Common variants near MC4R are associated with fat mass, weight and risk of obesity

Gene-environment interactions and obesity--further aspects of genomewide association studies

Advances in genotyping technologies have facilitated the advent of the genomewide association studies in large study populations and thereby led to the identification of an impressive-and still increasing-number of genetic variants with significant impact on the risk of widespread lifestyle health problems such as obesity, diabetes, and cardiovascular disease. Yet, the scientific community is a long way from reaching a comprehensive picture of the heritable components of these diseases and advancing from plain statistical significance into a biological understanding where the true contribution to a trait is recognized. Increasingly large study populations, denser single-nucleotide polymorphism mapping, deep sequencing, and raised awareness of the importance of structural variants may add to the known genetic variance underlying common complex disorders; however, genetic variance alone probably cannot account for disease susceptibility without the addition of pre- and postnatal environmental and/or behavioral factors. Moreover, an interaction between genetic and environmental factors may hinder the detection of genetic effects if not accounted for, e.g., in genomewide association studies, and prospective cohort studies have hence been proposed to surpass the classic case-control design. With a focus on obesity we describe some of the recently reported gene-environment interactions for polymorphisms identified in the FTO and INSIG2 genes. Ultimately, a thorough understanding of the gene-environment interactions underlying a common complex condition such as obesity may suggest novel treatment or intervention strategies to complement the harmful effect of detrimental genetic variation and thus may assist in improving the quality of life for affected individuals.

Exploring the unknown: assumptions about allelic architecture and strategies for susceptibility variant discovery

Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.

Obesity, serious mental illness and antipsychotic drugs

The prevalence of overweight and obesity is higher in people with mental illness than in the general population. Body weight is tightly regulated by a complex system involving the cortex and limbic system, the hypothalamus and the gastrointestinal tract. While there are justifiable concerns about the weight gain associated with antipsychotic medication, it is too simplistic to ascribe all obesity in people with serious mental illness (SMI) to their drug treatment. The development of obesity in SMI results from the complex interaction of the genotype and environment of the person with mental illness, the mental illness itself and antipsychotic medication. There are dysfunctional reward mechanisms in SMI that may contribute to poor food choices and overeating. While it is clear that antipsychotics have profound effects to stimulate appetite, no one receptor interaction provides an adequate explanation for this effect, and many mechanisms are likely to be involved. The complexity of the system regulating body weight allows us to start to understand why some individuals appear much more prone to weight gain and obesity than others.

Investigation of the locus near MC4R with childhood obesity in Americans of European and African ancestry

Recently a modest, but consistently, replicated association was demonstrated between obesity and the single-nucleotide polymorphism (SNP), rs17782313, 3' of the MC4R locus as a consequence of a meta-analysis of genome-wide association (GWA) studies of the disease in white populations. We investigated the association in the context of the childhood form of the disease utilizing data from our ongoing GWA study in a cohort of 728 European-American (EA) obese children (BMI > or =95th percentile) and 3,960 EA controls (BMI <95th percentile), as well as 1,008 African-American (AA) obese children and 2,715 AA controls. rs571312, rs10871777, and rs476828 (perfect surrogates for rs17782313) yielded odds ratios in the EA cohort of 1.142 (P = 0.045), 1.137 (P = 0.054), and 1.145 (P = 0.042); however, there was no significant association with these SNPs in the AA cohort. When investigating all 30 SNPs present on the Illumina BeadChip at this locus, again there was no evidence for association in AA cases when correcting for the number of tests employed. As such, variants 3' to the MC4R locus present on the genotyping platform utilized confer a similar magnitude of risk of obesity in white children as to their adult white counterparts but this observation did not extend to AAs.

Does greater adiposity increase blood pressure and hypertension risk?: Mendelian randomization using the FTO/MC4R genotype

Elevated blood pressure increases the risk of experiencing cardiovascular events like myocardial infarction and stroke. Current observational data suggest that body mass index may have a causal role in the etiology of hypertension, but this may be influenced by confounding and reverse causation. Through the use of instrumental variable methods, we aim to estimate the strength of the unconfounded and unbiased association between body mass index/adiposity and blood pressure. We explore these issues in the Copenhagen General Population Study. We used instrumental variable methods to obtain estimates of the causal association between body mass index and blood pressure. This was performed using both rs9939609 (FTO) and rs17782313 (MC4R) genotypes as instruments for body mass index. Avoiding the epidemiological problems of confounding, bias, and reverse causation, we confirmed observational associations between body mass index and blood pressure. In analyses including those taking antihypertensive drugs, but for whom appropriate adjustment had been made, systolic blood pressure was seen to increase by 3.85 mm Hg (95% CI: 1.88 to 5.83 mm Hg) for each 10% increase in body mass index (P=0.0002), with diastolic blood pressure showing an increase of 1.79 mm Hg (95% CI: 0.68 to 2.90 mm Hg) for each 10% increase in body mass index (P=0.002). Observed associations are large and illustrate the considerable benefits in terms of reductions in blood pressure-related morbidity that could be achieved through a reduction in body mass index.

Role of central melanocortin pathways in energy homeostasis

The rise in the global prevalence of human obesity has emphasized the need for a greater understanding of the physiological mechanisms that underlie energy homeostasis. Numerous circulating nutritional cues and central neuromodulatory signals are integrated within the brain to regulate both short- and long-term nutritional state. The central melanocortin system represents a crucial point of convergence for these signals and, thus, has a fundamental role in regulating body weight. The melanocortin ligands, synthesized in discrete neuronal populations within the hypothalamus and brainstem, modulate downstream homeostatic signalling via their action at central melanocortin-3 and -4 receptors. Intimately involved in both ingestive behaviour and energy expenditure, the melanocortin system has garnered much interest as a potential therapeutic target for human obesity.

