Short-term fatty acid intervention elicits differential gene expression responses in adipose tissue from lean and overweight men
© The Author(s) 2008
Received: 29 August 2008
Accepted: 13 November 2008
Published: 26 November 2008
The goal of this study was to investigate the effect of a short-term nutritional intervention on gene expression in adipose tissue from lean and overweight subjects. Gene expression profiles were measured after consumption of an intervention spread (increased levels of polyunsaturated fatty acids, conjugated linoleic acid and medium chain triglycerides) and a control spread (40 g of fat daily) for 9 days. Adipose tissue gene expression profiles of lean and overweight subjects were distinctly different, mainly with respect to defense response and metabolism. The intervention resulted in lower expression of genes related to energy metabolism in lean subjects, whereas expression of inflammatory genes was down-regulated and expression of lipid metabolism genes was up-regulated in the majority of overweight subjects. Individual responses in overweight subjects were variable and these correlated better to waist–hip ratio and fat percentage than BMI.
KeywordsSubcutaneous adipose tissue Microarray Polyunsaturated fatty acids (PUFA) Conjugated linoleic acid (CLA) Medium chain triglycerides
Adipose tissue not only functions as a fat storage organ, it also has an important metabolic and endocrine function. Adipose tissue plays a role in insulin sensitivity and inflammatory status, e.g., through release of fatty acids and adipokines [1, 27]. In obesity, adipose tissue mass is increased and as a result, endocrine and metabolic functions of adipose tissue are affected. Moreover, obesity is associated with systemic inflammation due to macrophage infiltration in adipose tissue. Complications of obesity include insulin resistance, cardiovascular disease and metabolic syndrome [1, 38, 39].
It has been shown that energy restriction, changes in dietary macronutrient composition and weight loss result in gene expression changes in adipose tissue from overweight or obese subjects [6, 22, 35]. The goal of this study was to investigate the effects of a short-term nutritional intervention on gene expression in adipose tissue and to investigate whether the gene expression response differs between lean and overweight subjects. Earlier, we showed that dietary effects can be monitored by gene expression profiling in white blood cells .
The nutritional intervention consisted of a spread with increased levels of medium chain triglycerides, short-chain polyunsaturated fatty acids (PUFA: C18:2 and C18:3) and conjugated linoleic acid (CLA: C18:2) (further referred to as intervention spread). This composition was chosen to elicit an effect on food intake and satiety. Medium chain triglycerides, PUFA and CLA are reported to have satiating power [13, 18, 29]. The two spreads did not differ in their effect on satiety (described in detail elsewhere: Pasman et al., in preparation). To a large extent, it is unknown how the fatty acids can influence food intake, energy expenditure and eventually body mass . Analysis of adipose tissue gene expression is of interest because of its central role in fat and energy metabolism in response to nutritional interventions and because of its role in inflammation. Furthermore, PUFA have been reported to influence adipose tissue function [5, 21] and CLA can play a role in reduction of adipose tissue mass [3, 37, 40].
We found that in adipose tissue fatty acid transporter gene expression was slightly higher in lean subjects and slightly lower in overweight subjects in response to the intervention spread compared to the control spread. Also, fatty acid uptake showed a tendency to change in response to the intervention (details in Pasman et al., in preparation). Here we study in greater detail the response of adipose tissue to the different fatty acid intake by whole genome gene expression profiling of subcutaneous adipose tissue biopsies taken from the subjects after consumption of the intervention or control spread with an equal amount of fat for 9 days.
Effects of the short-term nutritional intervention were studied both in overweight and lean subjects, by focusing on enriched functional groups of genes and putting these in the context of the intervention, thereby aiming to shed a light on the potential mechanisms of action of the fatty acids.
