Nutrition, Metabolism & Cardiovascular Diseases (2010) 20, 249e257

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Dietary carbohydrate modification altersserum metabolic profiles in individualswith the metabolic syndrome*

M. Lankinen a,b,*, U. Schwab b,c, P.V. Gopalacharyulu a, T. Seppanen-Laakso a, L. Yetukuri a, M. Sysi-Aho a, P. Kallio d, T. Suortti a,D.E. Laaksonen c,e, H. Gylling b,c, K. Poutanen a,d, M. Kolehmainen d,M. Oresi�c a

a VTT Technical Research Centre of Finland, Espoo, Finlandb Department of Clinical Nutrition, School of Public Health and Clinical Nutrition, University of Kuopio, Kuopio, Finlandc Institute of Clinical Medicine, Internal Medicine, Kuopio University Hospital, Kuopio, Finlandd Department of Clinical Nutrition, Food and Health Research Centre, School of Public Health and Clinical Nutrition,University of Kuopio, Kuopio, Finlande Institute of Biomedicine, Physiology, University of Kuopio, Kuopio, Finland

Received 16 September 2008; received in revised form 29 March 2009; accepted 1 April 2009

KEYWORDSMetabolic syndrome;Diet;Metabolomics;Lipidomics

Abbreviations: BCAA, branched chainlysoPC, lysophosphatidylcholine; MS,diabetes mellitus; UPLC, ultra-perform

* Sources of Support for research: ThCenter of Finland and the Academy o

* Corresponding author at: School of1627, FI-70211 Kuopio, Finland. Tel.:

E-mail address: Maria.Lankinen@u

0939-4753/$ - see front matter ª 200doi:10.1016/j.numecd.2009.04.009

Abstract Background and aims: Whole-grain cereals and diets with a low glycemic index mayprotect against the development of type 2 diabetes and heart disease, but the mechanisms arepoorly understood. We studied the effect of carbohydrate modification on serum metabolicprofiles, including lipids and branched chain amino acids, and dependencies between theseand specific gene expression pathways in adipose tissue.Methods and results: Twenty subjects with metabolic syndrome were selected from the largerFUNGENUT study population, randomized either to a diet high in oat and wheat bread andpotato (OWP) or rye bread and pasta (RP). Serum metabolomics analyses were performed usingultra-performance liquid chromatography coupled to electrospray ionization mass spectrom-etry (UPLC/MS), gas chromatography (GC) and UPLC.

amino acid; DHA, docosahexaenoic acid; ES, enrichment score; GSEA, gene set enrichment analysis;metabolic syndrome; OWP, oat and wheat bread and potato; RP, rye bread and pasta; T2D, type 2

ance liquid chromatography.is work was supported by Fazer bakeries Ltd, Vaasan & Vaasan oy, and the Technology Development

f Finland (no 117996 to MO, no 209445 to MK, no 210449 to HG), and the Sigrid Juselius Foundation.Public Health and Clinical Nutrition, Department of Clinical Nutrition, University of Kuopio, P.O. Boxþ358 400 985 527; fax: þ358 403 552 769.ku.fi (M. Lankinen).

9 Elsevier B.V. All rights reserved.

250 M. Lankinen et al.

In the OWP group multiple proinflammatory lysophosphatidylcholines increased, while in theRP group docosahexaenoic acid (DHA 22:6n-3) increased and isoleucine decreased. mRNAexpression of stress reactions- and adipose tissue differentiation-related genes were up-regu-lated in adipose tissue in the OWP group. In the RP group, however, pathways related to stressreactions and insulin signaling and energy metabolism were down-regulated. The lipid profileshad the strongest association with the changes in the adipose tissue differentiation pathwaywhen using the elastic net regression model of the lipidomic profiles on selected pathways.Conclusion: Our results suggest that the dietary carbohydrate modification alters the serummetabolic profile, especially in lysoPC species, and may, thus, contribute to proinflammatoryprocesses which in turn promote adverse changes in insulin and glucose metabolism.ª 2009 Elsevier B.V. All rights reserved.

Introduction

Diets rich in whole-grain may protect against the develop-ment of obesity, the metabolic syndrome (MS), type 2diabetes mellitus (T2D) and cardiovascular disease [1e3].The metabolic syndrome is characterized by abdominalobesity, abnormalities of insulin, glucose and lipid metab-olism and hypertension. The syndrome may progress to T2Dand cardiovascular disease [4,5]. The pathogenesis ofmetabolic syndrome is heterogeneous, but diet, physicalactivity and genetic factors interact in its development [4].

