Asthma is a heterogeneous respiratory disease reflecting distinct pathobiological mechanisms. These mechanisms are based, at least partly, on different genetic factors shared by many other conditions, such as allergic diseases and obesity. Investigating the shared genetic effects enables better understanding the mechanisms of phenotypic correlations and is less subject to confounding by environmental factors. The increasing availability of large-scale genome-wide association study (GWAS) for asthma has enabled researchers to examine the genetic contributions to the epidemiological associations between asthma subtypes, and those between coexisting diseases/traits and asthma. Studies have found not only shared but also distinct genetic components between asthma subtypes, indicating that the heterogeneity is related to distinct genetics. This review summarizes a recently compiled analytical approach-genome-wide cross-trait analysis-to determine shared and distinct genetic architecture. The genome-wide cross-trait analysis features in several analytical aspects: genetic correlation, cross-trait meta-analysis, Mendelian randomization, polygenic risk score and functional analysis. In this article, we discuss in detail the scientific goals that can be achieved by these analyses, their advantages and limitations. We also make recommendations for future directions: 1) ethnicity-specific asthma GWASs, and 2) application of cross-trait methods to multi-omics data to dissect the heritability found in GWAS. Finally, these analytical approaches are also applicable to complex and heterogeneous traits beyond asthma.
Copyright © 2020. Published by Elsevier Inc.