Genome Wide Association for Addiction: Replicated Results and Comparisons of Two Analytic Approaches

Background

Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. “Nontemplate” genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance.

Methodology/Principal Findings

We report pooled “nontemplate” genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both “converge then cluster” and “cluster then converge” analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals.

Conclusions/Significance

These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to “cell adhesion” processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. “Nontemplate” GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, “template” GWA approaches in which “genome wide” levels of significance are sought for SNP data from single case vs control comparisons.     

Genome-wide association analysis reveals putative Alzheimer's disease susceptibility loci in addition to APOE

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder. To date four genes have been established to either cause early-onset autosomal-dominant AD (APP, PSEN1, and PSEN2(1-4)) or to increase susceptibility for late-onset AD (APOE5). However, the heritability of late-onset AD is as high as 80%, (6) and much of the phenotypic variance remains unexplained to date. We performed a genome-wide association (GWA) analysis using 484,522 single-nucleotide polymorphisms (SNPs) on a large (1,376 samples from 410 families) sample of AD families of self-reported European descent. We identified five SNPs showing either significant or marginally significant genome-wide association with a multivariate phenotype combining affection status and onset age. One of these signals (p = 5.7 x 10(-14)) was elicited by SNP rs4420638 and probably reflects APOE-epsilon4, which maps 11 kb proximal (r2 = 0.78). The other four signals were tested in three additional independent AD family samples composed of nearly 2700 individuals from almost 900 families. Two of these SNPs showed significant association in the replication samples (combined p values 0.007 and 0.00002). The SNP (rs11159647, on chromosome 14q31) with the strongest association signal also showed evidence of association with the same allele in GWA data generated in an independent sample of approximately 1,400 AD cases and controls (p = 0.04). Although the precise identity of the underlying locus(i) remains elusive, our study provides compelling evidence for the existence of at least one previously undescribed AD gene that, like APOE-epsilon4, primarily acts as a modifier of onset age.     

Genome wide association (GWA) study for early onset extreme obesity supports the role of fat mass and obesity associated gene (FTO) variants

Background

Obesity is a major health problem. Although heritability is substantial, genetic mechanisms predisposing to obesity are not very well understood. We have performed a genome wide association study (GWA) for early onset (extreme) obesity.

Methodology/Principal Findings

a) GWA (Genome-Wide Human SNP Array 5.0 comprising 440,794 single nucleotide polymorphisms) for early onset extreme obesity based on 487 extremely obese young German individuals and 442 healthy lean German controls; b) confirmatory analyses on 644 independent families with at least one obese offspring and both parents. We aimed to identify and subsequently confirm the 15 SNPs (minor allele frequency ≥10%) with the lowest p-values of the GWA by four genetic models: additive, recessive, dominant and allelic. Six single nucleotide polymorphisms (SNPs) in FTO (fat mass and obesity associated gene) within one linkage disequilibrium (LD) block including the GWA SNP rendering the lowest p-value (rs1121980; log-additive model: nominal p = 1.13×10⁻⁷, corrected p = 0.0494; odds ratio (OR)_CT 1.67, 95% confidence interval (CI) 1.22–2.27; OR_TT 2.76, 95% CI 1.88–4.03) belonged to the 15 SNPs showing the strongest evidence for association with obesity. For confirmation we genotyped 11 of these in the 644 independent families (of the six FTO SNPs we chose only two representing the LD bock). For both FTO SNPs the initial association was confirmed (both Bonferroni corrected p<0.01). However, none of the nine non-FTO SNPs revealed significant transmission disequilibrium.

Conclusions/Significance

Our GWA for extreme early onset obesity substantiates that variation in FTO strongly contributes to early onset obesity. This is a further proof of concept for GWA to detect genes relevant for highly complex phenotypes. We concurrently show that nine additional SNPs with initially low p-values in the GWA were not confirmed in our family study, thus suggesting that of the best 15 SNPs in the GWA only the FTO SNPs represent true positive findings.     