Whole-grain cereals and low glycemic index diets maymediate their effects through decreased insulin resistanceand lower postprandial insulinemic responses, which mayallow b-cell function to recover, thus improving insulinsecretion over the long term. Consumption of whole-grainsand cereal fiber has also been associated with lower levelsof inflammatory markers in some [6,7], but not all [8]studies.

We have shown previously that the rye bread and pastadiet enhances early insulin secretion in persons with theMS, although glucose tolerance or insulin resistance did notchange [2]. We have also found that dietary carbohydratemodification modulates the gene expression profile inabdominal subcutaneous adipose tissue by decreasing theexpression of genes regulating insulin signaling andapoptosis during the rye bread and pasta diet, and byincreasing the expression of genes related to metabolicstress and inflammatory and immune responses during theoat and wheat bread and potato diet [9]. The oat and wheatbread and potato diet also induced the proinflammatorychanges as measured by mRNA expression in adipose tissueand concentrations in serum of cytokines [10].

Hypothetically, both the improvement in early insulinsecretion and the increase in metabolic stress may bemediated by repeatedly lower postprandial insulinresponses to rye bread, and repeated decreases in plasmaglucose below fasting levels in the wheat and oat bread[10,11], respectively.

Serum patterns of metabolites reflect to some extentthe homeostasis of the organism. Metabolomics, a disci-pline dedicated to the global study of metabolites, maydeepen our knowledge of human health and the interactingand regulatory roles of nutrition [12,13]. For example,elevated serum branched chain amino acid (BCAA)concentrations have been associated with obesity andhyperinsulinemia [14]. Lipids also play a central role ininflammation and in the progression of glucose metabolism

towards diabetes [15]. Traditional clinical lipid measuresquantify total amounts of triacylglycerol, cholesterol, orlipoproteins. However, serum lipid profile is more complex.Current metabolomics platforms enable quantitative char-acterization of hundreds of diverse lipid molecules acrossmultiple lipid classes [16].

In this study our objective was to investigate the effectof dietary carbohydrate modification on serum metabolicprofiles, including lipids and BCAA, and to show the possibleinflammatory effect also at the level of lipid profile. Wealso aimed to study dependencies between serum metab-olites and specific gene expression pathways in adiposetissue to better understand the physiological importance ofdifferent lipids and metabolites in the context of dietaryinterventions.

Methods

Study population

Altogether 53 overweight or obese subjects with MS wererecruited to the FUNGENUT study. The inclusion criteriahave been described in detail earlier [9]. The FUNGENUTstudy was completed by 47 individuals. Those 20 subjectswhose adipose tissue samples were included for thegenome-wide transcriptomic analyses of adipose tissuebased on the availability of both pre- and post-interventionsamples and the purity of the samples were included in thepresent study. We also aimed to see if the transcriptomicand metabolomic information was complementary andassociated with each other.

All subjects volunteered to the study and gave theirwritten informed consent. The Ethics Committee of theHospital District of Northern Savo approved the study plan.The study complied with the Declaration of Helsinki.

Study design

The study design was reported in detail earlier [2,9]. Inbrief, the study consisted of a 4-week baseline period anda 12-week intervention period and there were two parallelgroups. The subjects were randomly assigned to an oat andwheat bread and potato (OWP) group and a rye bread andpasta (RP) group. The subjects replaced their customarilyused breads and baked products with the test breads.About 50% of the daily bread consumption in OWP group andRP group was to be oat bread and endosperm rye bread,

Diet carbohydrates and metabolic profile 251

respectively. The fiber content of the oat bread andendosperm rye bread was almost equal in order to achievesimilar fiber intake from breads. Nutrient composition ofthe test breads has been described earlier [2]. The subjectsin the RP group were advised to use at least one portion ofpasta at least three times a week, and in the OWP groupmainly potatoes as part of warm dishes. Otherwise, the dietwas to remain unchanged. Compliance with the diets andthe dietary intake was assessed with the daily records ofbread, potato, pasta and other cereal consumption andwith 4-days food records kept twice during the weeks 4 and8. Energy and nutrient intake was calculated using theMicroNutrica� software (version 2.5, Finnish Social Insur-ance Institute).

