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Genetic influences in childhood obesity: recent progress and recommendations for experimental designs

Abstract

The increasing prevalence of pediatric obesity around the world has become an area of scientific interest because of public health concern. Although since early stages of the lifespan body weight might be heavily influenced by an individual's behavior, epidemiological research highlights the involvement of genetic influences contributing to variation in fat accumulation and thus body composition. Results from genome-wide association studies and candidate gene approaches have identified specific regions across the human genome influencing obesity-related phenotypes. Reviewing the scientific literature provides support to the belief that at the conceptual level scientists understand that genes and environments do not act independently, but rather synergistically, and that such interaction might be the responsible factor for differences within and among populations. However, there is still limited understanding of genetic and environmental factors influencing fat accumulation and deposition among different populations, which highlights the need for innovative experimental designs, improved body composition measures and appropriate statistical methodology.

Introduction

Pediatric obesity has become a worldwide public health concern,1 as it continues to increase in prevalence and severity. Early-onset adult health implications, such as diabetes, heart disease, non-alcoholic hepatic steatosis and some cancers,1 presenting among children worldwide has created a sense of alarm among parents, caretakers, health practitioners and public health professionals. Efforts toward understanding the contributors to the pediatric obesity epidemic are, perhaps more than ever, paramount within the scientific and clinical communities, and should be collectively directed toward the development of preventive strategies.

Beyond the estimation of the prevalence of pediatric overweight and obesity based on standardized weight measures, research has shown that children of different populations around the world differ in body composition parameters. In the United States, for example, African-American children have been reported to have lower levels of abdominal adiposity compared with children of European- or Hispanic-American descent.2, 3, 4 Chinese youth have more body fat and Asian Indians have higher levels of adiposity, more truncal fat and lower muscle mass5 compared with white youth. These observed differences during childhood indicate that, from early stages of development, the genetic makeup of individuals interacts with environmental factors (influenced by the population-specific locations, cultures, social settings and practices) to create variation in fat acquisition and accumulation among populations. This paper reviews existing scientific literature supporting genetic contributors to pediatric obesity, with a focus on population differences in obesity-related phenotypes and methodological considerations.

Materials and methods

For this review, we evaluated and summarized the results of studies involving genetics and ancestral genetic background, and obesity-related phenotypes in the pediatric population. We identified these studies through searches in Medline (PubMed), Web of Science and Google for original research and review articles written in english, published between January 1990 and July 2011 using the following search terms independently and/or in combination: children, pediatric obesity, body mass index, adiposity, body fat, polymorphism, genetics, cardiovascular disease, heart disease, diabetes, insulin resistance and lipids. We also searched within the reference lists of identified papers to locate additional studies. We identified 79 articles from this original search. We also searched the online catalog of Genome Wide Association Studies (http://www.genome.gov/26525384).

Genetic determinants and population differences in pediatric obesity

A variety of study designs have been used to determine the heritability (that is, proportion of variation in a phenotype that is explained by genetic factors) of body mass index (BMI=kg/m2),6 including adoption studies,7, 8 and twin and virtual twin studies.9, 10 Although estimates vary according to methodology and sample characteristics, approximately 65% of the variation in BMI can be explained by genetic factors.6, 7, 10, 11 Evidence suggests that heritability estimates are similarly high for measures of obesity other than BMI, particularly those of fat distribution.12, 13 It has also been suggested that the heritability of obesity-related traits increases with age,14 implying that at early stages of the lifespan body weight is highly influenced by behavioral, social, parental and environmental factors, highlighting a potentially crucial time for intervention.

Family-based data have been pivotal in the identification of genetic determinants of body adiposity in humans. Linkage analyses have provided insights into genetics of early-onset obesity, identifying strongly associated genes with large phenotypic effects such as the leptin receptor (LEPR),15 brain-derived neurotrophic factor (BDNF) and melanocortin-4 receptor (MC4R).16 Some of these genes have also been associated with phenotypes involving energy balance, as exemplified by the association of multiple rare variants in MC4R with both energy intake and expenditure among Hispanic children.17 However, linkage methodology is limited in detecting genes of small effects, which likely underlie the genetic basis of complex traits such as obesity. Consequently, although linkage scans have led to the identification of several hundred genomic regions, as summarized elsewhere,18 most of the genes identified have failed to be replicated.19

