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Asthma is a chronic and genetically complex respiratory disease that affects over 300 million people worldwide. Here, we report a genome-wide analysis for asthma using data from the UK Biobank and the Trans-National Asthma Genetic Consortium. We identify 66 previously unknown asthma loci and demonstrate that the susceptibility alleles in these regions are, either individually or as a function of cumulative genetic burden, associated with risk to a greater extent in men than women. Bioinformatics analyses prioritize candidate causal genes at 52 loci, including CD52, and demonstrate that asthma-associated variants are enriched in regions of open chromatin in immune cells. Lastly, we show that a murine anti-CD52 antibody mimics the immune cell-depleting effects of a clinically used human anti-CD52 antibody and reduces allergen-induced airway hyperreactivity in mice. These results further elucidate the genetic architecture of asthma and provide important insight into the immunological and sex-specific relevance of asthma-associated risk variants.
Sex-specific Genetic Determinants of Cardiometabolic Traits
Although cardiovascular disease (CVD) has traditionally been viewed as a disease of men, new evidence suggests the existence of distinct differences in the risk factors, development, and outcomes between the two sexes. For example, our recent studies have revealed that the genetic factors for several intermediate cardiometabolic traits, such as blood levels of certain amino acids (i.e. glycine) and lipids (i.e. ceramides), represent potentially novel sex-specific mechanisms for CVD. This project proposes to build on our observations using genetic and clinical cardiometabolic data from the UK Biobank. By helping to determine the genetic basis of CVD, our proposed analyses could identify novel therapeutic targets and/or risk stratification tools. Thus, these studies would be consistent with UK Biobank's stated purpose to improve the prevention, diagnosis and treatment of a wide range of illnesses, including heart diseases. The genotype and specific clinical data we request from all UK Biobank participants will be used for statistical analyses. These large-scale computations will specifically test for genetic associations in men and women separately. We will also carry out these sex-stratified tests with the genetic risk factors all combined together in what is typically referred to as `genetic risk score analysis.` Full cohort for genotypes and clinical binary and quantitative CVD traits.