Fine mapping versus replication in whole-genome association studies

Association replication studies have a poor track record and, even when successful, often claim association with different markers, alleles, and phenotypes than those reported in the primary study. It is unknown whether these outcomes reflect genuine associations or false-positive results. A greater understanding of these observations is essential for genomewide association (GWA) studies, since they have the potential to identify multiple new associations that that will require external validation. Theoretically, a repeat association with precisely the same variant in an independent sample is the gold standard for replication, but testing additional variants is commonplace in replication studies. Finding different associated SNPs within the same gene or region as that originally identified is often reported as confirmatory evidence. Here, we compare the probability of replicating a gene or region under two commonly used marker-selection strategies: an "exact" approach that involves only the originally significant markers and a "local" approach that involves both the originally significant markers and others in the same region. When a region of high intermarker linkage disequilibrium is tested to replicate an initial finding that is only weak association with disease, the local approach is a good strategy. Otherwise, the most powerful and efficient strategy for replication involves testing only the initially identified variants. Association with a marker other than that originally identified can occur frequently, even in the presence of real effects in a low-powered replication study, and instances of such association increase as the number of included variants increases. Our results provide a basis for the design and interpretation of GWA replication studies and point to the importance of a clear distinction between fine mapping and replication after GWA.     

The 18p11.22 locus is associated with never smoker non-small cell lung cancer susceptibility in Korean populations

The proportion of never smoker non-small cell lung cancer (NSCLC) in Asia is about 30-40%. Despite the striking demographics and high prevalence of never smoker NSCLC, the exact causes still remain undetermined. Although several genome wide association (GWA) studies were conducted to find susceptibility loci for lung cancer in never smokers, no regions were replicated except for 5p15.33, suggesting locus heterogeneity and different environmental toxic effects. To identify genetic loci associated with susceptibility of lung cancer in never smokers, we performed a GWA analysis using the Affymetrix 6.0 SNP array. For discovery GWA set, we recruited 446 never smoking Korean patients with NSCLC and 497 normal subjects. We tested association of SNPs with lung cancer susceptibility using the Cochran-Armitage trend test. For validation, 39 SNPs were selected from the top 50 SNPs and five additional SNPs were selected in the DAB1 gene region which showed significant associations in the GWA analysis. The validation SNPs were genotyped in an independent sample including 434 patients and 1,000 controls. Among the 44 validation SNPs, two SNPs (rs11080466 and rs11663246) near the APCDD1, NAPG and FAM38B genes in the 18p11.22 region were replicated. P value of rs11080466 was 1.08 × 10(-6) in the combined sets (2.68 × 10(-5) in the discovery set and 2.60 × 10(-3) in the validation set) and odds ratio was 0.68 (0.58-0.79). We observed similar association for rs11663246. Our result suggests the 18p11.22 region as a novel lung cancer susceptibility locus in never smokers.     

Association Mapping for Fruit,Plant and Leaf Morphology Traits in Eggplant

An eggplant (Solanum melongena) association panel of 191 accessions, comprising a mixture of breeding lines, old varieties and landrace selections was SNP genotyped and phenotyped for key breeding fruit and plant traits at two locations over two seasons. A genome-wide association (GWA) analysis was performed using the mixed linear model, which takes into account both a kinship matrix and the sub-population membership of the accessions. Overall, 194 phenotype/genotype associations were uncovered, relating to 30 of the 33 measured traits. These associations involved 79 SNP loci mapping to 39 distinct chromosomal regions distributed over all 12 eggplant chromosomes. A comparison of the map positions of these SNPs with those of loci derived from conventional linkage mapping showed that GWA analysis both validated many of the known controlling loci and detected a large number of new marker/trait associations. Exploiting established syntenic relationships between eggplant chromosomes and those of tomato and pepper recognized orthologous regions in ten eggplant chromosomes harbouring genes influencing breeders’ traits.     

An analysis of single nucleotide polymorphisms of 125 DNA repair genes in the Texas genome-wide association study of lung cancer with a replication for the XRCC4 SNPs

DNA repair genes are important for maintaining genomic stability and limiting carcinogenesis. We analyzed all single nucleotide polymorphisms (SNPs) of 125 DNA repair genes covered by the Illumina HumanHap300 (v1.1) BeadChips in a previously conducted genome-wide association study (GWAS) of 1154 lung cancer cases and 1137 controls and replicated the top-hits of XRCC4 SNPs in an independent set of 597 cases and 611 controls in Texas populations. We found that six of 20 XRCC4 SNPs were associated with a decreased risk of lung cancer with a P-value of 0.01 or lower in the discovery dataset, of which the most significant SNP was rs10040363 (P for allelic test=4.89 x 10??). Moreover, the data in this region allowed us to impute a potentially functional SNP rs2075685 (imputed P for allelic test=1.3 x 10?3). A luciferase reporter assay demonstrated that the rs2075685G>T change in the XRCC4 promoter increased expression of the gene. In the replication study of rs10040363, rs1478486, rs9293329, and rs2075685, however, only rs10040363 achieved a borderline association with a decreased risk of lung cancer in a dominant model (adjusted OR=0.80, 95% CI=0.62-1.03 and P=0.079). In the final combined analysis of both the Texas GWAS discovery and replication datasets, the strength of the association was increased for rs10040363 (adjusted OR=0.77, 95% CI=0.66-0.89, P(dominant)=5 x 10?? and P for trend=5 x 10??) and rs1478486 (adjusted OR=0.82, 95% CI=0.71-0.94, P(dominant)=6 x 10?3 and P for trend=3.5 x 10?3). Finally, we conducted a meta-analysis of these XRCC4 SNPs with available data from published GWA studies of lung cancer with a total of 12,312 cases and 47,921 controls, in which none of these XRCC4 SNPs was associated with lung cancer risk. It appeared that rs2075685, although associated with increased expression of a reporter gene and lung cancer risk in the Texas populations, did not have an effect on lung cancer risk in other populations. This study underscores the importance of replication using published data in larger populations.     