The genetic contribution to non-syndromic human obesity

The last few years have seen major advances in common non-syndromic obesity research, much of it the result of genetic studies. This Review outlines the competing hypotheses about the mechanisms underlying the genetic and physiological basis of obesity, and then examines the recent explosion of genetic association studies that have yielded insights into obesity, both at the candidate gene level and the genome-wide level. With obesity genetics now entering the post-genome-wide association scan era, the obvious question is how to improve the results obtained so far using single nucleotide polymorphism markers and how to move successfully into the other areas of genomic variation that may be associated with common obesity.

Lean mean fat reducing "ghrelin" machine: hypothalamic ghrelin and ghrelin receptors as therapeutic targets in obesity

Obesity has reached epidemic proportions not only in Western societies but also in the developing world. Current pharmacological treatments for obesity are either lacking in efficacy and/or are burdened with adverse side effects. Thus, novel strategies are required. A better understanding of the intricate molecular pathways controlling energy homeostasis may lead to novel therapeutic intervention. The circulating hormone, ghrelin represents a major target in the molecular signalling regulating food intake, appetite and energy expenditure and its circulating levels often display aberrant signalling in obesity. Ghrelin exerts its central orexigenic action mainly in the hypothalamus and in particular in the arcuate nucleus via activation of specific G-protein coupled receptors (GHS-R). In this review we describe current pharmacological models of how ghrelin regulates food intake and how manipulating ghrelin signalling may give novel insight into developing better and more selective anti-obesity drugs. Accumulating data suggests multiple ghrelin variants and additional receptors exist to play a role in energy metabolism and these may well play an important role in obesity. In addition, the recent findings of hypothalamic GHS-R crosstalk and heterodimerization may add to the understanding of the complexity of bodyweight regulation.

The fat mass and obesity-associated (FTO) gene is associated with intramuscular fat content and growth rate in the pig

The association of the FTO gene with obesity has been implicated in various human populations. The FTO gene is also most likely involved in the regulation of energy balance and feed intake. Here, the FTO gene was studied as a candidate gene for fatness and growth rate traits in pigs. The amino acid sequence of the FTO gene showed high conservation among human, pig, and other important domestic animals. Twelve variants including ten SNPs and two indels were detected, and then five SNPs within different genomic regions were genotyped in the ISU Berkshire x Yorkshire pig resource family. The linkage disequilibrium analyses revealed that most of these FTO variants were not in strong LD with each other. The SNPs c.46-139A > T within intron 1 and a synonymous mutation c.594C > G (Ala198Ala) within exon 3 had significant (P < 0.01) associations with average daily gain on test and total lipid percentage in muscle, respectively. Five major haplotypes were identified and the subsequent association analyses suggested that haplotype 2 (-CTTGG-) was the most favorable for increased growth rate, while haplotype 1 (-CTACG-) was unfavorably associated with intramuscular fatness traits.

The effect of neurohormonal factors, epigenetic factors, and gut microbiota on risk of obesity

Molecular, cellular, and epidemiologic findings suggest that neurohormonal, epigenetic, and microbiologic mechanisms may influence risk for obesity by interacting with socioenvironmental factors. Homeostatic and nonhomeostatic neural controls of energy predispose people to obesity, and this predisposition may be exaggerated by the influence of media, marketing, and sleep patterns. Epigenetic gene regulation may account for the influence of modifiable early life or maternal exposures on obesity risk. Alterations in gut flora caused by infant feeding practices or later diet may influence the absorption and storage of energy. Further exploration of how these molecular-cellular mechanisms might increase obesity risk in response to modifiable socioeconomic factors requires the partnership of laboratory and public health researchers.

Adolescent obesity and social networks

The prevalence of overweight among children worldwide is growing at an alarming rate. Social relationships may contribute to the development of obesity through the interaction of biological, behavioral, and environmental factors. Although there is evidence that early environment influences the expression of obesity, very little research elucidates the social context of obesity among children or adolescents. Social network approaches can contribute to research on the role of social environments in overweight and obesity and strengthen interventions to prevent disease and promote health. By capitalizing on the structure of the network system, a targeted intervention that uses social relationships in families, schools, neighborhoods, and communities may be successful in encouraging healthful behaviors among children and their families.

The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts

BACKGROUND

In a genome-wide association study performed in the Framingham Offspring Cohort, individuals homozygous for the rs7566605 C allele located upstream of insulin-induced gene 2 (INSIG2) were reported to incur an increased risk of obesity. This finding was later replicated in four out of five populations examined. The goal of the study reported here was to assess the role of the INSIG2 single nucleotide polymorphism (SNP) in susceptibility to obesity in the prospective longitudinal Atherosclerosis Risk in Communities (ARIC) study (n = 14,566) and in three other cohorts: the Coronary Artery Risk Development in Young Adults (CARDIA) study (n = 3,888), the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 4,766), and extremely obese and lean individuals ascertained at the University of Ottawa (n = 1,502). The combined study sample is comprised of 24,722 white, African-American, and Mexican-American participants.

METHODS

Differences in mean body mass index (BMI) and other anthropometric measures including weight, waist circumference, and waist-to-hip ratio were assessed by a general linear model in individuals categorized by INSIG2 rs7566605 genotype. Multivariable logistic regression was used to predict the risk of obesity (BMI >or= 30 kg/m2).

RESULTS

There was no discernable variation in the frequencies of the three INSIG2 SNP genotypes observed between white, Hispanic, and African-American obese individuals and non-obese study subjects. When the relationship between rs7566605 and BMI considered either as a categorical variable or a continuous variable was examined, no significant association with obesity was found for participants in any of the four study populations or in a combined analysis (p = 0.38) under a recessive genetic model. There was also no association between the INSIG2 polymorphism and the obesity-related quantitative traits except for a reduced waist-to-hip ratio in white ARIC study participants homozygous for the C allele, and an increased waist-to-hip ratio in African-Americans in the ARIC cohort with the same genotype (p = 0.04 and p = 0.01, respectively). An association with waist-to-hip ratio was not seen when the combined study sample was analyzed (p = 0.74).

