Identification of Emerging Drug Targets for Pulmonary Functions Through Mendelian Randomization Analysis of the Plasma Proteome

Background The deterioration of lung function is strongly linked to a heightened risk of several diseases and an increase in mortality. Conditions such as COPD, ILD and asthma are notably connected to this decline. Proteins with genetic associations hold potential as promising therapeutic targets to enhance lung function. Method Initially, we assessed 4907 plasma genetic markers through MR at deCODE to identify links with lung function, pinpointing potential therapeutic targets. This was followed by pathway analysis, bidirectional MR, Steiger filtering, and colocalization analysis to establish causal links and investigate therapeutic potential. Utilizing this dual-stage network MR design, the mediation effects of proteins in the linkages between smoking, BMI, and lung functions were estimated. Validation was performed utilizing additional datasets from two external databases. Finally, we evaluated the druggability and associated side effects, paving the way for therapeutic interventions in pulmonary conditions. Result This study identifies multiple proteins as promising therapeutic targets for lung function, adhering to Bonferroni standards. Genetically predicted protein levels of 38, 28, and 37 proteins significantly correlate with FEV1, FVC, and FEV1/FVC, respectively, with these results replicated across databases. No reverse causality was found, and Bayesian colocalization analysis shows that 15 proteins share genetic loci with lung function. Some proteins mediate pathways by which BMI and smoking affect lung function. 5 proteins are noteworthy therapeutic targets. Finally, target proteins are associated with few side effects in PheW-MR. Conclusion Our finding indicated that the identified proteins could potentially serve as effective therapeutic targets for lung function.