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