A common genetic variant is associated with adult and childhood obesity

An exploration of the relationship between back muscle endurance and familial, physical, lifestyle, and psychosocial factors in adolescents and young adults

STUDY DESIGN

Cross-sectional investigation.

OBJECTIVE

To explore the relationship between back muscle endurance (BME) and a range of familial, physical, lifestyle, and psychosocial variables in adolescents and young adults.

BACKGROUND

There is evidence that low back pain interventions which focus on improved BME are effective. However, the mechanisms associated with BME performance in adolescents and young adults are largely unclear. In particular, the potential familial relationship between parents and their children remains unexplored.

METHODS

This study utilized a subset of participants from the Joondalup Spinal Health Study cohort. One hundred nine children (47 boys, 62 girls) and 101 parents (39 fathers, 62 mothers) completed a series of physical, lifestyle, and psychosocial assessments. The univariable relationship between each covariate and BME was explored. Those found to have an association with child BME (P<.2) were included in an initial multivariable model and sequentially removed, until all remaining covariates were statistically significant (P<.05).

RESULTS

Mothers' BME performance was related to children's performance, accounting for 14.4% of the variance in the children's BME. Fathers' BME performance had a similar, albeit nonsignificant effect. Children's sitting trunk angle, pain sensitivity, percent trunk fat, waist girth, and body mass index were associated with their BME performance, accounting for between 5.2% and 20.9% of BME.

CONCLUSIONS

The final multivariable model, including mother's BME, percent trunk fat, and sitting trunk angle, explained 28% of the variance in BME performance, suggesting that for successful BME intervention a range of multidimensional variables should be considered.

Genome wide association study identifies KCNMA1 contributing to human obesity

BACKGROUND

Recent genome-wide association (GWA) analyses have identified common single nucleotide polymorphisms (SNPs) that are associated with obesity. However, the reported genetic variation in obesity explains only a minor fraction of the total genetic variation expected to be present in the population. Thus many genetic variants controlling obesity remain to be identified. The aim of this study was to use GWA followed by multiple stepwise validations to identify additional genes associated with obesity.

METHODS

We performed a GWA analysis in 164 morbidly obese subjects (BMI:body mass index>40 kg/m2) and 163 Swedish subjects (>45 years) who had always been lean. The 700 SNPs displaying the strongest association with obesity in the GWA were analyzed in a second cohort comprising 460 morbidly obese subjects and 247 consistently lean Swedish adults. 23 SNPs remained significantly associated with obesity (nominal P<0.05) and were in a step-wise manner followed up in five additional cohorts from Sweden, France, and Germany together comprising 4214 obese and 5417 lean or population-based control individuals. Three samples, n=4133, were used to investigate the population-based associations with BMI. Gene expression in abdominal subcutaneous adipose tissue in relation to obesity was investigated for14 adults.

RESULTS

Potassium channel, calcium activated, large conductance, subfamily M, alpha member (KCNMA1) rs2116830*G and BDNF rs988712*G were associated with obesity in five of six investigated case-control cohorts. In meta-analysis of 4838 obese and 5827 control subjects we obtained genome-wide significant allelic association with obesity for KCNMA1 rs2116830*G with P=2.82×10(-10) and an odds ratio (OR) based on cases vs controls of 1.26 [95% C.I. 1.12-1.41] and for BDNF rs988712*G with P=5.2×10(-17) and an OR of 1.36 [95% C.I. 1.20-1.55]. KCNMA1 rs2116830*G was not associated with BMI in the population-based samples. Adipose tissue (P=0.0001) and fat cell (P=0.04) expression of KCNMA1 was increased in obesity.

CONCLUSIONS

We have identified KCNMA1 as a new susceptibility locus for obesity, and confirmed the association of the BDNF locus at the genome-wide significant level.

Molecular genetic studies of gene identification for sarcopenia

Sarcopenia, which is characterized by a progressive decrease of skeletal muscle mass and function with aging, is closely related to several common diseases (such as cardiovascular and airway diseases) and functional impairment/disability. Strong genetic determination has been reported for muscle mass and muscle strength, two most commonly recognized and studied risk phenotypes for sarcopenia, with heritability ranging from 30 to 85% for muscle strength and 45-90% for muscle mass. Sarcopenia has been the subject of increasing genetic research over the past decade. This review is designed to comprehensively summarize the most important and representative molecular genetic studies designed to identify genetic factors associated with sarcopenia. We have methodically reviewed whole-genome linkage studies in humans, quantitative trait loci mapping in animal models, candidate gene association studies, newly reported genome-wide association studies, DNA microarrays and microRNA studies of sarcopenia or related skeletal muscle phenotypes. The major results of each study are tabulated for easy comparison and reference. The findings of representative studies are discussed with respect to their influence on our present understanding of the genetics of sarcopenia. This is a comprehensive review of molecular genetic studies of gene identification for sarcopenia, and an overarching theme for this review is that the currently accumulating results are tentative and occasionally inconsistent and should be interpreted with caution pending further investigation. Consequently, this overview should enhance recognition of the need to validate/replicate the genetic variants underlying sarcopenia in large human cohorts and animal. We believe that further progress in understanding the genetic etiology of sarcopenia will provide valuable insights into important fundamental biological mechanisms underlying muscle physiology that will ultimately lead to improved ability to recognize individuals at risk for developing sarcopenia and our ability to treat this debilitating condition.

Multivariate linkage scan for metabolic syndrome traits in families with type 2 diabetes

The purpose of this study was to evaluate evidence for linkage to interrelated quantitative features of the metabolic syndrome (MetS). Data on eight quantitative MetS traits (body weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein (HDL) cholesterol, triglycerides (TGs), and fasting glucose and insulin measurements) and a 10 cM genome scan were available for 78 white families (n = 532 subjects). These data were used to conduct multipoint, multivariate linkage analyses, including tests for coincident linkage and complete pleiotropy. The strongest evidence for linkage from the bivariate analyses was observed on chromosome 1 (1p22.2) (HDL-TG; univariate lod score equivalent (lod(eq) = 3.99)) with stronger results from the trivariate analysis at the same location (HDL-TG-Insulin; lod(eq) = 4.32). Seven additional susceptibility regions (lod(eq) scores >1.9) were observed (1p36, 1q23, 2q21.2, 8q23.3, 14q23.2, 14q32.11, and 20p11.21). The results from this study indicate that several correlated traits of the MetS are influenced by the same gene(s) that account for some of the clustering of the MetS features.

Influence of common variants in FTO and near INSIG2 and MC4R on growth curves for adiposity in African- and European-American youth

Recent genome-wide association (GWA) studies identified several common variants for obesity: rs9939609 in FTO, rs7566605 near INSIG2 and both rs17782313 and rs17700633 near the MC4R gene. This study aimed to assess the influence of these polymorphisms on development of adiposity in European- (EA) and African-American (AA) youth in two ongoing longitudinal studies including 986 and 606 participants with age ranges of 10-25.8 and 4.0-23.9 years, respectively. Individual growth curve modeling was conducted separately in the two studies. We tested the effect of the SNPs on levels and increase with age (i.e., slope) of weight, body mass index (BMI), waist circumference and skinfolds from childhood to adulthood, and potential moderation by ethnicity or gender. Beta coefficients computed in the two studies were pooled using meta-analysis. Rs9939609 was associated with logtransformed levels of BMI (β = 0.021, P = 0.01), weight (β = 0.019, P = 0.04) and waist circumference (β = 0.012, P = 0.04). Rs17782313 was associated with triceps (β = 0.05, P = 0.02). Significant interactions of rs17700633 with gender were observed on subscapular-, suprailiac- and sum of skinfolds, with significant associations limited to males (P < 0.05). No significant interactions with ethnicity were found. Only one effect on the slope was observed, rs17700633 showed a significant interaction with age on triceps (β = 0.004, P = 0.04). In two longitudinal studies of EA and AA youth, we replicated the effect of FTO and common variants near MC4R on general and central adiposity. These variants did not affect the increase with age of adiposity from childhood to adulthood with one exception. Common variants for obesity identified in GWA studies have detectable but modest effects on growth curves for adiposity in EA and AA youth.

