Supporting Genomics in the Practice of Medicine

Heidi L. Rehm, PhD, FACMGDirector, Laboratory for Molecular Medicine, Partners Personalized Medicine

Associate Professor of Pathology, Brigham & Women’s Hospital and Harvard Medical School

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Questions

MI, 49y MI, 70y

39y

d. SCD, 7y6y 3y

38y

Case Presentation

40y

6 y

71y 68y

36y

Normal

HCM Family

Legend:

= Affected individuals

d. SCD, 49y d. SCD, 70y

39y

d. SCD, 7y6y6y 3y

38yLVHArrhythmia

SCD = Sudden Cardiac Death

LVH = Left Ventricular Hypertrophy

40y

Normal Echo

Normal Echo

Normal Echo

Normal Echo

40y

71y 68y

36y

HCM Family

Legend:

= Affected Individuals

+ = E187Q positive genotype- = E187Q negative genotype

d. SCD, 49y d. SCD, 70y

39y

d. SCD, 7y 7y

Normal ECHO

6y 3y

SCD = Sudden Cardiac Death

LVH = Left Ventricular Hypertrophy +

+- -

- 38yLVHArrhythmia

Glu187GlnTPM1

Pan Cardiomyopathy Test51 genes

Inconclusive

Positive 32%

Negative53%

15%

Copyright 2010 – Partners HealthCare System, Inc. – All Rights Reserved

When should exome/genome sequencing be used in the diagnostic work-up?

How can we increase the rate of success?

Diagnostic Testing for Rare Disease

Baylor exome experience:~25% success

Case: Nonsyndromic Hearing Loss

Congenital bilateral sensorineural hearing loss

Why should we perform genetic testing in children with hearing loss?

10-20% of kids will develop additional clinical features of syndromes later in life (longQT, retinitis pigmentosa, hypothyroidism, infertility, renal failure, etc)

Copyright 2010 – Partners HealthCare System, Inc. – All Rights Reserved

Option #1OtoGenome Test (70 genes) $3900

Clinical Sensitivity for HL = ~30%

Option #2Exome/Genome Sequencing (22,000 genes) $7000-9000

Testing Options for Hearing Loss

Case: Nonsyndromic Hearing Loss

• ~4 million sequence variants per child

• ~1,250,000 shared variants among the three siblings

• Spent 9 months investigating possible etiologies

• Ultimately pursued linkage analysis

WGS on 3 children

Matt Lebo

Copyright 2010 – Partners HealthCare System, Inc. – All Rights ReservedD3S1278 to D3S2453 = chr3:115,124,154-136,278,257 (3q13.31-22.3, 21 Mb)

Jun Shen

Some genes fail analysis by genome/exome sequencing

2 2 1 24

16

47

0

5

10

15

20

25

30

35

40

45

50

0% 1-24% 25-49% 50-74% 75-89% 90-98% >98%

STRC

Exome Coverage of 73 Hearing Loss Genes

Analyzed case by OtoGenome Test

STRC pSTRC

STRC pSTRC

Hom deletion of STRC

pSTRC

pSTRCSTRC Gene

Sami Amr

100 kb deletion(43.89 Mb to 43.99 Mb)

STRCPseudogene

STRC

100,000 Base Deletion Identified

Case: Deafness Infertility Syndrome

Males with this deletion will be infertile due to deletion of the adjacent CATSPER2 gene

Males can father children through intracytoplasmic sperm injection (ICSI)

Detection of full and partial gene deletions through targeted NGS: VisCap

Log2

ratio

sam

ple/

batc

h m

edia

nUSH2A heterozygous

exon 10 deletion

All exons, sorted by genome position USH2A exons (3’→5’)

OTOF deletion47 exons

Trevor Pugh

However, deletion analysis is not as robust in exome sequencing

IMPROVING EXOME SEQUENCING

COLLABORATIONo Harvard/Partners Lab for Molecular Medicine – Birgit Funkeo Children’s Hospital of Philadelphia – Avni Santanio Emory Genetics Laboratory –Madhuri Hegde

GOALSo Define medically relevant genes + develop framework for iterative curation

o Develop a “medically enhanced exome” capture kit (better coverage)

o Develop ancillary assays for genes that cannot be sequenced via NGS

PROGRESS  o ~ 4600 genes designated as version 1 – available on ICCG/ClinGen website 

