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1 From the Department of Clinical Nutrition, Food and Health Research Centre (PK, MK, and KSP), Department of Medicine (DEL and LN), Department of Computer Science (JK), and Department of Clinical Nutrition (TS, KS, LP, HMM, and MU), University of Kuopio, Kuopio, Finland, and VTT, Espoo, Finland (KSP)
2 PK and MK contributed equally to this work.
3 Supported by Fazer Bakeries Ltd, Vaasan & Vaasan Oy, the Technology Development Center of Finland, the Academy of Finland (no. 209445), the Sigrid Juselius Foundation, and the ABS graduate school.
4 Address reprint requests to M Kolehmainen, Department of Clinical Nutrition, Food and Health Research Centre, University of Kuopio, Finland. E-mail: marjukka.kolehmainen{at}uku.fi.
See corresponding editorial on page 1169.
ABSTRACT
Background: Diets rich in whole-grain cereals and foods with a low glycemic index may protect against type 2 diabetes, but the underlying molecular mechanisms are unknown.
Objective: The main objective was to test whether 2 different carbohydrate modifications—a rye-pasta diet characterized by a low postprandial insulin response and an oat-wheat-potato diet characterized by a high postprandial insulin response—affect gene expression in subcutaneous adipose tissue (SAT) in persons with the metabolic syndrome.
Design: We assessed the effect of carbohydrate modification on SAT gene expression in 47 subjects [24 men and 23 women with a mean (±SD) age of 55 ± 6 y] with the features of the metabolic syndrome in a parallel study design. The subjects had a mean (±SD) body mass index (kg/m2) of 32.1 ± 3.8 and a 2-h plasma glucose concentration of 8.0 ± 2.3 mmol/L. Adipose tissue biopsies were performed, and oral-glucose-tolerance tests and other biochemical measurements were conducted before and after the intervention.
Results: We detected 71 down-regulated genes in the rye-pasta group, including genes linked to insulin signaling and apoptosis. In contrast, the 12-wk oat-wheat-potato diet up-regulated 62 genes related to stress, cytokine-chemokine–mediated immunity, and the interleukin pathway. The insulinogenic index improved after the rye-pasta diet (P = 0.004) but not after the oat-wheat-potato diet. Body weight was unchanged in both groups.
Conclusions: Dietary carbohydrate modification with rye and pasta or oat, wheat, and potato differentially modulates the gene expression profile in abdominal subcutaneous adipose tissue, even in the absence of weight loss.
Key Words: Gene-nutrient interactions • metabolic syndrome • insulin resistance • microarray • adipose tissue • diet intervention • insulinemic response • rye • oat • wheat
INTRODUCTION
The pathogenesis of the metabolic syndrome is not well understood, but lifestyle, including diet, and genetic factors clearly interact in its development and progression. These interactions are likely to be reflected in gene expression. The metabolic syndrome, characterized by central obesity, abnormal insulin and glucose metabolism, dyslipidemia, and hypertension, predisposes to cardiovascular diseases and especially type 2 diabetes (T2DM) (1-3).
Abdominal obesity and insulin resistance are the core features of the metabolic syndrome; associated abnormalities include inflammation, endothelial function, sex hormone metabolism, and cortisol metabolism (4-6). Impaired first-phase insulin secretion is also an inherent feature in those who have impaired fasting glycemia or impaired glucose tolerance and is a strong risk factor for progression to T2DM (7-9).
Epidemiologic evidence suggests that diets rich in whole-grain cereals and foods with a low glycemic index may protect against T2DM (10, 11). Moreover, dietary resistant starch may improve insulin sensitivity (12). Rye bread generates a lower postprandial insulin response than does wheat bread, even though the postprandial glucose response remains unchanged (13). This response is not due to the fiber content of the bread, but may be due to the bread structure (14). Hypothetically, repeated lower postprandial insulinemic responses may allow ß cell function to recover or decrease insulin resistance, which improves early insulin secretion over the long term (15). In line with this hypothesis, we found that high-fiber rye bread increased the acute insulin response, but insulin sensitivity remained unchanged (16). Furthermore, we recently showed that rye and pasta-based carbohydrate modification can enhance early insulin secretion in persons with the metabolic syndrome (17), although no changes in glucose tolerance or insulin resistance were observed. This effect was found to be independent of the fiber content of the diet.