Blood samples after a 12-h overnight fast were drawn,body weight, waist circumference, systolic and diastolicblood pressures were measured and oral glucose tolerancetest and adipose tissue biopsy were performed at baselineand at the end of the intervention period.

Biochemical analyses

Serum total and HDL cholesterol and triglycerides weremeasured by enzymatic photometric methods withcommercial kits [Cholesterol CHOD-PAP (Roche Diagnostics,Mannheim, Germany) and Konelab HDL Cholesterol andKonelab Triacylglycerols (Thermo Clinical Labsystems Oy),respectively] and a Kone Pro Clinical Chemistry Analyzer(Thermo Clinical Labsystems Oy). LDL cholesterol wascalculated [17]. Plasma glucose was analyzed by theglucose dehydrogenase photometric method (Merck Diag-nostica, Darmstadt, Germany) and KonePro Clinical Chem-istry Analyser (Thermo Clinical Labsystems; Konelab,Vantaa, Finland). Serum insulin was analysed by thechemiluminescent immunoassay (ACS 180 Plus AutomatedChemiluminescence System: Bayer Diagnostics, Tarrytown,NY). The insulinogenic index as a measure of early insulinsecretion was calculated as the increase in serum insulinconcentration during the first 30 min after oral glucoseingestion divided by the corresponding increase in plasmaglucose concentration.

Metabolomic analyses

The fatty acid and lipidomic analyses were performed asdescribed earlier [18] with the exception of the followingchanges in procedures. In the fatty acid analysis the splitratio in injection was 1:13 instead of 1:20. In the lipidomicsanalysis serum samples were used and the amount ofinternal standard was 20 ml. The column was an AcquityUPLC�BEH C18 1 � 50 mm with 1.7 mm particles. Theinjection volume was 1.5 ml. Reserpine was used as the lockspray reference compound at a flow rate of 10 ml/min. Dataprocessing, lipids identification and the normalization wasperformed as described earlier [18,19]. BCAA analyses wereperformed as described [14].

Analysis of lipidomics and gene expression data

Multivariate statistical analyses were performed using Rstatistical language (http://www.r-project.org/). The

transcriptomic data (Affymetrix HG-U133 Plus 2.0 Gen-eChip) of subcutaneous abdominal adipose tissue were thesame as reported earlier [9]. Pathway analysis of the geneexpression data was performed using the gene set enrich-ment analysis (GSEA) method [20]. Clinically relevantpathways were selected from the significantly enrichedpathways (i.e., GSEA results) for further analysis. First,leading edge subset (the subset of genes that contributes tothe peak enrichment score [20]) of each pathway wasidentified and the corresponding gene expression sub-matrix was standardized (i.e., adjusted to zero mean andunit standard deviation). Second, PC1-summary, i.e., thefirst principal component [21] was extracted from theleading edge expression sub-matrix of each pathway. AsPC1-summary provides the best rank-one decomposition ofthe leading edge gene expression data-matrix, wedesignate it as the pathway profile. To capture thechange in pathway profiles we studied the differencesyij Z yij(t2) � yij(t1), where yij(t) is the pathway profile ofpathway i in person j prior (t Z t1) or after the treatment(t Z t2).

Associations between the gene expression pathways andthe lipid profiles were studied using the elastic netregression [22]. The cross-validation was performed byrandomly splitting the 20 subjects into a training set ofsize 16 and a test set of size 4. The splitting was randomlyperformed 100 times, and each time a regression modelwas build with the samples in the training data. Thatmodel was then used to predict the values in the test set.The squared differences between predictions and realmeasurements were summed and averaged over all therandom splits.

Further details on analyses of metabolomics and geneexpression data are available in the Supplement (Supple-ment link).

Statistical analyses

Biochemical data were statistically analyzed using the SPSSstatistical software (version 14.0, SPSS Inc., Chicago, IL)and R software version 2.4.1 [23]. The data are expressedas mean � SD. Fold changes for the lysophosphatidylcho-lines (LysoPC) were calculated dividing the endpoint valuesby the baseline values. The normality of distributions of thevariables was tested with the KolmogoroveSmirnov testwith Lillefor’s significance correction. The variables withabnormal distribution were normalized with logarithmictransformation. A non-parametric test was used if normaldistribution was not achieved with transformation. Pairedsamples t-test or Wilcoxon signed ranks test was used forcomparisons within the groups. For global lipidomics data,in order to correct for multiple comparisons, false discoveryrate (FDR) q-value was calculated [24], with significancethreshold set at recommended q < 0.25 [25]. Independentsamples t-test or ManneWhitney’s U-test was used forcomparisons between the groups. General linear model forrepeated measurements was used to determine differencesin dietary intake between the groups (the interaction oftime and group). Spearman rank correlation was used tocalculate correlation coefficients. P-values <0.05 wereconsidered significant.

