View the webinar at http://www.knome.com/webinar-supporting-genomics-practice-medicine. In this presentation, Dr. Heidi Rehm, Chief Laboratory Director of the Laboratory for Molecular Medicine at Partners Healthcare and one of the Principal Investigators on ClinGen, elucidates the challenges of genomics in medicine and outlined the path to integrating large scale sequencing into clinical practice.
Call Girls Coimbatore Just Call 8250077686 Top Class Call Girl Service Available
Supporting Genomics in the Practice of Medicine by Heidi Rehm
1. Supporting Genomics
in the Practice of Medicine
Heidi L. Rehm, PhD, FACMG
Director, Laboratory for Molecular Medicine, Partners Personalized Medicine
Associate Professor of Pathology, Brigham & Women’s Hospital and Harvard Medical School
2. Questions
If you have any questions
during the webinar,
please enter them in the
GoToWebinar pane.
We will answer as many
as possible at the end.
3. Case Presentation
MI, 49y MI, 70y
39y
38y
6y 3y d. SCD, 7y
71y 68y
40y
6 y
36y
Normal
4. HCM Family
Legend:
= Affected individuals
d. SCD, 49y d. SCD, 70y
39y
38y
LVH
Arrhythmia
Normal Echo
71y 68y
6y 3y 6y
d. SCD, 7y
SCD = Sudden Cardiac Death
LVH = Left Ventricular Hypertrophy
40y
Normal
Echo
Normal
Echo
Normal
Echo
36y
5. HCM Family
Legend:
= Affected Individuals
+ = E187Q positive genotype
- = E187Q negative genotype
d. SCD, 49y d. SCD, 70y
SCD = Sudden Cardiac Death
LVH = Left Ventricular Hypertrophy - 38y
+
39y
Pan Cardiomyopathy Test
51 genes
- - +
d. SCD, 7y 7y
Normal ECHO
6y 3y
LVH
Arrhythmia
Glu187Gln
TPM1
Positive
32%
Inconclusive
Negative
53%
15%
6. Diagnostic Testing for Rare Disease
Baylor exome
experience:
~25% success
When should exome/genome sequencing be used in
the diagnostic work-up?
How can we increase the rate of success?
Copyright 2010 – Partners HealthCare System, Inc. – All Rights Reserved
7. 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)
8. Testing Options for Hearing Loss
Option #1
OtoGenome Test (70 genes) $3900
Clinical Sensitivity for HL = ~30%
Option #2
Exome/Genome Sequencing (22,000 genes) $7000-9000
Copyright 2010 – Partners HealthCare System, Inc. – All Rights Reserved
9. Case: Nonsyndromic Hearing Loss
WGS on 3 children
• ~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
Matt Lebo
10. Jun Shen
D3S1278 to D3S2453 = chr3:115,124,154-136,278,257 (3q13.31-22.3, 21 Mb)
Copyright 2010 – Partners HealthCare System, Inc. – All Rights Reserved
12. Analyzed case by OtoGenome Test
STRC pSTRC
STRC pSTRC
Hom deletion
of STRC
pSTRC
STRC Gene pSTRC
Sami Amr
13. 100,000 Base Deletion Identified
100 kb deletion
(43.89 Mb to 43.99 Mb)
STRC
Pseudogene
STRC
14. 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)
15. Detection of full and partial gene deletions
through targeted NGS: VisCap
Trevor Pugh
Log2 ratio sample/batch median USH2A heterozygous
exon 10 deletion
OTOF deletion
47 exons
All exons, sorted by genome position USH2A exons (3’→5’)
However, deletion analysis is not as robust in exome
sequencing
16. IMPROVING EXOME SEQUENCING
COLLABORATION
o Harvard/Partners Lab for Molecular Medicine – Birgit Funke
o Children’s Hospital of Philadelphia – Avni Santani
o Emory Genetics Laboratory – Madhuri Hegde
GOALS
o 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
18. 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
19. Case #3: Distal Arthrogryposis Type 5
Disease is known to be AD and to occur de novo
No known genes for DA5
Clinical features:
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
Case from
Michael Murray, MD
20. Case: Distal Arthrogryposis Type 5
Two de novo mutations in exonic sequence:
ACSM4 – acyl-CoA synthetase medium-chain family member 4
5 nonsense variants identified in ESP; 1 with 6.4% MAF;
PIEZO2: mechanosensitive ion channel
Shamil Sunyeav
Great candidate, but how to we prove causality for a
novel gene-disease association?
