• early growth;
  • intrauterine growth restriction;
  • long-chain polyunsaturated fatty acids;
  • prebiotic;
  • probiotic


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information


To investigate the effect of a nutritional mixture (bovine milk oligosaccharides, Lactobacillus rhamnosus NCC4007, arachidonic and docosahexaenoic acid) on growth of intrauterine growth-restricted (IUGR) rats.


IUGR was induced by maternal food restriction. The offspring (males and females) were assigned to: REF (non-IUGR, no mixture), IUGRc (IUGR, no mixture), or IUGRmx (IUGR, mixture). The mixture was given from day 7 to day 58, when tissues and plasma from half of the animals were collected for hormones, metabolites and microarray analysis. The rest received a high-fat diet (HFD) until day 100. Glucose tolerance was measured at 56 and 98 days, and body fat content at 21, 52 and 97 days.


IUGRmx had the greatest growth during lactation, but from day 22 to day 54, both IUGR groups gained less body weight than the REF (P < 0.05). In the short-term (58 days), IUGRmx tended to be longer (P = 0.06) and had less body fat (P = 0.03) than IUGRc. These differences were not seen after HFD. Microarray analysis of hepatic mRNA expression at 58 and 100 days revealed a gender-dependent treatment effect, and expression of genes related to lipid metabolism was the most affected. Twelve of these genes were selected for studying differences in DNA methylation in the promoter region, for some, we observed age- and gender-related differences but none because of treatment.


The nutritional intervention promoted catch-up growth and normalized excessive adiposity in IUGR animals at short-term. The benefits did not extend after a period of HFD. IUGR and early diet had gender-dependent effects on hepatic gene expression.

Associations between low birth weight and increased risk of metabolic syndrome have been described in several epidemiological studies. The thrifty phenotype hypothesis proposes that poor foetal and infant nutrition produce changes in glucose–insulin metabolism aimed to improve immediate survival, but which also result in greater risk of type 2 diabetes later in life (Hales & Barker 2001). Low birth weight can be caused by intrauterine growth restriction (IUGR) resulting from maternal malnutrition, cigarette smoking or pregnancy-induced hypertension among others (Bergmann et al. 2008). After birth, most of these infants show rapid weight gain, which confers them advantages in terms of survival, low stature prevention and decrease in the risk of subnormal intellectual development (Ong 2007). However, accumulating evidence also indicates that catch-up growth is an important component of programming adult diseases, and associations between early rapid growth and increased later body mass index (BMI) have been described in several cohort studies (Claris et al. 2010). Evidence from animal studies suggests that alterations in insulin signalling caused by IUGR affect the development of visceral fat depots, which are key in determining the subsequent metabolic phenotype (Morrison et al. 2010).

Strategies that promote growth while normalizing insulin sensitivity, favouring lean mass accretion and limiting visceral fat would benefit this population. The potential of functional ingredients such as pre- and probiotics on modulating the onset and development of metabolic disorders has been extensively reviewed (Cani & Delzenne 2009). Likewise, LC-PUFA and specially n-3 fatty acids have shown to modulate adipose tissue function, increasing lipid catabolism and decreasing lipogenesis in animal models (Kopecky et al. 2009). However, the programming effect of these ingredients administered early in life has not been tested.

The objective of the present study was to evaluate the effect of supplementation early in life (7–56 days) with a mixture containing long-chain polyunsaturated fatty acids (LC-PUFA, arachidonic acid and docosahexaenoic acid), a bovine milk-derived oligosaccharide (BMO) and a probiotic (Lactobacillus rhamnosus NCC4007) in the growth and metabolic status of IUGR rats.

Material and methods

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information

Animals and diets

This study is in agreement with Good Publishing Practice in Physiology (Persson & Henriksson 2011). A summary of the experimental design is depicted in Figure 1; Sprague–Dawley timely mated females (n = 18, Charles River, L'Arbresle Cedex, France) were randomly allocated to ad libitum (AL, n = 6) or 50% food restriction during the last 10 days of gestation (R, n = 12). All females received a chow diet (Kliba Nafag 3437, Kaiseraugst, Switzerland) and were fed ad libitum during the lactation period. At birth, pups were weighted within the first 24 h, pooled within maternal groups (AL or R) and randomly allocated to a nursing dam and an experimental group. The experimental groups were composed by males and females (12 each) and were as follows: (i) Reference (REF): pups from AL dams receiving control gavage and control weaning diet (Table 1); (ii) IUGR control (IUGRc): pups from R dams receiving control gavage and control weaning diet; and (iii) IUGR mixture (IUGRmx): pups from R dams receiving a mixture containing BMO, Lactobacillus rhamnosus NCC4007 and LCPUFA in the gavage and in the weaning diet. The gavage was provided from 7 to 21 days; the mixture gavage provided 0.08% of body weight (BW) of bovine milk oligosaccharides enriched with galacto-oligosaccharides (BMO, 25.5% oligosaccharides, 33.4% lactose, 9.1% glucose, 8.1% galactose, 4.03% protein, 11.4% ash; Nestlé, Konolfingen, Switzerland); 0.03% BW of arachidonic acid (ARASCO, 44% purity, Martek Biosciences Corporation, Columbia, MD, USA); 0.03% BW of docosahexaenoic acid (DHASCO, 45% purity Martek Biosciences Corporation) and 1 × 109 CFU of Lactobacillus rhamnosus NCC4007 (Nestlé). In the control gavage, BMO was substituted by maltodextrin (Glucidex 12, Roquette, France), and DHA and AA were substituted by α linolenic (C18:3 n-3) and linoleic acid (C18:2 n-6) respectively. In addition, lactose, glucose, galactose, casein and skim milk were added to match the amounts provided by the BMO and Lactobacillus rhamnosus NCC4007 formulation.

