Nutrition

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REVIEW ARTICLE

How growth due to infant nutrition influences obesity and later disease risk Brigitte Brands, Hans Demmelmair, Berthold Koletzko ([email protected]), for the EarlyNutrition Project Dr. von Hauner Children’s Hospital, University of Munich Medical Centre, Munich, Germany

Keywords Early nutrition, Growth, Infant nutrition, Metabolic programming, Obesity

Correspondence Berthold Koletzko, Dr med Dr med habil MD, PhD, University-Professor of Paediatrics, Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children’s Hospital, University of Munich Medical Center, Lindwurmstr. 4, D-80337 Munich, Germany. Tel: +49 89 5160 2826 | Fax: +49 89 5160 7742 | Email: [email protected]

Received 2 July 2013; revised 11 January 2014; accepted 5 February 2014.

DOI:10.1111/apa.12593

ABSTRACT Infant nutrition has a major impact on immediate outcomes and long-term health and later

disease risks, such as obesity and related disorders, a phenomenon referred to as

‘metabolic programming’. This review discusses the currently postulated hypotheses and

mechanisms investigated by the EarlyNutrition project.

Conclusion: Rapid weight gain in the first 2 years of life, most notably mediated by diary protein, affects the insulin-like growth factor metabolic pathways. Epigenetic processes

seem to play a role.

INTRODUCTION Obesity rates have dramatically increased during the last decades, especially in childhood. Obesity is not only an adverse condition in itself, but it is also a prelude for many other noncommunicable diseases in later life, such as diabetes mellitus, metabolic syndrome and cardiovascular disease. This is not just true for developed countries, it is becoming increasingly dramatic in developing countries as well, where societies undergo a rapid socioeconomic tran- sition that results in the coexistence of both under-nutrition and over-nutrition (1). Data collected by the International Association for the Study of Obesity in 2012 highlight particular concerns about the high prevalence of childhood obesity in the different World Health Organisation (WHO) regions, with the highest percentage, of about 9%, in the Region of the Americas (Fig. 1). The economic burden associated with this obesity epidemic is dramatic (2).

Accumulating evidence suggests that being overweight or obese at 5 years of age predicts later obesity risk and associated disorders. Therefore, research into early-life factors associated with obesity risk has gained wide interest in recent years. Early-life prenatal and postnatal experi- ences are thought to induce permanent changes in the infant’s physiological functions, putting the body at risk of metabolic disorders (3,4), a phenomenon referred to as metabolic programming and first observed nearly 40 years ago (5). Among these early-life incidences, nutrition during pregnancy and infancy plays vital roles.

According to a recent systematic review and meta- analysis of prospective observational studies following up children from birth for at least 2 years, the strongest associations for childhood overweight were determined to

be maternal overweight, high infant birthweight and rapid weight gain during the first 12 months of life (6). This is consistent with a previous review by Brisbois et al. in 2011, which aimed to identify evidence-based early markers for obesity by evaluating studies with data from at least two time points in life (childhood ≤ 5 years of age; adulthood ≥ 18 and ≤ 50 years of age). The authors determined that of the 42 evaluated variables, infant growth patterns, in the form of early rapid growth and early adiposity rebound, was one of the seven most important variables for future preventative strategies in developed countries (7). These and other important factors associated with, or predictive for, adult obesity such as maternal smoking, body mass index (BMI) and pregnancy weight gain were also previ- ously identified by a comprehensive review of systematic reviews by Monasta et al. (8). Today, there is an evidence- based consensus that the prenatal and postnatal phases are key time points in the programming of later obesity. As

Key notes � The relationship between infant nutrition and growth in

the first 2 years, and later risks of obesity and associ- ated disorders is currently unclear.

� It is suggested that dairy protein influences insulin-like growth factor I concentrations in infancy and is asso- ciated with such programming effects, while epigenetic processes play an underpinning role.

� Further research is needed to unravel the exact mech- anistic pathways and provide a sound evidence base for practice recommendations.

Acta Pædiatrica ISSN 0803-5253

obesity may be programmed prenatally and during early infancy, preventive measures should be implemented at preconception, during pregnancy and throughout early childhood. Yet, there have been few intervention studies that have aimed to counteract the paediatric obesity epidemic in early life and they have so far failed to clearly determine effective methods of prevention (9). In particular, targeting infant populations would provide a unique oppor- tunity to counteract early programming events for obesity and associated disorders. However, intervention studies in this age group are very rare and demonstrate mixed outcomes (10). Although research has identified promising early marker candidates, there is currently insufficient evidence to isolate the strongest targets for effective and efficient intervention.

The present review aims to provide an update on selected research into the metabolic programming of obesity through infant nutrition and growth in the postnatal phase. Physiological aspects and postulated mechanisms are also discussed.

