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PURPOSE OF REVIEW: The prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the United States, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS) – including those of obesity – have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African ancestry participants are still just 3% of GWAS, Hispanic/Latinos are

Background Transgenerational epigenetic inheritance has been posited as a possible contributor to the observed heritability of metabolic syndrome (MetS). Yet the extent to which estimates of epigenetic inheritance for DNA methylation sites are inflated by environmental and genetic covariance within families is still unclear. We applied current methods to quantify the environmental and genetic contributors to the observed heritability and familial correlations of four previously associated MetS methylation sites at three genes (CPT1A, SOCS3 and ABCG1) using real data made available through the GAW20. Results Our findings support the role of both shared environment and genetic variation in explaining the heritability of MetS and the four MetS cytosine-phosphate-guanine (CpG) sites, although the resulting heritability estimates were indistinguishable from one another. Familial correlations by type of relative pair generally followed our expectation based on relatedness, but in the case of sister and parent pairs we observed nonsignificant trends toward greater correlation than expected, as would be consistent with the role of shared environmental factors in the inflation of our estimated correlations. Conclusions Our work provides an interesting and flexible statistical framework for testing models of epigenetic inheritance in the context of human family studies. Future work should endeavor to replicate our findings and advance these methods to more robustly describe epigenetic inheritance patterns in human populations.

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a “genetic-analysis group” variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.

Summary Background Adolescent obesity is predictive of future weight gain, obesity and adult onset severe obesity (body mass index [BMI] ≥40 kg m−2). Despite successful efforts to identify Single Nucleotide Polymorphisms (SNPs) influencing BMI

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.

Background Genome-wide association studies have implicated the transcription factor 7-like 2 (TCF7L2) gene in type 2 diabetes risk, and more recently, in decreased body mass index. Given the contrary direction of genetic effects on these two traits, it has been suggested that the observed association with body mass index may reflect either selection bias or a complex underlying biology at TCF7L2. Methods Using 9031 Hispanic/Latino adults (21–76 years) with complete weight history and genetic data from the community-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Baseline 2008–2011), we estimated the multivariable association between the additive number of type 2 diabetes increasing-alleles at TCF7L2 (rs7903146-T) and body mass index. We then used structural equation models to simultaneously model the genetic association on changes in body mass index across the life course and estimate the odds of type 2 diabetes per TCF7L2 risk allele. Results We observed both significant increases in type 2 diabetes prevalence at examination (independent of body mass index) and decreases in mean body mass index and waist circumference across genotypes at rs7903146. We observed a significant multivariable association between the additive number of type 2 diabetes-risk alleles and lower body mass index at examination. In our structured modeling, we observed non-significant inverse direct associations between rs7903146-T and body mass index at ages 21 and 45 years, and a significant positive association between rs7903146-T and type 2 diabetes onset in both middle and late adulthood. Conclusions Herein, we replicated the protective effect of rs7930146-T on body mass index at multiple time points in the life course, and observed that these effects were not explained by past type 2 diabetes status in our structured modeling. The robust replication of the negative effects of TCF7L2 on body mass index in multiple samples, including in our diverse Hispanic/Latino community-based sample, supports a growing body of literature on the complex biologic mechanism underlying the functional consequences of TCF7L2 on obesity and type 2 diabetes across the life course. Electronic supplementary material The online version of this article (10.1186/s40608-018-0200-x) contains supplementary material, which is available to authorized users.

Figure S1. BAIAP2 gene expression (from Gene-Tissue Expression project, GTEx) in human tissues [46]. (DOCX 193Â kb)

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N=60,552), African (N=8,429), Asian (N=9,959), and Hispanic/Latino (N=11,775) ethnicities. We identified over 50 novel loci at genome-wide significance in ancestry-specific and/or multiethnic meta-analyses. Recent fine mapping methods incorporating functional annotation, gene expression, and/or differences in linkage disequilibrium between ethnicities identified potential causal variants and genes at known and newly identified loci. Sixteen of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12.

Elevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies. A multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation. Previously reported SNP associations were significantly replicated (p ≤ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513. These findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries. The summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000356.v1.p1

BACKGROUND Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined. METHODS We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies. RESULTS Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4). CONCLUSIONS The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1–3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4–10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States—where minority populations have a disproportionately higher burden of chronic conditions13—the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.

OBJECTIVE: PR interval (PR) is a heritable electrocardiographic measure of atrial and atrioventricular nodal conduction. Changes in PR duration may be associated with atrial fibrillation, heart failure, and all-cause mortality. Hispanic/Latino populations have high burdens of cardiovascular morbidity and mortality, are highly admixed, and represent exceptional opportunities for novel locus identification. However, they remain chronically understudied. We present the first genome-wide association study (GWAS) of PR in 14,756 participants of Hispanic/Latino ancestry from three studies. METHODS: Study-specific summary results of the association between 1000 Genomes Phase 1 imputed SNPs and PR assumed an additive genetic model and were adjusted for global ancestry, study center/region, and clinical covariates. Results were combined using fixed-effects, inverse variance weighted meta-analysis. Sequential conditional analyses were used to identify independent signals. Replication of novel loci was performed in populations of Asian, African, and European descent. ENCODE and RoadMap data were used to annotate results. RESULTS: We identified a novel genome-wide association (P

