Abstract
Cardiomyopathy often results in heart failure and mortality, significantly impairing patients' quality of life. Advancements in genomics and proteomics now enable the identification of proteins associated with cardiomyopathy, offering valuable insights for its diagnosis and treatment. However, numerous potential pathogenic proteins remain unidentified, underscoring the need for further exploration of novel drug targets for cardiomyopathy. This study aims to employ Mendelian randomization (MR) to explore genetic associations between plasma proteins and cardiomyopathies, with the objective of identifying potential drug targets. Two-sample MR was employed to investigate causal relationships between cardiomyopathies and plasma proteins, using summary data from genome-wide association studies of different cardiomyopathy subtypes, such as dilated cardiomyopathy, hypertrophic cardiomyopathy (HCM), and restrictive cardiomyopathy (RCM). Cis-protein quantitative trait loci retrieved from the deCODE database served as genetic instruments. Steiger filtering was applied to assess and validate reverse causality. Enrichment analysis was conducted to elucidate potential biological effects, while protein-protein interaction networks were examined to explore interactions among proteins. Molecular docking was employed to evaluate the binding affinity between drugs and their targets. The MR analysis identified 70 significant proteins linked to cardiomyopathy, 12 to dilated cardiomyopathy, 60 to HCM, and 103 to RCM. Intersection analysis revealed 24 significant proteins. Following multiple hypothesis testing, 2 significant proteins (CCL17, SERPINA4) were identified for HCM, and 16 significant proteins (APOL3, C1QL1, CNDP1, CRLF1, CSF2RB, CTSH, GABARAPL2, GP1BA, ICAM5, NPPB, NTM, PDCD5, PTPRS, RNASET2, RTN4R, TCN2) were identified for RCM. Reverse causality testing provided no evidence of reverse causality for any positive genes. Enrichment analysis of protein-protein interaction networks indicated a potential biological role for the positive proteins. Moreover, potential drug targets for treating cardiomyopathy were identified. The genetic associations between plasma proteins and cardiomyopathy were analyzed, leading to the identification of specific proteins as potential biomarkers. Additionally, novel drug targets were identified, providing valuable insights for the diagnosis and treatment of cardiomyopathy.