Abstract
Gestational and postpartum high‐fat diets (HFDs) have been implicated as causes of obesity in offspring in later life. The present study aimed to investigate the effects of gestational and/or postpartum HFD on obesity in offspring. We established a mouse model of HFD exposure that included gestation, lactation and post‐weaning periods. We found that gestation was the most sensitive period, as the administration of a HFD impaired lipid metabolism, especially fatty acid oxidation in both foetal and adult mice, and caused obesity in offspring. Mechanistically, the DNA hypermethylation level of the nuclear receptor, peroxisome proliferator‐activated receptor‐α (Pparα), and the decreased mRNA levels of ten‐eleven translocation 1 (Tet1) and/or ten‐eleven translocation 2 (Tet2) were detected in the livers of foetal and adult offspring from mothers given a HFD during gestation, which was also associated with low Pparα expression in hepatic cells. We speculated that the hypermethylation of Pparα resulted from the decreased Tet1/2 expression in mothers given a HFD during gestation, thereby causing lipid metabolism disorders and obesity. In conclusion, this study demonstrates that a HFD during gestation exerts long‐term effects on the health of offspring via the DNA demethylation of Pparα, thereby highlighting the importance of the gestational period in regulating epigenetic mechanisms involved in metabolism.
Keywords: DNA demethylation, high‐fat diet, lipid metabolism, normal chow diet, obesity
1. INTRODUCTION
Obesity is a major health issue worldwide, with excessive fat intake contributing to disease progression. Increasing evidence shows that obesity increases the risk of developing type 2 diabetes, non‐alcoholic fatty liver disease and cardiovascular disease, thereby reducing the quality of life and life expectancy of patients. 1 , 2 However, it remains unknown whether there is a critical period during development from the gamete to the adult, and whether there is a relationship between high‐fat diet (HFD)‐induced obesity and gender. Nonetheless, maternal pre‐pregnancy and gestational obesity have adverse health outcomes in offspring, and this positive relationship has been confirmed in several studies. 3 , 4 The effects of a HFD given to mothers during lactation on metabolism in offspring are still controversial. 5 , 6 Presently, a wealth of food choices has resulted in bad eating habits, suggesting that changing environments may lead to adverse health outcomes in adults, which is a major driver of the obesity epidemic. However, it is unknown which period is most critical on the metabolism of offspring.
The pathogenesis of obesity not only includes various genetic factors, but also social and obesogenic environmental factors. 5 , 7 One study has investigated the epigenetic signature related to obesity in later life. 8 However, there is little information on the specific mechanisms of metabolic programming, including when and how epigenetic changes occur. DNA methylation is an important epigenetic hallmark, and DNA methylation patterns of genes are often altered by deleterious environmental factors. Furthermore, DNA methylation levels are regulated by DNA‐modifying enzymes. The ten‐eleven translocation (TET) family is comprised of important DNA‐modifying enzymes with roles in the epigenetic regulation of genes. 9 TETs promote DNA demethylation and increase gene expression. DNA demethylation occurs in foetal and adult livers and associates with the fatty acid β‐oxidation genes. 10 However, the major challenge is whether we can gauge the critical timing and the effects of HFD that can contribute to obesity.
In the present study, we established a mouse model to identify the most sensitive stage of obesity development in response to HFD. Furthermore, we confirmed its possible mechanism of action in obese offspring.
2. MATERIALS AND METHODS
2.1. Animal care
All animal protocols were approved by the Zhejiang University Animal Care and Use Committee. All mice were purchased from Beijing Weitonglihua Laboratory Animal (Beijing, China). The mouse HFD model was established as shown in Figure S1. Virgin C57BL/6J females (age, 6 weeks; weight, 12 g) were purchased and provided either a HFD (#D12492’ Research Diets, containing 20% protein, 60% fat) or a normal chow diet (NCD) (#D12450B; Research Diets, containing 20% protein, 10% fat) for 8 weeks before mating. Mice were provided either a NCD or a HFD during pre‐pregnancy and pregnancy. C57BL/6J male mice (age, 10 weeks) were used for mating. After birth, each group was divided into two groups: NCD and HFD groups based on the food provided to the mothers. After weaning, offspring in each group (four groups in total) was further divided into two groups: NCD and HFD groups based on the food provided to the offspring. This resulted in eight groups of offspring of two sexes, and there is only one pup from the same litter in each group (Figure S1).