Abdominal subcutaneous adipose tissue (SAT) produces a variety of secretory factors that have an important role in inflammation and insulin resistance via endocrine, paracrine, or autocrine signals (18, 19). Impaired insulin signaling occurs in adipocytes early in the development of insulin resistance, before overt glucose intolerance (20).
Gene expression profiling by microarrays is a valuable tool for finding new gene candidates and pathways in complex pathophysiological conditions and diseases such as the metabolic syndrome and T2DM. Microarrays have recently been applied to study changes in SAT gene expression occurring with caloric restriction and weight loss (21, 22). Microarray techniques have not been applied to human studies testing the effects of dietary interventions on gene expression in the absence of weight loss.
In this study, we examined the effects of 2 different carbohydrate modifications (low-insulin- and high-insulin-response diets) on gene expression in abdominal SAT and on glucose and insulin metabolism in persons with the metabolic syndrome. We hypothesized that the repeated lower postprandial insulin responses would be reflected to gene expression in SAT even in absence of weight loss.
SUBJECTS AND METHODS
Subjects
Fifty-three subjects were recruited to participate in the dietary intervention known as the Functional Genomics and Nutrition (FUNGENUT) Study. The study population is a subpopulation of a previously reported dietary intervention (17). At screening, the health status and medical history of the subjects were examined by an interview, clinical examination, and laboratory examinations (hemoglobin, lipid profile, insulin, glucose, and liver, kidney, and thyroid functions). The inclusion criteria were an age of 40–70 y, a body mass index (kg/m2) of 26–40, and 3 of the following 5 criteria for a diagnosis of the metabolic syndrome according to the National Cholesterol Education Program (23): impaired fasting glucose (6.1–6.9 mmol/L), waist circumference >102 cm (men) or >88 cm (women), triacylglycerol concentration >1.7 mmol/L, HDL-cholesterol concentration <1.0 mmol/L (men) or <1.2 mmol/L (women), and blood pressure >130 (systolic)/85 (diastolic) mm Hg or antihypertensive medication use. Persons were excluded if they had overt diabetes or were taking cholesterol-lowering, corticosteroid, analgesic, or anticoagulant medication. Forty-seven subjects (24 men and 23 women) entered the postintervention analyses. Twenty subjects were selected for the microarray analysis of gene expression in SAT (n = 10 per group). These subjects were selected because they had both pre- and postintervention samples that were, at most, only slightly contaminated by blood for the microarray analysis. The subjects gave written informed consent before participating in the study. The Ethics Committee of the University of Kuopio and Kuopio University Hospital approved the study. The study was carried out according to the Declaration of Helsinki.
Study design
The study design had 2 parallel groups and consisted of a 4-wk baseline period and a 12-wk test period. At the end of the baseline period, the subjects were randomly assigned according to sex, median age (cutoff: 57 y), and 2-h plasma glucose (cutoff: 7.35 mmol/L) to either a rye-pasta diet or to an oat-wheat-potato diet (Figure 1). The subjects replaced their normal breads and baked products with the test breads during the intervention. The aim was to cover >25% of the daily energy intake with the test breads.
FIGURE 1.. Flow diagram of the subjects’ progress through the phases of the study.
About 50% of the daily bread consumption in the oat-wheat-potato group was to be oat bread; similarly, 50% of the daily bread consumption in the rye-pasta group was to be endosperm rye bread. The aim was to achieve a similar fiber intake from the breads because the fiber content of these breads was almost equal (5.4 g fiber/100 g for the oat bread and 5.7 g fiber/100 g for the endosperm rye bread). The subjects in the rye-pasta group were given a package (400 g) of dark pasta or spaghetti 1 time/wk and were advised to use 1 portion of pasta (70 g dry pasta) 3 times/wk as part of warm dishes. The subjects in the oat-wheat-potato group were advised to use mainly potatoes as part of warm dishes and were given a package (210 g) of powdered mashed potatoes 1 time/wk. Otherwise, the diet was to remain unchanged.