CONCLUSION

These results suggest that the INSIG2 rs7566605 variant does not play a major role in determining obesity risk in a racially and ethnically diverse sample of 24,722 individuals from four cohorts.

Genome-wide association study identifies eight loci associated with blood pressure

Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.

NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Tissue-to-tissue coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific genes.

Background

Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus and several metabolic tissues, resulting in an energy imbalance at the systems level.

Results

To provide an inter-tissue view of obesity with respect to molecular states that are associated with physiological states, we developed a framework for constructing tissue-to-tissue coexpression networks between genes in the hypothalamus, liver or adipose tissue. These networks have a scale-free architecture and are strikingly independent of gene-gene coexpression networks that are constructed from more standard analyses of single tissues. This is the first systematic effort to study inter-tissue relationships and highlights genes in the hypothalamus that act as information relays in the control of peripheral tissues in obese mice. The subnetworks identified as specific to tissue-to-tissue interactions are enriched in genes that have obesity-relevant biological functions such as circadian rhythm, energy balance, stress response, or immune response.

Conclusions

Tissue-to-tissue networks enable the identification of disease-specific genes that respond to changes induced by different tissues and they also provide unique details regarding candidate genes for obesity that are identified in genome-wide association studies. Identifying such genes from single tissue analyses would be difficult or impossible.

Genome-wide association study identifies sequence variants on 6q21 associated with age at menarche

Earlier menarche correlates with shorter adult height and higher childhood body fat. We conducted a genome-wide association study of age at menarche (AAM) on 15,297 Icelandic women. Combined analysis with replication sets from Iceland, Denmark and the Netherlands (N = 10,040) yielded a significant association between rs314280[T] on 6q21, near the LIN28B gene, and AAM (effect = 1.2 months later per allele; P = 1.8 × 10(-14)). A second SNP within the same linkage disequilibrium (LD) block, rs314277, splits rs314280[T] into two haplotypes with different effects (0.9 months and 1.9 months per allele). These variants have been associated with greater adult height. The association with adult height did not account for the association with AAM or vice versa. Other variants, previously associated with height, did not associate significantly with AAM. Given the link between body fat and AAM, we also assessed 11 variants recently associated with higher body mass index (BMI) and 5 of those associated with earlier AAM.

Epilepsy pharmacogenetics

Large interindividual variation in efficacy and adverse effects of anti-epileptic therapy presents opportunities and challenges in pharmacogenomics. Although the first true association of genetic polymorphism in drug-metabolizing enzymes with anti-epileptic drug dose was reported 10 years ago, most of the findings have had little impact on clinical practice so far. Most studies performed to date examined candidate genes and were focused on candidate gene selection. Genome-wide association and whole-genome sequencing technologies empower hypothesis-free comprehensive screening of genetic variation across the genome and now the main challenge remaining is to select and study clinically relevant phenotypes suitable for genetic studies. Here we review the current state of epilepsy pharmacogenetics focusing on phenotyping questions and discuss what characteristics we need to study to get answers.

Combined effects of MC4R and FTO common genetic variants on obesity in European general populations

Genome-wide association scans recently identified common polymorphisms, in intron 1 of FTO and 188 kb downstream MC4R, that modulate body mass index (BMI) and associate with increased risk of obesity. Although their individual contribution to obesity phenotype is modest, their combined effects and their interactions with environmental factors remained to be evaluated in large general populations from birth to adulthood. In the present study, we analyzed independent and combined effects of the FTO rs1421085 and MC4R rs17782313 risk alleles on BMI, fat mass, prevalence and incidence of obesity and subsequent type 2 diabetes (T2D) as well as their interactions with physical activity levels and gender in two European prospective population-based cohorts of 4,762 Finnish adolescents (NFBC 1986) and 3,167 French adults (D.E.S.I.R.). Compared to participants carrying neither FTO nor MC4R risk allele (20-24% of the populations), subjects with three or four risk alleles (7-10% of the populations) had a 3-fold increased susceptibility of developing obesity during childhood. In adults, their combined effects were more modest (approximately 1.8-fold increased risk) and associated with a 1.27% increase in fat mass (P = 0.001). Prospectively, we demonstrated that each FTO and MC4R risk allele increased obesity and T2D incidences by 24% (P = 0.02) and 21% (P = 0.02), respectively. However, the effect on T2D disappeared after adjustment for BMI. The Z-BMI and ponderal index of newborns homozygous for the rs1421085 C allele were 0.1 units (P = 0.02) and 0.27 g/cm(3) (P = 0.005) higher, respectively, than in those without FTO risk allele. The MC4R rs17782313 C allele was more associated with obesity and fat mass deposition in males than in females (P = 0.003 and P = 0.03, respectively) and low physical activity accentuated the effect of the FTO polymorphism on BMI increase and obesity prevalence (P = 0.008 and P = 0.01, respectively). In European general populations, the combined effects of common polymorphisms in FTO and MC4R are therefore additive, predictive of obesity and T2D, and may be influenced by interactions with physical activity levels and gender, respectively.

Psychiatric GWAS Consortium Coordinating Committee, Cichon S, Craddock N, Daly M, Faraone SV, Gejman PV, Kelsoe J, Lehner T, Levinson DF, Moran A, Sklar P, Sullivan PF. Genomewide association studies: history, rationale, and prospects for psychiatric disorders

OBJECTIVE

The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses.

METHOD

A literature review was carried out, power and other issues discussed, and planned studies assessed.

RESULTS

Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress.

