Assessing the Genetic Causal Effects Between Blood Metabolites and Spinal Pain: A Bidirectional Two-Sample Mendelian Randomization Study

Shuang Wu,1,2,* Xing-chen Zhou,1,2,* Tao Li,1,2,* Jia-yu Sun,1,2 Long-hao Chen,1,2 Zi-cheng Wei,1,2 Kai-zheng Wang,1,2 Shuang-wei Hong,1,2 Hui-nan Xu,1,2 Zhi-zhen Lv,1,2 Li-jiang Lv1,2 1The Third Affiliated Hospital of Zhejiang, Chinese Medical University (Zhongshan Hospital of Zhejiang Province), Hangzhou, Zhejiang, People’s Republic of China; 2The Third School of Clinical Medicine (School of Rehabilitation Medicine), Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhi-zhen Lv; Li-jiang Lv, The Third School of Clinical Medicine (School of Rehabilitation Medicine), Zhejiang Chinese Medical University, No. 548, Binwen Road, Hangzhou, 310053, People’s Republic of China, Tel +86-13750821128; +86-13958107858, Email lvzhizhen1992@163.com; lvlijiang0288@163.comBackground: Previous metabolomics studies have indicated a close association between blood metabolites and pain. However, the causal relationship between blood metabolites and spinal pain (SP) remains unclear. This study employs a bidirectional two-sample Mendelian randomization (MR) analysis to evaluate the causal relationship between 452 blood metabolites and SP.Methods: We used bidirectional two-sample MR analysis to assess the causal relationship between blood metabolites and SP, including neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). Genome-wide association studies (GWAS) data for 452 metabolites (7,824 participants) were used as exposure variables. Summary data for NP were obtained from the UK Biobank, for TSP from the FinnGen Biobank, and for LBP from both the UK Biobank and the FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. Inverse-variance weighting (IVW) was used to estimate the causal relationships between metabolites and SP, complemented by various sensitivity analyses to account for pleiotropy and heterogeneity, ensuring robust results.Results: The IVW analysis identified 155 metabolites associated with SP risk and 142 metabolites influenced by SP. No significant heterogeneity or horizontal pleiotropy was observed through other analytical methods.Conclusion: This study demonstrates potential causal effects between blood metabolites and SP, providing new insights into the pathogenesis of SP. These findings lay a theoretical foundation for preventing and treating SP through targeted interventions on specific blood metabolites, potentially elucidating underlying biological mechanisms.Keywords: spinal pain, neck pain, thoracic spine pain, low back pain, back pain, blood metabolites, Mendelian randomization, causality