Plasma insulin and inflammatory markers prior to weight loss can predict dietary responders

Autor: Ling Chun Kong, Pierre-Henri Wuillemin, Froogh Hajduch, Jean-Philippe Bastard, Soraya Fellahi, Dominique Bonnefont-Rousselot, Randa Bittar, Arnaud Basdevant, Jean-Daniel Zucker, Joël Doré, Karine Clément, Salwa Rizkalla
Přispěvatelé: U872 team 7 Nutriomique, Institut National de la Santé et de la Recherche Médicale (INSERM), DECISION, Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), CHU Tenon [APHP], CHU Pitié-Salpêtrière [APHP], MICrobiologie de l'ALImentation au Service de la Santé (MICALIS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, ANR, CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Pitié-Salpêtrière [AP-HP], European Association for the Study of Diabetes (EASD). GBR., Nutrition et obésités: approches systémiques (UMR-S 1269) (Nutriomics), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
Jazyk: angličtina
Rok vydání: 2011
Předmět:
Zdroj: 47. Annual Meeting of the European Association for the Study of Diabetes (EASD)
47. Annual Meeting of the European Association for the Study of Diabetes (EASD), Sep 2011, Lisbonne, Portugal. ⟨10.1007/s00125-011-2276-4⟩
HAL
71st Scientific Session American Diabetes Association
71st Scientific Session American Diabetes Association, Jun 2011, San Diego, California, United States
47. Annual Meeting of the European Association for the Study of Diabetes (EASD), European Association for the Study of Diabetes (EASD). GBR., Sep 2011, Lisbonne, Portugal. ⟨10.1007/s00125-011-2276-4⟩
Popis: International audience; The ability to identify obese subjects who will lose weight in response to energy restriction is an important strategy in obesity clinical care.Fifty obese/overweight subjects were submitted to an energy restricted high protein diet for 6 weeks followed by a 6 weeks-maintenance diet. Based on their trajectories of weight loss during the study, three subjects clusters were identified. Cluster A (n=17) and Cluster B (n=15) lost more weight during the diet period, however during the stabilization phase cluster A continued to loose weight, whereas cluster B remained stable. Cluster C (n=17) lost less and rapidly regained weight during the stabilization. At baseline, subjects in cluster C had the highest plasma insulin (P=0.01), IL-6 (P=0.05) and adipose tissue inflammatory marker (HAM56, P=0.03), and the lowest plasma free fatty acid excursions after a glucose charge (FFA AUC, P=0.03). Gut microbiota was profiled from faecal samples by qPCR in all the subjects. Intriguingly subjects in cluster C had the highest level of Lactobacillus/Leuconostoc/Pediococcus group before diet. During the dietary program subjects in cluster C consumed more starchy foods, less protein and raw vegetables. Spearman correlations revealed positive relationship between weight regain after diet and HOMA-IR (P=0.0002, rs=0.5), inflammatory markers (leucocytes numbers: P=0.05, rs=0.27; Neutrophils: P=0.05, rs=0.28; IL-6: P=0.002, rs=0.43) as well as the number of Lactobacillus/Leuconostoc/Pediococcus group (p=0.005, rs=0.4) at baseline. Bayesian network (BN) was performed for prediction of the 3 clusters by using the data prior to the weight-loss dietary program. According to the learnt structure of BN, the levels of 4 biomarkers (plasma insulin, IL-6, leucocytes numbers and adipose tissue HAM56) at baseline were sufficient to characterize the distribution of the 3 clusters. The prediction of clusters was 75.5% (37 among 49 subjects). We concluded that individual responses to hypocaloric high protein dietary program could be predicted by plasma insulin, IL-6, leucocytes numbers and adipose tissue HAM56 levels prior to diet.
Databáze: OpenAIRE
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