CONCLUSIONS

GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

Admixture mapping of 15,280 African Americans identifies obesity susceptibility loci on chromosomes 5 and X

The prevalence of obesity (body mass index (BMI) > or =30 kg/m(2)) is higher in African Americans than in European Americans, even after adjustment for socioeconomic factors, suggesting that genetic factors may explain some of the difference. To identify genetic loci influencing BMI, we carried out a pooled analysis of genome-wide admixture mapping scans in 15,280 African Americans from 14 epidemiologic studies. Samples were genotyped at a median of 1,411 ancestry-informative markers. After adjusting for age, sex, and study, BMI was analyzed both as a dichotomized (top 20% versus bottom 20%) and a continuous trait. We found that a higher percentage of European ancestry was significantly correlated with lower BMI (rho = -0.042, P = 1.6x10(-7)). In the dichotomized analysis, we detected two loci on chromosome X as associated with increased African ancestry: the first at Xq25 (locus-specific LOD = 5.94; genome-wide score = 3.22; case-control Z = -3.94); and the second at Xq13.1 (locus-specific LOD = 2.22; case-control Z = -4.62). Quantitative analysis identified a third locus at 5q13.3 where higher BMI was highly significantly associated with greater European ancestry (locus-specific LOD = 6.27; genome-wide score = 3.46). Further mapping studies with dense sets of markers will be necessary to identify the alleles in these regions of chromosomes X and 5 that may be associated with variation in BMI.

Childhood obesity: are genetic differences involved?

This brief review focuses on the genetic contribution to childhood obesity. Evidence for a genetic component to excess body weight during growth is presented from the perspective of genetic epidemiology studies. Parental obesity is a predictor of childhood excess weight. The familial risk ratio for childhood obesity when a parent is obese reaches >2.5. Birth weight is characterized by a genetic heritability component on the order of 30%, with significant maternal and paternal effects in addition to the newborn genes. About 5% of childhood obesity cases are caused by a defect that impairs function in a gene, and >/=5 of these genes have been uncovered. However, the common forms of childhood obesity seem to result from a predisposition that primarily favors obesogenic behaviors in an obesogenic environment. Candidate gene and genomewide association studies reveal that these obesogenic genes have small effect sizes but that the risk alleles for obesity are quite common in populations. The latter may translate into a highly significant population-attributable risk of obesity. Gene-environment interaction studies suggest that the effects of predisposing genes can be enhanced or diminished by exposure to relevant behaviors. It is possible that the prevalence of childhood obesity is increasing across generations as a result of positive assortative mating with obese husbands and wives contributing more obese offspring than normal-weight parents.

A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits

To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 x 10(-9)) and 6q22 (rs12110693, P = 1.6 x 10(-9)), with the latter approximately 400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 x 10(-7)). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 x 10(-12)) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 x 10(-11)), tibia (P = 1.6 x 10(-6)) and heel (P = 1.9 x 10(-10)). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 x 10(-3), P = 1.4 x 10(-7) and P = 6.0 x 10(-4), respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways.

Genetic variance in the adiponutrin gene family and childhood obesity

Aim

The adiponutrin gene family consists of five genes (PNPLA1-5) coding for proteins with both lipolytic and lipogenic properties. PNPLA3 has previously been associated with adult obesity. Here we investigated the possible association between genetic variants in these genes and childhood and adolescent obesity.

Methods/Results

Polymorphisms in the five genes of the adiponutrin gene family were selected and genotyped using the Sequenom platform in a childhood and adolescent obesity case-control study. Six variants in PNPLA1 showed association with obesity (rs9380559, rs12212459, rs1467912, rs4713951, rs10947600, and rs12199580, p<0.05 after adjustment for age and gender). Three variants in PNPLA3 showed association with obesity before, but not after, adjustment for age and gender (rs139051, rs12483959, and rs2072907, p>0.05). When analyzing these SNPs in relation to phenotypes, two SNPs in the PNPLA3 gene showed association with insulin sensitivity (rs12483959: β = −0.053, p = 0.016, and rs2072907: β = −0.049, p = 0.024). No associations were seen for PNPLA2, PNPLA4, and PNPLA5.

Conclusions

Genetic variation in the adiponutrin gene family does not seem to contribute strongly to obesity in children and adolescents. PNPLA1 exhibited a modest effect on obesity and PNPLA3 on insulin sensitivity. These data, however, require confirmation in other cohorts and ethnic groups.

Joint effects of common genetic variants on the risk for type 2 diabetes in U.S. men and women of European ancestry

BACKGROUND

Genome-wide association studies have identified novel type 2 diabetes loci, each of which has a modest impact on risk.

OBJECTIVE

To examine the joint effects of several type 2 diabetes risk variants and their combination with conventional risk factors on type 2 diabetes risk in 2 prospective cohorts.

DESIGN

Nested case-control study.

SETTING

United States.

PARTICIPANTS

2809 patients with type 2 diabetes and 3501 healthy control participants of European ancestry from the Health Professionals Follow-up Study and Nurses' Health Study.

MEASUREMENTS

A genetic risk score (GRS) was calculated on the basis of 10 polymorphisms in 9 loci.

RESULTS

After adjustment for age and body mass index (BMI), the odds ratio for type 2 diabetes with each point of GRS, corresponding to 1 risk allele, was 1.19 (95% CI, 1.14 to 1.24) and 1.16 (CI, 1.12 to 1.20) for men and women, respectively. Persons with a BMI of 30 kg/m(2) or greater and a GRS in the highest quintile had an odds ratio of 14.06 (CI, 8.90 to 22.18) compared with persons with a BMI less than 25 kg/m(2) and a GRS in the lowest quintile after adjustment for age and sex. Persons with a positive family history of diabetes and a GRS in the highest quintile had an odds ratio of 9.20 (CI, 5.50 to 15.40) compared with persons without a family history of diabetes and with a GRS in the lowest quintile. The addition of the GRS to a model of conventional risk factors improved discrimination by 1% (P < 0.001).

LIMITATION

The study focused only on persons of European ancestry; whether GRS is associated with type 2 diabetes in other ethnic groups remains unknown.