Gene-centric characteristics of genome-wide association studies

Background

The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches.

Methodology/Principal Findings

In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics.

Conclusions/Significance

This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions.     

Genome-wide association study identifies Loci for body composition and structural soundness traits in pigs

Background

The recent completion of the swine genome sequencing project and development of a high density porcine SNP array has made genome-wide association (GWA) studies feasible in pigs.

Methodology/Principal Findings

Using Illumina''s PorcineSNP60 BeadChip, we performed a pilot GWA study in 820 commercial female pigs phenotyped for backfat, loin muscle area, body conformation in addition to feet and leg (FL) structural soundness traits. A total of 51,385 SNPs were jointly fitted using Bayesian techniques as random effects in a mixture model that assumed a known large proportion (99.5%) of SNPs had zero effect. SNP annotations were implemented through the Sus scrofa Build 9 available from pig Ensembl. We discovered a number of candidate chromosomal regions, and some of them corresponded to QTL regions previously reported. We not only have identified some well-known candidate genes for the traits of interest, such as MC4R (for backfat) and IGF2 (for loin muscle area), but also obtained novel promising genes, including CHCHD3 (for backfat), BMP2 (for loin muscle area, body size and several FL structure traits), and some HOXA family genes (for overall leg action). The candidate regions responsible for body conformation and FL structure soundness did not overlap greatly which implied that these traits were controlled by different genes. Functional clustering analyses classified the genes into categories related to bone and cartilage development, muscle growth and development or the insulin pathway suggesting the traits are regulated by common pathways or gene networks that exert roles at different spatial and temporal stages.

Conclusions/Significance

This study is one of the earliest GWA reports on important quantitative traits in pigs, and the findings will contribute to the further biological function analysis of the identified candidate genes and potential utilization of them in marker assisted selection.     

Rapid Assessment of Genetic Ancestry in Populations of Unknown Origin by Genome-Wide Genotyping of Pooled Samples

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).     

Type 2 diabetes whole-genome association study in four populations: the DiaGen consortium

Type 2 diabetes (T2D) is a common, polygenic chronic disease with high heritability. The purpose of this whole-genome association study was to discover novel T2D-associated genes. We genotyped 500 familial cases and 497 controls with >300,000 HapMap-derived tagging single-nucleotide-polymorphism (SNP) markers. When a stringent statistical correction for multiple testing was used, the only significant SNP was at TCF7L2, which has already been discovered and confirmed as a T2D-susceptibility gene. For a replication study, we selected 10 SNPs in six chromosomal regions with the strongest association (singly or as part of a haplotype) for retesting in an independent case-control set including 2,573 T2D cases and 2,776 controls. The most significant replicated result was found at the AHI1-LOC441171 gene region.     

Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies

We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide-polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called "GenePool," which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.     

Underestimated effect sizes in GWAS: fundamental limitations of single SNP analysis for dichotomous phenotypes

Complex diseases are often highly heritable. However, for many complex traits only a small proportion of the heritability can be explained by observed genetic variants in traditional genome-wide association (GWA) studies. Moreover, for some of those traits few significant SNPs have been identified. Single SNP association methods test for association at a single SNP, ignoring the effect of other SNPs. We show using a simple multi-locus odds model of complex disease that moderate to large effect sizes of causal variants may be estimated as relatively small effect sizes in single SNP association testing. This underestimation effect is most severe for diseases influenced by numerous risk variants. We relate the underestimation effect to the concept of non-collapsibility found in the statistics literature. As described, continuous phenotypes generated with linear genetic models are not affected by this underestimation effect. Since many GWA studies apply single SNP analysis to dichotomous phenotypes, previously reported results potentially underestimate true effect sizes, thereby impeding identification of true effect SNPs. Therefore, when a multi-locus model of disease risk is assumed, a multi SNP analysis may be more appropriate.     

