Research has shown that if a mother experiences a transitory perturbation to her environment during pregnancy or lactation, there are transgenerational consequences often involving a disordered metabolic phenotype in first generation offspring with recovery across subsequent generations. In contrast, little is known about the nature of the transgenerational response of offspring when a mother experiences a perturbation that is not transitory but instead persists across generations. Our study, using a rat model, subjected the parental generation to a change in environment and concomitant shift from a grain-based to obesogenic diets to generate an adipose phenotype in first generation offspring emulating a common scenario in human urbanisation and migration. We then investigated whether the obese phenotype was stable across generations when maintained in the transitioned environment, and whether dietary macronutrient balance affected the response. We found that second and third generation offspring had a reduced body fat to lean mass ratio and a reduced appetite relative to first generation offspring, irrespective of dietary macronutrient balance. The trajectory of this response is suggestive of a reduction in chronic disease risk across generations. This is one of the first studies, to our knowledge, to investigate the transgenerational response following parental transition to a persistent obesogenic environment, and to demonstrate that successive generations respond differently to this constant environment.
Citation: Tait AH, Raubenheimer D, Green MP, Cupido CL, Gluckman PD, Vickers MH (2015) Successive Generations in a Rat Model Respond Differently to a Constant Obesogenic Environment. PLoS ONE 10(7): e0129779. https://doi.org/10.1371/journal.pone.0129779
Academic Editor: Zane Andrews, Monash University, AUSTRALIA
Received: February 10, 2015; Accepted: May 12, 2015; Published: July 1, 2015
Copyright: © 2015 Tait et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: Funding was provided by the Health Research Council of New Zealand, Project 05/244 (http://www.hrc.govt.nz/) Public good funding. The authors also acknowledge funding support from Gravida: National Centre for Growth and Development, the Tertiary Education Commission of New Zealand and the Maurice Paykel Research Trust. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Epidemiological and experimental studies in animal models have shown that susceptibility to developing chronic disease in offspring may be increased if the mother experienced a transitory nutritional perturbation during pregnancy or while nursing, for example a period of calorie restriction, protein restriction or high fat feeding [1–8]. This phenotype is expressed even though the offspring themselves experienced no direct manipulations and were normally-nourished. Animals studies have further shown that second generation offspring may also be susceptible to developing chronic disease as a result of the transitory nutritional perturbation experienced by their grandmother, though third generation offspring show no such tendencies [9–16]. This transgenerational response is thought to be underpinned by mechanisms of epigenetic inheritance [17, 18].
In contrast to the body of data on offspring responses following a transient change in maternal environmental conditions, little is known about the response following a sustained transition in environmental conditions, which is first encountered by the parent then persists across generations. This scenario is highly relevant to the human nutritional transition. In human society, globalization involving global trade liberalization and increases in income and urbanization has created obesogenic environments by promoting positive energy balance through: (a) nutritional transitions to diets rich in animal products, refined grains and added sugar; and (b) reductions in physical activity [19–23]. Populations worldwide are transitioning in this way, and are continuing to experience obesogenic environments across generations. This has seen the worldwide prevalence of obesity double between 1980 and 2008 [19, 24]; whether or not this trend will persist in the face of on-going obesogenic environments is of much interest.
In this study, using a rat model, we manipulated the environment of the parents to emulate the human scenario of migration from rural to urban environments, or from a low to a high income society/country. This scenario involves both a radical change in environment and a change in nutrition to more obesogenic diets, which in humans leads to a greater risk of obesity[25, 26]. Our parental generation of rats simultaneously experienced a change in environment by way of relocation from the supplier’s facility to our research facility, and a change from a grain-based diet to a purified diet, akin to the shift towards more refined diets in humans. We then recorded the body composition and food intake of first, second and third generation offspring maintained under constant conditions on the transitioned diet. To investigate whether dietary macronutrient balance affected the transgenerational response, we also introduced a high fat or a low protein purified-ingredient diet to a subset of first generation offspring, whose descendants were likewise fed the high fat or low protein diets.
