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Objective: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns., Methods: We performed machine learning-based, integrative unsupervised clustering to identify proteomics- and metabolomics-defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m 2 ), leveraging data from 243 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits., Results: We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high-density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2., Conclusions: Although the two identified clusters may represent progressive obesity-related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage., (© 2024 The Obesity Society.)

Background/objectives: Obesity, defined as excessive fat accumulation that represents a health risk, is increasing in adults and children, reaching global epidemic proportions. Body mass index (BMI) correlates with body fat and future health risk, yet differs in prediction by fat distribution, across populations and by age. Nonetheless, few genetic studies of BMI have been conducted in ancestrally diverse populations. Gene expression association with BMI was assessed in the Multi-Ethnic Study of Atherosclerosis (MESA) in four self-identified race and ethnicity (SIRE) groups to identify genes associated with obesity., Subjects/methods: RNA-sequencing was performed on 1096 MESA participants (37.8% white, 24.3% Hispanic, 28.4% African American, and 9.5% Chinese American) and linear models were used to assess the association of expression from each gene for its effect on BMI, adjusting for age, sex, sequencing center, study site, five expression and four genetic principal components in each self-identified race group. Sample-size-weighted meta-analysis was performed to identify genes with BMI-associated expression across ancestry groups., Results: Within individual SIRE groups, there were zero to three genes whose expression is significantly (p < 1.97 × 10 -6 ) associated with BMI. Across all groups, 45 genes were identified by meta-analysis whose expression was significantly associated with BMI, explaining 29.7% of BMI variation. The 45 genes are expressed in a variety of tissues and cell types and are enriched for obesity-related processes including erythrocyte function, oxygen binding and transport, and JAK-STAT signaling., Conclusions: We have identified genes whose expression is significantly associated with obesity in a multi-ethnic cohort. We have identified novel genes associated with BMI as well as confirmed previously identified genes from earlier genetic analyses. These novel genes and their biological pathways represent new targets for understanding the biology of obesity as well as new therapeutic intervention to reduce obesity and improve global public health., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRS common ) with a rare variant PRS (PRS rare ) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m 2 ), obesity (BMI ≥ 30 kg/m 2 ), and extreme obesity (BMI ≥ 40 kg/m 2 ). We built PRSs common and PRSs rare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRS common explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRS rare explained 1.49%, and 2.97% and 3.68%, respectively. The PRS rare was associated with an increased risk of obesity and extreme obesity (OR obesity = 1.37 per SD PRS , P obesity = 1.7x10 -85 ; OR extremeobesity = 1.55 per SD PRS , P extremeobesity = 3.8x10 -40 ), which was attenuated, after adjusting for PRS common (OR obesity = 1.08 per SD PRS , P obesity = 9.8x10 -6 ; OR extremeobesity = 1.09 per SD PRS , P extremeobesity = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS rare and PRS common provided little improvement to the prediction of obesity (PRS rare was small (incremental Nagelkerke R 2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS rare AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS common provided little improvement to the prediction of obesity (PRS rare in the prediction of obesity risk, based on these large populations.common AUC = 0.708; PRS combined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS rare provides limited improvement over PRS common in the prediction of obesity risk, based on these large populations., Competing Interests: BP serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. PE has received sponsored research support from Bayer AG and from IBM Research and has also served on advisory boards or consulted for Bayer AG, Quest Diagnostics, MyoKardia and Novartis. SL receives sponsored research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim, Fitbit, and IBM, and has consulted for Bristol Myers Squibb/Pfizer, Blackstone Life Sciences, and Invitae. ES has received grant support from GSK and Bayer. The handling editor declared a past co-authorship with one of the authors RL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Choi, Chami, Boerwinkle, Fornage, Redline, Bis, Brody, Psaty, Kim, McDonald, Regan, Silverman, Liu, Vasan, Kalyani, Mathias, Yanek, Arnett, Justice, North, Kaplan, Heckbert, de Andrade, Guo, Lange, Rich, Rotter, Ellinor, Lubitz, Blangero, Shoemaker, Darbar, Gladwin, Albert, Chasman, Jackson, Kooperberg, Reiner, O’Reilly and Loos.)