Table 1. Composition of weaning diets
 Control1Diet containing experimental mixture2
g 100 g−1 of diet
Corn starch433.9533.95
Bovine milk-derived oligosaccharide compound9014.42
Fat mix (see below for composition)77
Minerals (AIN-93-G)103.503.50
Vitamins (AIN-93-VX)1011
Choline bitartrate40.250.25
  1. 14.53 kcal g−1, 18.32% protein, 24.46 kcal g−1, 18.78% protein, 3Smith trading. 4Synopharm, Germany, 5Roquette, France. 6Howeg, Switzerland. 7Fluka, USA. 8Merck, Germany. 9Nestlé, Switzerland, 10Socochim, Switzerland. 11Sofinol, Switzerland. 12Nutriswiss, Switzerland. 13Martek, USA. 14Sabo, Switzerland.

Fat mixg 100 g−1 of fat
Refined Palm Olein115054
Coconut oil111511
Low erucic rapeseed oil111512
Corn oil121410
Flaxseed oil1463

Figure 1. Experimental design. REF = Reference; IUGRc = intra-uterine growth-restricted control group; IUGRmx = intra-uterine growth-restricted group receiving a mixture of bovine milk oligosaccharides, Lactobacillus rhamnosus NCC4007, arachidonic and docosahexaenoic acid. Experimental groups were composed by 12 females and 12 males each.

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At 21 days, the pups were individually housed and fed semisynthetic diets modified from AIN 93G (Reeves et al. 1993) until day 58 (Table 1). During this period, Lactobacillus rhamnosus NCC4007 (1 × 109 CFU) was supplemented daily in a gelatin pellet, and the control group received a placebo pellet. Afterwards, half of the animals were killed and the remaining received a high-fat diet (60% calories from fat, 91 : 7 lard : soybean oil, D12492, Research Diets, New Brunswick, NJ, USA) without experimental mixture until day 100 when they were killed.


Body fat content was measured by nuclear magnetic resonance (NMR) at 21, 52 and 97 days. Oral glucose tolerance tests (OGTT) were performed at day 56 and at day 98; the rats were fasted for 6 h and then received an oral load of 2 g of glucose per kg of BW. Blood was obtained from the caudal vein before (time 0) and 15, 30, 45, 60 and 120 min after glucose load. Blood glucose was measured by duplicate with an automatic glucose metre (Ascencia Elite XL, Dublin, Ireland), and insulin was measured at 0, 30, 60 and 120 min. HOMA-IR index was calculated with the formula described by Cacho et al. (2008). Body weights were recorded daily during the first 21 days of life and three times per week for the rest of the experiment. Food intake was recorded three times per week from weaning until the end of the experiment. Euthanasia was performed at 58 and 100 days (six males and six females per group at each time). Animals were fasted for 6 h and killed by exsanguination under isoflurane anaesthesia. Nose–anus length was measured before exsanguinations in anaesthetized animals in recumbent position. Aortal blood was collected in tubes with EDTA. And portal blood was collected for GLP-2 analysis in tubes containing EDTA, aprotinin (40 μL mL−1 blood; Trasylol, Bayer, Leverkusen, Germany) and a DPP-IV inhibitor (10 μL mL−1 blood; Linco Research, St. Charles, MO, USA). Wet weight of liver, pancreas, small intestine, colon, caecum and adipose fat pads (mesenteric and parametrial or epididymal) was recorded. The liver was frozen in liquid nitrogen, and the pancreas was stored in an acid–ethanol solution, the femur was dissected, and its length was measured with a digital caliper.

Hormones and metabolites analysis

Plasma insulin, leptin, IGF-1, GLP-2, IGFBP-2 and IGFBP-3 were measured by ELISA with commercially available kits: Rat insulin ELISA kit 90060 (Crystal Chem, Downers Grove, IL, USA); rat leptin ELISA kit 90040 (Crystal Chem); rat IGF-1 ELISA kit (IDS immunodiagnostic, Frankfurt, Germany); GLP-2 ELISA kit RSCYK140R (Labodia S.A., Yens, Switzerland); rat IGFBP-2 ELISA kit RMEE08R (Mediagnost, Reutlingen, Germany); rat IGFBP-3 ELISA kit RMEE031R (Mediagnost). Plasma triglycerides, free fatty acids and cholesterol were measured using automated chemistry analyser (COBAS Mira Roche, Basel, Switzerland) with the following kits: triglycerides enzymatic kit TRIG GPO AXMJ00069 (Axon Lab, Hengesbern, Germany), free fatty acids enzymatic kit 99975406 (Wako Chemicals GmbH, Neuss, Germany) and cholesterol enzymatic kit 61218/61219 (BioMérieux S.A. Lyon, France). Liver triglycerides were extracted (Hara & Radin 1978), saponified (Frayn & Maycock 1980), and glycerol was quantified by a colorimetric method kit PAP 150 (Biomérieux). Pancreatic insulin was extracted overnight with an acid-ethanol-H2O solution and measured by ELISA kit 90060 (Crystal Chem).

