Identification of Druggable Genes for Asthma by Integrated Genomic Network Analysis

Abstract

Asthma is a common and heterogeneous disease characterized by chronic airway inflammation. Currently, the two main types of asthma medicines are inhaled corticosteroids and long-acting β2-adrenoceptor agonists (LABAs). In addition, biological drugs provide another therapeutic option, especially for patients with severe asthma. However, these drugs were less effective in preventing severe asthma exacerbation, and other drug options are still limited. Herein, we extracted asthma-associated single nucleotide polymorphisms (SNPs) from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) catalog and prioritized candidate genes through five functional annotations. Genes enriched in more than two categories were defined as “biological asthma risk genes.” Then, DrugBank was used to match target genes with FDA-approved medications and identify candidate drugs for asthma. We discovered 139 biological asthma risk genes and identified 64 drugs targeting 22 of these genes. Seven of them were approved for asthma, including reslizumab, mepolizumab, theophylline, dyphylline, aminophylline, oxtriphylline, and enprofylline. We also found 17 drugs with clinical or preclinical evidence in treating asthma. In addition, eleven of the 40 candidate drugs were further identified as promising asthma therapy. Noteworthy, IL6R is considered a target for asthma drug repurposing based on its high target scores. Through in silico drug repurposing approach, we identified sarilumab and satralizumab as the most promising drug for asthma treatment.

Identification of Hub Genes and Potential Biomarkers for Childhood Asthma by Utilizing an Established Bioinformatic Analysis Approach

“…A GWAS is a comprehensive analysis of all genetic variations in the form of SNPs that can be associated with certain traits. GWAS can help detect genetic biomarkers associated with common, complex diseases or phenotypes [ 20 , 31 , 32 , 33 , 34 , 35 ]. An integrated bioinformatics analysis was performed in this study based on candidate genes identified from GWAS loci, GO enrichment analyses, KEGG pathway enrichment analyses, and a constructed PPI network.…”

Genomic variants-driven drug repurposing for tuberculosis by utilizing the established bioinformatic-based approach

“…The selection criteria were adopted from those of Okada Y et al, which were later prioritized for the drug repurposing for rheumatoid arthritis [ 16 ]. These annotations have also been applied for the repurposing of drugs for several other diseases, including chronic hepatitis B [ 17 ], atopic dermatitis [ 18 ], asthma [ 19 ], and colorectal cancer [ 20 ].…”

Integration of genomic databases and bioinformatic approach to identify genomic variants for sjogren’s syndrome on multiple continents

“…Thus, African and American populations were possibly linked more to TNFAIP3 and IRF5 expressions and consequently to higher susceptibility to Sjogren's syndrome. Genomic variants are not only important for the identification of susceptibility of the disease but also it can be used to drive drug discovery (Adikusuma et al, 2021(Adikusuma et al, , 2022Irham et al, 2020Irham et al, , 2022.…”