL Usher type 1

CEACAM16 2 AD M X Postlingual, progressive, moderate SNHLCIB2 3 AR M X3 X1 Prelingual, severe to profound, flat SNHL Usher type 1J

CISD2 3 AR M/LOF X Variable onset, progerssive SNHL WFS2CLDN14 3 AR M, LOF X Prelingual, flat SNHL (variable progression)

CLPP 3 AR M, LOF X Congenital, severe to profound, flat SNHL Perrault SyndromeCLRN1 3 AR M, LOF X Variable onset, progerssive, moderate to severe SNHL Usher type 3ACOCH 3 AD M X Postlingual, progressive, profound SNHL Vestibular impairment

X3 Congenital, mild to moderately severe cookie-bite SNHLX3 Childhood/adulthood onset, mild to moderate SNHL Non-ocular stickler (STL3)

X1-2 Prelingual, profound, flat/cookiee-bite SNHLX3 Childhood, moderate to profound. Flat SNHL OSMED

DIABLO 3 AD M X Adulthood onset, progressive, mild to moderate, flat SNHLDFNA5 2 AD Exon 8 skipping X Postlingual, progressive SNHLDFNB59 3 AR M, LOF X Prelingual, severe to profound, flat SNHL Auditory neuropathyDIAPH1 3 AD M, LOF X Postlingual, low frequency progressive SNHLEDN3 3 AD/AR M, LOF X Variable HL Waardenburg type 4B

EDNRB 3 AD/AR M, LOF X Variable HL Waardenburg type 4BESPN 3 AD1, AR3 LOF X Prelingual, severe to profound, flat SNHL Vestibular areflexia, in some

ESRRB 3 AR M*, LOF X Early onset, severe to profound, flat/slightly sloping SNHLEYA1 3 AD M, LOF X Variable onset, mild to profound SNHL BOREYA4 3 AD LOF X Postlingual, progressive, moderate to profound, flat SNHLGIPC3 3 AR M, LOF X Prelingual, mild to profound, flat SNHL

X2-3 Congenital/late onset, mild to profound SNHLX2-3 Childhood onset, moderate to severe, high frequency SNHL Dermatologic manifestations

AR del Xa Congenital/childhood onset, mild to profound SNHL GJB2 dowregulationM X2 _ Hidrotic Ectodermal dysplasia

M, LOF X1 Variable SNHLGPR98 3 AR M, LOF X Prelingual, moderate to profound, sloping SNHL Usher type 2GPSM2 3 AR LOF Prelingual, severe to profound, slightly sloping SNHL McCullough syndromeGRHL2 3 AD LOF X Postlingual, progressive, mild to severe SNHL

GRXCR1 2 AR M, LOF X Congenital, moderate to profound, flat/slightly sloping SNHLHARS# 1-2 AR M X Childhood onset, progressive SNHL Usher type 3BHARS2 2 AR M X Childhood/teenage onset, progressive, mild to severe, flat SNHL Perrault Syndrome

HGF 2 AR Intronic del, splic X Prelingual, severe to profound, sloping SNHLHSD17B4 2 AR M, LOF X Childhood onset, moderate to severe SNHL Perrault Syndrome

ILDR1 3 AR M, LOF* X Prelingual, moderate to profound, sloping SNHLKARS 3 AR M X2 X2 Prelingual, moderate to severe, flat SNHL Peripheral neuropathy

KCNE1 3 AR M X Congenital, severe to profound, flat SNHL JLNS/Prolonged QTKCNQ1 3 AR M, LOF X Congenital, severe to profound, flat SNHL JLNS/Prolonged QTKCNQ4 3 AD M, LOF X Postlingual, progressive, sloping SNHLLARS2 2 AR M, LOF X Childhood onset, progressive, mild to severe, slightly rising SNHL Perrault SyndromeLHFPL5 3 AR M, LOF X Prelingual, severe to profound SNHLLOXHD1 3 AR M, LOF* X3 X1 Variable onset, variable SNHL Fuchs corneal dystrophyLRTOMT 3 AR M, LOF X Congenital, moderate to profound, flat SNHL

MARVELD2 3 AR LOF X Prelingual, moderate to profound, flat/sloping SNHLMIR96 3 AD Seed region X3 X1 Postlingual, progressive, flat/sloping SNHL Vertigo in someMITF 3 AD M, LOF X Variable HL Waardenburg type 2

MSRB3 2 AR M, LOF X Prelingual, severe to profound, flat SNHLMTRNR1 3 Mito. Point mutat. X Variable, progressive SNHL Aminoglycoside exposureMTTS1 3 Mito. Point mutat. X Variable, progressive SNHLMYH14 3 AD M*, LOF X3 X1 Postlingual, moderate to profound, flat SNHL Peripheral neuropathyMYH9 3 AD M*, LOF X2 X3 Variable onset, progressive SNHL Macrothrombocytopenia

