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1.
Hum Mol Genet ; 2019 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-31504550

RESUMO

Although hundreds of GWAS-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity, and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of thirty studies consisting of up to 13,005 cases (≥95th percentile of BMI achieved 2-18 years old) and 15,599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1,888 cases and 4,689 controls from seven cohorts of European and North/South American ancestry. In addition to observing eighteen previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene: METTL15). The variant was nominally associated in only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than ten SNPs (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

2.
Nature ; 570(7762): 514-518, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31217584

RESUMO

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.

3.
Curr Diab Rep ; 18(12): 145, 2018 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-30456705

RESUMO

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 USA, 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 < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine. RECENT FINDINGS: GWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all.

4.
BMC Obes ; 5: 26, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30305909

RESUMO

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.

5.
BMC Proc ; 12(Suppl 9): 22, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30275878

RESUMO

Even though there has been great success in identifying lipid-associated single-nucleotide polymorphisms (SNPs), the mechanisms through which the SNPs act on each trait are poorly understood. The emergence of large, complex biological data sets in well-characterized cohort studies offers an opportunity to investigate the genetic effects on trait variability as a way of informing the causal genes and biochemical pathways that are involved in lipoprotein metabolism. However, methods for simultaneously analyzing multiple omics, environmental exposures, and longitudinally measured, correlated phenotypes are lacking. The purpose of our study was to demonstrate the utility of the structural equation modeling (SEM) approach to inform our understanding of the pathways by which genetic variants lead to disease risk. With the SEM method, we examine multiple pathways directly and indirectly through previously identified triglyceride (TG)-associated SNPs, methylation, and high-density lipoprotein (HDL), including sex, age, and smoking behavior, while adding in biologically plausible direct and indirect pathways. We observed significant SNP effects (P < 0.05 and directionally consistent) on TGs at visit 4 (TG4) for five loci, including rs645040 (DOCK7), rs964184 (ZPR1/ZNF259), rs4765127 (ZNF664), rs1121980 (FTO), and rs10401969 (SUGP1). Across these loci, we identify three with strong evidence of an indirect genetic effect on TG4 through HDL, one with evidence of pleiotropic effect on HDL and TG4, and one variant that acts on TG4 indirectly through a nearby methylation site. Such information can be used to prioritize candidate genes in regions of interest, inform mechanisms of action of methylation effects, and highlight possible genes with pleiotropic effects.

6.
BMC Genet ; 19(Suppl 1): 69, 2018 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-30255772

RESUMO

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.

7.
PLoS One ; 13(7): e0200486, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30044860

RESUMO

Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-valuesbinomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.

8.
Artigo em Inglês | MEDLINE | ID: mdl-29943348

RESUMO

Acculturation markers, such as language use, have been associated with Latino depression. Language use may change between generations; however, few studies have collected intergenerational data to assess how language differences between generations impact depression. Using the Niños Lifestyle and Diabetes Study (2013-2014), we assessed how changes in Spanish language use across two generations of Mexican-origin participants in Sacramento, California, influenced offspring depressive symptoms (N = 603). High depressive symptoms were defined as CESD-10 scores ≥ 10. We used log-binomial and linear-binomial models to calculate prevalence ratios and differences, respectively, for depressive symptoms by language use, adjusting for identified confounders and within-family clustering. Decreased Spanish use and stable-equal English/Spanish use across generations protected against depressive symptoms, compared to stable-high Spanish use. Stable-low Spanish use was not associated with fewer depressive symptoms compared to stable-high Spanish use. Exposure to multiple languages cross-generationally may improve resource access and social networks that protect against depression.

9.
Biodemography Soc Biol ; 64(1): 30-42, 2018 Jan-Mar.
Artigo em Inglês | MEDLINE | ID: mdl-29741413

RESUMO

Foreign-born Hispanics have better cardiometabolic health upon arrival in the US than their US-born counterparts, yet this advantage diminishes as duration of residence in the US increases. Underlying mechanisms explaining this paradox have been understudied. Using data from the Sacramento Area Latino Study on Aging (SALSA), this study examined immigration history (immigrant generation and duration of US residence) in relation to biomarkers of inflammation (interleukin-6 (IL-6), soluble forms of type 1 and 2 receptors of tumor necrosis factor-alpha (sTNF-R1 and sTNF-R2), C-reactive protein (CRP), leptin, adiponectin) in a sample of 1,290 predominantly Mexican-origin immigrants. Second and ≥3rd generation immigrants had higher IL-6 and leptin levels than 1st generation immigrants living in the US for less than 15 years (2nd generation percent difference = 45.9; 95% CI: 24.7, 70.7 and 3rd generation percent difference = 41.8; 95% CI: 17.7, 70.4). CRP and sTNF-R1 levels were higher among ≥3rd generation immigrants than 1st generation immigrants with less than 15 years of US residency. Worse inflammatory profiles were observed among Mexican-origin immigrants with longer US immigration histories, independent of health, and behavioral factors. Additional research is warranted to understand the factors that shape trajectories of biological risk across generations of Hispanics.

