Variation in response to the most commonly used class of asthma controller medication, inhaled corticosteroids (ICS), presents a serious challenge in asthma management, particularly for steroid-resistant patients who display little or no response to treatment.
We applied a systems-biology approach to primary clinical and genomic data to identify and validate genes that modulate steroid response in children with asthma.
We selected 104 ICS-treated asthmatic non-Hispanic white children and determined a Steroid Responsiveness Endophenotype (SRE) using observations of six clinical measures over four years. We modeled each subject's cellular steroid response using data from a previously published study of immortalized lymphoblastoid cell lines (LCL) under dexamethasone (DEX) and sham treatment. We integrated SRE with LCL DEX response and genotypes to build a genome-scale network using the Reverse Engineering, Forward Simulation (REFS) modeling framework, identifying seven genes modulating SRE.
Three of these genes were functionally validated using a stable NFκB Luc reporter in A549 Human lung epithelial cells, IL1β cytokine stimulation, and dexamethasone treatment. Using siRNA transfection, knockdown of Family With Sequence Similarity 129 Member A (FAM129A) produced a reduction in steroid treatment response (p<0.001).
With this systems-based approach, we have shown that FAM129A is associated with variation in clinical asthma steroid responsiveness and that FAM129A modulates steroid responsiveness in lung epithelial cells.