Linkage disequilibrium pattern and age-at-diagnosis are critical for replicating genetic associations across ethnic groups in leprosy

One of the persistent challenges of genetic association studies is the replication of genetic marker-disease associations across ethnic groups. Here, we conducted high-density association mapping of PARK2/PACRG SNPs with leprosy and identified 69 SNPs significantly associated with leprosy in 198 single-case Vietnamese leprosy families. A total of 56 associated SNPs localized to the overlapping promoter regions of PARK2/PACRG. For this region, multivariate analysis identified four SNPs belonging to two major SNP bins (rs1333955, rs7744433) and two single SNP bins (rs2023004, rs6936895) that capture the combined statistical evidence (P = 1.1 × 10^?5) for association among Vietnamese patients. Next, we enrolled a case–control sample of 364 leprosy cases and 370 controls from Northern India. We genotyped all subjects for 149 SNPs that capture >80 % of the genetic variation in the Vietnamese sample and found 24 SNPs significantly associated with leprosy. Multivariate analysis identified three SNPs (rs1333955, rs9356058 and rs2023004) that capture the association with leprosy (P < 10^?8). Hence, two SNPs (rs1333955 and rs2023004) were replicated by multivariate analysis between both ethnic groups. Marked differences in the linkage disequilibrium pattern explained some of the differences in univariate analysis between the two ethnic groups. In addition, the strength of association for two promoter region SNP bins was significantly stronger among young leprosy patients in the Vietnamese sample. The same trend was observed in the Indian sample, but due to the higher age-at-diagnosis of the patients the age effect was less pronounced.     

Concordant association of lipid gene variation with a combined HDL/LDL-cholesterol phenotype in two European populations

OBJECTIVE: SNP/phenotype associations are difficult to validate. This comparative study demonstrates significant contribution of candidate genes to the variation of a complex cholesterol phenotype, measured in two general populations by a gene-based approach. METHODS: Independent samples of normolipidemic subjects from two Caucasian populations (371 Swiss and 157 Germans) were selected for a case-control-study (high LDL/low HDL versus low LDL/high HDL) with SNP genotypes as independent factors. We examined locus-specific common SNPs that densely cover the genomic regions of 10 lipid genes. RESULTS: Genotype effects were concordant in both ethnic samples, showing that APOE, ABCA1, CETP, and to a lesser degree LDLR, LIPC, and PLTP explained a substantial part of the genetic variation, whereas LPL was associated in only one sample. APOA1, LCAT, and SRB1 exerted no measurable influence. CONCLUSION: This comparison showed that sets of common SNPs representing candidate regions reproducibly validate significant linkage disequilibrium association with a complex metabolic trait.     

Identification of a Functional Genetic Variant at 16q12.1 for Breast Cancer Risk: Results from the Asia Breast Cancer Consortium

Genetic factors play an important role in the etiology of breast cancer. We carried out a multi-stage genome-wide association (GWA) study in over 28,000 cases and controls recruited from 12 studies conducted in Asian and European American women to identify genetic susceptibility loci for breast cancer. After analyzing 684,457 SNPs in 2,073 cases and 2,084 controls in Chinese women, we evaluated 53 SNPs for fast-track replication in an independent set of 4,425 cases and 1,915 controls of Chinese origin. Four replicated SNPs were further investigated in an independent set of 6,173 cases and 6,340 controls from seven other studies conducted in Asian women. SNP rs4784227 was consistently associated with breast cancer risk across all studies with adjusted odds ratios (95% confidence intervals) of 1.25 (1.20−1.31) per allele (P = 3.2×10⁻²⁵) in the pooled analysis of samples from all Asian samples. This SNP was also associated with breast cancer risk among European Americans (per allele OR  = 1.19, 95% CI  = 1.09−1.31, P = 1.3×10⁻⁴, 2,797 cases and 2,662 controls). SNP rs4784227 is located at 16q12.1, a region identified previously for breast cancer risk among Europeans. The association of this SNP with breast cancer risk remained highly statistically significant in Asians after adjusting for previously-reported SNPs in this region. In vitro experiments using both luciferase reporter and electrophoretic mobility shift assays demonstrated functional significance of this SNP. These results provide strong evidence implicating rs4784227 as a functional causal variant for breast cancer in the locus 16q12.1 and demonstrate the utility of conducting genetic association studies in populations with different genetic architectures.     

Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture

Replication has become the gold standard for assessing statistical results from genome-wide association studies. Unfortunately this replication requirement may cause real genetic effects to be missed. A real result can fail to replicate for numerous reasons including inadequate sample size or variability in phenotype definitions across independent samples. In genome-wide association studies the allele frequencies of polymorphisms may differ due to sampling error or population differences. We hypothesize that some statistically significant independent genetic effects may fail to replicate in an independent dataset when allele frequencies differ and the functional polymorphism interacts with one or more other functional polymorphisms. To test this hypothesis, we designed a simulation study in which case-control status was determined by two interacting polymorphisms with heritabilities ranging from 0.025 to 0.4 with replication sample sizes ranging from 400 to 1600 individuals. We show that the power to replicate the statistically significant independent main effect of one polymorphism can drop dramatically with a change of allele frequency of less than 0.1 at a second interacting polymorphism. We also show that differences in allele frequency can result in a reversal of allelic effects where a protective allele becomes a risk factor in replication studies. These results suggest that failure to replicate an independent genetic effect may provide important clues about the complexity of the underlying genetic architecture. We recommend that polymorphisms that fail to replicate be checked for interactions with other polymorphisms, particularly when samples are collected from groups with distinct ethnic backgrounds or different geographic regions.     

Genetic variants in the RELN gene are associated with otosclerosis in multiple European populations

Otosclerosis is a common form of hearing loss characterized by abnormal bone remodeling in the otic capsule. It is considered a complex disease caused by both genetic and environmental factors. In a previous study, we identified a region on chr7q22.1 located in the RELN gene that is associated with otosclerosis in Belgian–Dutch and French populations. Evidence for allelic heterogeneity was found in this chromosomal region in the form of two independent signals. To confirm this finding, we have completed a replication study that includes four additional populations from Europe (1,141 total samples). Several SNPs in this region replicated in these populations separately. While the power to detect significant association in each population is small, when all four populations are combined, six of seven SNPs replicate and show an effect in the same direction as in the previous populations. We also confirmed the presence of allelic heterogeneity in this region. These data further implicate RELN in the pathogenesis of otosclerosis. Functional research is warranted to determine the pathways through which RELN acts in the pathogenesis of otosclerosis.     

Genome-wide association study of bronchial asthma in the Volga-Ural region of Russia

Bronchial asthma is a chronic inflammatory respiratory disease that is caused by the complex interaction of environmental influences and genetic susceptibility. The first genome-wide association study of bronchial asthma discovered a significant association between SNPs within 17q12-21 genomic region and childhood bronchial asthma in individuals of European descent. Association with this genomic region was then replicated in a number of independent samples of European and Asian descent. Here we report results of the first genome-wide association study of bronchial asthma in the Volga-Ural region of Russia. The present study includes 358 unrelated patients with physician-diagnosed bronchial asthma and 369 disease-free control subjects of different ethnic origin (Russians, Tatars and Bashkirs). Genotyping of DNA samples was carried out using the Illumina Human610 quad array as a part of GABRIEL project (contract from the EC No LSHB-CT-2006-018996). After QC filtering procedures, a final set of 550915 SNPs genotyped in 330 cases and 348 controls was tested for association with bronchial asthma. Five markers on chromosome 17q12-21 showed statistically significant association with bronchial asthma (p < or = 4.79 x 10(-7)). SNP rs7216389 with the strongest evidence for association (p = 1.01 x 10(-7)) is located within the first intron of the GSDMB gene. Evidence for association was stronger with childhood-onset asthma (p = 1.97 x 10(-6) for SNP rs7216389) compared to late-onset asthma (p = 1.8 x 10(-4) for SNP rs7216389). Our replication study using three SNPs within GSDMB gene confirmed association with only childhood-onset asthma. In summary, these results suggest an important role for genetic variants within 17q12-q21 region in the development of bronchial asthma in the Volga-Ural region of Russia.     

A comparison of five methods for selecting tagging single-nucleotide polymorphisms

Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai). In two disease-associated regions from the Genetic Analysis Workshop 14 simulated data, we tested the association between tagSNP genotype and disease over the tagSNP sets chosen by each method for each sampling scheme. This was repeated for 100 replicates to estimate power. The two allelic methods chose essentially all SNPs in the region and had nearly optimal power. The two haplotypic methods chose about half as many SNPs. The haplotypic methods had poor performance compared to the allelic methods in both regions. We expected an improvement in power when the selection sample contained cases; however, there was only moderate variation in power between the sampling approaches for each method. Finally, when compared to the haplotypic methods, the reference method performed as well or worse in the region with ancestral disease haplotype structure.