Investigating the shared genetic structure between rheumatoid arthritis and stroke

Abstract

Abstract Background Rheumatoid arthritis (RA) increases the risk of stroke. However, the relationship between RA and stroke remains unclear. This study aimed to explore the shared genetics architecture (i.e., common genetic basis between different traits, diseases, or phenotypes) of RA and stroke, aiming to improve the intervention and management of patients with RA and stroke. Methods Pooled statistics from publicly available genome-wide association studies for RA (8,255 cases and 409,001 controls) and stroke (43,132 cases and 43,132 controls) were used. A genome-wide positive association was conducted to (examine the comprehensive effects of genetic variants on a particular trait, disease, or phenotype at the genome-wide scale). Local genetic correlation studies used linkage disequilibrium score regression and super genetic covariance analyzer. Single nucleotide polymorphisms (SNPs) at risk were identified using genome-wide association study multiple trait analysis and PLINK software (P snp <5e-08), followed by functional localization and annotation using Functional Mapping and Annotation of Genome-Wide Association Studies to identify specific genes and genetic variants that may contribute to the disease. Finally, a transcriptome-wide association study explored the relationship between genes and their association with RA risk. Results A genome-wide significant positive correlation was evident between RA and stroke (genetic correlation = 0.3756). Among the localized genomic regions, the correlation between RA and stroke in the region of chr2:201572564–202,829,668 was the most significant (p = 0.0015). We identified 179 significant SNPs and five common risk genes for RA and stroke (IRF5, RNASET2, ZNF438, UBE2LS, and SYNGR1). These genes are involved in the immune-inflammatory pathway. Conclusions The findings suggest a shared genetic structure between RA and stroke. These findings may provide new insights into RA and stroke pathogenesis, and contribute to the development of new diagnostic markers and therapeutic targeted drugs to improve the clinical outcomes of patients with RA and stroke.

Keywords

• Rheumatoid arthritis
• Stroke
• Genome-wide association studies
• Shared genetic structure
• Multi-trait association analysis