2.2. Serum biochemical measurements
Blood specimens were collected from 16‐week‐old mice after overnight fasting. The serum levels of fasting triglyceride (TG), total cholesterol (TC), high‐density lipoprotein (HDL), low‐density lipoprotein (LDL) and non‐esterified fatty acids (NEFA) were measured using a biochemical analyser (TBA120FR; Toshiba, Tokyo, Japan). The serum level of fasting insulin was quantified using a mouse insulin enzyme‐linked immunosorbent assay (Crystal Chem, Downers Grove, IL, USA). The fasting glucose level was measured using a biochemical analyser (TBA120FR; Toshiba). After euthanization, livers and free gonadal adipose tissues were harvested and measured to calculate the liver‐to‐weight ratio and gonadal fat‐to‐weight ratio.
2.3. Tissue collection, histology and analysis of gene expression
Livers were harvested after collecting blood. For lipid accumulation analysis, left liver lobes were fixed, embedded in paraffin and sectioned for staining with Oil Red O. Total RNA from livers was extracted using TRIzol reagent (Life Technologies, Grand Island, NY, USA). cDNA was synthesized using oligo‐dT and random primers (Takara, Tokyo, Japan). The levels of target genes were measured using quantitative real‐time polymerase chain reaction (PCR) (LightCycler 480 II; Roche, Switzerland) with SYBR green detection (Takara). The level of each target gene was normalized to the β‐actin level. All primer (Sangon Biotech, Shanghai, China) sequences are shown in Table S1.
2.4. Pyrosequencing
DNA was extracted from livers using the TIANmap DNA kit (Tiangen, Beijing, China) and converted to bisulphite using the EpiTect Bisulfite Kit (Qiagen, Dusseldorf, Germany) according to the manufacturer's instructions. Pyrosequencing was used to assess the methylation status of gene promoter regions. Methylation pyrosequencing primers were designed by PyroMark Assay Design software 2.0 (Qiagen). Agarose gel electrophoresis was used to analyse each PCR product. PCR was performed in a 12.5 μL final volume that included EpiTaq Hot Start DNA polymerase (Takara, Dalian, China). For pyrosequencing analysis, bisulphite PCR products were processed according to the manufacturer's instructions (Qiagen). In brief, 10 μL of the PCR product was immobilized on 5 μL of streptavidin Sepharose high‐performance beads (GE Healthcare, Chicago, IL, USA) and annealed to 1 μL of a sequencing primer (final concentration, 10 μM) for 2 minute at 80°C. Pyrosequencing was performed using a PSQ 96MA instrument (Qiagen) using appropriate enzymes, substrates and nucleotides (PyroMark Gold Q24 reagents; Qiagen). CpG analysis was performed using PSQ 96MA software. Primer sequences and positions of validated CpG sites are shown in Table S2.
2.5. Statistical analysis
Statistical analysis was performed using SPSS Statistics 20.0 software (IBM, Armonk, NY, USA) and GraphPad Prism 6.0 software (La Jolla, CA, USA). All data are presented as the mean ± standard error of the mean. Unpaired Student's t tests were used to analyse statistical significance between two independent groups. One‐way analysis of variance followed by the least significance difference post hoc test was used to analyse statistical significance among three or more groups. All reported P values are two‐sided. P < .05 was considered statistically significant.
3. RESULTS
3.1. Administration of a HFD during gestation affects lipid metabolism and causes obesity in offspring
We analysed the offspring that were given a HFD during gestation, during weaning and after weaning. Irrespective of whether the offspring were given a NCD or HFD after weaning, the offspring that were given a HFD during gestation had a significantly increased bodyweight compared to the offspring of the other groups at 16 weeks of age, and there were no sex‐specific differences in chance of obesity (Figure 1A–D, one‐way analysis of variance [ANOVA], P < .05). Among the four groups given a HFD after weaning, the weight gain was most obvious in the groups given a HFD during gestation (H‐H–H and H–N–H, Figure 1B, D, one‐way ANOVA, P < .05).
