Skip to main content
Top
Published in: Diabetologia 11/2014

01-11-2014 | Article

Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss

Authors: Harish Dharuri, Peter A. C. ’t Hoen, Jan B. van Klinken, Peter Henneman, Jeroen F. J. Laros, Mirjam A. Lips, Fatiha el Bouazzaoui, Gert-Jan B. van Ommen, Ignace Janssen, Bert van Ramshorst, Bert A. van Wagensveld, Hanno Pijl, Ko Willems van Dijk, Vanessa van Harmelen

Published in: Diabetologia | Issue 11/2014

Login to get access

Abstract

Aims/hypothesis

Not all obese individuals develop type 2 diabetes. Why some obese individuals retain normal glucose tolerance (NGT) is not well understood. We hypothesise that the biochemical mechanisms that underlie the function of adipose tissue can help explain the difference between obese individuals with NGT and those with type 2 diabetes.

Methods

RNA sequencing was used to analyse the transcriptome of samples extracted from visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) of obese women with NGT or type 2 diabetes who were undergoing bariatric surgery. The gene expression data was analysed by bioinformatic visualisation and statistical analyses techniques.

Results

A network-based approach to distinguish obese individuals with NGT from obese individuals with type 2 diabetes identified acetyl-CoA metabolic network downregulation as an important feature in the pathophysiology of type 2 diabetes in obese individuals. In general, genes within two reaction steps of acetyl-CoA were found to be downregulated in the VAT and SAT of individuals with type 2 diabetes. Upon weight loss and amelioration of metabolic abnormalities three months following bariatric surgery, the expression level of these genes recovered to levels seen in individuals with NGT. We report four novel genes associated with type 2 diabetes and recovery upon weight loss: ACAT1 (encoding acetyl-CoA acetyltransferase 1), ACACA (encoding acetyl-CoA carboxylase α), ALDH6A1 (encoding aldehyde dehydrogenase 6 family, member A1) and MTHFD1 (encoding methylenetetrahydrofolate dehydrogenase).

