Analytic options for asthma genetics

Covariate-based linkage analysis: application of a propensity score as the single covariate consistently improves power to detect linkage

Successful identification of genetic risk loci for complex diseases has relied on the ability to minimize disease and genetic heterogeneity to increase the power to detect linkage. One means to account for disease heterogeneity is by incorporating covariate data. However, the inclusion of each covariate will add one degree of freedom to the allele sharing based linkage test, which may in fact decrease power. We explore the application of a propensity score, which is typically used in causal inference to combine multiple covariates into a single variable, as a means of allowing for multiple covariates with the addition of only one degree of freedom. In this study, binary trait data, simulated under various models involving genetic and environmental effects, were analyzed using a nonparametric linkage statistic implemented in LODPAL. Power and type I error rates were evaluated. Results suggest that the use of the propensity score to combine multiple covariates as a single covariate consistently improves the power compared to an analysis including no covariates, each covariate individually, or all covariates simultaneously. Type I error rates were inflated for analyses with covariates and increased with increasing number of covariates, but reduced to nominal rates with sample sizes of 1000 families. Therefore, we recommend using the propensity score as a single covariate in the linkage analysis of a trait suspected to be influenced by multiple covariates because of its potential to increase the power to detect linkage, while controlling for the increase in the type I error.

Genetic and environmental interaction in allergy and asthma

Asthma is an inflammatory disorder of the airways involving coordinate up-regulation of T(H)2-type cytokines encoded in a cluster on chromosome 5q(31-33) on T cells and inflammatory cells. There is also a requirement for local airway susceptibility factors that, together with T(H)2 polarization, results in hyperresponsiveness, variable airflow obstruction, and, over time, remodeling of the airway wall. Asthma has strong genetic and environmental components that interact both in the induction and subsequent expression of the disease phenotypes. Multiple genes are involved and probably interact. Whole genome screens are beginning to identify gene-rich regions of special relevance to asthma and atopy, although a novel disease-related gene has yet to be discovered from these. By contrast, there are a plethora of candidate genes whose function in relation to disease pathophysiologic mechanisms and response to treatment are known. Two examples are polymorphisms involving IL-4 receptors and the enzymes controlling cysteinyl leukotriene production. Abnormal signaling between the epithelium, which is in contact with the environment, and the underlying (myo)fibroblasts and dendritic cells indicating reactivation of the epithelial mesenchymal trophic unit, which is involved in fetal lung development and branching, provide a basis for asthma that encapsulates both T(H)2 polarization and airway wall remodeling.