The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for the association of serum 25-hydroxyvitamin D [25(OH)D] and pulmonary function. We conducted the largest cross-sectional meta-analysis of the 25(OH)D– pulmonary function association to date, based on nine European ancestry (EA) cohorts (n=22,838) and five African ancestry (AA) cohorts (n=4,290) in the CHARGE Consortium. Data were analyzed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean (SD) serum 25(OH)D was 68 (29) nmol/L for EAs and 49 (21) nmol/L for AAs. For each 1 nmol/L higher 25(OH)D, forced expiratory volume in the first second (FEV1) was higher by 1.1 mL in EAs (95% CI: 0.9,1.3; P=2.5×10-21) and 1.8 mL (95% CI: 1.1,2.5; P=1.6×10-7) in Aas (Prace difference=0.06), and forced vital capacity (FVC) was higher by 1.3 mL in EAs (95% CI: 1.0,1.6; P=1.1×10-20) and 1.5 mL (95% CI: 0.8,2.3; P=1.2×10-4) in AAs (Prace difference=0.56). Among EAs, the 25(OH)D–FVC association was stronger in smokers: per 1nmol/L higher 25(OH)D, FVC was higher by 1.7 mL (95% CI: 1.1,2.3) for current smokers and 1.7 mL (95% CI: 1.2,2.1) for former smokers, compared to 0.8 mL (95% CI: 0.4,1.2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EAs, a stronger association was observed for smokers compared to never smokers, which supports the importance of vitamin D in vulnerable populations.Cohort FundingThis work was supported by National Institutes of Health (NIH) grant number R21 HL125574 funded by the National Heart, Lung, and Blood Institute (NHLBI) and the NIH Office of Dietary Supplements (ODS) (co-Principal Investigators [co-PIs]: DBH and PAC). The corresponding author (PAC) had full access to the data for the meta-analysis, and had final responsibility for the decision to submit for publication. No funding source had any role in the analysis of the data, the writing of the manuscript, or the decision to submit it. This work was also supported in part by R01HL077612 (PI: RGB) and by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (ZO1 ES043012, PI: SJL). SJL is supported by the Intramural Research Program of NIH, National Institute of Environmental Health Sciences. Infrastructure for the CHARGE Consortium is supported in part by the NHLBI grant R01HL105756.The Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C, the National Institute on Aging (NIA) Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee, VSN: 00-063. The researchers are indebted to the participants for their willingness to participate in the study.The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by NHLBI contracts HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C. 25(OH)D measurements were conducted with the support of R01 HL103706 from the NHLBI and R01 HL103706-S1 from the NIH ODS. The authors thank the staff and participants of the ARIC study for their important contributions.This Cardiovascular Health Study (CHS) research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants U01HL080295, R01HL085251, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and R01HL130114 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Vitamin D measurements were made possible by NHLBI (R01HL084443-01A2).This work in Framingham Heart Study was supported by NHLBI’s Framingham Heart Study contract (N01-HC-25195 and HHSN268201500001I). Vitamin D measurements in the Framingham study were made possible by NIA (R01 AG14759 to SLB.).The Health Aging and Body Composition cohort study was supported by NIA contracts N01AG62101, N01AG2103, and N01AG62106, NIA grant R01-AG028050, NINR grant R01-NR012459, and in part by the Intramural Research Program of the NIA, NIH. This research was further supported by RC1AG035835, and the serum vitamin D assays were supported by R01AG029364.The Multi-Ethnic Study of Atherosclerosis (MESA) study is conducted and supported by NHLBI in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 from NHLBI, UL1-TR-000040, UL1-TR-001079, and UL1-TR-001881 from NCRR, and DK063491 from the NIDDK. The MESA Lung study was supported by grants R01 HL077612, RC1 HL100543 and R01 HL093081 from NHLBI. Support for the Mineral Metabolite dataset was provided by grant HL096875.The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, the Netherlands; the Organization for the Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Dutch Ministry of Education, Culture, and Science; the Dutch Ministry for Health, Welfare, and Sports; the European Commission (DG XII), and the Municipality of Rotterdam. LL was a postdoctoral fellow of the Research Foundation—Flanders (FWO) in Brussels, Belgium. Part of this work was supported by a FWO-grant G035014N. DSM Nutritional Products AG, Kaiseraugst, Switzerland, sponsored the Vitamin D serum analyses. The authors are grateful to the study participants, the staff from the Rotterdam Study, and the participating general practitioners and pharmacists.The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, and HHSN268200900041C from the National Heart, Lung, and Blood Institute (NHLBI), the Intramural Research Program of the National Institute on Aging (NIA), and an intra-agency agreement between NIA and NHLBI (AG0005).Author DisclosureDr. Psaty serves on the DSMB of a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson.All other authors have no conflicts of interest. There is no commercial support or financial interest from the tobacco industry for the research presented.The study sponsors were not involved in study design, data collection, data analysis, data interpretation, report writing, or decisions to submit the paper for publication. PAC and DBH had final responsibility for the decision to submit for publication.Online Supporting MaterialSupplemental table, figures, and methods are available.Abbreviation Footnote25(OH)D25-Hydroxyvitamin DAAAfrican AncestryAGESAge, Gene, Environment, Susceptibility Study—Reykjavik, IcelandARICAtherosclerosis Risk in Communities StudyCARDIACoronary Artery Risk Development in Young Adults StudyCHARGECohorts for Heart and Aging Research in Genomic Epidemiology ConsortiumCHSCardiovascular Health StudyCLIAChemiluminescence ImmunoassayCOPDChronic Obstructive Pulmonary DiseaseEAEuropean AncestryFEV1Forced Expiratory Volume in the First SecondFHS (Offspring)Framingham Heart Study—Offspring CohortFHS (Gen3)Framingham Heart Study—Generation 3 CohortFVCForced Vital CapacityHABCHealth, Aging, and Body Composition StudyLC-MS/MSLiquid Chromatography in Tandem with Mass SpectrometryMESAMulti-Ethnic Study of AtherosclerosisNHANESNational Health and Nutrition Examination SurveyPFTPulmonary Function TestRIARadioimmunoassayRSRotterdam (Netherlands) Study

