Sarigiannis Dimosthenis, Karakitsios Spyros, Anesti Ourania, Stem Arthur, Valvi Damaskini, Sumner Susan C J, Chatzi Leda, Snyder Michael P, Thompson David C, Vasiliou Vasilis
National Hellenic Research Foundation, 48 Vassileos Constantinou Avenue, Athens, 11635, Greece.
Department of Chemical Engineering, Environmental Engineering Laboratory, Aristotle University of Thessaloniki, University Campus, Thessaloniki, 54124, Greece.
Hum Genomics. 2025 Apr 30;19(1):48. doi: 10.1186/s40246-025-00761-6.
Understanding the interplay between genetic predisposition and environmental and lifestyle exposures is essential for advancing precision medicine and public health. The exposome, defined as the sum of all environmental exposures an individual encounters throughout their lifetime, complements genomic data by elucidating how external and internal exposure factors influence health outcomes. This treatise highlights the emerging discipline of translational exposomics that integrates exposomics and genomics, offering a comprehensive approach to decipher the complex relationships between environmental and lifestyle exposures, genetic variability, and disease phenotypes. We highlight cutting-edge methodologies, including multi-omics technologies, exposome-wide association studies (EWAS), physiology-based biokinetic modeling, and advanced bioinformatics approaches. These tools enable precise characterization of both the external and the internal exposome, facilitating the identification of biomarkers, exposure-response relationships, and disease prediction and mechanisms. We also consider the importance of addressing socio-economic, demographic, and gender disparities in environmental health research. We emphasize how exposome data can contextualize genomic variation and enhance causal inference, especially in studies of vulnerable populations and complex diseases. By showcasing concrete examples and proposing integrative platforms for translational exposomics, this work underscores the critical need to bridge genomics and exposomics to enable precision prevention, risk stratification, and public health decision-making. This integrative approach offers a new paradigm for understanding health and disease beyond genetics alone.
了解遗传易感性与环境及生活方式暴露之间的相互作用对于推进精准医学和公共卫生至关重要。暴露组被定义为个体一生中所接触的所有环境暴露的总和，它通过阐明外部和内部暴露因素如何影响健康结果来补充基因组数据。本论文重点介绍了整合暴露组学和基因组学的新兴转化暴露组学学科，提供了一种全面的方法来解读环境和生活方式暴露、基因变异性与疾病表型之间的复杂关系。我们重点介绍了前沿方法，包括多组学技术、全暴露组关联研究（EWAS）、基于生理学的生物动力学建模以及先进的生物信息学方法。这些工具能够精确表征外部和内部暴露组，有助于识别生物标志物、暴露 - 反应关系以及疾病预测和机制。我们还考虑了在环境卫生研究中解决社会经济、人口统计学和性别差异的重要性。我们强调暴露组数据如何能够将基因组变异置于具体情境中并增强因果推断，特别是在弱势群体和复杂疾病的研究中。通过展示具体实例并提出转化暴露组学的整合平台，这项工作强调了将基因组学和暴露组学联系起来以实现精准预防、风险分层和公共卫生决策的迫切需求。这种整合方法为超越单纯遗传学理解健康和疾病提供了一种新范式。