3.2. Administration of a HFD increased liver lipid accumulation and ectopic fat deposition in offspring
A hallmark feature of obesity is ectopic fat deposition. Lipid accumulation was observed in livers of mice of all groups, except the N–N–N group (Figure 2 and Supplemental Figure S2). More and bigger lipid droplets were observed in livers of offspring given a HFD after weaning (Figure 2C [male], D [female]) compared with livers of offspring given a NCD after weaning (Figure 2A [male], B [female])) at 16 weeks of age. An analysis of the liver‐to‐bodyweight ratio showed that there was no significant difference in male and female offspring given a NCD feeding after weaning (Figure 1E, G, one‐way ANOVA, P > .05). However, offspring given a HFD after weaning (groups H–N–H, N–H–H and H–H–H) showed significantly increased liver‐to‐bodyweight ratios compared with offspring given a NCD (group N–N–H), irrespective of whether the offspring were male (Figure 1F) or female (Figure 1H, one‐way ANOVA, P < .05). Furthermore, we evaluated the gonadal fat‐to‐bodyweight ratio. An analysis of the gonadal fat‐to‐weight ratio showed that in four NCD after‐weaning groups, all male and female offspring in H–N–N and H–H–N groups had significantly increased gonadal fat‐to‐weight ratio compared with the control group (N–N–N) (Figure 1E, G). In four HFD after‐weaning groups, all male and female offspring in H–N–H, N–H–H and H–H–H groups had significantly increased gonadal fat‐to‐weight ratios compared with the control group (N–N–H) (Figure 1F, H, one‐way ANOVA, P < .05). However, offspring of gestational HFD exposure groups, including H–N–H and H–H–H groups, had significantly higher gonadal fat‐to‐weight ratios than offspring in the N–H–H group (Figure 1F, H). Taken together, these results indicate that a HFD given during gestation contributes to bodyweight gain and ectopic fat deposition in offspring mice.
3.3. Administration of HFD altered serum TG, LDL, NEFA, fasting glucose and insulin levels in offspring
Given that the important hallmarks of obesity are metabolic disorders and insulin resistance, we measured serum TG, TC, LDL, HDL, NEFA, glucose and insulin levels in offspring. Compared with the control group (N–N–N), offspring exposed to a HFD during gestation or lactation showed increased TG, LDL, NEFA, fasting glucose and insulin levels (Table 1). Offspring exposed to a HFD after weaning (H–N–H, N–H–H and H–H–H groups) showed very significantly increased TG, LDL, NEFA, fasting glucose and insulin levels and a decreased HDL level (Table 2). These results indicate that mice exposed to a HFD during early life can develop lipid and glucose metabolism disorders that may increase the risk of obesity in later life.
TABLE 1.
N–N–N | H–N–N | N–H–N | H–H–N | |
---|---|---|---|---|
Male (n) | 10 | 8 | 11 | 9 |
TG (mmol/L) | 0.87 ± 0.07 | 1.34 ± 0.09* | 1.34 ± 0.11* | 1.44 ± 0.09* |
TC (mmol/L) | 2.02 ± 0.05 | 2.11 ± 0.04 | 2.05 ± 0.05 | 2.08 ± 0.05 |
LDL (mmol/L) | 0.21 ± 0.04 | 0.4 ± 0.07* | 0.31 ± 0.06* | 0.38 ± 0.08* |
HDL (mmol/L) | 1.7 ± 0.34 | 1.66 ± 0.04 | 1.63 ± 0.03 | 1.64 ± 0.06 |
NEFA (mmol/L) | 0.78 ± 0.06 | 1.09 ± 0.04* | 0.98 ± 0.07* | 1.08 ± 0.05* |
Glucose (mmol/L) | 3.89 ± 0.13 | 5.77 ± 0.24* | 6.7 ± 0.51* | 6.32 ± 0.28* |
Insulin (μIU/mL) | 11.55 ± 1.03 | 17.89 ± 1.02* | 14.04 ± 1.64 # | 18.03 ± 0.81 * , $ |
Female (n) | 8 | 8 | 8 | 9 |
TG (mmol/L) | 0.66 ± 0.05 | 0.96 ± 0.08* | 0.9 ± 0.03* | 1.04 ± 0.07* |
TC (mmol/L) | 1.96 ± 0.02 | 1.92 ± 0.05 | 1.94 ± 0.08 | 2.07 ± 0.04 # |
LDL (mmol/L) | 0.15 ± 0.01 | 0.21 ± 0.01* | 0.20 ± 0.01* | 0.26 ± 0.02 * , # , $ |
HDL (mmol/L) | 1.46 ± 0.03 | 1.23 ± 0.05* | 1.28 ± 0.07* | 1.16 ± 0.02* |
NEFA (mmol/L) | 0.67 ± 0.05 | 1.01 ± 0.05* | 0.79 ± 0.12* | 1.19 ± 0.08* |
Glucose (mmol/L) | 4.87 ± 0.24 | 6.49 ± 0.24* | 6.38 ± 0.21* | 6.48 ± 0.17* |
Insulin (μIU/mL) | 14.71 ± 1.14 | 23.58 ± 1.32* | 23.98 ± 3.17* | 23.94 ± 2.07* |
All parameters were measured at 16 weeks of age. All results are expressed as the mean ± SEM Significance was determined by one‐way ANOVA, followed by LSD post hoc test.
