Table_6_Drug Repurposing for Atopic Dermatitis by Integration of Gene Networking and Genomic Information.xlsx

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 r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico 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（Atopic Dermatitis, AD）是一种慢性复发性皮肤疾病。目前用于治疗AD的药物仍较为有限，多数为外用糖皮质激素乳膏或抗生素类药物。本研究尝试通过整合基因网络与基因组分析方法，挖掘潜在的AD治疗靶点与药物。研究从全基因组关联分析（Genome-Wide Association Study, GWAS）目录中提取与AD相关的单核苷酸多态性（Single Nucleotide Polymorphism, SNPs），共鉴定得到70个AD相关基因座；随后利用HaploReg v4.1工具，基于亚洲人群中r²>0.8的连锁不平衡阈值，将关联范围延伸至近端SNPs，最终筛选得到94个AD风险基因。接下来，本研究基于6项功能注释，通过生物信息学分析的计算机模拟（in silico）流程对AD风险基因进行优先级排序，以鉴定真正的生物学AD风险基因；最终借助STRING数据库，通过分子相互作用网络对上述基因进行拓展，进而筛选潜在药物靶点基因。分析结果显示，本研究共鉴定得到27个生物学AD风险基因，这些基因可映射至76个药物靶点基因。结合DrugBank数据库与治疗靶点数据库（Therapeutic Target Database），最终筛选得到25个药物靶点基因，对应53种药物。值得注意的是，已获批用于AD治疗的度普利尤单抗（dupilumab），成功被本研究的生物信息学分析识别。此外，本研究还发现10种具备临床或临床前证据的潜在AD治疗药物；其中，靶向JAK1基因的filgotinub与fedratinib被鉴定为潜在AD治疗药物。同时，四种单克隆抗体药物——莱柏利珠单抗（lebrikizumab）、特拉利珠单抗（tralokinumab）、托珠单抗（tocilizumab）与卡那单抗（canakinumab）——均被成功鉴定为具有AD重定位开发潜力的药物。综上，本研究结果证实，基因网络与基因组信息可作为潜在的药物发现资源，该研究思路具备可行性。