Probiotic analysis

The presence of Lactobacillus rhamnosus NCC4007 was tested in faecal samples of 12 animals (six males and six females) per group. The samples were taken at 52 days and plated on MRS agar (supplemented with antibiotics). DNA extracts of bacterial colonies obtained after incubation were submitted to PCR using strain-specific primers: CCTGGCTGACTTCAGAAAGAA: GAACACCAGAACGGCTGAGT. A product of 211 bp was expected for the specific detection of Lactobacillus rhamnosus NCC4007. PCR amplification products were analysed by agarose gel electrophoresis.

All IUGRmx samples were positive for Lactobacillus rhamnosus NCC4007, and all REF and IUGRc samples were negative.

Microarray analysis

Extraction of mRNA was performed from frozen liver with the Agencourt RNAdvance Tissue kit (Beckman Coulter, Brea, CA, USA). Extraction from frozen adipose tissue (parametrial/epididymal) was performed with a delipidation phase followed by RNeasy Mini Kit from QIAGEN (Duesseldorf, Germany). Briefly, tissue samples were homogenized at high speed with lysis buffer in the FastPrep24 instrument (MP biomedicals, Santa Ana, CA, USA). After addition of chloroform on the supernatant, the homogenate was separated into aqueous and organic phases by centrifugation. The upper, aqueous phase was extracted and processed for RNA quantification using Quant-It RiboGreen assay (Life Technologies, Paisley, UK) on spectramax reader. Purity was verified with the Agilent Bioanalyzer 2100 (Agilent RNA 6000 nano kit, Basel, Switzerland). All RNA samples had a quality score above 7.5 RIN.

All cRNA targets were synthesized, labelled and purified according to the Illumina TotalPrep RNA amplification protocol (Applied Biosystems/Ambion, Austin, TX, USA). Briefly, 300 ng of total RNA was used to produce double-stranded cDNA, followed by an in vitro transcription, along with biotin UTP. This method is based on the Eberwine T7 procedure (Van Gelder et al. 1990). Prior to the hybridization on the arrays, 750 ng of biotin labelled-cRNAs was used to prepare the hybridization mix, which contained control oligonucleotides (such as negative and hybridization controls), hybridization buffer and water. Then, 15 μL of each hybridization mix was dispensed on the arrays. After an overnight hybridization (16 h, 58 °C), the arrays were washed to remove non-hybridized material and stained with Streptavidin-Cy3, which bound with biotin. All samples were analysed on RatRef-12 V1 Expression BeadChips (Illumina, San Diego, CA, USA), which comprise probes to interrogate 22'500 transcripts. Scanning was performed using the BeadArray Reader (Illumina), which provides intensity values for all transcripts, measuring the signal emitted by the Streptavidin-Cy3 conjugates responding to a laser excitation. Signal intensities were extracted and summarized in the BeadStudio software (Illumina). Data were expressed as absolute intensities.

Statistical analysis

The following factors were taken into account in the statistical analysis: treatment (three levels, REF, IUGRc, IUGRmx); gender (two levels, males and females); age (two levels, 56 and 100 days). Only for transcriptomics, tissue was taken as a factor (two levels, liver and adipose tissue). The litter effect was not taken into account. For the clinical parameters, treatment comparisons were performed at each age, and for each gender, Wilcoxon tests were performed. If there was no interaction between gender and treatment, a global analysis was performed by Wilcoxon tests after removing from the data the gender effect. For gender comparisons at each age and for each treatment, Wilcoxon tests were performed. If there was no interaction between gender and treatment, a global analysis was performed by Wilcoxon tests after removing from the data the treatment effect. Data are presented as median + SEMedian (standard error of the median based on Sn of Rousseeuw) (Rousseeuw & Croux 1993). The software used for these analyses was R 2.6.1 (R Development Core Team 2007).

Analysis of microarray data was carried out with Partek software (Partek, St. Louis, MO, USA). After quantile normalization and a log2 transformation, quality control of the data was performed with a Pearson's correlation matrix and a principal component analysis on all probes to help determine possible outliers. To assess which transcripts were differentially expressed, an analysis of variance (anova) was performed, followed by a global error assessment (GEA). The GEA resulted in a robust mean squared error (MSE), which replaced the current MSE from the classical anova, a new F statistic was then calculated and a robust P-value derived. All interactions between fixed factors were taken into account. (four fixed factors: treatment, gender, age and tissue and one random factor: animal). Appropriate contrasts were performed (shown only on liver), and data are presented as fold changes. Genes that were differentially expressed (P < 0.001) and had at least onefold change were imported into Ingenuity Pathways Analysis Software (IPA; Ingenuity systems, Redwood city, CA, USA) for identification of altered biological functions and calculation of z-score algorithm predicting the direction of change. For DNA methylation data, only descriptive statistical analyses were performed, and means by treatment, age and gender were calculated.

