PO.PS01.07 · 人群科学
多血统甲基化组关联分析鉴定乳腺癌的假定风险甲基化标志物
Multi-ancestry methylation-wide association analyses identifies putative risk methylation markers for breast cancer
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摘要 Abstract
中文摘要
引言：异常DNA甲基化是癌症的一个标志。鉴定与乳腺癌风险相关的甲基化位点（CpG）有助于阐明疾病机制并为精准预防提供依据。我们开展了一项基于乳腺组织的多血统甲基化组关联研究（MeWAS），以发现乳腺癌易感CpG。
方法：我们使用Illumina MethylationEPIC芯片对来自152名非洲血统和267名欧洲血统女性的正常乳腺组织进行了DNA甲基化分析，并配有匹配的基因型数据。我们为每个甲基化标志物训练了血统特异性的遗传预测模型，然后通过将S-PrediXcan应用于血统匹配的乳腺癌GWAS汇总统计（欧洲：133,384例病例和113,789例对照；非洲：18,044例病例和22,187例对照）来检验其与乳腺癌风险的关联。我们还按雌激素受体状态（ER+、ER−）和三阴性乳腺癌（TNBC）进行了分层分析。随后使用METAL进行固定效应逆方差加权荟萃分析。使用R包missMethyl评估甲基化集富集分析。
结果：我们成功构建了160,204个非洲血统和166,069个欧洲血统的甲基化填补模型（R>0.1且P<0.05）。跨血统荟萃分析鉴定出625个CpG，其遗传预测的甲基化水平与总体乳腺癌风险显著相关（Bonferroni校正P<0.05），其中458个（73.3%）在先前的乳腺组织MeWAS中未曾报道。值得注意的是，cg23766285的遗传替代甲基化水平与总体乳腺癌风险之间的显著关联仅在非洲血统中观察到。在两个血统中均具有有效预测模型的308个CpG中，265个（86.0%）显示出一致的关联方向。我们另外鉴定出分别在Bonferroni校正P<0.05下专门与ER+、ER−乳腺癌和TNBC风险相关的32、11和11个CpG。与总体风险（比值比[OR]，1.19；95%置信区间[CI]，1.02-1.39）、ER−乳腺癌（OR，1.97；95% CI，1.29-3.05）和TNBC（OR，2.12；95% CI，1.27-3.61）相关的CpG在启动子区富集，而ER+相关的CpG则不然。所鉴定的CpG参与多种生物学过程，包括激素、p53和KRAS信号通路。
讨论：这是乳腺癌中首个多血统、大规模、基于组织的MeWAS。我们的发现为乳腺癌发生和乳腺癌差异提供了新的见解。
查看英文原文 English abstract
Introduction: Aberrant DNA methylation is a hallmark of cancer. Identifying methylation sites (CpGs) associated with breast cancer risk may help to elucidate disease mechanisms and inform precision prevention. We conducted a multi-ancestry breast tissue-based methylome-wide association study (MeWAS) to discover breast cancer susceptibility CpGs.
Methods: We profiled DNA methylation in normal breast tissue from 152 African ancestry and 267 European ancestry women using the Illumina MethylationEPIC array, with matched genotype data. We trained ancestry-specific genetic prediction models for each methylation marker, and then tested associations with breast cancer risk by applying S-PrediXcan to ancestry-matched breast cancer GWAS summary statistics (European:133,384 cases and 113,789 controls; African :18,044 cases and 22,187 controls)). We also performed stratified analyses by estrogen receptor status (ER+, ER−) and triple-negative breast cancer (TNBC). Then fixed effect inverse variance weighted meta-analysis was conducted using METAL. Methylation set enrichment analysis was evaluated using R missMethyl.
Results: We successfully built 160,204 African ancestry and 166,069 European ancestry methylation imputation models (R > 0.1 and P < 0.05). Meta-analysis across ancestries identified 625 CpGs whose genetically predicted methylation levels were significantly associated with overall breast cancer risk (Bonferroni-adjusted P < 0.05), 458 (73.3%) of which have not been reported in prior breast tissue MeWAS. Notably, the significant association between genetically proxied methylation levels of cg23766285 and overall breast cancer risk were only observed among African Ancestry. Among 308 CpGs with valid prediction models in both ancestries, 265 (86.0%) showed concordant directions of association. We additionally identified 32, 11, and 11 CpGs that were exclusively associated with risk of ER+ and ER- breast cancer and TNBC at Bonferroni corrected P <0.05, respectively. CpGs associated with overall risk (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.39), ER- breast cancer (OR, 1.97; 95% CI, 1.29-3.05), and TNBC (OR, 2.12; 95% CI, 1.27-3.61) were enriched in promoter regions, whereas ER+-associated CpGs were not. The identified CpGs are involved in various biological processes, including hormone, p53, and KRAS signaling pathways.
Discussion: This is the first multi-ancestry, large-scale, tissue-based MeWAS in breast cancer. Our findings offer novel insight into breast carcinogenesis and breast cancer disparities.
利益披露 Disclosure
S. Xu, None..
J. Shi, None..
Y. Lu, None.