Conclusions/interpretation

Downregulation of the acetyl-CoA network in VAT and SAT is an important feature in the pathophysiology of type 2 diabetes in obese individuals. ACAT1, ACACA, ALDH6A1 and MTHFD1 represent novel biomarkers in adipose tissue associated with type 2 diabetes in obese individuals.
Appendix
Available only for authorised users
Literature
1.
go back to reference Malik VS, Willett WC, Hu FB (2013) Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol 1:13–27 Malik VS, Willett WC, Hu FB (2013) Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol 1:13–27
2.
go back to reference Mokdad AH, Ford ES, Bowman BA et al (2003) Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA 289:76–79PubMedCrossRef Mokdad AH, Ford ES, Bowman BA et al (2003) Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA 289:76–79PubMedCrossRef
3.
go back to reference Van Gaal LF, Mertens IL, de Block CE (2006) Mechanisms linking obesity with cardiovascular disease. Nature 444:875–880PubMedCrossRef Van Gaal LF, Mertens IL, de Block CE (2006) Mechanisms linking obesity with cardiovascular disease. Nature 444:875–880PubMedCrossRef
4.
go back to reference Bluher M (2012) Are there still healthy obese patients? Curr Opin Endocrinol Diabetes Obes 19:341–346PubMedCrossRef Bluher M (2012) Are there still healthy obese patients? Curr Opin Endocrinol Diabetes Obes 19:341–346PubMedCrossRef
5.
go back to reference Bluher M (2013) Adipose tissue dysfunction contributes to obesity related metabolic diseases. Best Pract Res Clin Endocrinol Metab 27:163–177PubMedCrossRef Bluher M (2013) Adipose tissue dysfunction contributes to obesity related metabolic diseases. Best Pract Res Clin Endocrinol Metab 27:163–177PubMedCrossRef
6.
go back to reference Kantartzis K, Machann J, Schick F et al (2011) Effects of a lifestyle intervention in metabolically benign and malign obesity. Diabetologia 54:864–868PubMedCrossRef Kantartzis K, Machann J, Schick F et al (2011) Effects of a lifestyle intervention in metabolically benign and malign obesity. Diabetologia 54:864–868PubMedCrossRef
7.
go back to reference Lindstrom J, Tuomilehto J (2003) The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 26:725–731PubMedCrossRef Lindstrom J, Tuomilehto J (2003) The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 26:725–731PubMedCrossRef
8.
go back to reference Pajunen P, Kotronen A, Korpi-Hyovalti E et al (2011) Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey. BMC Public Health 11:754PubMedCrossRefPubMedCentral Pajunen P, Kotronen A, Korpi-Hyovalti E et al (2011) Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey. BMC Public Health 11:754PubMedCrossRefPubMedCentral
9.
go back to reference Wolfs MG, Rensen SS, Bruin-Van Dijk EJ et al (2010) Co-expressed immune and metabolic genes in visceral and subcutaneous adipose tissue from severely obese individuals are associated with plasma HDL and glucose levels: a microarray study. BMC Med Genomics 3:34PubMedCrossRefPubMedCentral Wolfs MG, Rensen SS, Bruin-Van Dijk EJ et al (2010) Co-expressed immune and metabolic genes in visceral and subcutaneous adipose tissue from severely obese individuals are associated with plasma HDL and glucose levels: a microarray study. BMC Med Genomics 3:34PubMedCrossRefPubMedCentral
10.
go back to reference Klikacova E, Roussel B, Marquez-Quinones A et al (2011) Worsening of obesity and metabolic status yields similar molecular adaptations in human subcutaneous and visceral adipose tissue: decreased metabolism and increased immune response. J Clin Endocrinol Metab 96:E73–E82CrossRef Klikacova E, Roussel B, Marquez-Quinones A et al (2011) Worsening of obesity and metabolic status yields similar molecular adaptations in human subcutaneous and visceral adipose tissue: decreased metabolism and increased immune response. J Clin Endocrinol Metab 96:E73–E82CrossRef
11.
go back to reference Qatanani M, Tan Y, Dobrin R et al (2013) Inverse regulation of inflammation and mitochondrial function in adipose tissue defines extreme insulin sensitivity in morbidly obese patients. Diabetes 62:855–863PubMedCrossRefPubMedCentral Qatanani M, Tan Y, Dobrin R et al (2013) Inverse regulation of inflammation and mitochondrial function in adipose tissue defines extreme insulin sensitivity in morbidly obese patients. Diabetes 62:855–863PubMedCrossRefPubMedCentral
12.
go back to reference Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628PubMedCrossRef Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628PubMedCrossRef
15.
go back to reference Van Harmelen V, Lonnqvist F, Thorne A et al (1997) Noradrenaline-induced lipolysis in isolated mesenteric, omental and subcutaneous adipocytes from obese subjects. Int J Obes Relat Metab Disord 21:972–979PubMedCrossRef Van Harmelen V, Lonnqvist F, Thorne A et al (1997) Noradrenaline-induced lipolysis in isolated mesenteric, omental and subcutaneous adipocytes from obese subjects. Int J Obes Relat Metab Disord 21:972–979PubMedCrossRef
16.
go back to reference Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC (2004) A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 20:93–99PubMedCrossRef Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC (2004) A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 20:93–99PubMedCrossRef
18.
20.
go back to reference Naimi M, Arous C, van Obberghen E (2010) Energetic cell sensors: a key to metabolic homeostasis. Trends Endocrinol Metab 21:75–82PubMedCrossRef Naimi M, Arous C, van Obberghen E (2010) Energetic cell sensors: a key to metabolic homeostasis. Trends Endocrinol Metab 21:75–82PubMedCrossRef
21.
go back to reference Herman MA, She P, Peroni OD, Lynch CJ, Kahn BB (2010) Adipose tissue branched chain amino acid (BCAA) metabolism modulates circulating BCAA levels. J Biol Chem 285:11348–11356PubMedCrossRefPubMedCentral Herman MA, She P, Peroni OD, Lynch CJ, Kahn BB (2010) Adipose tissue branched chain amino acid (BCAA) metabolism modulates circulating BCAA levels. J Biol Chem 285:11348–11356PubMedCrossRefPubMedCentral