Subjects and methods
Study design and subjects
The study was conducted at TNO Quality of Life, where subjects were recruited from a pool of volunteers. Each subject was informed about the study orally and in writing before they signed the informed consent forms. Subjects met the inclusion criteria: (1) healthy male subjects (lean: BMI between 18 and 25 kg/m2 or overweight/obese: BMI between 27.5 and 35 kg/m2), (2) normal Dutch eating pattern and used to consuming breakfast, (3) non-restrained eaters according to the Dutch Eating Behavior Questionnaire (lean: <2.5 and overweight/obese: <3.25) [33, 34]. Subjects with a disorder, using medication or having a history of medical or surgical events that may have affected study outcomes were excluded.
A total of 25 subjects (all of Dutch ancestry) were eligible of which 20 subjects were randomly selected as well as four reserves. Ten lean (BMI mean ± SD 21.2 ± 1.5 kg/m2, age range 19–41 years) and ten overweight men (BMI 29.7 ± 1.9 kg/m2, age range 21–58 years) started and completed the study. Body fat percentage was 12.2 ± 4.2% in the lean sub-group compared to 27.8 ± 3.7% in the overweight sub-group. Waist circumference was 79 ± 6 cm in the lean sub-group compared to 102 ± 8 cm in the overweight sub-group and waist–hip ratio (WHR) was 0.86 ± 0.05 in the lean sub-group compared to 0.96 ± 0.07 in the overweight subgroup.
The study was approved by the Medical Ethics Committee of the University Medical Centre of Utrecht (20 September 2005) and conducted according to the ICH Guideline for Good Clinical Practice in October–November 2005.
The composition of the spreads
Intervention spread (%)
Control spread (%)
Lauric acid (MCT, C12:0) (and C14:0)
Palmitic acid (C16:0)
Stearic acid (C18:0)
Oleic acid (C18:1)
Conjugated linoleic acid (C18:2)
Linoleic acid (C18:2)
Pinolenic acid (C18:3)
Other fatty acids
No carry-over effect of treatments was found for bodyweight (data not shown).
Adipose tissue biopsies
Two fat biopsies were taken from each subject, one after consumption of the placebo spread for 9 days and one after consumption of the intervention spread for 9 days. Biopsies were taken in the evening and time of sampling was kept constant as much as possible for the two treatments. Subcutaneous adipose tissue was obtained from the abdominal region by needle aspiration under local anesthesia using 2× 50 ml 8.4% NaHCO3, 0.05% lidocaine and 1.0 mg/ml epinephrine (according to Kolaczynski et al. ). Part of the fat suspension was immediately frozen in liquid nitrogen and stored at −80°C for RNA isolation.
RNA isolation, labeling and hybridization
RNA was isolated by homogenizing the adipose tissue biopsies in Trizol (Life Technologies S.A., Merelbeke, Belgium). After chloroform extraction the RNA isolation was continued using NucleoSpin RNA II kit (Bioké, Leiden). The protocol included a DNase digestion step.
The isolated RNA samples were processed according to Affymetrix protocols by Scienion Ag (Berlin, Germany). In brief, RNA quality and integrity were verified using the RNA 6000 Nano assay on the Agilent 2100 Bioanalyzer (Agilent Technologies), resulting in RNA samples from ten lean and eight overweight subjects to be included in the microarray analysis (RNA samples from two overweight subjects did not pass the RNA quality control).
Next, 1.5 μg of high-quality total RNA was used with the Affymetrix Eukaryotic One-Cycle Target Labeling and Control reagents to generate Biotin-labeled antisense cRNA. The labeled cRNA was further used for the hybridization to the NuGO Affymetrix Human Genechip NuGO_Hs1a520180 (custom designed by the European Nutrigenomics Organization NuGO, consisting of 23,941 probesets including 71 control probesets, for details see http://blog.bigcat.unimaas.nl/~martijn/NuGO/). After an automated process of washing and staining, absolute values of expression were calculated from the scanned array using the Affymetrix GCOS software.
Quality control of microarray data was performed using BioConductor packages (a.o. simpleaffy and affyplm, through the NuGO MadMax pipeline: https://madmax.bioinformatics.nl). One microarray did not pass quality control criteria due to high background values and low percentage of present calls. Therefore, microarray data for nine lean and eight overweight subjects were included in data analysis.
