BIDIRECTIONAL TWO-SAMPLE MENDELIAN RANDOMIZATION STUDY OF AUTOIMMUNE HEPATITIS AND PREMATURE OVARIAN INSUFFICIENCY
Keywords:
Autoimmune hepatitis, Premature ovarian insufficiency, Bidirectional Mendelian randomizationAbstract
Objective: To explore the bidirectional causal relationship between autoimmune hepatitis (AIH) and premature ovarian insufficiency (POI) by bidirectional Mendelian randomization (MR). Methods: Bidirectional MR analysis was used to explore the causal effect of AIH as the exposure factor and POI as the outcome index in the forward direction, and POI as the exposure factor and AIH as the outcome index in the reverse direction. Genome-wide association study (GWAS) data for AIH and POI were obtained from the IEU Open GWAS database. Single nucleotide polymorphisms (SNPs) that were strongly associated and independent were selected as instrumental variables (IVs) according to a predefined threshold. The causal association between AIH and POI was evaluated using inverse variance weighted (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode methods. Heterogeneity among SNPs was assessed using Cochran's Q test. The MR-PRESSO test was applied to detect potential outlier SNPs. Horizontal pleiotropy was examined using the MR-Egger intercept test. A leave-one-out sensitivity analysis was performed to determine whether the MR results were driven by any single SNP. Results: The IVW analysis in the forward MR revealed no causal relationship between AIH and the onset of POI (OR = 1.06, 95% CI:0.88-1.29, P = 0.54). In the reverse MR, the IVW analysis indicated a statistically significant association between genetically predicted POI and a reduced risk of AIH (OR = 0.94, 95% CI:0.89-0.99, P = 0.02). No evidence of horizontal pleiotropy or heterogeneity was detected for any instrumental variable in the bidirectional MR analysis. Conclusion: The forward MR analysis does not support a causal effect of AIH on POI. The reverse MR analysis suggests that POI may reduce the risk of AIH. However, the observed effect size is small. This causal inference requires cautious interpretation. Future studies with larger sample sizes are needed for validation.References
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