Research into ‘the developmental origins of adult health and disease’ has made considerable progress over the past two decades, but a clear consensus on the exact nutrients involved and their mechanisms remains to be established. This problem relates, in part, to the long-term developmental time frame in which changes in metabolism and cardiovascular function occur. At the same time, the discipline has had to contend with the dual challenges of integrating findings from lifetime epidemiological studies that have largely focused on birth weight and its relationship (or otherwise) with adult disease and the ability to incorporate these results into appropriate nutritional intervention studies using animal models. It is now established that there are many potential influences on offspring outcome, including maternal body composition, age and parity, genetic constitution and macro- and micronutrient intake and handling, size, shape and number of offspring, their gender and type of lactational diet. Thus, it is not unexpected that as knowledge of the intricacies involved expands, a substantive number of publications have, in retrospect, been misleading because of inappropriate statistical analysis and/or mismatches in the different groups (of which some key examples will be summarised).

In the present brief review an attempt will be made to provide an overview of some of the major challenges for both human and animal studies, in conjunction with optimal experimental paradigms that may be utilised in future research aimed at elucidating the precise mechanisms by which changes in the maternal diet during reproduction can impact on the lifetime health of resulting offspring. Particular emphasis will be given to the applicability of the animal model that has been utilised and how similarities in the reproductive process may enable its best use in future examinations of the nutritional programming of adult health and disease.

Animal models of nutritional programming

The main animal models that have been utilised to date to investigate the impact of maternal diet on long-term programming have been rats and sheep⁽Reference McMillen and Robinson¹⁷⁾. These animals obviously have very different developmental patterns in the relationship between placental and fetal growth, maturity at birth and milk composition⁽Reference Prentice and Prentice¹⁸⁾. The advantage of utilising rats is their very short gestational length. However, the type of diet they normally consume in the wild is very different from that fed to housed laboratory animals in which semi-purified diets are the norm. Such diets provide substantially greater differences in nutrients to pregnant rats than to controls and, therefore, should be considered ‘pharmacological’ as opposed to ‘physiological’ as they are outside the normal distribution of wild-type diets. For example, high-fat diets utilised to date in rat studies contain four times as much fat when compared with control diets and are at risk of being deficient in micronutrients. Not surprisingly, when fed a diet so rich in fat, maternal food intake is reduced⁽Reference Taylor, McConnell and Khan¹⁹⁾. In addition, rats exhibit coprophagia, which has a substantial effect on nutrient flux and the ability to experimentally manipulate the intake of specific nutrients.

Appreciable placental growth necessarily continues up to term in the rat to meet the much higher protein demands for fetal growth compared with that of man or sheep⁽Reference Widdowson²⁰⁾. In large mammals, however, the maximal period of placental growth is early in pregnancy in order to meet the greatly increased nutrient requirements of the fetus in late gestation when its growth is exponential⁽Reference Symonds, Budge and Mostyn²¹⁾. Furthermore, rats produce large litters whereas sheep and man only normally produce one (or two) offspring of comparable birth weight per pregnancy.

Comparative differences in organ development

Another substantive difference between rats and man (and rats and sheep) is that the development and maturation of the hypothalamic–pituitary system occurs after birth during the neonatal period in rats compared with during late gestation in sheep and man. Thus, any nutritional intervention that stops at birth in the rat will have substantially different outcomes compared with those extending into the neonatal period⁽Reference Symonds⁹⁾. Other organs that continue to develop postnatally in the rat, compared with prenatally in sheep and man, include the kidney and brown adipose tissue⁽Reference Symonds, Stephenson and Gardner⁶⁾ (Fig. 1). For example, in those species born with a mature hypothalamic–pituitary axis after a long gestation, such as in sheep and man, the majority of the appetite-controlling networks appear to be in place by mid- to late gestation⁽Reference Mühlhäusler, McMillen and Rouzaud²²⁾. This position is clearly in contrast to that in small mammals in which there is substantial development during the lactational period as the hypothalamic axis matures. It is thus not unexpected that leptin administration has such a marked effect on this process⁽Reference Bouret, Draper and Simerly²³⁾ and related processes⁽Reference Vickers, Gluckman and Coveny^24, Reference Attig, Solomon and Ferezou²⁵⁾, which are not seen when given to the late-gestation fetus or neonatal sheep⁽Reference Mostyn, Bispham and Pearce^26, Reference Yuen, Owens and Mühlhäusler²⁷⁾. Indeed, there is no postnatal leptin surge in either sheep⁽Reference Bispham, Budge and Mostyn²⁸⁾ or man⁽Reference Matsuda, Yokota and Iida²⁹⁾.

Fig. 1.

Summary of the ontogenic differences in development and maturation of the hypothalamus and kidney in relation to pre- and postnatal growth trajectories between large (including man) and small animals.