Background: African ancestry individuals with comparable overall anthropometric measures to Europeans have lower abdominal adiposity. To explore the genetic underpinning of different adiposity patterns, we investigated whether genetic risk scores for well-studied adiposity phenotypes like body mass index (BMI) and waist circumference (WC) also predict other, less commonly measured adiposity measures in 2420 African American individuals from the Jackson Heart Study., Methods: Polygenic risk scores (PRS) were calculated using GWAS-significant variants extracted from published studies mostly representing European ancestry populations for BMI, waist-hip ratio (WHR) adjusted for BMI (WHRBMIadj), waist circumference adjusted for BMI (WCBMIadj), and body fat percentage (BF%). Associations between each PRS and adiposity measures including BF%, subcutaneous adiposity tissue (SAT), visceral adiposity tissue (VAT) and VAT:SAT ratio (VSR) were examined using multivariable linear regression, with or without BMI adjustment., Results: In non-BMI adjusted models, all phenotype-PRS were found to be positive predictors of BF%, SAT and VAT. WHR-PRS was a positive predictor of VSR, but BF% and BMI-PRS were negative predictors of VSR. After adjusting for BMI, WHR-PRS remained a positive predictor of BF%, VAT and VSR but not SAT. WC-PRS was a positive predictor of SAT and VAT; BF%-PRS was a positive predictor of BF% and SAT only., Conclusion: These analyses suggest that genetically driven increases in BF% strongly associate with subcutaneous rather than visceral adiposity and BF% is strongly associated with BMI but not central adiposity-associated genetic variants. How common genetic variants may contribute to observed differences in adiposity patterns between African and European ancestry individuals requires further study., Competing Interests: The authors have declared that no competing interests exist.

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10 -7 ). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r 2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10 -4 ) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels., (Copyright © 2019 American Society of Human Genetics. All rights reserved.)

Obesity is a disease with a complex etiology and variable prevalence across different populations. While several studies have reported gut microbiota composition differences associated with obesity in humans, there has been a lack of consistency in the nature of the reported changes; it has been difficult to determine whether methodological differences between studies, underlying differences in the populations studied, or other factors are responsible for this discordance. Here we use 16 S rRNA data from previously published studies to explore how the gut microbiota-obesity relationship varies across heterogeneous Western populations, focusing mainly on the relationship between (1) alpha diversity and (2) Prevotella relative abundance with BMI. We provide evidence that the relationship between lower alpha diversity and higher BMI may be most consistent in non-Hispanic white (NHW) populations and/or those with high socioeconomic status, while the relationship between higher Prevotella relative abundance and BMI may be stronger among black and Hispanic populations. We further examine how diet may impact these relationships. This work suggests that gut microbiota phenotypes of obesity may differ with race/ethnicity or its correlates, such as dietary components or socioeconomic status. However, microbiome cohorts are often too small to study complex interaction effects and non-white individuals are greatly underrepresented, creating substantial challenges to understanding population-level patterns in the microbiome-obesity relationship. Further study of how population heterogeneity influences the relationship between the gut microbiota and obesity is warranted., Competing Interests: Competing interestsThe authors declare no competing interests.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Objective: The association of obesity susceptibility variants with change in body mass index (BMI) across the life course is not well understood., Subjects: In ancestry-stratified models of 5962 European American (EA), 2080 African American (AA) and 1582 Hispanic American (HA) individuals from the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examined associations between 34 obesity single-nucleotide polymorphisms (SNPs) with per year change in BMI, measured by the slope from a growth-curve analysis of two or more BMI measurements between adolescence and young adulthood. For SNPs nominally associated with BMI change (P<0.05), we interrogated age differences within data collection Wave and time differences between age categories that overlapped between Waves., Results: We found SNPs in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B and TMEM18 were significantly associated (P<0.0015≈0.05/34) with BMI change in EA and the ancestry-combined meta-analysis. rs9939609 in FTO met genome-wide significance at P<5e-08 in the EA and ancestry-combined analysis, respectively [Beta(se)=0.025(0.004);Beta(se)=0.021(0.003)]. No SNPs were significant after Bonferroni correction in AA or HA, although five SNPs in AA and four SNPs in HA were nominally significant (P<0.05). In EA and the ancestry-combined meta-analysis, rs3817334 near MTCH2 showed larger effects in younger respondents, whereas rs987237 near TFAP2B, showed larger effects in older respondents across all Waves. Differences in effect estimates across time for MTCH2 and TFAP2B are suggestive of either era or cohort effects., Conclusion: The observed association between variants in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B and TMEM18 with change in BMI from adolescence to young adulthood suggest that the genetic effect of BMI loci varies over time in a complex manner, highlighting the importance of investigating loci influencing obesity risk across the life course.