The parental generation (P) of Wistar rats (15 males, 30 females, all non-littermates) was sourced from a colony maintained on a grain-based diet (VRF1) from Charles River Laboratories (Charles River UK Ltd., Kent, UK) and transported to our research facility in Auckland, New Zealand. Upon arrival, aged approximately 32 days, P rats experienced a nutritional transition to a reference purified-ingredient diet (R) (Table 1, Fig 1). Purified-ingredient diets can be obesogenic for rats due to increased palatability, greater energy density [27, 28] and greater nutrient conversion efficiencies [27, 29, 30]. First, second and third generation offspring of P rats (F1, F2 and F3, respectively) were all fed exclusively on purified-ingredient diets.
The parental generation of rats (P) experienced a transition aged approx. 32 days in the form of relocation to our animal facility and a shift from grain-based nutrition to a reference purified-ingredient diet (R). P rats were mated to produce the first of three generations fed exclusively on purified-ingredient diets (F1). F1 offspring were either maintained on R, or were fed a high fat purified diet (HF) or a moderately low protein purified diet (LP) from weaning onwards. Second and third purified diet generations (F2, F3) were generated by mating females from each lineage (R, HF, LP) with males from the R lineage.
To investigate whether or not the macronutrient balance of the purified-ingredient diets influenced the transgenerational response, in addition to the lineage maintained in R a subset of F1 rats was weaned onto either a high fat purified-ingredient diet (HF) or moderately low protein purified-ingredient diet (LP) (Table 1) (F1 litters were systematically distributed among the three diet treatment groups to avoid litter biases among the dietary treatment lineages). F2 and F3 offspring were generated on each dietary lineage (R, HF and LP) by mating females from each lineage with unrelated males of the same generation from the R lineage. All purified-ingredient diets were fed ad libitum and were supplied by Purina TestDiet (PMI Nutrition, Richmond, IN, USA; R = 58B0 (AIN-76A); HF = 58V8 (D12451); LP = 5A3U (modified AIN-76A)).
All animal procedures were approved by the Animal Ethics Committee of the University of Auckland (Approval R402). Rats were housed from weaning in pairs or as singletons during pregnancy under standard conditions with wood shavings for bedding and free access to water in a room with a 12 h light / 12 h dark cycle, a temperature of 25°C and humidity of 50%. F1, F2 and F3 rats were housed in the same room and all procedures including daily husbandry were conducted by the same team of personnel throughout the study.
Virgin females were time-mated at approximately 130 days of age, using an oestrous cycle monitor (Model EC40, Fine Science Tools, Foster City, CA, USA) to assess the stage of oestrous before introducing the male, and housed singly after pregnancy confirmation. At birth, the sex and weight of each pup were recorded but litters were left intact until postnatal day 2 when they were standardised to 8–10 pups (equal number of males and females) to remove potential litter size effects (litters of 8–10 pups were left intact while litters of >10 pups were standardised to 10 pups by randomly selecting and then culling excess pups). At 22 days of age, pups were weaned from their mothers and housed in same-sex sibling pairs. From weaning until the end of the study, animals were checked daily and their bodyweights recorded every six days to monitor general wellbeing. Details of the animal model including matings, births and neonatal survival are presented in S1 Table.
Body composition, calorie intake and nutrient conversion efficiencies
Body composition was measured on a subset of eight males and eight females per group at approximately 115 days of age. This was done under light halothane anaesthesia (3%) by dual-energy X-ray absorptiometry (DXA) with dedicated small animal software (GE Medical Systems Lunar, Madison, WI, USA). Food (calorie) intake was measured across consecutive six-day periods from weaning onwards. We report the average intake of rats from age 58 days onwards (across nine consecutive periods) over which time intake was relatively stable. Since rats were housed in pairs, food intake was measured per pair and meaned to estimate the intake per rat. Nutrient conversion efficiencies were also evaluated per pair of rats with ANCOVA to analyse the combined body lean or fat mass of each pair, using their combined average daily intake of protein or non-protein energy, respectively, as the covariate [31, 32].