252 M. Lankinen et al.

Results

Clinical characteristics and dietary intake

The clinical characteristics of this subset of subjects (n Z 20)did not differ significantly between the groups at baseline,except for insulinogenic index, which was significantly higher(P Z 0.013) in the OWP group than in the RP group (Table 1).Clinical measurements did not change significantly duringthe intervention in either the RP or the OWP group.

Of daily energy intake 37 and 27% was covered with testbreads in the OWP and RP groups, respectively. The aim was�25%. Average test bread consumption was eight portionsa day in both groups. Potatoes were consumed 4.5 timesand pasta 0.7 times a week in the OWP group. Therespective values for the RP group were 2.5 times and 3.2times a week.

The food record data indicated that dietary intake ofprotein changed significantly during intervention (P Z 0.001).It increased in the OWP group from 74to 90 g (P Z 0.021) anddecreased in the RP group from 95 to 86 g (P Z 0.025).Otherwise dietary intake of energy and nutrients did notchange. In theRPgroup,daily intakeofdietaryfiberwas26 gatbaseline and 27 g during the test period. In the OWP group, itwas 24 and 22 g, respectively.

Serum metabolome

A total of 278 lipids were identified and quantified by theUPLC/MS lipidomics platform. The major differencefollowing the OWP intervention was the increase ofmultiple lysoPC species (Fig. 1). When investigating within-group changes (after the intervention vs. baseline) in theRP group only the diminished diacylglycerol DG(40:1)passed the q < 0.25 threshold (Fold Z 0.7; P Z 0.002). Theother diacylglycerol detected, DG(36:1), was also dimin-ished after the intervention (Fold Z 0.6; P Z 0.01;q Z 0.253).

When analysing the serum fatty acid content, serumdocosahexaenoic acid content (DHA 22:6n-3) increased in

Table 1 Clinical characteristics of the subjects at baseline (me

Rye bread pasta group

n Z 10(3 females, 7 males)

Age (years) 56.0 � 6.0Body mass index (kg/m2) 32.5 � 4.9Waist circumference (cm) 112.4 � 13.1Systolic blood pressure (mmHg) 137.1 � 16.0Diastolic blood pressure (mmHg) 88.5 � 9.9Serum cholesterol (mmol/L) 5.9 � 1.0HDL cholesterol (mmol/L) 1.4 � 0.3LDL cholesterol (mmol/L) 3.5 � 0.9Serum triacylglycerol (mmol/L) 2.3 � 1.0Plasma glucose (mmol/L) 6.5 � 0.5Fasting serum insulin (pmol/L) 72.3 � 48.8Insulinogenic index 67.0 � 23.5

a Independent samples t-test.b Logarithmic values used in statistical tests due the non-normality.

the RP group (P Z 0.01). Changes in fatty acids wereotherwise not significant (Table 2). Serum linoleate contentwas significantly lower in the RP group compared with theOWP group both at baseline and after the intervention(P Z 0.010 and P Z 0.013, respectively).

Concentrations of the BCAA isoleucine decreased in theRP group (Table 2). In Spearman rank correlation analyses,the changes in valine and leucine correlated negativelywith the changes in fasting plasma glucose concentration inthe RP group (P Z 0.028 and P Z 0.039, respectively),although there were no significant changes in valine,leucine or fasting glucose concentration in the RP groupduring the intervention.

Adipose tissue pathways affected by dietarycarbohydrate modification

According to the GSEA, several gene sets related to stressreactions, adipose tissue differentiation and DNA damagesignaling were up-regulated in the OWP group (Table 3),whereas pathways related stress reactions, insulin signalingand energy metabolism were down-regulated in the RPgroup.

To investigate whether any of the pathway changesobserved in adipose tissue were reflected in the serumlipidome, we performed regression analysis of lipidomicsprofiles on selected pathways found affected by thecarbohydrate modification. The lipid profiles had thestrongest association with the changes in the adipose tissuedifferentiation pathway (Fig. 2). Several serum lipids,including the cholesteryl esters ChoE(22:6n-3) andChoE(20:4n-6), were inversely related to the pathwayexpression as calculated by the collective changes inpathway’s leading edge genes (which were determined byGSEA).

