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Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype., (© 2013 WILEY PERIODICALS, INC.)

Characterization of genetic admixture of populations in the Americas and the Caribbean is of interest for anthropological, epidemiological, and historical reasons. Asthma has a higher prevalence and is more severe in populations with a high African component. Association of African ancestry with asthma has been demonstrated. We estimated admixture proportions of samples from six trihybrid populations of African descent and determined the relationship between African ancestry and asthma and total serum IgE levels (tIgE). We genotyped 237 ancestry informative markers in asthmatics and nonasthmatic controls from Barbados (190/277), Jamaica (177/529), Brazil (40/220), Colombia (508/625), African Americans from New York (207/171), and African Americans from Baltimore/Washington, D.C. (625/757). We estimated individual ancestries and evaluated genetic stratification using Structure and principal component analysis. Association of African ancestry and asthma and tIgE was evaluated by regression analysis. Mean ± SD African ancestry ranged from 0.76 ± 0.10 among Barbadians to 0.33 ± 0.13 in Colombians. The European component varied from 0.14 ± 0.05 among Jamaicans and Barbadians to 0.26 ± 0.08 among Colombians. African ancestry was associated with risk for asthma in Colombians (odds ratio (OR) = 4.5, P = 0.001) Brazilians (OR = 136.5, P = 0.003), and African Americans of New York (OR: 4.7; P = 0.040). African ancestry was also associated with higher tIgE levels among Colombians (β = 1.3, P = 0.04), Barbadians (β = 3.8, P = 0.03), and Brazilians (β = 1.6, P = 0.03). Our findings indicate that African ancestry can account for, at least in part, the association between asthma and its associated trait, tIgE levels., (© 2013 Wiley Periodicals, Inc.)

Admixture is a potential source of confounding in genetic association studies, so it becomes important to detect and estimate admixture in a sample of unrelated individuals. Populations of African descent in the US and the Caribbean share similar historical backgrounds but the distributions of African admixture may differ. We selected 416 ancestry informative markers (AIMs) to estimate and compare admixture proportions using STRUCTURE in 906 unrelated African Americans (AAs) and 294 Barbadians (ACs) from a study of asthma. This analysis showed AAs on average were 72.5% African, 19.6% European and 8% Asian, while ACs were 77.4% African, 15.9% European, and 6.7% Asian which were significantly different. A principal components analysis based on these AIMs yielded one primary eigenvector that explained 54.04% of the variation and captured a gradient from West African to European admixture. This principal component was highly correlated with African vs. European ancestry as estimated by STRUCTURE (r(2)=0.992, r(2)=0.912, respectively). To investigate other African contributions to African American and Barbadian admixture, we performed PCA on approximately 14,000 (14k) genome-wide SNPs in AAs, ACs, Yorubans, Luhya and Maasai African groups, and estimated genetic distances (F(ST)). We found AAs and ACs were closest genetically (F(ST)=0.008), and both were closer to the Yorubans than the other East African populations. In our sample of individuals of African descent, approximately 400 well-defined AIMs were just as good for detecting substructure as approximately 14,000 random SNPs drawn from a genome-wide panel of markers., ((c) 2010 Wiley-Liss, Inc.)

Genome-wide association studies (GWAS) have emerged as powerful means for identifying genetic loci related to complex diseases. However, the role of environment and its potential to interact with key loci has not been adequately addressed in most GWAS. Networks of collaborative studies involving different study populations and multiple phenotypes provide a powerful approach for addressing the challenges in analysis and interpretation shared across studies. The Gene, Environment Association Studies (GENEVA) consortium was initiated to: identify genetic variants related to complex diseases; identify variations in gene-trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes. GENEVA consists of several academic institutions, including a coordinating center, two genotyping centers and 14 independently designed studies of various phenotypes, as well as several Institutes and Centers of the National Institutes of Health led by the National Human Genome Research Institute. Minimum detectable effect sizes include relative risks ranging from 1.24 to 1.57 and proportions of variance explained ranging from 0.0097 to 0.02. Given the large number of research participants (N>80,000), an important feature of GENEVA is harmonization of common variables, which allow analyses of additional traits. Environmental exposure information available from most studies also enables testing of gene-environment interactions. Facilitated by its sizeable infrastructure for promoting collaboration, GENEVA has established a unified framework for genotyping, data quality control, analysis and interpretation. By maximizing knowledge obtained through collaborative GWAS incorporating environmental exposure information, GENEVA aims to enhance our understanding of disease etiology, potentially identifying opportunities for intervention., ((c) 2010 Wiley-Liss, Inc.)

