4.6 Article

Sex-specific gene and pathway modeling of inherited glioma risk

Journal

NEURO-ONCOLOGY
Volume 21, Issue 1, Pages 71-82

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/neuonc/noy135

Keywords

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Funding

  1. Research Training Grant from the Cancer Prevention and Research Institute of Texas (CPRIT) [RP160097T]
  2. Grant S. Roth Memorial Fund
  3. Young Scientist Summer Research Program
  4. National Institutes of Health, Bethesda, Maryland [R01CA139020, R01CA52689, P50097257, P30CA125123]
  5. McNair Medical Institute at Baylor College of Medicine
  6. Population Sciences Biorepository at Baylor College of Medicine
  7. Swedish Research Council
  8. Swedish Cancer Foundation
  9. National Institutes of Health [R01CA139020, R01CA52689, P50CA097257, R01CA126831]
  10. Loglio Collective
  11. National Brain Tumor Foundation
  12. Stanley D. Lewis and Virginia S. Lewis Endowed Chair in Brain Tumor Research
  13. Robert Magnin Newman Endowed Chair in Neuro-oncology
  14. National center for Research Resources, National Institutes of Health, through UCSF-CTSI grant [UL1 RR024131]
  15. National Center for Advancing Translational Sciences, National Institutes of Health, through UCSF-CTSI grant [UL1 RR024131]
  16. California Department of Public Health [103885]
  17. National Cancer Institute's Surveillance, Epidemiology and End Results Program [HHSN261201000140C, HHSN261201000035C, HHSN261201000034C]
  18. Centers for Disease Control and Prevention's National Program of Cancer Registries [U58DP003862-01]

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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 x 10(-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.

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