22. Matchmaker Needed!
Patient #1
Clinical Geneticist #1
Joel Krier
Patient #2
Clinical Geneticist #2
Genotypic Data
Gene A
Gene B
Gene C
Gene D
Gene E
Gene F
Phenotypic
Data
Feature 1
Feature 2
Feature 3
Feature 4
Feature 5
Genotypic
Data
Gene D
Gene G
Gene H
Phenotypic
Data
Feature 1
Feature 3
Feature 4
Feature 5
Feature 6
Notification
of
Match
Genomic
Matchmaker
Courtesy of Joel Krier
23. PhenoDB
Gene
Matcher
Multiple
disconnected
solutions
DECIPHER
LOVD
Café
Variome
Undiag.
Diseases
Program
ClinVar
&
ClinGenDB
GEM.app
Phenome
Central
24. 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……
25. Gene
Matcher
Multiple
Matchmaker
Exchange
disconnected
solutions
DECIPHER
LOVD
Café
Variome
Undiag.
Diseases
Program
ClinGenDB
GEM.app
Phenome
Central
API V1.0
26. A New Paradigm in Clinical Genomics
Traditional Paradigm
Research
Discoveries Clinical Lab Patient
Care
New Paradigm
Patient/Provider
Clinical Lab Researcher
27. Inherited Cancer Disorders
Hereditary Breast and Ovarian Cancer
56 Genes
Li‐Fraumeni Syndrome
Peutz‐Jeghers Syndrome
Lynch Syndrome, FAP, MYH‐Associated Polyposis
Von Hippel Lindau syndrome
Multiple Endocrine Neoplasia Types 1 & 2
Familial Medullary Thyroid Cancer (FMTC)
PTEN Hamartoma Tumor Syndrome
Retinoblastoma
Hereditary Paraganglioma‐Pheochromocytoma Syndrome
WT1‐related Wilms tumor
Neurofibromatosis type 2
Tuberous Sclerosis Complex
Cardiac Disorders
Ehlers Danlos Syndrome ‐ vascular type
Marfan Syndrome, Loeys‐Dietz Syndromes, and Familial Thoracic Aortic Aneurysms
Hypertrophic, Dilated, and ARV cardiomyopathy
Catecholaminergic polymorphic ventricular tachycardia
Romano‐Ward Long QT Syndromes Types 1, 2, and 3 and Brugada Syndrome
Familial hypercholesterolemia
Other: Malignant hyperthermia susceptibility
28. Defining the Low and High Bars for ROR
in the Clinical Setting………
Return candidate genes in clinical exome/genome?
Return raw reads/vcf?
Return all clinically valid IFs
Return all clinically actionable IFs (disease, carrier, PGx , etc)
Return certain clinically actionable IFs (ACMG list?)
Allow opt out of all IFs?
29. MedSeq WGS Pilot Clinical Trial
Robert
Green
100 Healthy Patients
(10 PCPs)
Project 2 Workflow
100 HCM Patients
(10 cardiologists)
50 50
Genome
Report
Cardiac
Risk
Supplement
50 50
Whole Genome
Sequencing
Standard of
Care
with
Family
History
Standard of
Care
with
Family
History
Genome
Report
Cardiac
Risk
Supplement
Compare Outcomes Compare Outcomes
30. The Whole Genome Report
Monogenic disease risk
Carrier risk
Pharmacogenomics
Blood type
31. 49 Mendelian Variants returned in first 20 MedSeq cases
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
Carrier
Status
40 variants
5 Dx
4 Cases
at Risk
Healthy Cohort
Chondrodysplasia punctata
Long QT
Combined pituitary hormone deficiency
Variegate porphyria
32. Review of Published Pathogenic Variants Found in WGS
3‐5 million variants
~20,000 Coding/Splice Variants
Published as
Disease‐Causing
20‐40
“Pathogenic”
Variants
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 McLaughlin
Kalotina Machini
Ozge Ceyhan Birsoy
Matt Lebo
Danielle Metterville
Somatic 2%
Weak
disease
association
65%
Not
medically
relevant
33%
MedSeq Project:
PI: Robert Green
33. The Problem
> 50 million genomic variants in humans
>20,000 genes
Most we don’t understand
34. Number of Variants Histogram of Pathogenic Variants from Diagnostic Testing of 15,000 Probands
1200
1000
800
600
400
200
0
(cardiomyopathy, hearing loss, rasopathies, aortopathies, somatic and hereditary cancer
pulmonary disorders, skin disorders, other genetic syndromes)
20
18
16
14
12
10
8
6
4
2
0
Lung Cancer
KRAS EGFR
G12C L858R