Discussion

We investigated the effects of a rye bread and pasta diet,characterized by a low postprandial insulin response, and

an � SD).

Oat and wheat bread and potato group P-valuea

n Z 10(6 females, 4 males)

57.1 � 6.1 0.731.0 � 4.0 0.5

104.9 � 7.6 0.1139.3 � 16.4 0.885.8 � 9.4 0.55.6 � 0.8 0.51.4 � 0.3 0.83.6 � 0.8 0.71.8 � 1.0 0.36.2 � 0.5 0.2

81.8 � 49.6 0.6b

123.2 � 60.1 0.013

Figure 1 Averages of fold changes for multiple lysoPCspecies, with 95% confidence interval in the OWP and RPgroups. The RP group is represented with gray bars and theOWP group with white bars. Multiple lysoPC species weresignificantly increased in the OWP group, whereas there wereno changes in the RP group. *, P < 0.05. P-values were calcu-lated using paired Wilcoxon test (differences within the groupsbefore and after intervention).

Table 2 Serum fatty acid (%) and branched chain amino acid (m

Rye bread and pasta group n

0-week 12-weeks

Fatty acidsMyristic acid (14:0) 1.53 � 0.44 1.38 � 0.55Myristoleic acid (14:1n-5) 0.16 � 0.07 0.15 � 0.07Palmitic acid (16:0) 28.42 � 1.2 28.57 � 2.00Palmitoleic acid (16:1n-7) 3.47 � 1.04 3.71 � 1.27Stearic acid (18:0) 8.48 � 1.21 8.37 � 1.35Oleic acid (18:1n-9) 24.40 � 3.66 23.20 � 3.20Cis-vaccenic acid (18:1n-7) 2.29 � 0.44 2.33 � 0.39Linoleic acid (18:2n-6) 16.3 � 2.31 15.94 � 3.12g-linolenic acid (18:3n-6) 0.39 � 0.16 0.36 � 0.10a-linolenic acid (18:3n-3) 1.00 � 0.31 0.90 � 0.24Homo-g-linolenic acid (20:3n-6) 1.87 � 0.70 1.91 � 0.56Arachidonic acid (20:4n-6) 5.81 � 1.82 6.04 � 1.82Eicosapentaenoic acid (20:5n-3) 1.56 � 0.57 2.06 � 1.10Dokosapentaenoic acid (22:5n-3) 0.91 � 0.15 1.00 � 0.15Dokosahexaenoic acid (22:6n-3) 3.43 � 0.78 4.08 � 1.29

Branced chain amino acidsValine 0.216 � 0.036 0.218 � 0.03Leucine 0.135 � 0.029 0.134 � 0.02Isoleucine 0.073 � 0 013 0.066 � 0.01

a Paired-samples t-test.b Logarithmic values used in statistical tests due the non-normality.c Wilcoxon signed ranks test used due to the abnormal distribution

Diet carbohydrates and metabolic profile 253

an oat and wheat bread and potato diet, characterized bya high postprandial insulin response, in individuals with theMS. We found that a 12-week dietary carbohydrate modi-fication altered the metabolic profiles.

The major difference resulting from the interventionwas the increase of multiple lysoPC species in the OWPgroup. LysoPC are reactive lipid by-products generated inthe hydrolysis of phosphatidylcholines by phospholipase A2[26]. Moreover, lysoPC has been found to be the majorbioactive lipid component of oxidized LDL and may beresponsible for many of the inflammatory effects ofoxidized LDL [26,27]. Previously these changes in lipidmetabolism have been associated with modification ofdietary fat intake [28], but interestingly we found that evena relatively small carbohydrate modification may changelipid profile. Strengthening this finding, the present findingsare complementary with our earlier results, suggestingactivation of pathways related to oxidative stress andinflammation in the OWP group [9], and with our results ofan increase in the adipose gene expression and serumconcentration of proinflammatory cytokines [10]. Theelevation of lysoPC in the OWP group and the absence ofsuch changes in the RP group suggest that the OWP dietinduce lipid peroxidation, whereas the RP diet has a neutraleffect. The explanation might be that traditionally bakedrye breads have higher content of fenolic compounds andantioxidants than wheat rolls [29]. In previous study intakeof whole-grain, in combination with other plant products,also decreased markers of lipid peroxidation [30].