Evidence suggests European American (EA) women have two- to five-fold increased odds of having pelvic organ prolapse (POP) when compared with African American (AA) women. However, the role of genetic ancestry in relation to POP risk is not clear. Here we evaluate the association between genetic ancestry and POP in AA women from the Women's Health Initiative Hormone Therapy trial. Women with grade 1 or higher classification, and grade 2 or higher classification for uterine prolapse, cystocele or rectocele at baseline or during follow-up were considered to have any POP (N = 805) and moderate/severe POP (N = 156), respectively. Women with at least two pelvic exams with no indication for POP served as controls (N = 344). We performed case-only, and case-control admixture-mapping analyses using multiple logistic regression while adjusting for age, BMI, parity and global ancestry. We evaluated the association between global ancestry and POP using multiple logistic regression. European ancestry at the individual level was not associated with POP risk. Case-only and case-control local ancestry analyses identified two ancestry-specific loci that may be associated with POP. One locus (Chromosome 15q26.2) achieved empirically-estimated statistical significance and was associated with decreased POP odds (considering grade ≥2 POP) with each unit increase in European ancestry (OR: 0.35; 95% CI: 0.30, 0.57; p-value = 1.48x10-5). This region includes RGMA, a potent regulator of the BMP family of genes. The second locus (Chromosome 1q42.1-q42.3) was associated with increased POP odds with each unit increase in European ancestry (Odds ratio [OR]: 1.69; 95% confidence interval [CI]: 1.28, 2.22; p-value = 1.93x10-4). Although this region did not reach statistical significance after considering multiple comparisons, it includes potentially relevant genes including TBCE, and ACTA1. Unique non-overlapping European and African ancestry-specific susceptibility loci may be associated with increased POP risk.

Childhood obesity is a global health concern due to its potential to increase cardiometabolic risk across the life course. In the United States (US) the burden of childhood obesity is highest among Hispanic/Latinos, in particular children or adolescents of Mexican descent. Although the genetic epidemiology of childhood obesity has been studied previously, the potential for novel childhood obesity loci in Hispanic/Latinos and the generalizability of previously reported loci to Hispanic/Latino children and adolescents are still unknown. Thus we aimed to conduct a genome-wide association study of childhood obesity in 1,612 Hispanic/Latino children and adolescents (2-18 years) collected as part of one Mexican (n=794 Mexico City Study) and two US (n=362 Children’s Hospital of Philadelphia; n=456 Viva La Familia Study) studies, and to generalize 11 previously reported childhood obesity loci from European descent samples to our Hispanic/Latino samples. Obesity cases and controls were defined by BMI-for-age percentiles based on the Centers for Disease Control and Prevention smoothed and sex-specific growth curves from 2000, wherein cases had percentiles ≥95 th and controls had percentiles ≤85 th . Each study performed a genome-wide logistic regression analysis of single nucleotide polymorphism (SNPs) after adjusting for sex, population stratification and relatedness, as applicable. We combined study results for SNPs >10 minor allele counts and imputation quality ≥0.5 using fixed-effect inverse-variance weighted meta-analysis. A priori, we estimated that in our sample (n effective =1,498) we would have >80% power to detect common SNPs (>15% minor allele frequency) across the genome (p-8 ) that increase the odds of childhood obesity of 55% per risk allele. Generalizability at 11 known childhood obesity loci was defined as p-6 ), including a SNP that associated with an increased odds of childhood obesity of 54% per risk allele (73% frequent) at ARHGAP21, which is expressed in an enhancer region in brain, muscle and adipose tissues and has been previously implicated with trunk fat mass in Viva la Familia at another SNP (r 2 SEC16B and TMEM18 generalized to Hispanic/Latinos (p≤0.01), corresponding to a 27% and 40% increased odds of obesity per risk allele (22-88% frequency). These preliminary results suggest the presence of novel loci for childhood obesity and the generalizability of genetic loci discovered in samples of European descent to Hispanic/Latinos, albeit with stronger effect sizes. Future work will attempt to identify additional Hispanic/Latino obesity cases and controls to replicate the suggestive associations.

Summary 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.

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.

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 of3.2 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.

Summary What is already known about this subject Genome-Wide Association Studies have successfully identified numerous genetic loci that influence body mass index in European-descent middle-aged adults. Adolescence is a high-risk period for the development of adult obesity and severe obesity. Physical activity is one of the most promising behavioural candidates for preventing and reducing weight gain, particularly among youth. What this study adds An examination of the joint association between 41 of the well-established obesity susceptibility single-nucleotide polymorphisms with

In human populations, assortative mating is almost univer-sally positive, with similarities between partners for quantit-ative phenotypes 1-6, common disease risk 1,3,7-10, beha-vi-our 6,11, social factors 12-14 and personality 4,5,11. The causes and genetic consequences of assortative mating remain un-re-solved because partner similarity can arise from different mechanisms: Phenotypic assortment based on mate choice 15,16, partner interaction and convergence in phenotype over time 14,17, or social homogamy where individuals pair according to social or environmental background. Here, we present theory and an analytical approach to test for genetic evidence of assortative mating and find a correlation in genetic value among partners for a range of phenotypes. Across three independent samples of 24,662 spousal pairs in total, we infer a correlation at trait-associated loci between partners for height (0.200, 0.004 standard error, SE) that matched the phenotypic correlation (0.201, 0.004 SE), and a correlation at trait-associated loci for BMI (0.143, 0.007 SE) that was significantly lower than the phenotypic value (0.228, 0.004 SE). We extend our analysis to the UK Biobank study (7,780 pairs), finding evidence of a correlation at trait-associated loci for waist-to-hip ratio (0.101, 0.041 SE), systolic blood pressure (0.138, 0.064 SE) and educational attainment (0.654, 0.014 SE). Our results imply that mate choice, combined with widespread pleiotropy among traits, affects the genomic architecture of traits in humans.

