Figure 52.0 Monarch butterflies. Figure 52.0x Monarch butterfly migration.
GA4GH Monarch Driver Project Introduction
Transcript of GA4GH Monarch Driver Project Introduction
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Monarch Initiative: Deep Phenotyping for
Improved Diagnostics and Analysis
Melissa Haendel, PhD@ontowonka
[email protected]@monarchinit
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Prevailing clinical diagnostic pipelines
leverage only a tiny fraction of the available
data
Under-utilized data Loss of discriminatory power
?
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Can we help machines understand
phenotypes?
“Palmoplantar hyperkeratosis”
Human phenotype
I have absolutely no idea what that means
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Ulcerated
paws
Palmoplantar
hyperkeratosis
Thick hand skin
"HandsEBS" by James Heilman, MD - Own work. Licensed under CC BY-SA 3.0 via Commons –https://commons.wikimedia.org/wiki/File:HandsEBS.JPG#/media/File:HandsEBS.JPGhttp://www.guinealynx.info/pododermatitis.html
Different communities use different languages
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The Human Phenotype Ontology
13,156phenotype terms
143,759 annotations for 7321 monogenic diseases
132,006 annotations for 3145 common diseases
bit.ly/hpo-paper
Peter Robinson, Sebastian Koehler, Chris Mungall
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Defining disease and clinical pathogenicity:
A lumping and splitting problem
source IDs
split/merge
manage resolution &provenance
MONDO Unified Disease Ontology
SEPIOScientific Evidence and
Provenance Information
One disease or two? What does the evidence favor?
One disease or two? How do we manage identifiers, hierarchy?
http://bit.ly/Monarch-Disease
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More species = more knowledge
19,008
78%
14,779
Number of human protein-coding genes in ExAC DB as per Lek et al. Nature 2016
19,008
Even inclusion of just four species boosts phenotypic coverage of genes by 38%
(5189%)
Combined = 89%
19,008
2,195 7,544 7,235 = 16,974 (union of coverage in any species)
9,739
51%
Mungall et al Nucleic Acids Research bit.ly/monarch-nar-2016
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“Fuzzy” phenotypic profile matching
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Example case solved by ExomiserP
he
no
typ
ic
pro
file
Ge
ne
s Heterozygous, missense mutation
STIM-1
N/A
Heterozygous, missense mutation
STIM-1N/A
Stim1Sax/Sax
Ranked STIM-1 variant maximally pathogenic based on cross-species G2P data,
in the absence of traditional data sourceshttps://exomiser.github.io/Exomiser/
bit.ly/stim1paper
In Genomics England 100K Genomes, of first 1936 diagnosed patients, 82% are in the top 5 Exomiser hits across a range
of rare diseases and family structures
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IMPC: Disease discovery from 3,328 gene
knockouts
Meehan et al, 2017, Nature Genetics, doi:10.1038/ng.3901
135 new candidate genes for Mendelian disorders
New model for Diamond–Blackfananemia • Phenotype profile similarity:
increased mean corpuscular hemoglobin and decreased erythrocyte cell numbers
• Differential expressionMay account for 46% of people with Diamond–Blackfan anemia with unknown genetic causes
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Lay-person HPO for patient use
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Layperson-HPO driven phenotyping tool
https://www.pcori.org/research-results/2017/realization-standard-care-rare-diseases-using-patient-engaged-phenotyping
Catherine Brownstein, Ingrid Holm
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Matchmaker Exchange for patients, diseases, and model
organisms to aid diagnosis and mechanistic discovery
Computational matching of rare disease patients and model organisms across clinical & public sources
bit.ly/mme-matchboxpatientarchive.orgbit.ly/exomiser-2017
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www.monarchinitiative.orgPIs: Melissa Haendel (OHSU), Chris Mungall (LBNL), Peter Robinson (JAX),
Damian Smedley (GEL), Tudor Groza (Garvan), David Osumi-Sutherland (EBI)
Funding:
NIH Office of Director: 1R24OD011883; NIH-UDP: HHSN268201300036C, HHSN268201400093P; NCINCI/Leidos #15X143)