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Micheletto, Francesco (2013) A model of beta-cell response to GLP-1 to quantify incretin effect in healthy and prediabetic subjects. [Tesi di dottorato]

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Abstract (inglese)

Glucose regulation, in healthy subjects, relies on a complex control system that keeps blood glucose level within a narrow range around its basal value. Impairment of the glucose regulatory system is the cause of several metabolic derangements, including diabetes, which is characterized by chronic hyperglycemia which leads to severe micro and macro-vascular complications. Diabetes is generally classified into two categories, type 1 and type 2 diabetes. Both arise from complex interactions between genes and the environment, and are characterized by an absolute deficiency of insulin production (type 1) or a relative deficiency of the pancreas to produce insulin in amounts sufficient to meet the body needs (type 2). The prevalence of diabetes is increasing dramatically in populations of the world, and its global incidence has been increasing steadily in the past several years. Traditional medications for type 2 diabetes, including insulin, sulfonylureas, glitinides, acarbose, metformin, and thiazolidinediones, lower blood glucose through diverse mechanisms of action. However, many of the oral hypoglycemic agents lose their efficacy over time, resulting in progressive deterioration in β-cell function and loss of glycemic control due to progressive loss of β-cell mass. Consequently, there is an increasing interest in developing therapeutic agents that preserve or restore functional β-cells mass such as the incretin hormone Glucagon-Like Peptide-1 (GLP-1). It not only acutely lowers blood glucose by promoting insulin secretion and inhibiting glucagon release, but also engages signaling pathways in the islet β-cells that leads to stimulation of β-cells proliferation and neo-genesis and inhibition of β-cell apoptosis.
Impairment of insulin secretion and glucagon suppression suggests that decreased β-cells responsiveness to GLP-1 is part of the pathogenesis of type 2 diabetes. Thus the ability to measure the effect of GLP-1 on insulin secretion can be useful to understand the pathogenesis of type 2 diabetes. Moreover it can be employed to optimized GLP-1 based therapy by determining those individuals who may benefit more from such therapy. However, a mechanistic model enabling direct quantitation of pancreatic response to GLP-1 has never been developed.
In this contribution a mathematical model which describes the mechanism of GLP-1 action on insulin secretion is proposed. It provides a direct measure of the β-cells responsivity indexes to glucose and GLP-1. Three databases were used to develop, test and validate the model.
Data of 88 healthy individuals, who underwent a hyperglycemic clamp with a concomitant GLP-1 intravenous infusion, were used for model formulation. A set of models of increasing complexity describing GLP-1 action on insulin secretion were tested. All models share the common assumption that insulin secretion is made up of two components, one proportional to glucose rate of change through dynamic responsivity, Φd, and one proportional to glucose through static responsivity, Φs, but differ in the modality of GLP-1 control on β-cells. For each model potentiation index П was derived representing the percent increase in secretion due to 1 pmol/l of circulating GLP-1. All the models fit the data well, as confirmed by the run test, which supported randomness of residuals in 70% of the subjects and provide precise estimate of model parameters. Model selection was tackled using standard criteria (e.g. ability to describe the data, precision of parameter estimates, model parsimony, residual independence). The most parsimonious model in most subjects assumes that above-basal insulin secretion depends linearly on GLP-1 concentration and its rate of change.
However, the hyperglycemic clamp with concomitant intravenous infusion of GLP-1, is not physiological and easy to perfume in large scale studies. Thus data of 22 impairing fasting glucose (IFG) subjects, studied twice with a mixed meal, were used to test the model performance in a more physiological condition. We found that during an oral test, a simpler model is sufficient to describe the data.
Validation of the model was performed using both simulations and real data of 10 healthy subjects studied with an OGTT and matched intravenous glucose challenge (I-IVG). The protocol allows to calculate a model-independent index (PI) from the comparison of insulin secretion rate estimated in these two occasions. The comparison between model-derived Π and incretin potentiation index PI shows that they are very similar (П = 6.55, CV = 65%; PI = 6.15 % per pmol/l). In addition in silico validation proved the ability of the model to single out the effect of GLP-1 on insulin secretion since it correctly estimated П in the 93 ± 1% of the simulations.

Abstract (italiano)