(www.iccg.org)o Improved exome capture kit with optimized coverage of these genes  ‐ available from 

Agilent 

HISEQ 2500 rapid ; 4 samples/lane

Medical Exome4,631 genes

10.7 Mb

Pan Cardio Pnl51 genes

262 kb

fully covered exons (100% ≥ 20x)

Agilent v5-PLUS (~200x)

Broad CRSP ICE(~200x)

fully covered exons (100% ≥ 20x)

94% 98%

88% 99%

Birgit Funke

Improved Coverage with Medical Exome Enhancement

In summary……

Targeted gene panels are recommended when:

• clinical sensitivity is high AND• panel cost is lower than exome

OR• exon level copy number changes are common and

detection is included in panels

Exome suggested when critical genes are well-covered on exome, cost/sensitivity tradeoff makes sense and CNV detection is addressed as needed

Case #3: Distal Arthrogryposis Type 5

Disease is known to be AD and to occur de novo

No known genes for DA5

Skeletal Spine stiffness, Hunched anteverted shoulders, Pectus excavatum, Limited forearm rotation and wrist extension, Bilateral club feet, Congenital finger contractures, Long fingers, Absent phalangeal creases, Poorly formed palmar creases, Camptodactyly, Dimples over large joints

Muscle Decreased muscle mass (especially in lower limbs), Firm muscles Face Triangular face, Decreased facial expression Ears Prominent ears Eyes Ophthalmoplegia, Deep-set eyes, Epicanthal folds, Ptosis, Duane anomaly, Keratoglobus,

Keratoconus, Macular retinal folds, Strabismus, Astigmatism, Abnormal electroretinogram, Abnormal retinal pigmentation

Clinical features:

Case from Michael Murray, MD

Case: Distal Arthrogryposis Type 5

Two de novo mutations in exonic sequence:

ACSM4 – acyl-CoA synthetase medium-chain family member 45 nonsense variants identified in ESP; 1 with 6.4% MAF;

PIEZO2: mechanosensitive ion channel

Great candidate, but how to we prove causality for a novel gene-disease association?

Shamil Sunyeav

Then came serendipity……

Second DA5 family with PIEZO2 mutation was found

BertrandCoste

Matchmaker Needed!

Patient #1Clinical Geneticist #1

Patient #2Clinical Geneticist #2

Genotypic DataGene AGene BGene CGene DGene EGene F

Phenotypic Data

Feature 1Feature 2Feature 3Feature 4Feature 5

GenotypicData

Gene DGene GGene H

Phenotypic Data 

Feature 1Feature 3Feature 4Feature 5 Feature 6

GenomicMatchmaker

Notificationof

Match

Courtesy of Joel Krier

Joel Krier

Multiple disconnected

solutions

PhenoDBGene 

Matcher

DECIPHER

LOVD

Café Variome

Undiag.  Diseases Program

PhenomeCentral

GEM.app

ClinVar& 

ClinGenDB

Matchmaker Exchange is a Driver Project for the Global Alliance Success highly dependent on large international effort Critical need for standards Activity spans multiple workgroups

1. Clinical (phenotyping and matching algorithms)2. Data (data format and interfaces)3. Security (patient privacy)4. Regulatory and Ethics (patient consent)

180 organizations from 25 countries so far……

Multiple disconnected

solutionsMatchmaker Exchange

Gene Matcher

DECIPHER

LOVD

Café Variome

Undiag.  Diseases Program

PhenomeCentral

GEM.app

ClinGenDB

API V1.0

A New Paradigm in Clinical Genomics

Patient/Provider

ResearcherClinical Lab

Research Discoveries Clinical Lab Patient

Care

Traditional Paradigm

New Paradigm

Inherited Cancer DisordersHereditary Breast and Ovarian CancerLi‐Fraumeni SyndromePeutz‐Jeghers SyndromeLynch Syndrome, FAP, MYH‐Associated PolyposisVon Hippel Lindau syndromeMultiple Endocrine Neoplasia Types 1 & 2Familial Medullary Thyroid Cancer (FMTC)PTEN Hamartoma Tumor SyndromeRetinoblastomaHereditary Paraganglioma‐Pheochromocytoma SyndromeWT1‐related Wilms tumorNeurofibromatosis type 2Tuberous Sclerosis Complex

