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Assessing beta cell function in adolescents from discrete C-peptide data
RamÃrez, Daniel Garrish, Justin Short, Kevin Diniz Behn, Cecilia
RamÃrez, Daniel
Garrish, Justin
Short, Kevin
Diniz Behn, Cecilia
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2025-04
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During adolescence there is an increase in insulin secretion in response to a pubertally-mediated reduction in insulin sensitivity. Although insulin secretion rate (ISR) cannot be measured directly, reliable inference of ISR has enabled the use of ISR-based metrics of pancreatic beta cell function. We recently developed a Bayesian hierarchical model (BHM) that incorporates physiological constraints to precisely infer continuous ISR profiles from discrete C-peptide data. By considering the logarithm of ISR as a Gaussian process, we construct physiologically meaningful, nonnegative ISR profiles with credible envelopes. Here, we apply this method to infer ISR profiles with uncertainty in an adolescent cohort. Plotting the predicted C-peptide profile obtained from the inferred ISR function against the true C-peptide measurements demonstrates the goodness of the fit. We assess beta cell function with ISR-based metrics including the area under the ISR curve, the maximum secretion rate, and the time to peak secretion. These measures allow for sensitive assessment of beta-cell function in teens with normal and impaired glucose tolerances.
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