Orthopaedic journal of sports medicine · 2025
Causal Relationships Between 4 Exposure Factors and Rotator Cuff Syndrome Using Mendelian Randomization Analysis.
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Zhang Zeyang, Han Shun, Sun Xiaowei, Guo Zelin, Wang Zhiqiang, Sha Peng, Liu Yuchen, Zhang Bing, Liu Yupeng
Аннотация
BACKGROUND: Although previous studies have investigated the risk factors for rotator cuff syndrome (RCS), there remains controversy due to uncontrolled and uncertain confounding factors in their analyses.
PURPOSE: To perform Mendelian randomization (MR) analysis using single-nucleotide polymorphisms to investigate the causal relationship between RCS and 4 risk factors: type 2 diabetes mellitus (T2DM), high blood pressure (HBP), body mass index (BMI), and low high-density lipoprotein cholesterol (HDL-C).
STUDY DESIGN: Descriptive epidemiology study.
METHODS: Genome-wide association study (GWAS) data for T2DM (ebi-a-GCST006867), BMI (ieu-b-40), HBP (finn-b-I9_HYPTENS), HDL-C (ieu-b-109), and RCS (ukb-b-50) were obtained from the IEU Open GWAS Project. The dataset of each risk factor was combined with the dataset of RCS, generating 4 datasets. Potential confounders and single-nucleotide polymorphisms related to RCS were excluded from these datasets. The causal relationships between the exposure factors and RCS were analyzed using 5 regression models: MR-Egger, weighted median estimate (WME), inverse-variance weighting (IVW), simple mode, and weighted mode. Heterogeneity in the causal effects was assessed using MR-Egger regression and IVW analyses. Sensitivity analyses were performed to determine the stability of the results.
RESULTS: The MR-Egger regression intercepts for T2DM, BMI, HBP, and HDL-C showed no horizontal pleiotropic effects. The results of the Cochran Q test showed P values of .075 and .080 for BMI in the MR-Egger regression and IVW models, respectively, indicating the absence of heterogeneity between BMI and RCS. The results of the weighted median estimate and IVW regression analyses showed a significant causal association between BMI and RCS, with odds ratios of 1.002 (95% CI, 1-1.004; P = .038) and 1.003 (95% CI, 1.001-1.005; P = .0003), respectively. No significant associations were found for T2DM, HDL-C, or HBP.
CONCLUSION: In the present study, BMI was positively associated with the risk of developing RCS, while T2DM, HBP, and low HDL-C were not associated with RCS development.
PURPOSE: To perform Mendelian randomization (MR) analysis using single-nucleotide polymorphisms to investigate the causal relationship between RCS and 4 risk factors: type 2 diabetes mellitus (T2DM), high blood pressure (HBP), body mass index (BMI), and low high-density lipoprotein cholesterol (HDL-C).
STUDY DESIGN: Descriptive epidemiology study.
METHODS: Genome-wide association study (GWAS) data for T2DM (ebi-a-GCST006867), BMI (ieu-b-40), HBP (finn-b-I9_HYPTENS), HDL-C (ieu-b-109), and RCS (ukb-b-50) were obtained from the IEU Open GWAS Project. The dataset of each risk factor was combined with the dataset of RCS, generating 4 datasets. Potential confounders and single-nucleotide polymorphisms related to RCS were excluded from these datasets. The causal relationships between the exposure factors and RCS were analyzed using 5 regression models: MR-Egger, weighted median estimate (WME), inverse-variance weighting (IVW), simple mode, and weighted mode. Heterogeneity in the causal effects was assessed using MR-Egger regression and IVW analyses. Sensitivity analyses were performed to determine the stability of the results.
RESULTS: The MR-Egger regression intercepts for T2DM, BMI, HBP, and HDL-C showed no horizontal pleiotropic effects. The results of the Cochran Q test showed P values of .075 and .080 for BMI in the MR-Egger regression and IVW models, respectively, indicating the absence of heterogeneity between BMI and RCS. The results of the weighted median estimate and IVW regression analyses showed a significant causal association between BMI and RCS, with odds ratios of 1.002 (95% CI, 1-1.004; P = .038) and 1.003 (95% CI, 1.001-1.005; P = .0003), respectively. No significant associations were found for T2DM, HDL-C, or HBP.
CONCLUSION: In the present study, BMI was positively associated with the risk of developing RCS, while T2DM, HBP, and low HDL-C were not associated with RCS development.