Hong Yanggang, Ye Jiani, Hua Chunyan
The Second School of Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Rheumatology (Oxford). 2026 Feb 4;65(2). doi: 10.1093/rheumatology/keaf606.
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 [genes with expression quantitative trait loci (eQTLs)] and therapeutic targets.
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.
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 >80%), including BLK (B lymphoid tyrosine kinase), RNF145 (Ring Finger Protein 145), FAM167A (Family with Sequence Similarity 167 Member A) and VRK3 (Vaccinia-Related Kinase 3). PheWAS analyses 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.
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.
系统性红斑狼疮（SLE）是一种具有复杂遗传结构和免疫细胞参与的多因素自身免疫性疾病。虽然全基因组关联研究（GWAS）已经确定了众多风险位点，但大多数是非编码的，这使得确定因果效应基因[具有表达数量性状位点（eQTL）的基因]和治疗靶点具有挑战性。
我们将来自14种人类免疫细胞类型的单细胞表达数量性状位点（sc-eQTL）数据与孟德尔随机化（MR）和贝叶斯共定位分析相结合，以确定与SLE有因果关系的效应基因。我们应用全表型组关联研究（PheWAS）来评估候选效应基因的潜在脱靶效应，并使用药物银行来确定针对这些效应基因的现有药物。
MR分析确定了62个在不同免疫细胞类型中对SLE有显著因果效应的效应基因。共定位分析确定了8个效应基因，有强有力的证据表明它们与SLE存在共同的遗传调控（PP.H4>80%），包括BLK（B淋巴细胞酪氨酸激酶）、RNF145（指环蛋白145）、FAM167A（序列相似性家族167成员A）和VRK3（痘苗相关激酶3）。PheWAS分析显示，大多数候选效应基因与非免疫性状的显著关联较少，表明不良反应风险较低。值得注意的是，BLK是 fostamatinib 和 zanubrutinib 的已知靶点，尽管其表达增加具有保护作用，但这突出了在SLE中抑制该靶点的潜在风险。
本研究证明了整合sc-eQTL、MR和共定位分析以确定SLE中免疫细胞特异性因果效应基因的实用性。这些发现为疾病机制提供了新的见解，并突出了有前景的、低风险的治疗靶点，以用于精准药物开发。