Genome-wide association study of anthropometric traits and evidence of interactions with age and study year in Filipino women

Increased values of multiple adiposity-related anthropometric traits are important risk factors for many common complex diseases. We performed a genome-wide association (GWA) study for four quantitative traits related to body size and adiposity (BMI, weight, waist circumference, and height) in a cohort of 1,792 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). This is the first GWA study of anthropometric traits in Filipinos, a population experiencing a rapid transition into a more obesogenic environment. In addition to identifying suggestive evidence of additional single-nucleotide polymorphism (SNP) association signals (P < 10(-5)), we replicated (P < 0.05, same direction of additive effect) associations previously reported in European populations of both BMI and weight with MC4R and FTO, of BMI with BDNF, and of height with EFEMP1, ZBTB38, and NPPC, but none with waist circumference. We also replicated loci reported in Japanese or Korean populations as associated with BMI (OTOL1) and height (HIST1H1PS2, C14orf145, GPC5). A difference in local linkage disequilibrium (LD) between European and Asian populations suggests a narrowed association region for BDNF, while still including a proposed functional nonsynonymous amino acid substitution variant (rs6265, Val66Met). Finally, we observed significant evidence (P < 0.0042) for age-by-genotype interactions influencing BMI for rs17782313 (MC4R) and rs9939609 (FTO), and for a study year-by-genotype interaction for rs4923461 (BDNF). Our results show that several genetic risk factors are associated with anthropometric traits in Filipinos and provide further insight into the effects of BDNF, FTO, and MC4R on BMI.

Learning genetic epistasis using Bayesian network scoring criteria

Background

Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have been developed for learning epistatic relationships from data. A well-known combinatorial method that has been successfully applied for detecting epistasis is Multifactor Dimensionality Reduction (MDR). Jiang et al. created a combinatorial epistasis learning method called BNMBL to learn Bayesian network (BN) epistatic models. They compared BNMBL to MDR using simulated data sets. Each of these data sets was generated from a model that associates two SNPs with a disease and includes 18 unrelated SNPs. For each data set, BNMBL and MDR were used to score all 2-SNP models, and BNMBL learned significantly more correct models. In real data sets, we ordinarily do not know the number of SNPs that influence phenotype. BNMBL may not perform as well if we also scored models containing more than two SNPs. Furthermore, a number of other BN scoring criteria have been developed. They may detect epistatic interactions even better than BNMBL.

Although BNs are a promising tool for learning epistatic relationships from data, we cannot confidently use them in this domain until we determine which scoring criteria work best or even well when we try learning the correct model without knowledge of the number of SNPs in that model.

Results

We evaluated the performance of 22 BN scoring criteria using 28,000 simulated data sets and a real Alzheimer's GWAS data set. Our results were surprising in that the Bayesian scoring criterion with large values of a hyperparameter called α performed best. This score performed better than other BN scoring criteria and MDR at recall using simulated data sets, at detecting the hardest-to-detect models using simulated data sets, and at substantiating previous results using the real Alzheimer's data set.

Conclusions

We conclude that representing epistatic interactions using BN models and scoring them using a BN scoring criterion holds promise for identifying epistatic genetic variants in data. In particular, the Bayesian scoring criterion with large values of a hyperparameter α appears more promising than a number of alternatives.

Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass

OBJECTIVE

The SH3-domain GRB2-like (endophilin)-interacting protein 1 (SGIP1) gene has been shown to be differentially expressed in the hypothalamus of lean versus obese Israeli sand rats (Psammomys obesus), and is suspected of having a role in regulating food intake. The purpose of this study was to assess the role of genetic variation in SGIP1 in human disease.

SUBJECTS

We performed single-nucleotide polymorphism (SNP) genotyping in a large family pedigree cohort from the island of Mauritius. The Mauritius Family Study (MFS) consists of 400 individuals from 24 Indo-Mauritian families recruited from the genetically homogeneous population of Mauritius. We measured markers of the metabolic syndrome, including diabetes and obesity-related phenotypes such as fasting plasma glucose, waist:hip ratio, body mass index and fat mass.

RESULTS

Statistical genetic analysis revealed associations between SGIP1 polymorphisms and fat mass (in kilograms) as measured by bioimpedance. SNP genotyping identified associations between several genetic variants and fat mass, with the strongest association for rs2146905 (P=4.7 × 10(-5)). A strong allelic effect was noted for several SNPs where fat mass was reduced by up to 9.4% for individuals homozygous for the minor allele.

CONCLUSIONS

Our results show association between genetic variants in SGIP1 and fat mass. We provide evidence that variation in SGIP1 is a potentially important determinant of obesity-related traits in humans.

Heritability of response inhibition in children

We report the heritability of response inhibition, latency, and variability, which are potential markers of genetic risk in neuropsychiatric conditions. Genetic and environmental influences on cancellation and restraint, response latency, and variability measured in a novel variant of the stop signal task were studied in 139 eight-year-old twin pairs from a birth cohort. Cancellation (50%), restraint (27%), and response latency (41%) showed significant heritability, the balance being non-shared environmental influences and/or error. Response variability was not heritable, with 23% of the variance attributable to shared environmental influences and 77% to non-shared environmental risk or error. The phenotypic correlation between response cancellation and restraint was -.44 and between response latency and restraint was .21. These phenotypic correlations were entirely genetic in origin. The phenotypic correlation between response variability and % successful inhibition was .27, but was not genetic. Cancellation and restraint were heritable and shared genetic influences, indicating that they may be influenced by a common gene or genes. Response latency was moderately heritable and shared genetic influences with restraint, but was not correlated with cancellation. Response variability was not heritable. These results support the potential of response inhibition and latency as endophenotypes in genetic research.

MC4R variant is associated with BMI but not response to resistance training in young females

Recently, a genome-wide association study (GWAS) that identified eight single-nucleotide polymorphisms (SNPs) associated with BMI highlighted a possible neuronal influence on the development of obesity. We hypothesized these SNPs would govern the response of BMI and subcutaneous fat to resistance training in young individuals (age = 24 years). We genotyped the eight GWAS-identified SNPs in the article by Willer et al. in a cohort (n = 796) that undertook a 12-week resistance-training program. Females with a copy of the rare allele (C) for rs17782313 (MC4R) had significantly higher BMIs (

CC/CT

n = 174; 24.70 ± 0.33 kg/m², TT: n = 278; 23.41 ± 0.26 kg/m², P = 0.002), and the SNP explained 1.9% of overall variation in BMI. Males with a copy of the rare allele (T) for rs6548238 (TMEM18) had lower amounts of subcutaneous fat pretraining (CT/TT: n = 65; 156,534 ± 7,415 mm³, CC: n = 136; 177,825 ± 5,139 mm³, P = 0.019) and males with a copy of the rare allele (A) for rs9939609 (FTO) lost a significant amount of subcutaneous fat with exercise (

AT/AA

n = 83; -798.35 ± 2,624.30 mm³, TT: n = 47; 9,435.23 ± 3,494.44 mm³, P = 0.021). Females with a copy of the G allele for a missense variant in the SH2B1 (rs7498665) was associated with less change of subcutaneous fat volume with exercise (

AG/GG

n = 191; 9,813 ± 2,250 mm³ vs. AA: n = 126; 770 ± 2,772 mm³; P = 0.011). These data support the original finding that there is an association between measures of obesity and a variant near the MC4R gene and extends these results to a younger population and implicates FTO, TMEM18, and SH2B1 polymorphisms in subcutaneous fat regulation.

