遗传预测的486种血液代谢物与食管癌风险的关系：一项孟德尔随机化研究
Genetically predicted 486 blood metabolites in relation to risk of esophageal cancer: a Mendelian randomization study
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影响因子:4
分区:生物学3区 / 生化与分子生物学3区
发表日期:2024
作者:
Caiyan Jia, Dan Yi, Mingze Ma, Qian Xu, Yan Ou, Fanming Kong, Yingjie Jia
DOI:
10.3389/fmolb.2024.1391419
摘要
提升不同阶段食管癌的治疗选择和改善患者生存率，依赖于及时而准确的诊断。血液代谢物可能在引发或预防食管癌中发挥作用，但仍需进一步研究以确定血液代谢物是否构成该疾病的遗传风险因素。为解决这些问题，我们利用两样本孟德尔随机化（MR）研究评价了486种血液代谢物作为遗传代理物与食管癌的因果关系。我们采用两样本MR分析，使用一项关于486种代谢物的全基因组关联研究（GWAS）数据和Sakaue等人关于食管癌的GWAS数据进行初步分析。因果分析主要采用随机逆方差加权（IVW）方法，辅以MR-Egger和加权中位数（WM）分析。敏感性分析包括MR-Egger截距检验、Cochran Q检验、MR-PRESSO和“逐一剔除”分析。此外，还利用独立的食管癌GWAS数据进行验证和Meta分析。应用FDR校正以识别具有因果关系的特征。为最终确认代谢物，我们进行了Steiger检验、连锁不平衡分数回归和共定位分析。还利用MetaboAnalyst 5.0分析了相关的代谢途径。研究发现，有三种代谢物与食管癌具有显著的因果关系：1-亚油酰甘油磷脂醇胺（OR=3.21，95%CI=1.42-7.26，p<0.01）、吡咯谷氨酰胺（OR=1.92，95%CI=1.17-3.17，p<0.01）和十二烷酸（12:0）（OR=3.06，95%CI=1.38-6.78，p<0.01）。本研究建立了三种血液代谢物与食管癌之间的因果联系，为其发病机制提供了新的见解。
Abstract
Enhancing therapy choices for varying stages of esophageal cancer and improving patient survival depend on timely and precise diagnosis. Blood metabolites may play a role in either causing or preventing esophageal cancer, but further research is needed to determine whether blood metabolites constitute a genetic risk factor for the disease. In order to tackle these problems, we evaluated the causal association between esophageal cancer and 486 blood metabolites that functioned as genetic proxies using a two-sample Mendelian randomization (MR) study.We utilized two-sample MR analyses to evaluate the causal links between blood metabolites and esophageal cancer. For the exposure, we used a genome-wide association study (GWAS) of 486 metabolites, and a GWAS study on esophageal cancer from Sakaue et al. was used for preliminary analyses. Causal analyses employed randomized inverse variance weighted (IVW) as the main method, supplemented by MR-Egger and weighted median (WM) analyses. Sensitivity analyses included the MR-Egger intercept test, Cochran Q test, MR-PRESSO, and leave-one-out analysis. Additionally, independent esophageal cancer GWAS data were utilized for replication and meta-analysis. FDR correction was applied to discern features with causal relationships. For conclusive metabolite identification, we conducted Steiger tests, linkage disequilibrium score regression, and colocalization analyses. Moreover, we utilized the program MetaboAnalyst 5.0 to analyze metabolic pathways.This study found an important association between esophageal cancer and three metabolites: 1-linoleoylglycerophosphoethanolamine* [odds ratio (OR) = 3.21, 95% confidence interval (CI): 1.42-7.26, p < 0.01], pyroglutamine* (OR = 1.92, 95% CI: 1.17-3.17, p < 0.01), and laurate (12:0) (OR = 3.06, 95% CI: 1.38-6.78, p < 0.01).This study establishes a causal link between three defined blood metabolites and esophageal cancer, offering fresh insights into its pathogenesis.