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Abstract <p>To investigate the potential causal relationship between gut microbiota (GM) and Alzheimer’s disease (AD) using Mendelian randomization (MR) approach. Genetic data from 18 340 individuals across 24 cohorts, collected by the MiBioGen consortium, were utilized. A total of 211 microbial taxa were initially identified; after excluding 15 taxa classified as ‘unknown,’ 196 were included in the batch analysis. Summary statistics for AD were extracted from a public GWAS database. Two-sample MR analysis was performed using the inverse-variance weighted (IVW) method, the weighted median method, and MR-Egger regression. Odds ratios (ORs) were calculated to estimate the causal effect of gut microbiota on AD. Heterogeneity and horizontal pleiotropy were assessed. A forest plot was generated to visualize the association between instrumental variable-related gut microbiota and AD risk. Four single nucleotide polymorphisms associated with gut microbiota were selected as instrumental variables. IVW results indicated that Desulfovibrio (OR = 1.0131, 95% CI: 1.0037 to 1.0224, <i>P</i> = 0.0059) and Defluviitaleaceae (OR = 1.0201, 95% CI: 0.999 to 1.0412, <i>P</i> = 0.0169) exhibited a positive causal effect on AD risk. Conversely, Slackia (OR = 0.9991, 95% CI: 0.9984 to 0.9999, <i>P</i> = 0.0259) and Lachnospiraceae NK4A136 group (OR = 0.999, 95% CI: 0.9982 to 0.9998, <i>P</i> = 0.0176) showed a negative causal effect on AD risk. Sensitivity analyses revealed no significant evidence of horizontal pleiotropy or heterogeneity. Conclusion: Gut microbiota plays a significant role in the pathophysiology of AD. The specific underlying mechanisms require further investigation.</p>

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Exploring the Causal Relationship between Gut Microbiota and Alzheimer’s Disease Based on Mendelian Randomization

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • J. Wang,
  • Ya H. Liu,
  • Zh. Cui

摘要

Abstract

To investigate the potential causal relationship between gut microbiota (GM) and Alzheimer’s disease (AD) using Mendelian randomization (MR) approach. Genetic data from 18 340 individuals across 24 cohorts, collected by the MiBioGen consortium, were utilized. A total of 211 microbial taxa were initially identified; after excluding 15 taxa classified as ‘unknown,’ 196 were included in the batch analysis. Summary statistics for AD were extracted from a public GWAS database. Two-sample MR analysis was performed using the inverse-variance weighted (IVW) method, the weighted median method, and MR-Egger regression. Odds ratios (ORs) were calculated to estimate the causal effect of gut microbiota on AD. Heterogeneity and horizontal pleiotropy were assessed. A forest plot was generated to visualize the association between instrumental variable-related gut microbiota and AD risk. Four single nucleotide polymorphisms associated with gut microbiota were selected as instrumental variables. IVW results indicated that Desulfovibrio (OR = 1.0131, 95% CI: 1.0037 to 1.0224, P = 0.0059) and Defluviitaleaceae (OR = 1.0201, 95% CI: 0.999 to 1.0412, P = 0.0169) exhibited a positive causal effect on AD risk. Conversely, Slackia (OR = 0.9991, 95% CI: 0.9984 to 0.9999, P = 0.0259) and Lachnospiraceae NK4A136 group (OR = 0.999, 95% CI: 0.9982 to 0.9998, P = 0.0176) showed a negative causal effect on AD risk. Sensitivity analyses revealed no significant evidence of horizontal pleiotropy or heterogeneity. Conclusion: Gut microbiota plays a significant role in the pathophysiology of AD. The specific underlying mechanisms require further investigation.