Body mass index and obesity- and diabetes-associated genotypes and risk for pancreatic cancer

BACKGROUND

The genetic factors predisposing individuals with obesity or diabetes to pancreatic cancer have not been identified.

AIMS

To investigate the hypothesis that obesity- and diabetes-related genes modify the risk of pancreatic cancer.

METHODS

We genotyped 15 single nucleotide polymorphisms of fat mass and obesity-associated (FTO), peroxisome proliferators-activated receptor gamma (PPARγ), nuclear receptor family 5 member 2 (NR5A2), AMPK, and ADIPOQ genes in 1,070 patients with pancreatic cancer and 1,175 cancer-free controls. Information on risk factors was collected by personal interview. Adjusted ORs (AOR) and 95% CIs were calculated using unconditional logistic regression.

RESULTS

The PPARγ P12A GG genotype was inversely associated with risk of pancreatic cancer (AOR, 0.21; 95% CI, 0.07-0.62). Three NR5A2 variants that were previously identified in a genome-wide association study were significantly associated with reduced risk of pancreatic cancer, AORs ranging from 0.57 to 0.79. Two FTO gene variants and one ADIPOQ variant were differentially associated with pancreatic cancer according to levels of body mass index (BMI; P(interaction) = 0.0001, 0.0015, and 0.03). For example, the AOR (95% CI) for FTO IVS1-2777AC/AA genotype was 0.72 (0.55-0.96) and 1.54 (1.14-2.09) in participants with a BMI of less than 25 or 25 kg/m(2) or more, respectively. We observed no significant association between AMPK genotype and pancreatic cancer and no genotype interactions with diabetes or smoking.

CONCLUSION

Our findings suggest the PPARγ P12A GG genotype and NR5A2 variants may reduce the risk for pancreatic cancer. A positive association of FTO and ADIPOQ gene variants with pancreatic cancer may be limited to persons who are overweight.

IMPACT

The discovery of genetic factors modifying the risk of pancreatic cancer may help to identify high-risk individuals for prevention efforts.

Body mass index and obesity- and diabetes-associated genotypes and risk for pancreatic cancer

BACKGROUND

The genetic factors predisposing individuals with obesity or diabetes to pancreatic cancer have not been identified.

AIMS

To investigate the hypothesis that obesity- and diabetes-related genes modify the risk of pancreatic cancer.

METHODS

We genotyped 15 single nucleotide polymorphisms of fat mass and obesity-associated (FTO), peroxisome proliferators-activated receptor gamma (PPARγ), nuclear receptor family 5 member 2 (NR5A2), AMPK, and ADIPOQ genes in 1,070 patients with pancreatic cancer and 1,175 cancer-free controls. Information on risk factors was collected by personal interview. Adjusted ORs (AOR) and 95% CIs were calculated using unconditional logistic regression.

RESULTS

The PPARγ P12A GG genotype was inversely associated with risk of pancreatic cancer (AOR, 0.21; 95% CI, 0.07-0.62). Three NR5A2 variants that were previously identified in a genome-wide association study were significantly associated with reduced risk of pancreatic cancer, AORs ranging from 0.57 to 0.79. Two FTO gene variants and one ADIPOQ variant were differentially associated with pancreatic cancer according to levels of body mass index (BMI; P(interaction) = 0.0001, 0.0015, and 0.03). For example, the AOR (95% CI) for FTO IVS1-2777AC/AA genotype was 0.72 (0.55-0.96) and 1.54 (1.14-2.09) in participants with a BMI of less than 25 or 25 kg/m(2) or more, respectively. We observed no significant association between AMPK genotype and pancreatic cancer and no genotype interactions with diabetes or smoking.

CONCLUSION

Our findings suggest the PPARγ P12A GG genotype and NR5A2 variants may reduce the risk for pancreatic cancer. A positive association of FTO and ADIPOQ gene variants with pancreatic cancer may be limited to persons who are overweight.

IMPACT

The discovery of genetic factors modifying the risk of pancreatic cancer may help to identify high-risk individuals for prevention efforts.

FTO and MC4R gene variants are associated with obesity in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility in women. It is also associated with metabolic disturbances that place women at increased risk for obesity and type 2 diabetes. There is strong evidence for familial clustering of PCOS and a genetic predisposition. However, the gene(s) responsible for the PCOS phenotypes have not been elucidated. This two-phase family-based and case-control genetic study was designed to address the question of whether SNPs identified as susceptibility loci for obesity in genome-wide association studies (GWAS) are also associated with PCOS and elevated BMI. Members of 439 families having at least one offspring with PCOS were genotyped for 15 SNPs previously shown to be associated with obesity. Linkage and association with PCOS was assessed using the transmission/disequilibrium test (TDT). These SNPs were also analyzed in an independent case-control study involving 395 women with PCOS and 176 healthy women with regular menstrual cycles. Only one of these 15 SNPs (rs2815752 in NEGR1) was found to have a nominally significant association with PCOS (χ² = 6.11, P = 0.013), but this association failed to replicate in the case-control study. While not associated with PCOS itself, five SNPs in FTO and two in MC4R were associated with BMI as assessed with a quantitative-TDT analysis, several of which replicated association with BMI in the case-control cohort. These findings demonstrate that certain SNPs associated with obesity contribute to elevated BMI in PCOS, but do not appear to play a major role in PCOS per se. These findings support the notion that PCOS phenotypes are a consequence of an oligogenic/polygenic mechanism.

Identifying genetic interactions in genome-wide data using Bayesian networks

It is believed that interactions among genes (epistasis) may play an important role in susceptibility to common diseases (Moore and Williams [2002]. Ann Med 34:88-95; Ritchie et al. [2001]. Am J Hum Genet 69:138-147). To study the underlying genetic variants of diseases, genome-wide association studies (GWAS) that simultaneously assay several hundreds of thousands of SNPs are being increasingly used. Often, the data from these studies are analyzed with single-locus methods (Lambert et al. [2009]. Nat Genet 41:1094-1099; Reiman et al. [2007]. Neuron 54:713-720). However, epistatic interactions may not be easily detected with single-locus methods (Marchini et al. [2005]. Nat Genet 37:413-417). As a result, both parametric and nonparametric multi-locus methods have been developed to detect such interactions (Heidema et al. [2006]. BMC Genet 7:23). However, efficiently analyzing epistasis using high-dimensional genome-wide data remains a crucial challenge. We develop a method based on Bayesian networks and the minimum description length principle for detecting epistatic interactions. We compare its ability to detect gene-gene interactions and its efficiency to that of the combinatorial method multifactor dimensionality reduction (MDR) using 28,000 simulated data sets generated from 70 different genetic models We further apply the method to over 300,000 SNPs obtained from a GWAS involving late onset Alzheimer's disease (LOAD). Our method outperforms MDR and we substantiate previous results indicating that the GAB2 gene is associated with LOAD. To our knowledge, this is the first successful model-based epistatic analysis using a high-dimensional genome-wide data set.

Introduction to genetics and childhood obesity: relevance to nursing practice

PURPOSE

The aims for this article are to provide an overview of the current state of research on genetic contributions to the development of childhood obesity and to suggest genetic-focused nursing practices to prevent childhood obesity.

ORGANIZING CONSTRUCTS

Genetic epidemiology of childhood obesity, modes to identifying obesity genes, types of human obesity genes, and nursing implications are discussed.