CONCLUSION

Although its discriminatory value is currently limited, a GRS that combines information from multiple genetic variants might be useful for identifying subgroups with a particularly high risk for type 2 diabetes.

PRIMARY FUNDING SOURCE

National Institutes of Health.

A novel variant on chromosome 7q22.3 associated with mean platelet volume, counts, and function

Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genome-wide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 +/- 0.001 log fL; P < 1.08 x 10(-24)) and PLT (per-G effect -4.55 +/- 0.80 10(9)/L; P < 7.19 x 10(-8)) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n = 35; P = .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n = 84; P = .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis.

Down syndrome--recent progress and future prospects

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and is associated with a number of deleterious phenotypes, including learning disability, heart defects, early-onset Alzheimer's disease and childhood leukaemia. Individuals with DS are affected by these phenotypes to a variable extent; understanding the cause of this variation is a key challenge. Here, we review recent research progress in DS, both in patients and relevant animal models. In particular, we highlight exciting advances in therapy to improve cognitive function in people with DS and the significant developments in understanding the gene content of Hsa21. Moreover, we discuss future research directions in light of new technologies. In particular, the use of chromosome engineering to generate new trisomic mouse models and large-scale studies of genotype-phenotype relationships in patients are likely to significantly contribute to the future understanding of DS.

MRAP and MRAP2 are bidirectional regulators of the melanocortin receptor family

The melanocortin receptor (MCR) family consists of 5 G protein-coupled receptors (MC1R-MC5R) with diverse physiologic roles. MC2R is a critical component of the hypothalamic-pituitary-adrenal axis, whereas MC3R and MC4R have an essential role in energy homeostasis. Mutations in MC4R are the single most common cause of monogenic obesity. Investigating the way in which these receptors signal and traffic to the cell membrane is vital in understanding disease processes related to MCR dysfunction. MRAP is an MC2R accessory protein, responsible for adrenal MC2R trafficking and function. Here we identify MRAP2 as a unique homologue of MRAP, expressed in brain and the adrenal gland. We report that MRAP and MRAP2 can interact with all 5 MCRs. This interaction results in MC2R surface expression and signaling. In contrast, MRAP and MRAP2 can reduce MC1R, MC3R, MC4R, and MC5R responsiveness to [Nle4,D-Phe7]alpha-melanocyte-stimulating hormone (NDP-MSH). Collectively, our data identify MRAP and MRAP2 as unique bidirectional regulators of the MCR family.

Gene X environment interaction of vigorous exercise and body mass index among male Vietnam-era twins

BACKGROUND

Secular trends over the past several decades suggest an environmental influence on body mass index (BMI). However, twin models that incorporate a gene-environment correlation and gene x environment interaction have not been applied to elucidate specific environmental factors that affect the heritability of BMI.

OBJECTIVE

Our aim was to determine whether one putative environmental predictor of obesity, vigorous exercise, shows evidence of a gene-environment correlation or gene x environment interaction with BMI among twins.

DESIGN

Twin structural equation modeling was used to examine a gene-environment correlation and a gene x environment interaction of vigorous exercise with BMI among 2710 monozygotic and 2327 dizygotic male-male twin pairs from the Vietnam Era Twin Registry -- a national registry of twin pairs who served in the military during the Vietnam War era.

RESULTS

Vigorous exercise significantly modified the additive genetic component of BMI, which indicated a gene x environment interaction (P < 0.001). BMI showed the greatest genetic influence among those who did not report vigorous exercise, with diminished genetic influence among those who did. Furthermore, vigorous exercise had a small but significant environmental effect on BMI (P = 0.006) -- a finding confirmed among monozygotic co-twins discordant for vigorous exercise.

CONCLUSIONS

Genetic influences on BMI are lower among those who report vigorous exercise. Consistent with an emerging literature, this suggests that vigorous exercise may mitigate some of the genetic influence on obesity. Molecular genetic studies of obesity should consider incorporating measures of behavioral and demographic factors to maximize the identification of novel obesity genes.

Proper analysis of secondary phenotype data in case-control association studies

Case-control association studies often collect extensive information on secondary phenotypes, which are quantitative or qualitative traits other than the case-control status. Exploring secondary phenotypes can yield valuable insights into biological pathways and identify genetic variants influencing phenotypes of direct interest. All publications on secondary phenotypes have used standard statistical methods, such as least-squares regression for quantitative traits. Because of unequal selection probabilities between cases and controls, the case-control sample is not a random sample from the general population. As a result, standard statistical analysis of secondary phenotype data can be extremely misleading. Although one may avoid the sampling bias by analyzing cases and controls separately or by including the case-control status as a covariate in the model, the associations between a secondary phenotype and a genetic variant in the case and control groups can be quite different from the association in the general population. In this article, we present novel statistical methods that properly reflect the case-control sampling in the analysis of secondary phenotype data. The new methods provide unbiased estimation of genetic effects and accurate control of false-positive rates while maximizing statistical power. We demonstrate the pitfalls of the standard methods and the advantages of the new methods both analytically and numerically. The relevant software is available at our website.

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.

Meta-analysis of genome-wide scans for human adult stature identifies novel Loci and associations with measures of skeletal frame size

Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1x10(-8) and rs910316 in TMED10, P-value = 1.4x10(-7)) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3x10(-7) and rs849141 in JAZF1, P-value = 3.2x10(-11)). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4x10(-5) and rs6817306 in LCORL, P-value = 4x10(-4)), hip axis length (including rs6830062 at LCORL, P-value = 4.8x10(-4) and rs4911494 at UQCC, P-value = 1.9x10(-4)), and femur length (including rs710841 at PRKG2, P-value = 2.4x10(-5) and rs10946808 at HIST1H1D, P-value = 6.4x10(-6)). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height.

