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Systematic characterization of germline variants from the DiscovEHR study endometrial carcinoma population

  • Miller, Jason E.1
  • Metpally, Raghu P.2
  • Person, Thomas N.2
  • Krishnamurthy, Sarathbabu3
  • Dasari, Venkata Ramesh3
  • Shivakumar, Manu2
  • Lavage, Daniel R.2
  • Cook, Adam M.3
  • Carey, David J.3
  • Ritchie, Marylyn D.1
  • Kim, Dokyoon2, 4, 5, 6
  • Gogoi, Radhika3
  • 1 Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Department of Genetics, Philadelphia, PA, 19104, USA , Philadelphia (United States)
  • 2 Biomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA, 17822, USA , Danville (United States)
  • 3 Weis Center for Research, Geisinger Medical Center, Danville, PA, 17822, USA , Danville (United States)
  • 4 Huck Institute of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA , University Park (United States)
  • 5 University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Philadelphia, USA , Philadelphia (United States)
  • 6 University of Pennsylvania, Institute for Biomedical Informatics, Philadelphia, USA , Philadelphia (United States)
Published Article
BMC Medical Genomics
Springer (Biomed Central Ltd.)
Publication Date
May 03, 2019
DOI: 10.1186/s12920-019-0504-9
Springer Nature


BackgroundEndometrial cancer (EMCA) is the fifth most common cancer among women in the world. Identification of potentially pathogenic germline variants from individuals with EMCA will help characterize genetic features that underlie the disease and potentially predispose individuals to its pathogenesis.MethodsThe Geisinger Health System’s (GHS) DiscovEHR cohort includes exome sequencing on over 50,000 consenting patients, 297 of whom have evidence of an EMCA diagnosis in their electronic health record. Here, rare variants were annotated as potentially pathogenic.ResultsEight genes were identified as having increased burden in the EMCA cohort relative to the non-cancer control cohort. None of the eight genes had an increased burden in the other hormone related cancer cohort from GHS, suggesting they can help characterize the underlying genetic variation that gives rise to EMCA. Comparing GHS to the cancer genome atlas (TCGA) EMCA germline data illustrated 34 genes with potentially pathogenic variation and eight unique potentially pathogenic variants that were present in both studies. Thus, similar germline variation among genes can be observed in unique EMCA cohorts and could help prioritize genes to investigate for future work.ConclusionIn summary, this systematic characterization of potentially pathogenic germline variants describes the genetic underpinnings of EMCA through the use of data from a single hospital system.

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