THE ROLE OF RAPID GROWTH IN INFANCY Both high birthweight and high weight gain in the first 2 years of life are associated with increased risk for later obesity (11). In addition to an increased obesity risk, high weight gain in the first 2 years of life is associated with a variety of other late-onset adverse health outcomes (12), such as increased risk of high blood pressure (13), increased body fat deposition (14), less favourable lipoprotein profiles (15) and diabetes (16). Although past studies have applied a wide range of indicators to define rapid growth and overweight or obesity, reviews and meta-analyses have, to date, all shown a strong and consistent association between rapid weight gain and an increased risk of obesity (6,17,18). The so-called Accelerated Weight Gain Hypothesis con- tends that rapid growth in the first or second year of life has a programming effect on the later risk of obesity and related disorders. Evidence shows that rapid weight gain may be an

early-programmed physiological adaptation resulting from previously experienced in utero growth restriction, the so- called postnatal catch-up growth. Such infants, indexed by their lower birthweight, show an increased central fat deposition and higher insulin resistance (19,20). In the case of infants born term and with a normal birthweight, a postulated trigger for accelerated weight gain may be an excess intake of growth-enhancing nutritional factors, such as protein. Moreover, it is suggested that accelerated weight gain may simply be phenotypic of a genetic marker for the later trajectory of weight gain. For example, we found early growth patterns predictive of overweight risk at school age in a study of 4235 German children aged 5–6 years who participated in the obligatory school entry health examina- tion in Bavaria, Germany. Data on early gains in weight, length, BMI and Ponderal Index were derived from the measurements taken during the preventive health care checks offered to all children at birth, 6 months, 12 months and 24 months (21). Overweight at school entry was assessed according to gender- and age-specific BMI cut- off points. When they looked at all the anthropometric measures and time intervals assessed, weight gain from birth to the age of 2 was determined to be the best predictor of overweight at school age. A recent meta-analysis by Druet et al. revealed a twofold higher risk of childhood obesity [odds ratio (OR) = 1.97 (95% confidence interval (CI) 1.83, 2.12)] and a 23% higher risk of adult obesity [OR = 1.23 (1.16, 1.30)] with every unit increase in stan- dard deviation scores between the ages of zero and one. This analysis comprised individual-level data on 47 661 participants from 10 cohort studies from the UK, France, Finland, Sweden, the United States and Seychelles (22).

While there has been a general consensus that early childhood is an important time for weight gain velocity and its association with later obesity risk, the debate is still continuing as to whether there are even more concrete and limited time frames for this programming effect (23,24). For instance, weight gain from the first weeks until 3 and 6 months has been reported to be more indicative of fat

Figure 1 Prevalence (%) of childhood obesity in the WHO regions (data from http://www.iaso.org/site_media/library/resource_images/Childhood_overweight_ and_obesity_by_Region.pdf, with permission from IASO). The table is based on measured data using the IOTF international cut-off points according to Cole et al. (61).

Brands et al. Relation between infant nutrition, growth and obesity

mass in adolescence than weight gain rates during the second half of year 1 and year 2 (25,26). Another open question is the optimal method for tracking infant weight gain velocities. While weight-for-length measurements are applied in clinical decision-making, more detailed informa- tion on body composition is required to differentiate between lean and fat mass developments which take place in different ratios at different time points during infant weight gain. It also remains unclear whether lean mass has the same predictive potential of later obesity risk as fat mass (23). As such, more reliable and accurate methods to assess body composition are essential to determine disease risk in later life due to the relatively poor predictive power of the current common measures of adiposity (body fat content) such as BMI. This issue has been recently acknowledged by an expert group meeting of the Early Nutrition Academy aimed at reconciling a standard methodology for applica- tion within the framework of the new European Union (EU)-funded research Project EarlyNutrition (www.pro- ject-earlynutrition.eu) (27). It seems conceivable that, as well as the direct relationships of fat mass, the size and distribution of fat depots are of relevance when it comes to the understanding of the association between maternal and offspring anthropometry or between early postnatal devel- opment and later obesity risk (27). The expert group identified a number of generally available measurements essential for detailed determination of anthropometry and body composition: weight, length, BMI, waist circumfer- ence, mid-upper arm circumference, subscapular and tri- ceps skinfold thicknesses, and bioelectrical impedance. Although demanding air displacement plethysmography and stabile isotope tracer dilution should be applied to determine whole body composition, dual X-ray absorpti- ometry is seen as a reference method. Imaging techniques such as ultrasound or magnetic resonance imaging are suitable for visualising regional fat distribution, but require high operator skills (27). While there remains a need for a clear evidence base of the optimal weight gain in infancy as a basis for preventive interventions, the different physio- logic starting points, such as preterm versus term infants and low versus high birth, should be taken into account when managing these different infant populations. This is also relevant in developing countries where growth faltering and stunting are further confounding variables that require dedicated approaches to determine optimal weight gain. Despite being adopted by more than 140 countries world- wide, implementation of the WHO’s 2006 updated inter- national growth standards is still pending in some countries (28). The question remains whether these global standards adequately reflect the situation in different populations and countries. This challenges clinical practice, where the evaluation of child growth trajectories and the interventions designed to improve child health depend highly on the growth charts used. For instance, analysis of longitudinal data of weight and length from 300 randomly selected full- term infants in Qatar revealed that when applying the WHO standard as a reference, more infants were identified as overweight than when the Center for Disease Control

standards released in 2000 were used (29). Infants in Qatar and in other countries such as India have shown a greater variability in terms of plus and minus standard deviation scores for weight and length, and the rate of exclusive breastfeeding is low. As infant nutrition is one of the exogenous factors shown to be associated with obesity risk, a large body of research addresses the relationship between breastfeeding versus formula feeding and its specific com- ponents on growth and later obesity.

