Association between metabolic syndrome and low back pain: a two-sample Mendelian randomization study

Abstract

Abstract This study uses two-sample MR analysis with GWAS summary statistics to evaluate the causal relationship between metabolic syndrome and low back pain. A two-sample Mendelian randomization analysis used GWAS summary statistics for low back pain from the FinnGen database and metabolic syndrome data, including waist circumference, hypertension, fasting blood glucose, HDL cholesterol, and triglyceride levels. Various methods like inverse variance weighted, MR-Egger, weighted median, and mode assessed the causal relationship, with sensitivity analyses addressing heterogeneity and pleiotropy. Our analysis found a statistically significant causal association between essential hypertension (OR 2.38, 95% CI 1.42–3.96; Padj = 0.002), metabolic syndrome (OR 1.05, 95% CI 1.01–1.10; Padj = 0.023) and waist circumference (OR 49, 95% CI 1.32–1.68; Padj < 0.001) and low back pain (OR 1.41, 95% CI 1.30–1.53, Padj < 0.001). In contrast, fasting blood glucose (FBG), HDL cholesterol, and triglycerides showed no significant associations with low back pain across all MR methods. The results of sensitivity analyses indicated that the heterogeneity and pleiotropy were unlikely to disturb the causal estimate. Our study indicates that increased essential hypertension, metabolic syndrome and waist circumference is causally associated with a higher risk of low back pain. Interventions targeting metabolic syndrome components, particularly blood pressure control and weight management, could help reduce the risk of low back pain. Further research is needed to explore the underlying biological pathways linking these metabolic factors to low back pain.

Keywords

• Two-sample Mendelian randomization
• Metabolic syndrome
• Low back pain
• Causality
• Genetic epidemiology