The subjects were especially advised not to change the amount and type of fat and cold cuts eaten with the bread. Another goal of the dietary counseling was that the subject's weight should not change >5% from their baseline weight. Compliance with the diets was assessed with the daily records of bread use and with 4-d food records. The subjects kept daily records of the number of portions of test breads, potato, and pasta eaten and the quantity, quality, and frequency of other cereals that were eaten. Four-day food records, which included one weekend day, were kept by the subjects twice during weeks 4–8 as described previously (17).
The test breads for this study were chosen on the basis of the results of our previous postprandial studies with whole-meal breads. In those studies, we showed that rye bread and pasta consumption produced relatively lower postprandial insulin responses than did wheat bread consumption (14, 24). Additionally, a subpopulation (n = 19) of the study underwent 2 postprandial challenges with the test breads presented in this study, in random order, during the screening phase of the study (17). For the postprandial tests, the subjects received the test meal, which contained the test bread (50 g available carbohydrates), 40 g cucumber, and 3 dL of a no-calorie orange drink. A fasting blood sample and 8 blood samples after the start of eating (15, 30, 45, 60, 90, 120, 150, and 180 min) were taken for the measurement of plasma glucose and insulin. The maximal responses and areas under the curve (AUCs) for glucose and insulin were calculated.
The subjects underwent a clinical investigation at baseline and at the end of the intervention period, including an oral-glucose-tolerance test, measurement of blood pressure, waist circumference, body weight, height, and body composition. Fasting blood samples were drawn for the biochemical measurements. An adipose tissue biopsy for gene expression studies and the determination of adipocyte cell size was taken.
Biochemical analyses and anthropometric and body-composition measurements
Plasma glucose was analyzed by using the glucose dehydrogenase photometric method (Merck Diagnostica, Darmstadt, Germany) and KonePro Clinical Chemistry Analyser (Thermo Clinical Labsystems; Konelab, Vantaa, Finland). Serum insulin was analyzed by using the chemiluminescent immunoassay (ACS 180 Plus Automated Chemiluminescence System; Bayer Diagnostics, Tarrytown, NY). Body weight was measured on the same calibrated electronic scale throughout the study. Waist circumference was measured halfway between the lowest rib and the iliac crest. Body composition was measured by bioelectrical impedance (BIA 101S with BODYGRAM software; Akern Srl Bioresearch, Florence, Italy). We used the insulinogenic index as a measure of early insulin secretion. The insulinogenic index was determined by the increment in insulin during the first 30 min after oral glucose ingestion divided by the corresponding increment in glucose. The quantitative insulin sensitivity check index (QUICKI) was calculated as 1/(ln insulin concentration + ln glucose concentration) (25).
Adipose tissue biopsy
An adipose tissue biopsy (0.5–5 g) sample was collected as a needle biopsy from the superficial abdominal SAT lateral to the umbilicus under local anesthesia (10 mg Lidocain/mL; Orion Pharma, Espoo, Finland) and was washed twice with Gibco phosphate-buffered saline (Invitrogen, Carlsbad, CA). Biopsy samples were collected after a 12-h fast. Part of the samples was stored in RNAlater (Ambion, Austin, TX) at 4 °C for later RNA extraction. After 24 h, RNAlater was removed and the samples were stored at –80 °C until RNA extraction. Adipocyte cell size was determined from the same samples as follows. After being washed, the adipocytes were isolated in the presence of collagenase (0.5 mg/mL) under constant shaking at 2 Hz at 37 °C in buffer containing 125 mmol NaCl/L, 5 mmol KCl/L, 1 mmol CaCl2/L, 2.5 mmol MgCl2/L, 1 mmol KH2PO4/L, 4 mmol glucose/L, 2% bovine serum albumin, and 25 mmol Tris/L at pH 7.4 (26, 27). After 60 min, the cells were filtered through nylon cloth and washed 3 times with the same buffer without collagenase. Direct microscopic determination of the adipocyte diameter was performed by placing an aliquot of the cell suspension on the Bürker chamber and examining it with a light microscope (model CH-2; Olympus, Center valley, PA). The diameters of 100–200 cells were estimated, and the median of the diameters was used to calculate fat cell volume.
