Research Paper Volume 12, Issue 11 pp 10715—10735
Subgroup analysis of proinsulin and insulin levels reveals novel correlations to metabolic indicators of type 2 diabetes
- 1 Department of Health Care Centre, Hainan General Hospital, Haikou 570311, Hainan, China
- 2 Department of Endocrinology, Hainan General Hospital, Haikou 570311, Hainan, China
- 3 Department of Endocrinology Laboratory, Hainan General Hospital, Haikou 570311, Hainan, China
Received: December 11, 2019 Accepted: April 27, 2020 Published: June 12, 2020https://doi.org/10.18632/aging.103289
How to Cite
Copyright © 2020 Li et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Proinsulin, insulin and proinsulin/insulin (P/I) ratio have been reported to be correlated with fasting plasma glucose (FPG) and Hemoglobin A1c (HbA1c) in whole population study therefore sensitive predictors of T2D progression. However, by analyzing data collected from 2018-2019 from a cohort of 1579 East Asian individuals from Hainan Province of China, we find that the associations of proinsulin, insulin and P/I ratio with diabetic indicators have distinct, sometimes opposite regression patterns in normal, prediabetic and diabetic subgroups. The strength of the associations are generally weak in normal and prediabetic groups, and only moderate in diabetic group between postprandial proinsulin and HbA1c, between postprandial insulin and FPG or HbA1c, and between postprandial P/I ratio and FPG or HbA1c. Receiver operating characteristic (ROC) curve analysis shows these parameters are weaker than age in predicting diabetes development, with P/I ratio being the weakest. Proinsulin and insulin levels are tightly associated with insulin sensitivity across all subgroups, as measured by Matsuda index. Together, our results suggest that proinsulin, insulin or P/I ratio are weak predictors of diabetes development in the whole population, urging the need for stratifying strategies and novel perspectives in evaluating and predicting hyperglycemia progression.