Genetic variants in intron 1 of the fat mass– and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646–kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10−6) had not been highlighted in previous studies. While rs56137030was correlated at r2>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.

Author Summary

Genetic variants within the fat mass– and obesity-associated (FTO) gene are associated with increased risk of obesity. To better understand which specific genetic variant(s) in this genetic region is associated with obesity risk, we attempt to genotype or impute all known genetic variants in the region and test for association with body mass index as a measurement of obesity in over 20,000 African Americans. We identified 29 potential candidate variants, of which one variant (rs1421085) is a particularly interesting candidate for future functional follow-up studies. Our example shows the powerful approach of studying a large African American population, substantially reducing the number of possible functional variants compared with European descent populations.

Habitual levels of dietary sodium and potassium are correlated with age-related increases in blood pressure (BP) and likely play a role in this phenomenon. Although extensive published evidence exists from randomized trials, relatively few large-scale community surveys with multiple 24-hour urine collections have been reported. We obtained three 24-hour samples on 2,704 individuals from Nigeria, Jamaica and the US to evaluate patterns of intake and within-person relationships to blood pressure. The average (±s.d.) age and weight of participants across all three sites were 39.9±8.6 years and 76.1±21.2 kg, respectively, and 55% of the total participants were females. Sodium excretion increased across the East-West gradient (e.g., 123.9±54.6, 134.1±48.8, 176.6±71.0 (±s.d.) mmol, Nigeria, Jamaica and US, respectively), while potassium was essentially unchanged (e.g., 46.3±22.9, 40.7±16.1, 44.7±16.4 (±s.d.) mmol, respectively). In multivariate analyses both sodium (positively) and potassium (negatively) were strongly correlated with blood pressure (p < 0.001); quantitatively the association was stronger, and more consistent in each site individually, for potassium. Within-population day-to-day variation was also greater for sodium than for potassium. Among each population group a significant correlation was observed between sodium and urine volume, supporting the prior finding of sodium as a determinant of fluid intake in free-living individuals. These data confirm the consistency with the possible role of dietary electrolytes as hypertension risk factors, reinforcing the relevance of potassium in these populations.

Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.

Best practice guidelines are being used to an increasing degree, not only by physicians to improve the level of care, but also by bureaucrats to constrain reimbursement and guide the pathways of care.

Background

Previous studies exploring the association between 25[OH]D levels and mortality in adults with and without kidney disease utilized 25[OH]D thresholds that have recently been scrutinized by the Institute of Medicine Committee to Review Dietary References Intakes for Vitamin D and Calcium.

Objective

We explored all-cause mortality rates across the spectrum of 25[OH]D levels over an eighteen-year follow-up among adults with and without an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2.

Design

The study included 1,097 U.S. adults with eGFR <60 ml/min/1.73 m2 and 14, 002 adults with eGFR ≥60 ml/min/1.73 m2. Mortality rates and rate ratios (RR) across 25[OH]D groups were calculated with Poisson regression and restricted cubic splines while adjusting for covariates.

Results

Prevalence of 25[OH]D levels <30 and <20 ng/ml among adults with eGFR <60 ml/min/1.73 m2 was 76.5% (population estimate 6.2 million) and 35.4% (population estimate 2.9 million), respectively. Among adults with eGFR ≥60 ml/min/1.73 m2, 70.5% had 25[OH]D levels <30 ng/ml (population estimate 132.2 million) while 30.3% had 25[OH]D levels <20 ng/ml (population estimate 56.8 million). Significantly higher mortality rates were noted among individuals with 25[OH]D levels <12 ng/ml compared to referent group (24 to <30 ng/ml): RR1.41 (95% CI 1.17, 1.71) among individuals with eGFR <60 ml/min/1.73 m2 and RR 1.32 (95% CI 1.13, 1.56) among individuals with eGFR ≥60 ml/min/1.73 m2 after adjustment for covariates including co-morbid conditions. Mortality rates were fairly similar across all 25[OH]D groups with levels >20 ng/ml after adjustment for all covariates.

