La prévalence du diabète ne cesse d’augmenter et la détection de sujets à risque de développer cette maladie reste une préoccupation importante afin qu’un programme de prévention leur soit proposé. Le dosage de l’HbA1c est utilisé pour l’évaluation de l’efficacité du traitement pris par les diabétiques. Il n’était pas utilisé pour le diagnostic des dysglycémies car les méthodes de ce dosage n’étaient pas standardisées. Actuellement l’IFCC (International Federation of Clinical Chemistry) propose une nouvelle méthode de référence pour cette mesure, et l’OMS (Organisation Mondiale de la Santé) a intégré ce paramètre dans les critères diagnostiques du diabète. but Evaluer la capacité de l’HbA1c à prédire un diabète incident, chercher des seuils, d’HbA1c, de GAJ et de glycémie deux heures (G2H) après un test d’hyperglycémie provoquée par voie orale (HGPO), au delà desquels les sujets sont plus à risque de développer un diabète incident et, enfin, étudier l’influence du tabac sur les variations de ces mesures. Méthodes Pour l’évaluation de la prédiction du diabète et la recherche de seuils, nous avons utilisé les données de l’étude australienne AusDiab, de l’étude danoise Inter99 et de l’étude française D.E.S.I.R. avec plus de 5500, 4500 et 3550 sujets, respectivement. Dans la troisième partie, nous avons utilisé les données du projet DETECT-2 (12 études, 26 000 sujets), ainsi que celles des études françaises D.E.S.I.R. et TELECOM (3700 sujets). Les distributions de l’HbA1c dans les trois premières études étaient différentes, nous avons donc, dans les deux premières parties d’analyses, ajusté les moyennes d’HbA1c à l’inclusion et après le suivi. Nous avons utilisé un modèle logistique pour la comparaison du pouvoir prédictif de l’HbA1c et de GAJ ; l’intervalle de confiance des Odds Ratios (ORs) à été obtenu par bootstrap. Pour rechercher les seuils de prédiction du diabète, nous avons comparé le modèle logistique (avec la variable glycémique) sans seuil au modèle avec seuil. Enfin, nous avons utilisé un modèle linéaire mixte pour évaluer la différence entre les moyennes d’HbA1c, de GAJ et de G2H en fonction du tabagisme, en attribuant un effet aléatoire à la variable ‘centre’. Résultats Avant ajustement des moyennes d’HbA1c, l’incidence du diabète (défini par la prise de traitement antidiabétique, une HbA1c≥6.5% ou une GAJ≥7mmol/l) était de 3.1% dans AusDiab, 2.7% dans Inter99 et 2.5% dans D.E.S.I.R. Les sujets dépistés comme étant diabétiques par l’HbA1c et par la GAJ n’étaient pas toujours les mêmes. L’incidence estimée du diabète augmente bien avec l’augmentation du taux de l’HbA1c et de la GAJ à l’inclusion. Pour chaque critère, l’aire sous la courbe de ROC (Receiver Operating Characteristic) était supérieure à 0.80 témoignant d’une bonne discrimination des deux tests entre les diabétiques incidents et les non diabétiques et le test de Hosmer-Lemeshow témoigne d’une bonne adéquation des modèles utilisés (p>0.05). Dans les trois populations, les ORs qui mesurent l’association entre les taux d’HbA1c et de GAJ et la survenue du diabète étaient presque toujours supérieurs pour l’HbA1c. Les seuils d’HbA1c et de GAJ au-delà desquels les sujets étaient plus à risque de développer un diabète variaient en fonction de la définition du diabète incident sauf pour l’HbA1c dans l’étude D.E.S.I.R. (5.3%) et la GAJ dans l’étude AusDiab (5.5mmol/l). Enfin, la moyenne d’HbA1c chez les fumeurs actuels était 0.10%(0.08,0.12) plus élevée que chez ceux qui n’ont jamais fumé ; la moyenne de G2H était -0.44(-0.51,-0.36) moins élevée chez les fumeurs actuels que chez ceux qui n’ont jamais fumé.Conclusion Ces résultats soulignent : 1) l’importance de l’utilisation de l’HbA1c comme critère diagnostique de dysglycémies, 2) la nécessité de mieux explorer les limites inférieures des stades intermédiaires qui précèdent la survenue du diabète, 3) l’importance de prendre en considération les facteurs qui peuvent influencer les taux d’HbA1c / The increasing prevalence of diabetes worldwide makes the detection of people at risk of developing diabetes a major concern, so that they can benefit from diabetes prevention programs. HbA1c is used to evaluate the effectiveness of treatment taken by diabetic patients. HbA1c had not been used to diagnose dysglycemia because the assay methods were not standardized. The International Federation of Clinical Chemistry has proposed a reference method, and in 2011 the World Health Organization included HbA1c as one of the criteria for the diagnosis of diabetes. aims: 1) To evaluate the ability of HbA1c to predict incident diabetes compared with fasting plasma glucose (FPG); 2) to find thresholds for HbA1c, FPG and two hour plasma glucose (G2H) after an oral glucose tolerance test (OGTT) beyond which subjects are more at risk for developing incident diabetes and finally; 3) to study the influence of smoking on HbA1c, FPG and G2H.Methods: Several populations were studied. To evaluate the prediction of diabetes and the search for thresholds, we used data from the Australian study (AusDiab), a Danish study (Inter99) and a French study (D.E.S.I.R.) with respectively more then 5500, 4500 and 3550 participants. In the third part, we used data from the DETECT-2 consortium (12 studies with more than 26 000 men and women) and from two French studies: D.E.S.I.R. and TELECOM (with more than 3700 participants). The distribution of HbA1c in AusDiab, Inter99 and D.E.S.I.R. differed, so in the first two parts of this thesis, we adjusted HbA1c so that all three studies had the same mean HbA1c at baseline and the same mean HbA1c at follow-up. We used a logistic model to quantify the predictive ability of HbA1c and FPG for diabetes, and then derived confidence intervals for the difference in Odds Ratios (ORs) by bootstrap. To search for thresholds to predict incident diabetes, based on HbA1c, FPG and G2H