Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB (Institute for Advanced Biosciences), University Grenoble Alpes, 38000 Grenoble, France.
Int J Environ Res Public Health. 2021 Jan 28;18(3):1138. doi: 10.3390/ijerph18031138.
Asthma is a widespread respiratory disease caused by complex contribution from genetic, environmental and behavioral factors. For several decades, its sensitivity to environmental factors has been investigated in single exposure (or single family of exposures) studies, which might be a narrow approach to tackle the etiology of such a complex multifactorial disease. The emergence of the exposome concept, introduced by C. Wild (2005), offers an alternative to address exposure-health associations. After presenting an overview of the exposome concept, we discuss different statistical approaches used to study the exposome-health associations and review recent studies linking multiple families of exposures to asthma-related outcomes. The few studies published so far on the association between the exposome and asthma-related outcomes showed differences in terms of study design, population, exposome definition and statistical methods used, making their results difficult to compare. Regarding statistical methods, most studies applied successively univariate (Exposome-Wide Association Study (ExWAS)) and multivariate (adjusted for co-exposures) (e.g., Deletion-Substitution-Addition (DSA) algorithm) regression-based models. This latest approach makes it possible to assess associations between a large set of exposures and asthma outcomes. However, it cannot address complex interactions (i.e., of order ≥3) or mixture effects. Other approaches like cluster-based analyses, that lead to the identification of specific profiles of exposure at risk for the studied health-outcome, or mediation analyses, that allow the integration of information from intermediate biological layers, could offer a new avenue in the understanding of the environment-asthma association. European projects focusing on the exposome research have recently been launched and should provide new results to help fill the gap that currently exists in our understanding of the effect of environment on respiratory health.
哮喘是一种由遗传、环境和行为因素复杂共同作用引起的广泛的呼吸道疾病。几十年来，人们一直在对单一暴露（或单一暴露源家族）研究中研究其对环境因素的敏感性，而这种方法可能过于狭隘，难以解决如此复杂的多因素疾病的病因。C. Wild（2005 年）提出的“暴露组学”概念提供了一种解决暴露与健康关联的替代方法。在介绍暴露组学概念概述之后，我们讨论了用于研究暴露组与健康关联的不同统计方法，并回顾了最近将多种暴露源家族与哮喘相关结局联系起来的研究。迄今为止，关于暴露组学与哮喘相关结局之间关联的少数研究在研究设计、人群、暴露组学定义和使用的统计方法方面存在差异，使得它们的结果难以比较。在统计方法方面，大多数研究应用了连续的单变量（暴露组全基因组关联研究（ExWAS））和多变量（调整共同暴露因素）（例如，删除-替换-添加（DSA）算法）回归模型。这种最新方法使得评估大量暴露因素与哮喘结局之间的关联成为可能。然而，它无法解决复杂的相互作用（即，阶数≥3）或混合效应。其他方法，如基于聚类的分析，可以确定与所研究健康结局相关的特定风险暴露特征，或中介分析，可以整合来自中间生物学层的信息，为理解环境与哮喘的关联提供新途径。最近，一些专注于暴露组学研究的欧洲项目已经启动，这些项目应该会提供新的结果，以帮助填补我们对环境对呼吸健康影响的理解方面目前存在的空白。
