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Increasing phenotypic annotation improves the diagnostic rate of exome sequencing in a rare neuromuscular disorder.

Author information

Affiliations

  • 1. Institute of Genetic Medicine, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK.
      Authors
    • Thompson R 1
    • Töpf A 1
    (2 authors)
  • 2. Centro Nacional de Análisis Genómico (CNAG-CRG), Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.
      Authors
    • Papakonstantinou Ntalis A 2
    • Beltran S 2
    • Lochmüller H 2
    (3 authors)
  • 3. Departamento de Neurologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil.
      Authors
    • de Paula Estephan E 3
    (1 author)
  • 4. Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India.
      Authors
    • Polavarapu K 4
    (1 author)
  • 5. Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands.
      Authors
    • 't Hoen PAC 5
    (1 author)
    • Show all (6)

ORCIDs linked to this article

Show all (7)

Human Mutation, 23 Jun 2019, 40(10):1797-1812
https://doi.org/10.1002/humu.23792 PMID: 31231902 

Abstract 

Phenotype-based filtering and prioritization contribute to the interpretation of genetic variants detected in exome sequencing. However, it is currently unclear how extensive this phenotypic annotation should be. In this study, we compare methods for incorporating phenotype into the interpretation process and assess the extent to which phenotypic annotation aids prioritization of the correct variant. Using a cohort of 29 patients with congenital myasthenic syndromes with causative variants in known or newly discovered disease genes, exome data and the Human Phenotype Ontology (HPO)-coded phenotypic profiles, we show that gene-list filters created from phenotypic annotations perform similarly to curated disease-gene virtual panels. We use Exomiser, a prioritization tool incorporating phenotypic comparisons, to rank candidate variants while varying phenotypic annotation. Analyzing 3,712 combinations, we show that increasing phenotypic annotation improved prioritization of the causative variant, from 62% ranked first on variant alone to 90% with seven HPO annotations. We conclude that any HPO-based phenotypic annotation aids variant discovery and that annotation with over five terms is recommended in our context. Although focused on a constrained cohort, this provides real-world validation of the utility of phenotypic annotation for variant prioritization. Further research is needed to extend this concept to other diseases and more diverse cohorts.

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Read article at publisher's site: https://doi.org/10.1002/humu.23792

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Funding 

Funders who supported this work.

CIHR (1)

Canadian Institutes of Health Research (1)

FP7 Health (2)

FP7 Research infrastructures (1)

H2020 Health (2)