Li Yan, Qianchuan He, Shiv P Verma, Xu Zhang, Ann-Sophie Giel, Carlo Maj, Kathryn Graz, Elnaz Naderi, Jianhong Chen, Mourad Wagdy Ali, Puya Gharahkhani, Xiang Shu, Kenneth Offit, Pari M Shah, Hans Gerdes, Daniela Molena, Amitabh Srivastava, Stuart MacGregor, Claire Palles, René Thieme, Michael Vieth, Ines Gockel, Thomas L Vaughan, Johannes Schumacher, Matthew F Buas
{"title":"生物靶向发现-复制扫描确定G×G与巴雷特食管和食管腺癌风险相关的相互作用。","authors":"Li Yan, Qianchuan He, Shiv P Verma, Xu Zhang, Ann-Sophie Giel, Carlo Maj, Kathryn Graz, Elnaz Naderi, Jianhong Chen, Mourad Wagdy Ali, Puya Gharahkhani, Xiang Shu, Kenneth Offit, Pari M Shah, Hans Gerdes, Daniela Molena, Amitabh Srivastava, Stuart MacGregor, Claire Palles, René Thieme, Michael Vieth, Ines Gockel, Thomas L Vaughan, Johannes Schumacher, Matthew F Buas","doi":"10.1016/j.xhgg.2025.100399","DOIUrl":null,"url":null,"abstract":"<p><p>Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (1) known/plausible links to BE/EAC pathogenesis (n = 493) or (2) prior evidence of biological interactions (n = 4,196). Approximately 75 × 10<sup>6</sup> SNP×SNP interactions were screened via hierarchical group lasso (glinternet) using BEACON GWAS data. The top ∼2,000 interactions retained in each scan were prioritized using p values from single logistic models. Identical scans were repeated among males only (78%), with two independent GWAS datasets used for replication. In overall and male-specific primary replications, 11 of 187 and 20 of 191 interactions satisfied p < 0.05, respectively. The strongest evidence for secondary replication was for rs17744726×rs3217992 among males, with consistent directionality across all cohorts (P<sub>meta</sub> = 2.19 × 10<sup>-8</sup>); rs3217992 \"T\" was associated with reduced risk only in individuals homozygous for rs17744726 \"G.\" Rs3217992 maps to the CDKN2B 3' UTR and reportedly disrupts microRNA-mediated repression. Rs17744726 maps to an intronic enhancer region in BLK. Through in silico prioritization and experimental validation, we identified a nearby proxy variant (rs4841556) as a functional modulator of enhancer activity. Enhancer-gene mapping and eQTLs implicated BLK and FAM167A as targets. 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Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (1) known/plausible links to BE/EAC pathogenesis (n = 493) or (2) prior evidence of biological interactions (n = 4,196). Approximately 75 × 10<sup>6</sup> SNP×SNP interactions were screened via hierarchical group lasso (glinternet) using BEACON GWAS data. The top ∼2,000 interactions retained in each scan were prioritized using p values from single logistic models. Identical scans were repeated among males only (78%), with two independent GWAS datasets used for replication. In overall and male-specific primary replications, 11 of 187 and 20 of 191 interactions satisfied p < 0.05, respectively. 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引用次数: 0
摘要
遗传基因是导致食管腺癌(EAC)及其前体巴雷特食管(BE)风险的重要因素。全基因组关联研究已经确定了约30个BE/EAC的易感性变异,但遗传相互作用仍未得到检验。为了应对大规模G×G扫描中的挑战,我们将知识引导过滤和机器学习方法相结合,重点关注与BE/EAC发病机制(n=493)有已知/可能联系的基因(B)生物相互作用的先前证据(n= 4196)。利用BEACON GWAS数据,通过分层分组lasso (glinternet)筛选~ 75 x 106 SNP×SNP相互作用。使用单个逻辑模型的P值对每次扫描中保留的前2000个相互作用进行优先排序。相同的扫描仅在男性中重复(78%),使用两个独立的GWAS数据集进行复制。在总体和男性特异性的初级重复中,187个相互作用中的11个和191个相互作用中的20个满足Pmeta=2.19×10-8);rs3217992“T”仅在与rs17744726“G”纯合的个体中与风险降低相关。Rs3217992映射到CDKN2B 3'UTR,据报道破坏了microrna介导的抑制。Rs17744726映射到BLK中的内含子增强子区。通过芯片优先级排序和实验验证,我们确定了一个邻近的代理变体(rs4841556)作为增强子活性的功能调节剂。增强基因定位和eQTLs涉及BLK和FAM167A作为靶标。该研究首次在BE/EAC中进行了系统的G×G调查,揭示了BLK基因型与CDKN2B变异的差异风险关联,提示编码肿瘤抑制和炎症关键介质的两个风险位点之间存在新的生物学依赖性。
Biologically targeted discovery-replication scan identifies G×G interaction in relation to risk of Barrett's esophagus and esophageal adenocarcinoma.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (1) known/plausible links to BE/EAC pathogenesis (n = 493) or (2) prior evidence of biological interactions (n = 4,196). Approximately 75 × 106 SNP×SNP interactions were screened via hierarchical group lasso (glinternet) using BEACON GWAS data. The top ∼2,000 interactions retained in each scan were prioritized using p values from single logistic models. Identical scans were repeated among males only (78%), with two independent GWAS datasets used for replication. In overall and male-specific primary replications, 11 of 187 and 20 of 191 interactions satisfied p < 0.05, respectively. The strongest evidence for secondary replication was for rs17744726×rs3217992 among males, with consistent directionality across all cohorts (Pmeta = 2.19 × 10-8); rs3217992 "T" was associated with reduced risk only in individuals homozygous for rs17744726 "G." Rs3217992 maps to the CDKN2B 3' UTR and reportedly disrupts microRNA-mediated repression. Rs17744726 maps to an intronic enhancer region in BLK. Through in silico prioritization and experimental validation, we identified a nearby proxy variant (rs4841556) as a functional modulator of enhancer activity. Enhancer-gene mapping and eQTLs implicated BLK and FAM167A as targets. The first systematic G×G investigation in BE/EAC, this study uncovers differential risk associations for CDKN2B variation by BLK genotype, suggesting novel biological dependency between two risk loci encoding key mediators of tumor suppression and inflammation.