Asthma and obesity are two of the most common chronic illnesses worldwide. Epidemiologic studies have consistently demonstrated the comorbidity of these conditions, with longitudinal reports suggesting that obesity is a risk factor for the development of asthma and vice versa. Asthma and obesity have strong genetic components, and twin studies suggest that a potential mechanism explaining the asthma-obesity association is shared genetic predisposition or genetic pleiotropy. However, to date, only a few studies have empirically sought to identify the posited pleiotropic variants. Those studies had limited success in identifying pleiotropic loci and had important methodological constraints, including the use of a candidate-gene approach. Specifically, the candidate-gene approach is limited by our current understanding of the genetic architectures of obesity and asthma and of the mechanistic overlaps between the two diseases. Therefore, our study will search for genetic variants that display pleiotropy for asthma and obesity using a hypothesis-free genome-wide association study approach. Two analytic methods will be employed: (1) a univariate pleiotropy-informed false discovery rate-based framework and (2) a multivariate approach called MultiPhen. Our discovery-phase analyses will utilize existing genotype and phenotype data from the third wave of the Nord-Trndelag Health study (HUNT3). The HUNT3 analytic sample will consist of n=27,712 adults aged 20 years or older [11,285 obese and 1,119 asthmatic cases (of which 639 are both obese and asthmatic), and 15,947 non-asthmatic, normal weight controls]. Genome-wide significant pleiotropic loci identified in HUNT3 will be candidates for replication. Our replication-phase analyses will utilize existing phenotype and whole-exome sequencing data from Dr. Andrew DeWan's FAstGen Study. The FAstGen analytic sample will consist of n=384 adults aged 18 years or older [182 obese and 154 asthmatic cases (of which 81 are both obese and asthmatic) and 129 non- asthmatic, normal weight controls]. In secondary analyses, we will characterize the effects of the candidate pleiotropic loci via mediation analyses. We will also investigate whether the candidate pleiotropic loci are associated with asthma and obesity in children, using data from a subset of HUNT3 subjects who were originally recruited into the first wave of the adolescent component of HUNT (Young-HUNT1) and thus also have phenotype data from adolescence [n=1,202; ages 13-19 years]. Lastly, we will evaluate the performance of our two analytic methods, using replication of pleiotropic signals as a metric of the relative performance of the methods. This will be the first study to investigate pleiotropy for asthma and obesity on a genome-wide scale, using pleiotropy-informed methods and incorporating mediation analyses to characterize pleiotropic effects. Findings from this work will advance our understanding of the mechanistic links between asthma and obesity; provide the first comparison of the performance of our two pleiotropy detection methods using real- world data; and promote specific prevention and treatment efforts for obese asthmatics.
Asthma and obesity are comorbid conditions, and shared genetic predisposition or genetic pleiotropy may account for this comorbidity. This research project aims to identify genetic variants that display pleiotropy for asthma and obesity using a genome-wide association study approach. Knowledge gained from this study will advance our understanding of the mechanistic links between asthma and obesity, as well as promote specific prevention and treatment efforts for obese asthmatics.