Integrating post-genomic approaches as a strategy to advance our understanding of health and disease

Following the publication of the complete human genomic sequence, the post-genomic era is driven by the need to extract useful information from genomic data. Genomics, transcriptomics, proteomics, metabolomics, epidemiological data and microbial data provide different angles to our understanding of gene-environment interactions and the determinants of disease and health. Our goal and our challenge are to integrate these very different types of data and perspectives of disease into a global model suitable for dissecting the mechanisms of disease and for predicting novel therapeutic strategies. This review aims to highlight the need for and problems with complex data integration, and proposes a framework for data integration. While there are many obstacles to overcome, biological models based upon multiple datasets will probably become the basis that drives future biomedical research.

The PsyCoLaus study: methodology and characteristics of the sample of a population-based survey on psychiatric disorders and their association with genetic and cardiovascular risk factors

BACKGROUND

The Psychiatric arm of the population-based CoLaus study (PsyCoLaus) is designed to: 1) establish the prevalence of threshold and subthreshold psychiatric syndromes in the 35 to 66 year-old population of the city of Lausanne (Switzerland); 2) test the validity of postulated definitions for subthreshold mood and anxiety syndromes; 3) determine the associations between psychiatric disorders, personality traits and cardiovascular diseases (CVD), 4) identify genetic variants that can modify the risk for psychiatric disorders and determine whether genetic risk factors are shared between psychiatric disorders and CVD. This paper presents the method as well as sociodemographic and somatic characteristics of the sample.

METHODS

All 35 to 66 year-old persons previously selected for the population-based CoLaus survey on risk factors for CVD were asked to participate in a substudy assessing psychiatric conditions. This investigation included the Diagnostic Interview for Genetic Studies to elicit diagnostic criteria for threshold disorders according to DSM-IV and algorithmically defined subthreshold syndromes. Complementary information was collected on potential risk and protective factors for psychiatric disorders, migraine and on the morbidity of first-degree relatives, whereas the collection of DNA and plasma samples was already part of the original CoLaus survey.

RESULTS

A total of 3,691 individuals completed the psychiatric evaluation (67% participation). The gender distribution of the sample did not differ significantly from that of the general population in the same age range. Although the youngest 5-year band of the cohort was underrepresented and the oldest 5-year band overrepresented, participants of PsyCoLaus and individuals who refused to participate revealed comparable scores on the General Health Questionnaire, a self-rating instrument completed at the somatic exam.

CONCLUSION

Despite limitations resulting from the relatively low participation in the context of a comprehensive and time-consuming investigation, the PsyCoLaus study should significantly contribute to the current understanding of psychiatric disorders and comorbid somatic conditions by: 1) establishing the clinical relevance of specific psychiatric syndromes below the DSM-IV threshold; 2) determining comorbidity between risk factors for CVD and psychiatric disorders; 3) assessing genetic variants associated with common psychiatric disorders and 4) identifying DNA markers shared between CVD and psychiatric disorders.

Narrowing down the role of common variants in the genetic predisposition to obesity

The extent to which common variants contribute to common phenotypes and disease in humans has important consequences for the future of medical genomics. Two reports have recently clarified this issue for one of the most pressing public health concerns, obesity. These large and comprehensive genome-wide association studies find that common variants within at least 11 genes are associated with obesity. Interestingly, most of these genes are highly expressed in the central nervous system, further highlighting its role in the pathogenesis of obesity. However, the individual and combined effects of these variants explain only a small fraction of the inherited variability in obesity, suggesting that rare variants may contribute significantly to the genetic predisposition for this condition.

Mouse models for the central melanocortin system

Obesity is characterized by an excess storage of body fat and promotes the risk for complex disease traits such as diabetes mellitus and cardiovascular diseases. The obesity prevalence in Europe is rising and meanwhile ranges from 10 to 20% in men and 15-25% in women. Body fat accumulation occurs in states of positive energy balance and is favored by interactions among environmental, psychosocial and genetic factors. Energy balance is regulated by a complex neuronal network of anorexigenic and orexigenic neurons which integrates peripheral and central hormonal and neuronal signals relaying information on the metabolic status of organs and tissues in the body. A key component of this network is the central melanocortin pathway in the hypothalamus that elicits metabolic and behavioral adaptations for the maintenance of energy homeostasis. Genetic defects in this system cause obesity in mice and humans. In this review we emphasize mouse models with spontaneous natural mutations as well as targeted mutations that contributed to our understanding of the central melanocortin system function in the control of energy balance.

Common variation at the adiponectin locus is not associated with colorectal cancer risk in the UK

A recent study examined common genetic variants at the adiponectin locus (ADIPOQ) in two case-control colorectal cancer (CRC) series from the USA and reported a positive association between a single nucleotide polymorphism (SNP) in the 5' region of the gene (rs266729) and decreased disease risk. In an attempt to replicate the previously reported association, we examined data from two CRC genome-wide association studies based on the UK population. The first cohort comprised 931 familial colorectal tumour cases and 929 cancer-free controls. The second included 1216 individuals with Dukes stage B or C CRCs from two clinical trials and 1436 controls from the 1958 Birth Cohort. We tested associations between CRC risk and 82 SNPs in a region of 250 kb around the ADIPOQ gene; nine of these SNPs were located in the coding and promoter regions. None of the markers tested was significantly associated with CRC risk after correction for multiple testing under any of the models in any of the two cohorts. A meta-analysis of the data also failed to detect any association. We, therefore, failed to replicate an association between common variants at ADIPOQ and CRC risk in the UK, and suggest that the previous report is either population-specific or a false-positive result.