La regolazione della glicemia in soggetti sani, si basa su un complesso sistema di controllo che permette di mantenere il livello di glucosio nel sangue all’interno di un range ristretto che oscilla attorno al suo valore basale. Il mal funzionamento di tale sistema è la causa di patologie metaboliche, ad esempio il diabete. Questa patologia è caratterizzata da iperglicemia cronica che, se non curata, a lungo termine comporta gravi complicanze micro e marco vascolari. Il diabete è comunemente classificato in tipo 1 e tipo 2. Entrambi derivano da complesse interazioni tra ambente e geni, e sono caratterizzati da una totale mancanza di produzione di insulina, nel tipo 1, o da una carenza da parte del pancreas nel produrre insulina in quantità sufficiente per soddisfare le necessità dell’organismo, nel tipo 2. La prevalenza del diabete è in costante aumento in tutto il mondo, così come la sua incidenza è in costante crescita negli ultimi anni. I farmaci tradizionali per la terapia del diabete di tipo 2, come l’insulina, sulfaniluree, metformina e tiazolidinedioni, riducono la glicemia attraverso diversi meccanismi di azione. Tuttavia, molti degli agenti ipoglicemizzanti assunti per via orale, perdono di efficacia con il tempo causando un progressivo deterioramento della funzionalità e riduzione della massa delle β-cellule con conseguente riduzione del controllo glicemico. Di conseguenza vi è un crescente interesse nello sviluppo di nuovi agenti terapeutici che preservino la massa e ripristino la funzionalità delle β-cellule. Uno di questi è l’ormone Glucagon-Like Peptide-1 (GLP-1), che non solo riduce la glicemia aumentando la secrezione di insulina, ma agisce anche nel signaling nelle isole di Langherans stimolando la proliferazione e la neo-genesi delle β-cellule e inibendone l’apoptosi. La ridotta secrezione di insulina e la mancata soppressione del glucagone inducono ad ipotizzare che la diminuita risposata delle β-cellule al GLP-1 possa essere parte della patogenesi del diabete di tipo 2. Pertanto la capacità di misurare l’effetto del GLP-1 sulla secrezione dell’insulina è utile per studiare la patogenesi della malattia ed ottimizzare valutare l’efficacia delle terapie basate sul GLP-1. Infatti è cruciale determinare quali soggetti possono beneficiare maggiormente di tale terapia per ottimizzare le risorse. Tuttavia, non è ancora disponibile un modello che descriva l’azione del GLP-1 sulla secrezione di insulina e permetta di quantificarne l’entità.
In questo lavoro viene proposto un modello matematico che descrive i meccanismi di azione del GLP-1 sulla secrezione di insulina, fornendo una misura diretta dell’aumento della secrezione dell’insulina dovuto all’effetto del GLP-1. Sono stati utilizzati tre database per sviluppare, testare e validare i modelli proposti.
I dati di 88 soggetti sani sottoposti ad un clamp iperglicemico con contemporanea infusione intravenosa di GLP-1, sono stati utilizzati per lo sviluppo del modello. Sono stati testati una serie di modelli dell’azione del GLP-1 sulla secrezione di insulina di complessità crescente. Tutti i modelli si basano sulla comune assunzione che la secrezione di insulina è costituita da due componenti, una proporzionale alla concentrazione ed una alla velocità di variazione del glucosio plasmatico, modulate rispettivamente dalla responsività statica Φs e dalla responsività dinamica Φd. Ogni modello differisce dagli altri nella descrizione della modalità di azione del GLP-1. Per ciascun modello è stato derivato un indice di potenziamento, П, che rappresenta l’aumento percentuale della secrezione di insulina dovuta ad 1 pmol/l di GLP-1. I modelli predicono bene i dati (infatti il run test conferma la casualità dei residui nel 70% dei soggetti) e forniscono stime precise dei parametri . La selezione del modello ottimo è stata affrontata confrontando le prestazioni dei modelli sulla base di criteri standard (capacità di descrivere i dati, la precisione della stima dei parametri, la parsimonia, la casualità dei residui).
Il modello più parsimonioso ipotizza che la secrezione sopra basale di insulina dipenda linearmente sia dalla concentrazione di GLP-1 sia dalla sua variazione.
Tuttavia le condizioni sperimentali di tale protocollo non sono fisiologiche e applicabili su larga scala. Pertanto, i dati di 22 soggetti IFG (Impaired Fasting Glucose), studiati due volte con un pasto misto, sono stati utilizzati per testare il modello in una condizione sperimentale più vicina alla fisiologia. I risultati dimostrano che per descrivere i dati di un test orale, è sufficiente un modello più semplice.
La validazione del modello è stata effettuata sia in simulazione sia utilizzando i dati reali di 10 soggetti, studiati due volte: una prima volta utilizzando un test orale di tolleranza al glucosio (OGTT) e successivamente un test intravenoso di tolleranza al glucosio durante il quale il glucosio è stato infuso in modo tale da riprodurre la glicemia osservata durante l’OGTT. Questo protocollo permette di calcolare un indice di potenziamento (PI) modello-indipendente dal confronto tra la secrezione di insulina stimata nelle due occasioni. Il confronto tra il potenziamento stimato con il modello, П, e l’indice di potenziamento PI mostra che i due indici sono molto simili (П = 6.55, CV = 65%; PI = 6.15 % per pmol/l). Inoltre nel 93 ± 1% delle simulazioni effettuate il modello è in grado di quantificare correttamente l’effetto del GLP-1 sulla secrezione di insulina.

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Tipo di EPrint:Tesi di dottorato
Relatore:Dalla Man, Chiara
Dottorato (corsi e scuole):Ciclo 25 > Scuole 25 > INGEGNERIA DELL'INFORMAZIONE > BIOINGEGNERIA
Data di deposito della tesi:29 Gennaio 2013
Anno di Pubblicazione:29 Gennaio 2013
Parole chiave (italiano / inglese):GLP-1, secrezione di insulina, modello, beta-cellule, effetto incretina / GLP-1, insulin secretion, modeling, beta-cells, incretin effect.
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 Bioingegneria elettronica e informatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:5657
Depositato il:15 Ott 2013 15:49
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