Supplementary Figures. (DOCX 112Â kb)

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide1,2. Although 58 genomic regions have been associated with CAD thus far3-9, most of the heritability is unexplained9, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed metaanalysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 x 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p. Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with celltype- specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

Investigating genetic architecture of complex traits in ancestrally diverse populations is imperative to understand the etiology of disease. However, the current paucity of genetic research in people of African and Latin American ancestry, Hispanic and indigenous peoples in the United States is likely to exacerbate existing health disparities for many common diseases. The Population Architecture using Genomics and Epidemiology, Phase II (PAGE II), Study was initiated in 2013 by the National Human Genome Research Institute to expand our understanding of complex trait loci in ethnically diverse and well characterized study populations. To meet this goal, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially improve fine-mapping and functional discovery by increasing variant coverage across multiple ethnicities at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits. Studying the frequency distribution of clinically relevant mutations, putative risk alleles, and known functional variants across multiple populations will provide important insight into the genetic architecture of complex diseases and facilitate the discovery of novel, sometimes population-specific, disease associations. DNA samples from 51,650 self-identified African ancestry (17,328), Hispanic/Latino (22,379), Asian/Pacific Islander (8,640), and American Indian (653) and an additional 2,650 participants of either South Asian or European ancestry, and other reference panels have been genotyped on MEGA by PAGE II. MEGA was designed as a new resource for studying ancestrally diverse populations. Here, we describe the methodology for selecting trait-specific content for use in multi-ethnic populations and how enriching MEGA for this content may contribute to deeper biological understanding of the genetic etiology of complex disease.

In GWAS, “generalization” is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. Current practices for declaring generalizations rely on testing associations while controlling the Family Wise Error Rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. This approach does not guarantee control over the FWER or False Discovery Rate (FDR) of the generalization null hypotheses. It also fails to leverage the two-stage design to increase power for detecting generalized associations. We provide a formal statistical framework for quantifying the evidence of generalization that accounts for the (in)consistency between the directions of associations in the discovery and follow-up studies. We develop the directional generalization FWER (FWERg) and FDR (FDRg) controlling r-values, which are used to declare associations as generalized. This framework extends to generalization testing when applied to a published list of SNP-trait associations. Our methods control FWERg or FDRg under various SNP selection rules based on p-values in the discovery study. We find that it is often beneficial to use a more lenient p-value threshold than the genome-wide significance threshold. In a GWAS of Total Cholesterol (TC) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), when testing all SNPs with p-values< 5 × 10−8 (15 genomic regions) for generalization in a large GWAS of whites, we generalized SNPs from 15 regions. But when testing all SNPs with p-values< 6.6 × 10−5 (89 regions), we generalized SNPs from 27 regions.

Central adiposity is a leading risk factor for cardiovascular disease, and genetic factors contribute both to fat distribution, measured as waist-to-hip ratio adjusted for BMI (WHRa), and to differences in central adiposity prevalence. To date, 49 loci have been associated with WHRa, based on studies of common [minor allele frequency (MAF) ≥5%] single nucleotide variants (SNVs), primarily in European descent populations. Our aim was to identify low frequency (LFV: MAF RAPGEF3 [MAF=0.01, β (SE) = -0.09 (0.012), P=1.28E-13]. In addition, one novel RV reached CWS in men for UGGT2 [MAFACVR1C [MAFRAPGEF3 (P=1.18E-11) as significantly associated with WHRa in the all ancestry sex combined analyses after correction for multiple tests (PRAPGEF3 also shows a significant association (p=4.68E-12) in all ancestry, sex combined gene-based analysis of BMI. RAPGEF3 is expressed in subcutaneous and visceral adipose tissue, and has been implicated in insulin regulation. RAPGEF3 plays a role in the GLP1 pathway, which controls insulin secretion in response to blood glucose concentration. Our results highlight the importance of large-scale genomic studies for identifying LFV and RV influencing central fat distribution. Understanding these genetic effects may provide insights into the progression of central adiposity and highlight potential population-specific variants that increase susceptibility.

Introduction: African Americans have the highest prevalence of obesity in the U.S. Our prior work on HapMap imputed genome-wide association studies (GWAS) from the African Ancestry Anthropometry Genetics Consortium (AAAGC) revealed seven genome-wide significant loci for body mass index (BMI). Hypothesis: In this study, we extended to use genome-wide imputation to the cosmopolitan 1000 Genomes Phase 1 reference panel to examine individuals of African ancestry for association with BMI (N=53,493), waist-to-hip ratio adjusted for BMI (WHRadjBMI) (N=23,692) and height (N=53,362) in the discovery and replication stages. Methods: In each study, traits were stratified by gender and transformed to normality and adjusted for age, study specific covariates and principal components for single variant association test under an additive model. In the discovery stage, meta-analyses using fixed-effects inverse variance weighted method were performed to combine association results in all and sex-stratified samples. Variants with P Results: For BMI, we observed genome-wide significant associations (P Conclusions: We identified 12 novel loci associated with anthropometry traits in sex-combined and sex-stratified analyses of African ancestry populations and additional European populations. Our findings support that imputation to higher density reference panels such as 1000 Genomes improves the power to detect associations at low frequency variants, which is particularly useful for African ancestry populations with a low degree of linkage disequilibrium.

Liver attenuation (LA) [Hounsfield Units (HU)] by computed tomography is a validated quantitative measure that is inversely related to liver fat burden. We examined race and sex differences on the distribution of LA [one of the first stages of fatty liver disease (FLD)] and the predictors of these mean differences in European American (EA) and African American (AA) participants of the Family Heart Study.A total of 1242 (1064 EA, 178 AA) and 1477 (1150 EA, 327 AA) men and women, respectively, underwent computed tomography examination from which LA and abdominal adipose volume were measured. LA (adjusted for phantom and field center) was the dependent variable in linear mixed models (to control for family relatedness) that tested for mean differences by race and by sex. Independent explanatory variables included age, BMI, visceral adipose tissue volume (VAT), subcutaneous adipose tissue volume, alcohol consumption, triglyceride, HDL-cholesterol, and insulin resistance.Mean LA varied significantly by sex, [(men) 57.76±10.03 HU and (women) 60.03±10.91 HU, P=0.0002], but not by race. Higher LA was associated with older age, whereas higher values of VAT, triglycerides, and insulin resistance were associated with lower LA in men and women. In contrast, alcohol consumption and BMI were associated with lower LA only among men. In analyses stratified by race, LA was associated with alcohol consumption, VAT, and insulin resistance in both EA and AA and with age, BMI, and HDL-cholesterol in EA participants only.Our study findings confirm that there are important sex differences and race by sex interaction effects on the distribution of LA, the prevalence of FLD, and on the influence of metabolic risk factors on LA and FLD.