RNA extraction
Total RNA obtained before and after the intervention from adipose tissue of each subject was extracted initially with Trizol (Invitrogen) followed by further purification with RNeasy Mini-Kit (Qiagen, Valencia, CA). RNA isolation and purification were performed according to the manufacturer's instructions (Invitrogen and Qiagen). RNA concentrations and the ratio of A260 to A280 were determined with the use of a NanoDrop-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE); the acceptable ratio of A260 to A280 was 1.9–2.1. Integrity of the RNA was assessed by using agarose gel electrophoresis. RNA samples from 10 subjects each from both the rye-pasta group and the oat-wheat-potato group were chosen for microarray analyses based on the purity of the tissue (avoidance of blood contamination) and RNA. One tissue sample was used for each microarray analysis.
cDNA synthesis and oligonucleotide microarrays
Synthesis of biotin-labeled complementary RNA (cRNA), hybridization to DNA microarrays (Affymetrix HG-U133 Plus 2.0 GeneChip) and detection of hybridized cRNA were performed as recommended by the manufacturer (Affymetrix Inc, Santa Clara, CA). Briefly, 2 µg total RNA was used to generate double-stranded cDNA by reverse transcription with the use of the One-Cycle cDNA Synthesis Kit (Affymetrix Inc). Labeled cRNA was prepared by using double-stranded cDNA as a template by in vitro transcription with the use of the IVT Kit (Affymetrix Inc). Biotinylated cRNA was fragmented and added to hybridization cocktail. Two hundred microliters of this cocktail was used for the hybridization of HG-U133 Plus 2.0 array (Affymetrix Inc) in a hybridization oven at 60 rpm at 45 °C for 16 h, which was followed by washings using the GeneChip Fluidics Station 400 (Affymetrix Inc). The arrays were stained with streptavidin-phycoerythrin (Molecular Probes, Eugene, OR), incubated with biotinylated anti-streptavidin immunoglobulin (Vector Laboratories, Burlington, Canada), and restained with streptavidin-phycoerythrin.
Microarray data extraction and analysis
The arrays were scanned with the HP GeneArray Scanner 3000 (Affymetrix Inc). Data were extracted from the scanned images and autoscaled to median intensity by using Affymetrix GeneChip Operating Software. Gene expression profiles were compared by using dChip (Internet: www.dchip.org), a package for the statistical analysis of microarray data in samples with a large number of replicates. Invariant set normalization was used to normalize arrays at the probe level (28). Model-based expression index signals were then calculated according to the PM/MM-difference model. After these steps, only genes that were present in >50% of the replicates in 1 of the 2 time points were selected for further analysis. To compare gene expression profiles between the 2 groups, we used the false discovery rate (FDR) to determine the significant changes in the genes using Significance Analysis of Microarrays (SAM) (29). We used 300 permutations to obtain the FDR value. An FDR of 0.18 ( = 0.7) in the rye-pasta group and of 0.24 ( = 0.6) in oat-wheat-potato group were used. The FDR is presented as a q value for each gene in the final list of significant genes. Genes were additionally defined as differentially expressed when a P value <0.05 was obtained by paired Student's t test. Further downstream analyses of gene annotations and pathways were conducted with PANTHER Classification System Version 6.0 (Internet: www.pantherdb.org) (30) and the Database for Annotation, Visualization and Integrated Discovery 2.1 (DAVID 2.1; Internet: http://david.abcc.ncifcrf.gov/) (31). In the PANTHER analysis, we compared our gene list with the Homo sapiens gene list of the National Center for Biotechnology Information using a paired t test (a P value <0.01 was considered significant in the biological processes, and a P value <0.05 was considered significant in the pathway analyses).