11.
Diabetologia ; 60(12): 2384-2398, 2017 12.
Artigo em Inglês | MEDLINE | ID: mdl-28905132

RESUMO

AIMS/HYPOTHESIS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS/INTERPRETATION: 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. DATA AVAILABILITY: 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.


Assuntos
Glicemia/metabolismo , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Mellitus Tipo 2/genética , Grupo com Ancestrais do Continente Europeu , Jejum/sangue , Feminino , Estudo de Associação Genômica Ampla , Humanos , Insulina/sangue , Masculino , Polimorfismo de Nucleotídeo Único/genética
12.
Epidemiology ; 28(6): 847-853, 2017 11.
Artigo em Inglês | MEDLINE | ID: mdl-28767517

RESUMO

BACKGROUND: Previous US population-based studies have found that body weight may be underestimated when self-reported. However, this research may not apply to all US Hispanics/Latinos, many of whom are immigrants with distinct cultural orientations to ideal body size. We assessed the data quality and accuracy of self-reported weight in a diverse, community-based, US sample of primarily foreign-born Hispanic/Latino adults. METHODS: Using baseline data (2008-2011) from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we described the difference between contemporaneous self-reported and measured current body weight (n = 16,119) and used multivariate adjusted models to establish whether the observed trends in misreporting in potential predictors of inaccuracy persisted after adjustment for other predictors. Last, we described the weighted percentage agreement in body mass classification using either self-reported or measured weight (n = 16,110). RESULTS: Self-reported weight was well correlated with (r = 0.95) and on average 0.23 kg greater than measured weight. The range of this misreporting was large and several factors were associated with misreporting: age group, gender, body mass categories, nativity, study site by background, unit of self-report (kg or lb), and end-digit preference. The percentage agreement of body mass classification using self-reported versus measured weight was 86% and varied across prevalent health conditions. CONCLUSIONS: The direction of misreporting in self-reported weight, and thus the anticipated bias in obesity prevalence estimates based on self-reported weights, may differ in US Hispanic/Latinos from that found in prior studies. Future investigations using self-reported body weight in US Hispanic/Latinos should consider this information for bias analyses.See video abstract at, http://links.lww.com/EDE/B276.


Assuntos
Peso Corporal , Confiabilidade dos Dados , Emigrantes e Imigrantes/estatística & dados numéricos , Hispano-Americanos , Autorrelato/normas , Adolescente , Adulto , Fatores Etários , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Obesidade/epidemiologia , Prevalência , Fatores Sexuais , Estados Unidos/epidemiologia , Adulto Jovem
13.
Hum Genet ; 136(6): 771-800, 2017 06.
Artigo em Inglês | MEDLINE | ID: mdl-28391526

RESUMO

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m2) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.


Assuntos
Índice de Massa Corporal , Grupos Étnicos/genética , Genética Populacional , Humanos , Obesidade/epidemiologia , Obesidade/genética
14.
BMC Proc ; 10(Suppl 7): 321-327, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27980656

RESUMO

BACKGROUND: There is great interindividual variation in systolic blood pressure (SBP) as a result of the influences of several factors, including sex, ancestry, smoking status, medication use, and, especially, age. The majority of genetic studies have examined SBP measured cross-sectionally; however, SBP changes over time, and not necessarily in a linear fashion. Therefore, this study conducted a genome-wide association (GWA) study of SBP change trajectories using data available through the Genetic Analysis Workshop 19 (GAW19) of 959 individuals from 20 extended Mexican American families from the San Antonio Family Studies with up to 4 measures of SBP. We performed structural equation modeling (SEM) while taking into account potential genetic effects to identify how, if at all, to include covariates in estimating the SBP change trajectories using a mixture model based latent class growth modeling (LCGM) approach for use in the GWA analyses. RESULTS: The semiparametric LCGM approach identified 5 trajectory classes that captured SBP changes across age. Each LCGM identified trajectory group was ranked based on the average number of cumulative years as hypertensive. Using a pairwise comparison of these classes the heritability estimates range from 12 to 94 % (SE = 17 to 40 %). CONCLUSION: These identified trajectories are significantly heritable, and we identified a total of 8 promising loci that influence one's trajectory in SBP change across age. Our results demonstrate the potential utility of capitalizing on extant genetic data and longitudinal SBP assessments available through GAW19 to explore novel analytical methods with promising results.

