Heritability variations of body linearity and obesity indicators during growth

Longitudinal as well as cross-sectional studies have shown variations with age in heritability estimates for body dimensions from infancy to adulthood, even though the patterns of variation are not completely clear. Further study on this subject is of great interest and may help obesity interventions for preventing or treating obesity in children. Therefore, the aim of the present study is to analyse the changes in the genetic and environmental architecture of 8 body linearity and obesity-related phenotypes during the growth process in a cross-sectional sample of 1018 nuclear families from the province of Biscay (Basque Country, Spain). The contribution of additive genetic effects to the variation of the analysed traits was estimated by a variance component analysis using the SOLAR program. Moderate to high heritability estimates were obtained for all 8 anthropometric phenotypes (38.23–65.98%). The heritability values show an increasing trend with age and in the course of the entire ontogenetic development two age periods were remarkable. At 7⁺–8⁺ years of age a strong increase in heritability estimates was found for all the anthropometric phenotypes, except for the sum of skinfolds (SF6), reflecting the biological significance of genes during mid-childhood. During puberty, most of the obesity related phenotypes showed their highest heritability values while linear measurements and weight presented a decrease in the genetic contributions. In conclusion, this study confirms that additive genetic influences have a considerable effect on body linearity and obesity-related traits throughout the growth period and that mid-childhood and puberty are very sensitive periods in human life cycle.     

Effect of Body Mass Index on Global DNA Methylation in Healthy Korean Women

Obesity is known to be strongly associated with cardiovascular disease and cancer, the leading causes of mortality worldwide, and develops owing to interactions between genes and the environment. DNA methylation can act as a downstream effector of environmental signals, and analysis of this process therefore holds substantial promise for identifying mechanisms through which genetic and environmental factors jointly contribute to disease risk. Global DNA methylation of peripheral blood cells has recently been proposed as a potential biomarker for disease risk. Repetitive element DNA methylation has been shown to be associated with prominent obesity-related chronic diseases, but little is known about its relationship with weight status. In this study, we quantified the methylation of Alu elements in the peripheral blood DNA of 244 healthy women with a range of body mass indexes (BMIs) using pyrosequencing technology. Among the study participants, certain clinical laboratory parameters, including hemoglobin, serum glutamic oxaloacetic transaminase, serum glutamic-pyruvic transaminase, total cholesterol, and triglyceride levels were found to be strongly associated with BMI. Moreover, a U-shaped association between BMI and Alu methylation was observed, with the lowest methylation levels occurring at BMIs of between 23 and 30 kg/m². However, there was no significant association between Alu methylation and age, smoking status, or alcohol consumption. Overall, we identified a differential influence of BMI on global DNA methylation in healthy Korean women, indicating that BMI-related changes in Alu methylation might play a complex role in the etiology and pathogenesis of obesity. Further studies are required to elucidate the mechanisms underlying this relationship.     

Shared genetic risk factors for obstructive sleep apnea and obesity.

Both obesity and obstructive sleep apnea (OSA) are complex disorders with multiple risk factors, which interact in a complicated fashion to determine the overall phenotype. In addition to environmental risk factors, each disorder has a strong genetic basis that is likely due to the summation of small to moderate effects from a large number of genetic loci. Obesity is a strong risk factor for sleep apnea, and there are some data to suggest sleep apnea may influence obesity. It is therefore not surprising that many susceptibility genes for obesity and OSA should be shared. Current research suggests that approximately half of the genetic variance in the apnea hypopnea index is shared with obesity phenotypes. Genetic polymorphisms that increase weight will also be risk factors for apnea. In addition, given the interrelated pathways regulating both weight and other intermediate phenotypes for sleep apnea such as ventilatory control, upper airway muscle function, and sleep characteristics, it is likely that there are genes with pleiotropic effects independently impacting obesity and OSA traits. Other genetic loci likely interact with obesity to influence development of OSA in a gene-by-environment type of effect. Conversely, environmental stressors such as intermittent hypoxia and sleep fragmentation produced by OSA may interact with obesity susceptibility genes to modulate the importance that these loci have on defining obesity-related traits.     

Sex-specific genetic architecture of human fatness in Chinese: the SAPPHIRe Study

To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex–genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia–Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype–sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.     