DNA methylation analysis

Targeted DNA methylation analysis was performed in selected genes identified by microarray analysis. Hepatic tissue samples were pulverized using the CryoPrep System (Covaris, Woburn, MA, USA). DNA extraction was performed with the Agencourt DNAdvanced kit (Beckman Coulter), following the manufacturer′s instructions. 50–100 ng μL−1 DNA was analysed at BioGlobe GmbH (Hamburg, Germany). Briefly, FASTA sequences from 2 kb upstream from the transcription start site (TSS) and 500 bp downstream from TSS obtained from Ensembl, NCBI and UCSC underwent an in silico assay for the identification of the so-called amplicons, regions with annotated CpG sites suitable for amplification by PCR after bisulphite conversion. Several amplicons for each gene were selected, and the required primers for amplification were designed and tested. DNA methylation analysis was performed using the EpiTYPER® workflow (Sequenom, San Diego, CA, USA). Means by treatment, age and gender were performed.


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information


Body weight by gender is presented in Table 2. As expected, maternal restriction caused lower birth weight in their offspring (P < 0.001). During lactation (0–21 days), IUGRmx gained the most weight (3.9 g more than IUGRc and 2.1 g more than REF; P = <0.001 and 0.02 respectively) and by 21 days was heavier than IUGRc and not different from REF (Table 2). BW diverged by gender at 35 days, and the males continued to be heavier than the females for the rest of the study (P < 0.001). During consumption of experimental diets (22–58), both IUGR groups gained less than REF (P < 0.04). At 56 days, the males in IUGR groups tended to be lighter than REF, but the difference was not statistically significant (P = 0.08). At this time point, IUGRc females were lighter than REF, and IUGRmx females were not significantly different from REF or IUGRc (Table 2). Food efficiency, nose–anus length and femur length are presented in Table S1. During experimental diets, food efficiency tended to be greater in IUGRmx than in IUGRc (P = 0.07) and REF (P = 0.06). At 58 days, nose–anus length was shorter in IUGRc compared with REF (P < 0.001) and tended to be shorter than IUGRmx (P = 0.06), while IUGRmx was not significantly different from REF (P = 0.11), accordingly, femur length was shorter in IUGRc than in the other groups (P = 0.03). After the high-fat diet period (59–100 days), body weight gain, food efficiency or body length was not different among groups.

Table 2. Body weight during the experiment
Day (n)Females Males 
  1. Different transcripts indicate P < 0.05.

0 (12)6.4 ± 0.09a5.3 ± 0.17b5.2 ± 0.17b<0.0016.8 ± 0.04a5.6 ± 0.17b5.6 ± 0.17b<0.001
21 (12)55.6 ± 1.1a51.31 ± 1.3b56.2 ± 1.5a0.00258.0 ± 0.8a55.0 ± 0.9b57.3 ± 0.9a0.02
56 (12)203.8 ± 3.3a187.7 ± 3.1b197.9 ± 6.2ab0.01300.6 ± 5.0292.3 ± 7.1293.2 ± 7.60.08
97 (6)269.1 ± 13.3281.4 ± 18.3268.2 ± 15.30.43506.4 ± 30.1459.1 ± 17.4472.7 ± 34.70.13

Body fat content and organ weights

Body fat content through the study is shown in Figure 2. At 21 days, both IUGR groups had greater body fat content than the REF (P < 0.001), but at day 50, only IUGRc was fatter than REF (P = 0.02). After the high-fat diet, there were no differences among groups. Organs and adipose tissue weight as% of BW are presented in Table 3. IUGRc males had greater epididymal fat than REF, and mesenteric fat also tended to be greater in IUGRc males than the other groups (P = 0.07). The weights of female fat pads were not different. Small intestine and colon weight were not different among treatments, but caecum was greater in IUGRmx than in the other groups (Table 3). There were no significant differences in organ weights at 100 days (data not shown).

Table 3. Organ weights after experimental diet period (58 days)
  1. a

    n = 6 per group.

  2. Different transcripts indicate P < 0.05.

Adipose tissue
Parametrial/Epididymal1.35 ± 0.271.34 ± 0.351.34 ± ± 0.08b1.37 ± 0.16a1.05 ± 0.09ab0.02
Mesenteric0.70 ± 0.090.71 ± 0.110.77 ± ± 0.100.88 ± 0.060.78 ± 0.090.07
Retroperitoneal0.42 ± 0.070.55 ± 0.080.64 ± ± 0.071.01 ± 0.120.85 ± 0.140.2
Small intestine2.71 ± 0.132.63 ± 0.092.68 ± ± 0.062.21 ± 0.032.28 ± 0.110.2
Colon0.29 ± 0.030.31 ± 0.030.36 ± ± 0.050.24 ± 0.020.24 ± 0.010.6
Caecum1.34 ± 0.04b1.19 ± 0.09c2.38 ± 0.02a0.0020.98 ± 0.09b1.05 ± 0.12b2.19 ± 0.17a0.002
Liver3.16 ± 0.093.24 ± 0.053.21 ± ± 0.093.58 ± 0.123.35 ± 0.190.07
Pancreas0.52 ± 0.050.49 ± 0.050.49 ± ± 0.050.33 ± 0.020.39 ± 0.050.09

Figure 2. Body fat content by treatment. Graphs contain median ± SE of the median. $ Significant difference (P < 0.05) REF vs. IUGRc; £ Significant difference (P < 0.05) REF and IUGRmx; * Significant difference (P < 0.05) IUGRc vs. IUGRmx.

