Background: A low-calorie diet (LCD) reduces fat mass excess, improves insulin sensitivity, and alters adipose tissue (AT) gene expression, yet the relation with clinical outcomes remains unclear. Objective: We evaluated AT transcriptome alterations during an LCD and the association with weight and glycemic outcomes both at LCD termination and 6 mo after the LCD. Design: Using RNA sequencing (RNAseq), we analyzed transcriptome changes in AT from 191 obese, nondiabetic patients within a multicenter, controlled dietary intervention. Expression changes were associated with outcomes after an 8-wk LCD (800-1000 kcal/d) and 6 mo after the LCD. Results were validated by using quantitative reverse transcriptase-polymerase chain reaction in 350 subjects from the same cohort. Statistical models were constructed to classify weight maintainers or glycemic improvers. Results: With RNAseq analyses, we identified 1173 genes that were differentially expressed after the LCD, of which 350 and 33 were associated with changes in body mass index (BMI; in kg/m 2 ) and Matsuda index values, respectively, whereas 29 genes were associated with both endpoints. Pathway analyses highlighted enrichment in lipid and glucose metabolism. Classification models were constructed to identify weight maintainers. A model based on clinical baseline variables could not achieve any classification , and Nestlé Institute of Health Sciences. This is a free access article, distributed under terms (http://www.nutrition.org/publications/ guidelines-and-policies/license/) that permit unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Supplemental Figures 1 and 2 and Supplemental Tables 1-11 are available from the "Online Supporting Material" link in the online posting of the article and from the same link in the online table of contents at http://ajcn. nutrition.org.CA and AV contributed equally to this work. Address correspondence to AV (e-mail: armand.valsesia@rd.nestle.com). Abbreviations used: AT, adipose tissue; CAV2, caveolin 2; C7, complement component 7; ELOVL5, ELOVL fatty acid elongase 5; ENSG, Ensembl gene identifier; eQTL, expression quantitative trait loci; FDR, false discovery rate; GSDMB, gasdermin B; LCD, low-calorie diet; LEP, leptin; LOX, lysyl oxidase; ME1, malic enzyme 1; MTCH2, mitochondrial carrier 2; NPY1R, neuropeptide Y receptor Y1; PCK2, phosphoenolpyruvate carboxykinase 2; PPAP2A, phosphatidic acid phosphatase type 2A; RNAseq, RNA sequencing; ROC, receiver operating characteristic; RSD, relative SD; RT-qPCR, reverse transcription quantitative polymerase chain reaction; SNP, single nucleotide polymorphism; SPARC, secreted protein acidic and cysteine rich; SVF, stromal vascular fraction; T2D, type 2 diabetes.
Impaired adipose tissue insulin signaling is a critical feature of insulin resistance. Here we identify a pathway linking the lipolytic enzyme, hormone-sensitive lipase (HSL), to insulin action via the glucose-responsive transcription factor ChREBP and its target, the fatty acid (FA) elongase, ELOVL6. Genetic inhibition of HSL in human adipocytes and mouse adipose tissue results in enhanced insulin sensitivity and induction of ELOVL6. ELOVL6 promotes an increase in phospholipid (PL) oleic acid which modifies plasma membrane fluidity and enhances insulin signaling. HSL deficiency-mediated effects are suppressed by gene silencing of ChREBP and ELOVL6. Mechanistically, physical interaction between HSL and ChREBPα, independently of lipase catalytic activity, impairs ChREBPα translocation into the nucleus and induction of ChREBPβ, the transcriptionally highly active isoform strongly associated to whole body insulin sensitivity. Targeting the HSL-ChREBP interaction may allow therapeutic strategies for the restoration of insulin sensitivity. Morigny, Houssier et al.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.