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The Monarch Initiative: A semantic phenomics approach to disease discovery

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Presented as part of the "Tools and Approaches to Assess the Genetic Basis of Disease" ACMG short course.

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The Monarch Initiative: A semantic phenomics approach to disease discovery

  1. 1. 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
  2. 2. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Disclosures NIH funding: • Monarch Initiative • BD2K Center for Genomics • FaceBase • NHGRI • NCI
  3. 3. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit The central dogma
  4. 4. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit What do all those variations do?
  5. 5. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Genomic Data Algorithmic Analysis Traditional medical genomics pipeline Patient: Exomes/ Genome Patient: Exomes/ Genome
  6. 6. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit We have a common language for sequence data…. ATCTTAGCACGTTAC… ….not so much for phenotypes
  7. 7. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Ulcerated paws Palmoplantar hyperkeratosis Thick hand skin
  8. 8. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Can we help machines understand phenotypic features? “Palmoplantar hyperkeratosis” Human phenotypic feature I have absolutely no idea what that means
  9. 9. ACMG Annual Clinical Genetics Meeting March 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?
  10. 10. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit The Human Phenotype Ontology Hyposmia Abnormality of globe location eyeball of camera-type eye sensory perception of smell Abnormal eye morphology Motor neuron atrophyDeeply set eyes motor neuronCL 34571 annotations in 22 species 157534 phenotype annotations 2150 phenotype annotations
  11. 11. ACMG Annual Clinical Genetics Meeting March 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
  12. 12. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit A disease is a collection of phenotypic features Patient Disease X Differential diagnosis with similar but non-matching phenotypes is difficult Flat back of head Hypotonia Abnormal skull morphology Decreased muscle mass
  13. 13. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Ontology-based phenotypic profile matching https://github.com/monarch-initiative/owlsim-v3
  14. 14. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Making OMIM and other disease resources computable Free text -> ontology curation enables interoperability
  15. 15. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Which phenotypic profile is most similar? Model X Patient Disease Y
  16. 16. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Model X Patient Disease Y Fuzzy phenotype feature matching
  17. 17. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Inferring phenotypic knowledge of the human coding genome from model organisms Other= rat, fly, worm, mouse, zebrafish
  18. 18. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Genes & Phenotypic features. Integrated & Computable.
  19. 19. 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
  20. 20. 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
  21. 21. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Disease diagnosis: using the interactome
  22. 22. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Image 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?
  23. 23. Phenotypic sufficiency score http://monarchinitiative.org/ page/services
  24. 24. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit Each Case Report associated 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
  25. 25. ACMG Annual Clinical Genetics Meeting March 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
  26. 26. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit HPO synonyms for the patient / layperson Small Lower Jaw Hypoplasia of the mandible Bat earsOtopastasis HP:0000394 Pref Label: Otopastasis Synonyms: lop ear, prominent ears Suggested synonyms: Bat ears; ears sticking out HP:0009118 Pref Label: Aplasia/Hypoplasia of the mandible Suggested Synonyms: Small Mandible; Small lower Jaw; Little Lower Jaw; Mandibular micrognathia; MicroMandible; Mandibular Deficiency; Mandibular Retrognathia … Small Head Micro- cephaly HP:0000252 Pref Label: Microcephaly Synonyms: Decreased Head Circumference; Reduced Head Circumference; Small head circumference Suggested Synonyms : Small Head; Little Head; Small Skull; Little Skull; Small Cranium…
  27. 27. ACMG Annual Clinical Genetics Meeting March 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
  28. 28. ACMG Annual Clinical Genetics Meeting March 8 – 12, 2016 • Tampa, Florida @monarchinit www.monarchinitiative.org PDs: 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)

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