Cardiac DisordersEhlers Danlos Syndrome ‐ vascular typeMarfan Syndrome, Loeys‐Dietz Syndromes, and Familial Thoracic Aortic AneurysmsHypertrophic, Dilated, and ARV cardiomyopathyCatecholaminergic polymorphic ventricular tachycardiaRomano‐Ward Long QT Syndromes Types 1, 2, and 3 and Brugada Syndrome Familial hypercholesterolemia

Other: Malignant hyperthermia susceptibility

56 Genes

Defining the Low and High Bars for RORin the Clinical Setting………

Return all clinically valid IFs

Return all clinically actionable IFs (disease, carrier, PGx , etc)

Allow opt out of all IFs?

Return candidate genes in clinical exome/genome?Return raw reads/vcf?

Return certain clinically actionable IFs (ACMG list?)

100 Healthy Patients(10 PCPs)

100 HCM Patients(10 cardiologists)

Cardiac Risk 

Supplement

Genome Report

50 50

Project 2 Workflow

Whole Genome Sequencing

MedSeq WGS Pilot Clinical Trial

Standard of CarewithFamily History

50 50

Standard of CarewithFamily History

CardiacRisk 

Supplement

Genome Report

Compare Outcomes Compare Outcomes

RobertGreen

The Whole Genome Report

Monogenic disease risk

Carrier risk

Pharmacogenomics

Blood type

49 Mendelian Variants returned in first 20 MedSeq cases

Carrier Status

40 variants

5 Dx4 Cases at Risk

Cardiomyopathy Cohort

Hypertrophic cardiomyopathy x 3 cases with confirmed results

Hypertrophic cardiomyopathy x 1 case – found missed mutation from research NGS

LEOPARD syndrome – case misdiagnosed with HCM

Healthy Cohort

Chondrodysplasia punctata

Long QT

Combined pituitary hormone deficiency

Variegate porphyria

Review of Published Pathogenic Variants Found in WGS

3‐5 million variants

~20,000 Coding/Splice Variants

20‐40 “Pathogenic” Variants

Published as Disease‐Causing          

Genes 

<1%

Rare CDS/Splice Variants

LOF in Disease Associated Genes

10‐20 Variants

Review evidence for gene-disease association and LOF role

Review evidence for variant pathogenicity

92% Excluded

67% Excluded

Acknowledgements:Heather McLaughlinKalotina MachiniOzge Ceyhan BirsoyMatt LeboDanielle Metterville

Weak disease association

65%

Not medically relevant

33%

Somatic 2%

MedSeq Project:PI: Robert Green

The Problem

> 50 million genomic variants in humans

>20,000 genes

Most we don’t understand

0

200

400

600

800

1000

1200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

0

2

4

6

8

10

12

14

16

18

20

Lung CancerKRAS EGFR G12C L858R

GJB235delG

GJB2M34T PTPN11

N308D

MYBPC3R502W

68% (1120/1648) percent of pathogenic/likely pathogenic variants are seen only once

96% of variants are seen <10 times

Number of Probands

Num

ber o

f Var

iant

sHistogram of Pathogenic Variants from Diagnostic Testing of 15,000 Probands

(cardiomyopathy, hearing loss, rasopathies, aortopathies, somatic and hereditary cancerpulmonary disorders, skin disorders, other genetic syndromes)

31%VUS

25%Positive

61% Negative 14%

Inconclusivenclusive

52% Benign

17%Path

BabySeq: Genome Sequence-Based Screening for Childhood Risk and Newborn Illness

Sequence

Healthy Newborns

Sick Newborns

Symptoms

Additional Related

Symptoms

New symptoms

STOP

Indication-Based Genomic Report 1

Updated Indication-Based Genomic Report 1

Indication-Based Genomic Report 2 Symptoms

Query

Indication-Based Genomic Report

Query

Genomic Newborn Screening Report

Consult GRC and

Laboratory

Consult GRC and

Laboratory

Alan Beggs/Robert Green (PIs)P. Park, H. Rehm, T. Yu, P. Agrawal, R. Parad, I. Holm, A. McGuire (co-PIs)

Fetus with US finding: ↑NT

PTPN11 p.Ile309ValPublished as “pathogenic” for 

Noonan syndrome

Patient contacted author of paper who said he later found the variant in 7% of AJ controls; now feels the variant is benign

Courtesy Sherri Bale

Noonan Syndrome Case

?