Abbreviations: HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; NEFA, non‐esterified fatty acids; TC, total cholesterol; TG, triacylglycerol.
P < .05.
P < .05.
P < .05.
TABLE 2.
N–N–H | H–N–H | N–H–H | H–H–H | |
---|---|---|---|---|
Male (n) | 10 | 9 | 8 | 12 |
TG (mmol/L) | 1.35 ± 0.10 | 1.83 ± 0.12* | 1.74 ± 0.10* | 2.00 ± 0.09* |
TC (mmol/L) | 2.85 ± 0.11 | 3.73 ± 0.23* | 3.67 ± 0.21*, # | 4.84 ± 0.13*, $ |
LDL (mmol/L) | 0.19 ± 0.02 | 0.39 ± 0.03* | 0.40 ± 0.02* | 0.56 ± 0.05*, # , $ |
HDL (mmol/L) | 2.56 ± 0.20 | 1.86 ± 0.23* | 2.00 ± 0.20* | 1.69 ± 0.07* |
NEFA (mmol/L) | 1.42 ± 0.06 | 1.86 ± 0.08** | 1.85 ± 0.09** | 2.24 ± 0.10**, ## , $$ |
Glucose (mmol/L) | 7.28 ± 0.36 | 11.12 ± 0.51** | 10.64 ± 0.47**, # | 13.34 ± 0.66**, ## , $$ |
Insulin (μIU/mL) | 19.09 ± 0.44 | 30.68 ± 1.43** | 29.96 ± 2.67**, # | 32.83 ± 3.49**, $ |
Female (n) | 13 | 10 | 9 | 10 |
TG (mmol/L) | 1.16 ± 0.07 | 1.46 ± 0.10* | 1.46 ± 0.11*, # | 1.57 ± 0.09*, $ |
TC (mmol/L) | 2.42 ± 0.08 | 2.67 ± 0.14 | 2.52 ± 0.14 | 3.16 ± 0.11**, ## , $$ |
LDL (mmol/L) | 0.78 ± 0.02 | 0.92 ± 0.04* | 0.92 ± 0.03* | 1.02 ± 0.08*, # , $ |
HDL (mmol/L) | 1.82 ± 0.04 | 1.58 ± 0.08* | 1.59 ± 0.09* | 1.34 ± 0.06*, # , $ |
NEFA (mmol/L) | 1.23 ± 0.04 | 1.68 ± 0.06** | 1.53 ± 0.08** | 1.75 ± 0.04**, $$ |
Glucose (mmol/L) | 6.70 ± 0.17 | 8.04 ± 0.23* | 8.00 ± 0.36* | 10.25 ± 0.62**, ## , $$ |
Insulin (μIU/mL) | 23.94 ± 2.07 | 30.73 ± 0.93** | 29.17 ± 1.04* | 30.64 ± 1.27** |
All parameters were measured at 16 weeks of age. All results are expressed as the mean ± SEM Significance was determined by one‐way ANOVA, followed by LSD post hoc test.
Abbreviations: HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; NEFA, non‐esterified fatty acids; TC, total cholesterol; TG, triacylglycerol.
P < .05
P < .01 vs N–N–H;
P < .05
P < .01 vs H–N–H ;
P < .05
P < .01 vs N–H–H.
3.4. Administration of a HFD down‐regulated Pparα mRNA expression in offspring at 16 weeks of age
We performed quantitative PCR (qPCR) analysis to determine whether a HFD given in early life could alter the expression of lipid metabolism‐related genes in the livers of F1 offspring at 16 weeks of age. We selected key genes with roles in lipid metabolism, including lipid transport, cholesterol metabolism, fatty acid transport, lipogenesis and fatty acid oxidation, as well as transcription factors (Figure 3). We found that male offspring from mothers given a HFD during gestation had significantly increased levels of Apo‐A1, Apo‐C3, Apo‐E, Scd1, Me1 and Srebp1 and significantly decreased levels of peroxisome proliferator‐activated receptor‐α (Pparα) and Cpt‐1a (Figure 3A[a–f], male). Female offspring from mothers given a HFD during gestation also had significantly increased levels of Cyp7A1, Scd1 and Srebp1, and significantly decreased levels of Pparα and Cpt‐1a (Figure 3B[a–f], female). These results suggest that gestational HFD exposure alters lipid metabolism–related genes in the liver, and gestation might be a sensitive period of HFD exposure.