Raw signal intensities (from CEL files) were normalized using the GCRMA algorithm (gc-rma slow). Probesets were filtered on at least one present call and at least one expression value above 5 (resulting in a set of 15,762 probesets). Expression data were log-transformed (base 2). The cross-over design of the study ensured measurement of gene expression profiles in adipose tissue of each subject after consumption of the placebo spread and after consumption of the intervention spread, allowing for analysis of gene expression changes in response to intervention within each subject [calculated as 2log ratio (intervention vs placebo)].
First, effects of BMI (lean sub-group or overweight sub-group), treatment (intervention spread or control spread) as well as the interaction component BMI × Intervention was tested using two-way ANOVA in SAS (SAS Institute Inc., Cary, USA). The null hypotheses (no difference) were rejected at the level of 0.01 of probability. When testing 15,762 probesets with these conditions, 158 probesets are expected to be called significant.
Second, a paired t test for treatment effect in the lean and in the overweight subgroup was performed in BRB ArrayTools (software for microarray data analysis developed by Dr. Richard Simon and Amy Peng Lam, http://linus.nci.nih.gov/BRB-ArrayTools.html), using multiple testing correction by estimation of false discovery rate (FDR). Threshold for significance was set by taking into account P value (<0.01) as well as estimated FDR (<20%). Finally, in case of responders and non-responders within a sub-group, differentially expressed genes were selected based on showing a consistent response in the majority of the subjects (defined as ≥25% expression change up in more than 50% of the subjects or ≥25% expression change down in more than 50% of the subjects).
Subsets of differentially expressed genes were analyzed further in GenMAPP to find functional groups of genes (based on Gene Ontology) that were overrepresented in the subsets . Other tools used for data analysis include Gene Set Enrichment Analysis  and T-profiler  for enrichment analysis of functional groups of genes. The tissue-specific gene sets were derived from SymAtlas (http://symatlas.gnf.org/SymAtlas/)  and from Lyons et al. . Cluster and treeview (http://rana.lbl.gov/EisenSoftware.htm, ) were used for generation of cluster trees, using average linkage clustering and uncentered correlation as similarity metric. A biological network was generated in MetaCore version 4.3 (GeneGo Inc., St Joseph, MI, USA). MetaCore™ is based on a proprietary manually curated database of human protein–protein, protein–DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression. Only curated interactions were used.
Data from the placebo intervention were used for comparison of gene expression levels in adipose tissue from lean and overweight subjects.
The gene expression data are available through ArrayExpress, a public repository for microarray data (http://www.ebi.ac.uk/arrayexpress/, accession numer E-TABM-377).
Enriched functional groups (based on Gene Ontology) in total set of differentially expressed genes in lean versus overweight subjects (3,069 probesets), in genes expressed at high levels in lean than in overweight (1,325 probesets) and in genes expressed at higher levels in lean than overweight (1,744 probesets)
Functional group of genes
Number of genes measured
Higher in lean
Higher in overweight
Generation of precursor metabolites and energy
Response to stress
Intracellular signaling cascade
I-kappaB kinase/NF-kappaB cascade
Scavenger receptor activity
On the other hand, genes involved in defense response, intracellular signaling and cell adhesion were expressed at higher levels in adipose tissue from overweight subjects than in adipose tissue from lean subjects. Within these groups of genes, gene expression of specific macrophage markers [e.g., CD14, CD163 and macrophage scavenger receptor 1 (MSR1)] was significantly higher in adipose tissue of overweight subjects (P < 0.001 for BMI-effect in two-way ANOVA), pointing towards presence of macrophages or inflammatory cells in the adipose tissue biopsies from overweight subjects. This is further illustrated in supplementary Fig. 1, which clearly shows higher expression of genes specific for CD14-positive monocytes in adipose tissue from seven overweight subjects than in adipose tissue from lean subjects. Enrichment analysis of tissue-specific gene sets, by comparing the lean sub-group to overweight sub-group (GSEA) and by analyzing overweight subjects individually (T-profiler), showed that this set of genes specific for CD14-positive monocytes was significantly enriched in the adipose tissue from overweight subjects compared to lean subjects and that this gene set was among the two most enriched gene sets in seven out of the eight overweight subjects. Other inflammatory markers that were expressed at higher level in adipose tissue from overweight subjects included leptin, complement factor D (CFD), interleukin receptor 6 (IL6R), interleukin receptor 10 alpha (IL10RA), interleukin 1 receptor antagonist (IL1RN) and a number of interleukins (IL15, IL17D, IL18) (data not shown).