BREASTFEEDING VERSUS FORMULA FEEDING AND OBESITY RISK Due to its proven health effects and long-term disease prevention potential, breastfeeding is considered the best practice in terms of infant feeding (30). Several health benefits have been reported, among them a protective effect against obesity and associated disorders. Although exclusive breastfeeding for 6 months was recommended by the WHO more than a decade ago, breastfeeding rates have still not reached the desired level in many parts of the world (31).

Many systematic reviews and meta-analyses of observa- tional studies have investigated the association between breastfeeding and obesity risk (32–34). Data from interven- tional studies are rare, due to the ethical limitations of randomising breastfeeding (35). Controlling for confound- ers along with the type of coding of response variables (continuous or binary) and the statistical method applied (linear, logistic or quantile regression) seem to be crucial factors in all observational studies, thus resulting in incon- sistent findings (36). We performed a meta-analysis of published epidemiological studies (cohort, case–control or cross-sectional studies) that included only those studies adjusting for at least three relevant confounding factors (birthweight, parental overweight, parental smoking, die- tary factors, physical activity and socioeconomic status/ parental education) and assessed obesity between the ages of five and 18 years (34). This analysis included nine studies totalling more than 69 000 children. The result of the meta- analysis showed that breastfeeding was associated with a significant reduction in the risk of obesity in childhood in the fixed model (adjusted OR 0.78, 95%; CI 0.71, 0.85). A dose-dependent effect of breastfeeding duration on the prevalence of obesity was reported in four of the nine studies. Funnel plot regression gave no indication of publication bias.

More recently, a Cochrane Review by Kramer and Kakuma (37) summarised the current status of research on duration of breastfeeding and health outcomes. The authors analysed 23 studies (two clinical trials, 21 observa- tional studies) conducted in both developed and developing countries. According to their updated meta-analysis, infants who are exclusively breastfed for 6 months benefit more from short-term health outcomes, such as reduced gastro- intestinal infections, while no impairments in growth, either in developed or developing countries have been observed. Examination of the long-term health benefits of exclusive breastfeeding compared to partial breastfeeding for 3 or 4 months showed no difference in the later risk of obesity

Relation between infant nutrition, growth and obesity Brands et al.

and related disorders between the two groups. Another recent meta-analysis by Weng et al. (6), covering 10 prospective studies, revealed that breastfeeding anytime in the first year reduced the odds of overweight in childhood by 15% compared to nonbreastfed infants (95% CI 0.74– 0.99; I2 = 73.3%; n = 10). A recent meta-analysis by Gale et al. in 2012 showed constantly higher fat free mass in formula-fed infants than breastfed infants during the first year of life. Fat mass was only higher in the formula-fed infants at the age of 12 months, while it was significantly lower at the earlier time points (38). This finding points at the importance of body composition and the complexity of the processes mediating the long-term effects of early growth.

We studied the relationship between breastfeeding and later overweight and obesity risk in a cross-sectional survey in Bavaria, Germany (21). Data on height and weight were obtained for 9357 children participating in the obligatory school health examination. Previously breastfed children showed a lower prevalence of both overweight (9.2 vs. 12.6%) and obesity (2.8% vs. 4.5%) than formula-fed children. Differences in social class or lifestyle could not account for the protective effect of breastfeeding. Children who had at any point been breastfed showed a significantly reduced adjusted OR for both overweight [OR 0.79 (95% CI: 0.68, 0.93)] and obesity [OR 0.75 (95% CI:0.57, 0.98)] compared to those who were never breastfed. The adjusted OR showed a significant inverse dose–response relationship between duration of breastfeeding and both overweight and obesity, which is consistent with a causal effect of breast- feeding or breast milk components on obesity reduction.

It is obvious that adequately powered intervention stud- ies would be needed to ultimately determine the causal relationships behind the inverse association between breastfeeding and obesity risk. For instance, a cluster randomised study in Belarus did cast doubt on the protec- tive effect of breastfeeding on obesity risk. The trial was performed in hospitals that were either assigned to promote breastfeeding or provide no active intervention (35). Despite the fact that intervention achieved a significantly longer duration of breastfeeding, no effect on obesity prevalence was determined at the age of six-and-a-half. It is important to note that this trial lacked sufficient statistical power to determine a protective effect of breastfeeding relative to formula feeding, as rates of breastfeeding were relatively similar in both the intervention and control groups, and the overall prevalence of obesity was low in this population (39).