Data from F1, F2 and F3 rats were analysed by two-way ANOVA or ANCOVA using generation and diet as factors, where a significant main effect of generation indicates that the phenotype was not stable (i.e. non-consistent) across generations, a significant statistical interaction between generation and diet indicates an effect of macronutrient balance on the transgenerational response, and a significant main effect of diet indicates a within-generation effect of diet. Sample sizes are presented in S2 Table. Male and female data were analysed separately based on the a priori assumption that the sexes may respond differently. Body composition and calorie intake data were analysed by two-way ANOVA and food conversion efficiency data were analysed by two-way ANCOVA with nutrient intake as the covariate (protein and non-protein energy as the covariate for body lean and fat mass, respectively) using SPSS (PASW Statistics 18, IBM Corp., Somers, NY, USA). Homoscedascity was confirmed with Levene’s test with a square root or rank transformation applied as necessary. Where the statistical interaction between generation and diet was significant (p < 0.05), the analysis was split by diet and the effect of generation was tested for each diet using one-way ANOVA or ANCOVA as appropriate. Otherwise, the interaction term was removed before testing the main effects. Where appropriate, for ANOVA Scheffe analysis was used for post-hoc tests of generation and Dunnett’s analysis with R as the control group for post-hoc tests of diet, and for ANCOVA the main effects were compared using a Sidak correction. Litter identity was initially included as a random effect in a mixed model ANOVA (using SAS version 9.1.3 for windows software, SAS Institute Inc., Cary, NC, USA), but there were no qualitative differences between the results of the standard model and this mixed model ANOVA, so litter identity was excluded to simplify the analysis and presentation. Data are presented as means ± SEM for ANOVA and estimated marginal means ± SEM for ANCOVA, and p was considered significant at < 0.05. Data are available from the Dryad Digital Repository:
Details of the animal model including maternal weight gain and food intake during pregnancy, litter size, maternal food intake during lactation are presented in S3 Table and S1 Fig Pup birth weights, weaning and adult weights are presented in Fig 2 and S3 Table. There was an overall higher birthweight in F2 compared to F3 and birthweights in the LP group were lower than for the R group for both males and females (Fig 2A and 2B). At weaning, body weights at F2 were lower in F2 males compared to F3 but this was not observed in females. For both males and females, weaning weights in the HF group were increased compared to both R and LP groups and the LP group weaning weights significantly lower compared to both R and HF offspring (Fig 2C and 2D). For male adult body weights, F1 weights were higher than for F2 and HF weights greater than for R (Fig 2E). For adult females, there were no differences across R and LP groups for HF offspring F1 weights were reduced overall compared to F2 (Fig 2F). As a baseline control, we have also shown in an independent cohort that male and female offspring fed the standard chow control diet do not show any weight changes over successive generations (S2 Fig).
Fat mass, lean mass and the ratio of fat to lean mass all changed across generations both for males and females (Table 2, Fig 3A–3F). For both sexes, fat mass in F3 was reduced relative to F1, and lean mass was greater in F2 and F3 relative to F1. In males, lean mass was also greater in F3 relative to F2. In both sexes, the ratio of fat to lean mass was reduced in F2 and F3 relative to F1. Macronutrient balance did not affect the trajectory of change across generations in any of our three measures of body composition for either sex, but had an effect within generation on fat mass and the ratio of fat to lean mass for both sexes and on lean mass for males. Fat mass and the ratio of fat to lean mass were greater in HF than R for both sexes, and in males only the ratio of fat to lean mass was greater in LP than R and lean mass was reduced in HF and LP compared to R.
Circles represent R, squares represent HF and triangles represent LP, where body composition and nutrient intake values are means ± SEM, and nutrient conversion efficiency values are estimated marginal means ± SEM. *effect of generation, #effect of dietary group. Results of the corresponding statistical analyses are shown in Table 2.
Calorie intake was also non-consistent across generations for both sexes (Table 2, Fig 3G and 3H), with F2 and F3 consuming fewer calories than F1. In females only, F2 consumed fewer calories than F3. Macronutrient balance did not affect the trajectory of change in food intake across generations for either sex, but did have a within-generation effect for both sexes, where HF and LP consumed more calories than R.
Food conversion efficiency
The conversion efficiency of ingested protein to body lean mass was non-consistent across generations for both sexes (Table 2, Fig 3I and 3J). In both sexes, this efficiency was greater in F2 and F3 relative to F1, and in males this efficiency was also greater in F3 relative to F2. Macronutrient balance did not affect the trajectory of change across generations, but did have a sex-dependent effect within generation, where in males HF had reduced efficiency compared to R and in females LP had greater efficiency than R.