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.

Little is known about how obesity susceptibility single nucleotide polymorphisms (SNPs) interact with moderate to vigorous physical activity (MVPA) in relation to BMI during adolescence, once obesogenic neighborhood factors are accounted for. In race stratified models, including European (EA; N=4977), African (AA; N=1726), and Hispanic Americans (HA; N=1270) from the National Longitudinal Study of Adolescent to Adult Health (1996; ages 12-21), we assessed the evidence for a SNPxMVPA interaction with BMI-for-age Z score, once accounting for obesogenic neighborhood factors including physical activity amenities, transportation and recreation infrastructure, poverty and crime. Eight SNPxMVPA interactions with suggestive significance (p<0.10; three in each EA, and AA, two in HA) were observed showing attenuation on BMI-for-age Z score in adolescents with ≥5 versus <5 bouts/week MVPA, except for rs10146997 (near NRXN3). Findings were robust to the inclusion of neighborhood-level variables as covariates. These findings suggest that any attenuation from MVPA on a genetic susceptibility to obesity during adolescence is likely not operating through obesogenic neighborhood factors., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet, published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes, were evaluated by mining GWAS datasets. eQTL analysis identified 1971 and 2078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2 were identified in both tissues. 62.1 % of top cis-eSNPs were within ±50 kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu ) and identified genetically regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes.

Gallbladder disease (GBD) has an overall prevalence of 10-40% depending on factors such as age, gender, population, obesity and diabetes, and represents a major economic burden. Although gallstones are composed of cholesterol by-products and are associated with obesity, presumed causal pathways remain unproven, although BMI reduction is typically recommended. We performed genetic studies to discover candidate genes and define pathways involved in GBD. We genotyped 15,241 women of European ancestry from three cohorts, including 3216 with GBD, using the Human cardiovascular disease (HumanCVD) BeadChip containing up to ~ 53,000 single-nucleotide polymorphisms (SNPs). Effect sizes with P-values for development of GBD were generated. We identify two new loci associated with GBD, GCKR rs1260326:T>C (P = 5.88 × 10(-7), ß = -0.146) and TTC39B rs686030:C>A (P = 6.95 x 10(-7), ß = 0.271) and detect four independent SNP effects in ABCG8 rs4953023:G>A (P=7.41 × 10(-47), ß = 0.734), ABCG8 rs4299376:G(>)T (P = 2.40 × 10(-18), ß = 0.278), ABCG5 rs6544718:T>C (P = 2.08 × 10(-14), ß = 0.044) and ABCG5 rs6720173:G>C (P = 3.81 × 10(-12), ß(=)0.262) in conditional analyses taking genotypes of rs4953023:G>A as a covariate. We also delineate the risk effects among many genotypes known to influence lipids. These data, from the largest GBD genetic study to date, show that specific, mainly hepatocyte-centred, components of lipid metabolism are important to GBD risk in women. We discuss the potential pharmaceutical implications of our findings.