MYO15A 3 AR M, LOF X Congenital, severe to profound, flat SNHLMYO3A 3 AR LOF X Postlingual, progressive, moderate to severe, sloping SNHL

AD3 M, LOF X Postlingual, progressive, moderate to profound sloping SNHLAR3 LOF X Congenital, profound SNHL Vestibular impairment in some

M, LOF X3 Congenital, severe to profound, flat SNHL Usher type 1M, LOF X3 Congenital, severe to profound, flat SNHL Vestibular impairment

AD M, In-frame del X2 Postlingual, mild to severe SNHL Vestibular impairmentOTOA 3 AR M, LOF X Prelingual, severe to profound, flat SNHLOTOF 3 AR M, LOF X Congenital, severe to profound, flat SNHL Auditory neuropathyOTOG 2 AR M, LOF X Prelingual/childhood onset, moderate, flat/slightly sloping SNHL Vestibular impairment in someOTOGL 3 AR LOF X Congenital, moderate to modertaley severe, sloping SNHLP2RX2 3 AD M X Teenage onset, progressive, moderately severe, flat SNHL High frequency tinnitusPAX3 3 AD M, LOF X Variable HL Waardenburg type 1 and 3

PCDH15 3 AR M, LOF X3 X3 Congenital, profound, flat SNHL Usher type 1POU3F4 3 X-linked M, LOF X Cogenital, moderate to profound, flat mixed HL IAC dilation/Perilymph. GusherPOU4F3 3 AD M, LOF X Adult onset, progressive, moderate to severe, sloping SNHLPRPS1 3 X-linked M X3 X3 Postlingual, progressive, severe to profound, flat SNHL PRS-I/Arts/CMTPTPRQ 3 AR M, LOF X Congenital, moderate to profound, flat SNHL

RDX 3 AR M, LOF X Prelingual, severe to profound, flat SNHLSERPINB6 2 AR LOF X Postlingual, moderate to severe, sloping SNHL

SIX1 3 AD M, LOF X Variable (3wk-22y) onset, mild to severe, mixed HL BORSLC26A4 3 AR M, LOF X3 X3 Congenital, progressive, severe to profound, SNHL Pendred/EVA

SMPX 3 X-linked LOF X Postlingual, progressive, moderate to profound, flat/sloping SNHLSNAI2 1-2 AR del X Severe/profound HL Waardenburg type 2DSOX10 3 AD M, LOF X Variable HL Waardenburg types 2E and 4CSTRC 3 AR M, LOF, del X3 X3 Childhood onset, mild to moderate, sloping SNHL Deafness Infertility SyndromeSYNE4 2 AR LOF X pre/postlingual progressive, mild to profound, sloping SNHL

TBC1D24 3 AR M X3 X3 Prelingual, profound, flat SNHL EpilepsyAD3 M X Pre/postlingual, progressive (in some), mild to severe SNHLAR3 LOF X Prelingual, moderate to profound, high/mid frequency SNHL

TIMM8A 3 X-linked M, LOF* X Congenital/early childhood onset, progressive, profound flat SNHL Mohr-Tranebjaerg syndromeAD3 M X Postlingual, progressive SNHLAR3 LOF X Congenital, profound, flat /slightly slopingSNHL

TMIE 3 AR M, LOF X Congenital, severe to profound, flat SNHLTMPRSS3 3 AR M, LOF X Congenital/childhood onset, severe to profound, flat SNHL

TPRN 3 AR LOF X Prelingual, severe to prfound, flat/slightly sloping SNHLTRIOBP 3 AR LOF X Prelingual, severe to profound, flat SNHLTSPEAR 2 AR LOF X Congenital, profound, flat SNHLUSH1C 3 AR M, LOF X3 X3 Prelingual, severe to profound, flat SNHL Usher type 1USH1G 3 AR M, LOF* X Congenital, profound, flat SNHL Usher type 1USH2A 3 AR M, LOF X Prelingual, moderate to profound, sloping SNHL Usher type 2

X3 Congenital, slowly progressive, low frequency SNHLX2 Childhood onset, progressive, mild to moderate, low-mid freq. SNHL WFS-like disorder

AR3 M, LOF X3 Early onset, progressive, high freq. SNHL Wolfram syndromeWHRN/DFNB3 3 AR M, LOF* X3 X3 Prelingual, moderate to profound, sloping SNHL Usher type 2

Key:1 - Weak Association Gene included on Subpanel:2 - Moderate Association3 - Definitive Association* - Most common# - included on subpanel only

Usher syndrome panel

Hearing Loss and Related Disorders (Genes)PhenotypeGene Evid. Inher. NonSynd. Synd.

AR3

X

M, In-frame del

M, LOF3

3AD3

Mutation Spect.

