Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Mataram, Mataram, Indonesia.
Front Immunol. 2021 Oct 13;12:724277. doi: 10.3389/fimmu.2021.724277. eCollection 2021.
Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.
特应性皮炎（AD）是一种慢性复发性皮肤病。治疗 AD 的药物仍然有限，大多数是局部皮质类固醇乳膏或抗生素。本研究试图通过整合基因网络和基因组分析方法来发现潜在的 AD 治疗方法。在此，从 GWAS 目录中提取与 AD 相关的单核苷酸多态性（SNP）。我们确定了 70 个与 AD 相关的基因座，然后根据 HaploReg v4.1，基于 >0.8 的亚洲人群，将这些基因座扩展到近端 SNP，发现了 94 个 AD 风险基因。接下来，我们使用基于生物信息学分析的管道，根据六个功能注释对 AD 风险基因进行优先级排序，以识别生物学 AD 风险基因。最后，我们根据 STRING 数据库中的分子相互作用将它们扩展，以找到药物靶基因。我们的分析显示了 27 个生物学 AD 风险基因，它们映射到 76 个药物靶基因。根据 DrugBank 和 Therapeutic Target Database，确定了 25 个与 53 种药物重叠的药物靶基因。重要的是，在这种生物信息学分析中成功地识别了批准用于 AD 的 dupilumab。此外，还发现了 10 种具有临床或临床前证据的潜在用于 AD 的药物。特别是，我们鉴定了靶向基因 JAK1 的 filgotinib 和 fedratinib 作为 AD 的潜在药物。此外，还成功鉴定了四种单克隆抗体药物（lebrikizumab、tralokinumab、tocilizumab 和 canakinumab）作为 AD 重新定位的有希望的药物。总之，结果表明基因网络和基因组信息作为潜在药物发现资源具有可行性。