The conversion efficiency of ingested carbohydrate and fat to body fat mass was non-consistent across generations for males only, where it was reduced in F3 relative to F2 (Table 2, Fig 3K and 3L). Macronutrient balance did not affect the trajectory across generations, but had a sex-dependent effect within generation, where in males LP had reduced efficiency compared to R and in females HF had greater efficiency than R.
Based on epidemiological and experimental models of transitory environmental changes, it is probable that perturbing the environment of the parents will increase the risk of chronic disease in first generation offspring by generating an adipogenic phenotype . An important question, however, is whether this phenotype will persist across generations if the environment remains unaltered in the transitioned state? One possibility is that the phenotype might persist across generations if on-going exposure to the transitioned state recreates the same response in each generation. Alternatively, the phenotype may not persist across generations if epigenetic inheritance affects the way successive generations respond to the transitioned environment.
In the present study we demonstrate that following an environmental transition in the parental generation, when successive generations of rat offspring are maintained under constant conditions in the transitioned environment the phenotype is not stable across generations. This instability across generations involves changes in body composition, calorie intake and nutrient conversion efficiencies, all of which are factors in the development of obesity and its co-morbidities. While transgenerational effects on phenotype have previously been reported in offspring following a transitory maternal environmental perturbation [10, 12, 15, 16], this is the first time, to our knowledge, that they have been shown to occur when offspring are maintained in the transitioned environment rather than reverting to pre-transition conditions. This is a critical point of difference for two reasons. First, our design bears more relevance to the human scenario in which populations worldwide are transitioning to and have subsequently continued to experience obesogenic environments. Second, with our design we are able to address the question of whether phenotypes can adapt to being maintained in the transitioned environment .
The change in offspring phenotype in this study involved a reduction in adiposity (ratio of fat to lean body tissue) and a reduction in appetite (calorie intake) across successive generations following the parental environmental transition. To interpret this response trajectory, since we were not able to measure the difference in phenotype between the parental generation and their first generation offspring, we refer to the studies of transitory maternal environmental perturbations. These studies, reviewed by [1, 3], highlight an increase in susceptibility to chronic disease in the adult offspring of mothers who experienced an environmental perturbation. Based on this outcome, we can assume that the first generation offspring in the present study had greater susceptibility to nutrition-related, chronic disease relative to animals whose parents did not experience an environmental transition. Therefore, in the present study an increase in adiposity and appetite across successive offspring generations would suggest an exacerbation of this high-risk phenotype, while a reduction in adiposity and appetite across generations would suggest an amelioration of the high-risk phenotype. Our results corresponded with the latter scenario, in which a reduction in adiposity and appetite with time and experience in the transitioned environment represents an amelioration of disease risk.
Interestingly, the trajectories of change in these phenotypes did not differ significantly between the three dietary lineages (reference, high fat and low protein). This suggests that the transgenerational pattern of change was related to the change in environment and/or purified nature of the transitioned diet but independent of the macronutrient balance of the transitioned diet. The respective roles that the change in environment and the change in nutrition played in inducing the initial transgenerational response have yet to be fully elucidated. We can infer that the change in nutrition must have played a role because rats that have relocated from the supplier’s facility to our research facility that are fed a grain-based diet in our facility do not typically become fat and show a consistent growth profile over success generations. It is however possible that nutrition interacted with the relocation-induced stress to exacerbate the impact of the obesogenic diets . Chronic stress is associated with hyperphagia in humans [35, 36], and in migrant populations has been implicated as a factor that interacts with the availability of processed foods to generate obesity [37, 38]. In the rat, it has been shown that mild stress in the presence of food can lead to hyperphagia and obesity [39–41].
The reduction in adiposity across generations shown by rats in this study was the product of both a decline in absolute fat mass and an increase in lean mass. The decline in food intake concomitant with change in body composition accounted for the decline in body fat mass in females, while males also showed a reduction in the conversion efficiency of ingested carbohydrate and fat to body fat mass, possibly achieved by changes in diet-induced thermogenesis . For both sexes, the increase in body lean mass over this same period during which food intake declined suggests a significant increase in the conversion efficiency of ingested protein to body lean mass. Further work is needed to determine how this was achieved and thus whether or not the same is possible in humans. Possible mechanisms that may also apply to humans include changes in the extent and rate of intestinal absorption of dietary protein, or changes in the fraction of the amino acid load that contributes to structural/functional protein needs versus oxidation or gluconeogenesis . Lastly, while the transgenerational pattern of phenotypic change was independent of the macronutrient balance of the transitioned diet, it is worth emphasising that macronutrient balance did elicit within-generation effects. For instance, appetite appeared greater in rats fed the high fat and low protein diets and adiposity was greater in rats fed the high fat diet compared to those fed the reference diet, as may be generally expected .