INTERACTING PHENOTYPES AND THE EVOLUTIONARY PROCESS: I. DIRECT AND INDIRECT GENETIC EFFECTS OF SOCIAL INTERACTIONS

Interacting phenotypes are traits whose expression is affected by interactions with conspecifics. Commonly-studied interacting phenotypes include aggression, courtship, and communication. More extreme examples of interacting phenotypes—traits that exist exclusively as a product of interactions—include social dominance, intraspecific competitive ability, and mating systems. We adopt a quantitative genetic approach to assess genetic influences on interacting phenotypes. We partition genetic and environmental effects so that traits in conspecifics that influence the expression of interacting phenotypes are a component of the environment. When the trait having the effect is heritable, the environmental influence arising from the interaction has a genetic basis and can be incorporated as an indirect genetic effect. However, because it has a genetic basis, this environmental component can evolve. Therefore, to consider the evolution of interacting phenotypes we simultaneously consider changes in the direct genetic contributions to a trait (as a standard quantitative genetic approach would evaluate) as well as changes in the environmental (indirect genetic) contribution to the phenotype. We then explore the ramifications of this model of inheritance on the evolution of interacting phenotypes. The relative rate of evolution in interacting phenotypes can be quite different from that predicted by a standard quantitative genetic analysis. Phenotypic evolution is greatly enhanced or inhibited depending on the nature of the direct and indirect genetic effects. Further, unlike most models of phenotypic evolution, a lack of variation in direct genetic effects does not preclude evolution if there is genetic variance in the indirect genetic contributions. The available empirical evidence regarding the evolution of behavior expressed in interactions, although limited, supports the predictions of our model.     

A genetic contribution to circulating cytokines and obesity in children

Cytokines are considered to be involved in obesity-related metabolic diseases. Study objectives are to determine the heritability of circulating cytokine levels, to investigate pleiotropy between cytokines and obesity traits, and to present genome scan results for cytokines in 1030 Hispanic children enrolled in VIVA LA FAMILIA Study. Cytokine phenotypes included monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-alpha), leptin, adiponectin, soluble intercellular adhesion molecule-1 (sICAM-1), transforming growth factor beta 1 (TGF-beta1), C-reactive protein (CRP), regulated upon activation, normal T-cell expressed and secreted (RANTES) and eotaxin. Obesity-related phenotypes included body mass index (BMI), fat mass (FM), truncal FM and fasting serum insulin. Heritabilities ranged from 0.33 to 0.97. Pleiotropy was observed between cytokines and obesity traits. Positive genetic correlations were seen between CRP, leptin, MCP-1 and obesity traits, and negative genetic correlations with adiponectin, ICAM-1 and TGF-beta1. Genome-wide scan of sICAM-1 mapped to chromosome 3 (LOD=3.74) between markers D3S1580 and D3S1601, which flanks the adiponectin gene (ADIPOQ). Suggestive linkage signals were found in other chromosomal regions for other cytokines. In summary, significant heritabilities for circulating cytokines, pleiotropy between cytokines and obesity traits, and linkage for sICAM-1 on chromosome 3q substantiate a genetic contribution to circulating cytokine levels in Hispanic children.     

Association among obesity-related anthropometric phenotypes: analyzing genetic and environmental contribution

Obesity has become a public-health and policy problem in many parts of the world. Epidemiological and population studies in this field are usually based on different anthropometric measures; however, common genetic and environmental factors between these phenotypes have been scarcely studied. The objective of this article is to assess the strength of these factors on the covariation among a large set of obesity-related traits. The subject group consisted of 533 nuclear families living in the Greater Bilbao (Spain), and included 1,702 individuals aged 2-61 years. Detailed anthropometric measurements (stature, breadths, circumferences and skinfolds) were carried out in each subject. Bivariate quantitative genetic analyses were performed using a variance-components procedure implemented in the software SOLAR. The results revealed that the majority of these traits is affected by common genetic and environmental factors. All correlations were significantly different from 1 and varied from non-significant to very high (>0.90, P < 0.0001), with clearly lower pleiotropic effects among pairs including fat-distribution traits. Despite the strong common genetic effects detected among phenotypes determining the amount of body fat and mass, there is a residual genetic influence on the local fatness measures that cannot be explained exclusively by the genetic influence on overall fatness. Moreover, the observed relationships confirm a partially different genetic control of truncal and peripheral fat. In conclusion, our findings highlight the relevance of considering different types of traits in the prevention and treatment of obesity, as well as in the search for genes involved in its development.     

