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与食管癌风险相关的486种遗传预测血液代谢物: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.

作者信息

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

机构信息

Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.

National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China.

出版信息

Front Mol Biosci. 2024 Oct 2;11:1391419. doi: 10.3389/fmolb.2024.1391419. eCollection 2024.

DOI:10.3389/fmolb.2024.1391419
PMID:39417005
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11479936/
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, < 0.01], pyroglutamine* (OR = 1.92, 95% CI: 1.17-3.17, < 0.01), and laurate (12:0) (OR = 3.06, 95% CI: 1.38-6.78, < 0.01).

CONCLUSION

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

摘要

背景与目的

增加食管癌不同阶段的治疗选择并提高患者生存率取决于及时、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,但需要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。为了解决这些问题,我们使用两样本孟德尔随机化(MR)研究评估了食管癌与486种作为遗传代理的血液代谢物之间的因果关联。

方法

我们利用两样本MR分析来评估血液代谢物与食管癌之间的因果联系。对于暴露因素,我们使用了一项针对486种代谢物的全基因组关联研究(GWAS),并使用了坂江等人关于食管癌的GWAS研究进行初步分析。因果分析采用随机逆方差加权(IVW)作为主要方法,并辅以MR-Egger和加权中位数(WM)分析。敏感性分析包括MR-Egger截距检验、 Cochr an Q检验、MR-PRESSO和留一法分析。此外,独立的食管癌GWAS数据用于重复验证和荟萃分析。应用FDR校正来识别具有因果关系的特征。为了最终确定代谢物,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,我们使用MetaboAnalyst 5.0程序分析代谢途径。

结果

本研究发现食管癌与三种代谢物之间存在重要关联:1-亚油酰基甘油磷酸乙醇胺*[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(12:0)(OR = 3.06,95% CI:1.38 - 6.78,P<0.01)。

结论

本研究确立了三种特定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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/25f7b952fd5f/fmolb-11-1391419-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/adf96a9e4a99/fmolb-11-1391419-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/f81db9dddf2d/fmolb-11-1391419-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/0a338f5ff8bc/fmolb-11-1391419-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/8d077dd9410e/fmolb-11-1391419-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/25f7b952fd5f/fmolb-11-1391419-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/adf96a9e4a99/fmolb-11-1391419-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/f81db9dddf2d/fmolb-11-1391419-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/0a338f5ff8bc/fmolb-11-1391419-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/8d077dd9410e/fmolb-11-1391419-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/11479936/25f7b952fd5f/fmolb-11-1391419-g005.jpg

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