More recently, genome-wide association studies (GWAS) have utilized large samples of individuals genotyped at approximately 500 thousand single nucleotide polymorphisms spread throughout the genome. To date, several GWAS for BMI have been performed and replicated utilizing populations of mainly Northern-European ancestry,20, 21, 22, 23, 24 finding risk alleles in or near approximately 32 genes25 (see Table 1). Another commonly used method for identifying genetic variants is the candidate gene approach where selection of genes is based on the known physiological role in pathways associated with obesity (for example, fat deposition, energy expenditure, food intake and metabolism). Over the past 20 years, studies incorporating this approach have identified a large number of potential genes contributing to variation in obesity-related traits.26 However, of the 127 candidate genes identified, few have been replicated across multiple studies. A summary of findings for genes associated with obesity using the candidate gene approach is presented in Table 2. Although many genetic contributors to adiposity have been identified, there is surprisingly very little overlap between those regions identified by candidate gene studies and those identified by GWAS.18

Table 1 List of loci associated with BMI from GWAS25
Table 2 Genes associated with obesity from candidate gene studies, based on Rankinen et al.18 and Walley et al.77

The search for genetic factors specifically influencing pediatric obesity-related outcomes has primarily focused on replicated candidate genes in adult studies. Among the studies that have examined genetic associations among children, most report equivocal results. For example, a large twin study in the United Kingdom of ten candidate genes reported to be associated with BMI in adults, found no evidence for an association in children at ages four, seven or ten.27 Conversely, a study of bi-ethnic US children investigating 11 different candidate genes involved in energy balance and adipogenesis observed multiple associations.28 Other candidate genes have been identified in pediatric populations around the world, as indicated in Table 3, with some (e.g. FTO-fat mass and obesity-associated protein) reported to increase obesity risk with increase in age.14 The lack of replication across genetic studies raises issues related to mechanistic differences in metabolic pathways owing to heterogeneity of samples, in terms of impact of genetic influence across the lifespan, different environmental exposures and potential differences in genetic ancestral background.

Table 3 Loci implicated in obesity among children by GWAS

Although there has been some progress in our understanding of the potential genetic determinants of obesity-related traits, there are still questions regarding the mechanisms of action of these genetic variants. Many of the variants discovered in GWAS are in or near genes expressed in the central nervous system and hypothalamus, suggesting a role in the regulation of food intake and energy expenditure.22 So far, the majority of risk alleles are found in noncoding regions, often in areas that are several kilobases away from the coding region of a gene. In addition, some of the genes associated with obesity might influence different phenotypes in a particular population, as seen in a recent example where MC4R, but not FTO, was found to be associated with self-reported eating behavior in European children and adults.29 In order to refine the genetic basis for obesity, large-scale GWAS should be followed by a multitude of small-scale studies to fine-map candidate regions. This will also determine whether the identified variants can be replicated with more explicit and better-defined phenotypes, and whether the variants contribute similarly among different sample populations, providing insights into possible mechanisms. The current decrease in cost associated with gene mapping makes it more feasible to obtain sequence data, enhancing research efforts. However, as we collectively move forward toward improving genetic analysis, new layers of complexity are likely to surface, including understanding of gene expression modification by environmental and/or developmental factors and the contributions of different epigenetic response owing to evolutionary developmental variation across populations.

In addition to individual genes, genetic ancestral background appears to contribute to the variation in adiposity at the population level. Genetic research has demonstrated within-group variation in genetic ancestry proportions among populations, particularly those in the United States, along with a relationship with disease risk.30 Some studies have reported significant associations between genetic admixture and measures of adiposity in specific groups, particularly in African-American women31, 32 and Hispanic individuals of Afro-Caribbean descent.33, 34 The results of the association of genetic admixture and obesity-related measures in North American Hispanics have not been consistent,32, 35, 36, 37, 38 and among Native Americans, only two studies have examined the relationship between BMI and genetic admixture (both finding a negative relationship between European admixture and BMI).35, 39 Regardless of the reported associations, it is important to consider the existence of studies failing to replicate these findings, thus raising concern about methodology and experimental design, the use of categories (used for racial/ethnic classification), and the importance of evaluating gene by environmental interactions in population studies.40, 41, 42, 43 Nevertheless, the evaluation of ancestral genetic background has helped in explaining observed racial/ethnic differences in weight and adiposity, particularly in the United States.44, 45, 46

