Causal relationship between cathepsins and rheumatoid arthritis: a bidirectional Mendelian randomization study

doi:10.3877/cma.j.issn.1674-0785.2025.09.008

Abstract

Abstract:

Objective

To investigate the causal relationship between cathepsins and rheumatoid arthritis (RA) using a two-sample Mendelian randomization (MR) approach.

Methods

Genome-wide association study (GWAS) data were used, with cathepsins as exposures and RA as the outcome variable. Inverse variance weighting (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode methods were applied to explore the causal relationship between exposures and the outcome, with IVW serving as the primary analytical method. Sensitivity analyses were performed to verify the reliability of the results. Additionally, a reverse MR analysis was conducted with RA as the exposure and cathepsins as the outcome variables.

Results

According to the IVW statistics, cathepsin B was positively causally associated with the risk of RA (odds ratio [OR]=1.044, 95% confidence interval [CI]=1.005~1.084, P=0.026); cathepsin F was inversely causally associated with the risk of RA (OR=1.068, 95%CI=1.020~1.118, P=0.005). The robustness of the results was confirmed by sensitivity analyses.

Conclusion

Individuals with genetically predicted higher cathepsin B levels may have an increased risk of RA, while the occurrence of RA may induce elevated cathepsin F levels.

Key words: Cathepsin, Rheumatoid arthritis, Mendelian randomization, Single nucleotide polymorphism

Biao Yang, Xinsuo Wei, Yachun Zhang, Yao Wang. Causal relationship between cathepsins and rheumatoid arthritis: a bidirectional Mendelian randomization study[J]. Chinese Journal of Clinicians(Electronic Edition), 2025, 19(09): 689-695.

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Figures/Tables 5

References 16

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暴露因素	结局因素	SNP数量	统计方法	OR值	95%CI	P值
组织蛋白酶B	类风湿关节炎节	20	逆方差加权法	1.044	1.005~1.084	0.026
			MR-Egger回归法	1.002	0.916~1.096	0.966
			加权中位数法	1.022	0.968~1.079	0.422
			简单模型法	1.060	0.966~1.164	0.231
			加权模式法	1.024	0.966~1.086	0.436
组织蛋白酶E		9	逆方差加权法	1.008	0.964~1.055	0.716
			MR-Egger回归法	1.015	0.941~1.093	0.715
			加权中位数法	1.009	0.950~1.071	0.777
			简单模型法	1.007	0.916~1.106	0.892
			加权模式法	1.005	0.929~1.087	0.910
组织蛋白酶F		12	逆方差加权法	1.004	0.962~1.048	0.851
			MR-Egger回归法	0.945	0.856~1.044	0.292
			加权中位数法	1.001	0.941~1.065	0.982
			简单模型法	0.951	0.849~1.065	0.400
			加权模式法	0.946	0.845~1.058	0.351
组织蛋白酶G		12	逆方差加权法	0.999	0.952~1.049	0.973
			MR-Egger回归法	0.944	0.851~1.049	0.309
			加权中位数法	0.986	0.921~1.055	0.683
			简单模型法	0.972	0.872~1.083	0.612
			加权模式法	0.980	0.917~1.049	0.575
组织蛋白酶H		11	逆方差加权法	1.021	0.989~1.053	0.208
			MR-Egger回归法	1.034	0.990~1.081	0.169
			加权中位数法	1.022	0.992~1.053	0.157
			简单模型法	1.030	0.932~1.138	0.575
			加权模式法	1.025	0.995~1.057	0.138
组织蛋白酶O		12	逆方差加权法	1.006	0.949~1.067	0.834
			MR-Egger回归法	0.936	0.819~1.070	0.358
			加权中位数法	0.991	0.920~1.067	0.811
			简单模型法	0.997	0.886~1.121	0.956
			加权模式法	0.989	0.884~1.105	0.847
组织蛋白酶S		23	逆方差加权法	1.028	0.994~1.063	0.106
			MR-Egger回归法	1.058	0.999~1.120	0.067
			加权中位数法	1.047	0.997~1.100	0.065
			简单模型法	1.010	0.920~1.108	0.838
			加权模式法	1.048	0.997~1.102	0.076
组织蛋白酶L2		12	逆方差加权法	1.052	0.971~1.141	0.217
			MR-Egger回归法	1.001	0.805~1.256	0.994
			加权中位数法	1.044	0.951~1.146	0.364
			简单模型法	1.001	0.838~1.196	0.990
			加权模式法	0.928	0.778~1.108	0.428
组织蛋白酶Z		13	逆方差加权法	1.013	0.967~1.063	0.579
			MR-Egger回归法	0.997	0.923~1.078	0.949
			加权中位数法	1.008	0.955~1.064	0.782
			简单模型法	0.995	0.897~1.103	0.923
			加权模式法	1.017	0.963~1.073	0.563