Epigenetic inheritance is the most likely mechanism for the change in phenotype observed across generations in the present study. Due to the timescale of our experiment, the possibility of progressive or reversible changes in DNA methylation or microRNA profiles may be some of the molecular epigenetic factors underlying the trans-generational physiological alterations we observed. An example of this has been reported for fly development whereby a wide range of mechanisms (some epigenetically inherited) were shown to develop to cope with recurrent environmental challenges . A further example was that of recent work by Li et al. which showed that a sustained dietary change (excess dietary methyl donors) increased epigenetic variation in isogenic mice . Further, there are also a number of proximate mechanisms that may be involved, such as transmeiotic epigenetic mechanisms, changes to female body condition (e.g. uterus size, hormonal balance etc.) or an aspect of lactation.
A further mechanism that may be involved is changes to the gut microbiota. Gut microbiota has the potential to modulate obesity through rates of fermentation and energy extraction as well as other microbially modulated mechanisms . For example, studies with mice where the gut microbiota of obese mice and lean controls was transplanted into germ-free recipients have shown that mice receiving the gut microbiota from obese donors gained significantly more body fat than the mice receiving the lean microbiota [48–50]. Which proximate mechanisms were involved in the transgenerational response found in this study is an interesting question which may be answered in future independent studies.
If our results do represent a form of adaptation to the transitioned environment, this would align with considerations of developmental plasticity and in particular the concept of predictive adaptive responses (PARs) [51–53]. The PARs hypothesis proposes that the degree of mismatch between the pre- and postnatal environment is a major determinant of subsequent disease. Thus, it is thought that whilst adaptive changes in fetal physiological function may be beneficial for short term survival in utero, these changes may be maladaptive in postnatal life and contribute to poor health outcomes particularly when offspring are exposed to catch-up growth, diet-induced obesity and other environmental factors. These so-called PARs therefore are proposed to be not merely side-effects of altered growth in utero, but are a strategy designed to optimise the physiology of the offspring for the postnatal environment it is most likely to experience, that is, the ‘predicted’ environment. As an example, suboptimal fetal nutrition may lead to metabolic adaptations which act to maximally utilise limited nutrient availability and therefore increase the chances of survival in continued poor conditions after birth. However these adaptations serve to increase the risk for metabolic disorders when exposed to an enriched postnatal nutrient environment. The risk of chronic disease can therefore be increased in offspring when their anticipated and realised environments are widely discrepant (which may occur if there is a perturbation in the nutritional environment), and their phenotype is inappropriate for the actual environment encountered [51–53]. An extension of this model is that following a permanent change in environmental conditions, experience with the new conditions will accumulate across generations so that the maternal state and thus offspring responses become increasingly appropriate for (and adapted to) the new conditions. The PARS framework also aligns with the work by Vyssotski et al. re the notion of epigenetic compensation whereby stresses in one generation can lead to compensatory physiological responses in the next generation .
A pressing question is whether and how the work presented here can be translated to the human setting. The nutritional transition applied to the parental generation of rats in our study i.e. a switch from a grain-based, unrefined diet to a refined-ingredient, high sugar, high fat or low protein diet, is characteristic of the human nutritional transition [55, 56], both in relation to dietary change within societies and the now frequent migration between societies. If successive generations of people were to respond to the transitioned environment in a similar manner to that observed in the present rodent study, this trajectory of change in phenotype would likely represent a shift towards a metabolic phenotype that would present a lower risk of chronic disease in later life.
S1 Fig. (a) Maternal weight gain and (b) calorie intake in pregnancy, litter size (c) and maternal calorie intake in lactation (d)(not measured for F1).
Circles represent R, squares represent HF and triangles represent LP, where values are means ± SEM. ^F2>F1; %HF and LP > R. Results of the corresponding statistical analyses are shown in S3 Table.
S2 Fig. Body weights in four consecutive generations of male and female rat offspring of normal pregnancies fed a standard chow diet throughout life and housed under standard conditions.
n = minimum of 6 litters per group. Data are shown as means ± SEM.
