Program in Genetic Epidemiology and Statistical Genetics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Genet Epidemiol. 2020 Jul;44(5):442-468. doi: 10.1002/gepi.22288. Epub 2020 Mar 1.
Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.
先前的转录组全基因组关联研究(TWAS)通过整合表达数量性状基因座和全基因组关联研究(GWAS)的数据,鉴定了乳腺癌风险基因,但对乳腺癌亚型特异性关联的分析有限。在这项研究中,我们使用 GTEx 的基因表达数据和迄今为止针对乳腺癌整体进行的最大 GWAS 荟萃分析的汇总统计数据进行了 TWAS,并按雌激素受体亚型(ER+和 ER-)进行了分析。我们进一步使用仅病例 TWAS 方法比较了与 ER+和 ER-亚型的关联。我们还在多个 TWAS 关联的区域进行了多基因条件分析。两个基因,STXBP4 和 HIST2H2BA,与 ER+乳腺癌但与 ER-乳腺癌无关。我们进一步确定了 30 个与总体乳腺癌风险相关的 TWAS 显著基因,其中包括四个在以前的研究中未发现的基因。条件分析在六个含有多个 TWAS 显著基因的区域中的三个区域中确定了单个独立的乳腺癌基因。我们的研究提供了乳腺癌遗传学和生物学的新信息,特别是关于 ER+和 ER-乳腺癌之间的基因组差异。