Genetic Association Between Rheumatoid Arthritis and Preeclampsia: A Bidirectional Mendelian Randomization and Bioinformatics Study

类风湿性关节炎与先兆子痫的遗传关联:一项双向孟德尔随机化和生物信息学研究

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Abstract

OBJECTIVE: To determine whether rheumatoid arthritis (RA) contributes to the increased risk of preeclampsia (PE) and to identify potential underlying biological mechanisms. METHODS: We performed an integrated bidirectional two-sample Mendelian randomization (MR) and transcriptomic analysis to elucidate the potential relationship between RA and PE. Instrumental variables (IVs) were selected from large-scale GWAS summary datasets from openGWAS and FinnGen databases. Primary analysis used inverse-variance weighted (IVW) method, supplemented by MR-Egger and weighted median. The odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the causal effect of the exposure on the outcome. Transcriptomic profiling of disease-relevant tissues (RA synovium and PE placenta from GEO datasets) identified shared differentially expressed genes (DEGs), which were subsequently characterized through Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network reconstruction. RESULTS: The forward MR analysis revealed a significant causal effect of RA on PE risk (OR (meta) = 1.05, 95% CI (meta): 1.02-1.07, P (meta) < 0.001), while reverse analysis showed directionally inconsistent associations (OR (meta) = 0.99, 95% CI (meta): 0.84-1.17, P (meta) = 0.89). Transcriptomic analysis of diseased tissues identified 98 shared DEGs enriched in calcium signaling (GO, P < 0.001) and FoxO pathways (KEGG, P = 0.003), with protein-protein interaction networks highlighting ACTN2 and EGF as central nodes. Disease-specific DEG profiles revealed upregulated MMP13 in RA and IL5 in PE. CONCLUSION: This study confirms that RA is a significant risk factor for developing PE during pregnancy. Identifying crucial genes presents opportunities for targeted interventions. Future work should focus on validating these findings and exploring the functional implications of the identified biomarkers.

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