LMMCase

To improve our knowledge of DNA variation will require a massive effort in data sharing

Clinical Domain WGsChairs: Jonathan Berg & 

Sharon PlonCancer co‐chairs: 

Matthew Ferber, Ken Offit, Sharon PlonCardiovascular co‐chairs: Euan Ashley, Birgit Funke, Ray Hershberger 

Metabolic co‐chairs: Rong Mao, Robert Steiner, David Valle

Pharmacogenomic co‐chairs: Teri Klein, Howard McLeod

ClinGen Working Groups (WG)

Actionability WG

Chair: Jim Evans

Informatics WG

Chair: Carlos Bustamante

EHR WG

Chair: Marc Williams

ClinVar IT Standards and Data Submission 

WG

Chairs: Sandy Aronson & Karen Eilbeck

Gene Curation WG

Chairs: Jonathan Berg & Christa Martin

Sequence Variant WG

Chairs: Sherri Bale & Madhuri Hegde

Structural Variant WG

Chairs: SwaroopArahdya & Erik 

Thorland ELSI and Genetic Counseling WG 

Chair: Andy Faucett & Kelly Ormond

Education, Engagement, Access 

WG 

Chair: Andy Faucett

Phenotyping WG

Chair: David Miller

ClinGenThe Clinical Genome Resource

LaunchedSept 2013

NCBI ClinVar LeadsMelissa LandrumDonna MaglottSteve Sherry

U41 Grant PIsDavid LedbetterChrista MartinBob NussbaumHeidi Rehm

U01 PIsJonathan BergJim Evans

David LedbetterMike Watson

U01 PIsCarlos Bustamante

Sharon Plon

NHGRI Program DirectorsLisa BrooksErin Ramos

Data Model WG

Chairs: Jonathan Berg & Heidi Rehm

Goals of ClinGenTo raise the quality of patient care by:

• Standardizing the annotation and interpretation of genomic variants

• Sharing variant and case level data through a centralized database for clinical and research use

• Developing machine‐learning algorithms to improve the throughput of variant interpretation

• Implementing an evidence‐based expert consensus process for curating genes and variants

• Assessing the actionability of genes and variants and supporting their use in clinical care systems

Rating System for Gene DosageHighest -- 3, 2, 1, 0, unlikely dosage sensitive -- Lowest

ACMG Lab QA Committee on theInterpretation of Sequence VariantsACMGSue Richards (chair), Heidi Rehm (co-chair)Sherri Bale, David Bick, Soma Das, Wayne Grody, Madhuri Hegde, Elaine Spector

AMPJulie Gastier-Foster, Elaine Lyon

CAPNazneen Aziz, Karl Voelkerding

42

PopulationData

Computational Data

Segregation Data

Other Database

Prevalence in affecteds statistically increased over controls 

MAF frequency is too high for disorderOR observation in controls inconsistent with  disease penetrance6

Truncating variant in a gene where LOF is a known mechanism of disease1 

De novo (paternity & maternity confirmed)3

Well‐established functional studies show a deleterious effect 4

Novel missense change at an amino acid residue where a different pathogenic missense change has been seen before2

Multiple lines of computational evidence support a deleterious effect on the gene /gene product 9

De novo (without paternity & maternity confirmed)3

Non‐segregation with disease5

Patient’s phenotype or FH matches  gene

For recessive disorders, detected in trans with a pathogenic variant11

Found in case with an alternate cause

Type of variant does not fit known mechanism of disease

Multiple lines of computational evidence suggest no impact on gene /gene product9

Well‐established functional studies show no deleterious effect4

Located in a mutational hot spotand/or known functional domain7

In‐frame indels in a repetitive region without a known function7

Same amino acid change as an established pathogenic variant2

In‐frame indels in a non‐repeat region

Stop‐loss variants12

Dominants: Observed in trans with a pathogenic variant 11

Functional Data

Co‐segregation with disease in multiple affecteds in multiple families5

Co‐segregation with disease in multiple affected family members5

De novo Data

Allelic Data

Absent  in 1000G and EVS

Strong

Observed in cis with a pathogenic variant Reputable database = benign

Strong Very StrongModerateSupporting Supporting

Reputable database = pathogenic

Missense in gene with low rate of benign missense variation and pathogenicmissenses common 