Real-time polymerase chain reaction
Real-time quantitative polymerase chain reaction (qPCR) was used to confirm the results obtained from oligonucleotide microarrays. For that purpose, 5 µg total RNA samples were used as a template for reverse transcriptase reactions to generate cDNA with the High Capacity cDNA Archive Kit according to the manufacturer's protocol (Applied Biosystems, Foster City, CA). qPCR was then performed with an ABI Prism 7500 real-time PCR system by using assays based on TaqMan chemistry (assay-by-design or assay-on-demand) and ABI Prism 7500 SDS software (Applied Biosystems). The endogenous control was chosen by using the Human Endogenous Control Kit (Applied Biosystems). Of the 11 possible candidates, cyclophilin A1 was chosen as the best candidate when cDNA pool constructed from isolated human adipose tissue RNA was used as a template. Each PCR consisted of 6 ng cDNA, 1X Assay Mix, and 1X TaqMan Universal PCR Master Mix with UNG (Applied Biosystems). qPCR data were collected during each extension phase of the PCR reaction by using ABI Prism 7500 SDS software. Threshold cycles were determined for each gene with the automated Ct option. For the standard curve, all samples were pooled to generate a representative cDNA for standard dilutions. A standard curve with 5 concentrations (0.17, 0.5, 2, 6, and 12 ng/µL) and calibrator (2 ng/µL) were used on every plate and for every gene. This standard curve was used to determine the relative quantity of cDNA in each sample by comparison by using methods described in the ABI Prism User Bulletin no. 2. Quantities on each plate were first corrected by the calibrator on the plate. Furthermore, the relative amount per plate was corrected with the corresponding values of endogenous control cyclophilin A1. Analyses for the relative quantity of specific genes before and after the intervention were analyzed in triplicate.
Statistical analysis
The data were analyzed with SPSS for WINDOWS 11.5 (SPPS Inc, Chicago, IL). Variables with skewed distributions by Shaphiro-Wilks test were normalized with logarithmic or reciprocal transformation. Untransformed values are reported as means ± SDs unless otherwise mentioned. A general linear model (GLM) for repeated measures was used to determine differences between the groups (the interaction of time and group) during the intervention with the corresponding baseline variable included in the analysis as a covariate. GLM for univariate analysis was used to assess the difference in the relative change during the intervention (calculated as the percentage change from baseline) of the insulinogenic index and QUICKI between the groups, with the baseline variable as a covariate. A paired-samples t test was used to examine changes in variables within each group.
RESULTS
Biochemical and clinical characteristics at baseline
The baseline characteristics of the 2 groups did not differ significantly, except for systolic blood pressure (P = 0.038; Table 1).
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TABLE 1. Clinical characteristics of the subjects at baseline1
Postprandial tests
In the postprandial challenge (n = 19), the insulin AUC and maximal insulin response to rye bread were lower than those to oat-wheat bread (P = 0.004 and P < 0.001, respectively). The glucose AUC (P = 0.31) and maximum glucose response (P = 0.46) did not differ significantly between the rye and oat-wheat bread portions.
Diet
Reported compliance with the diet was good. The portions of rye bread and oat-wheat bread consumed exceeded the minimum number recommended in the study (Table 2). During the intervention, carbohydrate, total fiber, and soluble and insoluble fiber intakes increased in the rye-pasta group; protein and soluble fiber intakes increased and the total fiber intake decreased in the oat-wheat-potato group (Table 2).
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TABLE 2. Daily energy and nutrient intakes in the rye-pasta and oat-wheat-potato groups at baseline and during the study and test bread intake during the study1
Oral-glucose-tolerance tests
There was a borderline significant difference (P = 0.055) in the insulinogenic index between the groups (Table 3). After the 12-wk intervention, we detected a significant improvement in the insulinogenic index (P = 0.004) in the rye-pasta group (Table 3). Moreover, the difference between groups in the relative percentage change in the insulinogenic index during the intervention was significant (P = 0.027). The insulinogenic index and the 30-min insulin concentration during the oral-glucose-tolerance test seemed to decrease during the intervention in the oat-wheat-potato group, but these changes were not significant (P = 0.151 and P = 0.160, respectively). Other biochemical and clinical characteristics did not change during the intervention.
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TABLE 3. Body weight, insulinogenic index, and quantitative insulin sensitivity check index (QUICKI) at the beginning (0 wk) and at the end (12 wk) of the intervention and plasma glucose concentrations in response to an oral-glucose-tolerance test at the beginning (0 wk) and at the end (12 wk) of the intervention1
Adipocyte cell size
Adipocyte cell size decreased by 21% in the rye-pasta group during the intervention (P = 0.011), but remained unchanged in the oat-wheat-potato group. The change in adipocyte size did not correlate with the gene expression of validated genes.