Enriched functional groups (based on Gene Ontology) in set of differentially expressed genes (813 probesets) and in sub-set of down-regulated genes (509 probesets) in sub-group of lean subjects in response to treatment
Functional group of genes
Number of genes measured
Generation of precursor metabolites and energy
Regulation of cell cycle
Complement activation\, classical pathway
Oxygen and reactive oxygen species metabolism
To our knowledge, this study is one of the first to perform large-scale gene expression analysis in human adipose tissue biopsies in response to a short-term nutritional intervention, in both lean and overweight subjects. The study is exploratory in nature and describes the results on a pathway or functional group level with interpretation in relation to the intervention and literature data.
Our study data indicated that a considerable part of the differences in gene expression profiles could be attributed to the difference in BMI between the two sub-groups. Expression of inflammation-related genes was significantly higher in subcutaneous adipose tissue biopsies from overweight subjects than those from lean subjects. Specifically, markers specific for monocytes in blood were significantly higher expressed in the adipose tissue from overweight subjects, as was shown by different enrichment analysis approaches. As tissue macrophages originate from monocytes in blood that migrate into tissue, this finding is consistent with increased macrophage content of adipose tissue from overweight subjects, as previously described by others . In addition to macrophage markers, also expression of specific adipokines was different between lean and overweight subjects. Consistent with other reports [14, 23], expression of leptin was higher and expression of adiponectin was lower (although not significantly) in adipose tissue from overweight subjects than in adipose tissue from lean subjects.
Expression of metabolism-related genes and genes encoding mitochondrial proteins was higher in subcutaneous adipose tissue from lean subjects than in adipose tissue from overweight subjects. A recent study of transcription profiles in adipose tissue from monozygotic twins discordant for BMI also reported lower expression of genes related to energy metabolism in obese subjects . In addition, they report a reduction in mitochondrial DNA in adipose tissue from obese subjects. Overall, this indicates a possible difference in mitochondrial content or mitochondrial activity in adipose tissue from lean subjects and overweight subjects. However, it can not be excluded that the increased mitochondrial activity actually reflects a difference in cell number in the adipose tissue biopsies, as increased adipose tissue mass can be due to increased adipocyte cell size as well as increased number of adipocytes.
The dietary intervention consisted of replacement of oleic acid and stearic acid in the placebo spread by short-chain polyunsaturated fatty acids (PUFA: C18:2 and C18:3), conjugated linoleic acid (CLA: C18:2) and medium chain triglycerides (C12:0) in the intervention spread. Thus, the gene expression differences can be related to differences in intake of all these fatty acids and should be interpreted in that context.
Both CLA and PUFA (specifically n-3 PUFA) can exert anti-inflammatory effects [4, 24]. In the majority of overweight subjects, dietary intervention resulted in down-regulation of expression of a number of inflammation-related genes (in enriched category ‘response to stress’) that were expressed at significantly higher level in adipose tissue from overweight subjects than in adipose tissue from lean subjects. This anti-inflammatory effect of the intervention was, e.g., seen for macrophage inflammatory protein 2 alpha (CXCL2), macrophage receptor MARCO (MARCO) and interleukin-1 receptor antagonist (IL1RN). In adipose tissue from lean subjects, the anti-inflammatory effect of the dietary intervention was restricted to down-regulation of genes involved in complement activation pathway (three subunits of complement C1q) and genes involved in reactive oxygen species metabolism.
In the majority of overweight subjects, dietary intervention affected expression of genes involved in lipid metabolism, resulting mostly in up-regulation of expression (Fig. 3). Expression of lipid metabolism genes was lower in adipose tissue from overweight subjects than in adipose tissue from lean subjects, therefore increased expression of lipid metabolism genes might be a beneficial effect of the intervention in overweight subjects. Moreover, increased energy expenditure as a result of up-regulation of lipid metabolism could be one of the mechanisms through which CLA decreases adipose tissue mass [4, 24, 37] and it could play a role in the proposed increase of energy expenditure by medium chain triglycerides . Additional effects of the dietary intervention in the majority of overweight subjects included effects on genes involved in apoptosis and genes involved in cell adhesion and extracellular matrix. Effects on these processes are consistent with recently described effects of CLA and PUFA [9, 12, 37].
In overweight subjects the response to the dietary intervention was not as strong as in the lean subjects and moreover, the response among the overweight subjects was variable. The consistent response in a selection of overweight subjects was not related to treatment order. Possibly, adipose tissue in overweight subjects is not as flexible and responsive to dietary intervention as adipose tissue in lean subjects. Also, the intervention effect might have been diluted due to increased adipose tissue mass in overweight subjects compared to the lean subjects, therefore resulting in less pronounced expression changes. Lastly, genotype and polymorphisms can not be exluded as a factor in the variation in response.
The overweight subjects were selected based on BMI, an obesity marker that does not take fully into account adipose tissue distribution in the body. In contrast, WHR and waist circumference are more specific markers for body fat distribution and presence of central or upper-body obesity [15, 19]. Interestingly, the individual response of the overweight subjects to the intervention correlated to the obesity phenotype markers WHR and fat percentage. For example, expression of mitochondrial genes was up-regulated in response to dietary intervention in the overweight subject with the lowest WHR and down-regulated in response to intervention in the overweight subject with the highest WHR. Interestingly, these two subjects have a similar BMI. Overall, these results show that the subjects, classified as overweight on the basis of their BMI, are heterogeneous in their response to dietary intervention and that this response is associated with obesity phenotype markers WHR and fat percentage, suggesting a link between body fat distribution and response to nutritional intervention.
The fat biopsies analyzed were subcutaneous biopsies, taken from the abdomen. Abdominal fat, mostly visceral abdominal fat, is often linked to complications and disease progression . However, some studies report a role for subcutaneous abdominal tissue in obesity related diseases . The finding that subcutaneous adipose tissue responds to nutritional intervention is encouraging for further research, as this is the only easily accessible source of adipose tissue from humans. Thus, whole genome expression profiling in adipose tissue may help to identify relevant mechanisms and targets of nutritional intervention in obesity prevention or treatment.
In summary, response to the dietary intervention was different in lean and overweight subjects. Increased short-chain polyunsaturated fatty acids (PUFA: C18:2 and C18:3), conjugated linoleic acid (CLA: C18:2) and medium chain triglycerides (C12:0) consumption resulted in lower expression of genes related to energy metabolism in lean subjects, whereas in the majority of overweight subjects expression of inflammatory genes was down-regulated and expression of lipid metabolism genes was up-regulated. Individual responses in overweight subjects were variable and these correlated better to obesity phenotype markers WHR and fat percentage than BMI.
The authors express their gratitude to the volunteers that participated in the study, to the people from the Metabolic Research Unit and laboratories who assisted in the organization of the study and to Michèle van den Wijngaard for RNA isolation. The authors are member of the European Nutrigenomics Organization (www.nugo.org). This study was financially supported by Dutch government through grant “Healthy nutrition” (grant number 04003).
Conflict of interest statement
None of the authors has any conflict of interest.
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
- Berg AH, Scherer PE (2005) Adipose tissue, inflammation, and cardiovascular disease. Circ Res 96:939–949PubMedView ArticleGoogle Scholar
- Boorsma A, Foat BC, Vis D, Klis F, Bussemaker HJ (2005) T-profiler: Scoring the activity of predefined groups of genes using gene expression data. Nucleic Acids Res 33:W592–W595PubMedView ArticleGoogle Scholar
- Brown JM, McIntosh MK (2003) Conjugated linoleic acid in humans: regulation of adiposity and insulin sensitivity. J Nutr 133:3041–3046PubMedGoogle Scholar
- Browning LM (2003) n-3 polyunsaturated fatty acids, inflammation and obesity-related disease. Proc Nutr Soc 62:447–453PubMedView ArticleGoogle Scholar
- Calder PC (2006) n-3 Polyunsaturated fatty acids, inflammation, and inflammatory diseases. Am J Clin Nutr 83Google Scholar
- Dahlman I, Linder K, Nordstrom EA, Andersson I, Liden J et al (2005) Changes in adipose tissue gene expression with energy-restricted diets in obese women. Am J Clin Nutr 81:1275–1285PubMedGoogle Scholar
- Doniger SW, Salomonis N, Dahlquist KD, Vranizan K, Lawlor SC, Conklin BR (2003) MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol 4:R7PubMedView ArticleGoogle Scholar
- Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95:14863–14868PubMedView ArticleGoogle Scholar
- Fischer-Posovszky P, Kukulus V, Zulet MA, Debatin KM, Wabitsch M (2007) Conjugated linoleic acids promote human fat cell apoptosis. Horm Metab Res 39:186–191PubMedView ArticleGoogle Scholar
- Goodpaster BH, Thaete FL, Simoneau JA, Kelley DE (1997) Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat. Diabetes 46:1579–1585PubMedView ArticleGoogle Scholar
- Hertz R, Magenheim J, Berman I, Bar-Tana J (1998) Fatty acyl-CoA thioesters are ligands of hepatic nuclear factor-4a. Nature 392:512–516PubMedView ArticleGoogle Scholar
- Huber J, Löffler M, Bilban M, Reimers M, Kadl A et al (2007) Prevention of high-fat diet-induced adipose tissue remodeling in obese diabetic mice by n-3 polyunsaturated fatty acids. Int J Obes 31:1004–1013View ArticleGoogle Scholar
- Kamphuis MMJW, Lejeune MPGM, Saris WHM, Westerterp-Plantenga MS (2003) Effect of conjugated linoleic acid supplementation after weight loss on appetite and food intake in overweight subjects. Eur J Clin Nutr 57:1268–1274PubMedView ArticleGoogle Scholar
- Kern PA, Di Gregorio GB, Lu T, Rassouli N, Ranganathan G (2003) Adiponectin expression from human adipose tissue: relation to obesity, insulin resistance, and tumor necrosis factor-? expression. Diabetes 52:1779–1785PubMedView ArticleGoogle Scholar
- Kok P, Seidell JC, Meinders AE (2004) The value and limitations of the Body Mass Index (BMI) in the assessment of the health risks of overweight and obesity. Ned Tijdschr Geneeskd 148:2379–2382PubMedGoogle Scholar
- Kolaczynski JW, Morales LM, Moore J, Considine RV, Pietrzkowski Z et al (1994) A new technique for biopsy of human abdominal fat under local anaesthesia with Lidocaine. Int J Obes 18:161–166Google Scholar
- Kovacs EMR, Mela DJ (2006) Metabolically active functional food ingredients for weight control. Obes Rev 7:59–78PubMedView ArticleGoogle Scholar
- Lawton CL, Delargy HJ, Brockman J, Smith FC, Blundell JE (2000) The degree of saturation of fatty acids influences post-ingestive satiety. Br J Nutr 83:473–482PubMedGoogle Scholar
- Lev-Ran A (2001) Human obesity: an evolutionary approach to understanding our bulging waistline. Diabetes Metab Res Rev 17:347–362PubMedView ArticleGoogle Scholar
- Lyons PA, Koukoulaki M, Hatton A, Doggett K, Woffendin HB et al (2007) Microarray analysis of human leucocyte subsets: the advantages of positive selection and rapid purification. BMC Genomics 8:64PubMedView ArticleGoogle Scholar