Other Data

Benign Pathogenic

The Scoring Rules for Classification

Pathogenic 1 Very Strong AND

1 Strong OR≥2 (Moderate OR Supporting)

2 Strong 1 Strong AND

≥3 Moderate OR≥2 Moderate and 2 Supporting OR≥1 Moderate and 4 Supporting

Likely Pathogenic1 Very strong or Strong AND

≥1 Moderate OR ≥2 Supporting

≥3 Moderate ≥2 Moderate AND 2 Supporting ≥1 Moderate AND 4 Supporting

Very Strong: PVS1Strong: PS1-PS4Moderate: PM1-PM6Supporting: PP1-PP5Stand-Alone: BA1Strong: BS1-BS4Supporting: BP1-BP6

Benign1 Stand Alone OR≥ 2 Strong

Likely Benign1 Strong and ≥1 Supporting OR>2 Supporting

Uncertain SignificanceIf other criteria are unmet or arguments for benign and pathogenic are equal in strength

Public LSDBs>600

PharmGKB

PopulationDatabases

EVS1000GdbSNP

MedicalLiterature

Clinical LabDatabases

OMIM

Variant Databases

COSMIC

HGMD$$$

Research Lab Databases

Largely absent from the public domain

Largely without standardized

assertions

Need genomic data and phenotypes/outcomes to objectively inform our knowledge of human variation

www.ncbi.nlm.nih.gov/clinvar

Submitter Variants GenesClinical LabsHarvard Medical School and Partners Healthcare 6996 155Emory Genetics Laboratory 5252 507Ambry Genetics 4167 ?International Standards For Cytogenomic Arrays 4134 17711GeneDx 3700 250University of Chicago 3687 462Sharing Clinical Reports Project 2045 2ARUP Laboratories 1417 7LabCorp 1391 140InVitae 436Counsyl 112 20University Pennsylvania Genetic Diagnostic Lab 68 1American College of Med Genetics and Genomics 23 1

26459

General DatabasesOMIM 24443 3360GeneReviews 3738 406

28181LSDB/Researcher – Assertions SubmittedBreast Cancer Information Core (BIC) 3793 2InSiGHT 2360 4Juha Muilu Group; FIMM, Finland (FIMM) 840 39ClinSeq Project 425 35Martin Pollak (Nephrology, BIDMC, Harvard) 234 39CFTR2 133 1

7785LSDB/Researcher – No Assertions111 Submitters 50063 >6957

ClinVar120,830 submissions107,098 unique variants

50,063 variants without assertions from 111 submitters

62,425 variants with assertions from >3360 genes

ClinGenDB

Data Flows in ClinGen

ExpertCuratedVariants

Case-level Data

Variant-level DataClinVar

Data

Locus‐Specific Databases

Clinical Labs Clinics Patients

Sharing Clinical Reports Project

Curation Interface

Free‐the‐Data Campaign

Patient Registries

Researchers

Unpublished or Literature Citations

InSiGHT

CFTR2PharmGKB

The Sharing Clinical Reports Project and Free‐the‐Data Campaign for BRCA1 and BRCA2

Goal: Improve the care and safety of patients through data sharing

Method: Request clinical lab reports from clinics and patients

Status: >60 clinics and > 200 patients have submitted de-identified reports leading to 4278 variants collected

sharingclinicalreports.org

Acknowledgements: Bob Nussbaum (UCSF)Danielle Metterville (ICCG)Laura SwaminathanGeorge Riley (NCBI)Larry Brody (BIC)Sharon Terry (Genetic Alliance) Genetic Alliance Staff and SC

www.free‐the‐data.org

Public BRCA1/2 Variants

5712 unique variants in ClinVar

GeneDx, Counsyl and ENIGMA submissions being processed

Global Alliance BRCA ChallengeLOVD: 3262 variantsUniversal Mutation Database: 3913 variantsBRCA Circos DatabaseCOGR Database (Canada) UK database

