孟德尔随机化
全基因组关联研究
疾病
共域化
遗传关联
免疫系统
医学
生物
免疫学
红斑狼疮
基因分型
系统性红斑狼疮
数量性状位点
生物信息学
等位基因
候选基因
计算生物学
药物数据库
表达数量性状基因座
自身免疫性疾病
TLR7型
生物标志物
遗传建筑学
精密医学
遗传学
人类白细胞抗原
微阵列分析技术
临床试验
T细胞
一致性
因果关系(物理学)
表型
作者
Yanggang Hong,Jiani Ye,Chun-Yan Hua
标识
DOI:10.1093/rheumatology/keaf606
摘要
Abstract Objective Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease with complex genetic architecture and immune cell involvement. While genome-wide association studies (GWAS) have identified numerous risk loci, most are non-coding, making it challenging to pinpoint causal eGenes and therapeutic targets. Methods We integrated single-cell expression quantitative trait loci (sc-eQTL) data from 14 human immune cell types with Mendelian randomization (MR) and Bayesian colocalization analyses to identify eGenes causally associated with SLE. We applied phenome-wide association studies (PheWAS) to assess potential off-target effects of candidate eGenes and used DrugBank to identify existing drugs targeting these eGenes. Results MR analysis identified 62 eGenes with significant causal effects on SLE across diverse immune cell types. Colocalization analysis prioritized eight eGenes with strong evidence of shared genetic regulation with SLE (PP.H4 > 0.80), including BLK, RNF145, FAM167A, and VRK3. PheWAS analysis revealed few significant associations with non-immune traits for most candidate eGenes, suggesting low risk of adverse effects. Notably, BLK is a known target of fostamatinib and zanubrutinib, although its increased expression was protective, highlighting potential risks of inhibition in SLE. Conclusion This study demonstrates the utility of integrating sc-eQTL, MR, and colocalization analyses to identify immune-cell-specific causal eGenes in SLE. The findings offer new insights into disease mechanisms and highlight promising, low-risk therapeutic targets for precision drug development.
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