孟德尔随机化
表达数量性状基因座
全基因组关联研究
计算生物学
转录组
生物
现象
生物信息学
医学
基因
遗传学
表型
单核苷酸多态性
基因型
基因表达
遗传变异
作者
Xiaopeng Yu,Ruiqi Jiang,Ziming Li,Xiaoxue Li,Haihui Jiang,Zhigang Zhao
标识
DOI:10.3389/fimmu.2024.1428962
摘要
Background Multiple sclerosis (MS) represents a multifaceted autoimmune ailment, prompting the development and widespread utilization of numerous therapeutic interventions. However, extant medications for MS have proven inadequate in mitigating relapses and halting disease progression. Innovative drug targets for preventing multiple sclerosis are still required. The objective of this study is to discover novel therapeutic targets for MS by integrating single-cell transcriptomics and Mendelian randomization analysis. Methods The study integrated MS genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data for analysis and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and MS. Sequential analyses involving colocalization and Phenome-wide association studies (PheWAS) were conducted to validate the causal role of candidate genes. Results Following stringent quality control preprocessing of scRNA-seq data, 1,123 expression changes across seven peripheral cell types were identified. Among the seven most prevalent cell types, 97 genes exhibiting at least one eQTL were discerned. Examination of MR associations between 28 proteins with available index pQTL signals and the risk of MS outcomes was conducted. Co-localization analyses and PheWAS indicated that FCRL3 may exert influence on MS. Conclusion The integration of scRNA-seq and MR analysis facilitated the identification of potential therapeutic targets for MS. Notably, FCRL3, implicated in immune function, emerged as a significant drug target in the deCODE databases. This research underscores the importance of FCRL3 in MS therapy and advocates for further investigation and clinical trials targeting FCRL3.
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