The Scoring Rules for ClassificationPathogenic

1 Very Strong AND1 Strong OR≥2 (Moderate OR Supporting)

2 Strong 1 Strong AND

≥3 Moderate OR≥2 Moderate and 2 Supporting OR≥1 Moderate and 4 Supporting

Likely Pathogenic1 Very strong or Strong AND

≥1 Moderate OR ≥2 Supporting

≥3 Moderate ≥2 Moderate AND 2 Supporting ≥1 Moderate AND 4 Supporting

Very Strong: PVS1Strong: PS1-PS4Moderate: PM1-PM6Supporting: PP1-PP5Stand-Alone: BA1Strong: BS1-BS4Supporting: BP1-BP6

Benign1 Stand Alone OR≥ 2 Strong

Likely Benign1 Strong and ≥1 Supporting OR>2 Supporting

Uncertain SignificanceIf other criteria are unmet or arguments for benign and pathogenic are equal in strength

Expert Panel

Single-Source

1. Literature references without assertions2. Inconsistency in assertions

Multi-Source Consistency

Practice Guideline

ClinVar Review Levels

Mendelian Categories:PathogenicLikely pathogenicUncertain significanceLikely benignBenign (InSiGHT and CFTR2)

(e.g. 23 CF)

No stars

Summary Assertions in ClinVar

Clinical Assertions

ClinVar Evidence Tab

ClinVar Expert Panel Designation (3 stars)

• Download submission form on ClinVar website• Panel should include multiple institutions and expertise

– medical specialists in disease area– medical geneticists– clinical laboratory diagnosticians/ molecular pathologists – researchers relevant to the disease, gene, functional assays and statistical analyses  

• Process for COI review and updating assertions• Publications or links that describe annotation process• Information provided is reviewed by ClinGen Executive Committee and posted on ClinVar w/designation

Expert Panel

Single-SourceEvidence-Based Review Method Provided

1. Literature references without assertions2. Inconsistency in assertions

Multi-Source ConsistencyEvidence-Based Review Methods Provided

Practice Guideline

New Idea for ClinVar Review Levels

Mendelian Categories:PathogenicLikely pathogenicUncertain significanceLikely benignBenign (InSiGHT and CFTR2)

(e.g. 23 CF)

No stars

Single-SourceNo Method Provided

?

Proposed Access Level Requirementsand Data Types

Clinical Labs

Lab 1

Lab 2

Variants reassessed

by Lab 140 variants

still discrepant

40 variants consistent

Variants reassessed

by Lab 2

10 variants consistent

Clinical Experts

Committee Review

Expert Committee Review• Discuss classification rules• Review discrepant variants with

input from experts in that disease and assign classification

80 variants discrepant

50 variants consistent

• Rule Differences• Silent (VUS vs LB)• Differences in frequency cut-offs

• Reporting differences influence stringency!• Lab 1 excludes Lik Ben, Lab 2 includes• Greater willingness of Lab 1 to classify as

Lik Ben!• Other (use of computational data)

• 1/80 variants needs expert input • atypical GLA/Fabry variant

30 variants still discrepant

Info disseminated back to labs

Feedback to Committee

Courtesy of Birgit Funke

Pass on what

needs expert input

CONF. CALL

Lab 1+2 review • Discrepancies• Rules

VARIANT HARMONIZATION (LMM – EMORY GENETICS LAB)

ClinGenDBCuration Tool

Expert Curation of Genes and Variants by Clinical Workgroups

Gene Resource

ExpertCuratedVariants

Case-level Data

Variant-level DataClinVar

Disease WGs

Clinical Domain WGs

Data

Machine Learning Algorithms

Locus‐Specific Databases

Clinical Labs

PharmGKB CFTR2

QC report

InSiGHT

Disease-Targeted NGS Tests on the Market

Disease area GenesCancerHereditary cancers (e.g. breast, colon, ovarian) 10‐50

Cardiac diseasesCardiomyopathies 50‐70Arrhythmias (e.g. LongQT) 10‐30Aortopathies (e.g. Marfan) 10