Background: Adolescence is a sensitive period for weight gain and risky health behaviors, such as smoking. Genome-wide association studies (GWAS) have identified loci contributing to adult body mass index (BMI). Evidence suggests that many of these loci have a larger influence on adolescent BMI. However, few studies have examined interactions between smoking and obesity susceptibility loci on BMI. This study investigates the interaction of current smoking and established BMI SNPs on adolescent BMI. Using data from the National Longitudinal Study of Adolescent to Adult Health, a nationally-representative, prospective cohort of the US school-based population in grades 7 to 12 (12-20 years of age) in 1994-95 who have been followed into adulthood (Wave II 1996; ages 12-21, Wave III; ages 18-27), we assessed (in 2014) interactions of 40 BMI-related SNPs and smoking status with percent of the CDC/NCHS 2000 median BMI (%MBMI) in European Americans (n = 5075), African Americans (n = 1744) and Hispanic Americans (n = 1294)., Results: Two SNPs showed nominal significance for interaction (p < 0.05) between smoking and genotype with %MBMI in European Americans (EA) (rs2112347 (POC5): β = 1.98 (0.06, 3.90), p = 0.04 and near rs571312 (MC4R): β 2.15 (-0.03, 4.33) p = 0.05); and one SNP showed a significant interaction effect after stringent correction for multiple testing in Hispanic Americans (HA) (rs1514175 (TNNI3K): β 8.46 (4.32, 12.60), p = 5.9E-05). Stratifying by sex, these interactions suggest a stronger effect in female smokers., Conclusions: Our study highlights potentially important sex differences in obesity risk by smoking status in adolescents, with those who may be most likely to initiate smoking (i.e., adolescent females), being at greatest risk for exacerbating genetic obesity susceptibility.

Background: The objective of this study was to investigate the genetic association of 4 candidate variants with blood pressure and test the modifying effects of environmental factors including age, sex, and body mass index (BMI)., Methods: We used a linear mixed-effects model to test for variant main effects and variant interactions with age, sex, and BMI on systolic (SBP) and diastolic (DBP) blood pressure in 7,319 Chinese adults from the China Health and Nutrition Survey (CHNS). We attempted to replicate our significant interaction findings in 1,996 Chinese men from the Fangchenggang Area Male Health and Examination Survey (FAMHES)., Results: Two variants (rs11105378 near ATP2B1 and rs1458038 near FGF5) were significantly associated (P < 0.00625 = 0.05/8) with both SBP and DBP in CHNS. Variant rs1378942 near CSK was nominally associated with SBP (P = 0.01). The signal at rs1458038 exhibited a genotype-by-BMI interaction affecting blood pressure (P interaction = 0.0018 for SBP; P interaction = 0.049 for DBP), with the strongest variant effects in those with the highest BMI. In FAMHES, rs1458038 also showed stronger effects on SBP and DBP among men with the highest BMI., Conclusions: Our findings suggest high BMI increases the effect of the blood pressure-increasing allele at rs1458038 near FGF5, further highlighting the importance of obesity prevention in reducing hypertension risk., (© American Journal of Hypertension, Ltd 2015. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Little is known about the interaction between genetic and behavioural factors during lifecycle risk periods for obesity and how associations vary across race/ethnicity., Objective: The objective of this study was to examine joint associations of adiposity-related single-nucleotide polymorphisms (SNPs) and moderate to vigorous physical activity (MVPA) with body mass index (BMI) in a diverse adolescent cohort., Methods: Using data from the National Longitudinal Study of Adolescent Health (n = 8113: Wave II 1996; ages 12-21, Wave III; ages 18-27), we assessed interactions of 41 well-established SNPs and MVPA with BMI-for-age Z-scores in European Americans (EA; n = 5077), African-Americans (AA; n = 1736) and Hispanic Americans (HA; n = 1300)., Results: Of 97 assessed, we found nominally significant SNP-MVPA interactions on BMI-for-age Z-score in EA at GNPDA2 and FTO and in HA at LZTR2/SEC16B. In EA, the estimated effect of the FTO risk allele on BMI-for-age Z-score was lower (β = -0.13; 95% confidence interval [CI]: 0.08, 0.18) in individuals with ≥5 vs. <5 (β = 0.24; CI: 0.16, 0.32) bouts of MVPA per week (P for interaction 0.02). Race/ethnicity-pooled meta-analysis showed nominally significant interactions for SNPs at TFAP2B, POC5 and LYPLAL1., Conclusions: High MVPA may attenuate underlying genetic risk for obesity during adolescence, a high-risk period for adult obesity., (© 2013 The Authors. Pediatric Obesity © 2013 International Association for the Study of Obesity.)

