Serum alanine transaminase levels predict type 2 diabetes risk among a middle-aged and elderly Chinese population

• Published in: Annals of hepatology Vol. 18; no. 2; pp. 298 - 303
• Main Authors: Li, Yaru, Wang, Jing, Han, Xu, Hu, Hua, Wang, Fei, Yu, Caizheng, Yuan, Jing, Yao, Ping, Li, Xiulou, Yang, Kun, Miao, Xiaoping, Wei, Sheng, Wang, Youjie, Chen, Weihong, Liang, Yuan, Zhang, Xiaomin, Guo, Huan, Yang, Handong, Wu, Tangchun, He, Meian
• Format: Journal Article
• Language: English
• Published: Mexico Elsevier 01.03.2019
• Subjects: Age Factors; Aged; Alanine aminotransferase; Alanine Transaminase - blood; Biomarkers - blood; China - epidemiology; Diabetes Mellitus, Type 2 - blood; Diabetes Mellitus, Type 2 - diagnosis; Diabetes Mellitus, Type 2 - epidemiology; Female; Gastroenterology and Hepatology; Humans; Incidence; Male; Middle Aged; Prediction model; Prognosis; Prospective Studies; Risk Assessment; Risk Factors; Time Factors; Type 2 diabetes; Up-Regulation; China; Type 2 diabetes; Alanine aminotransferase; Prediction model
• ISSN: 1665-2681
• DOI: 10.1016/j.aohep.2017.02.001

AbstractIntroduction and aimIt is indicated that high levels of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are associated with increased incident type 2 diabetes risk. However, whether serum ALT levels could improve the discrimination of type 2 diabetes remains unclear. MethodsThe data was derived from the Dongfeng-Tongji cohort study, which was established in 2008 and followed until October 2013. A total of 17,173 participants free of type 2 diabetes at baseline were included and 1159 participants developed diabetes after 4.51 (0.61) years of follow-up. Cox proportional hazard regression model was used to calculate the hazard ratios (HRs) for the association between ALT and AST levels with incident diabetes risk. Receiver-operating characteristic (ROC) curves analysis was used to evaluate the predictive accuracy of models incorporating traditional risk factors with and without ALT. ResultsCompared with the lowest quartile of ALT and AST levels, the highest quartile had a significantly higher risk of developing type 2 diabetes (HR: 2.17 [95% CI: 1.78–2.65] and 1.29 [1.08–1.54], respectively) after adjustment for potential confounders. The addition of ALT levels into the traditional risk factors did not improve the predictive ability of type 2 diabetes, with AUC increase from 0.772 to 0.774; P= 0.86. ConclusionsAlthough elevated ALT or AST levels increased incident type 2diabetes risk, addition of ALT levels into the prediction model did not improve the discrimination of type 2 diabetes.