Asthma, atopy, and related phenotypes are heterogeneous complex traits, with both genetic and environmental risk factors. Extensive research has been conducted and over hundred genes have been associated with asthma and atopy phenotypes, but many of these findings have failed to replicate in subsequent studies. To separate true associations from false positives, candidate genes need to be examined in large well-characterized samples, using standardized designs (genotyping, phenotyping and analysis). In an attempt to replicate previous associations we amalgamated the power and resources of four studies and genotyped 5,565 individuals to conduct a genetic association study of 93 previously associated candidate genes for asthma and related phenotypes using the same set of 861 single-nucleotide polymorphisms (SNPs), a common genotyping platform, and relatively harmonized phenotypes. We tested for association between SNPs and the dichotomous outcomes of asthma, atopy, atopic asthma, and airway hyperresponsiveness using a general allelic D. Daley and M. Lemire contributed equally to this manuscript. Electronic supplementary materialThe online version of this article

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We have developed a robust microarray genotyping chip that will help advance studies in genetic epidemiology. In population-based genetic association studies of complex disease, there could be hidden genetic substructure in the study populations, resulting in false-positive associations. Such population stratification may confound efforts to identify true associations between genotype/haplotype and phenotype. Methods relying on genotyping additional null single nucleotide polymorphism (SNP) markers have been proposed, such as genomic control (GC) and structured association (SA), to correct association tests for population stratification. If there is an association of a disease with null SNPs, this suggests that there is a population subset with different genetic background plus different disease susceptibility. Genotyping over 100 null SNPs in the large numbers of patient and control DNA samples that are required in genetic association studies can be prohibitively expensive. We have therefore developed and tested a resequencing chip based on arrayed primer extension (APEX) from over 2000 DNA probe features that facilitate multiple interrogations of each SNP, providing a powerful, accurate, and economical means to simultaneously determine the genotypes at 110 null SNP loci in any individual. Based on 1141 known genotypes from other research groups, our GC SNP chip has an accuracy of 98.5%, including non-calls.

Background: Arrayed primer extension (APEX) is a microarray-based rapid minisequencing methodology that may have utility in 'personalized medicine' applications that involve genetic diagnostics of single nucleotide polymorphisms (SNPs). However, to date there have been few reports that objectively evaluate the assay completion rate, call rate and accuracy of APEX. We have further developed robust assay design, chemistry and analysis methodologies, and have sought to determine how effective APEX is in comparison to leading 'gold-standard' genotyping platforms. Our methods have been tested against industry-leading technologies in two blinded experiments based on Coriell DNA samples and SNP genotype data from the International HapMap Project.