Asthma is a heterogeneous respiratory disease reflecting distinct pathobiologic 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 of 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 epidemiologic associations between asthma subtypes and those between coexisting diseases and/or 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 analytic approach—genome-wide cross-trait analysis—to determine shared and distinct genetic architecture. The genome-wide cross-trait analysis features in several analytic 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 their limitations. We also make recommendations for future directions: (1) ethnicity-specific asthma GWASs and (2) application of cross-trait methods to multiomics data to dissect the heritability found in GWASs. Finally, these analytic approaches are also applicable to complex and heterogeneous traits beyond asthma.

哮喘是一种异质性呼吸系统疾病，反映了不同的病理生物学机制。这些机制至少部分基于许多其他疾病共有的不同遗传因素，例如过敏性疾病和肥胖症。研究共享的遗传效应可以更好地理解表型相关性的机制，并且较少受到环境因素的混淆。哮喘的大规模全基因组关联研究 (GWAS) 的日益普及使研究人员能够检查对哮喘亚型之间的流行病学关联以及共存疾病和/或特征与哮喘之间的流行病学关联的遗传贡献。研究发现，哮喘亚型之间不仅有共同的遗传成分，而且有不同的遗传成分，表明异质性与不同的遗传有关。这篇综述总结了最近编译的分析方法——全基因组交叉性状分析——以确定共享和不同的遗传结构。全基因组交叉性状分析在几个分析方面具有特征：遗传相关性、交叉性状荟萃分析、孟德尔随机化、多基因风险评分和功能分析。在本文中，我们详细讨论了这些分析可以实现的科学目标、它们的优点和局限性。我们还为未来的方向提出了建议：（1）种族特异性哮喘 GWAS 和（2）将交叉特征方法应用于多组学数据以剖析在 GWAS 中发现的遗传力。最后，这些分析方法也适用于哮喘以外的复杂和异质性状。