3.5. Administration of a HFD impaired fatty acid oxidation earlier than lipogenesis at E18.5 day
We performed qPCR analysis to examine the levels of the genes associated with lipid metabolism in the foetal liver at E18.5 day. The genes related to lipid metabolism included those involved in lipid transport, cholesterol metabolism, fatty acid transport and lipogenesis. Compared with the foetuses from mothers given a NCD during gestation, Cpt‐1a and Pparα mRNA levels were significantly decreased in the livers of both males (Figure 4A[e, f], male) and females (Figure 4B[e, f], female) at E18.5 day from the mothers given a HFD during gestation. These results are consistent with those in the livers of adult offspring (Figure 3) and provide further evidence that gestational HFD exposure alters genes related to lipid metabolism in the liver and gestation is a sensitive period of HFD exposure.
3.6. Administration of a HFD reprogrammes DNA methylation patterns by decreasing Tets expression instead of increasing Dnmts expression at E18.5 day
Based on our finding of decreased Pparα expression in mice at E18.5 day and 16 weeks of age, we further examined the DNA methylation pattern of Pparα and the relative mRNA levels of DNA‐modifying enzymes. We found increased methylation in CpG sites of the Pparα promoter in the livers of foetuses at E18.5 day from mothers given a HFD during gestation compared to mothers given a NCD during gestation (Figure 5A [male], B [female]). The mean methylation level of the Pparα promoter was significantly higher in offspring of the gestational HFD group than that in offspring of the NCD group (Figure 5E [male], F [female]). These hypermethylation patterns may have been caused by the decreased expression levels of Tet1 and Tet2, because we found that the expression levels Tet1 and Tet2 were significantly lower in the liver of foetuses at E18.5 day from mothers given a HFD during gestation than those given a NCD (Figure 5C [male], D [female]), whereas there were no significant differences in the expression levels of the methyltransferases, Dnmts, between these two groups (Figure 5C [male], D [female]). These results indicate that a HFD given during gestation induces hypermethylation of Pparα by decreasing the expression of Tet1 and Tet2.
3.7. Administration of HFD induces hypermethylation of Pparα by decreasing Tets expression in offspring at 16 weeks of age
We examined the DNA methylation patterns of Pparα in male and female offspring at 16 weeks of age. Similar to the findings in foetuses, we found increased methylation in CpG sites of the Pparα promoter in the livers of offspring at 16 weeks of age from mothers given a HFD during gestation than that from mothers given a NCD (Figure 6A [male], B [female]). The mean methylation level of the Pparα promoter was significantly higher in offspring of the gestational HFD group than those of the NCD group (Figure 6E [male], F [female]). We also detected a lower expression level of Tet2 in the livers of male offspring (Figure 6C [male]) and lower expression levels of Tet1 and Tet2 in the livers of female offspring (Figure 6D [female]) at 16 weeks of age from mothers given a HFD during gestation than those given a NCD, whereas there were no significant differences in the expression levels of Dnmt1 and Dnmt3a between these two groups (Figure 6C [male], D [female]). These results provide further evidence that a HFD given during gestation induces hypermethylation of Pparα by decreasing the expression of Tet1 and Tet2.
4. DISCUSSION
‘Mismatch'nutritional changes and/or a sedentary lifestyle can increase the risk of obesity. 11 Previous studies have shown that a maternal HFD‐ or self‐HFD‐induced obesity leads to different metabolism disorders. 12 , 13 , 14 Here, we provide evidence to support two fundamental principles of programming: sensitivity and duration. We found that gestation was the most sensitive period to induce obesity in late life, and there was no difference between the sexes in chance of obesity. Furthermore, we found that lactation and administration of a HFD post‐weaning increased the incidence of lipid metabolism disorders and obesity in offspring.
We speculated that the DNA demethylation level of Pparα associated with lipid metabolism disorders and obesity in offspring. The altered DNA methylation pattern of Pparα may have been caused by aberrant demethylation, which was attributed to the decreased expression of Tets that may have been triggered by a maternal HFD during gestation. Consistently, we found that the aberrant demethylation of Pparα was associated with lipid metabolism disorders and obesity in offspring. Mechanistically, the hypermethylation of the Pparα promoter is attributed to decreased DNA‐modifying enzymes of Tets in offspring from mothers given a HFD during gestation, which may have disrupted demethylation.
