Sex-specific gene and pathway modeling of inherited glioma risk

Quinn T. Ostrom, Warren Coleman, William Huang, Joshua B. Rubin, Justin D. Lathia, Michael E. Berens, Gil Speyer, Peter Liao, Margaret R. Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, John K. Wiencke, Lucie S. Mccoy, Helen M. Hansen, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Richard S. Houlston, Dora Il'yasovaRobert B. Jenkins, Christoffer Johansen, Daniel H. Lachance, Rose K. Lai, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen M. Schildkraut, Sanjay Shete, Ulrika Andersson, Preetha Rajaraman, Stephen J. Chanock, Martha S. Linet, Zhaoming Wang, Meredith Yeager, Beatrice Melin, Melissa L. Bondy, Jill S. Barnholtz-Sloan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Background To date, genome-wide association studies (GWAS) have identified 25 risk variants for glioma, explaining 30% of heritable risk. Most histologies occur with significantly higher incidence in males, and this difference is not explained by currently known risk factors. A previous GWAS identified sex-specific glioma risk variants, and this analysis aims to further elucidate risk variation by sex using gene- and pathway-based approaches. Methods Results from the Glioma International Case-Control Study were used as a testing set, and results from 3 GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for nominally significant autosomal SNPs (P < 0.01 in a previous meta-analysis) and nominally significant X-chromosome SNPs (P < 0.01), 3 algorithms (Pascal, BimBam, and GATES) were used to generate gene scores, and Pascal was used to generate pathway scores. Results were considered statistically significant in the discovery set when P < 3.3 × 10 â '6 and in the validation set when P < 0.001 in 2 of 3 algorithms. Results Twenty-five genes within 5 regions and 19 genes within 6 regions reached statistical significance in at least 2 of 3 algorithms in males and females, respectively. EGFR was significantly associated with all glioma and glioblastoma in males only and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the BioCarta telomeres pathway in both males and females. Conclusions These results provide additional evidence that there may be differences by sex in genetic risk for glioma. Additional analyses may further elucidate the biological processes through which this risk is conferred.

Original languageEnglish
Pages (from-to)71-82
Number of pages12
JournalNeuro-Oncology
Volume21
Issue number1
DOIs
StatePublished - 1 Jan 2019

Funding

FundersFunder number
Acta Oncologica
Baylor College of Medicine, Houston, Texas, USA
Brigham and Women’s Hospital
C.I.A.
Cancer Prevention Institute of CaliforniaHHSN261201000035C
Centers for Disease Control and Prevention’s58DP003862-01
Core Genotyping Facility
Dan L. Duncan Comprehensive Cancer Center
Danish Cancer Society Research Center
Department of Medicine
Department of Population and Quantitative Health Sciences
Department of Public Health Sciences
Department of Stem Cell Biology and Regenerative Medicine, Cleveland Clinic Foundation
E.B.C.
Grant S.  Roth Memorial Fund
Mayo Clinic College of Medicine
Mayo Clinic Comprehensive Cancer Center
McNair Medical Institute
National Brain Tumor Foundation
National Cancer Institute’sHHSN261201000140C
SAIC-Frederick
U.A.
UCSF-CTSIUL1 RR024131
Young Scientist Summer Research Program
National Institutes of HealthP50097257, P30CA125123, R01CA139020, R01CA126831, R01CA52689
National Cancer InstituteP50CA097257, R01CA207360
National Center for Research Resources
Public Health Institute
Cancer Prevention and Research Institute of TexasRP160097T
California Department of Public Health103885
Yale University
Association of Schools of Public Health
Institute for Clinical and Translational Research, University of Wisconsin, Madison
University of Southern CaliforniaHHSN261201000034C
National Center for Advancing Translational Sciences
Duke University
Memorial Sloan-Kettering Cancer Center
University of Texas MD Anderson Cancer Center
Baylor College of Medicine
Department of Neurology, University of Pittsburgh
University of California, San Francisco
Case Western Reserve University
School of Medicine
Case Comprehensive Cancer Center, Case Western Reserve University
Georgia State University
School of Medicine, Case Western Reserve University
School of Law, University of Virginia
Wellcome Trust
Division of Cancer Epidemiology and Genetics, National Cancer Institute
Swedish Cancer Foundation
NorthShore University HealthSystem
Duke Cancer Institute
Institute of Cancer Research
Royal Swedish Academy of Sciences
Faculty of Medicine, Assiut University

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