© The Author 2016. Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown.We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.

BackgroundRecent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.ObjectiveWe investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.DesignFourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.ResultsProcessed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.ConclusionThe association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Current evidence suggests a multifactorial etiology to pelvic organ prolapse (POP), including genetic predisposition. We conducted a genome-wide association study of POP in African American (AA) and Hispanic (HP) women from the Women's Health Initiative Hormone Therapy study. Cases were defined as any POP (grades 1-3) or moderate/severe POP (grades 2-3), while controls had grade 0 POP. We performed race-specific multiple logistic regression analyses between SNPs imputed to 1000 genomes in relation to POP (grade 0 vs 1-3; grade 0 vs 2-3) adjusting for age at diagnosis, body mass index, parity, and genetic ancestry. There were 1274 controls and 1427 cases of any POP and 317 cases of moderate/severe POP. Although none of the analyses reached genome-wide significance (p

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

Investigators often meta-analyze multiple genome-wide association studies (GWASs) to increase the power to detect associations of single nucleotide polymorphisms (SNPs) with a trait. Meta-analysis is also performed within a single cohort that is stratified by, e.g., sex or ancestry group. Having correlated individuals among the strata may complicate meta-analyses, limit power, and inflate Type 1 error. For example, in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), sources of correlation include genetic relatedness, shared household, and shared community. We propose a novel mixed-effect model for meta-analysis, "MetaCor," which accounts for correlation between stratum-specific effect estimates. Simulations show that MetaCor controls inflation better than alternatives such as ignoring the correlation between the strata or analyzing all strata together in a "pooled" GWAS, especially with different minor allele frequencies (MAFs) between strata. We illustrate the benefits of MetaCor on two GWASs in the HCHS/SOL. Analysis of dental caries (tooth decay) stratified by ancestry group detected a genome-wide significant SNP (rs7791001, P-value = 3.66×10-8, compared to 4.67×10-7 in pooled), with different MAFs between strata. Stratified analysis of body mass index (BMI) by ancestry group and sex reduced overall inflation from λGC=1.050 (pooled) to λGC=1.028 (MetaCor). Furthermore, even after removing close relatives to obtain nearly uncorrelated strata, a naive stratified analysis resulted in λGC=1.058 compared to λGC=1.027 for MetaCor.

Glycated hemoglobin (HbA1c) is used to classify glycaemia and type 2 diabetes (T2D). Body mass index (BMI) is a predictor of HbA1c levels and T2D. We tested 43 established BMI and obesity loci for association with HbA1c in a nationally representative multiethnic sample of young adults from the National Longitudinal Study of Adolescent to Adult Health [Add Health: age 24-34 years; n = 5641 European Americans (EA); 1740 African Americans (AA); 1444 Hispanic Americans (HA)] without T2D, using two levels of covariate adjustment (Model 1: age, sex, smoking, and geographic region; Model 2: Model 1 covariates plus BMI). Bonferroni adjustment was made for 43 SNPs and we considered P0.0011 statistically significant. Means (SD) for HbA1c were 5.4% (0.3) in EA, 5.7% (0.4) in AA, and 5.5% (0.3) in HA. We observed significant evidence for association with HbA1c for two variants near SH2B1 in EA (rs4788102, P = 2.2 × 10(-4) ; rs7359397, P = 9.8 × 10(-4) ) for Model 1. Both results were attenuated after adjustment for BMI (rs4788102, P = 1.7 × 10(-3) ; rs7359397, P = 4.6 × 10(-3) ). No variant reached Bonferroni-corrected significance in AA or HA. These results suggest that SH2B1 polymorphisms are associated with HbA1c, largely independent of BMI, in EA young adults.

INTRODUCTION: Genome wide association studies (GWAS) have identified over 150 loci associated with lipids traits. The majority of these GWAS were performed in European Americans (EA); no large-scale studies exist for Hispanic descent populations. Additionally, in many cases, the genetic architecture of these trait-influencing loci remains largely unknown. To address these gaps in knowledge, we performed one of the most ethnically diverse fine-mapping genetic studies on HDL-C, LDL-C, and triglycerides (TG) to-date. HYPOTHESIS: Here we aimed to identify variants with the strongest association at each locus, detect population-specific signals, and refine previously identified EA GWAS loci. METHODS: We used Metabochip data from African American (AA, ~21,000), Hispanic American (HA, ~20,000), Asian (AS, ~2,000), and Native American (NA, ~550) participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study. We applied multiple linear regression models and assumed an additive mode of inheritance to test for association between genotypes and HDL-C, LDL-C, or log-transformed TG levels; lipid levels were corrected for lipid-lowering medication use. Model covariates included age, sex, and principal components of ancestry. We first conducted a meta-analysis within each ethnic group separately and then performed a combined trans-ethnic fixed effects meta-analysis. Significance was defined as p < 1 x 10 -6 ; equivalent to 0.05/ the mean number of variants at each Metabochip lipid locus. RESULTS: For HDL-C, 19 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, APOB, LIPC, STARD3, LIPG, and APOC1, have not been reported in EA. We identified a signal unique to HA at APOA5. In addition, we refined the set of candidate functional variants at PPP1R3B, LPL, and PLTP. For LDL-C, 16 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, PCSK9, APOB, APOA5, CLIP2, and APOC1, have not been reported in EA. We identified a signal unique to HA at SLC22A1. In addition, we refined the set of candidate functional variants at TIMD4 and LDLR. For TG, 15 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 3 of these loci, APOB, APOA5, and LIPC, have not been reported in EA. In addition, we refined the set of candidate functional variants at ANGPTL3, MLXIPL, PPP1R3B, and LPL. CONCLUSIONS: By taking advantage of the genetic architecture of ethnically diverse populations, we identified novel lipid-influencing variants in HA and refined the set of candidate functional variants at GWAS lipid loci. Anticipated conditional analyses will provide further insight into secondary and ethnic-specific signals. Our results can guide the creation of more informed risk models, which can then be used for targeted prevention efforts, especially for underrepresented populations.

