Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA.
Neuro Oncol. 2019 Jan 1;21(1):71-82. doi: 10.1093/neuonc/noy135.
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.
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.
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.
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.
迄今为止，全基因组关联研究（GWAS）已经确定了 25 个与神经胶质瘤相关的风险变异，这些变异可以解释 30%的遗传风险。大多数组织学类型的神经胶质瘤在男性中的发病率明显更高，而目前已知的风险因素并不能解释这种差异。先前的 GWAS 确定了性别特异性的神经胶质瘤风险变异，本分析旨在通过基因和途径方法进一步阐明性别间的风险变化。
使用Glioma International Case-Control Study 的结果作为测试集，并通过荟萃分析结合 3 项 GWAS 的结果作为验证集。使用先前荟萃分析中名义上显著的常染色体 SNP（P < 0.01）和名义上显著的 X 染色体 SNP（P < 0.01）的汇总统计数据，使用 3 种算法（Pascal、BimBam 和 GATES）生成基因评分，并用 Pascal 生成途径评分。在发现集中，当 P < 3.3×10-6 时，结果在 3 种算法中的 2 种中具有统计学意义；在验证集中，当在 3 种算法中的 2 种中 P < 0.001 时，结果具有统计学意义。
在男性和女性中，分别有 25 个基因位于 5 个区域内，19 个基因位于 6 个区域内，在至少 2 种算法中达到统计学意义。EGFR 仅与男性的所有神经胶质瘤和胶质母细胞瘤显著相关，TERT 与女性的神经胶质瘤显著相关，在考虑已知风险位点后，这些结果仍然具有统计学意义。男性和女性的 BioCarta 端粒体途径均具有名义上的相关性。
这些结果提供了更多证据，表明性别可能会影响神经胶质瘤的遗传风险。进一步的分析可能会进一步阐明风险的生物学过程。
