The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran's Q statistic (MR-IVW) and Rucker's Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The "leave-one-out" analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = -0.546, p = 0.025), pantothenate (correlation coefficient = -0.565, p = 0.038), caprylate (correlation coefficient = -0.333, p = 0.037), pelargonate (correlation coefficient = -0.339, p = 0.047), X-11317 (correlation coefficient = -0.350, p = 0.038), X-12510 (correlation coefficient = -0.399, p = 0.034), and X-13859 (Correlation coefficient = -0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.
Keywords: blood; genetic; joints; metabolite; spine.