Conclusions

Regardless of presence of eGFR <60 ml/min/1.73 m2, mortality rates across groups with 25[OH]D levels 20–40 ng/ml are similar.

Corrigendum to Acta Cryst. (2004), E60, o2295–o2297.

The name of one of the authors in the paper by Watkin et al. [Acta Cryst. (2004), E60, o2295–o2297] is corrected.

Purpose

A region of chromosome 22 which includes APOL1 and MYH9 genes was recently identified as a risk locus for non-diabetic forms of kidney disease, including idiopathic and HIV-associated focal segmental glomerular sclerosis and kidney disease clinically attributed to hypertension among African Americans. The purposes of the current study were, therefore, to examine the frequency of these variants and to determine whether they are associated with chronic kidney disease (CKD) among native Africans.

Methods

To investigate the possible evidence of association between variants in these genes and non-diabetic CKD among West Africans, we performed a case/control analysis in a sample of 166 Nigerians without history of European admixture. Our study included a total of 9 variants on APOL1 (n = 4) and MYH9 (n = 5) genes.

Results

We observed significantly strong associations with previously reported APOL1 variants rs73885319 and rs60910145, and their two-allele “G1” haplotype (P < 0.005). We did not observe significant evidence of association between non-diabetic CKD and any of the MYH9 variants or haplotypes after accounting for multiple testing in our sample.

Conclusions

In conclusion, APOL1 risk variants are associated with non-diabetic forms of CKD among Nigerians of Yoruba ethnicity. Further information on APOL1/MYH9 variants may lead to screening programs, which could lead to earlier detection and interventions for non-diabetic kidney disease.

Recent studies suggest that obesity may be “contagious” between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers’ influence on one another, rather than treating “high risk” adolescents in isolation.

Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10−5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10−7 for SBP and 7.52 × 10−7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome.

Background

The pathway-focused association approach offers a hypothesis driven alternative to the agnostic genome-wide association study. Here we apply the pathway-focused approach to an association study of hypertension, systolic blood pressure (SBP), and diastolic blood pressure (DBP) in 1614 Nigerians with genome-wide data.

Methods and Results

Testing of 28 pathways with biological relevance to hypertension, selected a priori, containing a total of 101 unique genes and 4,349 unique single-nucleotide polymorphisms (SNPs) showed an association for the adrenergic alpha 1 (ADRA1) receptor pathway with hypertension (p<0.0009) and diastolic blood pressure (p<0.0007). Within the ADRA1 pathway, the genes PNMT (hypertension Pgene<0.004, DBP Pgene<0.004, and SBP Pgene<0.009, and ADRA1B (hypertension Pgene<0.005, DBP Pgene<0.02, and SBP Pgene<0.02) displayed the strongest associations. Neither ADRA1B nor PNMT could be the sole mediator of the observed pathway association as the ADRA1 pathway remained significant after removing ADRA1B, and other pathways involving PNMT did not reach pathway significance.

Conclusions

We conclude that multiple variants in several genes in the ADRA1 pathway led to associations with hypertension and DBP. SNPs in ADRA1B and PNMT have not previously been linked to hypertension in a genome-wide association study, but both genes have shown associations with hypertension through linkage or model organism studies. The identification of moderately significant (10−2>p>10−5) SNPs offers a novel method for detecting the “missing heritability” of hypertension. These findings warrant further studies in similar and other populations to assess the generalizability of our results, and illustrate the potential of the pathway-focused approach to investigate genetic variation in hypertension.