Given that different developmental processes take place at different stages, we speculated that the various programming mechanisms were also related to the time point of exposure. However, our results suggest that gestation is the most sensitive period for lipid metabolism disorders and obesity after the administration of a HFD. There are different windows of opportunity for the programming of epigenetically labile genes. Some studies support the alteration of epigenetic status during development as an important cause induced adult obesity. 15 , 16 Gestation is considered as the most sensitive period because high DNA synthesis and DNA methylation patterns are established for normal tissue development during the embryonic period. 17 These two reprogramming events are the times when the epigenetic state changes most widely in the life cycle.
The administration of a HFD during lactation may induce obesity in mice, consistent with the results of previous studies. 18 , 19 Sexual dimorphism is a common research area in clinical trials and basic medical research. 20 In this study, we did not observe sexual dimorphism in lipid metabolism and obesity. One possible reason is that diet‐induced obesity in mice varies by age of onset, 21 and oestrogen in adult females may have caused a difference between the sexes. Another possibility is that there are significant differences in adipose tissue distribution between males and females, 22 , 23 and women typically have greater fat accumulation in gluteal‐femoral depots. 24
Lipid metabolism mainly involves lipogenesis and fatty acid catabolism. In this study, we revealed that impaired fatty acid oxidation was initiated at pregnancy much earlier than lipogenesis, and the decreased expression of the upstream transcription factor Pparα started at gestation. Previous studies have reported that HFD exposure can disrupt lipogenesis and fatty acid oxidation, 25 , 26 but they did not identify the initiating factors. In this study, we mainly investigated whether the administration of a HFD during pregnancy would alter the expression of lipid metabolism‐related genes in the livers of offspring. We found that the levels of several lipid metabolism‐related genes were altered in offspring from mothers given a HFD during gestation. Among these genes, decreased Pparα expression was not only observed in livers of offspring but also in livers of foetuses from mothers given a HFD during gestation. PPARα is a key regulator of fatty acid oxidation in mice. 27 Hepatocyte‐specific PPARα deficiency can lead to hepatic lipid accumulation. 28 PPARα can also stimulate the transcription of fatty acid β‐oxidation relative genes. 29 In the present study, the administration of a HFD during pregnancy led to decreased expression of Pparα in foetal livers, possibly by inhibiting the demethylation of Pparα‐dependent fatty acid oxidation–related genes and ultimately inhibiting lipid catabolism and inducing obesity.
There is increasing evidence that environmental stress can affect gene transcription, and gene transcription rates can be regulated through DNA methylation levels. Several studies have hypothesized that DNA methylation is fully established by the time of birth. 30 , 31 , 32 However, many fatty acid β‐oxidation‐related genes undergo DNA demethylation with increased mRNA expression in the postnatal mouse liver. 33 DNA methylation is a gene transcription silencing mechanism. In this study, we speculated that the relationship between the reduced expression of Tets and the increased methylation level of Pparα may have started during gestation, thereby leading to lipid metabolism disorders and obesity in offspring later in life. Furthermore, it has been reported that DNA methylation patterns of metabolism‐related genes in the liver change dynamically in early life, thereby activating hepatic metabolic processes to adapt to the nutritional environment. 34 , 35 , 36
The administration of a HFD during gestation down‐regulated the levels of Tet1 and Tet2 in offspring at E18.5 days, whereas the Dnmts level was not altered. TET2 is necessary for cell development, 37 and postnatal demethylation in the liver was mediated by TET2. 38 Reduced expression of Tet1 and Tet2 may associate with an enhanced DNA methylation level of Pparα, and decreased expression of Tets may compromise demethylation. Previous studies have reported that DNA demethylation is PPARα dependent, 39 and PPARα mediates DNA demethylation of fatty acid β‐oxidation genes. 34 In the present study, a gestational HFD reduced Tet1 and Tet2 expression, thereby resulting in hypermethylation of hepatic Pparα and decreased PPARα expression. Finally, reduced PPARα expression increased the risk of obesity in offspring from mothers given a HFD.
In summary, we found that a HFD given during gestation alters lipid metabolism–related genes by altering epigenetic programs. A gestational HFD impairs the demethylation of Pparα, thereby inducing obesity in offspring in later life. Early interventions and avoiding exposure should help to prevent lipid metabolic disorders associated with obesity.
CONFLICT OF INTEREST
The authors declare that they have no conflicts of interest.