Genetic susceptibility to obesity and diet intakes: association and interaction analyses in the Malmö Diet and Cancer Study

Gene–environment interactions need to be studied to better understand the obesity. We aimed at determining whether genetic susceptibility to obesity associates with diet intake levels and whether diet intakes modify the genetic susceptibility. In 29,480 subjects of the population-based Malmö Diet and Cancer Study (MDCS), we first assessed association between 16 genome-wide association studies identified obesity-related single-nucleotide polymorphisms (SNPs) with body mass index (BMI) and associated traits. We then conducted association analyses between a genetic risk score (GRS) comprising of 13 replicated SNPs and the individual SNPs, and relative dietary intakes of fat, carbohydrates, protein, fiber and total energy intake, as well as interaction analyses on BMI and associated traits among 26,107 nondiabetic MDCS participants. GRS associated strongly with increased BMI (P = 3.6 × 10^?34), fat mass (P = 6.3 × 10^?28) and fat-free mass (P = 1.3 × 10^?24). Higher GRS associated with lower total energy intake (P = 0.001) and higher intake of fiber (P = 2.3 × 10^?4). No significant interactions were observed between GRS and the studied dietary intakes on BMI or related traits. Of the individual SNPs, after correcting for multiple comparisons, NEGR1 rs2815752 associated with diet intakes and BDNF rs4923461 showed interaction with protein intake on BMI. In conclusion, our study does not provide evidence for a major role for macronutrient-, fiber- or total energy intake levels in modifying genetic susceptibility to obesity measured as GRS. However, our data suggest that the number of risk alleles as well as some of the individual obesity loci may have a role in regulation of food and energy intake and that some individual loci may interact with diet.     

Effects of maternal body morphology, morning sickness, gestational diabetes and hypertension on fluctuating asymmetry in young women

The magnitude of fluctuating asymmetry (FA)—an indicator of genetic and phenotypic quality—can be affected by genetic perturbations, environmental stressors, and maternal effect (maternal age, diseases, dietary deficiency). Maternal effect on human FA has been typically investigated in newborns or very young children. There are no studies investigating whether maternal effect can disrupt developmental mechanisms responsible for the secondary sexual traits that are manifested at adulthood under the influence of steroid hormones. We investigated the effect of maternal degree of obesity, gestational diabetes and hypertension, and morning sickness on the magnitude of FA in nonsexual traits as well as asymmetric thigh circumference—a sexually differentiated trait—in adult daughters. Results revealed that gestational diabetes and hypertension and maternal obesity are positively associated with FA in nonsexual traits. FA in nonsexual traits was not associated with morning sickness; however, the FA in the sexual trait (thigh circumference) was positively related to third-trimester morning sickness. Fluctuating asymmetries of nonsexual traits and thigh circumference were significantly correlated. This preliminary study demonstrates a maternal effect on adult daughters' developmental instability as measured by sexual and nonsexual traits.     

Towards genetic markers in animal populations as biomonitors for human-induced environmental change

Genetic markers provide potentially sensitive indicators of changes in environmental conditions because the genetic constitution of populations is normally altered well before populations become extinct. Genetic indicators in populations include overall genetic diversity, genetic changes in traits measured at the phenotypic level, and evolution at specific loci under selection. While overall genetic diversity has rarely been successfully related to environmental conditions, genetically based changes in traits have now been linked to the presence of toxins and both local and global temperature shifts. Candidate loci for monitoring stressors are emerging from information on how specific genes influence traits, and from screens of random loci across environmental gradients. Drosophila research suggests that chromosomal regions under recent intense selection can be identified from patterns of molecular variation and a high frequency of transposable element insertions. Allele frequency changes at candidate loci have been linked to pesticides, pollutants and climate change. Nevertheless, there are challenges in interpreting allele frequencies in populations, particularly when a large number of loci control a trait and when interactions between alleles influence trait expression. To meet these challenges, population samples should be collected for longitudinal studies, and experimental programmes should be undertaken to link variation at candidate genes to ecological processes.     