Geographic variation has been of interest to both health planners and social epidemiologists. However, while the major focus of interest of planners has been on variation in health care spending, social epidemiologists have focused on health; and while social epidemiologists have observed strong associations between poor health and poverty, planners have concluded that income is not an important determinant of variation in spending. These different conclusions stem, at least in part, from differences in approach. Health planners have generally studied variation among large regions, such as states, counties, or hospital referral regions (HRRs), while epidemiologists have tended to study local areas, such as ZIP codes and census tracts. To better understand the basis for geographic variation in hospital utilization, we drew upon both approaches. Counties and HRRs were disaggregated into their constituent ZIP codes and census tracts and examined the interrelationships between income, disability, and hospital utilization that were examined at both the regional and local levels, using statistical and geomapping tools. Our studies centered on the Milwaukee and Los Angeles HRRs, where per capita health care utilization has been greater than elsewhere in their states. We compared Milwaukee to other HRRs in Wisconsin and Los Angeles to the other populous counties of California and to a region in California of comparable size and diversity, stretching from San Francisco to Sacramento (termed “San-Framento”). When studied at the ZIP code level, we found steep, curvilinear relationships between lower income and both increased hospital utilization and increasing percentages of individuals reporting disabilities. These associations were also evident on geomaps. They were strongest among populations of working-age adults but weaker among seniors, for whom income proved to be a poor proxy for poverty and whose residential locations deviated from the major underlying income patterns. Among working-age adults, virtually all of the excess utilization in Milwaukee was attributable to very high utilization in Milwaukee’s segregated “poverty corridor.” Similarly, the greater rate of hospital use in Los Angeles than in San-Framento could be explained by proportionately more low-income ZIP codes in Los Angeles and fewer in San-Framento. Indeed, when only high-income ZIP codes were assessed, there was little variation in hospital utilization among California’s 18 most populous counties. We estimated that had utilization within each region been at the rate of its high-income ZIP codes, overall utilization would have been 35 % less among working-age adults and 20 % less among seniors. These studies reveal the importance of disaggregating large geographic units into their constituent ZIP codes in order to understand variation in health care utilization among them. They demonstrate the strong association between low ZIP code income and both higher percentages of disability and greater hospital utilization. And they suggest that, given the large contribution of the poorest neighborhoods to aggregate utilization, it will be difficult to curb the growth of health care spending without addressing the underlying social determinants of health.

Background

The reasons for racial/ethnic disparities in hypertension prevalence in the U.S are poorly understood.

Methods

Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether individual and neighborhood-level chronic stressors contribute to these disparities in cross-sectional analyses. The sample consisted of 2679 MESA participants (45–84yrs) residing in Baltimore, New York, and North Carolina. Hypertension was defined as systolic or diastolic blood pressure ≥140 or 90mmHg, or taking anti-hypertensive medications. Individual-level chronic stress was measured by self-reported chronic burden and perceived major and everyday discrimination. A measure of neighborhood (census tract) chronic stressors (i.e. physical disorder, violence) was developed using data from a telephone survey conducted with other residents of MESA neighborhoods. Binomial regression was used to estimate associations between hypertension and race/ethnicity before and after adjustment for individual and neighborhood stressors.

Results

The prevalence of hypertension was 59.5% in African Americans (AA), 43.9% in Hispanics, and 42.0% in whites. Age and sex adjusted relative prevalences of hypertension (compared to whites) were 1.30 [95% Confidence Interval (CI): 1.22–1.38] for AA and 1.16 [95% CI: 1.04–1.31] for Hispanics. Adjustment for neighborhood stressors reduced these to 1.17 [95% CI: 1.11–1.22] and 1.09 [95% CI: 1.00–1.18] respectively. Additional adjustment for individual-level stressors, acculturation, income, education, and other neighborhood features only slightly reduced these associations.

Conclusion

Neighborhood chronic stressors may contribute to race/ethnic differences in hypertension prevalence in the U.S.

Motivation: Admixed populations offer a unique opportunity for mapping diseases that have large disease allele frequency differences between ancestral populations. However, association analysis in such populations is challenging because population stratification may lead to association with loci unlinked to the disease locus.

Methods and results: We show that local ancestry at a test single nucleotide polymorphism (SNP) may confound with the association signal and ignoring it can lead to spurious association. We demonstrate theoretically that adjustment for local ancestry at the test SNP is sufficient to remove the spurious association regardless of the mechanism of population stratification, whether due to local or global ancestry differences among study subjects; however, global ancestry adjustment procedures may not be effective. We further develop two novel association tests that adjust for local ancestry. Our first test is based on a conditional likelihood framework which models the distribution of the test SNP given disease status and flanking marker genotypes. A key advantage of this test lies in its ability to incorporate different directions of association in the ancestral populations. Our second test, which is computationally simpler, is based on logistic regression, with adjustment for local ancestry proportion. We conducted extensive simulations and found that the Type I error rates of our tests are under control; however, the global adjustment procedures yielded inflated Type I error rates when stratification is due to local ancestry difference.