Fatty acid analysis revealed an increase in serum DHAcontent in the RP group. Grain products do not containDHA, but the absolute amount of a-linolenic acid is higher

M) content before and after the intervention (means � SD).

Z 10 Oat-wheat bread and potato group n Z 10

P-valuea 0-week 12-weeks P-valuea

0.47 1.36 � 0.58 1.13 � 0.46 0.080.62 0.14 � 0.06 0.11 � 0.06 0.050.82 27.84 � 1.81 27.54 � 1.28 0.520.50b 2.76 � 0.63 2.72 � 0.65 0.760.82 8.70 � 0.82 8.94 � 1.09 0.260.08 22.90 � 2.01 22.77 � 1.85 0.810.85 2.25 � 0.34 2.23 � 0.25 0.760.62 19.14 � 2.90 19.45 � 2.59 0.640.52b 0.37 � 0.06 0.41 � 0.11 0.170.17 1.1 � 0.22 0.98 � 0.23 0.080.53 1.90 � 0.28 1.97 � 0.32 0.190.37 5.59 � 1.50 5.71 � 1.70 0.770.13b 1.54 � 0.56 1.51 � 0.64 0.810.12 0.92 � 0.21 0.97 � 0.23 0.570.01 3.51 � 1.01 3.58 � 1.05 0.84

7 0.860b 0.197 � 0.044 0.210 � 0.021 0.541c

7 0.823 0.130 � 0.012 0.132 � 0.012 0.4730 0.013 0.069 � 0.007 0.074 � 0.007 0.106

even after logarithmic transformation.

Table 3 Clinically relevant enriched pathways.

Name ofpathway

Size ofpathway

Rye bread and pasta group Oat-wheat bread and potato group Short description

Up/downregulated

NOMP-value

FDRq-value

Up/downregulated

NOMP-value

FDRq-value

PGC 26 Down 0.003 0.148 Up 0.017 0.130 PGC related genesSTRESS_ARSENIC_SPECIFIC_UP 19 Down 0.009 0.184 Up 0.003 0.043 Genes up-regulated 4 h following arsenic

treatmentINSULIN_SIGNALING 13 Down 0.011 0.183 e e e Genes related to insulin signalingST_P38_MAPK_PATHWAY 11 e e e Up 0.068 0.163 p38 is a MAP kinase regulated by cytokines and

cellular stressADIP_DIFF_CLUSTER1 11 e e e Up 0.007 0.055 Progressively down-regulated over 24 h during

differentiationof 3T3-L1 fibroblast into adipocytes

CELL_SURFACE_RECEPTOR_LINKED_SIGNAL_TRANSDUCTION

19 Up 0.003 0.058 e e e Any series of molecular signals initiated by thebinding of anextracellular ligand to a receptor on the surface ofthe target cell

ADIP_DIFF_CLUSTER2 10 e e e Up 0.068 0.171 Strongly up-regulated at 2 h during differentiationof 3T3-L1fibroblast into adipocytes

BASSO_GERMINAL_CENTER_CD40_DN 12 Up 0.010 0.135 Up 0.057 0.171 CD40 down-regulated genesPROLIFERATION_GENES 61 e e e Up 0.000 0.006 Proliferation related genesDNA_DAMAGE_SIGNALING 15 e e e Up 0.070 0.169 Genes involved in DNA damage signaling

NOM P-value, the uncorrected P-value. FDR q-value, false discovery rate and multiple testing correction (q-value). PGC, peroxisome proliferator-activated receptor-g (PPARg) coactivator.MAPK, mitogen-activated protein kinase. CD40, integral membrane protein of the tumor necrosis factor receptor (TNF-R) family.

254M

.La

nkin

en

et

al.

Figure 2 Associations between gene expression pathways and lipid profiles using the elastic net regression model. (A) The firstprincipal component, PC1, of a GE-pathway is predicted using an elasticnet regression model. The measured values correspond tothe actual values of PC1 and the predicted values refer to leave-one-out cross-validation predictions, i.e., each sample is predictedusing measurements only from the other samples. In an ideal case, all points should fall to the diagonal line. (B) Lipids related toAdipose tissue differentiation cluster 1-pathway. The error bars represent 95% confidence interval. Phosphatidylcholine (PC),phosphatidylethanolamine (PE), triacylglycerol (TAG), cholesterol ester (ChoE), lysophosphatidylcholine (lysoPC). (C) Adiposetissue differentiation cluster 1 leading edge genes.

