Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

Although many genetic variants are known for obesity, their function remains largely unknown. Here, in a weight-loss intervention cohort, the authors identify protein quantitative trait loci associated with BMI at baseline and after weight loss and find FAM46A to be a regulator of leptin in adipocytes

Adipose tissue transcriptomic signature highlights the pathological relevance of extracellular matrix in human obesity

Analysis of the transcriptomic signature of white adipose tissue in obese human subjects revealed increased interstitial fibrosis and an infiltration of inflammatory cells into the tissue

Macrophages and Adipocytes in Human Obesity: Adipose Tissue Gene Expression and Insulin Sensitivity During Calorie Restriction and Weight Stabilization

International audienceOBJECTIVE: We investigated the regulation of adipose tissue gene expression during different phases of a dietary weight loss program and its relation with insulin sensitivity. RESEARCH DESIGN AND METHODS: Twenty-two obese women followed a dietary intervention program composed of an energy restriction phase with a 4-week very-low-calorie diet and a weight stabilization period composed of a 2-month low-calorie diet followed by 3-4 months of a weight maintenance diet. At each time point, a euglycemic-hyperinsulinemic clamp and subcutaneous adipose tissue biopsies were performed. Adipose tissue gene expression profiling was performed using a DNA microarray in a subgroup of eight women. RT-quantitative PCR was used for determination of mRNA levels of 31 adipose tissue macrophage markers (n = 22). RESULTS: Body weight, fat mass, and C-reactive protein level decreased and glucose disposal rate increased during the dietary intervention program. Transcriptome profiling revealed two main patterns of variations. The first involved 464 mostly adipocyte genes involved in metabolism that were downregulated during energy restriction, upregulated during weight stabilization, and unchanged during the dietary intervention. The second comprised 511 mainly macrophage genes involved in inflammatory pathways that were not changed or upregulated during energy restriction and downregulated during weight stabilization and dietary intervention. Accordingly, macrophage markers were upregulated during energy restriction and downregulated during weight stabilization and dietary intervention. The increase in glucose disposal rates in each dietary phase was associated with variation in expression of sets of 80-110 genes that differed among energy restriction, weight stabilization, and dietary intervention. CONCLUSIONS: Adipose tissue macrophages and adipocytes show distinct patterns of gene regulation and association with insulin sensitivity during the various phases of a dietary weight loss program

Semicarbazide-sensitive amine oxidase / vascular adhesion protein-1 activity exerts an antidiabetic action in Goto-Kakizaki rats

n this study we have explored whether the bifunctional protein semicarbazide-sensitive amine oxidase (SSAO)/vascular adhesion protein-1 (VAP-1) represents a novel target for type 2 diabetes. To this end, Goto-Kakizaki (GK) diabetic rats were treated with the SSAO substrate benzylamine and with low ineffective doses of vanadate previously shown to have antidiabetic effects in streptozotocin-induced diabetic rats. The administration of benzylamine in combination with vanadate in type 2 diabetic rats acutely stimulated glucose tolerance, and the chronic treatment normalized hyperglycemia, stimulated glucose transport in adipocytes, and reversed muscle insulin resistance. Acute in vivo administration of benzylamine and vanadate stimulated skeletal muscle glucose transport, an effect that was also observed in incubated muscle preparations coincubated with adipose tissue explants or with human recombinant SSAO. Acute administration of benzylamine/vanadate also ameliorated insulin secretion in diabetic GK rats, and this effect was also observed in incubated pancreatic islets. In keeping with these observations, we also demonstrate that pancreatic islets express SSAO/VAP-1. As far as mechanisms of action, we have found that benzylamine/vanadate causes enhanced tyrosine phosphorylation of proteins and reduced protein tyrosine phosphatase activity in adipocytes. In addition, incubation of human recombinant SSAO, benzylamine, and vanadate generates peroxovanadium compounds in vitro. Based on these data, we propose that benzylamine/vanadate administration generates peroxovanadium locally in pancreatic islets, which stimulates insulin secretion and also produces peroxovanadium in adipose tissue, activating glucose metabolism in adipocytes and in neighboring muscle. This opens the possibility of using the SSAO/VAP-1 activity as a local generator of protein tyrosine phosphatase inhibitors in antidiabetic therapy

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

BACKGROUND: The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS: The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8-12 kgs weight loss) could always be differentiated from non-responders (<4 kgs weight loss). We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box) approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%+/-8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier) improved prediction accuracy to 80.9%+/-2.2%. CONCLUSION: Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition

Effet de la somatostatine sur une lignee cellulaire pancreatique tumorale de rat, d'origine acinaire : caracterisation de son recepteur, role antiproliferatif

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Activation du métabolisme énergétique par le co-activateur PGC-1Alpha et implication du récepteur nucléaire PPAR Alpha dans l adipocyte blanc humain

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Multiway SIR for biological data integration

National audienc

Multiway-SIR for longitudinal multi-table data integration

International audienceAn extension of DUAL-STATIS to the sliced-inverse regression (SIR) framework is proposed to analyze multi-table datasets with respect to a numeric variable of interest. The method is designed to analyze the case where a data set $\mathbf{X}$, which corresponds to a set of $p$ variables measured $T$ times on the same $n$ subjects is related to a real target variable $\mathbf{y}$, measured on the same $n$ subjects. The approach is an exploratory method which aims at understanding the evolution of the relation between $\mathbf{X}$ and $\mathbf{y}$ through time. The method proceeds in two steps: 1) an inter-structure analysis studies the resemblance between the different time steps by computing similarities between estimates of the covariance of the mean of $\mathbf{X}_{..t}$ conditional to $\mathbf{y}$. Similarly to SIR, the conditional expectation is estimated by slicing the range of $\mathbf{y}$. The result of this analysis is a compromise covariance matrix $\Gamma^c$, which captures a compromise correlation structure of $\mathbb{E}(\mathbf{X}_{..t}|y)$ over $t$; 2) an intra-structure analysis which is a generalized PCA of the compromise. This second step results in graphical outputs which can be used to explore the covariance structure between variables and time steps conditional to $\mathbf{y}$. The method is illustrated on a real problem related to the consequences of a low calorie diet on obese persons in which the target variable of interest is the weight gain/loss