While the underlying mechanisms by which breastfeeding could reduce the risk of later obesity remain unclear, a role in the physiological programming of some important signalling pathways is postulated. Overall, breastfed infants gain weight more slowly than formula-fed infants, particu- larly after 3 months of age. A likely physiological explana- tion for this association might be the observed higher plasma-insulin levels in formula-fed infants compared to breastfed infants, which may stimulate fat deposition. These higher insulin levels themselves may be triggered by the

higher protein content of infant formula and the absence of growth modulating bioactive compounds that are present in breast milk. As far back as 20 years ago, it was demon- strated that nutrients modulate endocrine systems such as the IGF axis which plays a vital role in early growth (40).

To date, overall evidence has demonstrated that breast- feeding is associated with a moderate but consistent protective effect against later obesity. These findings high- light the importance of encouraging the promotion, protec- tion and support of breastfeeding, as well as implementing ethical approaches for the marketing of breast milk substi- tutes such as infant formulae and follow-on formulae which do not undermine breastfeeding (41).

UNDERLYING MECHANISMS – THE IGF AXIS AND EARLY PROTEIN SUPPLY Human growth can be divided into three periods: growth in infancy, childhood and puberty. According to the growth model by Karlberg, these three periods underscore different mechanisms of endocrine regulation. While sex hormones are the drivers for a growth spurt in puberty, human growth hormone (hGH) is the primary stimulator of growth during childhood. Early in life, however, hGH appears to play a minor role – here the IGF axis is of major importance. Nutrients such as proteins as well as energy intake have been shown to be associated with secretion of IGF-I. A review by Larnkjaer et al. (42) summarises the different periods pre- and postnatal and when IGF-I levels are associated with foetal and infant growth. In the case of intrauterine growth restriction and preterm birth, IGF-I levels have been shown to positively correlate with the observed phase of catch-up growth. It is proposed that during infancy and childhood, the relationship between IGF-I levels and growth velocities changes, where IGF-I levels increase with age during childhood until puberty. Of particular interest are the growth patterns and IGF-I levels during infancy that seem to support the idea of a more complex pattern of growth regulation. Studies have shown changing IGF-I levels over the first month of life, from an initial increase after birth followed by a decrease from the age of 2 months until the age of 8–9 months, after which IGF-I levels again increase (Fig. 2) (42).

Research in this area has attempted to disentangle the complex metabolic and endocrine pathways from the exogenous factors acting on them. Of particular interest is dairy protein, its influence on IGF-I concentrations in infancy and thus its associated programming effect on later obesity and related disorders. On a molecular level, mTOR seems to play a central role in observable short-term effects. The evolutionarily highly conserved mTOR complex acts via its phosphorylation activity in signal transduction processes. mTOR consists of two structurally and function- ally distinct complexes (mTORC1 and mTORC2) with several functional subunits (43). Cell culture and animal studies, including experimental knockouts of mTOR subunits, showed the importance of mTOR for sensing energy and nutrient status for the regulation of anabolic and

Brands et al. Relation between infant nutrition, growth and obesity

catabolic processes (44). These experiments also identified IGF-I and amino acids as potent upstream activators of mTOR (44). Comparison of higher and lower protein infant formulas showed higher levels of essential amino acids and IGF-I as well as higher weight gain in the infants with higher protein intake (45,46). This points at the potential functional importance of mTOR for the ‘Early Protein Hypothesis’, which postulates increased weight gain in early infancy as a consequence of higher protein intake and mediation by elevated levels of IGF-I and especially branched chain amino acids (11). Moreover, a recent study by Madsen et al. (47) showed that IGF-I levels at the age of 9 months were 14% lower in infants who were still breastfed compared to infants with a shorter period of breastfeeding.

We explored the ‘Early Protein Hypothesis’ in a rando- mised clinical trial, the European Childhood Obesity Project (48). This multicentric trial was set up in study centres in five European countries, Belgium, Germany, Italy, Poland and Spain. To be eligible for inclusion in the study, participants had to be apparently healthy, term infants born from uncomplicated, singleton pregnancies. Formula-fed infants randomly and exclusively received one of the two formulae no later than from the eighth full week of life onward. Breastfed children had to be exclusively breastfed for the first 3 months. Infant formulae were replaced by follow-on formulae from the fifth month of age onwards and provided until the age of 1 year.

The lower protein (LP) and higher protein (HP) infant and follow-on formulae had an identical energy density achieved by adapting the fat content, whereas the protein contents were 1.8 g protein/100 kcal versus 2.9 g protein/ 100 kcal in the infant formulae and 2.2 g protein/100 kcal versus 4.4 g protein/kcal in the follow-on formulae. The relative contents of amino acids were practically identical in all formulae.

A reference group of 619 breastfed infants was recruited, of whom 298 children could be followed until 24 months. Complete anthropometric follow-up data at 24 months of

age were available for 313 LP infants (follow-up rate = 58%) and 323 HP infants (59%). The protein intake was significantly different between the two formula groups at all time points up to 12 months of age but not thereafter. The difference ranged between 5.5 g/day (95% CI 5.1–5.9) in the first month to 8.5 g (7.8–9.3) at 6 months. Differ- ences in weight and weight-for-length between the LP and HP formula groups emerged at 6 months of age and persisted until the end of the study period. At 24 months of age, length was not different between the intervention groups. The mean weight attained at 24 months was 12.42 kg and 12.60 kg for the lower and higher protein groups, respectively. HP led to a significantly higher BMI than LP during the intervention period from 6 months onwards as well as after the end of the intervention (Fig. 3). Interestingly, the BMI in the LP group was identical to the breastfed group at 2 years of age. The effects of the intervention were not different between the countries for any of the analysed anthropometric measures. In addition

Figure 2 Schematic course of IGF-I levels in the postnatal phase (redrawn data from Ref. (42).

