Impact of the gut microbiota and associated metabolites on cardiometabolic traits, chronic diseases and human longevity: a Mendelian randomization study

肠道菌群及其相关代谢产物对心血管代谢特征、慢性疾病和人类寿命的影响:一项孟德尔随机化研究

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Abstract

Features of the gut microbiota have been associated with several chronic diseases and longevity in preclinical models as well as in observational studies. Whether these relations underlie causal effects in humans remains to be established. We aimed to determine whether the gut microbiota influences cardiometabolic traits as well as the risk of chronic diseases and human longevity using a comprehensive 2-Sample Mendelian randomization approach. We included as exposures 10 gut-associated metabolites and pathways and 57 microbial taxa abundance. We included as outcomes nine cardiometabolic traits (fasting glucose, fasting insulin, systolic blood pressure, diastolic blood pressure, HDL cholesterol, LDL cholesterol, triglycerides, estimated glomerular filtration rate, body mass index [BMI]), eight chronic diseases previously linked with the gut microbiota in observational studies (Alzheimer's disease, depression, type 2 diabetes, non-alcoholic fatty liver disease, coronary artery disease (CAD), stroke, osteoporosis and chronic kidney disease), as well as parental lifespan and longevity. We found 7 associations with evidence of causality before and after sensitivity analyses, but not after multiple testing correction (1198 tests). Most effect sizes (4/7) were small. The two largest exposure-outcome effects were markedly attenuated towards the null upon inclusion of BMI or alcohol intake frequency in multivariable MR analyses. While finding robust genetic instruments for microbiota features is challenging hence potentially inflating type 2 errors, these results do not support a large causal impact of human gut microbita features on cardiometabolic traits, chronic diseases or longevity. These results also suggest that the previously documented associations between gut microbiota and human health outcomes may not always underly causal relations.

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