S1 Table. Matings, births and neonatal survival.
S2 Table. Sample sizes for post-weaning measures.
We thank Kylie Wright and Lara Kimble for their assistance with the animal work and Joanna Stewart for her assistance with the statistical analyses.
Conceived and designed the experiments: AHT DR MHV PDG. Performed the experiments: AHT MHV MPG CLC. Analyzed the data: AHT DR MHV MPG. Contributed reagents/materials/analysis tools: AHT DR MHV PDG MPG CLC. Wrote the paper: AHT DR MHV MPG.
- 1. Langley-Evans SC, Bellinger L, Sculley D, Langley-Evans A, McMullen S. Manipulation of the maternal diet in rat pregnancy: Different approaches to the demonstration of the programming principle Adv Exp Med Biol. 2006;573:87–102.
- 2. McMillen IC, Robinson JS. Developmental origins of the metabolic syndrome: prediction, plasticity, and programming. Physiol Rev. 2005;85(2):571–633. pmid:15788706.
- 3. Armitage JA, Taylor PD, Poston L. Experimental models of developmental programming: consequences of exposure to an energy rich diet during development. J Physiol. 2005;565(Pt 1):3–8. pmid:15695245.
- 4. Howie GJ, Sloboda DM, Kamal T, Vickers MH. Maternal nutritional history predicts obesity in adult offspring independent of postnatal diet. J Physiol. 2009;587(Pt 4):905–15. Epub 2008/12/24. pmid:19103681.
- 5. Buckley AJ, Keseru B, Briody J, Thompson M, Ozanne SE, Thompson CH. Altered body composition and metabolism in the male offspring of high fat-fed rats. Metabolism. 2005;54(4):500–7. pmid:15798958.
- 6. Petry CJ, Dorling MW, Pawlak DB, Ozanne SE, Hales CN. Diabetes in old male offspring of rat dams fed a reduced protein diet. Int J Exp Diabetes Res. 2001;2(2):139–43. pmid:12369717.
- 7. Taylor PD, McConnell J, Khan IY, Holemans K, Lawrence KM, Asare-Anane H, et al. Impaired glucose homeostasis and mitochondrial abnormalities in offspring of rats fed a fat-rich diet in pregnancy. Am J Physiol Regul Integr Comp Physiol. 2005;288(1):R134–9. Epub 2004/09/25. pmid:15388492.
- 8. Vickers MH, Breier BH, Cutfield WS, Hofman PL, Gluckman PD. Fetal origins of hyperphagia, obesity, and hypertension and postnatal amplification by hypercaloric nutrition. Am J Physiol Endocrinol Metab. 2000;279(1):E83–7. Epub 2000/07/14. pmid:10893326.
- 9. Drake AJ, Walker BR, Seckl JR. Intergenerational consequences of fetal programming by in utero exposure to glucocorticoids in rats. Am J Physiol Regul Integr Comp Physiol. 2005;288(1):R34–8. Epub 2004/06/05. pmid:15178540.
- 10. Burdge GC, Slater-Jefferies J, Torrens C, Phillips ES, Hanson MA, Lillycrop KA. Dietary protein restriction of pregnant rats in the F0 generation induces altered methylation of hepatic gene promoters in the adult male offspring in the F1 and F2 generations. Br J Nutr. 2007;97(3):435–9. Epub 2007/02/23. pmid:17313703.
- 11. Gluckman PD, Hanson MA, Beedle AS. Non-genomic transgenerational inheritance of disease risk. Bioessays. 2007;29:145–54. pmid:17226802
- 12. Jimenez-Chillaron JC, Isganaitis E, Charalambous M, Gesta S, Pentinat-Pelegrin T, Faucette RR, et al. Intergenerational transmission of glucose intolerance and obesity by in utero undernutrition in mice. Diabetes. 2009;58:460–8. pmid:19017762
- 13. Drake AJ, Liu L. Intergenerational transmission of programmed effects: public health consequences. Trends Endocrin Metab. 2010;21(4):206–13.