Fertility rates have declined in many developing countries and this has implications for health and development of subsequent generations. Guatemala has the highest fertility rates in Central America. Reproductive histories were obtained by interview in 2002–04, in a cohort of 779 women and 647 men who had participated as young children in a nutrition supplementation trial in Guatemala conducted between 1969 and 1977. Most women (77%) and men (79%) are currently married. Among the 700 women and 524 men reporting at least one birth, mean age at first birth was 20.7 ± 3.8 years and 23.1 ± 3.9 years respectively. Knowledge (> 80%) and use (∼70%) of modern contraceptive methods is fairly high; knowledge increases with parental socioeconomic status (SES) as measured in 1975. Younger respondents have experienced fewer pregnancies and live births compared with older respondents; age-specific fertility rates between 20 and 24 years were 294, 249, 236, and 261 births per 1,000 women, respectively, for women born from 1962–65, 1966–69, 1969–73, and 1974–77. Women in the top tertile of parental SES have had significantly fewer pregnancies (3.3) compared with those in the middle (3.7) and lower (3.8) tertiles. Migrants to Guatemala City reported greater knowledge of contraceptive methods, fewer pregnancies and living children, higher age at first birth, and more pregnancy and newborn complications as compared with cohort members who remained in the original villages (p < .05 for each comparison). Fertility rates, especially between 20 and 24 years, have declined over time. Differences in reproductive behaviors by parental SES and current residence suggest the role of social transitions in determining family formation in Guatemala.

Central adiposity, assessed by waist-to-hip ratio (WHR), has been associated with increased risk for cardiovascular disease. Both genetic and lifestyle factors, including physical inactivity, have been independently associated with WHR adjusted for BMI (WHRadjBMI). Physical activity (PA) is an important component of interventions for reducing or preventing central adiposity and has been shown to attenuate genetic influences on adiposity. However, the influence of PA on loci associated with central fat, independent of total body fat, is unknown. Our objective was to identify genetic variants whose effects on WHRadjBMI are modified by PA. To this end, we performed a meta-analysis of 36 genome-wide association studies, including 94,779 individuals of European ancestry. PA was standardized within each study (physically active and inactive) with the lowest quintile being defined as inactive. WHR was adjusted for BMI, age, and age 2 in men and women separately. Each study tested the SNP x PA interaction alone, and also tested the joint effects of both the interaction and SNP main effect using a two degree of freedom (2df) test. We pooled the results from individual studies using fixed-effects inverse variance weighted meta-analysis in men and women combined and separately. The 2df joint test reached genome-wide significance (p-8 ) for 23 loci, which included 11 novel loci for WHRadjBMI. Of these 11 loci, 7 were identified in women only, and one in men only. For each of the 23 loci, the association of the joint test was primarily driven by the SNP main effect on WHRadjBMI, rather than its interaction with PA. When we examined the interaction effects of the 23 loci, separately from main effect, the interaction reached nominal significance for 11 loci (5 of these were novel): e.g. established loci in/near LYPLAL1 (p=1.0e -7 ), VEGFA (p=3.8e -4 ), TBX15 (p=2.1e -5 in women), and RSPO3 (p=5.5e -3 ), and novel (in women only), in/near TMEM131 (p =3.2e -4 ), FAM186A (p=4.1e -4 ), and FLJ45974 (p=1.9e -3 ). In each case, the effect of the WHRadjBMI-increasing allele was smaller in the active group than in the inactive group; e.g. for the SNP near LYPLAL1 , in the active versus inactive: β[SE] = 0.024(0.036) vs 0.215(0.084), respectively. For the interaction term alone, no loci reached genome-wide significance, but a search at P-6 revealed 3 additional novel loci; 2 in men and women combined (in/near MYO18B and COX11P ) and 1 in men only (in SNW1 ). Our findings suggest that joint tests of main and interaction effects help elucidate the genetic basis of abdominal obesity and that genetic effects are larger in physically inactive compared to active individuals. To follow-up our initial findings, we are currently collecting data from 25 additional studies with genome-wide or Metabochip data.

The cohort design allows investigators to explore the genetic basis of a variety of diseases and traits in a single study while avoiding major weaknesses of the case-control design. Most cohort studies employ multistage cluster sampling with unequal probabilities to conveniently select participants with desired characteristics, and participants from different clusters might be genetically related. Analysis that ignores the complex sampling design can yield biased estimation of the genetic association and inflation of the type I error. Herein, we develop weighted estimators that reflect unequal selection probabilities and differential nonresponse rates, and we derive variance estimators that properly account for the sampling design and the potential relatedness of participants in different sampling units. We compare, both analytically and numerically, the performance of the proposed weighted estimators with unweighted estimators that disregard the sampling design. We demonstrate the usefulness of the proposed methods through analysis of MetaboChip data in the Hispanic Community Health Study/Study of Latinos, which is the largest health study of the Hispanic/Latino population in the United States aimed at identifying risk factors for various diseases and determining the role of genes and environment in the occurrence of diseases. We provide guidelines on the use of weighted and unweighted estimators, as well as the relevant software.

Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10⁻⁸) near FTO (P = 3.72 × 10⁻²³), TMEM18 (P = 3.24 × 10⁻¹⁷), MC4R (P = 4.41 × 10⁻¹⁷), TNNI3K (P = 4.32 × 10⁻¹¹), SEC16B (P = 6.24 × 10⁻⁹), GNPDA2 (P = 1.11 × 10⁻⁸) and POMC (P = 4.94 × 10⁻⁸) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10⁻⁵ after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.