Behavioral genetic factors

Although individual exposure to the obesigenic environment does not necessarily influence choice, the observed increase of heritability throughout the lifespan may result from genetic predisposition to behaviors promoted by an environment of great accessibility to foods and limited opportunities for physical activity. Recent evidence has demonstrated that behavioral practices respond to genetic factors. For example, heritability estimates for feeding behaviors such as food cue responsiveness and eating rate have been reported.47, 48 Apart from eating behaviors, physiological factors such as dopamine,49 serotonin50 and cannabinoid receptor candidate genes have also been identified as contributing to eating behavior and thus, body weight regulation in children.51 Genetic determinants of physical activity performance and fitness phenotypes have been reported with >200 estimated associated DNA variants.52 Although the majority of these studies were conducted in adults, it is highly possible that associations translate to the pediatric population and, in fact, could control physiological and/or behavioral process(es) that cause(s) children to take a certain body composition trajectory.

The variation of behavioral traits among populations cannot be explained solely by genetics. There are many behavioral practices mediated by factors such as culture, family practices, accessibility to resources, spirituality, social status and economical solvency among others that contribute to obesity-related behaviors. Childhood behaviors represent a significant influence on body composition trajectory, and thus long-term overall health. Hence, there is a call for research initiatives targeted toward the understanding of how cultural, social and economical practices impact behavioral choice, and how these factors interact with biological parameters throughout the childhood continuum to signal processes of fat accumulation.

Study design considerations

As reviewed, most of the identified genetic contributors to obesity-related traits have been discovered through population research. The study of population differences in obesity-related traits serves as a portal to the understanding of etiology of individual variability. Such understanding becomes relevant in the development of prevention strategies and treatment for those at a higher risk for disease. As we continue to explore the scientific discovery funnel that moves from population biology down to individual treatment, it is pertinent to continue efforts to improve population research.

As previously stated, few studies in the field of obesity have investigated the interrelation between genes and environment. However, acquiring an insight into the development of obesity as a disease throughout the lifespan will rely on the implementation of experimental designs with appropriate measurements and statistical methodology to evaluate the action and interaction of biological and non-biological parameters. As the scientific community collectively moves toward eliminating the global burden of pediatric obesity, the following methodological aspects deserve consideration when designing studies targeted to understanding the genetic etiology childhood obesity and population differences:

  1. 1

    The contributions of genes and environment to overweight and obesity act synergistically (or antagonistically) rather than independently, and thus a clear dichotomy between genetic and environmental influences on related traits cannot exist. There is evidence demonstrating how the environment interacts with genetic makeup and expression to influence a trait. Epigenetic mechanisms have also been documented, whereby environmental factors physically affect gene expression without altering the DNA sequence. Of particular interest is evidence showing the impact of the intra-uterine environment and birth weight on differences in early-onset obesity.53, 54, 55 The importance of defining a priori what researchers mean by environment in a particular study should also be stressed when designing studies, paying particular attention to the limitations in accurately quantifying those factors traditionally considered as environmental in clinical research. Understanding how environmentally related exposures and parent-of-origin effects contribute to genetic expression and disease risk is an exciting avenue for future research, which will provide additional insight into the etiology of pediatric obesity and population differences. Furthermore, the recent identification of a set of genetic variants by GWAS is likely to make this task more manageable, by simply investigating whether and how these genetic associations are mediated by environmental, behavioral factors and vice versa.56

  2. 2

    Genetic influences likely vary amongst populations. Many of the associations identified in GWAS, for instance, have been conducted among European adults. It is not known whether these associations will apply equally to other racial/ethnic populations or other age groups. In the case of the well-documented FTO gene, for instance, a particular SNP associated with obesity has been identified and replicated in Chinese and Mexican populations,57, 58 despite a large difference in the frequency of the risk allele between the two populations (12.6% vs 45%).57 However, although associations between FTO and obesity have recently been found in other worldwide populations,59, 60, 61, 62, 63, 64 no association between FTO variants and BMI were found among a West African population in Gambia, or in an Oceanic population.65, 66 Similarly, in children, a recent study evaluating the contributions of the MC4R variant (a recent finding of GWAS in adults) to childhood obesity was replicated in children of European descent, but not of African descent.67 As the identification of specific genetic variants responsible for obesity progresses, it will be important to examine how the effect of these variants differs between populations, and to identify population- and age-specific pathways to obesity.

