关键词: 静息态脑网络, 自身免疫性疾病, 孟德尔随机化, 功能连接, 结构连接

Abstract: BACKGROUND: Recent studies have shown a potential association between resting-state brain networks and autoimmune diseases. However, the underlying neuro-regulatory mechanisms remain unclear.
OBJECTIVE: To explore the potential causal relationship between resting-state brain network functional/structural connectivity and autoimmune diseases using bidirectional two-sample Mendelian randomization.
METHODS: The resting-state brain network genome-wide association study (GWAS) data from the UK Biobank database (a large biomedical database jointly constructed by the UK government, the Scottish government, and the Wellcome Trust), as well as GWAS data on autoimmune diseases integrated from the IEU Open GWAS database (a genome-wide association study database developed by the MRC Integrated Epidemiology Unit (IEU) at the University of Bristol in the UK), GWAS Catalog database (a genome wide association study database under the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI)), and FinnGen database (a large public-private partnership project initiated in Finland) were used to screen independent genetic variants significantly associated with exposure factors as instrumental variables. Bidirectional Mendelian randomization was conducted for seven resting-state brain networks (functional/structural connectivity) and nine autoimmune diseases (rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, type 1 diabetes, Sjogren's syndrome, myasthenia gravis, ulcerative colitis, inflammatory bowel disease, and celiac disease). The inverse variance weighted method served as the primary analysis method to assess potential bidirectional causal relationships, supplemented by MR-Egger, weighted median, simple mode and weighted mode methods for complementary analysis. Multiple testing correction was performed using the false discovery rate (FDR) with q < 0.05. Cochran’s Q test was used to evaluate heterogeneity, Mendelian randomization Pleiotropy RESidual Sum and Outlier method was used to evaluate horizontal pleiotropy, leave-one-out method was used to test robustness of results, and cross-database consistency test was used to verify statistical significance of autoimmune disease data from different sources, ensuring reliability of research findings.
RESULTS AND CONCLUSION: In forward Mendelian randomization analyses involving nine autoimmune diseases, increased functional connectivity in the default mode network was positively associated with a higher risk of rheumatoid arthritis [odds ratio (OR)=1.431, 95% confidence interval (CI)=1.108–1.850, P=0.006, q=0.048). Reduced functional connectivity in the dorsal attention network may correlate with decreased rheumatoid arthritis risk (OR=0.797, 95%CI=0.677–0.938, P=0.006, q=0.048). Decreased structural connectivity in the visual network was linked to reduced inflammatory bowel disease risk (OR=0.957, 95%CI=0.932–0.982, P < 0.001, q=0.014), while weakened structural connectivity in the ventral attention network was similarly correlated with diminished inflammatory bowel disease risk (OR=0.724, 95%CI=0.575–0.911, P=0.005, q=0.04). Reverse Mendelian randomization analyses revealed no significant causal effects of autoimmune diseases on resting-state brain network connectivity strength (q > 0.05). This Mendelian randomization study provides the first evidence of a bidirectional causal relationship between resting-state brain network connectivity abnormalities and autoimmune disease pathogenesis, thereby elucidating the pivotal role of brain network dysregulation in autoimmune pathology. These findings provide a theoretical basis for the development of neuroimaging biomarkers and neuroimmune targeted therapy strategies for autoimmune diseases.

Key words: resting-state brain networks, autoimmune diseases, Mendelian randomization, functional connectivity, structural connectivity