Shared genetic architecture between heart failure and depression from cross-trait genome-wide analysis

Song Xi; Shi Hongwei

doi:10.3969/j.issn.1002-1949.2025.10.011

Abstract：Objective To evaluate the genetic correlation between heart failure and depression in order to identify shared genetic loci and explore potential causal relationships.Methods We used summary statistics from large-scale genome-wide association studies(GWAS)of heart failure(cases:n=47 309,controls:n=930 014)and depression(cases:n=294 322,controls:n=741 438).Genetic correlation was assessed by using linkage disequilibrium score regression(LDSC).The MiXeR method was applied to estimate the genetic overlap between the two diseases.Conditional/combined false discovery rate(condFDR/conjFDR)frameworks identified loci shared by both diseases,followed by functional annotation.Finally,bidirectional Mendelian randomization(MR)was used to investigate causal relationships between heart failure and depression.Results A significant genetic correlation was found between heart failure and depression(rg=0.286 6,SE=0.028 6,P=1.209 5×10-23).The MiXeR model estimated that 2 100±200 genetic variants contributed to both conditions,indicating substantial overlap.ConjFDR analysis identified seven shared loci:LRRC7,SPATS2L,UBA7,NCR3,GTF2I,IGSF9B,and ASXL3.MR analysis showed that depression increased the risk of heart failure(OR 1.21,95%CI 1.12-1.31,P=2.44×10-6),while reverse MR analysis did not support heart failure as a risk factor for depression.Conclusions This study reveals a genetic correlation between heart failure and depression and depression may increase the risk of heart failure.Though these findings provide initial evidence of shared genetic factors,further research is needed to confirm the biological mechanisms and clinical relevance.