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Atopy was defined as at least one SPT resulting in a wheal size of 3?mm or greater (Table?1). Lung function measurements were performed using a 7L wedge spirometer (Vitalograph Spiropharma, Copenhagen, Denmark) which consisted of at least two maximal expiratory manoeuvres from total lung capacity to residual volume, with the highest consistent forced exhaled volume in 1?second (FEV1) and forced vital capacity (FVC) values used in the analyses (25). DNA was isolated from peripheral blood using standard methods (26, 27). Genotyping of CD14 C-159T, SCGB1A1 A38G, ADRB2 Arg16Gly and ADRB2 Gln27Glu was conducted using previously described methods (14, 28, 29). Genotyping accuracy was confirmed by Succimer DNA sequencing a randomly selected 10% of the population using the ABI Prism BigDye Terminator Kit (PE Biosystems, Foster City, CA, USA). Data were analysed using the statistical package spss (version 11; SPSS Inc., Chicago, IL, USA), and genotype frequencies were assessed for Hardy�CWeinberg equilibrium (30). Regression analysis was used to investigate the relationship between see more candidate genotypes and the various asthma-related phenotypes, adjusting for known confounders, such as age, gender and genetic admixture. Genetic admixture was included in the model as a binary variable, with study individuals either being full Inuit (all four grandparents being Inuit) or admixed (having at least one non-Inuit grandparent). Binary outcomes such as ever asthma, atopy, rhinitis and dermatitis were analysed using binary logistic regression, while linear regression analysis was used to analyse continuous outcomes such as lung function and airway responsiveness. In view of the reported effect of tobacco smoke on the pathogenesis of asthma (31), all asthma RSL3 mouse and pulmonary function regression analyses included tobacco smoke exposure. Furthermore, because of the potential confounding effects of height on pulmonary function, FEV1 and FVC outcomes were adjusted for height. To confirm significant differences in genotype�Cphenotype relationships between Greenland Inuit and Inuit resident in Denmark, data from the two populations were pooled and genotypes by place of residence interaction variables were created and included in the model. The effect of gender and genetic admixture on significant genotype�Cphenotype associations was also further explored by stratifying each population, first by gender and then by genetic admixture, then reanalysed for previously detected associations. P-values of