Contact: mingyao@upenn.edu; chun.li@vanderbilt.edu.

Supplementary information: Supplementary data are available at Bioinformatics online.

Background

The prevalence of obesity has increased in societies of all socio-cultural backgrounds. To date, guidelines set forward to prevent obesity have universally emphasized optimal levels of physical activity. However there are few empirical data to support the assertion that low levels of energy expenditure in activity is a causal factor in the current obesity epidemic are very limited.

Methods/Design

The Modeling the Epidemiologic Transition Study (METS) is a cohort study designed to assess the association between physical activity levels and relative weight, weight gain and diabetes and cardiovascular disease risk in five population-based samples at different stages of economic development. Twenty-five hundred young adults, ages 25-45, were enrolled in the study; 500 from sites in Ghana, South Africa, Seychelles, Jamaica and the United States. At baseline, physical activity levels were assessed using accelerometry and a questionnaire in all participants and by doubly labeled water in a subsample of 75 per site. We assessed dietary intake using two separate 24-hour recalls, body composition using bioelectrical impedance analysis, and health history, social and economic indicators by questionnaire. Blood pressure was measured and blood samples collected for measurement of lipids, glucose, insulin and adipokines. Full examination including physical activity using accelerometry, anthropometric data and fasting glucose will take place at 12 and 24 months. The distribution of the main variables and the associations between physical activity, independent of energy intake, glucose metabolism and anthropometric measures will be assessed using cross-section and longitudinal analysis within and between sites.

Discussion

METS will provide insight on the relative contribution of physical activity and diet to excess weight, age-related weight gain and incident glucose impairment in five populations' samples of young adults at different stages of economic development. These data should be useful for the development of empirically-based public health policy aimed at the prevention of obesity and associated chronic diseases.

Identification and characterization of the genetic variants underlying type 2 diabetes susceptibility can provide important understanding of the etiology and pathogenesis of type 2 diabetes. We previously identified strong evidence of linkage for type 2 diabetes on chromosome 22 among 3,383 Hypertension Genetic Epidemiology Network (HyperGEN) participants from 1,124 families. The checkpoint 2 (CHEK2) gene, an important mediator of cellular responses to DNA damage, is located 0.22 Mb from this linkage peak. In this study, we tested the hypothesis that the CHEK2 gene contains one or more polymorphic variants that are associated with type 2 diabetes in HyperGEN individuals. In addition, we replicated our findings in two other Family Blood Pressure Program (FBPP) populations and in the population-based Atherosclerosis Risk in Communities (ARIC) study. We genotyped 1,584 African-American and 1,531 white HyperGEN participants, 1,843 African-American and 1,569 white GENOA participants, 871 African-American and 1,009 white GenNet participants, and 4,266 African-American and 11,478 white ARIC participants for four single nucleotide polymorphisms (SNPs) in CHEK2. Using additive models, we evaluated the association of CHEK2 SNPs with type 2 diabetes in participants within each study population stratified by race, and in a meta-analysis, adjusting for age, age2, sex, sex-by-age interaction, study center, and relatedness. One CHEK2 variant, rs4035540, was associated with an increased risk of type 2 diabetes in HyperGEN participants, two replication samples, and in the meta-analysis. These results may suggest a new pathway in the pathogenesis of type 2 diabetes that involves pancreatic beta-cell damage and apoptosis.

Motivation: Adjustment for population structure is necessary to avoid bias in genetic association studies of susceptibility variants for complex diseases. Population structure may differ from one genomic region to another due to the variability of individual ancestry associated with migration, random genetic drift or natural selection. Current association methods for correcting population stratification usually involve adjustment of global ancestry between study subjects.

