# Integrating single-cell RNA sequencing and Mendelian randomization analysis to identify potential drug targets for dilated cardiomyopathy

## TL;DR

This study uses genetic and single-cell data to identify potential drug targets for dilated cardiomyopathy, a heart condition with limited treatment options.

## Contribution

The novel integration of Mendelian randomization and single-cell RNA sequencing reveals new candidate drug targets for DCM.

## Key findings

- IMPA1 and ITIH4 are identified as protective candidates for DCM with consistent evidence across tissues.
- Reduced IMPA1 expression in fibroblasts suggests inositol metabolism dysregulation contributes to DCM fibrosis.
- Fibroblast communication and differentiation are altered in DCM, linking to disease progression.

## Abstract

Dilated cardiomyopathy (DCM), a leading cause of heart failure and sudden cardiac death, lacks therapies targeting disease progression. Genome-wide association studies (GWAS) have identified genetic loci linked to DCM, but translating these findings into actionable drug targets remains challenging. Integrating the druggable genome with multi-omics approaches offers a promising strategy for precision therapy.

We combined Mendelian randomization (MR), Bayesian co-localization, and single-cell RNA sequencing to identify causal drug targets for DCM. Tissue-specific cis-eQTL and pQTL datasets from heart and blood tissues were analyzed using two-sample MR, Steiger filtering, and summary-data-based MR (SMR). Single-cell transcriptomic data (GSE145154) from DCM and control hearts were processed for cellular annotation, communication, and pseudo-time analysis.

MR and co-localization identified IMPA1 and ITIH4 as protective candidates for DCM, with consistent evidence across cardiac and blood tissues (PPH4 > 0.75). SMR and HEIDI tests confirmed shared causal variants between protein expression and DCM. Single-cell analysis revealed reduced IMPA1 expression in activated fibroblasts of DCM hearts, implicating inositol metabolism dysregulation in fibrosis. ITIH4 showed associations with metabolic traits but no adverse cardiac effects. Fibroblast subpopulations exhibited altered communication and differentiation trajectories in DCM, highlighting their role in disease progression.

This multi-omics study prioritizes IMPA1 and ITIH4 as transcriptomic candidates with suggestive causal associations to DCM, linking inositol signaling and extracellular matrix stability to disease mechanisms. These findings underscore the potential of integrating genomics and single-cell transcriptomics to accelerate drug discovery in cardiovascular diseases.

The online version contains supplementary material available at 10.1186/s41065-025-00539-9.