GJB2
35delG
31%
VUS
GJB2
M34T PTPN11
N308D
MYBPC3
R502W
68%
(1120/1648)
percent of
pathogenic/likely
pathogenic
variants are
seen only once
96% of variants are
seen <10 times
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Number of Probands
25%
Positive
61%
Negative 14%
Inconclusive
52%
Benign
17%
Path
35. BabySeq: Genome Sequence-Based Screening
for Childhood Risk and Newborn Illness
Alan Beggs/Robert Green (PIs)
P. Park, H. Rehm, T. Yu, P. Agrawal, R. Parad, I. Holm, A. McGuire (co-PIs)
Healthy
Newborns
Sequence
Sick
Newborns
Symptoms
Additional
Related
Symptoms
New symptoms
STOP
Query
Indication-Based
Genomic Report 1
Updated
Indication-Based
Genomic Report 1
Indication-Based
Symptoms Genomic Report 2
Query
Indication-Based
Genomic Report
Genomic Newborn
Screening Report
Consult
GRC and
Laboratory
Consult
GRC and
Laboratory
36. Noonan Syndrome Case
PTPN11 p.Ile309Val
Published 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
Fetus with US finding: ↑NT
?
LMM
Case
37. To improve our knowledge of DNA
variation will require a massive
effort in data sharing
38. ClinGen Working Groups (WG)
Clinical Domain WGs
Chairs: Jonathan Berg &
Sharon Plon
Cancer co‐chairs:
Matthew Ferber, Ken
Offit, Sharon Plon
Cardiovascular co‐chairs:
Euan Ashley,
Birgit Funke, Ray
Hershberger
Metabolic co‐chairs:
Rong Mao, Robert
Steiner, David Valle
Pharmacogenomic co‐chairs:
Teri Klein,
Howard McLeod
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: Swaroop
Education,
Engagement, Access
WG
Chair: Andy Faucett
Arahdya & Erik
Thorland ELSI and Genetic
Counseling WG
Chair: Andy Faucett &
Kelly Ormond
Phenotyping WG
Chair: David Miller
ClinGen
The Clinical Genome Resource
Launched
Sept 2013
NCBI ClinVar Leads
Melissa Landrum
Donna Maglott
Steve Sherry
U41 Grant PIs
David Ledbetter
Christa Martin
Bob Nussbaum
Heidi Rehm
U01 PIs
Jonathan Berg
Jim Evans
David Ledbetter
Mike Watson
U01 PIs
Carlos Bustamante
Sharon Plon
NHGRI Program
Directors
Lisa Brooks
Erin Ramos
Data Model WG
Chairs: Jonathan Berg
& Heidi Rehm
39. Goals of ClinGen
To 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
40. Rating System for Gene Dosage
Highest -- 3, 2, 1, 0, unlikely dosage sensitive -- Lowest
41. ACMG Lab QA Committee on the
Interpretation of Sequence Variants
ACMG
Sue Richards (chair), Heidi Rehm (co-chair)
Sherri Bale, David Bick, Soma Das, Wayne Grody, Madhuri Hegde, Elaine
Spector
AMP
Julie Gastier-Foster, Elaine Lyon
CAP
Nazneen Aziz, Karl Voelkerding
42
42. Population
Data
Computational
Data
Segregation
Data
Other
Database
Supporting Supporting Moderate Strong Very Strong
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
Well‐established
functional studies
show a deleterious
effect 4
De novo (paternity &
maternity confirmed)3
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
Missense in gene with
low rate of benign
missense variation
and pathogenic
missenses common
Patient’s phenotype
or FH matches gene
For recessive
disorders, detected
in trans with a
pathogenic variant11
Multiple lines of
computational
evidence suggest no
impact on gene
/gene product9
Type of variant does
not fit known
mechanism of
disease
Found in case with
an alternate cause
Well‐established
functional studies show
no deleterious effect4
Located in a
mutational hot spot
and/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
Reputable database
= pathogenic
Other Data
Benign Pathogenic
43. 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 Pathogenic
1 Very strong or Strong AND
≥1 Moderate OR
≥2 Supporting
≥3 Moderate
≥2 Moderate AND 2 Supporting
≥1 Moderate AND 4 Supporting
Benign
1 Stand Alone OR