22.
go back to reference Dahlman I, Forsgren M, Sjogren A et al (2006) Downregulation of electron transport chain genes in visceral adipose tissue in type 2 diabetes independent of obesity and possibly involving tumor necrosis factor-alpha. Diabetes 55:1792–1799PubMedCrossRef Dahlman I, Forsgren M, Sjogren A et al (2006) Downregulation of electron transport chain genes in visceral adipose tissue in type 2 diabetes independent of obesity and possibly involving tumor necrosis factor-alpha. Diabetes 55:1792–1799PubMedCrossRef
23.
24.
go back to reference Cai L, Sutter BM, Li B, Tu BP (2011) Acetyl-CoA induces cell growth and proliferation by promoting the acetylation of histones at growth genes. Mol Cell 42:426–437PubMedCrossRefPubMedCentral Cai L, Sutter BM, Li B, Tu BP (2011) Acetyl-CoA induces cell growth and proliferation by promoting the acetylation of histones at growth genes. Mol Cell 42:426–437PubMedCrossRefPubMedCentral
25.
go back to reference Cai L, Tu BP (2011) On acetyl-CoA as a gauge of cellular metabolic state. Cold Spring Harb Symp Quant Biol 76:195–202PubMedCrossRef Cai L, Tu BP (2011) On acetyl-CoA as a gauge of cellular metabolic state. Cold Spring Harb Symp Quant Biol 76:195–202PubMedCrossRef
26.
go back to reference Sahoo S, Franzson L, Jonsson JJ, Thiele I (2012) A compendium of inborn errors of metabolism mapped onto the human metabolic network. Mol Biosyst 8:2545–2558PubMedCrossRef Sahoo S, Franzson L, Jonsson JJ, Thiele I (2012) A compendium of inborn errors of metabolism mapped onto the human metabolic network. Mol Biosyst 8:2545–2558PubMedCrossRef
27.
go back to reference Thiele I, Swainston N, Fleming RM et al (2013) A community-driven global reconstruction of human metabolism. Nat Biotechnol 31:419–425PubMedCrossRef Thiele I, Swainston N, Fleming RM et al (2013) A community-driven global reconstruction of human metabolism. Nat Biotechnol 31:419–425PubMedCrossRef
28.
go back to reference Haapalainen AM, Merilainen G, Pirila PL, Kondo N, Fukao T, Wierenga RK (2007) Crystallographic and kinetic studies of human mitochondrial acetoacetyl-CoA thiolase: the importance of potassium and chloride ions for its structure and function. Biochemistry 46:4305–4321PubMedCrossRef Haapalainen AM, Merilainen G, Pirila PL, Kondo N, Fukao T, Wierenga RK (2007) Crystallographic and kinetic studies of human mitochondrial acetoacetyl-CoA thiolase: the importance of potassium and chloride ions for its structure and function. Biochemistry 46:4305–4321PubMedCrossRef
29.
go back to reference GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group, Wellcome Trust Case Control Consortium, Zhou K et al (2011) Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet 43:117–120PubMedCrossRefPubMedCentral GoDARTS and UKPDS Diabetes Pharmacogenetics Study Group, Wellcome Trust Case Control Consortium, Zhou K et al (2011) Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet 43:117–120PubMedCrossRefPubMedCentral
30.
31.
go back to reference Lappalainen T, Sammeth M, Friedlander MR et al (2013) Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501:506–511PubMedCrossRefPubMedCentral Lappalainen T, Sammeth M, Friedlander MR et al (2013) Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501:506–511PubMedCrossRefPubMedCentral
32.
go back to reference ’t Hoen PA, Friedlander MR, Almlof J et al (2013) Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories. Nat Biotechnol 31:1015–1022PubMedCrossRef ’t Hoen PA, Friedlander MR, Almlof J et al (2013) Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories. Nat Biotechnol 31:1015–1022PubMedCrossRef
33.
go back to reference Soronen J, Laurila PP, Naukkarinen J et al (2012) Adipose tissue gene expression analysis reveals changes in inflammatory, mitochondrial respiratory and lipid metabolic pathways in obese insulin-resistant subjects. BMC Med Genomics 5:9PubMedCrossRefPubMedCentral Soronen J, Laurila PP, Naukkarinen J et al (2012) Adipose tissue gene expression analysis reveals changes in inflammatory, mitochondrial respiratory and lipid metabolic pathways in obese insulin-resistant subjects. BMC Med Genomics 5:9PubMedCrossRefPubMedCentral
34.
go back to reference Karelis AD, Faraj M, Bastard JP et al (2005) The metabolically healthy but obese individual presents a favorable inflammation profile. J Clin Endocrinol Metab 90:4145–4150PubMedCrossRef Karelis AD, Faraj M, Bastard JP et al (2005) The metabolically healthy but obese individual presents a favorable inflammation profile. J Clin Endocrinol Metab 90:4145–4150PubMedCrossRef
35.
go back to reference Naukkarinen J, Heinonen S, Hakkarainen A et al (2014) Characterising metabolically healthy obesity in weight-discordant monozygotic twins. Diabetologia 57:167–176PubMedCrossRef Naukkarinen J, Heinonen S, Hakkarainen A et al (2014) Characterising metabolically healthy obesity in weight-discordant monozygotic twins. Diabetologia 57:167–176PubMedCrossRef
36.
go back to reference Phillips CM, Perry IJ (2013) Does inflammation determine metabolic health status in obese and nonobese adults? J Clin Endocrinol Metab 98:E1610–E1619PubMedCrossRef Phillips CM, Perry IJ (2013) Does inflammation determine metabolic health status in obese and nonobese adults? J Clin Endocrinol Metab 98:E1610–E1619PubMedCrossRef
Metadata
Title
Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss
Authors
Harish Dharuri
Peter A. C. ’t Hoen
Jan B. van Klinken
Peter Henneman
Jeroen F. J. Laros
Mirjam A. Lips
Fatiha el Bouazzaoui
Gert-Jan B. van Ommen
Ignace Janssen
Bert van Ramshorst
Bert A. van Wagensveld
Hanno Pijl
Ko Willems van Dijk
Vanessa van Harmelen
Publication date
01-11-2014
Publisher
Springer Berlin Heidelberg
Published in
Diabetologia / Issue 11/2014
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-014-3347-0

Other articles of this Issue 11/2014

Diabetologia 11/2014 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine