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Am J Clin Nutr 89: 407-415, 2009. First published December 3, 2008; doi:10.3945/ajcn.2008.25970
 American Journal of Clinical Nutrition, doi:10.3945/ajcn.2008.25970
Vol. 89, No. 1, 407-415, January 2009
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© 2009 American Society for Clinical Nutrition

ORIGINAL RESEARCH COMMUNICATION

Changes in the transcriptome of abdominal subcutaneous adipose tissue in response to short-term overfeeding in lean and obese men1,2,3

Jennifer Shea, Curtis R French, Jessica Bishop, Glynn Martin, Barbara Roebothan, David Pace, Donald Fitzpatrick and Guang Sun

1 From the Discipline of Genetics (JS, JB, GM, and GS), Divisions of Community Health (BR) and Medicine (DP and DF), Faculty of Medicine, Memorial University of Newfoundland, St John's, Canada, and the Department of Biological Sciences, University of Alberta, Edmonton, Canada (CRF).

2 Supported by grant MOP-62858 from the Canadian Institutes for Health Research (to GS), the Canada Foundation for Innovation, and Novartis Pharmaceuticals (to GS).

3 Reprints not available. Address correspondence to G Sun, 300 Prince Philip Drive, St John's, NL, Canada A1B 3V6. E-mail: gsun{at}mun.ca.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Obesity is caused by the excessive accumulation of adipose tissue as a result of a chronic energy surplus. Little is known regarding the molecular mechanisms involved in the response to an energy surplus in human adipose tissue at the genomic level.

Objective: The objective was to investigate changes in the transcriptome of abdominal subcutaneous adipose tissue after a positive energy challenge induced by overfeeding in both lean and obese subjects to identify novel obesity candidate genes.

Design: A total of 26 men were recruited and classified on the basis of percentage body fat (measured by dual-energy X-ray absorptiometry) as lean (<20%) or obese (>25%) to participate in the baseline comparison. Sixteen men participated in the overfeeding study (8 lean and 8 obese). Adipose tissue biopsy samples were collected from all subjects at the subumbilical region. Global gene expression profiles were determined at baseline and after a 7-d hypercaloric diet at 40% above normal energy requirements by using whole human genome DNA microarrays.

Results: Overfeeding induced differential expression in 45 genes. Six genes displayed a significant interaction effect between adiposity status and overfeeding treatment, including transferrin (TF), stearoyl-CoA desaturase (SCD), transaldolase 1 (TALDO1), cathepsin C (CTSC), insulin receptor substrate 2 (IRS2), and pyruvate dehydrogenase kinase, isozyme 4 (PDK4). Overfeeding resulted in changes in expression of these genes in lean subjects, whereas no significant changes were evident in obese subjects.

Conclusions: Differential expression of these 6 genes may represent a protective mechanism at the molecular level in lean subjects in response to an energy surplus. These genes represent valuable candidates for downstream studies related to obesity.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Obesity can be defined as the excessive accumulation of adipose tissue caused by a chronic energy imbalance between energy intake and energy expenditure (1). Obesity rates among developed countries have increased substantially in the past 3 decades and are now affecting billions globally. The consequences of excess body weight are numerous and include type 2 diabetes, hypertension, coronary artery disease, and many types of cancer (2). Increases in calorie intake combined with decreases in physical activity levels and an underlying genetic predisposition all contribute to the obesity epidemic. Current research indicates that many genes play a role in the development of obesity. As of October 2005, >600 genes, markers, and chromosomal regions have been associated with obesity phenotypes (3). Estimates of the heritability of body mass index (BMI), a marker of obesity, are between 30% and 70% (4–7). However, the underlying molecular and genetic bases surrounding this phenomenon is still unclear.

Aside from its role in storage, adipose tissue actively communicates with cells, tissues, and the central nervous system through a network of endocrine, paracrine, and autocrine signals. The discovery of numerous adipocyte-derived hormones has demonstrated an active role of this tissue in the development of obesity and related metabolic disorders (8–10). With the recent advent of microarrays, researchers have been able to examine the global gene expression profiles of adipose tissue to investigate its role in obesity. Microarray profiling of adipose tissue in numerous populations has led to the discovery of many processes that are now thought to be involved in the pathogenesis of this disease, including lipolysis (11), inflammation/immune response (12–14), apoptosis (15, 16), adipogenesis (17), and extracellular matrix constituents (18). Moreover, the use of microarray technology has led to the discovery of adipokines, which have been implicated in the pathogenesis of obesity (8, 19). However, most of these studies were cross-sectional in nature and performed comparisons between lean and obese individuals or between subcutaneous and visceral adipose tissue.

Energy homeostasis is a key factor in the regulation of body weight and subsequently obesity; therefore, study of the effects of changes in energy balance may provide further insight into the underlying genetic and molecular mechanisms responsible for obesity. Many studies have identified genes modulated by a negative energy balance, induced by exercise (20–22) or calorie restriction (23, 24). Surprisingly, critical data are lacking regarding changes in gene expression under conditions of a positive energy balance, which is the fundamental cause of the rising prevalence of human obesity. In the current study, we investigated changes in global gene expression profiles in abdominal subcutaneous adipose tissue in response to a positive energy balance induced by overfeeding. Overfeeding studies provide a means to investigate genetic and biochemical changes as well as individual differences that would be evident with extended overeating. Previous studies have shown that changes in nutritional status, such as overfeeding, can have major effects on adipose tissue metabolism (25), gene expression (26), and adipocytokine regulation (27). The objectives of the current study were to 1) define mRNA expression profiles of abdominal subcutaneous adipose tissue in lean and obese men at baseline and identify any differences between the 2, and 2) identify genes that are induced and/or suppressed in response to a positive energy challenge to provide novel obesity candidate genes for the study of human obesity.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Subjects were recruited from an ongoing overfeeding study investigating the effects of a positive energy balance on endocrine factors and glucose and lipid metabolism (27, 28). A total of 65 subjects participated in the previous study. A subset of these subjects agreed to undergo an adipose tissue biopsy for the current microarray study. Twenty-six subjects participated in the baseline study (13 lean and 13 obese); of these, 16 (8 lean and 8 obese) agreed to take part in the overfeeding intervention. All subjects were from the city of St John's and surrounding area in the Canadian province of Newfoundland and Labrador. Inclusion criteria were as follows: 1) male; 2) 19–29 y of age; 3) at least a third generation Newfoundlander; 4) healthy with no serious metabolic, cardiovascular, or endocrine disease; 5) no use of medication for lipid metabolism; and 6) stable weight (± 2.5 kg) in the previous 6 mo. All subjects provided written informed consent, and the Research Ethics Board of the Faculty of Medicine, Memorial University of Newfoundland, approved the study.

Study design
This study used a longitudinal design. All measurements, blood samplings, and adipose tissue samplings were performed twice: before the 1-wk overfeeding protocol began and the day after the week of overfeeding (day 8).

Overfeeding protocol
Full details of the overfeeding protocol were previously described by us (27, 28). Briefly, subjects consumed 40% more calories than their normal energy requirements, and this consisted of 15% protein, 35% fat, and 50% carbohydrates to mimic the common daily diet in North America. Baseline energy intake assessments were completed for each subject before the overfeeding protocol began. Baseline energy requirements were estimated for each subject with the use of three 24-h food recalls and a 30-d dietary inventory. Subjects were then started on a 40% hypercaloric diet for 7 d. Subjects were offered 3 meals/d, and energy values and macronutrient contents of the food were measured by using Food Processor SQL software (version 9.5.0.0; ESHA Research, Salem, OR). Subjects were asked to maintain their usual pattern of physical activity. Total energy expenditure was estimated with an Actical physical activity level monitor (Mini Mitter Co, Inc, Bend, OR) for 7 d before the study began and during the overfeeding period. Any differences in physical activity levels between baseline and the overfeeding period were controlled below 15%.

Measurement of body composition
Total percentage body fat (%BF) and percentage trunk fat (%TF) were measured by using dual-energy X-ray absorptiometry (Lunar Prodigy; GE Medical Systems, Madison, WI). Measurements were performed after the removal of all metal accessories, while lying in a supine position as previously described (29). Software version 4.0 was used for the analysis. All measurements were completed before and 1 d after the overfeeding protocol.

Serum measurements
Blood samples were taken from all subjects before and after completion of the overfeeding period, after 12 h of fasting. Serum was stored at –80°C for subsequent analyses. Serum insulin concentrations were measured with an Immulite immunoassay analyzer (DPC, Los Angeles, CA). The homeostasis model assessment (HOMA) was used as a measure of insulin resistance [HOMA-IR = insulin (µU/mL) x glucose (mmol/L)/22.5)] and β cell function [HOMA-β = 20 x insulin (µU/mL)/(glucose – 3.5)] (30). Serum concentrations of glucose, total cholesterol, HDL cholesterol, and triacylglycerols were measured by using Synchron reagents on an Lx20 analyzer (Beckman Coulter Inc, Fullerton, CA). LDL cholesterol was calculated according to the following formula: (total cholesterol) – (HDL cholesterol) – (triacylglycerols/2.2), which is reliable in the absence of severe hyperlipidemia. A detailed description of all serum measurements can be found in our previous articles (27–29, 31).

Adipose tissue biopsy and RNA isolation
Subcutaneous adipose tissue samples were obtained after a 12-h fast, before and 1 d after overfeeding. Adipose tissue was removed from the subumbilical region with use of a local anesthetic composed of 10 mL lidocaine in dilute bupivacaine (40 mL of 0.25% bupivacaine in 250 mL normal saline). Approximately 1–2 g subcutaneous adipose tissue was removed and immediately flash frozen in liquid nitrogen and subsequently stored in liquid nitrogen until further analysis. Total RNA was isolated from {approx}500 mg adipose tissue by using an RNeasy lipid tissue midi kit (Qiagen, CA). RNA concentration and purity were determined spectrophotometrically (Eppendorf, Hamburg, Germany), and integrity was assessed on a 2100 bioanalyzer by electrophoresis on an agarose gel (Agilent Technologies, Santa Clara, CA). All samples had a ratio of {approx}2:1 of 28S to 18S RNA.

Microarrays
Total RNA from the adipose tissue samples was amplified by using a low input linear amplification kit (Agilent Technologies), based on the T7 linear amplification system, which has been validated for use in microarray experiments (32). In separate parallel reactions, each amplified sample was labeled with either cyanine 3 (Cy3) or cyanine 5 (Cy5) (Perkin Elmer, MA). Concurrently, amplified reference RNA (Stratagene, CA) was also labeled with Cy3 or Cy5. Samples were then purified with an RNeasy mini elute kit (Qiagen). Hybridization of amplified, labeled RNA samples was accomplished by using Agilent's in situ hybridization kit. Each Cy3- or Cy5-labeled sample was competitively hybridized, with a Cy5- or Cy3-labeled universal human reference RNA, to Agilent's 44K whole human genome chip. Reverse hybridization (dye swap) was performed to account for differences in signal strength between Cy3 and Cy5. Arrays were hybridized at 60°C for 17.5 h All arrays were scanned with the ScanArray Express (Perkin Elmer) and then quantified by using Imagene software (version 5.6; Biodiscovery Inc, CA).

RT-PCR validation
We chose to validate the expression of 6 genes from our microarray data: transferrin (TF), stearoyl-CoA desaturase (SCD), transaldolase 1 (TALDO1), cathepsin C (CTSC), insulin receptor substrate 2 (IRS2), and pyruvate dehydrogenase kinase, isozyme 4 (PDK4). These genes were identified as being significantly differentially expressed between lean and obese subjects in response to the overfeeding intervention. Total RNA was extracted from adipose tissue samples as described above. Reverse transcription was performed with 300 ng total RNA from each sample, and 100 ng cDNA was used as a template for real-time polymerase chain reaction (RT-PCR) as recommended by the manufacturer (Applied Biosystems, Foster City, CA). β2-Microglobulin (B2M) was used as an endogenous control to normalize gene expression (Applied Biosystems). PCR was performed on an ABI PRISM 7000 Sequence Detection System (Applied Biosystems) using a TaqMan Universal PCR Master Mix and TaqMan Gene Expression Assays (Applied Biosystems), which contain a mixture of forward and reverse primers as well as a specific TaqMan probe. Each probe was labeled at the 5' end with the reporter dye FAM(6-carboxy-fluorescein) and at the 3' end with the quencher 6-minor groove binder. Each reaction contained 100 ng cDNA, PCR Master Mix, 900 nmol/L of each primer, and 250 nmol/L of TaqMan probe in a final volume of 20 µL. Thermal cycling conditions were as follows: 50°C for 2 min, 95°C for 10 min, 40 cycles of 95°C for 15 s, and 60°C for 1 min.

All samples were measured in triplicate, and a negative control was included. The comparative CT method was used to calculate mean fold change. The comparative CT method is similar to the standard curve method, except that it uses the formula 2–{Delta}{Delta}Ct to achieve the same result for relative quantification. The CT method also eliminates the need for a standard curve, thereby giving higher throughput and also reducing the adverse effect of any dilution errors made when creating the standard curve. In order for the comparative CT method to be valid, there must be no major difference in amplification efficiencies of the target and endogenous control. We tested the amplification efficiency for each of the probes and endogenous control and found them to be approximately equal.

Data analysis
Physical characteristics of subjects are presented as means ± SEs. Before the statistical analyses were performed, subjects were grouped according to adiposity status. Subjects were classified on the basis of %BF criteria as lean (<20%) or obese (>25%) according to criteria recommended by Bray (33). Differences in physical and biochemical variables between the 2 groups at baseline (before overfeeding) and in response to overfeeding were assessed by using the General Linear Model procedure for repeated measures. SPSS version 15.0 (SPSS Inc, Chicago, IL) was used for all analyses. Statistical analyses were 2-sided, and a P value < 0.05 was considered to be statistically significant.

The raw microarray data obtained were analyzed by using GeneSifter (http://www.genesifter.net/web/), which has been used in the analyses of microarray data (34–36). The analysis was performed on 2 levels: 1) identification of genes that were significantly up- or down-regulated between lean and obese subjects at baseline (before the overfeeding intervention) was performed by using Student's t test (n = 26), and 2) identification of genes that were significantly differentially expressed because of the overfeeding intervention or adiposity status (lean compared with obese) or genes that were significant because of an interaction effect between the 2 was conducted by using 2-factor ANOVA (n = 16).

GeneSifter establishes the biological significance based on both the Gene Ontology Consortium and the Kyoto Encyclopedia of Genes and Genomes (KEGG) public pathway. A z score report was used to analyze the biological process ontologies and KEGG pathway terms associated with the differentially expressed genes. The z score was derived by dividing the difference between the observed number of genes meeting a specific Gene Ontology term and the expected number of genes, based on the total number of genes in the array. A positive z score indicates that more genes than expected fulfilled the criteria in a certain group or pathway; therefore, that group or pathway is likely to be affected by the treatment. The parameters used in the analyses were as follows: threshold = 1.5 and log transformation. A threshold set at 1.5 indicates the minimum fold change required to be deemed significantly differentially expressed (compared with the selected control sample; in our case, lean subjects before overfeeding). Although the chosen threshold has no statistical significance, it was chosen with the assumption that a larger fold change increases the likelihood of that gene having a significant biological effect. Data were transformed to a logarithmic scale to ensure a normal distribution of data on all arrays. The Benjamini and Hochberg (37, 38) false discovery rate method was used for the correction of multiple testing. This method controls the expected proportion of falsely rejected hypotheses and is the recommended false discovery rate procedure for microarray data.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Analyses of physical and biochemical variables at baseline and in response to a 7-d overfeeding protocol
Physical and biochemical characteristics of subjects at baseline are shown in Table 1. There were no significant differences in age and height between the 2 groups; however, weight, BMI, %BF, and %TF were all significantly higher in obese subjects. Total body fat (kg) and total trunk fat (kg) were also significantly higher in obese subjects. Obese subjects had higher fasting serum insulin concentrations and higher insulin resistance and β cell function. Changes in physical and biochemical characteristics in response to overfeeding are also shown in Table 1. After the overfeeding intervention, weight, BMI, and total body fat (kg) were significantly higher in subjects. Triacylglycerols were also significantly increased in subjects in response to the hypercaloric diet. There were no significant between-subject interactions.


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  		TABLE 1. Physical and biochemical characteristics of subjects at baseline and in response to 7 d of overfeeding1

 
Identification of differentially expressed genes between lean and obese subjects at baseline (n = 26)
Using Student's t test with a threshold of 1.5, log transformation and P < 0.05 (corrected by Benjamini and Hochberg method), 385 genes were found to be differentially expressed in the adipose tissue of obese individuals compared with lean subjects (see Supplementary Table 1 under "Supplemental data" in the online issue). Of these, 158 were up-regulated and 227 were down-regulated in the adipose tissue of obese subjects compared with lean.

Identification of differentially expressed genes due to overfeeding (n = 16)
On the basis of a threshold of 1.5 and a 2-factor ANOVA where P < 0.05 (corrected by Benjamini and Hochberg method), a total of 45 genes were significantly differentially expressed as a result of the overfeeding intervention (Table 2), whereas 398 were significant due to adiposity status. Numerous studies have investigated differences in global gene expression between lean and obese individuals; therefore, we decided to focus on the 45 genes significantly affected by the overfeeding intervention. Most genes affected by the dietary intervention were up-regulated in response to overfeeding in both lean and obese subjects; however, 7 genes were down-regulated in response to the hypercaloric diet. These genes were as follows: zinc finger, HIT type 3 (ZNHIT3), CD44 molecule (Indian blood group) (CD44), met proto-oncogene (hepatocyte growth factor receptor) (MET), cyclin-dependent kinase inhibitor 1C (CDKN1C), solute carrier family 19 (thiamine transporter), member 2 (SLC19A2), cathepsin C (CTSC), and PDK4.


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  		TABLE 2. Differentially expressed genes in subcutaneous adipose tissue in lean (n = 8) and obese (n = 8) subjects in response to a 40% hypercaloric diet1

 
The unique design of our study allowed us to investigate possible genes that were differentially regulated between lean and obese subjects in response to overfeeding (an interaction effect). Six genes demonstrated significant adiposity status by overfeeding interaction (Table 3): TF, SCD, TALDO1, CTSC, IRS2, and PDK4. Expression of these 6 genes was verified by using RT-PCR and demonstrated similar expression trends compared with the microarray data. Expression of TF increased significantly in lean subjects after overfeeding; however, no significant change in expression levels was evident in obese subjects (Figure 1). SCD increased significantly in both lean and obese subjects; however, the increase in expression level was much more pronounced in lean subjects. TALDO1 increased significantly in lean subjects in response to the overfeeding intervention, whereas expression decreased slightly in obese subjects. Expression of CTSC decreased in lean subjects after overfeeding, whereas no change was evident in obese subjects. IRS2 and PDK4 decreased significantly in both lean and obese individuals after overfeeding; however, the change was more substantial in lean individuals.


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  		TABLE 3. Genes displaying a significant adiposity status in response to an overfeeding interaction effect1

 

Figure 1
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  		FIGURE 1. Mean (±SE) fold changes in a subset of genes selected for validation of microarray results with the use of real-time polymerase chain reaction in lean (n = 8) and obese (n = 8) men before and after overfeeding. A: TF, SCD, and TALDO1 increased in the lean subjects in response to the overfeeding intervention, whereas no significant changes were evident in the obese subjects. B: CTSC, IRS2, and PDK4 decreased in lean subjects in response to the overfeeding intervention, whereas no significant changes were evident in the obese subjects.

 
Significance of biological pathways represented in genes differentially regulated by overfeeding
KEGG pathways significantly affected by the overfeeding intervention are shown in Table 4. A z score report was generated displaying only those terms with a z-score >2.0. Genes involved in both carbohydrate and lipid metabolism were significantly affected by the overfeeding intervention. Specifically, pyruvate metabolism, glycolysis/gluconeogenesis, propanoate metabolism, and the pentose phosphate pathway all had a significant overrepresentation of genes after the overfeeding protocol. In terms of lipid metabolism, fatty acid elongation in the mitochondria and linoleic acid metabolism both had a z-score >2.0. Interestingly, oxidative phosphorylation and sulfur metabolism, 2 pathways involved in energy metabolism, also had significant z scores. Many other pathways involved in cell communication (gap junction), cell signaling (extracellular matrix–receptor interaction), and the endocrine system [peroxisome proliferator–activated receptor signaling pathway, and metabolism of cofactors and vitamins (vitamin B-6 metabolism, thiamine metabolism, and riboflavin metabolism)] were all significantly affected by the hypercaloric diet.


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  		TABLE 4. Effect of overfeeding on the expression of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways1

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Numerous studies have been conducted in recent years that examined differences in gene expression profiles of adipose tissue between lean and obese individuals. Others have performed site comparisons (subcutaneous compared with visceral adipose tissue), and few have investigated changes in gene expression in response to a negative energy balance created through an increase in energy expenditure (20–22) or through calorie restriction (23, 24). However, the major factor leading to obesity is an energy surplus, and there is currently no data available regarding changes in the transcriptome of adipose tissue during a positive energy balance in humans. We performed, for the first time, a study to comprehensively investigate the expression profiles of abdominal subcutaneous adipose tissue in response to an energy surplus induced through a short-term positive energy challenge using whole human genome microarray technology.

Physical and biochemical variables were compared between the current study and our previous overfeeding studies (27, 28). The variables measured for the lean subgroup of 8 subjects from the current study were statistically similar to those of the lean subjects (n = 37) from our previous study. The obese subgroup had a significantly higher BMI, weight, and %TF than did the overweight/obese subjects from the previous study (data not shown). In addition, glucose, insulin, and insulin resistance was elevated in obese subjects. In the present study, we were interested in investigating differences in gene expression between 2 extremes of the weight spectrum (lean compared with obese), whereas the total overfeeding cohort contains subjects spanning the entire weight spectrum (lean, normal weight, overweight, and obese); therefore, the results were not unexpected.

A major finding in our study was the identification of 45 genes that were differentially expressed in response to overfeeding. These genes are involved in a wide variety of biological processes known to be implicated in the development of obesity, including the immune response, lipid metabolism, and energy production. Many genes regulated by the overfeeding intervention were identified in previous studies as being differentially expressed in the adipose tissue of lean and obese individuals (14), in obese individuals after weight loss (18), and in diet-induced obese rats (39). These include genes involved in lipid metabolism (SCD, FADS1), glucose metabolism (IRS2, PDK4), cell adhesion processes (NID2, CD44, LAMB1), immune response (CTSC), and energy pathway/electron transport (ECHS1, NDUFB7). We have also identified novel genes not previously examined in the context of obesity that are regulated by a positive energy challenge. Their role in the development of human obesity and in individual differences in the predisposition to weight gain is a valuable issue to investigate.

It is known that there is a genetic basis for the predisposition to weight gain when exposed to a positive energy balance, such as the current situation in Western societies. However, as to how adiposity status may influence the genetic response to an energy surplus in human adipose tissue has not been studied. This is very important because the information obtained will provide insight into the genetic targets responsible for the interindividual differences in weight gain. An important finding in our study was the discovery of 6 genes whose expression levels were significantly affected by adiposity status during a positive energy challenge. These genes may represent the most promising targets for future obesity research.

SCD is an iron-containing enzyme involved in the metabolism of lipid, where it catalyzes a rate-limiting step in the synthesis of unsaturated fatty acids (40). The products of SCD are the most abundant fatty acids in triacylglycerols, cholesterol esters, and phospholipids. Aside from being components of lipids, unsaturated fatty acids also serve as mediators of signal transduction, cellular differentiation, and apoptosis (41–43); therefore, changes in SCD activity would be expected to have an effect on a variety of metabolic pathways, including those involved in obesity (44). Indeed, evidence indicates that high SCD activity favors fat storage and obesity. In a recent study, diet-induced obese rats had an increase in SCD expression of {approx}2-fold compared with that in lean animals (39). In our study, SCD gene expression was up-regulated in lean subjects in response to overfeeding; however, no significant change was evident in obese subjects. This finding differs from that previously shown in animal studies. The difference between lean and obese subjects may represent a clue regarding the genetic basis of the response to a positive energy challenge. Further studies are warranted to address its biological significance.

TALDO1 is involved in the metabolism of both energy and lipid, where it acts as a key enzyme in the nonoxidative pentose phosphate pathway. TF is involved in iron transport into cells by receptor-mediated endocytosis (45). There is currently little data available regarding the potential role of both these genes in energy homeostasis. The differential response of TALDO1 and TF in lean subjects compared with that in obese subjects after a positive energy challenge may indicate a role for these genes in the genetic proneness toward obesity.

It is now accepted that obesity represents an inflammatory state resulting from chronic activation of the innate immune system. CTSC is involved in the immune response, where it appears to be a central coordinator for activation of many serine proteinases in immune/inflammatory cells (46). Although little is known regarding the role that CTSC plays in the development of obesity, a protein with a similar function, cathepsin S, was recently identified as a novel marker of adiposity, specifically as a link between obesity and atherosclerosis (19). It is possible that CTSC acts in a similar manner. The differential expression of this gene requires further investigation to fully comprehend its role in the pathogenesis of obesity.

IRS2 encodes a cytoplasmic signaling molecule that mediates the effects of insulin and other cytokines (47). Numerous studies have shown a direct correlation between common variants in this gene and severe obesity (48) and type 2 diabetes (49). In our study, expression of IRS2 decreased in lean subjects after the hypercaloric diet, which may have contributed to the increase in insulin resistance evident in these individuals. No change was apparent in IRS2 expression in obese subjects after overfeeding and, similarly, no change in insulin resistance was apparent. The mechanism through which IRS2 acts in adipose tissue of lean subjects to in response to a hypercaloric diet, however, is still unclear.

PDK4 is a member of the pyruvate dehydrogenase kinase family, a group of enzymes that inhibit the pyruvate dehydrogenase complex (PDC) by phosphorylating one of its subunits (50). Activation of PDK4 results in metabolic switching of oxidative fuel use from glucose to fatty acids and occurs during times of starvation (51). Dietary intake of carbohydrate results in an increase in activity of the PDC in white and brown adipose tissues and liver of rats, likely through inhibition of PDK4 activity, to support fatty acid biosynthesis (52). In this manner, a decrease in PDK4 expression in lean subjects after overfeeding may lead to an increase in overall energy production, through activation of the PDC, to combat the excess in energy intake. This hypothesis is further supported by the fact that increases in expression of 2 key enzymes comprising the PDC (dihydrolipoamide S-acetyltransferase and pyruvate dehydrogenase alpha 1) were evident in lean subjects in response to overfeeding but not in obese subjects. This protective molecular mechanism appears to be blunted in obese subjects and necessitates further studies to understand the role of PDK4 in the genetic predisposition to weight gain.

The findings from our study highlight the importance of gene expression profiles obtained from specific tissues or organs essential for the development of obesity. Future studies are warranted to investigate expression profiles of other adipose tissue depots as well as skeletal muscle and liver under overfeeding conditions. Our study also reflects the necessity of investigating changes in the transcriptome under conditions similar to obesity, such as a positive energy balance.

In summary, we examined the transcriptome of abdominal subcutaneous adipose tissue under conditions of positive energy balance in human subjects. A total of 45 genes were identified as being significantly differentially expressed in response to overfeeding. We were also able to identify 6 genes that displayed a differential response to the overfeeding intervention between lean and obese subjects. Differential expression of these genes in lean subjects may represent a defense mechanism at the molecular level to protect the body against an energy surplus. This protective mechanism appears to be missing or blunted in obese subjects. Therefore, these genes are important targets to further investigate the role they play in the genetic predisposition for obesity.


   ACKNOWLEDGMENTS
 
We greatly appreciate the contributions of all the volunteers to the present study.

The authors' responsibilities were as follows—JS: assisted with the data collection and responsible for data the analysis and writing of the manuscript; CRF, GM, and JB: assisted with the data collection and editing of the manuscript; BR: provided guidance with the overfeeding protocol; DP and DF: performed all adipose tissue biopsy procedures; and GS: responsible for the study design and the revision of the manuscript. None of the authors had a personal or financial conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication February 8, 2008. Accepted for publication October 29, 2008.





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