BMI SD score −0.5 0.0 0.5

***

Age (months)

Figure 3 BMI standard deviation scores (SD scores) from birth to the age of 2 years in subjects participating in the European Childhood Obesity Project fed breast milk, or randomised to receive for the first year of life formulae with lower protein (LP) or higher protein (HP) contents. Formula-fed infants in the HP group showed higher BMI values than breastfed infants in infancy and at 2- years-of-age. The group randomised to LP had significantly lower BMI levels than the HP group and LP normalised BMI levels at the age of 2 years comparable to breastfed subjects. Redrawn from Ref. (60). **p < 0.01, ***p < 0.001.

Relation between infant nutrition, growth and obesity Brands et al.

to total body growth, a significant effect on kidney growth was also found (49).

Using the data from previous cohort studies, we esti- mated the potential impact of reduced protein intake in infancy on obesity in adolescence. We calculated an expected reduction in obesity prevalence at 14–16-years- of-age of 13% (48). The effects of the intervention after the early toddler age are currently explored in the longer-term follow-up study.

LONG-TERM EFFECTS ON OBESITY RISK – IS EPIGENETICS THE MISSING LINK? Based on the important findings above, there is clearly a case for manipulatable physiological mechanisms acting to alter growth in early life with long-term consequences for adult obesity. The question remains how the organism memorises these early incidences, with effects being exerted many years later and even transmitted from one generation to the next. Even though evidence clearly shows that nonmodifiable genetic factors play an important role in the early onset of obesity, these alone appear to be insufficient in explaining the rapid increase in obesity over the last decades. Moreover, the detected central role of molecular complexes in signal transduction processes such as mTOR and the concomitant short-term changes observed in metabolism and growth might not provide a full explana- tion for long-term programming of obesity risk.

The alteration of gene expression by exogenous factors, or epigenetics, has received much attention in recent years. Epigenetics refers not only to reversible changes but also to irreversible mechanisms that are induced by environment factors and lead to altered gene activity. The stability of these changes is thought to be maintained mitotically and poten- tially also meiotically, thus contributing to heritable altera- tions in gene expression over generations. The transcription of genes can be down-regulated or genes can even be inactivated by methylation of deoxyribonucleic acid (DNA) (addition of methyl groups to cytosine bases) at the primary structural level of genetic material (50). Other epigenetic mechanisms initiate genetic changes at secondary and higher structural levels, for example, via the methylation and acetylation of histones (proteins around which DNA is folded) or at a transcriptional level by interfering microRNA. Epigenetic modifications have been shown to be inducible by exogenous factors including nutrient intake. This phenom- enon is particularly pronounced during developmental plas- ticity and can shape the phenotype of organisms (51). Epigenetic processes that take place prenatally are thus postulated to be the underpinning root of long-term meta- bolic programming incidences (52–54). Recent studies of DNA methylation in infants and their body composition in childhood have supported the hypothesis that epigenetic processes are involved in the programming of body compo- sition (55,56). To date, few studies have successfully applied genome-scale DNA methylation analysis to identify highly variable regions of differential methylation in humans that consistently co-vary with BMI over time (57).

It has been proposed that it is not only protein, specifically branch-chained amino acids, but also other nutrients such as long-chain polyunsaturated fatty acids that have an indirect or even direct effect on epigenetic processes. These substrates may activate specific transcription factors or interact with response elements within chromatin that modulate transcription and physiological response such as energy or lipid metabolism (58). Investigating the underlying methylation patterns and the metabolite profiles associated with excessive weight gain during infancy potentially enables the determination of individual susceptibility to later obesity, which can be applied in monitoring programs aiming at optimising infant nutrition. The challenge now remains to develop specific studies aimed at investigating how and which nutritional exposures interact with under- lying genetic determinants to dysregulate gene expression resulting in obesity and related metabolic disorders (59). Application of sophisticated tools for targeted metabolomic and epigenomic profiling provides opportunities for the detection of relevant but as yet unidentified regulatory substrates involved in the modulation of growth and body composition. Metabolomics and epigenomics are combined in the Meta-Growth project funded by the European Research Council with an Advanced Investigator Grant for Prof. Koletzko at the University of Munich Medical Centre.