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Oral glucose tolerance tests

There was no effect of IUGR on oral glucose tolerance at any time point. At 56 days, HOMA-IR was greater in IUGRc males compared with REF (P = 0.03; 0.74 ± 0.10, 1.40 ± 0.28, 0.85 ± 0.13 for REF, IUGRc and IUGRmx respectively) and also pancreatic insulin concentration (P = 0.008; 155.2 ± 29.9, 224.1 ± 30.1, 203.6 ± 48.0 μg mg−1 for REF, IUGRc and IUGRmx respectively). In IUGRmx, neither HOMA-IR nor pancreatic insulin was significantly different from IUGRc or REF. No differences were observed at 100 days (data not shown).

Hormones, metabolites and hepatic triglycerides

There were no differences in plasma leptin, IGF1, IGFBP2, IGFBP3, free fatty acids, triglycerides (TG) or cholesterol at any time point (Table S1). At day 58, portal GLP-2 concentration was increased by 17% in IUGRmx compared with the other two groups. This difference was not observed at day 100, when IUGRc had lower GLP-2 than REF (Table S1). Treatment effect on liver TG concentration was gender-dependent: at 58 days, the mixture caused a decrease in males, which was significantly different from REF (P = 0.02) and tended to be different from IUGRc (P = 0.07; 36.4 ± 10.8, 26.3 ± 2.14, 16.20 ± 2.35 mg g−1 for REF, IUGRc and IUGRmx respectively), but no significant differences were observed in females (28.10 ± 2.71, 29.15 ± 6.32, 33.76 ± 7.96 mg g−1 for REF, IUGRc and IUGRmx respectively). By 100 days, there were not significant differences in males, but IUGR females had greater liver TG than REF, nevertheless, the difference was only statistically significant for IUGRc (P = 0.04; 28.5 ± 2.8, 34.04 ± 6.3, 48.5 ± 12.6 mg g−1 for REF, IUGRc and IUGRmx respectively). When males and females were analysed together, both IUGR groups tended to have more liver TG than REF (P = 0.06; 35.5 ± 7.0, 58.5 ± 9.7, 62.0 ± 9.8 mg g−1 for REF, IUGRc and IUGRmx respectively).

Gene expression

To get an insight into differences in energy metabolism that could explain the observations in growth and body fat content, we performed microarray analyses in adipose tissue and liver. The quality control containing the Pearson's correlation matrix and the principal component analysis for all probes is presented in Figure S1. Gene expression changes in adipose tissue were moderate, and no relevant functions related to energy metabolism were altered (results not shown). In liver, gene expression changes were gender- and time-dependent. The functions more affected were related to lipid metabolism and are presented in Table 4 and Figure S2 (males) and Table 5 and Figure S3 (females). In the males, supplementation with the mixture decreased expression of genes involved in lipid, fatty acids and terpenoid synthesis, fatty acid, terpenoid and steroid metabolism and concentration and lipid conversion (Table 4, day 58). This is in line with the decreased hepatic TG concentration observed in this group. After the period of high-fat diet, lipid functions were more deeply affected in IUGRc than in IUGRmx compared with REF. However, this was not reflected in different TG concentration between the IUGR groups, probably because synthesis and oxidation functions were both increased in IUGRc (Table 4, day 100). The effect of the mixture in hepatic gene expression was less evident in females, in spite of several genes that differed between IUGRc and IUGRmx, the direction of the function (z-score) was only modestly affected (Table 5, day 58). For both IUGR groups, steroid and terpenoid metabolism were increased, for IUGRmx, also synthesis of terpenoid and cholesterol. Genes involved in lipid transport were reduced in IUGRc compared with REF and IUGRmx. After receiving the high-fat diet (100 days), the differences among groups were reduced (Table 4, day 100). The 12 genes with greatest fold change among treatments are listed in Tables S2 (males) and S3 (females). We observed that several genes with an extensive fold change between IUGRc vs. REF were altered in the opposite direction between females at 58 days and males at 100 days, and this pattern was not seen in IUGRmx. These genes are presented in Table 6 and were analysed for DNA methylation patterns.

Table 4. Gene expression differences in males clustered by function
FunctionDay 58Day 100
IUGRc vs. REFaIUGRmx vs. REFbIUGRmx vs. IUGRccIUGRc vs. REFaIUGRmx vs. REFbIUGRmx vs. IUGRcc
Genes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-value
  1. ns: non-significant difference (P > 0.05).

  2. a

    Change of IUGRc with respect to REF.

  3. b

    Change of IUGRmx with respect to REF.

  4. c

    Change of IUGRmx with respect to IUGRc.