- 14. Drake AJ, Walker BR. The intergenerational effects of fetal programming: non-genomic mechanisms for the inheritance of low birth weight and cardiovascular risk. J Endocrinol. 2004;180:1–16. pmid:14709139
- 15. Harrison M, Langley-Evans SC. Intergenerational programming of impaired nephrogenesis and hypertension in rats following maternal protein restriction during pregnancy. Brit J Nutr. 2009;101:1020–30. pmid:18778527
- 16. Benyshek DC, Johnston CS, Martin JF, Ross WD. Insulin sensitivity is normalized in the third generation (F3) offspring of developmentally programmed insulin resistant (F2) rats fed an energy-restricted diet. Nutr Metab. 2008;5:26–31. pmid:18928547
- 17. Gluckman PD, Hanson MA, Buklijas T, Low FM, Beedle AS. Epigenetic mechanisms that underpin metabolic and cardiovascular diseases. Nat Rev Endocrinol. 2009;5(7):401–8. Epub 2009/06/03. pmid:19488075
- 18. Gluckman PD, Hanson MH, Low FM. The role of developmental plasticity and epigenetics in human health. Birth Defects Res, Part C. 2011;93:12–8.
- 19. Malik VS, Willett WC, Hu FB. Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol. 2013;9:13–27. pmid:23165161
- 20. Hawkes C. Uneven dietary development: linking the policies and processes of globalization with the nutrition transition, obesity and diet-related chronic diseases. Global Health. 2006;2:4. pmid:16569239
- 21. Kearney J. Food consumption trends and drivers. Philo Trans R Soc Lond B Biol Sci. 2010;365:2793–807. pmid:20713385
- 22. Popkin BM. Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. Am J Clin Nutr. 2006;84:289–98. pmid:16895874
- 23. Fuster V, Kelly BB. Promoting Cardiovascular Health in the Developing World: A Critical Challenge to Achieve Global Health. Fuster V, Kelly BB, editors: The National Academies Press; 2010.
- 24. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet. 2011;377:557–67. pmid:21295846
- 25. Delavari M, Sonderlund AL, Swinburn B, Mellor D, Renzaho A. Acculturation and obesity among migrant populations in high income countries—a systematic review. BMC Public Health. 2013;13(458). pmid:23663279
- 26. Popkin BM. Contemporary nutritional transition: determinants of diet and its impact on body composition. Proc Nutr Soc. 2011;70:82–91. pmid:21092363
- 27. Rutten AA, de Groot AP. Comparison of cereal-based diet with purified diet by short-term feeding studies in rats, mice and hamsters, with emphasis on toxicity characteristics. Food Chem Toxicol. 1992;30(7):601–10. Epub 1992/07/01. pmid:1521834.
- 28. Welch CC, Kim EM, Grace MK, Billington CJ, Levine AS. Palatability-induced hyperphagia increases hypothalamic Dynorphin peptide and mRNA levels. Brain Res. 1996;721:126–31. pmid:8793092
- 29. Lien EL, Boyle FG, Wrenn JM, Perry RW, Thompson CA, Borzelleca JF. Comparison of AIN-76A and AIN-93G diets: a 13-week study in rats. Food Chem Toxicol. 2001;39(4):385–92. Epub 2001/04/11. pmid:11295485.
- 30. Anastasia JV, Brauna BL, Smith KT. General and histopathological results of a two-year study of rats fed semi-purified diets containing casein and soya protein. Food Chem Toxicol. 1990;28:147–56. pmid:2344989
- 31. Raubenheimer D, Simpson SJ. The geometry of compensatory feeding in the locust. Anim Behav. 1993;45:953–64.
- 32. Raubenheimer D, Simpson SJ. The analysis of nutrient budgets. Functional Ecology. 1994;8(6):783–91. pmid:BACD199598089942 Copyright BIOSIS 2003.
- 33. Jablonka E, Raz G. Transgenerational epigenetic inheritance: prevalence, mechanisms, and implications for the study of heredity and evolution. Q Rev Biol. 2009;84:131–76. pmid:19606595
- 34. Sinha R, Jastreboff AM. Stress as a common risk factor for obesity and addiction. Biol Psychiatry. 2013;73:827–35. pmid:23541000
- 35. Jaremka LM, Belury MA, Andridge RR, Malarkey WB, Glaser R, Christian L, et al. Interpersonal stressors predict ghrelin and leptin levels in women. Psychoneuroendocrinology. 2014;48:178–88. Epub 2014/07/18. pmid:25032903; PubMed Central PMCID: PMCPMC4117712.
