Introduction/objectives: Several observational investigations have observed the possible links between Alzheimer's disease (AD) and metabolic dysfunction associated with fatty liver disease (MAFLD), yet the underlying causal relationships remain undetermined. This study aimed to systemically infer the causal associations between AD and MAFLD by employing a bidirectional network two-sample Mendelian randomization (MR) analysis.
Methods: Genome-wide significant (P < 5 × 10) genetic variants associated with AD and MAFLD were selected as instrumental variables (IVs) from the consortium of FinnGen, MRC-IEU, UK biobank, and genome-wide association studies (GWAS), respectively. The study sample sizes range from 55,134 to 423,738 for AD and from 218,792 to 778,614 for MAFLD. In the forward analysis, AD was set as the exposure factor, and MAFLD was employed as the disease outcome. Causal relationships between AD and MAFLD were evaluated using inverse-variance weighted (IVW), MR Egger regression, the weighted median, and weighted mode. Additionally, the reverse MR analysis was conducted to infer causality between MAFLD and AD. Sensitivity analyses were performed to assess the robustness of causal estimates.
Results: In the forward MR analysis, the genetically determined family history of AD was associated with a lower risk of MAFLD (mother's history: OR=0.08, 95%CI: 0.03, 0.22, P = 7.91 × 10; OR=0.83, 95%CI: 0.74, 0.94, P = 3.68 × 10; father's history: OR=0.01, 95%CI: 0.01, 0.08, P = 5.48 × 10; OR=0.79, 95%CI: 0.68, 0.93, P = 4.07 × 10; family history: OR=0.84, 95%CI: 0.77, 0.91, P = 6.30 × 10; OR=0.15, 95%CI: 0.05, 0.41, P = 2.51 × 10) in the primary MAFLD cohort. Consistent findings were observed in an independent MAFLD cohort (all P < 0.05). However, the reverse MR analysis suggested that genetic susceptibility to MAFLD had no causal effects on developing AD.
Conclusion: Our study demonstrates a causal association between a family history of AD and a lower risk of MAFLD. It suggests that individuals with a history of AD may benefit from tailored metabolic assessments to better understand their risk of MAFLD, and inform the development of preventive strategies targeting high-risk populations.
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http://dx.doi.org/10.1007/s11306-024-02193-0 | DOI Listing |
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