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The ClinGen Epilepsy Gene Curation Expert Panel-Bridging the divide between clinical domain knowledge and formal gene curation criteria.

Ingo HelbigErin Rooney RiggsCarrie-Anne BarryKarl Martin KleinDavid DymentCourtney ThaxtonBekim SadikovicTristan T SandsJacy L WagnonKhalida LiaquatMaria Roberta CilioGhayda MirzaaKristen ParkErika AxeenElizabeth ButlerTanya M BardakjianPasquale StrianoAnnapurna PoduriRebecca K SiegertAndrew R GrantKatherine L HelbigHeather C Mefford
Published in: Human mutation (2019)
The field of epilepsy genetics is advancing rapidly and epilepsy is emerging as a frequent indication for diagnostic genetic testing. Within the larger ClinGen framework, the ClinGen Epilepsy Gene Curation Expert Panel is tasked with connecting two increasingly separate fields: the domain of traditional clinical epileptology, with its own established language and classification criteria, and the rapidly evolving area of diagnostic genetic testing that adheres to formal criteria for gene and variant curation. We identify critical components unique to the epilepsy gene curation effort, including: (a) precise phenotype definitions within existing disease and phenotype ontologies; (b) consideration of when epilepsy should be curated as a distinct disease entity; (c) strategies for gene selection; and (d) emerging rules for evaluating functional models for seizure disorders. Given that de novo variants play a prominent role in many of the epilepsies, sufficient genetic evidence is often awarded early in the curation process. Therefore, the emphasis of gene curation is frequently shifted toward an iterative precuration process to better capture phenotypic associations. We demonstrate that within the spectrum of neurodevelopmental disorders, gene curation for epilepsy-associated genes is feasible and suggest epilepsy-specific conventions, laying the groundwork for a curation process of all major epilepsy-associated genes.
Keyphrases
  • genome wide
  • copy number
  • genome wide identification
  • healthcare
  • machine learning
  • dna methylation
  • temporal lobe epilepsy
  • magnetic resonance imaging
  • deep learning
  • gene expression
  • congenital heart disease