How does body fat influence bone mass in childhood? A Mendelian randomization approach

Fat mass may be a causal determinant of bone mass, but the evidence is conflicting, possibly reflecting the influence of confounding factors. The recent identification of common genetic variants related to obesity in children provides an opportunity to implement a Mendelian randomization study of obesity and bone outcomes, which is less subject to confounding and several biases than conventional approaches. Genotyping was retrieved for variants of two loci reliably associated with adiposity (the fat mass and obesity-related gene FTO and that upstream of the MC4R locus) within 7470 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) who had undergone total body DXA scans at a mean of 9.9 yr. Relationships between both fat mass/genotypes and bone measures were assessed in efforts to determine evidence of causality between adiposity and bone mass. In conventional tests of association, both with and without height adjustment, total fat mass was strongly related to total body, spinal, and upper and lower limb BMC (ratio of geometric means [RGM]: 1.118 [95% CI: 1.112, 1.123], 1.110 [95% CI: 1.102, 1.119], 1.101 [95% CI: 1.093, 1.108], 1.146 [95% CI: 1.143, 1.155]; p < 10(-10) [adjusted for sex, height, and sitting height]). Equivalent or larger effects were obtained from instrumental variable (IV) regression including the same covariates (1.139 [95% CI: 1.064, 1.220], 1.090 [95% CI: 1.010, 1.177], 1.142 [95% CI: 1.049, 1.243], 1.176 [95% CI: 1.099, 1.257]; p = 0.0002, 0.03, 0.002, and 2.3(-6) respectively). Similar results were obtained after adjusting for puberty, when truncal fat mass was used in place of total fat, and when bone area was used instead of bone mass. In analyses where total body BMC adjusted for bone area (BA) was the outcome (reflecting volumetric BMD), linear regression with fat mass showed evidence for association (1.004 [95% CI: 1.002, 1.007], p = 0.0001). IV regression also showed a positive effect (1.031 [95% CI: 1.000, 1.062], p = 0.05). When MC4R and FTO markers were used as instruments for fat mass, similar associations with BMC were seen to those with fat mass as measured by DXA. This suggests that fat mass is on the causal pathway for bone mass in children. In addition, both directly assessed and IV-assessed relationships between fat mass and volumetric density showed evidence for positive effects, supporting a hypothesis that fat effects on bone mass are not entirely accounted for by association with overall bone size.

Variants near MC4R are associated with obesity and influence obesity-related quantitative traits in a population of middle-aged people: studies of 14,940 Danes

OBJECTIVE

Variants downstream of the melanocortin-4 receptor gene (MC4R) have been reported to associate with obesity. We examined rs17782313, rs17700633, rs12970134, rs477181, rs502933, and rs4450508 near MC4R for association with obesity-related quantitative traits, obesity, and type 2 diabetes in Danish individuals.

RESEARCH DESIGN AND METHODS

The variants were investigated for association with obesity-related quantitative traits in 5,807 population-based sampled individuals, obesity in 14,940 individuals, and type 2 diabetes in 8,821 individuals.

RESULTS

The minor risk alleles of rs17782313, rs17700633, and rs12970134 were associated with BMI (effect per allele 0.25 kg/m2, P = 0.01; 0.23, P = 0.01; and 0.31, P = 7 x 10(-4), respectively), waist circumference (0.67 cm, P = 0.006; 0.53, P = 0.02; and 0.85, P = 3 x 10(-4)), and body weight (1.04 kg, P = 6 x 10(-4); 0.71, P = 0.01; and 1.16, P = 8 x 10(-5)). In case-control studies of obesity defined by BMI, the minor C-allele of rs17782313 was associated with overweight/obesity and obesity (odds ratio [OR] 1.09, P = 0.006 and OR 1.12, P = 0.003, respectively). Similarly, the minor A-allele of rs17700633 was associated with overweight/obesity and obesity (1.12, P = 8 x 10(-5) and 1.16, P = 2 x 10(-5)), and the minor A-allele of rs12970134 was also associated with overweight/obesity and obesity (1.13, P = 2 x 10(-5) and 1.15, P = 6 x 10(-5)). rs477181, rs502933, and rs4450508 were not significantly associated with obesity in the Danish population. The frequency of the minor risk alleles of rs17782313 and rs12970134 was higher among patients with type 2 diabetes than among glucose-tolerant individuals (OR 1.08, P = 0.08 and 1.08, P = 0.06, respectively); however, these borderline associations were abolished after adjustment for BMI.

CONCLUSIONS

rs17782313, rs17700633, and rs12970134 near MC4R associate with measures of obesity in Danish individuals.

Environmental exposure measurement in cancer epidemiology

Environmental exposures, used in the broadest sense of lifestyle, infections, radiation, natural and man-made chemicals and occupation, are a major cause of human cancer. However, the precise contribution of specific risk factors and their interaction, both with each other and with genotype, continues to be difficult to elucidate. This is partially due to limitations in accurately measuring exposure with the subsequent risk of misclassification. One of the primary challenges of molecular cancer epidemiology therefore is to improve exposure assessment. Progress has been made with biomarkers such as carcinogens and their metabolites, DNA and protein adducts and mutations measured in various tissues and body fluids. Nevertheless, much remains to be accomplished in order to establish aetiology and provide the evidence base for public health decisions. This review considers some of the principles behind the application of exposure biomarkers in cancer epidemiology. It also demonstrates how the same biomarkers can contribute both to establishing the biological plausibility of associations between exposure and disease and be valuable endpoints in intervention studies. The potential of new technologies such as transcriptomics, proteomics and metabonomics to provide a step change in environmental exposure assessment is discussed. An increasing recognition of the role of epigenetic changes in carcinogenesis presents a fresh challenge as alterations in DNA methylation, histone modification and microRNA in response to environmental exposures demand a new generation of exposure biomarker. The overall importance of this area of research is brought into sharp relief by the large prospective cohort studies (e.g. UK Biobank) which need accurate exposure measurement in order to shed light on the complex gene:environment interactions underlying common chronic disorders including cancer. It is suggested that a concerted effort is now required, with appropriate funding, to develop and validate the required exposure assessment methodology before these cohorts come to maturity.

