Unraveling the Molecular Nexus Between Ankylosing Spondylitis and IgA Nephropathy: Insights from Mendelian Randomization and Bioinformatics Analysis.

Introduction: Renal complications are frequently observed in patients with ankylosing spondylitis (AS), with IgA nephropathy (IgAN) being a particularly significant concern. Although anecdotal evidence suggests a potential association between AS and IgAN, robust epidemiological data remain limited. Previous studies have reported varying prevalence rates of IgAN among AS patients, but these studies are often constrained by small sample sizes and inconsistent methodologies. Establishing a causal relationship between AS and IgAN through conventional observational studies has proven challenging due to confounding factors and reverse causality. Mendelian randomization (MR) offers a promising alternative, utilizing genetic variants to explore causal relationships. This study employs MR combined with bioinformatics analysis to investigate the molecular link between AS and IgAN, aiming to identify potential therapeutic targets.

Methods: Two publicly available datasets were utilized: a genome-wide association study (GWAS) of AS (dataset ID: ebi-a-GCST005529) with 9,069 AS cases and 13,578 controls, and IgAN data from the FinnGen project, which included 653 cases and 411,528 controls. Instrumental variables were selected based on stringent criteria. MR analysis was conducted using the inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods to assess the causal relationship between AS and IgAN. Reverse MR analysis and sensitivity analysis were conducted to validate the findings. Bioinformatics analysis involved acquiring gene expression data from the GEO database and identifying differentially expressed genes (DEGs) using the Limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, and hub gene identification were performed to elucidate the biological functions involved.

Results: 24 independent single nucleotide polymorphisms (SNPs) associated with AS were identified through stringent SNP selection. MR analysis revealed a protective causal relationship between AS and IgAN [odds ratio (OR) =0.552, 95% confidence interval (CI), 0.339-0.900; P = 0.017]. Analysis of DEGs identified 332 DEGs for IgAN and 5,521 DEGs for AS, with 59 common DEGs shared between the two diseases. Functional enrichment analysis highlighted significant changes in biological processes, cellular components, molecular functions, and KEGG pathways. PPI network analysis identified eight hub genes, including CX3CR1, which links AS and IgAN. External validation confirmed CX3CR1 as a crucial gene associated with both diseases.

Conclusion: This study provides evidence of a protective causal relationship between AS and IgAN using MR analysis. Furthermore, bioinformatics analysis identifies CX3CR1 as a key gene, suggesting its role in mediating the protective link between AS and IgAN. These findings provide valuable insights into the molecular mechanisms underlying the connection between the two diseases and propose CX3CR1 as a potential therapeutic target for IgAN.