Results: We suggest interrogating local population structure for fine mapping to more accurately locate true casual genes by better adjusting the confounding effect due to local ancestry. By extensive simulations on genome-wide datasets, we show that adjusting global ancestry may lead to false positives when local population structure is an important confounding factor. In contrast, adjusting local ancestry can effectively prevent false positives due to local population structure and thus can improve fine mapping for disease gene localization. We applied the local and global adjustments to the analysis of datasets from three genome-wide association studies, including European Americans, African Americans and Nigerians. Both European Americans and African Americans demonstrate greater variability in local ancestry than Nigerians. Adjusting local ancestry successfully eliminated the known spurious association between SNPs in the LCT gene and height due to the population structure existed in European Americans.

Contact: xiaofeng.zhu@case.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

We compare the SNP-based and gene-based association studies using 697 unrelated individuals. The Benjamini-Hochberg procedure was applied to control the false discovery rate for all the multiple comparisons. We use a linear model for the single-nucleotide polymorphism (SNP) based association study. For the gene-based study, we consider three methods. The first one is based on a linear model, the second is similarity based, and the third is a new two-step procedure. The results of power using a subset of SNPs show that the SNP-based association test is more powerful than the gene-based ones. However, in some situations, a gene-based study is able to detect the associated variants that were neglected in a SNP-based study. Finally, we apply these methods to a replicate of the quantitative trait Q1 and the binary trait D (D = 1, affected; D = 0, unaffected) for a genome-wide gene search.

Summary

We longitudinally explored the relationship of body size and adiponectin levels in 393 community-dwelling Afro-Jamaicans. Adiponectin levels were greater in women, increased with age and declined with abdominal adiposity. Multivariate regression analyses suggest that subcutaneous fat in women may contribute significantly to the variance in their adiponectin levels.

Extracellular polysaccharide (EPS) is produced by diverse bacterial pathogens and fulfills assorted roles, including providing a structural matrix for biofilm formation and more specific functions in virulence, such as protection against immune defenses. We report here the first investigation of some of the genes important for biofilm formation in Photorhabdus luminescens and demonstrate the key role of the phosphomannose isomerase gene, manA, in the structure of functional EPS. Phenotypic analyses of a manA-deficient mutant showed the importance of EPS in motility, insect virulence, and biofilm formation on abiotic surfaces as well as the requirement of this gene for the use of mannose as the sole carbon source. Conversely, this defect had no apparent impact on symbiosis with the heterorhabditid nematode vector. A more detailed analysis of biofilm formation revealed that the manA mutant was able to attach to surfaces with the same efficiency as that of the wild-type strain but could not develop the more extended biofilm matrix structures. A compositional analysis of P. luminescens EPS reveals how the manA mutation has a major effect on the formation of a complete, branched EPS.

Genome-wide association studies have identified many common genetic variants that are associated with polygenic traits, and have typically been performed with individuals of recent European ancestry. In these populations, many common variants are tightly correlated, with the perfect or near-perfect proxies for the functional or true variant showing equivalent evidence of association, considerably limiting the resolution of fine mapping. Populations with recent African ancestry often have less extensive and/or different patterns of linkage disequilibrium (LD), and have been proposed to be useful in fine-mapping studies. Here, we strongly replicate and fine map in populations of predominantly African ancestry the association between variation at the FTO locus and body mass index (BMI) that is well established in populations of European ancestry. We genotyped single nucleotide polymorphisms that are correlated with the signal of association in individuals of European ancestry but that have varying degrees of correlation in African-derived individuals. Most of the variants, including one previously proposed as functionally important, have no significant association with BMI, but two variants, rs3751812 and rs9941349, show strong evidence of association (P = 2.58 × 10−6 and 3.61 × 10−6 in a meta-analysis of 9881 individuals). Thus, we have both strongly replicated this association in African-ancestry populations and narrowed the list of potentially causal variants to those that are correlated with rs3751812 and rs9941349 in African-derived populations. This study illustrates the potential of using populations with different LD patterns to fine map associations and helps pave the way for genetically guided functional studies at the FTO locus.