- 36. Andrews ZB, Abizaid A. Neuroendocrine mechanisms that connect feeding behavior and stress. Frontiers in neuroscience. 2014;8:312. Epub 2014/10/18. pmid:25324716; PubMed Central PMCID: PMCPMC4181285.
- 37. Delavari M, Farrelly A, Renzaho A, Mellor D, Swinburn B. Experiences of migration and the determinants of obesity among recent Iranian immigrants in Victoria, Australia. Ethnicity & health. 2013;18(1):66–82. Epub 2012/06/26. pmid:22724556.
- 38. Kaplan SA, Ahmed R, Musah A. "When you walk in the rain, you get wet": a qualitative study of Ghanaian immigrants' perspective on the epidemiological paradox. Journal of immigrant and minority health / Center for Minority Public Health. 2015;17(1):255–62. Epub 2013/07/25. pmid:23881531.
- 39. Wardle J. Eating behaviour and obesity. Obes Rev. 2007;8(Suppl. 1):73–5. pmid:17316306
- 40. Tamashiro KLK, Hegeman MA, Nguyen MMN, Melhorn SJ, Ma LY, Woods SC, et al. Dynamic body weight and body composition changes in response to subordination stress. Physiol Behav. 2007;91:440–8. pmid:17512562
- 41. Morley JE, Levine AS, Rowland NE. Stress induced eating. Life Sciences. 1983;32:2169–82. pmid:6341739
- 42. Stock MJ. Gluttony and thermogenesis revisited. Int J Obes Relat Metab Disord. 1999;23(11):1105–17. Epub 1999/12/01. pmid:10578199.
- 43. Bilsborough S, Mann N. A review of issues of dietary protein intake in humans. Int J Sport Nutr Exerc Metab. 2006;16:129–52. pmid:16779921
- 44. Simpson SJ, Raubenheimer D. Obesity: the protein leverage hypothesis. Obes Rev. 2005;6(2):133–42. Epub 2005/04/20. pmid:15836464.
- 45. Stern S, Fridmann-Sirkis Y, Braun E, Soen Y. Epigenetically heritable alteration of fly development in response to toxic challenge. Cell reports. 2012;1(5):528–42. Epub 2012/07/27. pmid:22832276.
- 46. Li CC, Cropley JE, Cowley MJ, Preiss T, Martin DI, Suter CM. A sustained dietary change increases epigenetic variation in isogenic mice. PLoS genetics. 2011;7(4):e1001380. Epub 2011/05/05. pmid:21541011; PubMed Central PMCID: PMCPMC3080854.
- 47. Bäckhed F. Programming of Host Metabolism by the Gut Microbiota. Ann Nutr Metab. 2011;58(suppl 2):44–52. pmid:21846980
- 48. Turnbaugh PJ, Bäckhed F, Fulton L, Gordon JI. Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe. 2008;3:213–23. pmid:18407065
- 49. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444:1027–31. pmid:17183312
- 50. Vijay-Kumar M, Aitken JD, Carvalho FA, Cullender TC, Mwangi S, Srinivasan S, et al. Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5. Science. 2010;328:228–31. pmid:20203013
- 51. Bateson P. Fetal experience and good adult design. Int J Epidemiol. 2001;30(5):928–34. pmid:11689495.
- 52. Bateson P, Barker D, Clutton-Brock T, Deb D, D'Udine B, Foley RA, et al. Developmental plasticity and human health. Nature. 2004;430(6998):419–21. pmid:15269759.
- 53. Gluckman PD, Hanson MA. Living with the past: evolution, development, and patterns of disease. Science. 2004;305(5691):1733–6. Epub 2004/09/18. pmid:15375258.
- 54. Vyssotski DL. Transgenerational epigenetic compensation: Heritable compensation of disturbed functionality. Evolocus. 2011;1:1–6.
- 55. Drewnowski A. The real contribution of added sugars and fats to obesity. Epidemiol Rev. 2007;29:160–71. Epub 2007/06/27. pmid:17591599.
- 56. Popkin BM, Gordon-Larsen P. The nutrition transition: worldwide obesity dynamics and their determinants. Int J Obes Relat Metab Disord. 2004;28 Suppl 3:S2–9. pmid:15543214.