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 language | English (US) |
|---|---|
| Pages (from-to) | 71-82 |
| Number of pages | 12 |
| Journal | Neuro-oncology |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2019 |
ASJC Scopus subject areas
- Oncology
- Clinical Neurology
- Cancer Research
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In: Neuro-oncology, Vol. 21, No. 1, 01.01.2019, p. 71-82.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Sex-specific gene and pathway modeling of inherited glioma risk
AU - Ostrom, Quinn T.
AU - Coleman, Warren
AU - Huang, William
AU - Rubin, Joshua B.
AU - Lathia, Justin D.
AU - Berens, Michael E.
AU - Speyer, Gil
AU - Liao, Peter
AU - Wrensch, Margaret R.
AU - Eckel-Passow, Jeanette E.
AU - Armstrong, Georgina
AU - Rice, Terri
AU - Wiencke, John K.
AU - Mccoy, Lucie S.
AU - Hansen, Helen M.
AU - Amos, Christopher I.
AU - Bernstein, Jonine L.
AU - Claus, Elizabeth B.
AU - Houlston, Richard S.
AU - Il'yasova, Dora
AU - Jenkins, Robert B.
AU - Johansen, Christoffer
AU - Lachance, Daniel H.
AU - Lai, Rose K.
AU - Merrell, Ryan T.
AU - Olson, Sara H.
AU - Sadetzki, Siegal
AU - Schildkraut, Joellen M.
AU - Shete, Sanjay
AU - Andersson, Ulrika
AU - Rajaraman, Preetha
AU - Chanock, Stephen J.
AU - Linet, Martha S.
AU - Wang, Zhaoming
AU - Yeager, Meredith
AU - Melin, Beatrice
AU - Bondy, Melissa L.
AU - Barnholtz-Sloan, Jill S.
N1 - Funding Information: necessarily represent the official views of the NIH. The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #U58DP003862-01 awarded to the California Department of Public Health. Funding Information: In Sweden work was additionally supported by Acta Oncologica through the Royal Swedish Academy of Science (BM salary) and the Swedish Research Council and Swedish Cancer Foundation. Funding Information: Q.T.O. is supported by a Research Training Grant from the Cancer Prevention and Research Institute of Texas (CPRIT; RP160097T). J.W.C. was supported by the Grant S. Roth Memorial Fund. W.H. was supported by the Young Scientist Summer Research Program. The GICC was supported by grants from the National Institutes of Health, Bethesda, Maryland (R01CA139020, R01CA52689, P50097257, and P30CA125123). Additional support was provided by the McNair Medical Institute and the Population Sciences Biorepository at Baylor College of Medicine. Funding Information: Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA (Q.T.O., P.L., J.S.B.S.); Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA (Q.T.O., G.A., M.L.B.); Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA (Q.T.O.); University School, Chagrin Falls, Ohio, USA (W.C.); Case Western Reserve University, Cleveland, Ohio, USA (W.H.); Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, USA; Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri, USA (J.B.R.); Department of Stem Cell Biology and Regenerative Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA (J.D.L.); Cancer and Cell Biology Division, The Translational Genomics Research Institute, Phoenix, Arizona, USA (M.E.B., G.S.); Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA (M.R.W., T.R., J.K.W., L.S.M., H.M.H.); Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota, USA (J.E.E.P.); Institute for Clinical and Translational Research, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA (C.I.A.); Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA (J.L.B., S.H.O.); School of Public Health, Yale University, New Haven, Connecticut, USA (E.B.C.); Department of Neurosurgery, Brigham and Women’s Hospital, Boston, Massachusetts, USA (E.B.C.); Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom (R.S.H.); Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia, USA (D.I.); Cancer Control and Prevention Program, Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina, USA (D.I.); Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina, USA (D.I.); Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA (R.B.J.); Oncology Clinic, Finsen Center, Rigshospitalet and Survivorship Research Unit, The Danish Cancer Society Research Center, Copenhagen, Denmark (C.J.); Department of Neurology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA (D.H.L.); Departments of Neurology and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA (R.K.L.); Department of Neurology, NorthShore University HealthSystem, Evanston, Illinois, USA (R.T.M.); Cancer and Radiation Epidemiology Unit, Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel (S.S.); Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel (S.S.); Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA (J.M.S.); Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA (S.S.); Department of Radiation Sciences, Faculty of Medicine, Umeå University, Umeå, Sweden (U.A., B.M.); Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA (P.R., S.J.C., M.S.L., Z.W., M.W., M.Y.); Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, USA (S.J.C., Z.W., M.Y.); Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA (Z.W.) Funding Information: The UCSF Adult Glioma Study was supported by the National Institutes of Health (grant numbers R01CA52689, P50CA097257, R01CA126831, and R01CA139020), the Loglio Collective, the National Brain Tumor Foundation, the Stanley D. Lewis and Virginia S. Lewis Endowed Chair in Brain Tumor Research, the Robert Magnin Newman Endowed Chair in Neuro-oncology, and by donations from families and friends of John Berardi, Helen Glaser, Elvera Olsen, Raymond E. Cooper, and William Martinusen. This project also was supported by the National center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through UCSF-CTSI grant number UL1 RR024131. Its contents are solely the responsibility of the authors and do not Funding Information: The ideas and opinions expressed herein are those of the author(s) Endorsement by the State of California Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their contractors and subcontractors is not intended nor should be inferred. UK10K data generation and access was organized by the UK10K consortium and funded by the Wellcome Trust. Publisher Copyright: © The Author(s) 2018.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85059233481&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059233481&partnerID=8YFLogxK
U2 - 10.1093/neuonc/noy135
DO - 10.1093/neuonc/noy135
M3 - Article
C2 - 30124908
AN - SCOPUS:85059233481
SN - 1522-8517
VL - 21
SP - 71
EP - 82
JO - Neuro-oncology
JF - Neuro-oncology
IS - 1
ER -