- Madsen L, Petersen RK, Kristiansen K (2005) Regulation of adipocyte differentiation and function by polyunsaturated fatty acids. Biochimica et Biophysica Acta Mol Basis Dis 1740:266–286View ArticleGoogle Scholar
- Mangravite LM, Dawson K, Davis RR, Gregg JP, Krauss RM (2007) Fatty acid desaturase regulation in adipose tissue by dietary composition is independent of weight loss and is correlated with the plasma triacylglycerol response. Am J Clin Nutr 86:759–767PubMedGoogle Scholar
- Mapfei M, Halaas J, Ravussin E, Pratley RE, Lee GH et al (1995) Leptin levels in human and rodent: Measurement of plasma leptin and ob RNA in obese and weight-reduced subjects. Nat Med 1:1155–1161View ArticleGoogle Scholar
- Moloney F, Toomey S, Noone E, Nugent A, Allan B et al (2007) Antidiabetic effects of cis-9, trans-11-conjugated linoleic acid may be mediated via anti-inflammatory effects in white adipose tissue. Diabetes 56:574–582PubMedView ArticleGoogle Scholar
- Odom DT, Zizlsperger H, Gordon DB, Bell GW, Rinaldi NJ et al (2004) Control of Pancreas and Liver Gene Expression by HNF Transcription Factors. Science 303:1378–1381PubMedView ArticleGoogle Scholar
- Pietilainen KH, Naukkarinen J, Rissanen A, Saharinen J, Ellonen P et al (2008) Global transcript profiles of fat in monozygotic twins discordant for BMI: pathways behind acquired obesity. PLoS Med 5:e51PubMedView ArticleGoogle Scholar
- Ronti T, Lupattelli G, Mannarino E (2006) The endocrine function of adipose tissue: An update. Clin Endocrinol 64:355–365Google Scholar
- Sampath H, Ntambi JM (2005) Polyunsaturated fatty acid regulation of genes of lipid metabolism. Annu Rev Nutr 25:317–340PubMedView ArticleGoogle Scholar
- St-Onge MP, Jones PJH (2002) Physiological effects of medium-chain triglycerides: Potential agents in the prevention of obesity. J Nutr 132:329–332PubMedGoogle Scholar
- Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA et al (2004) A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci USA 101:6062–6067PubMedView ArticleGoogle Scholar
- Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL et al (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102:15545–15550PubMedView ArticleGoogle Scholar
- van Erk MJ, Blom WA, van Ommen B, Hendriks HF (2006) High-protein and high-carbohydrate breakfasts differentially change the transcriptome of human blood cells. Am J Clin Nutr 84:1233–1241PubMedGoogle Scholar
- Van Strien T, Frijters JER, Bergers GPA, Defares PB (1986) The Dutch eating behavior questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. Int J Eat Disord 5:295–315View ArticleGoogle Scholar
- Van Strien T, Frijters JER, Bergers GPA, Defares PB (1986) Nederlandse vragenlijst voor eetgedrag Lisse, Zwets and Zeitlinger b.vGoogle Scholar
- Viguerie N, Vidal H, Arner P, Holst C, Verdich C et al (2005) Adipose tissue gene expression in obese subjects during low-fat and high-fat hypocaloric diets. Diabetologia 48:123–131PubMedView ArticleGoogle Scholar
- Wajchenberg BL (2000) Subcutaneous and visceral adipose tissue: Their relation to the metabolic syndrome. Endocr Rev 21:697–738PubMedView ArticleGoogle Scholar
- Wang YW, Jones PJH (2004) Conjugated linoleic acid and obesity control: Efficacy and mechanisms. Int J Obes 28:941–955View ArticleGoogle Scholar
- Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante J (2003) Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest 112:1796–1808PubMedGoogle Scholar
- Wellen KE, Hotamisligil GS (2003) Obesity-induced inflammatory changes in adipose tissue. J Clin Invest 112:1785–1788PubMedGoogle Scholar
- Whigham LD, Watras AC, Schoeller DA (2007) Efficacy of conjugated linoleic acid for reducing fat mass: A meta-analysis in humans. Am J Clin Nutr 85:1203–1211PubMedGoogle Scholar