Tracking the progression to type 2 diabetes with a proportional-derivative insulin secretion model. (February 2017)

• Record Type: Journal Article
• Authors: Othman, Nor Azlan; Docherty, Paul D.; Damanhuri, Nor Salwa; Chase, J. Geoffrey
• Is Part Of: Control engineering practice. Volume 59(2017)
• Page Start: 165
• Page End: 172
• Publication Date: 2017-02
• Subjects: Insulin secretion -- Type2 diabetes -- Proportional-derivative -- Normal glucose tolerance -- Impaired fasting glucose; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2016.10.012
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Background: Modelling insulin secretion as a function of peripheral C-peptide levels by mathematical deconvolution is widespread. However, the measurement resolution for successful deconvolution and high cost of C-peptide assays means measurement of insulin secretion can only be undertaken in small scale research endeavours. This research models the nature of insulin secretion ( U N ) during the pathogenesis of type 2 diabetes. Methods: A proportional-derivative U N model is based on the physiological, closed-loop insulin secretion response to increasing glucose ( ϕ D ) and glucose excursions ( ϕ P ). A total of 204 dynamic insulin sensitivity and secretion test (DISST) data sets from 68 participants in a 10-week dietary intervention trial were used to determine ϕ D and ϕ P values. The resulting gain values are used to classify subjects and thus the evaluation of U N over increasing insulin resistance. Results: Participants with impaired fasting glucose ( G 0 >5.56 mmol L -1 ) had a lower median ϕ D value that becomes almost equal to ϕ P . In contrast, NGT participants ( G 0 <5.56 mmol L -1 ), ϕ D that tended to be much greater than ϕ P . Thus, as the metabolic state of a participant moves from NGT to pre-diabetes, the participant is loses first phase insulin burst secretion. The resulting gains are classified by easily measured basal glucose. Conclusions: The simplicity of this PD U N model in a DISST model framework provides clear relationship between the U N profile and the readily available metabolic state of each participant. These relationships could significantly improve the cost and resolution of model-based tests like the DISST. Highlights: A proportional-derivative model of insulin responses to glucose is presented. The model was evaluated on 204 low dose dynamic insulin sensitivity tests. Those with IFG had a trend towards a more proportional responses. Those with NGT had a trend towards a more derivative responses. This conforms to observations of insulin secretion during pathogenesis of T2DM.