Nephron development occurs primarily after birth, as does brown fat, which in sheep and man was originally thought to be completely lost in the postnatal period⁽Reference Lean³⁰⁾, but is retained throughout the life cycle in the rodent. As such, brown adipose tissue has a fundamental impact on the energy balance of adult rats because it uniquely possesses uncoupling protein 1 and is thus able to rapidly generate large amounts of heat⁽Reference Cannon and Nedergaard³¹⁾. Indeed, brown fat has a pivotal role in the regulation of thermogenesis, with a thermogenic potential of 300 W/g whilst all other tissues generate approximately 1 W/g⁽Reference Power³²⁾. Not unexpectedly, loss of uncoupling protein 1 is accompanied by an increase in fat mass, making it difficult to dissociate the dietary and related effects on changes in fat mass from adaptations in uncoupling protein 1 in this species⁽Reference Mostyn, Keisler and Webb³³⁾. Recently, indirect measurements in patients with cancer suggest that brown fat may be retained in small amounts in these individuals⁽Reference Nedergaard, Bengtsson and Cannon³⁴⁾. Its location is, however, primarily in the neck region⁽Reference Christensen, Clark and Morton^35, Reference Goetze, Lavely and Ziessman³⁶⁾ and whether it has any functional importance in energy balance remains to be established.

Methodological considerations in the interpretation of metabolic programming

There have been two major problems with rat studies utilised in the assessment of long-term cardiovascular outcomes. First, in many studies blood pressure has only been measured using the tail-cuff technique in restrained and heated animals during the day when they are normally inactive, being nocturnal animals (for example, see Langley-Evans⁽Reference Langley-Evans³⁷⁾; Kwong et al.⁽Reference Kwong, Wild and Roberts³⁸⁾). It is recognised that this approach can give very different results when compared with blood pressure measurements obtained using telemetry⁽Reference D'Angelo, Elmarakby and Pollock³⁹⁾; as such, it is only recommended for use in obviously hypertensive animals in which the technique was originally validated⁽Reference Bunag⁴⁰⁾. Thus, in the majority of studies in which it has been used in this area the tail-cuff technique is not informative in relation to the modest differences in blood pressure recorded in such normotensive rats. This factor may explain why in more recent studies the offspring born to dams fed a low-protein high-carbohydrate diet through pregnancy show either no difference or a reduction in blood pressure when measured using either telemetry or an indwelling arterial catheter⁽Reference Fernandez-Twinn, Ekizoglou and Wayman^41, Reference Hoppe, Evans and Moritz⁴²⁾. Comparable findings are seen in offspring born to dams in which food intake is reduced by 50% through pregnancy compared with controls⁽Reference Brennan, Kaufman and Reynolds⁴³⁾. A further confounding factor in many of these early studies has been a failure to consider the dam as the experimental unit rather than her offspring⁽Reference Kwong, Wild and Roberts³⁸⁾, which is now recommended as standard practice⁽Reference Festing⁴⁴⁾. There also appears to be a marked divergence in the long-term outcomes between genders in rats that is primarily linked to the faster, as well as continued, growth of males compared with females⁽Reference Symonds and Gardner⁴⁵⁾.

Despite the fact that sheep are ruminants, they have proved invaluable in enabling the understanding of the nutritional and endocrine regulation of placento–fetal development. As in man, the primary metabolic substrate for fetal metabolism is glucose, for which GLUT 1 is the main placental regulator⁽Reference Dandrea, Wilson and Gopalakrishnan⁴⁶⁾. Glucose is thus transported across the placenta by active diffusion determined by its concentration in maternal blood⁽Reference Edwards, Symonds and Warnes⁴⁷⁾. In addition, not only does kidney development show a very similar ontogeny in sheep and man, but the distribution of total nephrons across the adult population is comparable⁽Reference Symonds, Budge, Mostyn and Watkins⁴⁸⁾. It is also feasible to obtain very consistent blood pressure recordings in the offspring using arterial cannulation whilst the animal is standing freely with continual access to its diet⁽Reference Gardner, Pearce and Dandrea⁴⁹⁾. At the same time, there is no discernable difference in blood pressure control or glucose regulation between genders when measured in intact adult sheep⁽Reference Symonds, Budge, Mostyn and Watkins^48, Reference Gardner, Tingey and van Bon⁵⁰⁾.

Mismatched offspring and later outcomes?

Another confounding factor that has become apparent in a number of recent studies using sheep is a mismatch between the numbers of singletons and twins between nutritional groups. This mismatch has introduced erroneous conclusions, which is not unexpected given the pronounced differences in outcomes of human newborns that are also dependent on fetal number⁽Reference Hayes, Paul and Ness⁵¹⁾. Appropriate statistical correction (as in the case of rat studies) for this factor is therefore necessary⁽Reference Festing⁴⁴⁾. Some of the more prominent examples of such mismatch between control and intervention groups are summarised in Table 1. Indeed, this mismatch is further confounded by using both twins from the same mother for whom the lactational environment will be further altered. In contrast, when one twin is reared alone by its mother, its growth rate matches that of a singleton, as does its later blood pressure control and glucose homeostasis⁽Reference Gardner, Tingey and van Bon^50, Reference Gopalakrishnan, Gardner and Dandrea⁵²⁾.

Table 1.

Summary of studies into nutritional programming in which outcome measures are potentially confounded by a mismatch between groups in their composition of offspring from singleton and twin pregnancies

It is now clear that future studies in the area will need to take into account not only changes in diet through pregnancy but also the relative contributions of gender, litter size, type and duration of lactation as well as weaning diets. These considerations will undoubtedly increase the time necessary to conduct such studies as well as their cost, but it is imperative that with the plethora of nutritional models already established these factors are optimised in order to elucidate the main pathways involved rather than pursuing models that may have little translational relevance⁽Reference Symonds, Stephenson and Budge⁵³⁾.