Identification of novel drug targets for multiple sclerosis by integrating plasma genetics and proteomes

Yi Liu , Qian Wang , Yuhui Zhao , Liu Liu , Jingxi Hu , Yao Qiao , Jinyi Chen , Chao Qin
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Abstract

Background

Genome-wide association studies (GWAS) have revealed numerous loci associated with multiple sclerosis (MS). However, the challenge lies in deciphering the mechanisms by which these loci influence the target traits. Here, we employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for MS.

Methods

We systematically integrated MS GWAS data (N = 115,803) with human plasma proteome data (N = 7213) and conducted proteome-wide association studies (PWAS) to identify MS-associated pathogenic proteins. Following this, we employed Mendelian randomization and Bayesian colocalization analyses to verify the causal relationship between these significant plasma proteins and MS. Lastly, we utilized the Drug-Gene Interaction Database (DGIdb) to identify potential drug targets for MS.

Results

The PWAS identified 25 statistically significant cis-regulated plasma proteins associated with MS at a false discovery rate of P < 0.05. Further analysis revealed that the abundance of 7 of these proteins (PLEK, TNXB, CASP3, CD59, CR1, TAPBPL, ATXN3) was causally related to the incidence of MS. Our findings indicated that genetically predicted higher levels of TNXB and CD59 were associated with a lower risk of MS, whereas higher levels of PLEK, CASP3, CR1, TAPBPL, and ATXN3 were associated with an increased risk of MS. Three plasma proteins (PLEK, CR1, CD59) were validated by colocalization analysis. Among these, CR1 was prioritized as a target for Eculizumab due to its significant association with MS risk. Additionally, PLEK, CR1, and CD59 were identified as druggable target genes.

Conclusions

Our proteomic analysis has identified PLEK, CR1, and CD59 as potential drug targets for MS treatment. Developing pharmacological inducers or inhibitors for these proteins could pave the way for new therapeutic approaches, potentially improving outcomes for MS patients.

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通过整合血浆遗传学和蛋白质组,确定治疗多发性硬化症的新型药物靶点。
背景:全基因组关联研究(GWAS)发现了许多与多发性硬化症(MS)相关的基因位点。然而,破译这些基因位点影响目标性状的机制是一项挑战。在此,我们采用了一种整合分析管道,以有效地转化遗传关联,从而识别多发性硬化症的新型蛋白质:我们将多发性硬化症的 GWAS 数据(N = 115803)与人类血浆蛋白质组数据(N = 7213)进行了系统整合,并开展了全蛋白质组关联研究(PWAS),以确定与多发性硬化症相关的致病蛋白。随后,我们采用孟德尔随机化和贝叶斯共定位分析来验证这些重要的血浆蛋白与多发性硬化症之间的因果关系。最后,我们利用药物基因相互作用数据库(DGIdb)确定了治疗多发性硬化症的潜在药物靶点:结果:PWAS 发现了 25 个与多发性硬化症相关的具有统计学意义的顺式调控血浆蛋白,误发现率为 P 结论:我们的蛋白质组分析发现了多发性硬化症的潜在药物靶点:我们的蛋白质组分析确定了PLEK、CR1和CD59是治疗多发性硬化症的潜在药物靶点。开发这些蛋白的药理诱导剂或抑制剂可为新的治疗方法铺平道路,从而改善多发性硬化症患者的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Experimental gerontology
Experimental gerontology Ageing, Biochemistry, Geriatrics and Gerontology
CiteScore
6.70
自引率
0.00%
发文量
0
审稿时长
66 days
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