Diet carbohydrates and metabolic profile 255

256 M. Lankinen et al.

in rye (78 mg/100 g) than in oat (53 mg/100 g) or wheat(61 mg/100 mg). Although serum a-linolenic acid concen-trations did not increase, it is possible that higher intake ofa-linolenic acid in the RP group was effectively convertedto DHA through endogenous desaturation and elongation[31]. Another explanation for the increase of DHA may beincreased dietary intake. However, the dietary intake ofDHA based on 4-day food records did not change. The mainsource of dietary DHA is fatty fish. It is possible that theconsumption of especially fatty fish was not estimatedreliably enough with the 4-day food records. To assess fattyacid composition of the diet reliably a 7-day food recordmay be needed [32].

Branched chain amino acid isoleucine decreased in theRP group. High serum BCAA concentrations have beenassociated with decreased BCAA catabolism and obesityand hyperinsulinemia, which suggests that BCAA maycontribute to insulin resistance [14]. Since grain productsare not the main source of dietary isoleucine, it is unlikelythat the carbohydrate modification of diet directly affecteddietary intake or plasma concentrations of isoleucine.Foods having overall higher protein content, such as meat,soy bean or milk products, contain substantially moreisoleucine than rye, oat or wheat. Daily protein intakedecreased in the RP group during the intervention, andprobably also the dietary intake of isoleucine decreased.Thus, other aspects than the intervention could have aneffect on this change.

To better understand the physiological importance ofobserved lipidomic profile changes we also examined thedependencies between lipids and specific gene expressionpathways in adipose tissue. The gene sets related to stressreaction, adipose tissue differentiation and DNA damagesignaling were up-regulated in the OWP group, whereaspathways related to stress reactions, insulin signaling andenergy metabolism were down-regulated in the RP group.These findings confirm and complement the results of ourearlier report [9]. Regression analysis showed that changesin the lipid profiles associate with changes in specific geneexpression pathways, e.g., decrease of serum cholesterylesters (ChoE(22:6) and ChoE(20:4)) associated with up-regulation of the adipose tissue differentiation pathway.Cellular cholesterol accumulation is necessary during adi-pogenesis, and the gene expression of cholesterol estertransfer protein (CETP) is induced early during the differ-entiation of adipocytes [33]. Accordingly, decrease of ChoEin serum may reflect their accumulation in the adiposetissue.

In both lipidomic and gene expression analyses, dietarycarbohydrate modification affected the molecular profilesof the OWP group more than the RP group. Consideringdietary habits in Finland especially within the age rangeand geographical area of this study, subjects in the RPgroup probably had to change their diet substantially lessthan subjects in the OWP group. Overall, approximately 85%of Finnish males and females include rye bread in theirdiet, and 25% of males and 22% of females use wheat bread[34]. However, consumption of potatoes is more commonthan consumption of pasta within this area and age group[34]. The consumption of potatoes and pasta nonethelessplayed a minor role in this study, because they comprisedless than 5% of total daily energy intake.

As a potential weakness of the study, the clinical char-acteristics of the two groups were not entirely similar atbaseline. The study population was a subgroup of a largerstudy [2], and thus balancing of the groups by sex did notoccur within the present subgroups. In the larger study,baseline early insulin secretion as measured by the insuli-nogenic index did not differ between groups at baseline,but improved in the RP group during the intervention. Inthis sub-study the insulinogenic index was higher in theOWP than in the RP group at baseline, but did not changesignificantly in either group.

In conclusion, we demonstrated that dietary carbohy-drate modification alters the serum metabolic profile,especially in lysoPC species, in patients with the MS. Thischange may contribute to proinflammatory processes seenin obesity and MS which in turn promote adverse changes ininsulin and glucose metabolism. This study also indicatedthat nutrigenomics, including metabolomics, lipidomics andtranscriptomics, allows comprehensive phenotyping ofresponses to dietary interventions.

Acknowledgements

Professor Hannu Mykkanen is greatly appreciated forproviding the study samples and data for lipidomic anal-yses. We thank Eeva Lajunen for the assistance during theintervention, Anna-Liisa Ruskeepaa for the help with fattyacid analysis and Leena Ohrnberg for the help withbranched chain amino acids analysis.

Appendix ASupplemental material

Supplementary information for this manuscript can bedownloaded at doi: 10.1016/j.numecd.2009.04.009.

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