Integrative genomic network-based drug repositioning for allergic diseases

Abstract
Allergy diseases are currently not totally cured, but treatment could reduce the symptoms and progress over time in many cases. Unfortunately, drug choice is limited, posing substantial challenges for drug discovery or utilizing the old drug for a new disease called repurposing drugs. Finding a novel drug involves a lot of time, money, and effort. In addition to the high expense, the chances of a promising candidate compound becoming a US FDA-approved drug are low. Drug repositioning/repurposing is a method used to extend the effects of approved drugs or revitalize those that have failed, which will resolve these obstacles and problems. This thesis focuses on discovering potential treatments for allergy diseases based on an approach that integrates gene networks and genomics. Three diseases (atopic dermatitis (AD), asthma, and allergic contact dermatitis (ACD)) were included in the study.
In the first study, we investigated discover potential drugs repurposed for AD. Herein, the AD-associated SNPs were obtained from the GWAS catalog. We identified 70 AD risk loci, and 94 genes were found by extending the AD risk loci using HaploReg version 4.1 for Asian populations with r2 > 0.8. The scoring system was developed using six functional annotations to predict drug candidates optimally using in silico pipelines. Twenty-seven biological AD risk genes were identified and then mapped into 76 drug target genes using the STRING database. We identified 25 drug target genes that overlap 53 drugs in DrugBank and Therapeutic Target Database. Interestingly, dupilumab was successfully found in this bioinformatics analysis of the 53 drugs. Dupilumab was known as one of the drugs available used for AD. This finding confirms the feasibility and reliability of gene-based drug repurposing. Furthermore, ten drugs were identified with clinical or preclinical evidence that could be useful in AD. Specifically, we identified filgotinib and fedratinib with target JAK1 inhibitors that might be repurposed to AD because JAK1 is an essential potential target for AD.
In the second study, we conducted drug repositioning for asthma. This study used the GWAS and PheWAS databases to obtain asthma risk SNPs that could yield information that might help guide to drug repurposing process. We used five biological criteria to prioritize asthma-associated genes and develop biological risk candidates for drug repositioning. Our research identified 139 biological asthma risk genes and 64 drugs that target 22 of these genes. Noteworthy, reslizumab, mepolizumab, theophylline, dyphylline, aminophylline, oxtriphylline, and enprofylline are seven of 64 drugs successfully identified in this bioinformatic analysis as clinical use for asthma. In addition, we observed in a ClinicalTrial.gov and an intensive PubMed literature review 17 drugs in a clinical trial and preclinical study potentially useful for asthma. Additionally, 11 out of 40 candidate drugs were potential candidates to treat asthma. Notably, IL6R would be an ideal target for repurposing asthma drugs due to its high target scores. We found sarilumab and satralizumab to be the most potential candidate drugs for asthma using in silico drug repurposing.
In the third study, we conducted our data mining analysis for drug targets of ACD by integrating the differentially expressed genes (DEGs). We identified 370 DEGs, including 281 upregulated and 79 down-regulated genes. A GO and KEGG pathway were analyzed to determine the biological functions of genes and pathways involved in ACD. Then, using protein-protein interaction analysis, we clustered these genes and discovered 10 Hub genes that are deemed significant in our model. Additionally, we used the drug-gene interaction database to conduct a drug-gene interaction analysis of module genes. We discovered 14 drugs that might be used to prevent and cure ACD. Noteworthy, among 14 drugs, two drugs are currently under clinical trials and three are off-label used for ACD. In addition, four anticancer drugs were identified as promising ACD therapy. However, due to the high risk of side effects, anticancer drugs were not considered for ACD drug repurposing in our study. Through a transcriptomic-driven drug discovery approach, we identified five drugs (risperidone, diclofenac, loratadine, collagenase clostridium histolyticum, and ocriplasmin) as the most promising drug to be repositioned in ACD therapy.
Overall, this study has provided the most promising candidate drugs that have not been reported as anti-allergic and offer a valuable drug repurposing approach to provide empirical evidence for drug discovery of allergic diseases.
Keywords: Atopic dermatitis, asthma, allergic contact dermatitis, bioinformatics, drug repurposing, functional annotations, genomic, transcriptomic.