A mechanistic study of bisphenol a exposure on asthma through integrating clinical research, network toxicology, machine learning, and multi-omics

IntroductionBPA exposure is known to be correlated with asthma incidence. This study aimed to investigate the molecular mechanisms underlying bisphenol A (BPA)-induced asthma.MethodsIn this study, network toxicology, machine learning, and bioinformatics approaches were integrated with differential expression analysis across multiple datasets. Clinical validation was performed using serum BPA measurement, lung function tests, and quantitative PCR in peripheral blood mononuclear cells.ResultsBPA w