AR3

M

M, LOFGJB2

Congenital/childhood onset, mild to profound SNHL

COL11A2AD3

M

TECTA 3

WFS1 3

GJB6 3AD

AD3

3TMC1

AR

MYO6 3

MYO7A 3

Hearing Loss Gene Assessment

145 genes with published hearing loss associations

91 54

Insufficient Evidence Sufficient

Evidence

Sami Amr

Limited 131 (9%)

Disputed 1 (0.1%)

Definitive 509 (34%)

Strong 519 (35%)

Moderate 344 (23%)

The BabySeq Project

• Curating ~3,500 disease-associated genes

• 1504 genes curated so far

• 780 meet criteria for return (highly penetrant, childhood onset or treatable with strong or definitive evidence for gene’s cause for disease

Courtesy Ozge Birsoy

Well babies NICU babies

Leadership: Robert Green & Alan Beggs Pankaj Agrawal, Ingrid Holm,

Amy McGuire, Richard Parad, Peter Park,

Heidi Rehm, Tim Yu

THU 11:00-11:15 PLATFORM PRESENTATION:

Selecting the Right Genes to Report in Newborn Genomic Sequencing: The

BabySeq Project

Ozge Birsoy Partners HealthCare Personalized Medicine,

Harvard Medical School and The Broad Institute

Proposed Evidence Required to Include a Gene In a Clinical Test:

Definitive evidence Strong evidence Moderate evidence Limited evidence Disputed evidence

Exome/Genome

Predictive Tests & SFs

Diagnostic Panels

Genes with less evidence can be included in test design and analyzed in a research context to build evidence

Clinical Actionability

38

• Focus on findings associated with specific therapeutic or surveillance interventions in pre-symptomatic individuals 1. Define elements of

actionability 2. Standardize evidence reviews 3. Score gene-disease pairs with

a semi-quantitative actionability metric

• Develop clear and robust criteria to guide decisions regarding actionable secondary findings

Katrina Goddard Jim Evans

GenomeConnect • To engage patients in data submission,

ClinGen created a patient portal

39

GenomeConnect: • Collects patient-entered

phenotypic information and genetic testing reports through PatientCrossroads registry platform

• Transfers associated phenotypic and genotypic data into ClinGen-hosted database

• Connects participants with other families/individuals with same genetic variant(s) and researchers

Andy Faucett Brianne Kirkpatrick

ClinGen Acknowledgements Jonathan Berg Lisa Brooks Carlos Bustamante Jim Evans Melissa Landrum David Ledbetter Donna Maglott Christa Martin Robert Nussbaum Sharon Plon Erin Ramos Heidi Rehm Steve Sherry Michael Watson Erica Anderson Swaroop Arahdya Sandy Aronson Euan Ashley Larry Babb Erin Baldwin Sherri Bale Louisa Baroudi Les Biesecker Chris Bizon David Borland Rhonda Brandon Michael Brudno Damien Bruno Atul Butte Hailin Chen Mike Cherry Eugene Clark

Soma Das Johan den Dunnen Edwin Dodson Karen Eilbeck Marni Falk Andy Faucett Xin Feng Mike Feolo Matthew Ferber Penelope Freire Birgit Funke Monica Giovanni Katrina Goddard Robert Green Marc Greenblatt Robert Greenes Ada Hamosh Bret Heale Madhuri Hegde Ray Hershberger Lucia Hindorff Sibel Kantarci Hutton Kearney Melissa Kelly Muin Khoury Eric Klee Patti Krautscheid Joel Krier Danuta Krotoski Shashi Kulkarni Matthew Lebo Charles Lee

Jennifer Lee Elaine Lyon Subha Madhavan Teri Manolio Rong Mao Daniel Masys Peter McGarvey Dominic McMullan Danielle Metterville Laura Milko David Miller Aleksander Milosavljevic Rosario Monge Stephen Montgomery Michael Murray Rakesh Nagarajan Preetha Nandi Teja Nelakuditi Annie Niehaus Elke Norwig-Eastaugh Brendon O’Fallon Kelly Ormond Daniel Pineda-Alvaraz Darlene Reithmaier Erin Riggs George Riley Peter Robinson Wendy Rubinstein Shawn Rynearson Cody Sam Avni Santani

Neil Sarkar Melissa Savage Jeffery Schloss Charles Schmitt Sheri Schully Alan Scott Chad Shaw Weronika Sikora-Wohlfield Bethanny Smith Packard Tam Sneddon Sarah South Marsha Speevak Justin Starren Jim Stavropoulos Greer Stephens Christopher Tan Peter Tarczy-Hornoch Erik Thorland Stuart Tinker David Valle Steven Van Vooren Matthew Varugheese Yekaterina Vaydylevich Lisa Vincent Karen Wain Meredith Weaver Kirk Wilhelmsen Patrick Willems Marc Williams Eli Williams