Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.

Autor: Coales EM; School of Food Science and Nutrition, University of Leeds, Leeds, United Kingdom., Ajjan RA; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom., Pearson SM; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom., O'Mahoney LL; Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, United Kingdom., Kietsiriroje N; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom., Brož J; Department of Internal Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic., Holmes M; School of Food Science and Nutrition, University of Leeds, Leeds, United Kingdom., Campbell MD; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom; School of Nursing and Health Sciences, University of Sunderland, Sunderland, United Kingdom. Electronic address: matthew.campbell@sunderland.ac.uk.
Jazyk: angličtina
Zdroj: Canadian journal of diabetes [Can J Diabetes] 2022 Apr; Vol. 46 (3), pp. 225-232.e2. Date of Electronic Publication: 2021 Sep 06.
DOI: 10.1016/j.jcjd.2021.09.002
Abstrakt: Objectives: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombotic profiles in type 1 diabetes (T1D). We applied an unsupervised machine-learning approach to determine whether interindividual differences in rapid-acting insulin levels associate with parameters of vascular health in patients with T1D.
Methods: We re-analyzed baseline pretreatment meal-tolerance test data from 2 randomized controlled trials in which 32 patients consumed a mixed-macronutrient meal and self-administered a single dose of rapid-acting insulin individualized by carbohydrate counting. Postprandial serum insulin, tumour necrosis factor (TNF)-alpha, plasma fibrinogen, human tissue factor (HTF) activity and plasminogen activator inhibitor-1 (PAI-1) were measured. Two-step clustering categorized individuals based on shared clinical characteristics. For analyses, insulin pharmacokinetic summary statistics were normalized, allowing standardized intraindividual comparisons.
Results: Despite standardization of insulin dose, individuals exhibited marked interpersonal variability in peak insulin concentrations (48.63%), time to peak (64.95%) and insulin incremental area under the curve (60.34%). Two clusters were computed: cluster 1 (n=14), representing increased serum insulin concentrations; and cluster 2 (n=18), representing reduced serum insulin concentrations (cluster 1: 389.50±177.10 pmol/L/IU h -1 ; cluster 2: 164.29±41.91 pmol/L/IU h -1 ; p<0.001). Cluster 2 was characterized by increased levels of fibrinogen, PAI-1, TNF-alpha and HTF activity; higher glycated hemoglobin; increased body mass index; lower estimated glucose disposal rate (increased insulin resistance); older age; and longer diabetes duration (p<0.05 for all analyses).
Conclusions: Reduced serum insulin concentrations are associated with insulin resistance and a prothrombotic milieu in individuals with T1D, and therefore may be a marker of adverse vascular outcome.
(Copyright © 2021 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: