Effects of circulating inflammatory proteins on spinal degenerative diseases: Evidence from genetic correlations and Mendelian randomization study

循环炎症蛋白对脊柱退行性疾病的影响:来自遗传相关性和孟德尔随机化研究的证据

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Abstract

BACKGROUND: Numerous investigations have suggested links between circulating inflammatory proteins (CIPs) and spinal degenerative diseases (SDDs), but causality has not been proven. This study used Mendelian randomization (MR) to investigate the causal associations between 91 CIPs and cervical spondylosis (CS), prolapsed disc/slipped disc (PD/SD), spinal canal stenosis (SCS), and spondylolisthesis/spondylolysis. METHODS: Genetic variants data for CIPs and SDDs were obtained from the genome-wide association studies (GWAS) database. We used inverse variance weighted (IVW) as the primary method, analyzing the validity and robustness of the results through pleiotropy and heterogeneity tests and performing reverse MR analysis to test for reverse causality. RESULTS: The IVW results with Bonferroni correction indicated that beta-nerve growth factor (β-NGF), C-X-C motif chemokine 6 (CXCL6), and interleukin-6 (IL-6) can increase the risk of CS. Fibroblast growth factor 19 (FGF19), sulfotransferase 1A1 (SULT1A1), and tumor necrosis factor-beta (TNF-β) can increase PD/SD risk, whereas urokinase-type plasminogen activator (u-PA) can decrease the risk of PD/SD. FGF19 and TNF can increase SCS risk. STAM binding protein (STAMBP) and T-cell surface glycoprotein CD6 isoform (CD6 isoform) can increase the risk of spondylolisthesis/spondylolysis, whereas monocyte chemoattractant protein 2 (MCP2) and latency-associated peptide transforming growth factor beta 1 (LAP-TGF-β1) can decrease spondylolisthesis/spondylolysis risk. CONCLUSIONS: MR analysis indicated the causal associations between multiple genetically predicted CIPs and the risk of four SDDs (CS, PD/SD, SCS, and spondylolisthesis/spondylolysis). This study provides reliable genetic evidence for in-depth exploration of the involvement of CIPs in the pathogenic mechanism of SDDs and provides novel potential targets for SDDs.

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