Fulltext

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Permuth JB 1 , Pirie A 2 , Ann Chen Y 3 , Lin HY 3 , Reid BM 1 , Chen Z 3 Show all authors , Monteiro A 1 , Dennis J 2 , Mendoza-Fandino G 1 , AOCS Study Group , Australian Cancer Study (Ovarian Cancer) , Anton-Culver H 4 , Bandera EV 5 , Bisogna M 6 , Brinton L 7 , Brooks-Wilson A 8 , Carney ME 9 , Chenevix-Trench G 10 , Cook LS 11 , Cramer DW 12 , Cunningham JM 13 , Cybulski C 14 , D'Aloisio AA 15 , Anne Doherty J 16 , Earp M 17 , Edwards RP 18 , Fridley BL 19 , Gayther SA 20 , Gentry-Maharaj A 21 , Goodman MT 22 , Gronwald J 14 , Hogdall E 23 , Iversen ES 24 , Jakubowska A 14 , Jensen A 25 , Karlan BY 26 , Kelemen LE 27 , Kjaer SK 25 , Kraft P 28 , Le ND 29 , Levine DA 6 , Lissowska J 30 , Lubinski J 14 , Matsuo K 31 , Menon U 21 , Modugno R 18 , Moysich KB 32 , Nakanishi T 33 , Ness RB 34 , Olson S 35 , Orlow I 35 , Pearce CL 20 , Pejovic T 36 , Poole EM 37 , Ramus SJ 20 , Anne Rossing M 38 , Sandler DP 39 , Shu XO 40 , Song H 41 , Taylor JA 39 , Teo SH 42 , Terry KL 12 , Thompson PJ 26 , Tworoger SS 37 , Webb PM 43 , Wentzensen N 44 , Wilkens LR 45 , Winham S 46 , Woo YL 47 , Wu AH 20 , Yang H 44 , Zheng W 48 , Ziogas A 49 , Phelan CM 1 , Schildkraut JM 50 , Berchuck A 51 , Goode EL 17 , Pharoah PD 2 , Sellers TA 1 , Ovarian Cancer Association Consortium

Affiliations 

  • 1 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
  • 2 Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
  • 3 Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
  • 4 Department of Epidemiology, Director of Genetic Epidemiology Research Institute, UCI School of Medicine, University of California Irvine, Irvine, CA, USA
  • 5 Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
  • 6 Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
  • 7 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
  • 8 Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver BC, Canada
  • 9 Department of Obstetrics and Gynecology, John A Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, USA
  • 10 Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Queensland, Australia
  • 11 Division of Epidemiology and Biostatistics, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico, USA
  • 12 Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital, Boston, Massachusetts, USA
  • 13 Department of Laboratory of Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
  • 14 International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
  • 15 Social and Scientific Systems, Inc, Durham, NC, USA
  • 16 Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NY, USA
  • 17 Department of Health Science Research, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
  • 18 Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
  • 19 Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, USA
  • 20 Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California, USA
  • 21 Women's Cancer, Institute for Women's Health, University College London, London, UK
  • 22 Cancer Prevention and Control, Samuel Oshin Comprehensive Cancer Institute, Cedars- Sinai Medical Center, Los Angeles, CA, USA
  • 23 Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark and Molecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark
  • 24 Department of Statistical Science, Duke University, Durham, NC, USA
  • 25 Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
  • 26 Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
  • 27 Department of Public Health Sciences, Medical University of South Carolina College of Medicine, Charleston, SC, USA
  • 28 Program in Genetic Epidemiology and Statistical Genetics, Harvard TH Chan School of Public Health, Boston, MA, USA
  • 29 Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada
  • 30 Department of Cancer Epidemiology and Prevention, The Maria Sklodowska-Curie Memorial Cancer Center, Warsaw, Poland
  • 31 Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Aichi, Japan
  • 32 Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA
  • 33 Department of Gynecologic Oncology, Aichi Cancer Center Central Hospital, Nagoya, Aichi, Japan
  • 34 The University of Texas School of Public Health, Houston, TX, USA
  • 35 Memorial Sloan Kettering Cancer Center, Department of Epidemiology and Biostatistics, New York,NY, USA
  • 36 Department of Obstetrics and Gynecology, Oregon Health and Science University, Portland, OR, USA
  • 37 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
  • 38 Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
  • 39 Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
  • 40 Vanderbilt University School of Medicine, Nashville, TN, USA
  • 41 Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
  • 42 Cancer Research Malaysia, Subang Jaya, Malaysia
  • 43 Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
  • 44 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda MD, USA
  • 45 Cancer Epidemiology Program, University of Hawaii Cancer Center, Hawaii, USA
  • 46 Department of Health Science Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
  • 47 Department of Obstetrics and Gynaecology, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
  • 48 Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
  • 49 Department of Epidemiology, University of California Irvine, Irvine, CA, USA
  • 50 Department of Community and Family Medicine, Duke University Medical Center, Durham, NC, USA
  • 51 Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina, USA, Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk
Hum Mol Genet, 2016 08 15;25(16):3600-3612.
PMID: 27378695 DOI: 10.1093/hmg/ddw196

Abstract

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P  P≥5.0 ×10 -  7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 -  5; PSKAT-o = 9.23 × 10 -  4) and KRT13 (PAML = 1.67 × 10 -  4; PSKAT-o = 1.07 × 10 -  5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

MeSH terms
Similar publications