Genome wide association studies (GWAS) have identified numerous loci associated with BMI, a major risk factor for cardiometabolic disease. Yet, genetic associations with trajectory of weight change have been less studied, particularly in highly vulnerable populations such as racially diverse older women. We conducted a GWAS analysis on longitudinal weight among African American participants in the Women’s Health Initiative SNP Health Association Resource (WHI SHARe) study to better understand the genetic architecture of weight change during the post-menopausal period of the life course. Between 1993 and 2005, we collected longitudinal data on weight in 6,852 African American women between the ages of 50 and 79 at baseline. The average weight at first measure was 81 kg (16) with a range of 46 to 129 kg. The average change in weight per year was 0.09 kg (0.36) ranging from -3.3 to 5.7 kg. The average follow-up duration was 5.3 years (range: 1 to 11). We used time-varying, repeated weight measures across the trial period to perform a growth curve analysis for weight change. Using a mixed model with an unstructured covariance matrix, weight was regressed on year since randomization for both fixed and random effects to derive each individual’s weight change slope. Individuals were genotyped using Affymetrix 6.0 array and ~ 3.2 million SNPs were imputed using MACH (v1.0.16) and a 50(CEU):50(YRI) HapMap 2 reference panel. We performed association analyses with weight change residuals adjusted for clinical covariates and principal components, using an additive genetic model. While no associations reached genome wide significance (p

Genome-wide association (GWA) studies have identi[[Unable to Display Character: fi]]ed nearly 50 common variants for obesity, many of which influence body mass index (BMI), a common proxy for obesity assessed in large epidemiological studies. The associations of these variants with change in BMI across the life course are not well understood, but are of particular interest during the transition from adolescence to young adulthood, a high risk period for weight gain. The current study assessed the association of 41 established obesity SNPs with change in BMI during the period between adolescence and young adulthood in an ethnically diverse, nationally representative cohort, the National Longitudinal Study of Adolescent Health, followed for 13 years. Race/ethnicity-stratified linear mixed models accounted for sampling design, family relatedness, and repeated measures of BMI. Models included a SNP-by-year interaction term and adjusted for sex, age at baseline, current smoking, and geographic region. Analyses included 6383 European American (EA), 2252 African American (AA) and 1700 Hispanic American (HA) participants with measurements from 1996 (ages 12-21 y) to 2008 (ages 24-34 y), with an average of 2.6 observations per individual. For analyses in AA we excluded SNPs (n=14) that failed to capture signal of functional variant in a recent African American population genome-wide association study (Monda et al 2012). Average BMI gain over the 13-year period was 4.9 (SD=5.0) kg/m 2 , with higher increases in AA 5.8 (SD=5.7) kg/m 2 and HA 5.5 (SD=5.6) kg/m 2 . Model results for the 41 SNPs in EA and HA and 27 SNPs in AA suggest that SNP by year interactions show nominal significance (pQPCTL ) and none in AA or HA. Each effect allele for rs2287019 contributed an increase of 0.030(SE=0.009) kg/m 2 per year to BMI in EA. These findings suggest that the locus near QPCTL and possibly other obesity loci play a role in the trajectory of BMI across the period from adolescence to young adulthood, a period with high risk for subsequent adult obesity. These findings may help inform the biological processes that influence weight gain at this vulnerable period of the life cycle and may provide information that is useful for the design of effective interventions to prevent weight gain.

Obesity is a global health concern. Recent studies suggest there may be shared genetic predispositions to obesity phenotypes across diverse racial and ethnic groups, yet the identification of adiposity-related genetic variants among Hispanics, now the largest minority group in the United States (U.S.), remains largely unknown. We interrogated an a priori list of 58 (41 overall body mass and 17 central adiposity) index single nucleotide polymorphisms (SNPs) previously studied in samples of European descent (ED) among 3,587 U.S. Hispanic women in the Women's Health Initiative-SNP Health Association Resource (WHI-SHARe). Body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) were measured using standardized protocols. Inverse normal BMI, WC, and WHR models were adjusted for age, smoking status, study center, and genetic ancestry using principal components. Additionally WC and WHR were adjusted for BMI. Genotyping was performed using the Affymetrix 6.0 array. In the absence of the previously described SNP, the closest available SNP was selected as a proxy (r2≥0.3 in CEU). No SNPs reached genome-wide significance in this analysis likely due to limited power. Eight BMI/weight loci (TMEM18, ETV5, SLC39A8, NUDT3/HMGA1, FAIM2, FTO, MC4R, KCTD15) and two WC/WHR loci (VEGFA, ITPR2-SSPN) were nominally significant (p

In the past five years genome-wide association studies (GWAS) have identified common genetic loci associated with body mass index (BMI) mainly in European middle-aged adult populations. The influence of these loci in adolescence, a period of risk for weight gain, and whether there are different associations across adolescent groups at highest risk (e.g., ethnic minority populations), remains largely unknown. We examined whether obesity susceptibility loci identified from previous GWAS in adults were associated with BMI in an ethnically diverse adolescent cohort. Using 8918 participants from the National Longitudinal Study of Adolescent Health, or Add Health (aged 12-21 years in 1996, 52.6 % female), we assessed the association of 43 SNPs, selected based on statistical significance in previous GWAS, with BMI across four ethnic US subpopulations (5,296 European Americans, EA, 1,815 African Americans, AfA, 1,356 Hispanic Americans, HA, and 451 Asian Americans, AsA). Buccal cells from participants were extracted and genotyped using TaqMan (sample call rate: 97.5%, SNP call rate: 100%). Inverse normal transformed BMI residuals, adjusted for gender and age, were used in ethnicity-stratified models with SNPs in PLINK, assuming an additive model. An inverse-variance-weighted meta-analysis was used to combine results across the 4 ethnic groups. Average BMI across all ethnic groups was 23.6±5.2 kg/m2, ranging from 22.6±5.2 kg/m2 in AsA to 24.3±5.8 kg/m2 in AfA. The effect estimates for all 43 SNPs were directionally consistent across ethnicity with previously published results. Of the 43 SNPs, 20 were associated with BMI at pTMEM18 (rs6548238, meta-analysis p-value p=1.32E-10), had one of the largest differences in effect size compared to middle-aged European adults (Willer et al 2009) with a per allele increase of 0.70±0.11 kg/m2 in this sample versus 0.26±0.07 kg/m2 in adults (beta[SE] difference = 0.44[0.08]; p=1.4E-08). Variants associated with BMI in adults were also associated with BMI in adolescents, with some comparatively larger effects during this vulnerable period. R01HD057194

