Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis

被引:3
作者
Fu, Kai [1 ,2 ]
Si, Shucheng [3 ]
Jin, Xinzhong [4 ]
Zhang, Yan [5 ]
Duong, Vicky [2 ,4 ]
Cai, Qianying [1 ,6 ]
Li, Guangyi [1 ]
Oo, Win Min [2 ,7 ]
Zheng, Xianyou [1 ]
Boer, Cindy G. [8 ]
Zhang, Yuqing [9 ,10 ]
Wei, Xiaojuan [1 ,6 ]
Zhang, Changqing [1 ]
Gao, Youshui [1 ]
Hunter, David J. [2 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Orthoped Surg, Shanghai Peoples Hosp 6, Sch Med, Shanghai, Peoples R China
[2] Univ Sydney, Kolling Inst, Sydney Musculoskeletal Hlth, Sydney, Australia
[3] Peking Univ Third Hosp, Res Ctr Clin Epidemiol, Beijing, Peoples R China
[4] Univ New South Wales, Ctr Big Data Res Hlth, Sydney, Australia
[5] Southern Med Univ, Zhujiang Hosp, Clin Res Ctr, Guangzhou, Guangdong, Peoples R China
[6] Shanghai Jiao Tong Univ, Shanghai Peoples Hosp 6, Shanghai Inst Microsurg Extrem, Sch Med, Shanghai, Peoples R China
[7] Univ Med Mandalay, Mandalay Gen Hosp, Dept Phys Med & Rehabil, Mandalay, Myanmar
[8] Erasmus MC, Med Ctr, Dept Internal Med, Rotterdam, Netherlands
[9] Harvard Med Sch, Massachusetts Gen Hosp, Dept Med, Div Rheumatol Allergy & Immunol, Boston, MA USA
[10] Harvard Med Sch, Massachusetts Gen Hosp, Mongan Inst, Boston, MA USA
来源
EBIOMEDICINE | 2024年 / 107卷
基金
中国博士后科学基金; 北京市自然科学基金;
关键词
Osteoarthritis; Drug targets; Antidiabetic drugs; Gene expression; Mendelian randomization; MENDELIAN RANDOMIZATION; POTASSIUM CHANNELS; ANALYSES IDENTIFY; GENETIC-VARIANTS; LOCI; CHONDROCYTES; INSIGHT; EQTL;
D O I
10.1016/j.ebiom.2024.105285
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly. Methods We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised. Findings Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 x 10(-4)), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 x 10(-4)), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 x 10(-4)), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 x 10(-4)) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype. Interpretation Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs.
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页数:14
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