CLINICAL RELEVANCE

The successful integration of genetics into nursing practice will provide opportunities for nurses to participate fully as major agents and collaborators in the health care revolution.

CONCLUSIONS

Practicing nurses across the profession will need to become knowledgeable about genetics and take part in obesity prevention through genetic assessment of susceptibility and appropriate environmental interventions.

Genetics of childhood obesity

Obesity is a major health problem and an immense economic burden on the health care systems both in the United States and the rest of the world. The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Besides environmental factors, genetic factors are known to play an important role in the pathogenesis of obesity. Genome-wide association studies (GWAS) have revealed strongly associated genomic variants associated with most common disorders; indeed there is general consensus on these findings from generally positive replication outcomes by independent groups. To date, there have been only a few GWAS-related reports for childhood obesity specifically, with studies primarily uncovering loci in the adult setting instead. It is clear that a number of loci previously reported from GWAS analyses of adult BMI and/or obesity also play a role in childhood obesity.

Gene by sex interaction for measures of obesity in the framingham heart study

Obesity is an increasingly prevalent and severe health concern with a substantial heritable component and marked sex differences. We sought to determine if the effect of genetic variants also differed by sex by performing a genome-wide association study modeling the effect of genotype-by-sex interaction on obesity phenotypes. Genotype data from individuals in the Framingham Heart Study Offspring cohort were analyzed across five exams. Although no variants showed genome-wide significant gene-by-sex interaction in any individual exam, four polymorphisms displayed a consistent BMI association (P-values .00186 to .00010) across all five exams. These variants were clustered downstream of LYPLAL1, which encodes a lipase/esterase expressed in adipose tissue, a locus previously identified as having sex-specific effects on central obesity. Primary effects in males were in the opposite direction from females and were replicated in Framingham Generation 3. Our data support a sex-influenced association between genetic variation at the LYPLAL1 locus and obesity-related traits.

Planning a genome-wide association study: points to consider

It is well established that genetic diversity combined with specific environmental exposures contributes to disease susceptibility. However, it has turned out to be challenging to isolate the genes underlying the genetic component conferring susceptibility to most complex disorders. Traditional candidate gene and family-based linkage studies, which dominated gene discovery efforts for many years, were largely unsuccessful in unraveling the genetics of these traits due to the relatively limited information gained. Within the last 5 years, new advances in high-throughput methods have allowed for large volumes of single nucleotide polymorphisms (SNPs) throughout the genome to be genotyped across large and comprehensively phenotyped patient cohorts. Unlike previous approaches, these 'genome-wide association studies' (GWAS) have extensively delivered on the promise of uncovering genetic determinants of complex diseases, with hundreds of novel disease-associated variants being largely replicated by independent groups. This review provides an overview of these recent breakthroughs in the context of the pitfalls and challenges related to designing and carrying out a successful GWAS.

Replication of genetic variants from genome-wide association studies with metabolic traits in an island population of the Adriatic coast of Croatia

Twenty-two single-nucleotide polymorphisms (SNPs) in 10 gene regions previously identified in obesity and type 2 diabetes (T2D) genome-wide association studies (GWAS) were evaluated for association with metabolic traits in a sample from an island population of European descent. We performed a population-based study using 18 anthropometric and biochemical traits considered as continuous variables in a sample of 843 unrelated subjects (360 men and 483 women) aged 18-80 years old from the island of Hvar on the eastern Adriatic coast of Croatia. All eight GWAS SNPs in FTO were significantly associated with weight, body mass index, waist circumference and hip circumference; 20 of the 32 nominal P-values remained significant after permutation testing for multiple corrections. The strongest associations were found between the two TCF7L2 GWAS SNPs with fasting plasma glucose and HbA1c levels, all four P-values remained significant after permutation tests. Nominally significant associations were found between several SNPs and other metabolic traits; however, the significance did not hold after permutation tests. Although the sample size was modest, our study strongly replicated the association of FTO variants with obesity-related measures and TCF7L2 variants with T2D-related traits. The estimated effect sizes of these variants were larger or comparable to published studies. This is likely attributable to the homogenous genetic background of the relatively isolated study population.

Novel common copy number variation for early onset extreme obesity on chromosome 11q11 identified by a genome-wide analysis

Heritability of obesity is substantial and recent meta-analyses of genome-wide association studies (GWASs) have been successful in detecting several robustly associated genomic regions for obesity using single-nucleotide polymorphisms (SNPs). However, taken together, the SNPs explain only a small proportion of the overall heritability. Copy number variations (CNVs) might contribute to the 'missing heritability'. We searched genome-wide for association between common CNVs and early-onset extreme obesity. Four hundred and twenty-four case-parents obesity trios and an independent sample of 453 extremely obese children and adolescents and 435 normal-weight and lean adult controls were genotyped by the Affymetrix Genome-Wide Human SNP Array 6.0. We detected 20 common copy number variable regions (CNVRs) which were associated with obesity. The most promising CNVRs were followed-up in an independent sample of 365 obesity trios, confirming the association for two candidate CNVRs. We identified a common CNVR exclusively covering the three olfactory receptor genes OR4P4, OR4S2 and OR4C6 to be associated with obesity (combined P-value = 0.015 in a total of 789 families; odds ratio for the obesity effect allele = 1.19; 95% confidence interval = 1.016-1.394). We also replicated two common deletions (near NEGR1 and at chromosome 10q11.22) that have previously been reported to be associated with body weight. Additionally, we support a rare CNV on chromosome 16 that has recently been reported by two independent groups. However, rare CNVs had not been the focus of our study. We conclude that common CNVs are unlikely to contribute substantially to the genetic basis of early-onset extreme obesity.

Genetic risk sum score comprised of common polygenic variation is associated with body mass index

Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI (p value = 3.19 E-06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits.

A genome-wide study reveals copy number variants exclusive to childhood obesity cases

The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Genomic copy number variations (CNVs) have been strongly implicated in subjects with extreme obesity and coexisting developmental delay. To complement these previous studies, we addressed CNVs in common childhood obesity by examining children with a BMI in the upper 5(th) percentile but excluding any subject greater than three standard deviations from the mean in order to reduce severe cases in the cohort. We performed a whole-genome CNV survey of our cohort of 1080 defined European American (EA) childhood obesity cases and 2500 lean controls (< 50(th) percentile BMI) who were genotyped with 550,000 SNP markers. Positive findings were evaluated in an independent African American (AA) cohort of 1479 childhood obesity cases and 1575 lean controls. We identified 17 CNV loci that were unique to at least three EA cases and were both previously unreported in the public domain and validated via quantitative PCR. Eight of these loci (47.1%) also replicated exclusively in AA cases (six deletions and two duplications). Replicated deletion loci consisted of EDIL3, S1PR5, FOXP2, TBCA, ABCB5, and ZPLD1, whereas replicated duplication loci consisted of KIF2B and ARL15. We also observed evidence for a deletion at the EPHA6-UNQ6114 locus when the AA cohort was investigated as a discovery set. Although these variants may be individually rare, our results indicate that CNVs contribute to the genetic susceptibility of common childhood obesity in subjects of both European and African ancestry.

Linkage analysis of obesity phenotypes in pre- and post-menopausal women from a United States mid-western population

Background

Obesity has a strong genetic influence, with some variants showing stronger associations among women than men. Women are also more likely to distribute weight in the abdomen following menopause. We investigated whether genetic loci link with obesity-related phenotypes differently by menopausal status.