≥ 2 Strong
Likely Benign
1 Strong and ≥1 Supporting OR
>2 Supporting
Uncertain Significance
If other criteria are unmet or
arguments for benign and
pathogenic are equal in strength
Very Strong: PVS1
Strong: PS1-PS4
Moderate: PM1-PM6
Supporting: PP1-PP5
Stand-Alone: BA1
Strong: BS1-BS4
Supporting: BP1-BP6
44. Public LSDBs
>600
Variant Databases
Pharm
GKB
Medical
Literature
Population
Databases
EVS
1000G
dbSNP
Clinical Lab
Databases
OMIM
HGMD
$$$
COSMIC
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
46. Submitter Variants Genes
Clinical Labs
Harvard Medical School and Partners Healthcare 6996 155
Emory Genetics Laboratory 5252 507
Ambry Genetics 4167 ?
International Standards For Cytogenomic Arrays 4134 17711
GeneDx 3700 250
University of Chicago 3687 462
Sharing Clinical Reports Project 2045 2
ARUP Laboratories 1417 7
LabCorp 1391 140
InVitae 436
Counsyl 112 20
University Pennsylvania Genetic Diagnostic Lab 68 1
American College of Med Genetics and Genomics 23 1
26459
General Databases
OMIM 24443 3360
GeneReviews 3738 406
28181
LSDB/Researcher – Assertions Submitted
Breast Cancer Information Core (BIC) 3793 2
InSiGHT 2360 4
Juha Muilu Group; FIMM, Finland (FIMM) 840 39
ClinSeq Project 425 35
Martin Pollak (Nephrology, BIDMC, Harvard) 234 39
CFTR2 133 1
7785
LSDB/Researcher – No Assertions
111 Submitters 50063 >6957
ClinVar
120,830 submissions
107,098 unique variants
62,425 variants
with assertions
from >3360 genes
50,063 variants
without assertions
from 111 submitters
47. Data Flows in ClinGen
Clinical Labs Clinics Patients
Expert
Curated
Variants
Case-level Data
ClinVar
Variant-level Data
Data
ClinGenDB
Locus‐Specific Databases
Sharing Clinical
Reports Project
Curation Interface
Free‐the‐Data
Campaign
Patient Registries
Researchers
Unpublished
or
Literature
Citations
PharmGKB CFTR2
InSiGHT
48. 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 Swaminathan
George Riley (NCBI)
Larry Brody (BIC)
Sharon Terry (Genetic Alliance)
Genetic Alliance Staff and SC
www.free‐the‐data.org
49. Public BRCA1/2 Variants
5712 unique variants in ClinVar
GeneDx, Counsyl and ENIGMA
submissions being processed
Global Alliance BRCA Challenge
LOVD: 3262 variants
Universal Mutation Database: 3913 variants
BRCA Circos Database
COGR Database (Canada)
UK database
50. 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 Pathogenic
1 Very strong or Strong AND
≥1 Moderate OR
≥2 Supporting
≥3 Moderate
≥2 Moderate AND 2 Supporting
≥1 Moderate AND 4 Supporting
Benign
1 Stand Alone OR
≥ 2 Strong
Likely Benign
1 Strong and ≥1 Supporting OR
>2 Supporting
Uncertain Significance
If other criteria are unmet or
arguments for benign and
pathogenic are equal in strength
Very Strong: PVS1
Strong: PS1-PS4
Moderate: PM1-PM6
Supporting: PP1-PP5
Stand-Alone: BA1
Strong: BS1-BS4
Supporting: BP1-BP6
51. ClinVar Review Levels
Practice
Guideline
Mendelian Categories:
Pathogenic
Likely pathogenic
Uncertain significance
Likely benign
Benign Expert Panel
(InSiGHT and CFTR2)
Multi-Source Consistency
Single-Source
1. Literature references without assertions
2. Inconsistency in assertions
(e.g. 23 CF)
No stars
55. 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
56. New Idea for ClinVar Review Levels
Practice
Guideline
Mendelian Categories:
Pathogenic
Likely pathogenic
Uncertain significance
Likely benign
Benign Expert Panel
(InSiGHT and CFTR2)
Multi-Source Consistency
Evidence-Based Review Methods Provided
Single-Source
Evidence-Based Review Method Provided
1. Literature references without assertions
2. Inconsistency in assertions
(e.g. 23 CF)
No stars
Single-Source
No Method Provided
?
