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ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida Melissa Haendel, PhD A semantic phenomics approach to disease discovery @monarchinit @ontowonka

The Monarch Initiative: A semantic phenomics approach to disease discovery

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Page 1: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

Melissa Haendel, PhD

A semantic phenomics approach to disease discovery

@monarchinit @ontowonka

Page 2: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Disclosures

NIH funding:• Monarch Initiative• BD2K Center for Genomics• FaceBase• NHGRI• NCI

Page 3: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

The central dogma

Page 4: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

What do all those variations do?

Page 5: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Genomic Data

Algorithmic Analysis

Traditional medical genomics pipeline

Patient:

Exomes/Genome

Patient:

Exomes/Genome

Page 6: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

We have a common language for sequence data…. ATCTTAGCACGTTAC… ….not so much for phenotypes

Page 7: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Ulcerated paws

Palmoplantar hyperkeratos

is

Thick hand skin

Page 8: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Can we help machines understand phenotypic features?

“Palmoplantar hyperkeratosi

s”

Human phenotypic featureI have absolutely

no idea what that means

???

Page 9: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Obstacles to phenome-based interpretation

Building a comprehensive phenomic database requires multiple disparate sources:

Human Genes, Variants, etc. databases Orthologous genes in model organisms

Phenotype Search and Matching How do utilize phenotypes in a variant filtering pipeline? How do we match phenotypes in different species? How much difference does phenotyping make?

Page 10: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

The Human Phenotype Ontology

Page 11: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Existing clinical vocabularies don’t adequately cover phenotypic descriptions

Winnenburg and Bodenreider, ISMB PhenoDay, 2014

UMLS

SNOMED CT

CHV

MedDRA

MeSH

NCIT

ICD10-C

ICD9-CM

ICD-10

OMIM

MedlinePlus

Page 12: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

A disease is a collection of phenotypic features

Patient

Disease XDifferential diagnosis with similar but non-matching phenotypes is difficult

Flat back of head Hypotonia

Abnormal skull morphology Decreased muscle mass

Page 13: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Ontology-based phenotypic profile matching

https://github.com/monarch-initiative/owlsim-v3

Page 14: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Making OMIM and other disease resources computable

Free text -> ontology curation enables interoperability

Page 15: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Which phenotypic profile is most similar?Model X

Patient

Disease Y

Page 16: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Model X

Patient

Disease Y

Fuzzy phenotype feature matching

Page 17: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Inferring phenotypic knowledge of the human coding genome from model organisms

Other= rat, fly, worm, mouse, zebrafish

Page 18: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Genes & Phenotypic features. Integrated & Computable.

Page 19: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

Combining genotype and phenotypic data for variant prioritization

Remove off-target and common variants

Variant score from allele freq and pathogenicity

Phenotype score from phenotypic similarity

PHIVE score to give final candidates

Mendelian filters

tinyurl.com/exomiser

Page 20: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

York platelet syndrome and STIM1

Markello T et al. Molecular Genetics and Metabolism 2015, 114: 474 Grosse J, J Clin Invest 2007 117: 3540-50

Impaired platelet aggregation(HP:0003540)

Thromocytopenia (HP:0001873)

Abnormal platelet activation(MP:0006298)

Thrombocytopenia (MP:0003179)

UDP_2542 Stim1Sax/Sax

http://www.nature.com/gim/journal/vaop/ncurrent/full/gim2015137a.html

Page 21: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Disease diagnosis: using the interactome

Page 22: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinitImage credit: Viljoen and Beighton, J Med Genet. 1992

Schwartz-Jampel Syndrome, Type I

Hspg2 mutation, a proteoglycan

~100 phenotype annotations

How much phenotyping is a enough?

Page 23: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

Phenotypic sufficiency score

http://monarchinitiative.org/page/services

Page 24: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Each Case Reportassociated with an HPO profile

Robinson, P. N., Mungall, C. J., & Haendel, M. (2015). Capturing phenotypes for precision medicine. Molecular Case Studies, 1(1), a000372. doi:10.1101/mcs.a000372

Capturing phenotypes for precision medicine

Page 25: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

patientarchive.org: Patient data and knowledge exchange

Automatic extraction of HPO from clinical summaries

Intuitive visualization Encrypted patient sensitive

data Search over encrypted data Collaborative diagnosis Fine-grained patient data

sharing

Page 26: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

HPO synonyms for the patient / layperson

Small Lower

Jaw

Hypoplasia of the mandible

Bat earsOtopastasis

HP:0000394Pref Label: OtopastasisSynonyms: lop ear, prominent earsSuggested synonyms:Bat ears; ears sticking out

HP:0009118Pref Label: Aplasia/Hypoplasia of the mandibleSuggested Synonyms: Small Mandible; Small lower Jaw; Little Lower Jaw; Mandibular micrognathia; MicroMandible; Mandibular Deficiency; Mandibular Retrognathia …

Small Head

Micro-cephaly

HP:0000252Pref Label: MicrocephalySynonyms: Decreased Head Circumference; Reduced Head Circumference; Small head circumferenceSuggested Synonyms : Small Head; Little Head; Small Skull; Little Skull; Small Cranium…

Page 27: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

Conclusions Making phenotypic features computable is crucial for precision

medicine• Variant interpretation needs more than genomic data• Methods of incorporating phenotypic features are evolving• We need all the organisms’ G2P data

The Monarch Portal integrates and organizes gene-phenotype data• Ontologies make phenotypes computable• Depth and breadth of structured phenotype data is growing

Future work• Environmental/exposure• Quantitative/imaging data• Complex/common diseases and cancer

Page 28: The Monarch Initiative: A semantic phenomics approach to disease discovery

ACMG Annual Clinical Genetics MeetingMarch 8 – 12, 2016 • Tampa, Florida

@monarchinit

www.monarchinitiative.orgPDs: Melissa Haendel, Chris Mungall, Peter Robinson

Funding:NIH Office of Director: 1R24OD011883; NIH-UDP: HHSN268201300036C, HHSN268201400093P; NCINCI/Leidos #15X143, BD2K U54HG007990-S2 (Haussler) & BD2K PA-15-144-U01 (Kesselman)