Work

From early-onset asthma to chronic obstructive pulmonary disease: potential mediating proteins and therapeutic targets

Year: 2026

Type: article

Abstract: BACKGROUND AND OBJECTIVE: Early-onset asthma (EOA) significantly increases the risk of chronic obstructive pulmonary disease (COPD), yet the causal mechanisms and molecular mediators underlying this progression remain poorly understood. Multi-omics integration provides a powerful framework for prioritizing potential mediating proteins and disease-specific therapeutic candidates. METHODS: This study integrated large-scale genetic and proteomic data using Mendelian randomization (MR) approaches to investigate the progression from EOA to COPD. Proteome-wide MR evaluated protein quantitative trait loci (pQTLs) in relation to EOA and COPD risk, with mediation analysis evaluating their roles and single-cell transcriptomics defining the cell-type-specific expression of the mediating proteins. Finally, colocalization, multi-tissue expression quantitative trait loci (eQTLs), and druggability assessment were used to prioritize potential disease-specific therapeutic targets. RESULTS: Evidence from genetic instruments supports a causal relationship between EOA and COPD. Proteome-wide analyses of 7847 pQTLs identified 339 proteins with potential effects on EOA and 389 on COPD. Six proteins, KREMEN1, BLMH, CNTN5, IL1RN, MIA, and PILRA, showed statistically significant mediation effects in the EOA-to-COPD pathway. PILRA strongly colocalized at shared genetic loci between the two diseases and was significantly downregulated in macrophages from COPD patients. For disease-specific targets, immune-tissue eQTL validation supported ITPKA in EOA. Integration of druggability assessment with multi-tissue eQTL analyses prioritized FES, CCN3, NMI, and NMT1 as promising therapeutic candidates for COPD. CONCLUSION: These findings provide genetic evidence supporting a causal relationship between EOA and COPD, reveal putative mediating proteins, and prioritize therapeutic candidates with translational potential, offering new insights into pathogenesis, prevention, and intervention.

Source: Briefings in Bioinformatics

DOI: 10.1093/bib/bbag209