Genetic risk factors for body mass index and obesity in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) Study

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. As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated the association between thirteen GWAS-identified 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 beta 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 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. 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. 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

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits

Frequency of exacerbations in patients with chronic obstructive pulmonary disease: an analysis of the SPIROMICS cohort

Background Present treatment strategies to stratify exacerbation risk in patients with chronic obstructive pulmonary disease (COPD) rely on a history of two or more events in the previous year. We aimed to understand year to year variability in exacerbations and factors associated with consistent exacerbations over time. Methods In this longitudinal, prospective analysis of exacerbations in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) cohort, we analysed patients aged 40–80 years with COPD for whom 3 years of prospective data were available, identified through various means including care at academic and non-academic medical centres, word of mouth, and existing patient registries. Participants were enrolled in the study between Nov 12, 2010, and July 31, 2015. We classified patients according to yearly exacerbation frequency: no exacerbations in any year; one exacerbation in every year during 3 years of follow-up; and those with inconsistent exacerbations (individuals who had both years with exacerbations and years without during the 3 years of follow-up). Participants were characterised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric category (1–4) on the basis of post-bronchodilator FEV1. Stepwise logistic regression was used to compare factors associated with one or more acute exacerbations of COPD every year for 3 years versus no exacerbations in the same timeframe. Additionally, a stepwise zero-inflated negative binomial model was used to assess predictors of exacerbation count during follow-up in all patients with available data. Baseline symptom burden was assessed with the COPD assessment test. This trial is registered with ClinicalTrials.gov, number NCT01969344. Findings 2981 patients were enrolled during the study. 1843 patients had COPD, of which 1105 patients had 3 years of complete, prospective follow-up data. 538 (49%) of 1105 patients had at least one acute exacerbation during the 3 years of follow-up, whereas 567 (51%) had none. 82 (7%) of 1105 patients had at least one acute exacerbation each year, whereas only 23 (2%) had two or more acute exacerbations in each year. An inconsistent pattern (both years with and without acute exacerbations) was common (456 [41%] of the group), particularly among GOLD stages 3 and 4 patients (256 [56%] of 456). In logistic regression, consistent acute exacerbations (≥1 event per year for 3 years) were associated with higher baseline symptom burden, previous exacerbations, greater evidence of small airway abnormality on CT, lower interleukin-15 concentrations, and higher interleukin-8 concentrations, than were no acute exacerbations. Interpretation Although acute exacerbations are common, the exacerbation status of most individuals varies markedly from year to year. Among patients who had any acute exacerbation over 3 years, very few repeatedly had two or more events per year. In addition to symptoms and history of exacerbations in the year before study enrolment, we identified several novel biomarkers associated with consistent exacerbations, including CT-defined small airway abnormality, and interleukin-15 and interleukin-8 concentrations

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p