Phenotype-based Matching Using PhenoDB Terms in BHCMG PhenoDB to Maximize Whole Exome/Genome Data Interpretation

Nara Sobreira, MD, PhD Johns Hopkins University

McKusick-Nathans Institute of Genetic Medicine

http://genematcher.org

GeneMatcher overview

Intended to find other patients/animal models for a novel candidate disease gene

Only deidentified data and genes, so no IRB required Automated matching Submitters choose to follow up at their discretion Now also matching on phenotypic features (since

October 1st 2105)

GeneMatcher Matching options

As of May 1st 2016: 4,459 genes 1,675 submitters 55 countries 5,267 matches

on 1,216 genes

Growth in number of genes and matches in GeneMatcher

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Gene Count Match Count

Matchmaker Exchange Matching options

As of May 1st 2016: 100 matches with

PhenomeCentral 87 matches with

DECIPHER

Hum Mut 34:561, 2013

Hum Mut 36:425, 2015

http://phenodbresearch.net OR http://phenodb.org

BHCMG PhenoDB numbers Holds data on 4,426 submissions

Including 53 cohorts ranging from 5-295

More than 6,225 samples have been sequenced by BHCMG Holds phenotype data from more than 10,284 individuals BHCMG has identified more than 222 novel genes More than 231 known genes and 136 phenotypic expansion

From Robinson PN, Kohler S, Bauer S, Seelow D, Horn D, Mundlos S. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet. Nov 2008;83(5):610-615.

From Robinson PN, Kohler S, Bauer S, Seelow D, Horn D, Mundlos S. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet. Nov 2008;83(5):610-615.

Phenotype Matching Algorithms- General Approach

Testing set - 44 published cases with known Mendelian phenotypes and detailed phenotypic descriptions

Question: Can the algorithms match query cases of a known syndrome to other cases with same diagnosis in the testing set?

Algorithm Validation

Defined test set Picked phenotype to be tested, remove all cases of this

phenotype from the testing set Picked a case with the testing phenotype as a query case and a

case to be put back into testing set Applied the matching algorithm Is testing case in top 1 or top 5 most similar cases? Repeat x 1000

Pairs-Based Testing Approach

Percent of Cases For Which the Best Phenotypic Match From the Database Has the Same Syndrome

SimUI Jaccard Distance WangResnick-PhenoDB

Resnick-OMIM

SimGIC-PhenoDB

SimGIC-

OMIM PhenoDigm

Congenital Disorder of Deglysolyation

1 1 0.87 1 1 1 1 1 1

Floating-Harbor Syndrome

1 1 1 1 1 1 1 1 1

Poretti-Boltshauser Syndrome

1 1 1 1 1 1 1 1 1

Cerebrocosto-mandibular Syndrome

0.98 0.63 0.57 0.53 0.25 0.25 0.86 0.84 0.46

BHCMG PhenoDB database use Buske et al. Hum Mutat, 2015 Oct. Removed all cases with fewer than 5 phenotypic features Removed all phenotypes for which only one case was present in

database N=1,152 cases across 32 phenotypes Ran “Top 1” and “Top 5” Pairs-Based Test

Fraction of Cases for Which the Matching Case is in Top 5 Most Similar Cases

“Real-World” Algorithm Testing n=4,114 Wide range of depth phenotypic annotation depth Many cases without assigned OMIM syndromes ID

BHCMG PhenoDB database use

How Well Does a Randomly Selected Query Case Match to Other Cases of Same Clinical Syndrome?

Top 5 Top 25 Top 1st %ile Top 5th %ile

Gomez-Lopez-Hernandez Syndrome (N=6) 2/5 2/5 2/5 4/5Hemifacial Microsomia (N=13) 1/12 2/12 2/12 8/12Lateral Meningocele Syndrome (N=6) 0/5 0/5 0/5 0/5

What Factors Impact Successful Phenotypic Matching?

Phenotypic Features per Case Top 5 Top 25

Top 1st %ile

Top 5th %ile

Gomez-Lopez-Hernandez Syndrome (N=6) 7 2/5 2/5 2/5 4/5Hemifacial Microsomia (N=13) 8 1/12 2/12 2/12 8/12Lateral Meningocele Syndrome (N=6) 1 0/5 0/5 0/5 0/5

As a user of a phenotype matching algorithm, how far “down the list” would you need to go to find relevant matches?

Removed cases with fewer than 5 features

Threshold Testing

Threshold Testing

Algorithms perform best for patients/syndromes with rare and highly specific phenotypic annotations

Depth of phenotypic annotation is key Inherent limitations to reducing a patient with a Mendelian

disorder to a list of phenotypic terms Phenotypic matching in combination with genomic data (e.g. a

VCF file) may offer opportunities for gene discovery

Preliminary Conclusions and Next Steps

Thanks for your attention!Acknowledgements

Joel Krier and François Schiettecatte for the phenotype-matching

project

Ada Hamosh, François Schiettecatte, Corinne Boehm, Julie

Hoover-Fong, Reid Sutton, Jim Lupski, David Valle and others for

PhenoDB

Ada Hamosh and François Schiettecatte for GeneMatcher

The CMGs and especially the Baylor-Hopkins CMG team