Genome-wide association (GWA) studies have identified common variants that are associated with a variety of traits and diseases, but most studies have been performed in European-derived populations. Here, we describe the first genome-wide analyses of imputed genotype and copy number variants (CNVs) for anthropometric measures in African-derived populations: 1188 Nigerians from Igbo-Ora and Ibadan, Nigeria, and 743 African-Americans from Maywood, IL. To improve the reach of our study, we used imputation to estimate genotypes at ∼2.1 million single-nucleotide polymorphisms (SNPs) and also tested CNVs for association. No SNPs or common CNVs reached a genome-wide significance level for association with height or body mass index (BMI), and the best signals from a meta-analysis of the two cohorts did not replicate in ∼3700 African-Americans and Jamaicans. However, several loci previously confirmed in European populations showed evidence of replication in our GWA panel of African-derived populations, including variants near IHH and DLEU7 for height and MC4R for BMI. Analysis of global burden of rare CNVs suggested that lean individuals possess greater total burden of CNVs, but this finding was not supported in an independent European population. Our results suggest that there are not multiple loci with strong effects on anthropometric traits in African-derived populations and that sample sizes comparable to those needed in European GWA studies will be required to identify replicable associations. Meta-analysis of this data set with additional studies in African-ancestry populations will be helpful to improve power to detect novel associations.

Background

Levels of physical activity (PA) in the general population are difficult to characterize. Historically measurement has been based on self-report, which can be subject to bias. PA monitor use has created opportunities to improve surveillance and analytic research on activity and health. The aims of the current study were to investigate the associations between objectively measured PA and cardiovascular disease risk factors and obesity.

Methods

Data on PA from accelerometers, demographics, blood pressure, plasma glucose and lipids, self-reported hypertension and diabetes were obtained for adults, ages 20-65, in the NHANES surveys, 2003-2006. Outcomes were assessed as levels of moderate and vigorous activity, percentage of participants meeting recommended guidelines, and the correlations between activity and cardiovascular risk factors. Accelerometry data were available on 3,370 adults. Based on standard algorithms, activity levels were extremely low in all age-gender-race/ethnic groups, with an average of only 1 bout of vigorous activity lasting longer than 1 minute/day.

Results

Men spent 35 minutes in moderate activity/day, women 21 minutes; >75% of this activity was accumulated in 1-minute bouts. Levels of activity declined sharply after age 50 in all groups. Negative associations were observed between minutes of combined moderate and vigorous activity and systolic blood pressure, blood glucose, diabetes, hypertension, body mass index and obesity, and a positive association was seen with HDL-cholesterol (all P ≤ 0.03), suggesting valid rank ordering of participants by activity level.

Conclusion

The magnitude of the gap between self-report and accelerometry activity must be a result of either a vast social acceptability bias in reporting or inaccurate measurement with accelerometry. Therefore, due to the low validity of self reported PA data for epidemiologic research, it is pertinent to encourage the use of valid, objective methods to assess PA.

Background

The rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex.

Methods and Findings

To describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within- and between-group heterogeneity.

Conclusion

As a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.

SUMMARY

We address the asymptotic and approximate distributions of a large class of test statistics with quadratic forms used in association studies. The statistics of interest take the general form D = XT AX, where A is a general similarity matrix which may or may not be positive semi-definite, and X follows the multivariate normal distribution with mean μ and variance matrix Σ, where Σ may or may not be singular. We show that D can be written as a linear combination of independent chi-square random variables with a shift. Furthermore, its distribution can be approximated by a chi-square or the difference of two chi-square distributions. In the setting of association testing, our methods are especially useful in two situations. First, when the required significance level is much smaller than 0.05 such as in a genome scan the estimation of p-values using permutation procedures can be challenging. Second, when an EM algorithm is required to infer haplotype frequencies from un-phased genotype data the computation can be intensive for a permutation procedure. In either situation, an efficient and accurate estimation procedure would be useful. Our method can be applied to any quadratic form statistic and therefore should be of general interest.