Abstract
AIM: Low back pain (LBP) is one of the most common health problems worldwide. This study aimed to determine whether blood metabolites were causally linked to the risk of LBP. METHODS: Based on summary-level genome-wide association studies, we designed a Mendelian randomization (MR) study. Instrumental variables were selected for each blood metabolite with the following criteria: genome-wide significance levels of < 5e(-8) and independent clumping (r(2) < 0.001, distance < 10,000 kb). Inverse-variance weighting (IVW) was used as the primary statistical method. The weighted median (WM) method and MR-Egger regression were implemented to complement IVW. Subsequently, sensitivity analyses were conducted, including Cochran's Q test, MR-Egger intercept analysis, scatter plots, leave-one-out analysis, and funnel plots. RESULTS: IVW revealed that higher levels of lactate (odds ratio [OR] = 0.974, 95% confidence interval [CI] 0.953-0.995, P = 0.017), medium low-density lipoprotein triglycerides (OR = 0.990, 95% CI 0.983-0.997, P = 0.005) and albumin (OR = 0.985, 95% CI 0.973-0.998, P = 0.019) had a causal effect on decreased risk of LBP, whereas positive causality was detected between genetic predisposition to tyrosine and LBP (OR = 1.016, 95% CI 1.001-1.032, P = 0.043). Estimates from WM and MR-Egger were consistent with the direction of the IVW method. Additionally, there was no evidence of heterogeneity or pleiotropy in this study. CONCLUSION: This MR study demonstrated that four blood metabolites were causally related to LBP. It is possible to enhance the diagnosis of LBP, prognostic outcome predictions, and the personalization of therapy by analyzing novel signatures of metabolites.