Yu-Ching Chou1, San-Lin You2, Chyi-Huey Bai3, Yu-Chan Liao1, Cheng-Yu Wei4, Chien-An Sun5. 1. School of Public Health, National Defense Medical Center, Taipei City, Taiwan, Republic of China. 2. Department of Medicine, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China; Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China. 3. School of Public Health, College of Public Health and Nutrition, Taipei Medical University, Taiepi City, Taiwan, Republic of China. 4. Department of Exercise and Health Promotion, College of Education, Chinese Culture University, New Taipei City, Taiwan, Republic of China. 5. Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China; Department of Public Health, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan, Republic of China. Electronic address: 040866@mail.fju.edu.tw.
Abstract
BACKGROUND/ PURPOSE: There is conflicting data regarding the utility of measuring apolipoproteins in addition to traditional lipid measures in risk assessment of cardiometabolic diseases. The aim of this study was to determine whether apolipoprotein measurements can improve the ability to predict the future development of type 2 diabetes beyond what is possible based on traditional type 2 diabetes risk factors and clinical routine lipid measurements. METHODS: A total of 4,223 Chinese adults without diabetes were followed for a mean duration of 5.42 years. The hazard ratios (HRs) with 95% confidence intervals (CIs) derived from the Cox proportional hazards model were used to analyze the longitudinal associations of apolipoprotein B (apo B), apolipoprotein A-I (apo A-I), and the apo B/apo A-I ratio with the risk of type 2 diabetes. Further, the analysis of the area under receiver operating characteristics curves (AUC) was performed to test the predictive value of apolipoprotein measurements. RESULTS: After adjusting for potential confounders, the HRs of diabetes consistently showed an increasing trend across both the apo B and the apo B/apo A-I ratio quartiles (p for trend = 0.004). In analyses of AUC, the predictive ability for type 2 diabetes risk for the apo B and the apo B/apo A-I ratio was superior to that of routine lipid and lipoprotein measurements. CONCLUSION: Apolipoprotein measurements significantly predict diabetes risk in an Asian population. Furthermore, the predictive ability of apo B alone to detect diabetes was comparable with that of the apo B/apo A-I ratio and better than the routine lipid measurements.
BACKGROUND/ PURPOSE: There is conflicting data regarding the utility of measuring apolipoproteins in addition to traditional lipid measures in risk assessment of cardiometabolic diseases. The aim of this study was to determine whether apolipoprotein measurements can improve the ability to predict the future development of type 2 diabetes beyond what is possible based on traditional type 2 diabetes risk factors and clinical routine lipid measurements. METHODS: A total of 4,223 Chinese adults without diabetes were followed for a mean duration of 5.42 years. The hazard ratios (HRs) with 95% confidence intervals (CIs) derived from the Cox proportional hazards model were used to analyze the longitudinal associations of apolipoprotein B (apo B), apolipoprotein A-I (apo A-I), and the apo B/apo A-I ratio with the risk of type 2 diabetes. Further, the analysis of the area under receiver operating characteristics curves (AUC) was performed to test the predictive value of apolipoprotein measurements. RESULTS: After adjusting for potential confounders, the HRs of diabetes consistently showed an increasing trend across both the apo B and the apo B/apo A-I ratio quartiles (p for trend = 0.004). In analyses of AUC, the predictive ability for type 2 diabetes risk for the apo B and the apo B/apo A-I ratio was superior to that of routine lipid and lipoprotein measurements. CONCLUSION: Apolipoprotein measurements significantly predict diabetes risk in an Asian population. Furthermore, the predictive ability of apo B alone to detect diabetes was comparable with that of the apo B/apo A-I ratio and better than the routine lipid measurements.
Authors: Devegowda Namitha; Aliya Nusrath; N Asha Rani; Shilpashree Y Dhananjaya; Tejaswi H Lokanathan; B N Kruthi; A G Vijay Kumar Journal: Cureus Date: 2022-03-22
Authors: Sara Sokooti; Jose L Flores-Guerrero; Hiddo J L Heerspink; Margery A Connelly; Stephan J L Bakker; Robin P F Dullaart Journal: Cardiovasc Diabetol Date: 2021-07-28 Impact factor: 9.951