Methods

We performed univariate and bivariate linkage analysis for the phenotypes of body mass index (BMI), waist (W) and hip (H) circumferences (WC, HC), and WH ratio (WHR) separately among 172 pre-menopausal and 405 post-menopausal women from 90 multigenerational families using a genome scan with 403 microsatellite markers. Bivariate analysis used pair-wise combinations of obesity phenotypes to detect linkage at loci with pleiotropic effects for genetically correlated traits. BMI was adjusted in models of WC, HC and WHR.

Results

Pre-menopausal women, compared to post-menopausal women, had higher heritability for BMI (h² = 94% versus h² = 39%, respectively) and for HC (h² = 99% versus h² = 43%, respectively), and lower heritability for WC (h² = 29% versus h² = 61%, respectively) and for WHR (h² = 39% versus h² = 57%, respectively). Among pre-menopausal women, the strongest evidence for linkage was for the combination of BMI and HC traits at 3p26 (bivariate LOD = 3.65) and at 13q13-q14 (bivariate LOD = 3.59). Among post-menopausal women, the highest level of evidence for genetic linkage was for HC at 4p15.3 (univariate LOD = 2.70) and 14q13 (univariate LOD = 2.51). WC was not clearly linked to any locus.

Conclusions

These results support a genetic basis for fat deposition that differs by menopausal status, and suggest that the same loci encode genes that influence general obesity (BMI) and HC, specifically, among pre-menopausal women. However, lower heritability among pre-menopausal women for WC and WHR suggests that pre-menopausal waist girth may be influenced to a greater extent by controllable environmental factors than post-menopausal waist girth. Possibly, targeted interventions for weight control among pre-menopausal women may prevent or attenuate post-menopausal abdominal weight deposition.

Insulin-induced gene: a new regulator in lipid metabolism

Insulin-induced genes (Insigs) including Insig-1 and Insig-2, are proteins that mediate sterol regulation of sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP) and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMG-CoA reductase). Insigs perform distinct tasks in the regulation of these effectors: they promote the endoplasmic reticulum (ER) retention of SCAP, but ubiquitin-mediated degradation of HMG-CoA reductase. Through these activities, Insig-1 and Insig-2 influence cholesterol metabolism, lipogenesis, and glucose homeostasis in diverse tissues such as adipose tissue and liver. In this article, we focus on the functions, expression and regulation, gene polymorphisms of Insigs, and their deficiency with diseases.

The INSIG2 rs7566605 polymorphism is not associated with body mass index and breast cancer risk

Background

The single nucleotide polymorphism rs7566605, located in the promoter of the INSIG2 gene, has been the subject of a strong scientific effort aimed to elucidate its possible association with body mass index (BMI). The first report showing that rs7566605 could be associated with body fatness was a genome-wide association study (GWAS) which used BMI as the primary phenotype. Many follow-up studies sought to validate the association of rs7566605 with various markers of obesity, with several publications reporting inconsistent findings. BMI is considered to be one of the measures of choice to evaluate body fatness and there is evidence that body fatness is related with an increased risk of breast cancer (BC).

Methods

we tested in a large-scale association study (3,973 women, including 1,269 invasive BC cases and 2,194 controls), nested within the EPIC cohort, the involvement of rs7566605 as predictor of BMI and BC risk.

Results and Conclusions

In this study we were not able to find any statistically significant association between this SNP and BMI, nor did we find any significant association between the SNP and an increased risk of breast cancer overall and by subgroups of age, or menopausal status.

Fine Mapping of the Insulin-Induced Gene 2 Identifies a Variant Associated With LDL Cholesterol and Total Apolipoprotein B Levels

Background—

In a whole-genome scan, a single nucleotide polymorphism (SNP) (rs7566605) upstream of the insulin-induced gene 2 ( INSIG2 ) was shown to influence body mass index and obesity in the Framingham Heart Study, with replication of these results in an additional 4 of 5 studies. However, other studies could not replicate the association. Because INSIG2 plays an important role in cholesterol biosynthesis, we hypothesized that human INSIG2 variants might play a role in the regulation of plasma lipid and lipoprotein levels.

Methods and Results—

We selected tagging SNPs spanning >100 kb of INSIG2 locus and sequenced 18 434 base pairs to discover novel SNPs. Thirty-two SNPs were genotyped in 645 individuals from the Quebec Family Study. Two SNPs (rs10490626 and rs12464355) were associated with plasma low-density lipoprotein cholesterol (LDL-C) ( P <0.0015) and total apolipoprotein B (apoB) levels ( P <0.014), whereas no association was found between any SNP and body mass index. We replicated the finding of rs10490626 for both LDL-C and total apoB in additional study samples, including 758 individuals from Saguenay–Lac St. Jean, Quebec ( P =0.040 for LDL-C, P =0.044 for apoB), 3247 Europeans ( P =0.028 for LDL-C, P =0.030 for apoB), and 1695 South Asians ( P =0.0036 for LDL-C, P =0.034 for apoB) from the INTERHEART study (for LDL-C, the combined 2-sided P =6.2×10 −5 and for total apoB, P =0.0011). Furthermore, we identified a variant in the human sorbin and SH 3 -domain–containing-1 gene that was associated with INSIG2 mRNA levels, and this SNP was shown to act in combination with rs10490626 to affect LDL-C ( P =0.022) in the Quebec Family Study and in INTERHEART South Asians ( P =0.019) and Europeans ( P =0.052).

Conclusion—

These results suggest that INSIG2 genetic variants may have a more direct role in lipid and lipoprotein metabolism than in obesity.

Association of an INSIG2 obesity allele with cardiovascular phenotypes is gender and age dependent

Background

The INSIG2 gene has been implicated in cholesterol metabolism and a single nucleotide polymorphism (SNP) near INSIG2 has been shown to be associated with obesity. We sought to determine the relationship of the INSIG2 SNP to cardiovascular disease (CVD) related phenotypes.

Methods and Results

Nine hundred forty six patients undergoing percutaneous coronary intervention (PCI) in wave 5 of the multicenter NHLBI Dynamic Registry were genotyped using RT-PCR/TaqMan/allelic discrimination for the rs7566605 SNP near the INSIG2 gene. Clinical variables analyzed include demographics, medical history, and procedural details. The prevalence of peripheral vascular disease (PVD) was significantly higher in older men (≥65 years) who were either homozygous or carriers of the obesity/lipid risk allele ("C") compared to non-carriers (odds ratio 3.4, p = 0.013) using a logistic regression model incorporating history of hypercholesterolemia, history of hypertension, cerebrovascular disease, history of diabetes, and BMI. A similar relationship with cerebrovascular disease was found in older (>65) women (odds ratio 3.4, p = 0.013). The INSIG2 SNP was not associated with BMI, nor with other clinical variables.

Conclusion

Age and gender may influence the association of the INSIG2 obesity SNP with PVD and cerebrovascular disease in patients with pre-existing CVD.

Analyses of shared genetic factors between asthma and obesity in children

BACKGROUND

Epidemiologic studies consistently show associations between asthma and obesity. Shared genetics might account for this association.

OBJECTIVE

We sought to identify genetic variants associated with both asthma and obesity.

METHODS

On the basis of a literature search, we identified genes from (1) genome-wide association studies (GWASs) of body mass index (BMI; n = 17 genes), (2) GWASs of asthma (n = 14), and (3) candidate gene studies of BMI and asthma (n = 7). We used GWAS data from the Childhood Asthma Management Program to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n = 359 subjects) and BMI (n = 537).