Fatty acid metabolism13 (−1.07)0.0146 (−1.62)<0.00135 (−1.87)0.02100 (3.06)<0.001nsns110 (−2.13)<0.001
Steroid metabolismnsns24 (−1.70)<0.00118 (−0.69)0.0358 (−0.69)<0.001nsns63 (−0.40)<0.001
Terpenoid metabolismnsns29 (−1.18)<0.00124 (−0.67)0.00167 (−0.54)<0.001nsns72 (0.11)<0.001
Oxidation of lipid6 (−0.82)0.0419 (0.98)0.00115 (−0.03)0.0431 (2.28)<0.001nsns44 (−0.43)<0.001
Concentration of lipid19 (0.65)0.00266 (−1.00)<0.00154 (−0.69)<0.001122 (0.256)<0.00150 (−0.49)<0.001136 (−0.60)<0.001
Conversion of lipidnsns18 (−1.04)<0.00115 (−0.69)<0.00133 (−0.57)<0.00111 (0.79)0.0240 (0.09)<0.001
Synthesis of lipid16 (0.25)0.00452 (−1.16)<0.00144 (−1.21)0.003111 (2.32)<0.001nsns119 (−1.54)<0.001
Synthesis of terpenoidnsns22 (−1.38)<0.00118 (−0.80)0.0147 (−0.07)<0.001nsns51 (−1.59)<0.001
Synthesis of fatty acid7 (−1.09)0.0424 (−1.10)<0.00120 (−1.25)0.0246 (2.38)<0.001nsns47 (−1.67)<0.001
Transport of lipidnsns17 (−0.97)<0.001nsns31 (2.28)<0.001nsns36 (−2.1)<0.001
Table 5. Gene expression differences in females clustered by function
FunctionDay 58Day 100
IUGRc vs. REFaIUGRmx vs. REFbIUGRmx vs. IUGRccIUGRc vs. REFaIUGRmx vs. REFbIUGRmx vs. IUGRcc
Genes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-valueGenes, n (z-score)P-value
  1. ns: non-significant difference (P > 0.05). na: Z-score not calculated.

  2. a

    Change of IUGRc with respect to REF.

  3. b

    Change of IUGRmx with respect to REF.

  4. c

    Change of IUGRmx with respect to IUGRc.

Fatty acid metabolism86 (−0.85)<0.001nsns100 (0.39)<0.00112 (0.98)0.00226 (0.62)0.004nsns
Steroid metabolism48 (1.17)<0.00118 (2.56)<0.00160 (−0.09)<0.00111 na<0.00119 (0.20)<0.00116 (−0.12)0.01
Terpenoid metabolism57 (1.20)<0.00121 (1.42)<0.00170 (−0.51)<0.00113 (−0.51)<0.00122 (0.44)<0.00119 (0.37)<0.001
Oxidation of lipid43 (−0.33)<0.00111 (1.18)0.00241 (−0.02)<0.0016 (−1.08)0.0114 (0.45)<0.00113 (0.70)0.01
Concentration of lipid98 (0.18)<0.00132 (0.51)<0.001124 (1.00)<0.001nsns38 (−1.23)<0.001nsns
Conversion of lipid31 (−0.43)<0.00111 (1.14)<0.00142 (0.58)<0.001nsnsnsns14<0.001
Synthesis of lipid93 (−0.33)<0.00122 (1.18)0.01109 (0.32)<0.00112 (0.80)0.0129 (0.33)0.009nsns
Synthesis of terpenoid43 (0.25)<0.00114 (1.32)<0.00152 (0.74)<0.001nsns14 (−0.76)0.005nsns
Synthesis of cholesterol15 (0.55)<0.0016 (2.00)<0.00119 (−0.20)<0.0013 na0.02nsnsnsns
Synthesis of fatty acids34 (−0.19)<0.001nsns43 (−0.36)<0.001nsnsnsnsnsns
Transport of lipid28 (−1.80)<0.001nsns33 (1.61)<0.0017 na<0.001nsnsnsns
Table 6. Fold change expression of genes selected for DNA methylation analysis
Gene (Entrez id)IUGRc vs. REFaIUGRmx vs. REFb
Day 58Day 100Day 58Day 100
  1. a

    Change of IUGRc with respect to REF.

  2. b

    Change of IUGRmx with respect to REF.

A1bg (140656)−1.44−122.58129.42−1.31−−1.01
Akr1b7 (116463)1.37−78.5680.541.03−2.651.071.03−1.15
Aldh1a7 (29651)−1.04−11.6212.981.03−2.5−1.09−1.161.43
Cyp2c11 (29277)1.0199.70−78.811.151.031.421.06−1.00
Cyp2c13 (171521)1.0737.22−29.40−1.06−1.071.33−1.031.19
Cyp3a2 (266682)1.14200.87−164.351.30−−1.11
Hsd11b1 (25116)−1.029.19−10.22−−1.04−1.25
Ifi47 (246208)1.41−12.3611.191.01−2.24−1.141.04−1.01
Lox (24914)−1.0114.84−12.511.031.24−1.08−3.47−1.16
Prlr (24684)1.21−11.8611.53−1.27−2.33−1.17−1.071.03
Scd1 (246074)−1.00−7.435.391.84−1.37−1.641.77−1.03
Sult1e1 (25355)−1.05160.21−106.661.24−1.021.881.03−1.13

