Effects of Liraglutide, a Human Glucagon-Like Peptide-1 Analog, on Glucose/Lipid Metabolism, and Adipocytokines in Patients With Type 2 Diabetes
Notice bibliographique
Résumé
The glucagon-like peptide 1 (GLP-1), one of gastrointestinal hormones, stimulates insulin secretion from pancreatic s-cells in a glucose-dependent manner. Recently, liraglutide, a human GLP-1 analog, has been introduced as therapeutic strategies for type 2 diabetes mellitus. Clinical studies have demonstrated reduction in blood glucose and body weight, improvements in pancreatic s-cell function and a low risk for hypoglycemia with liraglutide [1, 2]. Since diabetes is signifi cantly associated with cardiovascular events, it is very important to understand effects of anti-diabetic drugs on other cardiovascular risk biomarkers. Therefore, we studied effects of liraglutide on glucose/lipid metabolism and adipocytokines in patients with type 2 diabetes. Five patients (4 females and one male) with type 2 diabetes participated in this study. The mean ± SD of age, body height, body weight, body mass index and hemoglobin A1c were 60.2 ± 8.9 years old, 156.1 ± 5.4 cm, 71.6 ± 15.6 kg, 29.5 ± 7.0 kg/m2 and 9.1 ± 2.1%, respectively. We measured high-sensitivity C-reactive protein (hs-CRP), adiponectin, interleukin-6, and small dense low-density lipoprotein (sdLDL), oxidized LDL (ox-LDL) and cholesterol level in each lipoprotein fraction using the high-performance liquid chromatography (HPLC) method before and after the two weeks treatment using liraglutide (0.3 mg for one week and 0.6 mg for one week) [3]. The data are presented in Figure 1. A statistical signifi cant increase in serum fasting C-peptide levels was observed following two week treatment with liraglutide. However, fasting plasma glucose levels were elevated. Although statistical signifi cances were not obtained compared with baseline, serum levels of total cholesterol (TC) and triglyceride (TG) tended to decrease. Liraglutide also tended to reduce TG-rich lipoproteins such as chylomicron, intermediate density-lipoprotein (IDL), very low density-lipoprotein (VLDL) and sd-LDL. Although statistical signifi cances were not also obtained compared with baseline, serum adiponectin levels decreased, and interleukin-6 and hs-CRP levels increased. Further, serum ox-LDL increased following liraglutide treatment. In the LEAD (Liraglutide Effect and Action in Diabetes) 4 study, serum C-peptide levels signifi cantly increased, and serum levels of TC, TG, LDL-cholesterol (LDL-C), free fatty acids (FFA) signifi cantly decreased following 26-week treatment with liraglutide [4]. Seino Y et al performed the 24-week, multicenter, double blind, randomized parallelgroup trial compared the effi cacy and safety of liraglutide and glibenclamide monotherapy in Japanese subjects with type 2 diabetes [5]. Liraglutide signifi cantly reduced serum FFA levels compared with glibenclamide, however, there were no signifi cant differences in serum levels of TC, LDLC, VLDL-C, HDL-C and TG between the two groups. In our study, liraglutide signifi cantly increased serum C-peptide levels compared with baseline, which supports the results of LEAD 4 study and our previous study and also suggests that two weeks is suffi cient to increase serum C-peptide [4, 6]. To our knowledge, our report is the fi rst to study serum levels of IDLC, CM-C, sd-LDL following liraglutide treatment. Although statistical signifi cant differences were not obtained compared with baseline, liraglutide tended to reduce TG, TG-rich lipoprotein, and sd-LDL. In the LEAD 4 and study by Seino Y et al, liraglutide signifi cantly decreased serum FFA levels [4, 5]. Liraglutide has been reported to reduce postprandial glucagon levels by 20% [7]. Glucagon stimulates lipolysis in adipocytes and increase plasma FFA levels [8]. Reduction of glucagon-mediated increase in serum FFA Manuscript accepted for publication August 22, 2011
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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