Whole genome sequence analysis of pulmonary function and COPD in 44,287 multi-ancestry participants

Whole genome sequence (WGS) data in multi-ancestry samples supports discovery of low-frequency or population-specific genetic variants associated with chronic obstructive pulmonary disease (COPD) and lung function. We performed single variant, structural variant, and gene-based analysis of pulmonary function (FEV 1 , FVC and FEV 1 /FVC) and COPD case–control status in 44,287 multi-ancestry participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We validated findings using the UK Biobank and assessed implicated genes using lung single-cell RNA-seq (scRNA-seq) data sets. Applying a genome-wide significance threshold ( P < 5 × 10 –9 ), we replicated known loci and identified novel associations near LY86 , MAGI1, GRK7, and LINC02668 . Colocalization with gene expression quantitative trait loci (eQTL) from the Lung Tissue Research Consortium highlighted known candidate genes including ADAM19, THSD4 , C4B , and PSMA4 , which were not identified through other eQTL sources. Multi-ancestry analysis improved fine-mapping resolution (e.g., HTR4 and RIN3 ). Gene-based analysis identified and replicated HMCN1 . In human lung scRNA-seq data sets, lung epithelial cells and immune cell types showed enriched expression, while fibroblasts showed higher expression for HMCN1 . CRISPR targeting HMCN1 in IMR90 demonstrated reduced expression of collagen genes. Large-scale multi-ancestry WGS analysis improves variant discovery and fine-mapping resolution for lung function and COPD and highlights biologically relevant genes and pathways.