AUTHOR CONTRIBUTIONS
Haiyan Pang, Jianzhong Sheng, Hefeng Huang: designed the experiments. Haiyan Pang, Dandan Ling: performed the animal experiments and collected and analysed data. Yi Cheng, Luyang Jin: performed the animal experiments. Rubab Akbar, Jun Ren, Haiyan Wu, Bin Chen, Yin Zhou, Hong Zhu, Yuzhong Zhou: collected animal materials. Haiyan Pan,Jianzhong Sheng, Hefeng Huang: wrote and edited the manuscript. All authors read and approved the final manuscript. Jianzhong Sheng: is the guarantor of this work and, as much, has full access to all data in the study and takes responsibility for the integrity and accuracy of data analysis.
Supporting information
Pang H, Ling D, Cheng Y, et al. Gestational high‐fat diet impaired demethylation of Ppar α and induced obesity of offspring. J Cell Mol Med. 2021;25:5404–5416. 10.1111/jcmm.16551
Haiyan Pang and Dandan Ling contributed equally to this study.
Funding information
This work was supported by National Natural Science Foundation of China (#2017YFC1001001 and #2018YFC1004402) Natural Science Foundation of Shanghai (19410740600)
Contributor Information
Hefeng Huang, Email: hhf57@zju.edu.cn.
Jianzhong Sheng, Email: shengjz@zju.edu.cn.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
REFERENCES
- 1. Swinburn BA, Millar L, Utter J, et al. The Pacific Obesity Prevention in Communities project: project overview and methods. Obes Rev. 2011;12(suppl 2):3‐11. [DOI] [PubMed] [Google Scholar]
- 2. James PT. Obesity: the worldwide epidemic. Clin Dermatol. 2004;22:276‐280. [DOI] [PubMed] [Google Scholar]
- 3. Metzger BE, Persson B, Lowe LP, et al. Hyperglycemia and adverse pregnancy outcome study: neonatal glycemia. Pediatrics. 2010;126:e1545‐e1552. [DOI] [PubMed] [Google Scholar]
- 4. Lappas M. Effect of pre‐existing maternal obesity, gestational diabetes and adipokines on the expression of genes involved in lipid metabolism in adipose tissue. Metabolism. 2014;63:250‐262. [DOI] [PubMed] [Google Scholar]
- 5. Vogt M, Paeger L, Hess S, et al. Neonatal insulin action impairs hypothalamic neurocircuit formation in response to maternal high‐fat feeding. Cell. 2014;156:495‐509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Cordner ZA, Khambadkone SG, Boersma GJ, et al. Maternal high‐fat diet results in cognitive impairment and hippocampal gene expression changes in rat offspring. Exp Neurol. 2019;318:92‐100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Zhang M, Ikeda K, Xu JW, Yamori Y, Gao XM, Zhang BL. Genistein suppresses adipogenesis of 3T3‐L1 cells via multiple signal pathways. Phytother Res. 2009;23:713‐718. [DOI] [PubMed] [Google Scholar]
- 8. Castellano‐Castillo D, Moreno‐Indias I, Fernández‐García JC, et al. Adipose tissue LPL methylation is associated with triglyceride concentrations in the metabolic syndrome. Clin Chem. 2018;64:210‐218. [DOI] [PubMed] [Google Scholar]
- 9. Melamed P, Yosefzon Y, David C, Tsukerman A, Pnueli L. Tet enzymes, variants, and differential effects on function. Front Cell Dev Biol. 2018;6:22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Lienert F, Wirbelauer C, Som I, Dean A, Mohn F, Schubeler D. Identification of genetic elements that autonomously determine DNA methylation states. Nat Genet. 2011;43:1091‐1097. [DOI] [PubMed] [Google Scholar]
- 11. Kessler NJ, Waterland RA, Prentice AM, Silver MJ. Establishment of environmentally sensitive DNA methylation states in the very early human embryo. Sci Adv. 2018;4:t2624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Ortega FB, Lavie CJ, Blair SN. Obesity and cardiovascular disease. Circ Res. 2016;118:1752‐1770. [DOI] [PubMed] [Google Scholar]
- 13. Seravalle G, Grassi G. Obesity and hypertension. Pharmacol Res. 2017;122:1‐7. [DOI] [PubMed] [Google Scholar]
- 14. Catalano PM, Shankar K. Obesity and pregnancy: mechanisms of short term and long term adverse consequences for mother and child. BMJ Clin Res. 2017;356:j1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Nie L, Shuai L, Zhu M, et al. The landscape of histone modifications in a high‐fat diet‐induced obese (DIO) mouse model. Mol Cell Proteomics. 2017;16:1324‐1334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Roberts‐Toler C, O’Neill BT, Cypess AM. Diet‐induced obesity causes insulin resistance in mouse brown adipose tissue. Obesity (Silver Spring). 2015;23:1765‐1770. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Faulk C, Dolinoy DC. Timing is everything: the when and how of environmentally induced changes in the epigenome of animals. Epigenetics. 2011;6:791‐797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Ullah R, Su Y, Shen YI, et al. Postnatal feeding with high‐fat diet induces obesity and precocious puberty in C57BL/6J mouse pups: a novel model of obesity and puberty. Front Med. 2017;11:266‐276. [DOI] [PubMed] [Google Scholar]