Background: There has been little investigation of gene-by-environment interactions related to sedentary behaviour, a risk factor for obesity defined as leisure screen time (ST; i.e. television, video and computer games)., Objective: To test the hypothesis that limiting ST use attenuates the genetic predisposition to increased body mass index (BMI), independent of physical activity., Design: Using 7642 wave II participants of the National Longitudinal Study of Adolescent Health, (Add Health; mean = 16.4 years, 52.6% female), we assessed the interaction of ST (h week(-1) ) and 41 established obesity single nucleotide polymorphisms (SNPs) with age- and sex-specific BMI Z-scores in 4788 European-American (EA), 1612 African-American (AA) and 1242 Hispanic American (HA) adolescents., Results: Nominally significant SNP*ST interaction were found for FLJ35779 in EA, GNPDA2 in AA and none in HA (EA: beta [SE] = 0.016[0.007]), AA: beta [SE] = 0.016[0.011]) per 7 h week(-1) ST and one risk allele in relation to BMI Z-score., Conclusions: While for two established BMI loci, we find evidence that high levels of ST exacerbate the influence of obesity susceptibility variants on body mass; overall, we do not find strong evidence for interactions between the majority of established obesity loci. However, future studies with larger sample sizes, or that may build on our current study and the growing published literature, are clearly warranted., (© 2013 The Authors. Pediatric Obesity © 2013 International Association for the Study of Obesity.)

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

Background: an increase in sedentary activities is likely a major contributor to the rise in obesity over the last three decades. Little research has examined interactions between genetic variants and sedentary activity on obesity phenotypes. High levels of sedentary activity during adolescence may interact with genetic factors to influence body mass changes between adolescence and young adulthood, a high risk period for weight gain., Methods: in the National Longitudinal Study of Adolescent Health, siblings and twin pairs (16.5 ± 1.7 years) were followed into young adulthood (22.4 ± 1.8 years). Self-reported screen time (TV, video, and computer use in h/week) and body mass index (kg/m(2) ), calculated from measured height and weight at adolescence and at young adulthood, were available for 3795 participants. We employed a variance component approach to estimate the interaction between genotype and screen time for body mass changes. Additive genotype-by-screen time interactions were assessed using likelihood-ratio tests. Models were adjusted for race, age, sex, and age-by-sex interaction., Results: the genetic variation in body mass changes was significantly larger in individuals with low ( δ(G) = 27.59 ± 1.58) compared with high (δ(G) = 18.76 ± 2.59) levels of screen time (p < 0.003) during adolescence., Conclusions: Our findings demonstrate that sedentary activities during adolescence may interact with genetic factors to influence body mass changes between adolescence and young adulthood. Accounting for obesity-related behaviours may improve current understanding of the genetic variation in body mass changes., (2010 John Wiley & Sons, Ltd.)

The complex interplay between genes and environment affecting body mass gain over lifecycle periods of risk is not well understood. We use longitudinal sibling cohort data to examine the role of shared household environment, additive genetic, and shared genetic effects on BMI and BMI change. In the National Longitudinal Study of Adolescent Health, siblings and twin pairs sharing households for > or =10 years as adolescents (N = 5,524; mean = 16.5 +/- 1.7 years) were followed into young adulthood (N = 4,368; mean = 22.4 +/- 1.8 years). Using a variance component approach, we quantified genetic and household effects on BMI in siblings and nonsiblings sharing household environments over time. Adjusting for race, age, sex, and age-by-sex interaction, we detected a heritability of 0.43 +/- 0.05 for BMI change. Significant household effects were noted during the young adulthood period only (0.11 +/- 0.06). We find evidence for shared genetic effects between BMI and BMI change during adolescence (genetic correlation (rho(G)) = 0.61 +/- 0.03) and young adulthood (rho(G) = 0.23 +/- 0.06). Our findings support a complex etiology of BMI and BMI change.

