Multi-Omics and network-based exploration of potential molecular pathways in heart failure relevant to left bundle branch pacing response heterogeneity: Immune remodeling, hub gene identification, and drug repurposing hypotheses

Left bundle branch pacing (LBBP) has gained increasing attention as a novel pacing strategy, but its molecular underpinnings in the context of heart failure (HF) remain unclear due to limited LBBP-specific datasets.We integrated three GEO datasets (GSE5406, GSE19303, GSE21610) representing HF transcriptomics and performed batch correction, differential expression analysis, functional enrichment, immune infiltration profiling, weighted gene co-expression network analysis (WGCNA), hub gene identification, and drug-pathway prediction.PCA demonstrated successful batch correction across datasets. Differentially expressed genes (DEGs), including HOPX, NPPA, MYH6, SERPINA3, and ASPN, were identified. Enrichment analyses indicated extracellular matrix remodeling, cardiac development, and cGMP-PKG signaling. Immune analysis showed significant alterations in B cell memory, plasma cells, CD8 T cells, regulatory T cells, NK cells, monocytes, macrophages (M0/M1/M2), dendritic cells, and mast cells. WGCNA highlighted significant modules (MEpink, MElightyellow, MEyellow, MEgreenyellow) associated with treatment response. Hub gene analysis confirmed ASPN, HOPX, MYH6, SERPINA3, and NPPA as key drivers. Drug prediction suggested multiple candidates, including β-blockers, RAAS inhibitors, anti-fibrotic agents, vericiguat, metformin, and SGLT2 inhibitors.This integrative analysis of HF transcriptomics reveals potential immune remodeling, hub genes, and repurposable drugs relevant to LBBP response heterogeneity, providing hypothesis-generating insights and potential therapeutic strategies for validation in LBBP-specific cohort.