Chronic inflammation that affects primarily metabolic organs, such as white adipose tissue (WAT), is considered as a major cause of human obesity-associated co-morbidities. However, the molecular mechanisms initiating this inflammation in WAT are poorly understood. By combining transcriptomics, ChIP-seq and modeling approaches, we studied the global early and late responses to a high-fat diet (HFD) in visceral (vWAT) and subcutaneous (scWAT) AT, the first being more prone to obesity-induced inflammation. HFD rapidly triggers proliferation of adipocyte precursors within vWAT. However, concomitant antiadipogenic signals limit vWAT hyperplastic expansion by interfering with the differentiation of proliferating adipocyte precursors. Conversely, in scWAT, residing beige adipocytes lose their oxidizing properties and allow storage of excessive fatty acids. This phase is followed by tissue hyperplastic growth and increased angiogenic signals, which further enable scWAT expansion without generating inflammation. Our data indicate that scWAT and vWAT differential ability to modulate adipocyte number and differentiation in response to obesogenic stimuli has a crucial impact on the different susceptibility to obesity-related inflammation of these adipose tissue depots.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

In addition to improving insulin sensitivity in type 2 diabetes, the thiazolidinedione family of compounds and the pharmacologic activation of their best-characterized target PPARγ have been proposed as a therapeutic option for cancer treatment. In this study, we reveal a new mode of action for the thiazolidinedione rosiglitazone that can contribute to tumorigenesis. Rosiglitazone activated a tumorigenic paracrine communication program in a subset of human melanoma cells that involves the secretion of cytokines, chemokines, and angiogenic factors. This complex blend of paracrine signals activated nonmalignant fibroblasts, endothelial cells, and macrophages in a tumor-friendly way. In agreement with these data, rosiglitazone promoted human melanoma development in xenografts, and tumors exposed to rosiglitazone exhibited enhanced angiogenesis and inflammation. Together, these findings establish an important tumorigenic action of rosiglitazone in a subset of melanoma cells. Although studies conducted on cohorts of diabetic patients report overall benefits of thiazolidinediones in cancer prevention, our data suggest that exposure of established tumors to rosiglitazone may be deleterious. These findings uncover a novel mechanism by which the thiazolidinedione compound rosiglitazone contributes to tumorigenesis, thus highlighting a potential risk associated with its use in patients with established tumors. .

Transcriptional regulations exert a critical control of metabolic homeostasis. In particular, the nuclear receptors (NRs) are involved in regulating numerous pathways of the intermediate metabolism. The purpose of the present study was to explore in liver cells the interconnectedness between three of them, LXR, FXR, and PPARα, all three known to act on lipid and glucose metabolism, and also on inflammation. The human cell line HepaRG was selected for its best proximity to human primary hepatocytes. Global gene expression of differentiated HepaRG cells was assessed after 4 hours and 24 hours of exposure to GW3965 (LXR agonist), GW7647 (PPARα agonist), and GW4064 and CDCA (FXR synthetic and natural agonist, respectively). Our work revealed that, contrary to our expectations, NR specificity is largely present at the level of target genes, with a smaller than expected overlap of the set of genes targeted by the different NRs. It also highlighted the much broader activity of the synthetic FXR ligand compared to CDCA. More importantly, our results revealed that activation of FXR has a pro-proliferative effect and decreases the number of tetraploid (or binucleated) hepatocytes, while LXR inhibits the cell cycle progression, inducing hepatocyte differentiation and an increase in tetraploidism. Conclusion: these results highlight the importance of analyzing the different NR activities in a context allowing a direct confrontation of each receptor outcome, and reveals the opposite role of FXR and LXR in hepatocyte cells division and maturation.

Obesity is a common complex trait that elevates the risk for various diseases, including type 2 diabetes and cardiovascular disease. A combination of environmental and genetic factors influences the pathogenesis of obesity. Advances in genomic technologies have driven the identification of multiple genetic loci associated with this disease, ranging from studying severe onset cases to investigating common multifactorial polygenic forms. Additionally, findings from epigenetic analyses of modifications to the genome that do not involve changes to the underlying DNA sequence have emerged as key signatures in the development of obesity. Such modifications can mediate the effects of environmental factors, including diet and lifestyle, on gene expression and clinical presentation. This review outlines what is known about the genetic and epigenetic contributors to obesity susceptibility, along with the albeit limited therapeutic options currently available. Furthermore, we delineate the potential mechanisms of actions through which epigenetic changes can mediate environmental influences and the related opportunities they present for future interventions in the management of obesity.

Transcriptional regulations exert a critical control of metabolic homeostasis. In particular, the nuclear receptors (NRs) are involved in regulating numerous pathways of the intermediate metabolism. The purpose of the present study was to explore in liver cells the interconnectedness between three of them, LXR, FXR, and PPARα, all three known to act on lipid and glucose metabolism, and also on inflammation. The human cell line HepaRG was selected for its best proximity to human primary hepatocytes. Global gene expression of differentiated HepaRG cells was assessed after 4 hours and 24 hours of exposure to GW3965 (LXR agonist), GW7647 (PPARα agonist), and GW4064 and CDCA (FXR synthetic and natural agonist, respectively). Our work revealed that, contrary to our expectations, NR specificity is largely present at the level of target genes, with a smaller than expected overlap of the set of genes targeted by the different NRs. It also highlighted the much broader activity of the synthetic FXR ligand compared to CDCA. More importantly, our results revealed that activation of FXR has a pro-proliferative effect and decreases polyploidy of hepatocytes, while LXR inhibits the cell cycle progression, inducing hepatocyte differentiation and a higher polyploidism. Conclusion: these results highlight the importance of analyzing the different NR activities in a context allowing a direct confrontation of each receptor outcome, and reveals the opposite role of FXR and LXR in hepatocyte cells division and maturation. Gene Set Enrichment Analysis (GSEA)Gene set enrichment analysis (GSEA) was performed as described in (9) for each treatment at each time point. Most of the gene sets were taken from KEGG, while BIOCARTA sets from the Broad Institute's Molecular Signatures Database (MsigDB version 3.0: www.broadinstitute.org/gsea/msigdb) are explicitly mentioned. Genes that were part of a gene set but that were not found on the Affymetrix chip via their gene symbol were removed from the gene sets. Of these reduced gene sets, those that had fewer than 10 or more than 500 genes were discarded, leaving a total of 327 gene sets. The gene sets were scored against the ranked lists from the LIMMA analysis (four per time point). The absolute t-values from the moderated t-tests were used for both ranking and weighting the genes. P-values were computed using sample permutation with 500 iterations, separately for each of the two time points. At each iteration, the limma model with four contrasts described in the section above was run on the permuted data in order to compute gene set scores for all four treatmentcontrol comparisons. The estimated p-value for a gene set is the proportion of sample permutations that led to a higher score than the original data. To correct for multiple testing, the p-values of the gene sets were adjusted by the Benjamini-Hochberg method. This was done globally for the four gene set lists from time point 4 hours and for the four gene-set lists from time point 24h. We considered a gene set potentially enriched if it ha...