RESULTS

One top BMI GWAS SNP from the literature, rs10938397 near glucosamine-6-phosphate deaminase 2 (GNPDA2), was associated with both BMI (P = 4 x 10(-4)) and asthma (P = .03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (P < .05) with both phenotypes for several genes: neuronal growth regulator 1 (NEGR1); roundabout, axon guidance receptor, homolog 1 (ROBO1); diacylglycerol kinase, gamma (DGKG); Fas apoptotic inhibitory molecule 2 (FAIM2); fat mass and obesity associated (FTO); and carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 8 (CHST8) among the BMI GWAS genes; interleukin 1 receptor-like 1 / interleukin 18 receptor 1 (IL1RL1/IL18R1), dipeptidyl-peptidase 10 (DPP10), phosphodiesterase 4D (PDE4D), V-myb myeloblastosis viral oncogene homolog (MYB), PDE10A, IL33, and especially protein tyrosine phosphatase, receptor type D (PTPRD) among the asthma GWAS genes; and protein kinase C, alpha (PRKCA) among the BMI and asthma candidate genes.

CONCLUSIONS

SNPs within several genes showed associations to BMI and asthma at a genetic level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci.

Association of maternally inherited GNAS alleles with African-American male birth weight

OBJECTIVE

Human birth weight variation has a significant genetic component and important clinical consequences. We performed a survey of single nucleotide polymorphisms (SNPs) in 14 candidate genes to identify associations with birth weight variation.

METHODS

SNP variation was surveyed in 221 healthy African-American mother-newborn pairs. Genes were selected based on previous association with obesity-related traits, significant differences in circulating protein levels in low birth weight pregnancies or association with newborn size in model organisms or growth disorders in humans. Association was tested via multiple linear regression with adjustment for significant covariables.

RESULTS

Under a dominant model SNP rs7754561 of ENPPI was significantly associated with birth weight. Among imprinted loci, maternal genotypes for SNP rs6026576 of GNAS were significantly associated with birth weight (additive and dominant models). This association was restricted to male offspring. Analyses that distinguished between alleles of paternal and maternal origin demonstrated that only maternally-transmitted alleles were associated with birth weight and that this association was restricted to male newborns.

CONCLUSION

The effect of only maternally-transmitted alleles of GNAS may be a consequence of the complex splicing and imprinting pattern of the GNAS gene, although the reason this effect is observed only among male newborns is unclear.

Genome-wide linkage and association scans for quantitative trait Loci of serum lactate dehydrogenase-the framingham heart study

Serum lactate dehydrogenase (LDH) is used in diagnosing many diseases and is significantly determined by genetic factors. Three genes coding for LDH isoenzymes were mapped to chromosome 11q15 and 12p12. We used 330 Framingham Heart Study largest families for microsatellite linkage scan and 100K SNPs association scan to determine quantitative trait loci of LDH level. We estimated the heritability at 41%. Our genome-wide linkage analysis yielded several chromosomal regions, other than 11q and 12p, with LOD scores between 1 and 2.5. None of the 100K SNPs with a P-value <10(-4) in our genome-wide association study was close to the chromosomal regions where the LDH genes reside. Our study demonstrated a strong genetic effect on the variation of LDH levels. There may not be a single gene with a large effect, instead may be several genes with small effects in controlling the variation of serum LDH. Those genes may be located on chromosomal regions that differ from where the genes encoding LDH isoenzymes reside.

Obesity and diabetes genetic variants associated with gestational weight gain

OBJECTIVE

We sought to determine whether genetic variants associated with diabetes and obesity predict gestational weight gain.

STUDY DESIGN

A total of 960 participants in the Pregnancy, Infection, and Nutrition cohorts were genotyped for 27 single-nucleotide polymorphisms (SNPs) associated with diabetes and obesity.

RESULTS

Among Caucasian and African American women (n = 960), KCNQ1 risk allele carriage was directly associated with weight gain (P < .01). In Bayesian hierarchical models among Caucasian women (n = 628), we found posterior odds ratios >3 for inclusion of TCF2 and THADA SNPs in our models. Among African American women (n = 332), we found associations between risk allele carriage and weight gain for the THADA and INSIG2 SNPs. In Bayesian variable selection models, we found an interaction between the TSPAN8 risk allele and pregravid obesity, with lower weight gain among obese risk allele carriers.

CONCLUSION

We found evidence that diabetes and obesity risk alleles interact with maternal pregravid body mass index to predict gestational weight gain.

Obesity and diabetes genes are associated with being born small for gestational age: results from the Auckland Birthweight Collaborative study

Background

Individuals born small for gestational age (SGA) are at increased risk of rapid postnatal weight gain, later obesity and diseases in adulthood such as type 2 diabetes, hypertension and cardiovascular diseases. Environmental risk factors for SGA are well established and include smoking, low pregnancy weight, maternal short stature, maternal diet, ethnic origin of mother and hypertension. However, in a large proportion of SGA, no underlying cause is evident, and these individuals may have a larger genetic contribution.

Methods

In this study we tested the association between SGA and polymorphisms in genes that have previously been associated with obesity and/or diabetes. We undertook analysis of 54 single nucleotide polymorphisms (SNPs) in 546 samples from the Auckland Birthweight Collaborative (ABC) study. 227 children were born small for gestational age (SGA) and 319 were appropriate for gestational age (AGA).

Results and Conclusion

The results demonstrated that genetic variation in KCNJ11, BDNF, PFKP, PTER and SEC16B were associated with SGA and support the concept that genetic factors associated with obesity and/or type 2 diabetes are more prevalent in those born SGA compared to those born AGA. We have previously determined that environmental factors are associated with differences in birthweight in the ABC study and now we have demonstrated a significant genetic contribution, suggesting that the interaction between genetics and the environment are important.

Common INSIG2 polymorphisms are associated with age-related changes in body size and high-density lipoprotein cholesterol from young adulthood to middle age

Insulin-induced gene 2 (INSIG2) plays an important role in the regulation of cholesterol and fatty acids synthesis. A polymorphism, rs7566605, located 10 kilobases upstream of the INSIG2 gene, was identified in a genomewide association study of obesity. We conducted an association study of 12 INSIG2 tag-single nucleotide polymorphisms with longitudinal measures of body size (body mass index and waist circumference) and lipid metabolism (plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides levels). We investigated their interaction with age in 4304 Coronary Artery Risk Development in Young Adults participants (49.5% blacks, 50.5% whites) followed prospectively for 20 years. rs7566605 was not associated with variation in body size or lipid metabolism at any age in either racial group. However, rs1352083 and rs10185316 were associated with age-related decline in high-density lipoprotein cholesterol in whites (P = .0005 and .04, respectively). A similar trend was observed in blacks who consistently maintained a body mass index less than 25 kg/m(2) over the study period. These data support a role of INSIG2 sequence variation in the regulation of cholesterol metabolism.

Recent progress in the genetics of common obesity

The genetic contribution to interindividual variation in common obesity has been estimated at 40-70%. Yet, despite a relatively high heritability, the search for obesity susceptibility genes has been an arduous task. This paper reviews recent progress made in the obesity genetics field with an emphasis on established obesity susceptibility loci identified through candidate gene as well as genome-wide studies. For the last 15 years, candidate gene and genome-wide linkage studies have been the two main genetic epidemiological approaches to identify genetic loci for common traits, yet progress has been slow and success limited. Only recently have candidate gene studies started to succeed; by means of large-scale studies and meta-analyses at least five variants in four candidate genes have been found to be robustly associated with obesity-related traits. Genome-wide linkage studies, however, have so far not been able to pinpoint genetic loci for common obesity. The genome-wide association approach, which has become available in recent years, has dramatically changed the pace of gene discoveries for common disease, including obesity. Three waves of large-scale high-density genome-wide association studies have already discovered at least 15 previously unanticipated genetic loci incontrovertibly associated with body mass index and extreme obesity risk. Although the combined contribution of these loci to the variation in obesity risk at the population level is small and their predictive value is typically low, these recently discovered loci are set to improve fundamentally our insights into the pathophysiology of obesity.

