Big data and systems biology for biomarker discovery in chronic hypersensitivity pneumonitis and drug repurposing using deep learning-based DTI models

Chronic hypersensitivity pneumonitis (CHP) is commonly associated with repeated inhalation of organic dust-containing microbial agents. The identification and mitigation of exposure to these microbes are key steps in managing and preventing CHP. Therefore, to elucidate the pathogenetic mechanisms underlying fibrosis and identify biomarkers for targeted therapeutics, a systems biology approach integrating large-scale microarray data mining and whole-genome RNA-sequencing data is crucial. In this study, systems biology methodologies were employed to construct genome-wide genetic and epigenetic networks for fibrotic lung cells from CHP patients and healthy controls. Protein-protein interaction networks and gene/microRNA/long non-coding RNA regulatory networks were established using RNA sequencing data, followed by refinement through a system identification framework. By applying principal network projection and the Kyoto Encyclopedia of Genes and Genomes pathway annotation, core signaling pathways and their downstream cellular dysfunctions were identified, revealing key signaling pathways, such as the mitogen-activated protein kinase, phosphoinositide 3-kinase, chemokine (C-X-C motif) ligand (CXCL)/CXC chemokine receptors family, and chemokine (C-C motif) ligand (CCL) family signaling pathways. In addition, significant biomarkers of pathogenetic mechanisms of CHP, such as AKT1, CCL20, cell division cycle 23, CXCL1, nuclear factor-kappa B, and tumor necrosis factor, were identified as potential drug targets of CHP. Significant biomarkers associated with cell inhibitors, cellular dysfunction, and cellular disorders were identified as drug targets in the core disease-causing signaling pathways. Finally, using a deep neural network-based drug-target interaction model and drug design specification, three molecular drugs, azathioprine, masitinib, and primaquine, were screened and proposed as candidates for a multiple-molecular drug for the treatment of CHP.