CONCLUSIONS AND FUTURE PERSPECTIVES – THE EARLYNUTRITION PROJECT Accumulating evidence underscores the potential of nutri- tion during infancy to be a powerful and modifiable determinant of childhood obesity risk. In particular, growth during early life and its association with specific nutritional components such as protein offer a huge opportunity for effective prevention. The EarlyNutrition Project funded by the EU is currently undertaking the largest metabolic programming project to better understand this relationship as one of the central topics of its comprehensive rese- arch programme (www.project-earlynutrition.eu). Research includes prepregnancy, pregnancy and infancy. Long-term effects of breastfeeding duration, interindividual variation in breast milk composition, and of complementary feeding patterns on later adiposity and metabolic response are studied. Moreover, it will be explored whether novel approaches of modifying the nitrogen composition of infant formula or reducing the glycaemic index of follow-on formula improve the metabolic response and thereby lead to reduced adiposity with preventive benefits.

It has been shown that obesity and related co-morbidities are specifically increased in people who experienced ‘developmental mismatch’ between a suboptimal prenatal/ infant environment and an obesogenic childhood environ- ment. Therefore, interactions between the velocities of prenatal and postnatal growth in relation to adiposity in late childhood are examined. Fostered evidence that excessive weight gain in pregnancy and/or rapid early infant weight gain leads to later obesity will help to formulate policies aimed at reversing the increasing rates of childhood obesity

Brands et al. Relation between infant nutrition, growth and obesity

and related disorders. Studies in the project are under- pinned by metabolomic and epigenomic analyses to eluci- date the mechanisms behind the different observational and interventional settings. Of special interest is the detection of discernible and potentially preventable adverse patterns in early metabolic programming.

The project aims to deliver decisive proof that dietary modifications in infancy, in particular relating to breast- feeding and complementary feeding practices, as well as novel compositional approaches to infant formula, can reduce the risk of obesity and related disorders in offspring. These combined approaches will give important new insights into and contribute to the development of new intervention strategies for the prevention of obesity and related disorders.

ACKNOWLEDGEMENTS The studies reported herein have been carried out with partial financial support from the Commission of the European Communities, specific RTD Programme ‘Quality of Life and Management of Living Resources’, within the 5th Frame- work Programme, research Grant Nos. QLRT–2001–00389 and QLK1-CT-2002-30582, the 6th Framework Programme, contract no. 007036, the 7th Framework Programme, con- tract no. FP7-289346-EARLY NUTRITION and the Euro- pean Research Council Advanced Grant ERC-2012-AdG – contract no. 322605 META-GROWTH. This manuscript does not necessarily reflect the views of the Commission and in no way anticipates the future policy in this area. Additional support from the National Competence Network on Obesity, Grant No. 01 GI 0825, German Ministry of Education and Research, Berlin, the Child Health Foundation, Munich, and the University of Munich Innovative Research Priority Project MC-Health (subproject I) is gratefully acknowledged. The authors declare no conflicts of interest. Contribution of the authors to this manuscript was as follows: BB undertook the literature search and wrote this nonsystematic review paper, and HD and BK edited the manuscript.

References

1. Yang ZY, Huffman SL. Nutrition in pregnancy and early childhood and associations with obesity in developing countries. Matern Child Nutr 2013; 9: 105–19.

2. Withrow D, Alter DA. The economic burden of obesity worldwide: a systematic review of the direct costs of obesity. Obes Rev 2010; 12: 131–41.

3. Koletzko B, Brands B, Poston L, Godfrey K, Demmelmair H. Early nutrition programming of long-term health. Proc Nutr Soc 2012; 71: 371–8.

4. Koletzko B. The power of programming: developmental origins of health and disease. Am J Clin Nutr 2011; 94: 1747S–2043S.

5. D€orner G. Perinatal hormone levels and brain organization: In Stumpf WE, Grant LD, editors. Anatomical neuroendocrinology. Basel: Karger, 1975: 245–52.

6. Weng SF, Redsell SA, Swift JA, Yang M, Glazebrook CP. Systematic review and meta-analyses of risk factors for childhood overweight identifiable during infancy. Arch Dis Child 2012; 97: 1019–26.

7. Brisbois TD, Farmer AP, McCargar LJ. Early markers of adult obesity: a review. Obes Rev 2012; 13: 347–67.

8. Monasta L, Batty GD, Cattaneo A, Lutje V, Ronfani L, van Lenthe FJ, et al. Early-life determinants of overweight and obesity: a review of systematic reviews. Obes Rev 2010; 11: 695–708.

9. Waters E, de Silva-Sanigorski A, Hall BJ, Brown T, Campbell KJ, Gao Y, et al. Interventions for preventing obesity in children: In The Cochrane C, Waters E, editors. Cochrane Database Syst Rev. Chichester, UK: John Wiley & Sons, Ltd, 2011.

10. Ciampa PJ, Kumar D, Barkin SL, Sanders LM, Yin HS, Perrin EM, et al. Interventions aimed at decreasing obesity in children younger than 2 years: a systematic review. Arch Pediatr Adolesc Med 2010; 164: 1098–104.

11. Koletzko B, von Kries R, Closa R, Escribano J, Scaglioni S, Giovannini M, et al. Can infant feeding choices modulate later obesity risk? Am J Clin Nutr 2009; 89: 1502S–8S.

