Genetically predicted 486 blood metabolites in relation to risk of esophageal cancer: a Mendelian randomization study.

IF 3.9 3区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Frontiers in Molecular Biosciences Pub Date : 2024-10-02 eCollection Date: 2024-01-01 DOI:10.3389/fmolb.2024.1391419

Caiyan Jia, Dan Yi, Mingze Ma, Qian Xu, Yan Ou, Fanming Kong, Yingjie Jia

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Abstract

Background and objective: 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.

Methods: 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.

Results: 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).

Conclusion: This study establishes a causal link between three defined blood metabolites and esophageal cancer, offering fresh insights into its pathogenesis.

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基因预测的 486 种血液代谢物与食管癌风险的关系：孟德尔随机研究。

背景和目的：针对食管癌的不同阶段加强治疗选择和提高患者生存率取决于及时和精确的诊断。血液代谢物可能在导致或预防食管癌方面发挥作用，但要确定血液代谢物是否构成食管癌的遗传风险因素，还需要进一步研究。为了解决这些问题，我们利用双样本孟德尔随机化（MR）研究评估了食管癌与 486 种血液代谢物之间的因果关系，这些代谢物可作为遗传替代物：我们利用双样本 MR 分析来评估血液代谢物与食管癌之间的因果关系。在暴露方面，我们使用了对 486 种代谢物的全基因组关联研究（GWAS），并使用了 Sakaue 等人对食管癌的 GWAS 研究进行初步分析。因果分析以随机逆方差加权（IVW）为主要方法，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leave-one-out分析。此外，还利用独立的食管癌 GWAS 数据进行了复制和荟萃分析。应用FDR校正来识别具有因果关系的特征。为了确定代谢物，我们进行了 Steiger 检验、连锁不平衡评分回归和共定位分析。此外，我们还利用 MetaboAnalyst 5.0 程序分析了代谢途径：本研究发现食管癌与三种代谢物有重要关联：1-亚油酰甘油磷酸乙醇胺*[比值比（OR）=3.21，95% 置信区间（CI）：1.42-7.26，P <0.01]、焦谷氨酰胺*（OR = 1.92，95% CI：1.17-3.17，P <0.01）和月桂酸酯（12:0）（OR = 3.06，95% CI：1.38-6.78，P <0.01）：本研究确定了三种明确的血液代谢物与食管癌之间的因果关系，为食管癌的发病机制提供了新的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Molecular Biosciences Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

7.20

自引率

4.00%

发文量

1361

审稿时长

14 weeks

期刊介绍： Much of contemporary investigation in the life sciences is devoted to the molecular-scale understanding of the relationships between genes and the environment — in particular, dynamic alterations in the levels, modifications, and interactions of cellular effectors, including proteins. Frontiers in Molecular Biosciences offers an international publication platform for basic as well as applied research; we encourage contributions spanning both established and emerging areas of biology. To this end, the journal draws from empirical disciplines such as structural biology, enzymology, biochemistry, and biophysics, capitalizing as well on the technological advancements that have enabled metabolomics and proteomics measurements in massively parallel throughput, and the development of robust and innovative computational biology strategies. We also recognize influences from medicine and technology, welcoming studies in molecular genetics, molecular diagnostics and therapeutics, and nanotechnology. Our ultimate objective is the comprehensive illustration of the molecular mechanisms regulating proteins, nucleic acids, carbohydrates, lipids, and small metabolites in organisms across all branches of life. In addition to interesting new findings, techniques, and applications, Frontiers in Molecular Biosciences will consider new testable hypotheses to inspire different perspectives and stimulate scientific dialogue. The integration of in silico, in vitro, and in vivo approaches will benefit endeavors across all domains of the life sciences.