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

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.