15.
BMC Proc ; 10(Suppl 7): 371-377, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27980664

RESUMO

BACKGROUND: Nearly half of adults in the United States who are diagnosed with hypertension use blood-pressure-lowering medications. Yet there is a large interindividual variability in the response to these medications. Two complementary gene-environment interaction methods have been published and incorporated into publicly available software packages to examine interaction effects, including whether genetic variants modify the association between medication use and blood pressure. The first approach uses a gene-environment interaction term to measure the change in outcome when both the genetic marker and medication are present (the "interaction model"). The second approach tests for effect-size differences between strata of an environmental exposure (the "med-diff" approach). However, no studies have quantitatively compared how these methods perform with respect to 1 or 2 degree of freedom (DF) tests or in family-based data sets. We evaluated these 2 approaches using simulated genotype-medication response interactions at 3 single nucleotide polymorphisms (SNPs) across a range of minor allele frequencies (MAFs 0.1-5.4 %) using the Genetic Analysis Workshop 19 family sample. RESULTS: The estimated interaction effect sizes were on average larger in the interaction model approach compared to the med-diff approach. The true positive proportion was higher for the med-diff approach for SNPs less than 1 % MAF, but higher for the interaction model when common variants were evaluated (MAF >5 %). The interaction model produced lower false-positive proportions than expected (5 %) across a range of MAFs for both the 1DF and 2DF tests. In contrast, the med-diff approach produced higher but stable false-positive proportions around 5 % across MAFs for both tests. CONCLUSIONS: Although the 1DF tests both performed similarly for common variants, the interaction model estimated true interaction effects with less bias and higher true positive proportions than the med-diff approach. However, if rare variation (MAF <5 %) is of interest, our findings suggest that when convergence is achieved, the med-diff approach may estimate true interaction effects more conservatively and with less variability.

16.
Am J Hum Genet ; 98(1): 165-84, 2016 Jan 07.
Artigo em Inglês | MEDLINE | ID: mdl-26748518

RESUMO

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.


Assuntos
Variação Genética , Hispano-Americanos/genética , Estudo de Associação Genômica Ampla , Humanos , Estados Unidos
17.
Am J Hum Genet ; 95(6): 675-88, 2014 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-25480034

RESUMO

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.


Assuntos
Estudos de Associação Genética/métodos , Inquéritos Epidemiológicos , Hispano-Americanos/genética , Modelos Estatísticos , Adolescente , Adulto , Idoso , Estudos de Coortes , Simulação por Computador , Feminino , Genótipo , Inquéritos Epidemiológicos/métodos , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Projetos de Pesquisa , Amostragem , Estados Unidos , Adulto Jovem
18.
Rehabil Res Pract ; 2014: 873872, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24876969

RESUMO

Purpose. The adult myopathy assessment tool (AMAT) is a performance-based battery comprised of functional and endurance subscales that can be completed in approximately 30 minutes without the use of specialized equipment. The purpose of this study was to determine the construct validity and internal consistency of the AMAT with a sample of adults with spinal and bulbar muscular atrophy (SBMA). Methods. AMAT validity was assessed in 56-male participants with genetically confirmed SBMA (mean age, 53 ± 10 years). The participants completed the AMAT and assessments for disease status, strength, and functional status. Results. Lower AMAT scores were associated with longer disease duration (r = -0.29; P < 0.03) and lower serum androgen levels (r = 0.49-0.59; P < 0.001). The AMAT was significantly correlated with strength and functional status (r = 0.82-0.88; P < 0.001). The domains of the AMAT exhibited good internal consistency (Cronbach's α = 0.77-0.89; P < 0.001). Conclusions. The AMAT is a standardized, performance-based tool that may be used to assess functional limitations and muscle endurance. The AMAT has good internal consistency, and the construct validity of the AMAT is supported by its significant associations with hormonal, strength, and functional characteristics of adults with SBMA. This trial is registered with Clinicaltrials.gov identifier NCT00303446.

19.
Am J Hum Genet ; 93(4): 661-71, 2013 Oct 03.
Artigo em Inglês | MEDLINE | ID: mdl-24094743

RESUMO

Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.


Assuntos
Afro-Americanos/genética , Índice de Massa Corporal , Genoma Humano , Estudo de Associação Genômica Ampla/métodos , Obesidade/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Loci Gênicos , Predisposição Genética para Doença , Genótipo , Humanos , Desequilíbrio de Ligação , Masculino , Pessoa de Meia-Idade , Obesidade/etnologia , Polimorfismo de Nucleotídeo Único , Adulto Jovem
20.
Obesity (Silver Spring) ; 21(4): 835-46, 2013 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-23712987

RESUMO

OBJECTIVE: Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups. DESIGN AND METHODS: As part of the "Population Architecture using Genomics and Epidemiology (PAGE)" Consortium, we investigated the association between 13 GWAS-identified single-nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated ß coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined "replicating SNPs" (in European Americans) and "generalizing SNPs" (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI. RESULTS: By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians. CONCLUSION: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations.


Assuntos
Índice de Massa Corporal , Grupos Étnicos/genética , Metagenômica/métodos , Obesidade/epidemiologia , Obesidade/genética , Alelos , Frequência do Gene , Loci Gênicos , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Desequilíbrio de Ligação , Fenótipo , Polimorfismo de Nucleotídeo Único , Fatores de Risco
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