Key points are not available for this paper at this time.
Lung cancer (LC) and heart failure (HF) frequently co-occur with substantial clinical consequences, yet their shared genetic architecture remains poorly characterized. Emerging evidence suggests common pathophysiological pathways may underlie this comorbidity, particularly involving neural signaling and inflammatory processes. We conducted cross-trait meta-analyses of genome-wide association studies (GWAS) encompassing 23 cancer types and 14 cardiovascular diseases using MTAG and CPASSOC. Tissue-specific expression patterns were evaluated using GTEx data, while single-cell RNA sequencing analyzed differential gene expression in HF patients and LC cases compared to healthy controls. Pharmacological screening was performed using DrugBank and PharmGKB databases to identify potential therapeutic candidates. Our analyses identified 48 pleiotropic single nucleotide polymorphisms clustered within chromosome 15q25.1 that were significantly associated with both LC and HF (p < 1 × 10− 76). These variants implicated key genes including CHRNA3, CHRNA5, HYKK, and PSMA4, which demonstrated enrichment in neuroactive ligand-receptor interaction pathways and specific expression in cardiac tissues and immune cells. Twenty candidate drugs targeting cholinergic pathways were identified. These findings uncover a shared genetic locus and neural pathways underlying LC-HF comorbidity, offering mechanistic insights and therapeutic opportunities. The results highlight the need for integrated cardiology-oncology approaches in managing these complex conditions. Graphical overview of the integrative pipeline employed to uncover the shared genetic architecture between lung cancer and heart failure. The workflow sequentially applies genome-wide LD-score regression to estimate genetic correlation, cross-trait analyses to pinpoint pleiotropic loci, gene- and pathway-level enrichment to highlight convergent biology, tissue-specific eQTL colocalization to map regulatory effects, cross-phenotype network interrogation to reveal broader disease connections, and drug–target matching to identify repurposing opportunities, culminating in a PheWAS summary that contextualizes the clinical relevance of the identified variants
Mu et al. (Mon,) studied this question.