<![CDATA[Lung diseases induced by environmental exposures such as air pollution, cigarette smoke, and industrial particles remain a significant global health concern, contributing to high morbidity and mortality rates. Genetic variations are known to influence individual responses to environmental exposures, but the molecular mechanisms underlying these interactions are not well understood. This study aims to identify genetic variants, specifically Single Nucleotide Polymorphisms (SNPs), that may increase the risk of lung diseases using a bioinformatics approach. The analysis was conducted by integrating various public genetic databases, including PheWAS, GWAS Catalog, HaploReg v4.2, GTEx Portal, and Ensembl Genome Browser. SNPs were filtered based on p-value < 0.05 and odds ratio (OR) > 1. Missense mutations in selected SNPs were further analyzed for gene expression in lung tissue and distribution across populations. From an initial 151 SNPs, 86 met the statistical criteria, and six were identified as missense variants. Two genes, TNIP1 and PSMB8, showed significantly high expression in lung tissue. SNP rs2071543 in PSMB8 exhibited a strong correlation with increased gene expression and demonstrated notable allele frequency variation across populations. These findings suggest that genetic variations, particularly in PSMB8, may contribute to individual susceptibility to lung diseases induced by environmental exposures. This study highlights the importance of multidatabase analysis in identifying genetic biomarkers and provides a foundation for the development of precision therapies for multifactorial lung diseases.]]>
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