at inclusion, we compared logistic regression models that were linear in the glycaemic variable, without a threshold, with a spline model with a threshold. Linear mixed models with ‘centre’ as a random variable, were used to assess the difference between the means of HbA1c, FPG and G2H in current-, ex- and never-smokers.Results: With unadjusted HbA1c data, the incidence of diabetes (defined by treatment, HbA1c≥6.5% or FPG≥7 mmol/l) was 3.1% in AusDiab, 2.7% in Inter99 and 2.5% in D.E.S.I.R.. Subjects detected as having diabetes by HbA1c and FPG were not always the same. The incidence of diabetes increased with increasing HbA1c and FPG at baseline. For each test, the area under the Receiver Operating Characteristic curve was greater than 0.80, indicating good discrimination for these two measures between those with and without incident diabetes, and the Hosmer-Lemeshow test indicated that the models fitted well (p>0.05). In all three populations, the ORs measuring the association between HbA1c and FPG and the development of diabetes were almost always higher for HbA1c than for FPG. The thresholds of HbA1c and FPG above which the incidence of diabetes were higher, varied according to the definition of incident diabetes - except for HbA1c in D.E.S.I.R. (always 5.3%) and for FPG in AusDiab (always 5.5mmol/l). Finally, in current-smokers, the mean HbA1c was 0.10%(0.08,0.12) higher than in never-smokers; the mean G2H was 0.44( 0.51,-0.36) lower in current-smokers than in never-smokers. Conclusion: The results that we found emphasize: 1) the importance of using HbA1c as a diagnostic criterion for dysglycemia, as those diagnosed diabetic by HbA1c did not have always an FPG ≥ 7 mmol/l, 2) the need to better explore the lower limits of the “pre-diabetic” stage as the thresholds of HbA1c, FPG and 2H-PG that we found were lower than those used in clinical practice, 3) the importance to consider factors that may influence HbA1c and G2H, such as smoking.

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Background: African-Americans are a vulnerable population group with disproportionately elevated rates of type 2 Diabetes Mellitus (DM). Resistant starch is a promising food ingredient that has the potential to reduce the risk factors involved in the development of type 2 DM. To date, there is a dearth of published research studies on the effect of resistant starch on African-Americans who are at increased risk for type 2 DM. Objective: The major objective of this study was to determine if daily consumption of approximately twelve grams of high-maize™ 260 resistant starch (RS) added to bread improved glucose homeostasis by monitoring changes in fasting plasma glucose, fructosamine, hemoglobin A1c, insulin, glucagon-like peptide-1, C-reactive protein, homeostasis model assessment insulin resistant (HOMA- IR) and beta-cell function (HOMA-Beta), serum acetate, propionate, and butyrate levels. Design: A fourteen-week, randomized, double-blind, within-subject crossover design feeding study was carried out in African-American males (n=8) and females (n=7) at increased risk for type 2 DM who resided in Southwest Virginia. All participants consumed bread containing added RS or control bread (no added RS) for six-weeks. RS and control bread feedings were separated by a two-week washout period. Results: Fasting Plasma Glucose (FPG) levels were significantly lower (P = 0.0179) after six-week control bread feedings compared to baseline. FPG levels were also significantly lower (P < 0.0001) after two-week washout period than at baseline. FPG levels were significantly higher (P < 0.0001) after six-week resistant starch bread feeding than at washout. FPG levels due to consumption of resistant starch versus control bread approached significance (P = 0.0574). Fructosamine levels were significantly lower (P = 0.0054) after control bread and resistant starch bread (P < 0.0012) consumption compared to baseline. No significant differences were found in fructosamine levels due to resistant bread intake versus control (P = 0.9692). Mean baseline HbA1c levels were 6.9% (n=15). This value was slightly lowered to 6.79% (n=14) at the end of the fourteen-week study, although statistical significance was not found. Mean ± standard errors for HbA1c values were 6.9% ± 0.18% and 6.9% ± 0.14% at baseline for the sequence groups, resistant starch first (n=7) and control treatment first (n=8) groups, respectively. Mean± standard error HbA1c values were 6.7%± 0.27% and 6.9% ± 0.27% at the conclusion of fourteen-week study for sequence groups, resistant starch first group (n=7) and control treatment first group, respectively. Baseline mean and standard errors C-reactive Protein (CRP) levels for male and female combined results were 0.62 ± 0.16 mg/dL (n=15). Mean CRP levels were 0.53 ± 0.12 mg/dL for resistant starch bread and 0.64 ± 0.21 mg/dL for control bread feeding periods. No significant differences were found for treatment, gender, or sequence effects for C-reactive protein levels during the fourteen-week study (P > 0.05). Mean HOMA-IR levels following six-week resistant starch and control bread consumption decreased to normal values (> 2.5), although no significant differences were found for treatment (P = 0.5923). Conclusions: Eighty-seven grams of Hi- maize™ 260 Resistant Starch added to baked loaves of bread consumed by a free-living African-American population at increased risk for type 2 diabetes did not consistently show significance in all clinical indicators and biochemical markers assessed. On the basis of the evidence in this study we do not have evidence that this amount of resistant starch in this population's diet will prevent the onset of diabetes. However, results are suggestive that higher levels of resistant starch in a more controlled experiment could reduce clinical risk factors for type 2 diabetes. / Ph. D.