Gene expression profiles
Rye-pasta group
We detected a list of 71 genes (Table 4) using an FDR of 0.18 and a P value <0.05 as selection criteria. After the 12-wk rye-pasta diet, the expression of all genes was down-regulated modestly, ie, mean changes of 0.71- to 0.93-fold. The list included genes closely linked to the insulin signaling pathway, including insulin-like-growth-factor (IGF) binding protein-5 (IGFBP5; mean: 0.84; range: 0.71–1.02) and the insulin receptor (IR; mean: 0.73; range: 0.39–0.92). The gene expression for hormone-sensitive lipase (LIPE; mean: 0.85; range: 0.71–1.00) was also down-regulated. The Panther Classification System was used to detect clusters on the basis of gene ontology terms. We determined clusters for both biological processes and pathways. Clusters formed on the basis of biological processes included apoptosis (P = 0.009). Genes related to apoptosis were lectin, tumor necrosis factor receptor superfamily 1A, fragile X mental retardation, autosomal homolog, mitochondrial ribosomal protein S30, twist homolog 2, and secreted frizzled-related protein 1.
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TABLE 4. Differentially expressed genes after 12 wk of the rye-pasta diet (n = 10)
Oat-wheat-potato group
We detected a list of 62 genes (Table 5) using an FDR of 0.24 and a P value <0.05) as selection criteria. Interestingly, after the 12-wk oat-wheat-potato diet, we found results opposite to those of rye-pasta group and detected only up-regulation of gene expression, with the changes ranging from 1.07- to 1.93-fold. Surprisingly, 11 of the genes had a close link to stress response: serum glucocorticoid regulated kinase, map kinase interacting serine/threonine kinase 2, dual specificity phosphatase 6 (DUSP6), chemokine (C-C motif) ligand 18 (pulmonary and activation-regulated), heat shock 10-kDa protein 1 (chaperonin 10), heat shock 70-kDa protein 8, peroxiredoxin 6, thioredoxin domain-containing transcriptional intermediary factor 1, B cell linker, CD86 antigen, and zinc finger protein 443. Clusters formed on the basis of biological processes included protein phosphorylation (P = 0.006), cytokine- and chemokine-mediated immunity (P = 0.008), and protein modification (P = 0.009). Furthermore, clusters for pathways including the oxidative stress pathway (P = 0.005) and the interleukin pathway (P = 0.037) and inflammation mediated by the chemokine- and cytokine-signaling pathway (P = 0.059) were formed. Genes closely linked to oxidative stress were DUSP6 (mean: 1.32; range: 1.06–2.20) and MAP kinase interacting serine/threonine kinase 2 (MKNK2; mean: 1.15; range: 1.04–1.42).
View this table:
TABLE 5. Differentially expressed genes after 12 wk of the oat-wheat-potato diet (n = 10)
Real-time polymerase chain reaction validation
Microarray results with qPCR were validated for 7 genes. Four genes were selected to validate gene expression in the rye-pasta group and 3 genes in the oat-wheat-potato group. The genes encoding LIPE (0.88-fold change), growth arrest-specific 7 (GAS7; 0.93-fold change), IGFBP5 (0.86-fold change), and cyclin D2 (CCND2; 0.87-fold) were confirmed in the rye-pasta group. Genes encoding serum/glucocorticoid regulated kinase (SGK; 1.41-fold change), phospoinositide-3-kinase (PIK3C2B; 0.92-fold change), and solute carrier family 40 (SLC40A1; 1.36-fold change) were selected in the oat-wheat potato group. For 6 genes (LIPE, GAS7, IGFBP5, CCND2, SKG, and SLC40A1), the changes in gene expression were in accordance with microarray data. For one gene (PIK3C2B), the changes in expression from microarray findings were not confirmed by qPCR (Figure 2).
