Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanism

Discovery

Melissa Haendel, PhD @ontowonka

Prevailing clinical genomic pipelines leverage only a tiny fraction of the available

data

PATIENT EXOME/ GENOME

PATIENT CLINICAL PHENOTYPES

PUBLIC GENOMIC DATA

PUBLIC CLINICAL PHENOTYPE,

DISEASE DATA

POSSIBLE DISEASES

DIAGNOSIS & TREATMENT

PATIENT ENVIRONMENT PUBLIC ENVIRONMENT, DISEASE DATA

PATIENT OMICS PHENOTYPES

PUBLIC OMICS PHENOTYPES,CORRELATIONS

Under-utilized data

Genes Environment Phenotypes+ =

Computable encodings are essential

Base pairsVariant notation (eg. HGVS) SNOMED-CTMedical procedure coding

Environment Ontology

@ontowonka

The Human Phenotype Ontology

11,813 phenotype terms

127,125 rare disease - phenotype annotations

136,268 common disease -phenotype annotations

http://bit.ly/hpo-paper

Existing clinical vocabularies don’t adequately cover phenotypic

descriptions

Winnenburg and Bodenreider, 2014

0

10

20

30

40

50

60

70

80

90

100

HPO UMLS SNOMED CT CHV MedDRAMeSH NCIT ICD10 OMIM

Perc

ent c

over

age

=> HPO is now in the UMLS

monarchinitiative.org

Why model organisms matter to patients

Model data can provide up to

80% phenotypic coverage of the human coding

genome

Fuzzy phenotype matching for diagnosis

Deep phenotyping and “fuzzy” matching algorithms improve diagnostics

Bone et al.Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiencyGenetics in Medicine (2015) doi:10.1038/gim.2015.137

Phen

otyp

ic pr

ofile

Gene

s

Heterozygous, missense mutationSTIM-1

Heterozygous, missense mutation

STIM-1

Stim1Sax/Sax

4.9% exomes w dual molecular diagnoses, differentiated w deep phenotyping

Matchmaker Exchange for patients, diseases, and model organisms to aid diagnosis and mechanistic

discovery

www.monarchinitiative.orghttp://bit.ly/Monarch-MME

Goal: Get clinical sites & public databases to provide standardized phenotype data

Journals are now requiring HPO terms

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

HPO language translations

We need your help! http://bit.ly/hpo-translations

Translation of labels, synonyms, and text definitions

Italian Spanish Russian French

German English layperson Japanese Chinese100%11%

12%

100%

19%19%

near 100%

20%

monarchinitiative.org

How much phenotyping is enough?

Enlarged ears (2)Dark hair (6) Female (4)Male (4)

Blue skin (1)Pointy ears (1)

Hair absent on head (1)Horns present (1)

Hair present on head (7)

Enlarged lip (2)

Increased skin pigmentation (3)

bit.ly/annotationsufficiency

Genes Environment Phenotypes+ =

Biology central dogma

Standards for exchanging data must be up to these challenges.

@ontowonka

Genes Environment Phenotypes

VCF PXFGFF

Standard exchange mechanisms exist for genes … but for phenotypes?

Environment?

NEW

BED

@ontowonka

Introducing PhenoPackets

A packet of phenotype data to be used anywhere, written by anyone

http://phenopackets.org

What does a phenopacket look like? Alacrima Sleep Apnea Microcephaly

phenotype_profile:- entity: ”patient16" phenotype: types: - id: "HP:0000522" label: ”Alacrima" onset: description: “at birth” types: - id: "HP:0003577" label: "Congenital onset" evidence: - types: - id: "ECO:0000033" label: ”Traceable Author Statement" source: - id: ”PMID:"

Clinical labs Public

databases Journals

Layperson HPO + Phenopackets Dry eyes Stops breathing during

sleep Small head

phenotype_profile:- entity: “Grace” phenotype: types: - id: "HP:0000522" label: “Alacrima" onset: description: “at birth" types: - id: "HP:0003577" label: "Congenital onset" evidence: - types: - id: “ECO:0000033” label: “Traceable Author Statement" source: - id: “ https://twitter.com/examplepatient/status/123456789”

• Patient registries

• Social media

Standards are vital to realize a mechanistic classification of disease

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

Tudor Groza, Damian Smedley, Sebastian Köhler, Julie McMurry Funding: NIH Office of Director: 2R24OD011883; NHGRI UDP: HHSN268201300036C,

HHSN268201400093P; NCATS: UDN U01TR001395, Biomedical Data Translator: 1OT3TR002019; E-RARE 2015: Hipbi-RD

01GM1608