The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI> or =32.5, 35.0, 37.5, 40.0 kg/m(2) versus BMI<25 kg/m(2)) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far., Competing Interests: Dawn Waterworth and Vincent Moser are employers of GSK. Gudmar Thorleifsson is employer and shareholder of deCODE.

Objective: The underlying genetic component of obesity-related traits is not well understood, and there is limited evidence to support genetic association shared across multiple studies, populations, and environmental contexts. The present study investigated the association between candidate variants and obesity-related traits in a sample of 1,886 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS) cohort., Research Design and Methods: We selected and genotyped 19 single nucleotide polymorphisms in 10 genes (ADRB2, ADRB3, FTO, GNB3, INSIG2, LEPR, PPARG, TNF, UCP2, and UCP3) that had been previously reported to be associated with an obesity-related quantitative trait., Results: We observed evidence for association of the A allele of rs9939609 (FTO intron 1) with increased BMI (P = 0.0072 before multiple test correction), baseline BMI (P = 0.0015), longitudinal BMI based on eight surveys from 1983 to 2005 (P = 0.000029), waist circumference (P = 0.0094), and weight (P = 0.021). The increase in average BMI was approximately 0.4 for each additional A allele. We also observed association of the ADRB3 Trp64Arg variant with BMI, waist circumference, percent body fat, weight, fat mass, arm fat area, and arm muscle area (P < 0.05), although the direction of effect is inconsistent with the majority of previous reports., Conclusions: Our study confirms that FTO is a common obesity susceptibility gene in Filipinos, with an effect size similar to that seen in samples of European origin.

OBJECTIVE:: Adipose tissue distribution (visceral vs subcutaneous) has been shown to be an important predictor of insulin resistance, diabetes and cardiovascular disease, independent of body mass index. The beta-2 adrenergic receptor is a major lipolytic receptor in human fat cells and the gene that codes for this protein is an important candidate gene for measures of adiposity and fat deposition. We examined whether two common polymorphisms in codons 16 (Arg16Gly) and 27 (Gln27Glu) are associated with measures of fat distribution in participants of the IRAS Family Study. METHODS:: We recruited African-American (AA) and Hispanic-American (HA) families from Los Angeles, CA, USA (18 pedigrees, 272 AA individuals), San Antonio, TX, USA (33 pedigrees, 448 HA individuals) and San Luis Valley, CO, USA (12 pedigrees, 272 HA individuals). We estimated adipose tissue distribution via computed tomography. To test for an association between adiposity measures and these polymorphisms, we used generalized estimating equations, adjusting for age, gender, clinical site (ethnicity), body mass index, and familial correlation. RESULTS:: Of the 992 individuals genotyped for these polymorphisms, 57%were female and 15%had been diagnosed with type 2 diabetes mellitus. The mean age was 42.7±14.6?y. The Glu27 allele of the Gln27Glu polymorphism was positively associated with (P-value for recessive model): body mass index (0.025), visceral adipose tissue (<0.0001) and visceral-to-subcutaneous adipose ratio (0.009), but not with subcutaneous adipose tissue (0.952). The Arg16Gly polymorphism was not associated with any of the adiposity measures. CONCLUSIONS:: These findings suggest that genetic variation in the beta-2 adrenergic receptor gene influences fat deposition and body size in AAs and HAs. In particular, these results support a role for the gene in the distribution of visceral adipose tissue but not subcutaneous adipose tissue.International Journal of Obesity (2005) 29, 449-457. doi:10.1038/sj.ijo.0802883 Published online 18 January 2005 [ABSTRACT FROM AUTHOR]