孟德尔随机化
医学
内科学
肥胖
逻辑回归
单变量
甲状腺功能
风险因素
甲状腺
多元统计
统计
数学
遗传变异
基因型
基因
生物化学
化学
作者
Xin Li,Huilin Li,Tao Hong,Zanlin Li,Zhi Wang
出处
期刊:Journal of Investigative Medicine
[BMJ]
日期:2024-05-24
标识
DOI:10.1177/10815589241257214
摘要
To explore the causal relationship between obesity and hypothyroidism and identify risk factors and the predictive value of subclinical hypothyroidism (SCH) in obese patients using Mendelian randomization, this study employed five Mendelian randomization methods (MR Egger, Weighted Median, Inverse Variance Weighted, Simple Mode, and Weighted Mode) to analyze clinical data from 308 obese patients at the People's Hospital of Xinjiang Uygur Autonomous Region, from January 2015 to June 2023. Patients were divided based on thyroid function tests into normal (n = 173) and SCH groups (n = 56). Comparative analyses, along with univariate and multivariate logistic regression, were conducted to identify risk factors for SCH in obese patients. A significant association between obesity and hypothyroidism was established, especially highlighted by the inverse variance weighted method. SCH patients showed higher ages, thyroid-stimulating hormone levels, and thyroid autoantibody positivity rates, with lower T4 and FT4 levels. Age, FT4, thyroid autoantibodies, TPO-Ab, and Tg-Ab were confirmed as risk factors. The predictive value of FT4 levels for SCH in obesity was significant, with an Area Under the Curve (AUC) of 0.632. The study supports a potential causal link between obesity and hypothyroidism, identifying specific risk factors for SCH in obese patients. FT4 level stands out as an independent predictive factor, suggesting its utility in early diagnosis and preventive strategies for SCH.
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