He Lijuan, Yu Tingting, Zhang Wei, Wang Baojian, Ma Yufeng, Li Sen
DongFang Hospital, Beijing University of Chinese Medicine, Beijing, China.
School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Front Endocrinol (Lausanne). 2022 Jun 14;13:902142. doi: 10.3389/fendo.2022.902142. eCollection 2022.
Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT.
Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.
Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (=2.0×10), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.
The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.
跟腱病(AT)与严重疼痛相关,是功能障碍和残疾的原因,会导致社会和经济效益显著降低。已提出几种潜在风险因素与跟腱病的发生有关;然而,观察性流行病学研究的结果仍存在争议,可能是因为这些研究的设计存在残余混杂和反向因果关系。孟德尔随机化(MR)可以使用基因变异作为工具变量来推断暴露与疾病结局之间的因果关系,确定跟腱病的因果风险因素有助于早期干预。因此,我们采用孟德尔随机化策略来评估先前报道的风险因素(人体测量参数、生活方式因素、血液生物标志物和全身性疾病)与跟腱病风险之间的因果关联。
进行单变量孟德尔随机化以筛选假定风险因素与跟腱病之间的潜在因果关联。双向孟德尔随机化用于推断反向因果关系。进行多变量孟德尔随机化以研究其他肥胖相关特征(如腰臀比)对跟腱病的独立于体重指数(BMI)的因果效应。
采用逆方差加权法的单变量孟德尔随机化分析表明,基因预测的BMI与跟腱病风险显著相关(=2.0×10),BMI每增加1个标准差,比值比(95%置信区间)为1.44(1.14 - 1.81)。对于其他测试的风险因素,使用任何孟德尔随机化方法均未发现与跟腱病存在因果关系。双向孟德尔随机化表明跟腱病与BMI无因果关联,多变量孟德尔随机化表明在调整BMI后,本研究中纳入的其他人体测量参数不太可能与跟腱病风险存在因果关联。
BMI与跟腱病风险之间的因果关联表明,控制体重是预防跟腱病和减轻相应疾病负担的一种有前景的策略。