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揭示自身免疫性疾病的因果途径:一种多组学方法。

Unveiling causal pathways in autoimmune diseases: a multi-omics approach.

作者信息

Sha Hao, Zhu Weifeng

机构信息

School of Basic Medical Sciences, Jiangxi Medical College, Nanchang University, Nangchang, China.

出版信息

Autoimmunity. 2025 Dec;58(1):2480594. doi: 10.1080/08916934.2025.2480594. Epub 2025 Mar 26.

Abstract

Autoimmune diseases (ADs), such as Graves' disease (GD), Hashimoto's thyroiditis (HT), psoriasis, systemic lupus erythematosus (SLE), and type 1 diabetes (T1D), involve complex immune and inflammatory responses. This study employed Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data to examine the causal relationships among 91 circulating inflammatory proteins, 41 cytokines, 211 gut microbiota, and 731 immune cell traits in relation to ADs. Additionally, we integrated mediation and bioinformatics analyses, including protein-protein interaction (PPI) networks, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subnetwork discovery and key protein identification were performed using the Molecular Complex Detection (MCODE) plugin, alongside colocalization analysis and drug target exploration to identify potential mechanisms. MR analysis identified significant causal relationships between various circulating inflammatory proteins, cytokines, gut microbiota species, immune cells, and ADs, with certain relationships retaining significance after false discovery rate (FDR) correction. Mediation analysis demonstrated that inflammatory proteins mediate pathogenic pathways linking immune cells to psoriasis and gut microbiota to Hashimoto's thyroiditis. PPI and bioinformatics analyses highlighted 22 key proteins involved in ADs, while subnetwork analysis identified 15 central proteins. Fms-related tyrosine kinase 3 ligand (FLT3LG) exhibited strong colocalization evidence. Molecular docking confirmed several proteins as viable drug targets. This comprehensive multi-omics study advances our understanding of ADs, identifies novel therapeutic targets, and offers valuable insights for developing new treatment strategies.

摘要

自身免疫性疾病(ADs),如格雷夫斯病(GD)、桥本甲状腺炎(HT)、银屑病、系统性红斑狼疮(SLE)和1型糖尿病(T1D),涉及复杂的免疫和炎症反应。本研究利用全基因组关联研究(GWAS)数据进行孟德尔随机化(MR)分析,以检验91种循环炎症蛋白、41种细胞因子、211种肠道微生物群和731种免疫细胞特征与自身免疫性疾病之间的因果关系。此外,我们整合了中介和生物信息学分析,包括蛋白质-蛋白质相互作用(PPI)网络、基因本体(GO)富集和京都基因与基因组百科全书(KEGG)通路分析。使用分子复合物检测(MCODE)插件进行子网发现和关键蛋白鉴定,同时进行共定位分析和药物靶点探索以确定潜在机制。MR分析确定了各种循环炎症蛋白、细胞因子、肠道微生物群物种、免疫细胞与自身免疫性疾病之间的显著因果关系,在错误发现率(FDR)校正后,某些关系仍具有显著性。中介分析表明,炎症蛋白介导了将免疫细胞与银屑病以及肠道微生物群与桥本甲状腺炎联系起来的致病途径。PPI和生物信息学分析突出了22种参与自身免疫性疾病的关键蛋白,而子网分析确定了15种核心蛋白。Fms相关酪氨酸激酶3配体(FLT3LG)表现出强有力的共定位证据。分子对接证实了几种蛋白是可行的药物靶点。这项全面的多组学研究增进了我们对自身免疫性疾病的理解,确定了新的治疗靶点,并为开发新的治疗策略提供了有价值的见解。

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