DNA methylation

Analysis of the promoter region of Sult1e1 failed, but the methylation pattern in 49 amplicons within the promoter region of the other 11 genes could be analysed, and the percentage of methylation for 262 CpG sites was quantified. Three genes showed sexual dimorphism in their methylation pattern: A1bg, Akr1b7 and Ifi47 had gender-dependent (Table S4) and gender-specific age-dependent changes (Table S5) in several and adjacent CpG sites. This could have biological consequences and cause differential expression between genders. In the affected regions, most females showed intermediate methylation, whereas males showed hypermethylated CpG sites (close to 100% methylation in some cases). In females, age-dependent decreased methylation at 100 days was observed mainly in A1bg, resulting in an even larger difference in methylation with respect to the males at this age. Yet because we found no differences in methylation between REF and IUGR groups, the differences were not linked to the IUGR challenge or the post-natal diet. Therefore, additional mechanisms are probably responsible for the gene expression changes because of treatment.


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information

Supplementation with the mixture induced better growth during early life as indicated by the greater weight gain during lactation, greater femur length and a trend to have greater body length than IUGRc after the experimental diets. Similarly, improved growth recovery and restoration of intestinal permeability have been reported in neonatally stressed rats supplemented with a mixture containing arachidonic and docosahexaenoic acid, galacto- and fructo-oligosaccharides and Lactobacillus paracasei NCC2461 (Garcia-Rodenas et al. 2006). Better catch-up growth with the experimental mixture may have been the result of improved absorption mediated by GLP-2, which was increased in IUGRmx. GLP-2 is a key regulator of intestinal development and nutrient absorptive capacity (Sigalet 2012), and it increased intestinal glucose uptake in suckling pups when it was injected to their dams (Drozdowski et al. 2009). Similarly, others have reported that prebiotic treatment in obese mice increases intestinal production of GLP-2 (Cani et al. 2009), the mechanism of action may involve modulation of bacterial fermentation and increased production of short-chain fatty acids, which in turn stimulate GLP-2 production (Tappenden et al. 2003). Short-chain fatty acids have a trophic effect in the intestinal mucosa, which may explain the increased caecal weight observed in the present study and also reported in other experiments supplementing prebiotic oligosaccharides (Neyrinck et al. 2012).

Increased fat accumulation after catch-up growth is documented in low birth weight infants (Ibanez et al. 2008) and in animal models of IUGR (Bieswal et al. 2006, Bol et al. 2009, Isganaitis et al. 2009), but despite better growth, IUGRmx had less fat content than IUGRc at 52 days and was not significantly different from REF. Studies performed in a semistarvation-refeeding animal model indicate that the mechanism of catch-up fat includes a period of hyperinsulinaemia, decreased glucose utilization in the muscle and marked upregulation of insulin-mediated de novo lipogenesis (Cettour-Rose et al. 2005, Summermatter et al. 2009). In the present study, increased adiposity was observed in IUGRc males and females, but hyperinsulinaemia was only present in IUGRc males. A similar gender dimorphism has also been reported by others; male growth-restricted mice and sheep were more susceptible than females to develop insulin resistance and metabolic syndrome (Owens et al. 2007, Hermann et al. 2009). Like in this study, some animal and human interventions with pre- and probiotics have shown beneficial effects in obesity and adiposity: peri-natal supplementation with Lactobacillus rhamnosus prevented excessive weight gain during early life in infants (Luoto et al. 2010). Lactobacillus gasseri reduced mesenteric and subcutaneous adipose tissue in Zucker rats (Hamad et al. 2009) and abdominal visceral and subcutaneous fat in human subjects with high BMI (Kadooka et al. 2010). Lactobacillus paracasei caused reduction in body fat in mice fed a high-fat diet (Aronsson et al. 2010). Supplementation with oligofructose reduced body fat in high fat fed C57BL/6 male mice (Anastasovska et al. 2012), and long-chain inulin-reduced adiposity in female rats (Jamieson et al. 2008). Prebiotic fibres during growth (16 week from weaning) modulated weight gain afterwards in rats fed a high-fat diet (Maurer et al. 2010). LCPUFA have also been reported to affect body weight and adiposity; supplementation with arachidonic and docosohexaenoic acid for 8 week after weaning reduced epididymal fat pad weight in ApoE*3Leiden mice even after a period high-fat diet (Wielinga et al. 2012). Similarly, dietary n-3 LCPUFA from lactation until 42 days has been shown to reduce fat accumulation after a challenge with a western diet in a murine model (Oosting et al. 2010). But in the present study, a protective effect was not observed. Intra-uterine growth retardation is associated with development of non-alcoholic fatty liver disease in children (Nobili et al. 2007), and oral administration of probiotics has been reported to reduce high-fat diet-induced hepatic steatosis (Ma et al. 2008). In the present study, a decrease in hepatic TG was observed in IUGRmx males just after supplementation (day 58), but this effect was not persistent by 100 days.