Few comparison studies have been performed on single nucleotide polymorphism (SNP) tagging methods to examine their consistency and effectiveness in terms of inferences about association with disease. We applied several SNP tagging methods to SNPs on chromosome 12q (n=713) and compared the utility of these methods to detect association for asthma and serum IgE levels among a sample of African Caribbean families from Barbados selected through asthmatic probands. We found that a high level of information regarding association is retained in Clayton's htSNP, Stram's TagSNP, and de Bakker's Tagger. We also found a high degree of consistency between TagSNP and Tagger. Using this set of 713 SNPs on chromosome 12q, our study provides insight towards analytic strategies for future studies of complex traits., ((c) 2006 Wiley-Liss, Inc.)

Rapid development in biotechnology has enhanced the opportunity to deal with multipoint gene mapping for complex diseases, and association studies using quantitative traits have recently generated much attention. Unlike the conventional hypothesis-testing approach for fine mapping, we propose a unified multipoint method to localize a gene controlling a quantitative trait. We first calculate the sample size needed to detect linkage and linkage disequilibrium (LD) for a quantitative trait, categorized by decile, under three different modes of inheritance. Our results show that sampling trios of offspring and their parents from either extremely low (EL) or extremely high (EH) probands provides greater statistical power than sampling in the intermediate range. We next propose a unified sampling approach for multipoint LD mapping, where the goal is to estimate the map position (tau) of a trait locus and to calculate a confidence interval along with its sampling uncertainty. Our method builds upon a model for an expected preferential transmission statistic at an arbitrary locus conditional on the sampling scheme, such as sampling from EL and EH probands. This approach is valid regardless of the underlying genetic model. The one major assumption for this model is that no more than one quantitative trait locus (QTL) is linked to the region being mapped. Finally we illustrate the proposed method using family data on total serum IgE levels collected in multiplex asthmatic families from Barbados. An unobserved QTL appears to be located at tau; = 41.93 cM with 95% confidence interval of (40.84, 43.02) through the 20-cM region framed by markers D12S1052 and D12S1064 on chromosome 12. The test statistic shows strong evidence of linkage and LD (chi-square statistic = 18.39 with 2 df, P-value = 0.0001)., (Copyright 2002 Wiley-Liss, Inc.)

Variance components models were used to analyze total IgE levels in families ascertained though the Collaborative Study of the Genetics of Asthma (CSGA) using a genome-wide array of polymorphic markers. While IgE levels are known to be associated with clinical asthma and recognized to be under strong genetic control (here the heritability was estimated at 44-60% in the three racial groups), specific genes influencing this trait are still largely unknown. Multipoint analysis of 323 markers yielded little indication of specific regions containing a trait locus controlling total serum IgE levels (adjusted for age and gender). Although a number of regions showed LOD statistics above 1.5 in Caucasian families (chromosome 4) and in African-American families (chromosomes 2 and 4), none yielded consistent evidence in all three racial groups. Analysis of total IgE adjusted for gender, age and Allergy Index (a quantitative score of skin test sensitivity to 14 common aeroallergens) was conducted on these data. In this analysis, a much stronger signal for a trait locus controlling adjusted log[total IgE] was seen on the telomeric end of chromosome 18, but only in Caucasian families. This region accounted for most of the genetic variation in log[total IgE], and may represent a quantitative trait locus for IgE levels independent of atopic response. Oligogenic analysis accounting simultaneously for the contribution of this locus on chromosome 18 and other chromosomal regions showing some evidence of linkage in these Caucasian families (on chromosomes 2, 4 and 20) failed to yield significant evidence for interaction., (Copyright 2001 Wiley-Liss, Inc.)