A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics “vertical” approach that integrates multiple analytical steps using linear and logistic regression models. In a case–control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression–protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2–3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age...