MedicinePsychology

Zhifei Sun, Xiaoding Wang, Qinghe Zhao, Li Xin, P. Zhao, XiaoQing Wang, Dacheng Liu

2026.1.20INTERNATIONAL JOURNAL OF PSYCHIATRY IN MEDICINE

DOI: 10.1177/00912174251393073

tlooto Summary

A causal relationship between genetically predicted AF and a heightened risk of depression was found and 15 single nucleotide polymorphisms (SNPs) as markers were found using 15 single nucleotide polymorphisms as markers.

Abstract

BackgroundThis research assessed the causal influence of atrial fibrillation (AF) on depression.MethodsA two-sample Mendelian randomization (MR) approach was utilized along with data from additional databases. A genome-wide association study (GWAS) involving 463,010 participants allowed for the exploration of genetic variations associated with AF. Another GWAS with 215,644 individuals offered insights into the relationship between gene variants and depression. Data on the correlation between gene variants and depression were obtained from another GWAS encompassing 449,414 individuals. Effect sizes were assessed utilizing the inverse-variance weighted technique. Sensitivity analysis was conducted by weighted median, outlier, MR pleiotropy residual sum, weighted mode, and MR-Egger. A meta-analysis of the inverse-variance weighted (IVW) results from the two datasets was conducted.ResultsA significant association was found between genetically predicted AF and increased incidence of depression using 15 single nucleotide polymorphisms (SNPs) as markers. No evidence of gene pleiotropy was detected, as indicated by MR-Egger. Sensitivity analyses employing alternative Mendelian randomization techniques consistently yielded robust results. The combined odds ratio for depression was estimated at 29.19 (95% CI = 4.43-192.13, P < 0.001).ConclusionThis study found a causal relationship between genetically predicted AF and a heightened risk of depression.

Citation format

SUN, Zhifei, et al. Causal association between atrial fibrillation and depression: Evidence from mendelian randomization analyses. INTERNATIONAL JOURNAL OF PSYCHIATRY IN MEDICINE, 2026: 912174251393073.