Two-sample Mendelian randomization analysis of the association between dairy products and risk of osteoarthritis
10.3760/cma.j.cn141217-20240814-00245
- VernacularTitle:乳制品与骨关节炎风险关系的双样本孟德尔随机化分析
- Author:
Xuefeng LEI
1
;
Wenzheng ZHANG
1
;
Jiazhong JI
1
;
Long XUE
1
;
Tao YANG
1
;
Tao WEN
1
;
Tong MA
1
;
Yihui TU
1
;
Huaming XUE
1
Author Information
1. 同济大学医学院 同济大学附属杨浦医院骨关节外科，上海 200090
- Publication Type:Journal Article
- Keywords:
Osteoarthritis;
Mendelian randomization analysis;
Dairy products
- From:
Chinese Journal of Rheumatology
2025;29(8):668-673
- CountryChina
- Language:Chinese
-
Abstract:
Objective:A bidirectional Mendelian randomization approach was applied to dissect the causal association between dairy product consumption and osteoarthritis (OA), so to offering novel insights for the prevention, treatment, and prognosis assessment of knee osteoarthritis (KOA).Methods:A two-sample Mendelian randomization (MR) analysis was conducted using public available genome-wide association studies. The primary analysis was performed using the inverse variance weighted (IVW) method. To assess the stability and reliability of the results, we compared IVW and MR-Egger regression using Cochran′s Q test to evaluate SNP heterogeneity. MR-Egger regression was employed to assess pleiotropy, while a leave-one-out approach was used for sensitivity analysis. Results:Based on 207 instrumental variables (IVs), two-sample MR analysis revealed that for each standard deviation increase in genetically predicted cheese intake, the risk of OA was significantly negatively associated [ OR(95% CI)=0.98(0.98, 0.99), P<0.001], so did the risk of KOA [ OR(95% CI)=0.73(0.63, 0.85), P<0.001]. However, no significant association was found between OA risk and the intake of full-fat milk (30 IVs), semi-skimmed milk (15 IVs), skimmed milk (32 IVs), soy milk (25 IVs), or other types of milk (13 IVs), yogurt (11 IVs), or butter (3 IVs). Conclusion:The two-sample MR analysis revealed causally inverse associations between cheese intake and OA as well as KOA.