This study investigated whether nonalcoholic fatty liver disease (NAFLD) predicts prevalent coronary heart disease (CHD).Epidemiologic studies have used various definitions for NAFLD. Here, we considered both liver fat burden measured by CT (FL) and the non-specific measure of hepatic inflammation -alanine aminotransferase (ALT). The association of FL and ALT with CHD (self report of coronary bypass, myocardial infarction, or percutaneous transluminal coronary angioplasty) was investigated in 2756 European-American participants of the Family Heart Study.FL (p = 0.0084) and ALT (≥40 U/L, p = 0.014) were each individually associated with prevalent CHD. However, when accounting for traditional metabolic risk factors in a multivariate model FL had no predictive value for CHD in either men or women; whereas ALT was a significant predictor of CHD in men, and the association strengthened among non-diabetic men. In non-diabetic women, neither FL nor ALT was associated with CHD.ALT (≥40 U/L) was a predictor of prevalent CHD in men but not in women, while CT measured FL was not significant in either sex. The failure to account for traditional risk factors, heterogeneity by sex, and varying definitions of NAFLD may account for some of the conflicting evidence in the literature regarding the association between NAFLD and coronary disease.

Objective: The contribution of genetic variants to body mass index (BMI) during adolescence across multiethnic samples is largely unknown. We selected genetic loci associated with BMI or obesity in European-descent samples and examined them in a multiethnic adolescent sample. Design and Sample: In 5103 European American (EA), 1748 African American (AfA), 1304 Hispanic American (HA) and 439 Asian American (AsA) participants of the National Longitudinal Study of Adolescent Health (Add Health; ages 12–21 years, 47.5% male), we assessed the association between 41 established obesity-related single-nucleotide polymorphisms (SNPs) with BMI using additive genetic models, stratified by race/ethnicity, and in a pooled meta-analysis sample. We also compared the magnitude of effect for BMI–SNP associations in EA and AfA adolescents to comparable effect estimates from 11 861 EA and AfA adults in the Atherosclerosis Risk in Communities study (ages 45–64 years, 43.2% male). Results: Thirty-five of 41 BMI–SNP associations were directionally consistent with published studies in European populations, 18 achieved nominal significance (P

Introduction—Relatively few studies have interrogated gene-by sedentary behavior interactions on obesity phenotypes. Increasing sedentary behaviors (e.g., screen time: television, video, and computer use), have paralleled declines in physical activity in the United States and may play an important role in weight gain. Our purpose in this paper is to examine the possible influence of screen time during adolescence on the additive genetic variance of body mass change during a critical point in the lifecycle, the transition from adolescence to young adulthood. Methods—In the National Longitudinal Study of Adolescent Health, siblings and twin pairs (16.5±1.7 y) were followed into young adulthood (22.4±1.8 y). Self-reported screen time (hrs/wk) and body mass index (BMI kg/m 2 ), calculated from measured height and weight at adolescence and at young adulthood, was available for 3795 participants. We employed a variance component approach to estimate the interaction between genotype and screen time for body mass change. 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 change was significantly larger in individuals with low (σG=27.59±1.58) compared to high (σG=18.76 ± 2.59) levels of screen time (P

Better childhood nutrition is associated with earlier physical maturation during adolescence and increased schooling attainment. However, as earlier onset of puberty and increased schooling can have opposing effects on fertility, the net effect of improvements in childhood nutrition on a woman’s fertility are uncertain. Using path analysis, we estimate the strength of the pathways between childhood growth and subsequent fertility outcomes in Guatemalan women studied prospectively since birth. Height for age z score at 24 months was positively related to body mass index (BMI kg/m2) and height (cm) in adolescence and to schooling attainment. BMI was negatively associated (−0.23 ± 0.09 years per kg/m2; p < . 05) and schooling was positively associated (0.38 ± 0.06 years per grade; p < .001) with age at first birth. Total associations with the number of children born were positive from BMI (0.07 ± 0.02 per kg/m2; p < .05) and negative from schooling (−0.18 ± 0.02 per grade; p < .01). Height was not related to age at first birth or the number of children born. Taken together, childhood nutrition, as reflected by height at 2 years, was positively associated with delayed age at first birth and fewer children born. If schooling is available for girls, increased growth during childhood will most likely result in a net decrease infertility.

Background Food insecurity and obesity have potential health consequences for migrant and seasonal farm workers (MSFW). Methods Thirty-six Latino MSFW working in eastern North Carolina whose children attended Migrant Head Start completed interviews, focus groups and home visits. Content analysis, nutrient analysis, and non-parametric statistical analysis produced results. Results MSFW (63.8%) families were food insecure; of those, 34.7% experienced hunger. 32% of pre-school children were food insecure. Food secure families spent more money on food. Obesity was prevalent in adults and children but the relationship to food insecurity remains unclear. Strategies to reduce risk of foods insecurity were employed by MSFW, but employer and community assistance is needed to reduce their risk. Conclusions Food insecurity is rooted in the cultural lifestyle of farmwork, poverty, and dependency. MSFW obesity and food insecurity require further study to determine the relationship with migration and working conditions. Networking and social support are important for MSFW families to improve food security. Policies and community/workplace interventions could reduce risk of food insecurity and improve the health of workers. Am. J. Ind. Med. 53:443–462, 2010. © 2010 Wiley-Liss, Inc.

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.