Leptin at 14 y of age: an ongoing story

The cloning of the ob gene and its gene product leptin has led to the elucidation of a robust physiologic system that maintains constancy of fat stores. Leptin is a peptide hormone secreted by adipose tissue and regulates adipose tissue mass and energy balance. Recessive mutations in the leptin gene are associated with massive obesity in mice and in some humans, which establishes a genetic basis for obesity. Leptin circulates in blood and acts on the brain to regulate food intake and energy expenditure. When fat mass decreases, plasma leptin concentrations decrease, which stimulates appetite and suppresses energy expenditure until fat mass is restored. When fat mass increases, leptin concentrations increase, which suppresses appetite until weight is lost. This system maintains homeostatic control of adipose tissue mass.

Common genetic variation near MC4R is associated with eating behaviour patterns in European populations

Both rs17782313 (near MC4R) and rs1421085 (FTO) polymorphisms have been consistently associated with increased risk of obesity and with body mass index (BMI) variation. An effect of both polymorphisms on satiety has recently been suggested. We genotyped rs17782313 and rs1421085 in 5764 relatives from 1109 French pedigrees with familial obesity, 1274 Swiss class III obese adults as well as in 4877 French adults and 5612 Finnish teenagers from two randomly selected population cohorts. In all subjects, eating behaviour traits were documented through questionnaires. We first assessed the association of both single nucleotide polymorphisms with BMI and then studied eating behaviour. Under an additive model, the rs17782313-C MC4R allele showed a trend towards higher percentages of snacking in both French obese children (P=0.01) and Swiss obese adults (P=0.04) as well as in adolescents from the Finnish general population (P=0.04). In French adults with familial obesity, this allele tended to be also associated with a higher Stunkard hunger score (P=0.02) and in obese children with a higher prevalence of eating large amounts of food (P=0.04). However, no consistent association of the FTO rs1421085-C allele and available eating behaviour trait was found in our studied populations. The rs17782313-C allele nearby MC4R may modulate eating behaviour-related phenotypes in European obese and randomly selected populations, in both children and adults, supporting a regulatory role of this genetic variant on eating behaviour, as previously shown for MC4R non-synonymous loss-of-function mutations. The potential effect of the obesity-associated FTO gene on eating behaviour deserves additional investigation.

Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease

Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

Gene-environment interaction and obesity

The epidemic of obesity has become a major public health problem. Common-form obesity is underpinned by both environmental and genetic factors. Epidemiological studies have documented that increased intakes of energy and reduced consumption of high-fiber foods, as well as sedentary lifestyle, were among the major driving forces for the epidemic of obesity. Recent genome-wide association studies have identified several genes convincingly related to obesity risk, including the fat mass and obesity associated gene and the melanocortin-4 receptor gene. Testing gene-environment interaction is a relatively new field. This article reviews recent advances in identifying the genetic and environmental risk factors (lifestyle and diet) for obesity. The evidence for gene-environment interaction, especially from observational studies and randomized intervention trials, is examined specifically. Knowledge about the interplay between genetic and environmental components may facilitate the choice of more effective and specific measures for obesity prevention based on the personalized genetic make-up.

Non-replication of an association of CTNNBL1 polymorphisms and obesity in a population of Central European ancestry

BACKGROUND

A recent genome-wide association (GWA) study of U.S. Caucasians suggested that eight single nucleotide polymorphisms (SNPs) in CTNNBL1 are associated with obesity and increased fat mass. We analysed the respective SNPs in data from our previously published GWA for early onset obesity (case-control design), in GWA data from a population-based cohort of adults, and in an independent family-based obesity study. We investigated whether variants in CTNNBL1 (including rs6013029) and in three other genes (SH3PXD2B, SLIT3 and FLJ42133,) were associated with obesity.

METHODS

The GWA studies were carried out using Affymetrix(R) SNP Chips with approximately 500,000 markers each. In the families, SNP rs6013029 was genotyped using the TaqMan(R) allelic discrimination assay. The German case-control GWA included 487 extremely obese children and adolescents and 442 healthy lean individuals. The adult GWA included 1,644 individuals from a German population-based study (KORA). The 775 independent German families consisted of extremely obese children and adolescents and their parents.

RESULTS

We found no evidence for an association of the reported variants in CTNNBL1 with early onset obesity or increased BMI. Further, in our family-based study we found no evidence for over-transmission of the rs6013029 risk-allele T to obese children. Additionally, we found no evidence for an association of SH3PXD2B, SLIT3 and FLJ42133 variants in our two GWA samples.

CONCLUSION

We detected no confirmation of the recent association of variants in CTNNBL1 with obesity in a population of Central European ancestry.

Genotype-imputation accuracy across worldwide human populations

A current approach to mapping complex-disease-susceptibility loci in genome-wide association (GWA) studies involves leveraging the information in a reference database of dense genotype data. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and tested for disease association. This imputation strategy has been successful for GWA studies in populations well represented by existing reference panels. We used genotypes at 513,008 autosomal single-nucleotide polymorphism (SNP) loci in 443 unrelated individuals from 29 worldwide populations to evaluate the "portability" of the HapMap reference panels for imputation in studies of diverse populations. When a single HapMap panel was leveraged for imputation of randomly masked genotypes, European populations had the highest imputation accuracy, followed by populations from East Asia, Central and South Asia, the Americas, Oceania, the Middle East, and Africa. For each population, we identified "optimal" mixtures of reference panels that maximized imputation accuracy, and we found that in most populations, mixtures including individuals from at least two HapMap panels produced the highest imputation accuracy. From a separate survey of additional SNPs typed in the same samples, we evaluated imputation accuracy in the scenario in which all genotypes at a given SNP position were unobserved and were imputed on the basis of data from a commercial "SNP chip," again finding that most populations benefited from the use of combinations of two or more HapMap reference panels. Our results can serve as a guide for selecting appropriate reference panels for imputation-based GWA analysis in diverse populations.