12. Wells JC. The programming effects of early growth. Early Hum Dev 2007; 83: 743–8.

13. Bansal N, Ayoola OO, Gemmell I, Vyas A, Koudsi A, Oldroyd J, et al. Effects of early growth on blood pressure of infants of British European and South Asian origin at one year of age: the Manchester children’s growth and vascular health study. J Hypertens 2008; 26: 412–8.

14. Stettler N. Nature and strength of epidemiological evidence for origins of childhood and adulthood obesity in the first year of life. Int J Obes (Lond) 2007; 31: 1035–43.

15. Horta BL, Victora CG, Lima RC, Post P. Weight gain in childhood and blood lipids in adolescence. Acta Paediatr 2009; 98: 1024–8.

16. Dunger DB, Salgin B, Ong KK. Session 7: Early nutrition and later health early developmental pathways of obesity and diabetes risk. Proc Nutr Soc 2007; 66: 451–7.

17. Ong KK, Loos RJF. Rapid infancy weight gain and subsequent obesity: systematic reviews and hopeful suggestions. Acta Paediatr 2006; 95: 904–8.

18. Druet C, Ong KK. Early childhood predictors of adult body composition. Best Pract Res Clin Endocrinol Metab 2008; 22: 489–502.

19. Ong KK. Size at birth, postnatal growth and risk of obesity. Horm Res 2006; 65(Suppl. 3): 65–9.

20. Ibanez L, Ong K, Dunger DB, de Zegher F. Early development of adiposity and insulin resistance after catch-up weight gain in small-for-gestational-age children. J Clin Endocrinol Metab 2006; 91: 2153–8.

21. Toschke AM, Grote V, Koletzko B, von Kries R. Identifying children at high risk for overweight at school entry by weight gain during the first 2 years. Arch Pediatr Adolesc Med 2004; 158: 449–52.

22. Druet C, Stettler N, Sharp S, Simmons RK, Cooper C, Smith GD, et al. Prediction of childhood obesity by infancy weight gain: an individual-level meta-analysis. Paediatr Perinat Epidemiol 2012; 26: 19–26.

23. Gillman MW. Early infancy as a critical period for development of obesity and related conditions. Nestle Nutr Workshop Ser Pediatr Program 2010; 65: 13–20; discussion -4.

24. Adair LS, Martorell R, Stein AD, Hallal PC, Sachdev HS, Prabhakaran D, et al. Size at birth, weight gain in infancy and childhood, and adult blood pressure in 5 low- and middle-income-country cohorts: when does weight gain matter? Am J Clin Nutr 2009; 89: 1383–92.

25. Botton J, Heude B, Maccario J, Ducimetiere P, Charles MA. Postnatal weight and height growth velocities at different ages between birth and 5 y and body composition in adolescent boys and girls. Am J Clin Nutr 2008; 87: 1760–8.

Relation between infant nutrition, growth and obesity Brands et al.

26. Chomtho S, Wells JC, Williams JE, Davies PS, Lucas A, Fewtrell MS. Infant growth and later body composition: evidence from the 4-component model. Am J Clin Nutr 2008; 87: 1776–84.

27. Ward LC, Poston L, Godfrey KM, Koletzko B. Assessing early growth and adiposity: report from an earlynutrition academy workshop. Ann Nutr Metab 2013; 63: 120–30.

28. Rao S, Simmer K. World Health Organization growth charts for monitoring the growth of Australian children: time to begin the debate. J Paediatr Child Health 2012; 48: E84–90.

29. Soliman A, Eldabbagh M, Khalafallah H, Alali M, Elalaily RK. Longitudinal growth of infants in Qatar: comparison with WHO and CDC growth standards. Indian Pediatr 2011; 48: 791–6.

30. van Rossum C, B€uchner FL, Hoekstra JA. Quantification of Health Effects of Breastfeeding: Review of the Literature and Model Simulation: RIVM, 2005.

31. Lawrence RA. Increasing breastfeeding duration: changing the paradigm. Breastfeed Med 2011; 6: 367–8.

32. Harder T, Bergmann R, Kallischnigg G, Plagemann A. Duration of breastfeeding and risk of overweight: a meta-analysis. Am J Epidemiol 2005; 162: 397–403.

33. Horta B, Bahl R, Martines J, Victora C. Evidence of the long-term effects of breastfeeding: systematic reviews and meta-analysis. Geneva, Switzerland: World Health Organization Publication, 2007.

34. Arenz S, Ruckerl R, Koletzko B, von Kries R. Breast-feeding and childhood obesity – a systematic review. Int J Obes 2004; 28: 1247–56.

35. Kramer MS, Matush L, Vanilovich I, Platt RW, Bogdanovich N, Sevkovskaya Z, et al. A randomized breast-feeding promotion intervention did not reduce child obesity in Belarus. J Nutr 2009; 139: 417S–21S.

36. Beyerlein A, Toschke AM, von Kries R. Breastfeeding and childhood obesity: shift of the entire BMI distribution or only the upper parts? Obesity (Silver Spring) 2008; 16: 2730–3.

37. Kramer MS, Kakuma R. Optimal duration of exclusive breastfeeding. Cochrane Database Syst Rev 2012; CD003517.

38. Gale C, Logan KM, Santhakumaran S, Parkinson JR, Hyde MJ, Modi N. Effect of breastfeeding compared with formula feeding on infant body composition: a systematic review and meta-analysis. Am J Clin Nutr 2012; 95: 656–69.