Quantitative variation in obesity-related traits and insulin precursors linked to the OB gene region on human chromosome 7.

Despite the evidence that human obesity has strong genetic determinants, efforts at identifying specific genes that influence human obesity have largely been unsuccessful. Using the sibship data obtained from 32 low income Mexican American pedigrees ascertained on a type II diabetic proband and a multipoint variance-components method, we tested for linkage between various obesity-related traits plus associated metabolic traits and 15 markers on human chromosome 7. We found evidence for linkage between markers in the OB gene region and various traits, as follows: D7S514 and extremity skinfolds (LOD = 3.1), human carboxypeptidase A1 (HCPA1) and 32,33-split proinsulin level (LOD = 4.2), and HCPA1 and proinsulin level (LOD = 3.2). A putative susceptibility locus linked to the marker D7S514 explained 56% of the total phenotypic variation in extremity skinfolds. Variation at the HCPA1 locus explained 64% of phenotypic variation in proinsulin level and approximately 73% of phenotypic variation in split proinsulin concentration, respectively. Weaker evidence for linkage to several other obesity-related traits (e.g., waist circumference, body-mass index, fat mass by bioimpedance, etc.) was observed for a genetic location, which is approximately 15 cM telomeric to OB. In conclusion, our study reveals that the OB region plays a significant role in determining the phenotypic variation of both insulin precursors and obesity-related traits, at least in Mexican Americans.     

Genetic variation and correlation of dietary response in an advanced intercross mouse line produced from two divergent growth lines

Levels of human obesity have increased over the past 20 years worldwide, primarily due to changes in diet and activity levels. Although environmental changes are clearly responsible for the increasing prevalence of obesity, individuals may show genetic variation in their response to an obesogenic environment. Here, we measure genetic variation in response to a high-fat diet in a mouse model, an F16 Advanced Intercross Line derived from the cross of SM/J and LG/J inbred mouse strains. The experimental population was separated by sex and fed either a high-fat (42% of energy from fat) or low-fat (15% of energy from fat) diet. A number of phenotypic traits related to obesity and diabetes such as growth rate, glucose tolerance traits, organ weights and fat pad weights were collected and analysed in addition to serum levels of insulin, free fatty acids, cholesterol and triglycerides. Most traits are different between the sexes and between dietary treatments and for a few traits, including adult growth, fat pad weights, insulin and glucose tolerance, the dietary effect is stronger in one sex than the other. We find that fat pad weights, liver weight, serum insulin levels and adult growth rates are all phenotypically and genetically correlated with one another in both dietary treatments. Critically, these traits have relatively low genetic correlations across environments (average r =0.38). Dietary responses are also genetically correlated across these traits. We found substantial genetic variation in dietary response and low cross environment genetic correlations for traits aligned with adiposity. Therefore, genetic effects for these traits are different depending on the environment an animal is exposed to.     

Single-nucleotide polymorphisms in the TNF gene are associated with obesity-related phenotypes in vervet monkeys

Tumor necrosis factor (TNF) promoter single-nucleotide polymorphisms (SNPs) have been extensively characterized in humans, with numerous reports of associations with obesity-related phenotypes as well an array of infectious, immune-mediated, and inflammatory disease phenotypes. Controlling for the multitude of environmental risk factors in human studies has been a major confounder of efforts to elucidate the role and relative contribution of TNF promoter SNPs. As part of an ongoing initiative to further genetically and phenotypically characterize the St Kitts-origin vervet monkey (Chlorocebus aethiops ssp.) as an animal model of human obesity, we have conducted association analyses between TNF SNPs and previously defined obesity-related phenotypes in 265 pedigreed vervets. We report eight SNPs (-809G, -756A, -352C, -322A, +1285T, +2133T, +2362A, +2405), all contained within the same haplotype block and comprising a single haplotype, to be significantly associated with BMI, waist circumference, total plasma cholesterol (P < 0.05), and high-density lipoprotein-cholesterol (HDL-C) (P < 0.01). This study provides additional validation of the St Kitts-origin vervet model of obesity by demonstrating genetic associations analogous to that shown in humans.     