62. Evaluating Evidence
for Gene‐Disease Associations
Definitive evidence
Strong evidence
Moderate evidence
Limited evidence
No evidence
Disputed evidence
Evidence against
63. 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 controls
Multiple 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.
64. 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 & IFs
Diagnostic
Panels
66. 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
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
67. The MedSeq Project Collaborators
Project Leadership
Robert Green, MD, MPH
Zak Kohane, MD, PhD
Calum MacRae, MD, PhD
Amy McGuire, JD, PhD
Michael Murray, MD
Heidi Rehm, PhD
Christine Seidman, MD
Jason Vassy, MD, MPH, SM
Project Manager
Denise Lautenbach, MS, CGC
Project Personnel
Sandy Aronson, ALM, MA
Stewart Alexander, PhD
David Bates, MD
Jennifer Blumenthal-Barby, PhD
Ozge Ceyhan-Birsoy, PhD
Kurt Christensen, MPH, PhD
Allison Cirino, MS, CGC
Lauren Conner
Kelly Davis
Jake Duggan
Project Personnel (Cont.)
Lindsay Feuerman, MPH
Siva Gowrisankar, PhD
Carolyn Ho, MD
Leila Jamal,ScM, CGC
Peter Kraft, PhD
Joel Krier, MD
Sek Won Kong, MD
William Lane, MD, PhD
Matt Lebo, PhD
Lisa Lehmann, MD, PhD, MSc
In-Hee Lee, PhD
Ignat Leschiner, PhD
Christina Liu
Phillip Lupo, PhD, MPH
Kalotina Machini, PhD, MS
David Margulies, MD
Heather McLaughlin, PhD
Danielle Metterville, MS, CGC
Rachel Miller Kroouze, MA
Sarita Panchang
Jill Robinson, MA
Melody Slashinski, MPH, PhD
Shamil Sunyaev, PhD
Peter Ubel, MD
Scott Weiss, MD
External Advisory Board
Katrina Armstrong, MD
David Bentley, DPhil
Robert Cook-Deegan, MD
Muin Khoury, MD, PhD
Bruce Korf, MD, PhD (Chair)
Jim Lupski, MD, PhD
Kathryn Phillips, PhD
Lisa Salberg
Maren Scheuner, MD, MPH
Sue Siegel, MS
Sharon Terry, MA
Consultants
Les Biesecker, MD
George Church, PhD
Geoffrey Ginsburg, MD, PhD
Tina Hambuch, PhD
J. Scott Roberts, PhD
David Veenstra, PharmD, PhD
Protocol Monitoring Committee
Judy Garber, MD, MPH
David Miller, MD, PhD
Cynthia Morton, PhD
68. Matchmaker Exchange Acknowledgements
S Balasubramanian
Mike Bamshad
Sergio Beltran Agullo
Jonathan Berg
Kym Boycott
Anthony Brookes
Michael Brudno
Han Brunner
Oriean Buske
Deanna Church
Raymond Dalgliesh
Andrew Devereau
Johan den Dunnen
Helen Firth
Paul Flicek
Jan Friedman
Richard Gibbs
Marta Girdea
Robert Green
Matt Hurles
Ada Hamosh
Ekta Khurana
Sebastian Kohler
Joel Krier
Owen Lancaster
Melissa Landrum
Paul Lasko
Rick Lifton
Daniel MacArthur
Alex MacKenzie
Danielle Metterville
Debbie Nickerson
Woong‐Yan Park
Justin Paschall
Anthony Philippakis
Heidi Rehm
Peter Robinson
Francois Schiettecatte
Rolf Sijmons
Nara Sobreira
Jawahar Swaminathan
Morris Swertz
Rachel Thompson
Stephan Zuchner
