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.
Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.
E. Coales,R. Ajjan,S. Pearson,L. O’Mahoney,N. Kietsiriroje,J. Brož,M. Holmes,M. Campbell
Published 2021 in Canadian Journal of Diabetes
ABSTRACT
PUBLICATION RECORD
- Publication year
2021
- Venue
Canadian Journal of Diabetes
- Publication date
2021-09-01
- Fields of study
Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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