Immune disordersSevere combined immunodeficiency syndrome 18Periodic fever 7

Neurological/Neuromuscular/MetabolicAtaxia 40Cellular Energetics/Metabolism 656Congenital disorders of glycosylation 23‐28Dementia (e.g. Parkinson, Alzheimer) 32Developmental Delay/Autism/ID 30‐150Epilepsy 53‐130Hereditary neuropathy 34Microcephaly 11Mitochondrial disorders 37‐450Muscular dystrophy 12‐45

SensoryEye disease (e.g. retinitis pigmentosa) 66‐140Hearing loss and related syndromes 23‐72

OtherRasopathies (e.g. Noonan) 10Pulmonary disorders (e.g. cystic fibrosis) 12‐40Ciliopathies 94Short stature 12

Only 63% (92/145) of genes in clinical hearing loss tests have sufficient evidence for a disease-association

AGMG NGS Guideline

ACMG (www.acmg.net) > Publications > Laboratory Standards and Guidelines > NGS

Evaluating Evidence for Gene‐Disease Associations

Definitive evidenceStrong evidenceModerate evidenceLimited evidenceNo evidenceDisputed evidenceEvidence against

Evidence Level Evidence Description

DEFINITIVE The role of this gene in this particular disease has been repeatedly demonstrated in both the research and clinical diagnostic settings, and has been upheld over time (in general, at least 3 years).  No valid evidence has emerged that contradicts the role of the gene in the specified disease.

STRONG

There is strong evidence by at least two independent studies to support a causal role for this gene in this disease, such as:Strong statistical evidence  demonstrating an excess of pathogenic variants1 in affected individuals as compared to appropriately matched controlsMultiple pathogenic variants1 within the gene in unrelated probands with several different types of supporting experimental data2.  The number and type of evidence might vary (eg. fewer variants with stronger supporting data, or more variants with less supporting data)In addition, no valid evidence has emerged that contradicts the role of the gene in the noted disease.

MODERATE

There is moderate evidence to support a causal role for this gene in this disease, such as:At least 3 unrelated probands with pathogenic variants1 within the gene with some supporting experimental data2.  The role of this gene in this particular disease may not have been independently reported, but no valid evidence has emerged that contradicts the role of the gene in the noted disease. 

LIMITED

There is limited evidence to support a causal role for this gene in this disease, such as:Fewer than three observations of a pathogenic variant1 within the gene Multiple variants reported in unrelated probands but without sufficient evidence for pathogenicity per 2014 ACMG criteria

NO EVIDENCE No evidence reported for a causal role in disease.  

DISPUTED Valid evidence of approximate equivalent weight exists both supporting and refuting a role for this gene in this disease.

EVIDENCE AGAINST

Evidence refuting the role of the gene in the specified disease has been reported and significantly outweighs any evidence supporting the role.

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

Definitive evidenceStrong evidence

Moderate evidence

Limited evidenceDisputed evidence

Definitive evidenceStrong evidence

Moderate evidence

Limited evidenceDisputed evidence

Exome/Genome

Predictive Tests & IFs

Diagnostic Panels

www.iccg.org

clinicalgenome.org

ClinGen AcknowledgementsJonathan  BergLisa BrooksCarlos  BustamanteJim EvansMelissa LandrumDavid  LedbetterDonna MaglottChrista MartinRobert NussbaumSharon PlonErin RamosHeidi RehmSteve SherryMichael WatsonErica AndersonSwaroop ArahdyaSandy  AronsonEuan AshleyLarry BabbErin BaldwinSherri BaleLouisa BaroudiLes BieseckerChris BizonDavid BorlandRhonda BrandonMichael BrudnoDamien BrunoAtul ButteHailin ChenMike CherryEugene Clark

Soma DasJohan den DunnenEdwin DodsonKaren EilbeckMarni FalkAndy FaucettXin  FengMike FeoloMatthew FerberPenelope FreireBirgit FunkeMonica GiovanniKatrina GoddardRobert GreenMarc GreenblattRobert GreenesAda HamoshBret HealeMadhuri HegdeRay HershbergerLucia HindorffSibel KantarciHutton KearneyMelissa KellyMuin KhouryEric KleePatti KrautscheidJoel KrierDanuta KrotoskiShashi KulkarniMatthew LeboCharles Lee

Jennifer LeeElaine LyonSubha MadhavanTeri ManolioRong MaoDaniel MasysPeter McGarveyDominic McMullanDanielle MettervilleLaura MilkoDavid MillerAleksander MilosavljevicRosario MongeStephen  MontgomeryMichael MurrayRakesh NagarajanPreetha NandiTeja NelakuditiElke Norwig‐EastaughBrendon O’FallonKelly OrmondDaniel Pineda‐AlvarazDarlene ReithmaierErin RiggsGeorge RileyPeter RobinsonWendy RubinsteinShawn RynearsonCody SamAvni SantaniNeil SarkarMelissa Savage

Jeffery SchlossCharles SchmittSheri SchullyAlan ScottChad ShawWeronika Sikora‐WohlfieldBethanny Smith PackardTam SneddonSarah SouthMarsha SpeevakJustin StarrenJim StavropoulosGreer StephensChristopher TanPeter Tarczy‐HornochErik ThorlandStuart TinkerDavid ValleSteven Van VoorenMatthew VarugheeseYekaterina VaydylevichLisa VincentKaren WainMeredith WeaverKirk WilhelmsenPatrick WillemsMarc WilliamsEli Williams

Project LeadershipRobert Green, MD, MPHZak Kohane, MD, PhDCalum MacRae, MD, PhDAmy McGuire, JD, PhD Michael Murray, MD Heidi Rehm, PhD Christine Seidman, MDJason Vassy, MD, MPH, SM

Project ManagerDenise Lautenbach, MS, CGC

Project PersonnelSandy Aronson, ALM, MAStewart Alexander, PhDDavid Bates, MD Jennifer Blumenthal-Barby, PhDOzge Ceyhan-Birsoy, PhD Kurt Christensen, MPH, PhDAllison Cirino, MS, CGCLauren Conner Kelly DavisJake Duggan

Project Personnel (Cont.)Lindsay Feuerman, MPHSiva Gowrisankar, PhD Carolyn Ho, MDLeila Jamal,ScM, CGC Peter Kraft, PhDJoel Krier, MD Sek Won Kong, MD William Lane, MD, PhD Matt Lebo, PhDLisa Lehmann, MD, PhD, MScIn-Hee Lee, PhDIgnat Leschiner, PhD Christina LiuPhillip Lupo, PhD, MPHKalotina Machini, PhD, MS David Margulies, MDHeather McLaughlin, PhDDanielle Metterville, MS, CGCRachel Miller Kroouze, MA Sarita PanchangJill Robinson, MAMelody Slashinski, MPH, PhDShamil Sunyaev, PhD Peter Ubel, MD Scott Weiss, MD

External Advisory BoardKatrina Armstrong, MDDavid Bentley, DPhilRobert Cook-Deegan, MDMuin Khoury, MD, PhDBruce Korf, MD, PhD (Chair)Jim Lupski, MD, PhDKathryn Phillips, PhDLisa SalbergMaren Scheuner, MD, MPHSue Siegel, MSSharon Terry, MA

ConsultantsLes Biesecker, MDGeorge Church, PhD Geoffrey Ginsburg, MD, PhDTina Hambuch, PhDJ. Scott Roberts, PhDDavid Veenstra, PharmD, PhD

Protocol Monitoring CommitteeJudy Garber, MD, MPHDavid Miller, MD, PhDCynthia Morton, PhD

The MedSeq Project Collaborators

Matchmaker Exchange AcknowledgementsS BalasubramanianMike BamshadSergio Beltran AgulloJonathan BergKym BoycottAnthony BrookesMichael BrudnoHan BrunnerOriean BuskeDeanna ChurchRaymond DalglieshAndrew DevereauJohan den DunnenHelen FirthPaul Flicek

Jan FriedmanRichard GibbsMarta GirdeaRobert GreenMatt HurlesAda HamoshEkta KhuranaSebastian KohlerJoel KrierOwen LancasterMelissa LandrumPaul LaskoRick LiftonDaniel MacArthurAlex MacKenzie

Danielle MettervilleDebbie NickersonWoong‐Yan ParkJustin PaschallAnthony PhilippakisHeidi RehmPeter RobinsonFrancois SchiettecatteRolf SijmonsNara SobreiraJawahar SwaminathanMorris SwertzRachel ThompsonStephan Zuchner