Identification of interacting genes in genome-wide association studies using a model-based two-stage approach

In this paper, we propose a two-stage approach based on 17 biologically plausible models to search for two-locus combinations that have significant joint effects on the disease status in genome-wide association (GWA) studies. In the two-stage analyses, we only test two-locus joint effects of SNPs that show modest marginal effects. We use simulation studies to compare the power of our two-stage analysis with a single-marker analysis and a two-stage analysis by using a full model. We find that for most plausible interaction effects, our two-stage analysis can dramatically increase the power to identify two-locus joint effects compared to a single-marker analysis and a two-stage analysis based on the full model. We also compare two-stage methods with one-stage methods. Our simulation results indicate that two-stage methods are more powerful than one-stage methods. We applied our two-stage approach to a GWA study for identifying genetic factors that might be relevant in the pathogenesis of sporadic Amyotrophic Lateral Sclerosis (ALS). Our proposed two-stage approach found that two SNPs have significant joint effect on sporadic ALS while the single-marker analysis and the two-stage analysis based on the full model did not find any significant results.

The common rs9939609 variant of the fat mass and obesity-associated gene is associated with obesity risk in children and adolescents of Beijing, China

Background

Previous genome-wide association studies for type 2 diabetes susceptibility genes have confirmed that a common variant, rs9939609, in the fat mass and obesity associated (FTO) gene region is associated with body mass index (BMI) in European children and adults. A significant association of the same risk allele has been described in Asian adult populations, but the results are conflicting. In addition, no replication studies have been conducted in children and adolescents of Asian ancestry.

Methods

A population-based survey was carried out among 3503 children and adolescents (6-18 years of age) in Beijing, China, including 1229 obese and 2274 non-obese subjects. We investigated the association of rs9939609 with BMI and the risk of obesity. In addition, we tested the association of rs9939609 with weight, height, waist circumference, waist-to-height ratio, fat mass percentage, birth weight, blood pressure and related metabolic traits.

Results

We found significant associations of rs9939609 variant with weight, BMI, BMI standard deviation score (BMI-SDS), waist circumference, waist-to-height ratio, and fat mass percentage in children and adolescents (p for trend = 3.29 × 10^-5, 1.39 × 10^-6, 3.76 × 10^-6, 2.26 × 10^-5, 1.94 × 10^-5, and 9.75 × 10^-5, respectively). No significant associations were detected with height, birth weight, systolic and diastolic blood pressure and related metabolic traits such as total cholesterol, triglycerides, HDL-cholesterol, LDL-cholesterol and fasting plasma glucose (all p > 0.05). Each additional copy of the rs9939609 A allele was associated with a BMI increase of 0.79 [95% Confidence interval (CI) 0.47 to 1.10] kg/m², equivalent to 0.25 (95%CI 0.14 to 0.35) BMI-SDS units. This rs9939609 variant is significantly associated with the risk of obesity under an additive model [Odds ratio (OR) = 1.29, 95% CI 1.11 to 1.50] after adjusting for age and gender. Moreover, an interaction between the FTO rs9939609 genotype and physical activity (p < 0.001) was detected on BMI levels, the effect of rs9939609-A allele on BMI being (0.95 ± 0.10), (0.77 ± 0.08) and (0.67 ± 0.05) kg/m², for subjects who performed low, moderate and severe intensity physical activity.

Conclusion

The FTO rs9939609 variant is strongly associated with BMI and the risk of obesity in a population of children and adolescents in Beijing, China.

Fine-mapping of obesity-related quantitative trait loci in an F9/10 advanced intercross line

Obesity develops in response to a combination of environmental effects and multiple genes of small effect. Although there has been significant progress in characterizing genes in many pathways contributing to metabolic disease, knowledge about the relationships of these genes to each other and their joint effects upon obesity lags behind. The LG,SM advanced intercross line (AIL) model of obesity has been used to characterize over 70 loci involved in fatpad weight, body weight, and organ weights. Each of these quantitative trait loci (QTLs) encompasses large regions of the genome and require fine-mapping to isolate causative sequence changes and possible mechanisms of action as indicated by the genetic architecture. In this study we fine-map QTLs first identified in the F(2) and F(2/3) populations in the combined F(9/10) advanced intercross generations. We observed significantly narrowed QTL confidence regions, identified many single QTL that resolve into multiple QTL peaks, and identified new QTLs that may have been previously masked due to opposite gene effects at closely linked loci. We also present further characterization of the pleiotropic and epistatic interactions underlying these obesity-related traits.

No association between polymorphisms in the INSIG1 gene and the risk of type 2 diabetes and related traits

BACKGROUND

The insulin-induced gene 1 (INSIG1) encodes a protein that blocks proteolytic activation of sterol regulatory element binding proteins, which are transcription factors that activate genes that regulate cholesterol, fatty acid, and glucose metabolism.

OBJECTIVE

We tested for associations between 6 INSIG1 tag single nucleotide polymorphisms (SNPs) (and captured all common variations in INSIG1) and the risk of type 2 diabetes (T2D), obesity, and related traits in 10,567 adults and 1155 adolescents from 5 population-based studies, a T2D case-control study, and a T2D case-series.

DESIGN

We genotyped tag SNPs and tested them for associations with the risk of T2D or obesity and with body mass index, waist circumference, systolic and diastolic blood pressure, and concentrations of fasting glucose, 2-h oral-glucose-tolerance test glucose, cholesterol, and triglyceride, with the assumption of an additive effect of the minor allele. Dominant effects were tested for the less-frequent SNPs (minor allele frequency <5%). Summary statistics of each study underwent meta-analysis.

RESULTS

Meta-analyses, which included 1655 T2D cases and 2911 control subjects, showed no association between any of the INSIG1 SNPs and T2D (P > 0.08). Furthermore, none of the SNPs showed an association with obesity in 1666 obese and 5737 nonobese individuals (P > 0.17). In agreement, none of the associations between the SNPs and any of the metabolic traits showed convincing associations in the 7562 adults from 4 population-based studies. Although a few nominally significant associations emerged, none of the associations survived multiple-testing correction. We observed no convincing associations with any of the studied traits in 1155 adolescents.

CONCLUSION

Although our study was sufficiently powered to identify small effects, the results suggest that common variation in INSIG1 is unlikely to have a major effect on T2D and obesity risk and related traits in white Europeans.

Evidence of shared genetic effects between pre- and postobesity epidemic BMI levels

United States has experienced a widespread obesity epidemic. However, it is unclear whether the obesogenic environment has uncovered genes previously unimportant in adiposity or whether genes influencing obesity are the same before and after the obesity epidemic. The objective of this study was to test whether BMI pre- and postobesity epidemic would be controlled by shared genetic effects. A 25-30-year follow-up of parents and children who participated in the National Institutes of Health-National Heart, Lung, and Blood Institute Lipid Research Clinics (LRC) Princeton School Study, 1973-1976, were followed up in 1999-2004 in the Princeton Follow-up Study (PFS). Heritability of BMI and genetic correlations between pre-epidemic BMI and BMI z-scores in adolescents and postobesity epidemic BMI were calculated. Even though they had similar ages, offspring had higher BMI in PFS than their parents in LRC (28.5 +/- 6.6 vs. 26.1 +/- 4.4, P < 0.0001). BMI measurements in offspring were strongly heritable (BMI(LRC): h(2) = 0.78 +/- 0.17; BMI z-score(LRC): h(2) = 0.61 +/- 0.16; BMI(PFS): h(2) = 0.64 +/- 0.16, all P < or = 0.0001). Further, the change of BMI exhibited a high heritability (h(2) = 0.51 +/- 0.18, P = 0.003). Bivariate analysis of BMI in LRC and PFS showed significant genetic correlation (0.70 +/- 0.16, P = 0.005), whereas the environmental correlation was not significant (0.36 +/- 0.17). Although the obesogenic environment may have changed between the 1970s and 2000s, many of the same genes are likely to be involved in establishing genetic susceptibility to obesity. Furthermore, shared genetic effects survive the period of the transition from adolescence to adulthood.