  3. 3

    Body composition trajectory responds to a cumulative process that initiates, in many cases, at early stages of the life course and continues throughout development. It is not completely clear at what time during the developmental or aging process the variants identified as contributors to obesity initiate their influence on fat accumulation; although some evidence suggest that their effects do indeed manifest themselves early in the lifespan.68, 69 However, the obesity risk attributable to gene variants has been reported to increase with age.14 In order to optimize treatment and prevention plans, more research is needed to understand how such gene–environment interactions change across the lifespan.

  4. 4

    Appropriate statistical methodology is needed to address the complexity of genetic interactions that influence variability in measures related to obesity. Relative heritability estimates for BMI average about 65%; however, genetic variants identified by GWAS explain a disappointingly small proportion of the expected genetic variation.70, 71 For example, although evidence supports an additive genetic contribution to BMI so that individuals with 13 risk alleles have greater BMI when compared with individuals of similar height with 3 risk alleles,22 a very large proportion of the total expected genetic variation remains unexplained by genetic variants identified to date.72 Despite recent methodological advances,73, 74 there is still an imminent need to develop statistical approaches that allow the evaluation of individual and interactive contributions of genetic, physiological and environmental factors. There is also a need for the simultaneous statistical evaluation of multiple and interactive genes, and their integration with other genomic data, including gene expression, high density SNP genotyping and sequencing. Newly developed statistical approaches are being used to simultaneously consider thousands of genetic markers across the genome, promising to identify relevant genomic regions and to explain a higher proportion of the expected heritability of obesity-related phenotypes.75 Follow-up of genetic association studies with functional studies that could uncover the molecular and physiological mechanisms underlying obesity phenotypes will serve as a crucial future step in the development of preventive and therapeutic strategies.

  5. 5

    As common variants have explained a small proportion of variation in BMI, there has been considerable debate as to whether rarer variants could explain much of the so-called missing heritability.71 As efforts proceed toward the identification of rare variants, various methods are being developed and tried with the goal of measuring and assessing rare variants, such as by collapsing them in some predefined regions of interest and evaluating their association with phenotypes.76 Rare variants could be measured via imputation using reference samples from the HapMap and the 1000 Genomes Projects, or by sequencing candidate regions, targeted exome regions or entire genomes. These methods are still in their infancy, and they will ultimately be guided by how they perform in explaining and predicting phenotypes.

  6. 6

    More precise and accurate measurements are needed to qualify and quantify fat acquisition in epidemiological studies. Although the use of BMI as a predictor of disease risk has been of great importance for public health, it is clear that BMI does not equally and accurately represent health status of individuals across populations. It is well documented that although some Asian populations have lower prevalence of BMI-defined obesity, adiposity levels (particularly in the abdominal compartment) is greater than other groups with higher BMI. For effective epidemiological research, it is important to examine more specific and clinically relevant phenotypes, such as measures of body composition, waist circumference and metabolic parameters.

Conclusions

A major risk factor for adult obesity is excessive fat accumulation during childhood. Differences in body composition have been consistently documented among members of diverse populations beginning early in an individual's lifespan. Genetic background is strongly implicated in fat accumulation, and underlies variation in obesity susceptibility. Although control mechanisms for body composition appear to have a strong genetic etiology, body fat accumulation is also influenced by external stimuli.

Success in identifying the etiology of pediatric obesity among diverse populations will depend on the development of appropriate statistical methods, accurate phenotypic measurements and sophisticated experimental designs that take into account the developmental origins and trajectory of body composition, as well as social, cultural and economical influences.

It is evident that our understanding of population differences in pediatric obesity will depend on our ability to take into account the continuous and cumulative process of fat accumulation and acquisition in individuals. Precise and population-specific classification of body composition will provide clarity to research endeavors, directing scientific discovery toward the identification of possible underlying physiological mechanisms, and ultimately improved prevention strategies.

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Acknowledgements

This work has been funded in part by NIH Grants R01-DK067426 and T32HL007457.

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Correspondence to J R Fernandez.

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Fernandez, J., Klimentidis, Y., Dulin-Keita, A. et al. Genetic influences in childhood obesity: recent progress and recommendations for experimental designs. Int J Obes 36, 479–484 (2012). https://doi.org/10.1038/ijo.2011.236

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Keywords

  • childhood obesity
  • genes
  • admixture
  • statistics
  • body composition

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