39. Beyerlein A, von Kries R. Breastfeeding and body composition in children: will there ever be conclusive empirical evidence for a protective effect against overweight? Am J Clin Nutr 2011; 94: 1772s–5s.

40. Dardevet D, Manin M, Balage M, Sornet C, Grizard J. Influence of low- and high-protein diets on insulin and insulin-like growth factor-1 binding to skeletal muscle and liver in the growing rat. Br J Nutr 1991; 65: 47–60.

41. Koletzko B. Marketing of dietetic products for infants and young children in Europe three decades after adoption of the International Code of Marketing of Breast Milk Substitutes. Ann Nutr Metab 2011; 43: A2268–9.

42. Larnkjaer A, Molgaard C, Michaelsen KF. Early nutrition impact on the insulin-like growth factor axis and later health consequences.CurrOpinClinNutrMetabCare2012;15:285–92.

43. Polak P, Hall MN. mTOR and the control of whole body metabolism. Curr Opin Cell Biol 2009; 21: 209–18.

44. Sengupta S, Peterson TR, Sabatini DM. Regulation of the mTOR complex 1 pathway by nutrients, growth factors, and stress. Mol Cell 2010; 40: 310–22.

45. Savino F, Fissore MF, Grassino EC, Nanni GE, Oggero R, Silvestro L. Ghrelin, leptin and IGF-I levels in breast-fed and formula-fed infants in the first years of life. Acta Paediatr 2005; 94: 531–7.

46. Socha P, Grote V, Gruszfeld D, Janas R, Demmelmair H, Closa-Monasterolo R, et al. Milk protein intake, the metabolic-endocrine response, and growth in infancy: data from a randomized clinical trial. Am J Clin Nutr 2011; 94: 1776S–84S.

47. Madsen AL, Larnkjaer A, Molgaard C, Michaelsen KF. IGF-I and IGFBP-3 in healthy 9 month old infants from the SKOT cohort: breastfeeding, diet, and later obesity. Growth Horm IGF Res 2011; 21: 199–204.

48. Koletzko B, von Kries R, Closa R, Escribano J, Scaglioni S, Giovannini M, et al. Lower protein in infant formula is associated with lower weight up to age 2 y: a randomized clinical trial. Am J Clin Nutr 2009; 89: 1836–45.

49. Escribano J, Luque V, Ferre N, Zaragoza-Jordana M, Grote V, Koletzko B, et al. Increased protein intake augments kidney volume and function in healthy infants. Kidney Int 2011; 79: 783–90.

50. Deaton AM, Bird A. CpG islands and the regulation of transcription. Genes Dev 2011; 25: 1010–22.

51. Choi SW, Friso S. Epigenetics: a new bridge between nutrition and health. Adv Nutr 2010; 1: 8–16.

52. Low FM, Gluckman PD, Hanson MA. Developmental plasticity and epigenetic mechanisms underpinning metabolic and cardiovascular diseases. Epigenomics 2011; 3: 279–94.

53. Hanley B, Dijane J, Fewtrell M, Grynberg A, Hummel S, Junien C, et al. Metabolic imprinting, programming and epigenetics – a review of present priorities and future opportunities. Br J Nutr 2010; 104: S1–25.

54. Turan N, Ghalwash MF, Katari S, Coutifaris C, Obradovic Z, Sapienza C. DNA methylation differences at growth related genes correlate with birth weight: a molecular signature linked to developmental origins of adult disease? BMC Med Genomics 2012; 5: 10.

55. Mathers J. Nutrition, epigenomics and the development of obesity: how the genome learns from experience. Obesity prevention: the role of brain and society on individual behavior. 1 ed. London, UK: Elsevier, 2010: 191–9.

56. Simmons R. Epigenetics and maternal nutrition: nature v. nurture. Proc Nutr Soc 2010; 70: 73–81.

57. Feinberg AP, Irizarry RA, Fradin D, Aryee MJ, Murakami P, Aspelund T, et al. Personalized epigenomic signatures that are stable over time and covary with body mass index. Sci Transl Med 2010; 2: 49ra67.

58. Cousins RJ, Aydemir TB, Lichten LA. Plenary Lecture 2 Transcription factors, regulatory elements and nutrient–gene communication. Proc Nutr Soc 2009; 69: 91–4.

59. Godfrey KM, Sheppard A, Gluckman PD, Lillycrop KA, Burdge GC, McLean C, et al. Epigenetic gene promoter methylation at birth is associated with child’s later adiposity. Diabetes 2011; 60: 1528–34.

60. Koletzko B, Beyer J, Brands B, Demmelmair H, Grote V, Haile G, et al. Early influences of nutrition on postnatal growth. Nestle Nutr Inst Workshop Ser 2013; 71: 11–27.

61. Cole T, Bellizzi M, Flegal K, Dietz W. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000; 320: 1240.

Brands et al. Relation between infant nutrition, growth and obesity

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