Molecular genetics of human obesity: A comprehensive review

Obesity and its related health complications is a major problem worldwide. Hypothalamus and their signalling molecules play a critical role in the intervening and coordination with energy balance and homeostasis. Genetic factors play a crucial role in determining an individual's predisposition to the weight gain and being obese. In the past few years, several genetic variants were identified as monogenic forms of human obesity having success over common polygenic forms. In the context of molecular genetics, genome-wide association studies (GWAS) approach and their findings signified a number of genetic variants predisposing to obesity. However, the last couple of years, it has also been noticed that alterations in the environmental and epigenetic factors are one of the key causes of obesity. Hence, this review might be helpful in the current scenario of molecular genetics of human obesity, obesity-related health complications (ORHC), and energy homeostasis. Future work based on the clinical discoveries may play a role in the molecular dissection of genetic approaches to find more obesity-susceptible gene loci.     

A genome-wide association study on obesity and obesity-related traits

Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m(2)) and 540 control subjects (BMI<25 kg/m(2)), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ～500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5 × 10(-12)). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67 × 10(-9)), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS.     

Multilocus analyses of seven candidate genes suggest interacting pathways for obesity-related traits in Brazilian populations

We investigated whether variants in major candidate genes for food intake and body weight regulation contribute to obesity-related traits under a multilocus perspective. We studied 375 Brazilian subjects from partially isolated African-derived populations (quilombos). Seven variants displaying conflicting results in previous reports and supposedly implicated in the susceptibility of obesity-related phenotypes were investigated: β2-adrenergic receptor (ADRB2) (Arg16Gly), insulin induced gene 2 (INSIG2) (rs7566605), leptin (LEP) (A19G), LEP receptor (LEPR) (Gln223Arg), perilipin (PLIN) (6209T > C), peroxisome proliferator-activated receptor-γ (PPARG) (Pro12Ala), and resistin (RETN) (-420 C > G). Regression models as well as generalized multifactor dimensionality reduction (GMDR) were employed to test the contribution of individual effects and higher-order interactions to BMI and waist-hip ratio (WHR) variation and risk of overweight/obesity. The best multilocus association signal identified in the quilombos was further examined in an independent sample of 334 Brazilian subjects of European ancestry. In quilombos, only the PPARG polymorphism displayed significant individual effects (WHR variation, P = 0.028). No association was observed either with the risk of overweight/obesity (BMI ≥ 25 kg/m2), risk of obesity alone (BMI ≥ 30 kg/m2) or BMI variation. However, GMDR analyses revealed an interaction between the LEPR and ADRB2 polymorphisms (P = 0.009) as well as a third-order effect involving the latter two variants plus INSIG2 (P = 0.034) with overweight/obesity. Assessment of the LEPR-ADRB2 interaction in the second sample indicated a marginally significant association (P = 0.0724), which was further verified to be limited to men (P = 0.0118). Together, our findings suggest evidence for a two-locus interaction between the LEPR Gln223Arg and ADRB2 Arg16Gly variants in the risk of overweight/obesity, and highlight further the importance of multilocus effects in the genetic component of obesity.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

A novel method for identifying nonlinear gene–environment interactions in case–control association studies

The genetic influences on complex disease traits generally depend on the joint effects of multiple genetic variants, environmental factors, as well as their interplays. Gene × environment (G × E) interactions play vital roles in determining an individual’s disease risk, but the underlying genetic machinery is poorly understood. Traditional analysis assuming linear relationship between genetic and environmental factors, along with their interactions, is commonly pursued under the regression-based framework to examine G × E interactions. This assumption, however, could be violated due to nonlinear responses of genetic variants to environmental stimuli. As an extension to our previous work on continuous traits, we proposed a flexible varying-coefficient model for the detection of nonlinear G × E interaction with binary disease traits. Varying coefficients were approximated by a non-parametric regression function through which one can assess the nonlinear response of genetic factors to environmental changes. A group of statistical tests were proposed to elucidate various mechanisms of G × E interaction. The utility of the proposed method was illustrated via simulation and real data analysis with application to type 2 diabetes.