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Rigshospitalet - en del af Københavns Universitetshospital

Sex-specific gene and pathway modeling of inherited glioma risk

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review


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  • 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'yasova
  • Robert 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
  • GliomaScan Consortium
Vis graf over relationer

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 × 10-6 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.

Udgave nummer1
Sider (fra-til)71-82
Antal sider12
StatusUdgivet - 1 jan. 2019

ID: 56594374