PDF(Pubmed)
Abstract：
Previous epidemiologic studies have suggested a potential negative correlation between total cholesterol (TC) and Gastric cancer (GC); however, several observational studies have shown conflicting results and have failed to provide definitive evidence for a causal relationship between TC and GC. Therefore, we conducted a 2-sample bidirectional Mendelian randomization (MR) study to explore the genetic correlation and potential causal relationship between the 2 variables. We screened for single nucleotide polymorphisms (SNPs) associated with TC and GC utilizing a large-scale genome-wide association study (GWAS) public database. The causal relationship was analyzed using 5 MR analysis methods: inverse variance weighting (IVW), weighted median, MR-Egger regression, weighted mode, and simple mode. Additionally, reverse MR analysis was performed to evaluate the possibility of reverse causality. Sensitivity analyses were conducted, including heterogeneity tests, horizontal multiple validity tests, and leave-one-out tests. After meticulous screening, 79 SNPs were identified as instrumental variables (IVs). The IVW method revealed a causal relationship between TC and GC (OR = 0.844; 95% CI: 0.741-0.961; P = .01). Sensitivity analyses did not detect significant horizontal pleiotropy. Though heterogeneity was observed in the forward MR analysis (IVW, Qp = 0.0006), the results remained reliable as we utilized the IVW random-effects model as the primary analytical method. Furthermore, inverse MR analysis found no evidence of reverse causality between TC and GC, effectively ruling out the influence of GC on the reverse causality of TC. Our MR study provided evidence of a causal association between TC and GC, suggesting that TC acts as a protective factor against GC due to its negative association with the disease.
摘要：
先前的流行病学研究表明，总胆固醇（TC）与胃癌（GC）之间存在潜在的负相关；然而，一些观察性研究显示结果相互矛盾,未能为TC和GC之间的因果关系提供明确的证据.因此,我们进行了2个样本的双向孟德尔随机化(MR)研究,以探讨这2个变量之间的遗传相关性和潜在的因果关系.我们利用大规模全基因组关联研究（GWAS）公共数据库筛选了与TC和GC相关的单核苷酸多态性（SNP）。使用5种MR分析方法分析因果关系：方差反加权(IVW)，加权中位数，MR-Egger回归，加权模式，和简单的模式。此外,进行反向MR分析以评估反向因果关系的可能性.进行了敏感性分析，包括异质性测试，横向多重有效性测试，和遗漏一次测试。经过精心筛选,79个SNP被鉴定为工具变量(IVs)。IVW方法揭示了TC和GC之间的因果关系（OR=0.844；95％CI：0.741-0.961；P=0.01）。敏感性分析未检测到显着的水平多效性。尽管在正向MR分析中观察到异质性(IVW，Qp=0.0006),我们使用IVW随机效应模型作为主要分析方法,结果仍然可靠.此外，反向MR分析没有发现TC和GC之间存在反向因果关系的证据，有效排除GC对TC反向因果关系的影响。我们的MR研究提供了TC和GC之间因果关系的证据，这表明TC作为抗GC的保护因子，因为它与疾病负相关。