暴露因素	结局因素	SNP数量	统计方法	OR值	95%CI	P值
组织蛋白酶B	类风湿关节炎节	20	逆方差加权法	1.044	1.005~1.084	0.026
			MR-Egger回归法	1.002	0.916~1.096	0.966
			加权中位数法	1.022	0.968~1.079	0.422
			简单模型法	1.060	0.966~1.164	0.231
			加权模式法	1.024	0.966~1.086	0.436
组织蛋白酶E		9	逆方差加权法	1.008	0.964~1.055	0.716
			MR-Egger回归法	1.015	0.941~1.093	0.715
			加权中位数法	1.009	0.950~1.071	0.777
			简单模型法	1.007	0.916~1.106	0.892
			加权模式法	1.005	0.929~1.087	0.910
组织蛋白酶F		12	逆方差加权法	1.004	0.962~1.048	0.851
			MR-Egger回归法	0.945	0.856~1.044	0.292
			加权中位数法	1.001	0.941~1.065	0.982
			简单模型法	0.951	0.849~1.065	0.400
			加权模式法	0.946	0.845~1.058	0.351
组织蛋白酶G		12	逆方差加权法	0.999	0.952~1.049	0.973
			MR-Egger回归法	0.944	0.851~1.049	0.309
			加权中位数法	0.986	0.921~1.055	0.683
			简单模型法	0.972	0.872~1.083	0.612
			加权模式法	0.980	0.917~1.049	0.575
组织蛋白酶H		11	逆方差加权法	1.021	0.989~1.053	0.208
			MR-Egger回归法	1.034	0.990~1.081	0.169
			加权中位数法	1.022	0.992~1.053	0.157
			简单模型法	1.030	0.932~1.138	0.575
			加权模式法	1.025	0.995~1.057	0.138
组织蛋白酶O		12	逆方差加权法	1.006	0.949~1.067	0.834
			MR-Egger回归法	0.936	0.819~1.070	0.358
			加权中位数法	0.991	0.920~1.067	0.811
			简单模型法	0.997	0.886~1.121	0.956
			加权模式法	0.989	0.884~1.105	0.847
组织蛋白酶S		23	逆方差加权法	1.028	0.994~1.063	0.106
			MR-Egger回归法	1.058	0.999~1.120	0.067
			加权中位数法	1.047	0.997~1.100	0.065
			简单模型法	1.010	0.920~1.108	0.838
			加权模式法	1.048	0.997~1.102	0.076
组织蛋白酶L2		12	逆方差加权法	1.052	0.971~1.141	0.217
			MR-Egger回归法	1.001	0.805~1.256	0.994
			加权中位数法	1.044	0.951~1.146	0.364
			简单模型法	1.001	0.838~1.196	0.990
			加权模式法	0.928	0.778~1.108	0.428
组织蛋白酶Z		13	逆方差加权法	1.013	0.967~1.063	0.579
			MR-Egger回归法	0.997	0.923~1.078	0.949
			加权中位数法	1.008	0.955~1.064	0.782
			简单模型法	0.995	0.897~1.103	0.923
			加权模式法	1.017	0.963~1.073	0.563

暴露因素	结局因素	多效性		异质性
暴露因素	结局因素	P_MR-Egger	P_MR-PRESSO	P_Cochran's_Q
组织蛋白酶B	类风湿关节炎	0.334	0.589	0.570
组织蛋白酶E		0.846	0.901	0.909
组织蛋白酶F		0.216	0.398	0.464
组织蛋白酶G		0.261	0.718	0.676
组织蛋白酶H		0.410	0.359	0.163
组织蛋白酶O		0.269	0.258	0.269
组织蛋白酶S		0.239	0.696	0.746
组织蛋白酶L2		0.638	0.017	0.039
组织蛋白酶Z		0.613	0.113	0.086

