Genetic and multi-omics characterization of idiopathic pulmonary fibrosis in a Chinese cohort

Most genes are shared across populations, but variant frequencies differ across ancestries and may influence disease susceptibility. In idiopathic pulmonary fibrosis (IPF), exome-based evidence from Chinese cohorts remains limited. This study used an integrative multi-omics strategy to prioritize genetically supported candidate genes in a Chinese IPF cohort. Peripheral blood whole-exome sequencing (WES) was performed in 72 patients with IPF and 30 healthy controls. Variant-level associations were evaluated using Fisher’s exact test followed by Firth bias-corrected logistic regression, and gene-level burden signals were assessed using sequence kernel association test-optimal unified test (SKAT-O). Candidate genes were further cross-validated in an independent lung bulk RNA-seq dataset. Protein-protein interaction analysis and four machine learning algorithms were then applied for candidate prioritization. Lung single-cell RNA sequencing data were used for cell-type-specific expression mapping, and virtual knockout analysis was performed to assess downstream network perturbation. Variant-level analysis identified 188 nominally significant loci, of which 111 remained significant after Firth regression. Gene-burden analysis identified 227 genes with nominal significance. Cross-validation with lung bulk RNA-seq yielded 47 overlapping genes supported by both genetic and expression evidence. Subsequent protein-protein interaction and machine learning analyses prioritized three candidate genes, PDCD1 , MYH11 , and PYGM . Single-cell analysis localized PDCD1 mainly to CD8 + cytotoxic T cells, MYH11 to pericytes and smooth muscle cells, and PYGM to alveolar macrophages. Virtual knockout analysis further linked these genes to immune regulation, cytoskeletal remodeling, and metabolic stress, respectively. In this study, integrative genetic and multi-omics analyses of a Chinese IPF cohort prioritized PDCD1 , MYH11 , and PYGM as candidate genes linked to immune regulation, cytoskeletal remodeling, and metabolic stress, respectively. These findings provide a population-specific molecular view of IPF and highlight biologically informed candidates for further mechanistic investigation.