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Neuro Oncol. 2019 Jan 1;21(1):71-82. doi: 10.1093/neuonc/noy135.

Sex-specific gene and pathway modeling of inherited glioma risk.

Author information

1
Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
2
Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA.
3
Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
4
University School, Chagrin Falls, Ohio, USA.
5
Case Western Reserve University, Cleveland, Ohio, USA.
6
Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, USA; Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri, USA.
7
Department of Stem Cell Biology and Regenerative Medicine, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
8
Cancer and Cell Biology Division, The Translational Genomics Research Institute, Phoenix, Arizona, USA.
9
Department of Neurological Surgery, School of Medicine, University of California San Francisco, San Francisco, California, USA.
10
Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
11
Institute for Clinical and Translational Research, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA.
12
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
13
School of Public Health, Yale University, New Haven, Connecticut, USA.
14
Department of Neurosurgery, Brigham and Women's Hospital, Boston, Massachusetts, USA.
15
Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom.
16
Department of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, Georgia, USA.
17
Cancer Control and Prevention Program, Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina, USA.
18
Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina, USA.
19
Department of Laboratory Medicine and Pathology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA.
20
Oncology Clinic, Finsen Center, Rigshospitalet and Survivorship Research Unit, The Danish Cancer Society Research Center, Copenhagen, Denmark.
21
Department of Neurology, Mayo Clinic Comprehensive Cancer Center, Mayo Clinic, Rochester, Minnesota, USA.
22
Departments of Neurology and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
23
Department of Neurology, NorthShore University HealthSystem, Evanston, Illinois, USA.
24
Cancer and Radiation Epidemiology Unit, Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, Israel.
25
Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
26
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
27
Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA.
28
Department of Radiation Sciences, Faculty of Medicine, Umea° University, Umea°, Sweden.
29
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
30
Core Genotyping Facility, National Cancer Institute, SAIC-Frederick, Inc, Gaithersburg, Maryland, USA.
31
Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.

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 × 10-6 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.

PMID:
30124908
PMCID:
PMC6303471
[Available on 2020-01-01]
DOI:
10.1093/neuonc/noy135

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