FIGURE 2.. Mean (±SEM) changes in gene expression in response to the rye-pasta and oat-wheat-potato diets determined by microarray () and quantitative polymerase chain reaction () analyses. n = 10 per group. Target genes are related to endogenous control cyclophilin A1. LIPE (hormone-sensitive lipase), GAS7 (growth arrest-specific 7), IGFBP5 (insulin-like growth factor binding protein 5), and CCND2 (cyclin D2) were confirmed in the rye-pasta group, and SGK (serum/glucocorticoid regulated kinase), PIK3C2B (phosphoinositide-3-kinase ß), and solute carrier family 40 (iron-regulated transporter), member 1 (SLC40A1) were confirmed in the oat-wheat-potato group. The change in expression of PIK3C2B found in the microarray analysis was not confirmed by quantitative polymerase chain reaction analyses.
DISCUSSION
In the present randomized parallel study, we found that a 12-wk carbohydrate modification of the diet differentially modulated gene expression in the abdominal SAT of men and women with the metabolic syndrome, even in the absence of changes in body weight and insulin sensitivity. General down-regulation of abdominal SAT gene expression was evident in the rye-pasta group, including the genes related to insulin signaling and apoptosis. In contrast, the oat-wheat-potato diet up-regulated genes related to stress, including inflammation and interleukin cytokines, oxidative stress, and heat shock proteins.
As we showed earlier in a larger sample of 72 subjects (17), the main clinical finding in this substudy was that long-term rye bread and pasta diets increased early insulin secretion as measured by the insulinogenic index. Deterioration of early insulin secretion is crucial in the progression from normal glucose tolerance to impaired glucose tolerance and further to T2DM. In this and previous studies (13, 14), rye bread has consistently induced lower postprandial insulin responses than wheat bread, even though the glycemic responses have been similar. The rye-pasta diet may improve early insulin secretion by decreasing the excess demands placed on the ß cells, which allows them to recover (15). Differences in fiber, fat, and protein contents do not explain the lower postprandial responses of insulin to rye bread (14) and do not seem to explain the differences in the change in insulin secretion between the rye-pasta and oat-wheat-potato groups during the intervention (17).
In the rye-pasta group, we detected changes in genes related to insulin signaling and apoptosis. The rye-pasta diet down-regulated IGFPB-5 gene expression. This protein modulates the effects of IGF-I and IGF-II, but its function in human fat tissue is unknown. However, the up-regulation of the closely related IGFBP-3 is known to induce insulin resistance in mouse adipocytes (32). Moreover, IGFBP-3 has been shown to be up-regulated in human omental adipose tissue of obese individuals (33). Thus, assuming that the mechanism of IGFBP-5 is similar to that of IGFBP-3, the down-regulation of IGFBP-5 seen in the present study might promote insulin sensitivity at the molecular level in SAT.
The rye-pasta diet down-regulated the gene encoding the insulin receptor. Selective knockout of the insulin receptor in the white adipose tissue of mice paradoxically improves lipid and glucose homeostasis (34), but such a knockout model may not be physiologically relevant for modest down-regulation brought about by carbohydrate modification. It has been proposed that the activation of the full cohort of insulin receptors is not required for normal insulin action; thus, the concept of "spare receptors" has been introduced (35). Repeatedly lower postprandial hyperinsulinemia (16) and lower postprandial nonesterified fatty acid concentrations could hypothetically contribute to the down-regulation of adipose tissue expression of the insulin receptor through decreased demand for receptor binding.
Down-regulation of the gene expressing LIPE in the rye-pasta group may occur as a consequence of the decrease in adipocyte cell size that we found with the rye-pasta diet. Some studies have reported a close association of adipocyte cell size with LIPE mRNA expression (36) and hormone-sensitive lipase concentration and activity (37). Thus, the decrease in cell size in the rye-pasta group could contribute to down-regulation of LIPE mRNA expression. Hormone-sensitive lipase is the rate-limiting enzyme of lipolysis, which is a hallmark of insulin resistance in adipose tissue. Therefore, down-regulation of LIPE and decreased adipocyte cell size suggest decreased lipolysis and enhanced insulin sensitivity in SAT after the rye-pasta diet (38). In this study, however, we did not find a significant correlation between LIPE gene expression and adipocyte cell size.