- 19. Sun B, Purcell RH, Terrillion CE, Yan J, Moran TH, Tamashiro KL. Maternal high‐fat diet during gestation or suckling differentially affects offspring leptin sensitivity and obesity. Diabetes. 2012;61:2833‐2841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Palmer BF, Clegg DJ. The sexual dimorphism of obesity. Mol Cell Endocrinol. 2015;402:113‐119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Salinero AE, Anderson BM, Zuloaga KL. Sex differences in the metabolic effects of diet‐induced obesity vary by age of onset. Int J Obes (Lond). 2018;42:1088‐1091. [DOI] [PubMed] [Google Scholar]
- 22. Karastergiou K, Smith SR, Greenberg AS, Fried SK. Sex differences in human adipose tissues ‐ the biology of pear shape. Biol Sex Differ. 2012;3:13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Karpe F, Pinnick KE. Biology of upper‐body and lower‐body adipose tissue‐link to whole‐body phenotypes. Nat Rev Endocrinol. 2015;11:90‐100. [DOI] [PubMed] [Google Scholar]
- 24. White UA, Tchoukalova YD. Sex dimorphism and depot differences in adipose tissue function. Biochim Biophys Acta. 2014;1842:377‐392. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Alves‐Bezerra M, Cohen DE. Triglyceride metabolism in the liver. Compr Physiol. 2017;8:1‐8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Hodson L, Gunn PJ. The regulation of hepatic fatty acid synthesis and partitioning: the effect of nutritional state. Nat Rev Endocrinol. 2019;15:689‐700. [DOI] [PubMed] [Google Scholar]
- 27. Gluckman PD, Hanson MA. The developmental origins of the metabolic syndrome. Trends Endocrinol Metab. 2004;15:183‐187. [DOI] [PubMed] [Google Scholar]
- 28. Wahli W, Michalik L. PPARs at the crossroads of lipid signaling and inflammation. Trends Endocrinol Metab. 2012;23:351‐363. [DOI] [PubMed] [Google Scholar]
- 29. Rakhshandehroo M, Knoch B, Muller M, Kersten S. Peroxisome proliferator‐activated receptor alpha target genes. PPAR Res. 2010;2010:1‐20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Waterland RA, Kellermayer R, Rached M‐T, et al. Epigenomic profiling indicates a role for DNA methylation in early postnatal liver development. Hum Mol Genet. 2009;18:3026‐3038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Law JA, Jacobsen SE. Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat Rev Genet. 2010;11:204‐220. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Seisenberger S, Andrews S, Krueger F, et al. The dynamics of genome‐wide DNA methylation reprogramming in mouse primordial germ cells. Mol Cell. 2012;48:849‐862. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Hon GC, Rajagopal N, Shen Y, et al. Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nat Genet. 2013;45:1198‐1206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Ehara T, Kamei Y, Yuan X, et al. Ligand‐activated PPARalpha‐dependent DNA demethylation regulates the fatty acid beta‐oxidation genes in the postnatal liver. Diabetes. 2015;64:775‐784. [DOI] [PubMed] [Google Scholar]
- 35. Ehara T, Kamei Y, Takahashi M, et al. Role of DNA methylation in the regulation of lipogenic glycerol‐3‐phosphate acyltransferase 1 gene expression in the mouse neonatal liver. Diabetes. 2012;61:2442‐2450. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Marra F, Svegliati‐Baroni G. Lipotoxicity and the gut‐liver axis in NASH pathogenesis. J Hepatol. 2018;68:280‐295. [DOI] [PubMed] [Google Scholar]
- 37. Vincent J, Huang Y, Chen P‐Y, et al. Stage‐specific roles for tet1 and tet2 in DNA demethylation in primordial germ cells. Cell Stem Cell. 2013;12:470‐478. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Hackett JA, Sengupta R, Zylicz JJ, et al. Germline DNA demethylation dynamics and imprint erasure through 5‐hydroxymethylcytosine. Science. 2013;339:448‐452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Reizel Y, Spiro A, Sabag O, et al. Gender‐specific postnatal demethylation and establishment of epigenetic memory. Genes Dev. 2015;29:923‐933. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.