暴露因素	结局因素	多效性		异质性
暴露因素	结局因素	P_MR-Egger	P_MR-PRESSO	P_Cochran's_Q
组织蛋白酶B	类风湿关节炎	0.334	0.589	0.570
组织蛋白酶E		0.846	0.901	0.909
组织蛋白酶F		0.216	0.398	0.464
组织蛋白酶G		0.261	0.718	0.676
组织蛋白酶H		0.410	0.359	0.163
组织蛋白酶O		0.269	0.258	0.269
组织蛋白酶S		0.239	0.696	0.746
组织蛋白酶L2		0.638	0.017	0.039
组织蛋白酶Z		0.613	0.113	0.086

暴露因素	结局因素	SNP数量	统计方法	OR值	95%CI	P值
类风湿关节炎	组织蛋白酶B	212	逆方差加权法	0.982	0.934~1.032	0.472
			MR-Egger回归法	1.005	0.934~1.093	0.909
			加权中位数法	0.954	0.878~1.039	0.280
			简单模型法	0.958	0.774~1.185	0.691
			加权模式法	0.979	0.906~1.059	0.600
	组织蛋白酶E	212	逆方差加权法	0.968	0.920~1.020	0.222
			MR-Egger回归法	0.957	0.877~1.044	0.322
			加权中位数法	0.908	0.838~0.985	0.019
			简单模型法	1.061	0.849~1.326	0.601
			加权模式法	0.947	0.863~1.040	0.257
	组织蛋白酶F	212	逆方差加权法	1.068	1.020~1.118	0.005
			MR-Egger回归法	1.126	1.042~1.217	0.003
			加权中位数法	1.090	0.993~1.196	0.070
			简单模型法	1.012	0.833~1.226	0.918
			加权模式法	1.095	1.010~1.186	0.029
	组织蛋白酶G	212	逆方差加权法	0.996	0.951~1.043	0.858
			MR-Egger回归法	0.981	0.908~1.061	0.638
			加权中位数法	0.992	0.907~1.085	0.862
			简单模型法	0.890	0.734~1.078	0.235
			加权模式法	0.996	0.922~1.076	0.919
	组织蛋白酶H	212	逆方差加权法	0.983	0.935~1.033	0.495
			MR-Egger回归法	1.009	0.928~1.097	0.835
			加权中位数法	1.007	0.918~1.105	0.876
			简单模型法	1.105	0.880~1.386	0.392
			加权模式法	1.013	0.928~1.106	0.775
	组织蛋白酶O	212	逆方差加权法	1.001	0.955~1051	0.955
			MR-Egger回归法	1.044	0.964~1.132	0.292
			加权中位数法	1.021	0.925~1.127	0.678
			简单模型法	0.869	0.707~1.068	0.184
			加权模式法	1.003	0.917~1.097	0.946
	组织蛋白酶S	212	逆方差加权法	0.989	0.944~1.036	0.640
			MR-Egger回归法	1.001	0.926~1.082	0.979
			加权中位数法	1.048	0.969~1.134	0.241
			简单模型法	1.033	0.834~1.278	0.768
			加权模式法	1.071	0.972~1.181	0.166
	组织蛋白酶L2	212	逆方差加权法	1.011	0.964~1.061	0.641
			MR-Egger回归法	1.048	0.967~1.136	0.252
			加权中位数法	1.068	0.977~1.169	0.149
			简单模型法	1.006	0.823~1.230	0.952
			加权模式法	1.072	0.991~1.159	0.086
	组织蛋白酶Z	212	逆方差加权法	0.977	0.928~1.028	0.361
			MR-Egger回归法	0.995	0.913~1.084	0.903
			加权中位数法	0.974	0.885~1.072	0.591
			简单模型法	0.922	0.741~1.148	0.469
			加权模式法	0.966	0.887~1.051	0.421

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