Interestingly, the 12-wk oat-wheat-potato diet seemed to especially activate genes responding to stress. The oxidative stress pathway, interleukin pathway, and inflammation mediated by the chemokine and cytokine signaling pathway were also activated. Moreover, the present data suggest that the oat-wheat-potato diet, which induced repeated high insulin responses, can provoke alterations in immune status and inflammation. It is well established that adipose tissue has a role in inflammation (39). Cross-sectional epidemiologic data suggest that whole grains and a low-glycemic-index diet may reduce systemic inflammation in women with T2DM (40). Up-regulation of gene expression for serum and glucocorticoid-regulated kinase suggests activation of the glucocorticoid axis, which can occur in response to various stress stimuli (cytokines, aldosterone, growth factors, oxidative stress, heat shock protein activation, and glucocorticoids) (41). Activation of the pituitary-adrenal glucocorticoid axis may be involved in the pathogenesis of the metabolic syndrome (42).
Enhanced gene expression for heat shock 10-kDa protein 1 and heat shock 70-kDa protein 8 indicate a reaction in response to any of a number of stresses, including oxidative stress and inflammation (43). Increased MAP kinase interacting serine/threonine kinase 2 gene expressions suggests activation of MAP kinases, which can be activated by heat shock proteins, inflammatory cytokines, oxidative stress, altered redox status, and other stresses. MAP kinase activation also contributes to the inflammatory response and oxidative stress and may play an important role in signal transduction (44).
The mechanisms by which the oat-wheat-potato diet induces gene expression of numerous manifestations of metabolic and oxidative stress and immune activation are unclear. One explanation could be the repeated mild postprandial hypoglycemia that follows the initial hyperglycemia induced by carbohydrates with a high-glycemic or insulinemic index (15). We also found that ingestion of wheat bread is followed by initial hyperinsulinemia and a subsequent transient drop in glycemia below fasting levels, which was not seen after the rye bread meals (14). Hypoglycemia results in activation of counterregulatory stress hormones such as cortisol, glucagons, and catecholamines, which restores its consequent restoration of fasting glucose concentrations and increased nonesterified fatty acid concentrations (15).
In this particular study, we used both P values (dChip) and FDR (SAM with 300 permutations) to interpreted the microarray data. We used q values for each individual gene rather than fold change thresholds; q values represent the FDR of each gene. Currently, there is no gold standard for microarray data analysis (45). However, the methods used in the present study are well established and are used widely elsewhere (21, 46). Real-time PCR was used to confirm selected results from the changes in gene expression found in the microarray analyses. In this study, changes in gene expression were moderate, but occurred even in the absence of weight loss. On the basis of findings from medium-term interventions of moderate weight loss in humans, dramatic changes would not be expected (21, 22).
It is possible that the changes in SAT gene expression might have indirectly influenced insulin secretion in the pancreas, but the mechanisms are unclear. It is unlikely that differences in intakes of protein, saturated fat, carbohydrate, and fiber in the rye-pasta and wheat-oat-potato groups differentially affected early insulin secretion (17). It is nonetheless possible that differences in macronutrient and micronutrient intakes contributed to the different patterns of changes in gene expression.
In conclusion, 2 dietary carbohydrate modifications differentially modulated the gene expression profile of mRNA expression in human SAT. Genes regulating insulin signaling and apoptosis were down-regulated during the rye-pasta diet, and genes related mainly to metabolic stress were up-regulated during the oat-wheat-potato diet. The changes in gene expression suggest that over the long term, such carbohydrate modifications may influence the risk of cardiovascular disease and T2DM, even in the absence of weight loss.
ACKNOWLEDGMENTS
We thank the staff of VTT Biotechnology for the development of the study breads and the staff of the Department of Clinical Nutrition, University of Kuopio, for their valuable contributions to the present study.
The authors’ responsibilities were as follows—MK, DEL, LN, HMM, and KSP: study design; DEL, KS, PK, MK, and TS: adipose tissue biopsy collection; PK and TS: practical aspects of the study, including RNA isolation and microarray work; PK, MK, and JK: bioinformatics from the gene expression data; PK and MK: statistical analyses; PK, MK, and DEL: first draft of the manuscript; MU and LP: critical revision of the manuscript. All authors: final manuscript preparation. None of the authors had any conflicts of interest.
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