Association of HTR2C, but not LEP or INSIG2, genes with antipsychotic-induced weight gain in a German sample

Background: Drug-induced bodyweight gain (BWG) is a serious concern in pharmacotherapy with second-generation antipsychotics. The interindividual variability is likely to be modulated by genetic factors. In the past, pharmacogenetic studies yielded conflicting results, and none of the identified genetic alterations exerts sufficient predictive value for this severe side effect of psychopharmacotherapy. Aim: We aimed to contribute to the replication and extension of prior association findings and investigated the genes encoding serotonin 2C receptor (HTR2C), insulin-induced gene 2 (INSIG2) and leptin (LEP). Patients & methods: We investigated the association of HTR2C, LEP and INSIG2 SNPs with antipsychotic-induced BWG in 128 German schizophrenic patients. Genotyping was performed for nine SNPs (HTR2C: rs498207, rs3813928, rs6318 and rs3813929; INSIG2: rs17587100, rs10490624, rs17047764 and rs7566605; LEP: rs7799039). Association analysis included logistic regression analysis and Pearson´s χ2 tests. Results: We report a significant association of three HTR2C SNPs (rs498207, rs3813928 and rs3813929) and of the respective haplotype with antipsychotic-induced BWG. Regarding the X-chromosomal SNP rs498207, individuals with AA/A genotype gained more weight than those with GG/G genotype. The association observed with the SNP rs498207 was also significant after correcting for multiple testing (p = 0.0196). No association was found for INSIG2 and LEP SNPs. Conclusion: The results contribute to the accumulating evidence for an association of the X-chromosomal HTR2C gene with antipsychotic-induced BWG. The proposed underlying mechanisms include decreased HTR2C gene expression with reduced 5-HT-modulated activation of hypothalamic proopiomelanocortin-neurons, and inverse 5-HT2C agonism in the presence of D2 receptor antagonism.

A three-stage approach for genome-wide association studies with family data for quantitative traits

BACKGROUND

Genome-wide association (GWA) studies that use population-based association approaches may identify spurious associations in the presence of population admixture. In this paper, we propose a novel three-stage approach that is computationally efficient and robust to population admixture and more powerful than the family-based association test (FBAT) for GWA studies with family data.We propose a three-stage approach for GWA studies with family data. The first stage is to perform linear regression ignoring phenotypic correlations among family members. SNPs with a first stage p-value below a liberal cut-off (e.g. 0.1) are then analyzed in the second stage that employs a linear mixed effects (LME) model that accounts for within family correlations. Next, SNPs that reach genome-wide significance (e.g. 10-6 for 34,625 genotyped SNPs in this paper) are analyzed in the third stage using FBAT, with correction of multiple testing only for SNPs that enter the third stage. Simulations are performed to evaluate type I error and power of the proposed method compared to LME adjusting for 10 principal components (PC) of the genotype data. We also apply the three-stage approach to the GWA analyses of uric acid in Framingham Heart Study's SNP Health Association Resource (SHARe) project.

RESULTS

Our simulations show that whether or not population admixture is present, the three-stage approach has no inflated type I error. In terms of power, using LME adjusting PC is only slightly more powerful than the three-stage approach. When applied to the GWA analyses of uric acid in the SHARe project of FHS, the three-stage approach successfully identified and confirmed three SNPs previously reported as genome-wide significant signals.

CONCLUSIONS

For GWA analyses of quantitative traits with family data, our three-stage approach provides another appealing solution to population admixture, in addition to LME adjusting for genetic PC.

Statistical challenges for genome-wide association studies of suicidality using family data

The etiology of suicide is complex in nature with both environmental and genetic causes that are extremely diverse. This extensive heterogeneity weakens the relationship between genotype and phenotype and as a result, we face many challenges when studying the genetic etiology of suicide. We are now in the midst of a genetics revolution, where genotyping costs are decreasing and genotyping speed is increasing at a fast rate, allowing genetic association studies to genotype thousands to millions of SNPs that cover the entire human genome. As such, genome-wide association studies (GWAS) are now the norm. In this article we address several statistical challenges that occur when studying the genetic etiology of suicidality in the age of the genetics revolution. These challenges include: (1) the large number of statistical tests; (2) complex phenotypes that are difficult to quantify; and (3) modest genetic effect sizes. We address these statistical issues in the context of family-based study designs. Specifically, we discuss several statistical extensions of family-based association tests (FBATs) that work to alleviate these challenges. As our intention is to describe how statistical methodology may work to identify disease variants for suicidality, we avoid the mathematical details of the methodologies presented.

Mapping genes for osteoporosis--old dogs and new tricks

In stark contrast to its horticultural origins, modern genetics is an extremely technology-driven field. Almost all the major advances in the field over the past 20 years have followed technological developments that have permitted change in study designs. The development of PCR in the 1980s led to RFLP mapping of monogenic diseases. The development of fluorescent-tagged genotyping methods led to linkage mapping approaches for common diseases that dominated the 1990s. The development of microarray SNP genotyping has led to the genome-wide association study era of the new millennium. And now the development of next-generation sequencing technologies is about to open up a new era of gene-mapping, enabling many potential new study designs. This review aims to present the strengths and weaknesses of the current approaches, and present some new ideas about gene-mapping approaches that are likely to advance our knowledge of the genes involved in heritable bone traits such as bone mineral density (BMD) and fracture.

Common SNPs in FTO gene are associated with obesity related anthropometric traits in an island population from the eastern Adriatic coast of Croatia

BACKGROUND

Multiple studies have provided compelling evidence that the FTO gene variants are associated with obesity measures. The objective of the study was to investigate whether FTO variants are associated with a broad range of obesity related anthropometric traits in an island population.

METHODOLOGY/PRINCIPAL FINDINGS

We examined genetic association between 29 FTO SNPs and a comprehensive set of anthropometric traits in 843 unrelated individuals from an island population in the eastern Adriatic coast of Croatia. The traits include 11 anthropometrics (height, weight, waist circumference, hip circumference, bicondilar upper arm width, upper arm circumference, and biceps, triceps, subscapular, suprailiac and abdominal skin-fold thicknesses) and two derived measures (BMI and WHR). Using single locus score tests, 15 common SNPs were found to be significantly associated with "body fatness" measures such as weight, BMI, hip and waist circumferences with P-values ranging from 0.0004 to 0.01. Similar but less significant associations were also observed between these markers and bicondilar upper arm width and upper arm circumference. Most of these significant findings could be explained by a mediating effect of "body fatness". However, one unique association signal between upper arm width and rs16952517 (P-value = 0.00156) could not be explained by this mediating effect. In addition, using a principle component analysis and conditional association tests adjusted for "body fatness", two novel association signals were identified between upper arm circumference and rs11075986 (P-value = 0.00211) and rs16945088 (P-value = 0.00203).

CONCLUSIONS/SIGNIFICANCE

The current study confirmed the association of common variants of FTO gene with "body fatness" measures in an isolated island population. We also observed evidence of pleiotropic effects of FTO gene on fat-free mass, such as frame size and muscle mass assessed by bicondilar upper arm width and upper arm circumference respectively and these pleiotropic effects might be influenced by variants that are different from the ones associated with "body fatness".