After the challenge with the high-fat diet, there were no differences in energy intake, adiposity or glucose tolerance between the IUGRc and REF groups. This was unexpected as it has been reported that caloric restriction during intrauterine life promotes hyperphagia (Vickers et al. 2000) and amplifies the detrimental effect of high caloric intake in rats (Bieswal et al. 2006). The challenge in the present study differs from others in the shorter period length (42 days) and the composition of the diet (60% of dietary calories from fat, without added sucrose), and this may have affected the response.

The effects of maternal food restriction and mixture supplementation on hepatic gene expression at 58 and 100 days were gender-dependent. Sexual dimorphism in hepatic gene expression is regulated by growth hormone (GH) gender-specific secretion patterns (Clodfelter et al. 2007, Wauthier & Waxman 2008). GH deficiency caused major alterations in expression of genes involved in fatty acid, xenobiotic and steroid hormone metabolism (Amador-Noguez et al. 2005), which were functions affected by gender and treatment in the present study. Impairment of the somatotrophic axis may occur as a consequence of intrauterine undernutrition; IUGR newborn infants have higher cord blood GH (Setia et al. 2007), and children born small for gestational age have different GH pulse frequency and peak amplitude than those born with adequate birth weight (Woods et al. 2002). In rats, food restriction during lactation resulted in ‘female-like’ GH secretion patterns in the adult males, but no changes were seen in females (Houdijk et al. 2003). Interestingly, some of the genes in which IUGR caused expression changes in opposite direction between genders (Table 6) have been reported as having sex-specific modulation by growth hormone: hepatic expression of A1bg1, Akr1b7, Ifi47 and Prlr has been reported to decrease in females after hypophysectomy and respond to GH injection (Wauthier & Waxman 2008). In the present study, the expression of these genes was severely decreased in IUGRc females at 58 days, when they had significantly lower BW than reference. The extent of the differences in gene expression was reduced by 100 days when IUGRc females had completed catch-up growth, and therefore, their BW was not different from REF. Cyp2c11, whose expression has been shown to decrease in males after hypophysectomy (Wauthier & Waxman 2008), was severely decreased in IUGRc males at 100 days; moreover, female predominant genes (A1bg1, Akr1b7, Ifi47 and Prlr) were increased when compared with REF. In IUGRc males, BW remained numerically lower than REF through the study although the difference did not reach significance. These observations suggest that GH secretion pattern may be altered in the IUGRc group and could have caused sex-specific changes in hepatic gene expression, but we cannot be conclusive because GH pulses were not measured in the present study. Furthermore, the molecular mechanism by which the experimental mixture was able to normalize GH secretion, for example improving nutrient absorption, remains to be elucidated. Our DNA methylation analysis revealed a potential role of this molecular mechanism in the previously known gender-specific expression of Akr1b7 (Kotokorpi et al. 2004) and Ifi47 (Wauthier & Waxman 2008), and as well the known gender-specific and age-dependent expression of A1bg (Tiong et al. 2006). Nevertheless, our results indicate that DNA methylation is not underlying the treatment by gender interaction expression changes observed in the selected genes. Epigenetic mechanisms like the presence of DNase hypersensitive chromosomal regions and sex-specific chromatin organization also cause sexual differences in metabolic processes (Gabory et al. 2011) and may be responsible for the observed effects.

In conclusion, the mixture of bovine milk oligosaccharides, Lactobacillus rhamnosus NCC4007, arachidonic and docosahexaenoic acid improved catch-up growth and prevented excessive adiposity at short-term. Data from the microarrays outlined some interesting gender differences in response to maternal restriction and early nutritional intervention that suggest growth hormone regulation by IUGR. Our DNA methylation analysis indicated that this molecular mechanism could mediate some gender-specific and age-dependent gene expression patterns in the liver. After a period of high-fat diet, we did not observe any effect either from pre-natal restriction or from post-natal treatment.

The authors would like to thank Rodrigo Bibiloni, Florence Blancher, Christian Darimont, Lucie Deschamps, Patricia Leone, Taoufiq Harach, Massimo Marchesini, Christophe Maubert, Christine Mettraux, Mathieu Membrez, Kurt Ornstein, Stéphane Pinaud, Manuel Ribeiro, Isabelle Rochat, José Sanchez García and Marie Camille Zwalen.


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. Conflict of interest
  7. References
  8. Supporting Information
apha12145-sup-0001-FigureS1.docxWord document565KFigure S1. Pearson correlation matrix on log2 expression. Principal component analysis of adipose tissue (A) and liver (B).
apha12145-sup-0002-FigureS2.docxWord document837KFigure S2. Network of genes involved in lipid synthesis and oxidation (males 58 days) and (males 100 days).
apha12145-sup-0003-FigureS3.docxWord document592KFigure S3. Network of genes involved in lipid synthesis and oxidation (females 58 days) and (females 100 days).
apha12145-sup-0004-TableS1.docxWord document16KTable S1. Growth parameters, metabolites and hormones during the experiment1.
apha12145-sup-0005-TableS2.docxWord document20KTable S2. Genes with greatest fold change in the females.
apha12145-sup-0006-TableS3.docxWord document20KTable S3. Genes with greatest fold change in the males.
apha12145-sup-0007-TableS4.docxWord document28KTable S4. DNA methylation differences by gender.
apha12145-sup-0008-TableS5.docxWord document28KTable S5. DNA methylation differences by age in each gender.

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