Department of Psychiatry, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada; Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.
Department of Psychiatry, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada; Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (ASTAR), Singapore; Brain - Body Initiative, Agency for Science, Technology and Research (ASTAR), Singapore.
Neurobiol Dis. 2023 Mar;178:106008. doi: 10.1016/j.nbd.2023.106008. Epub 2023 Jan 20.
We explore how functional genomics approaches that integrate datasets from human and non-human model systems can improve our understanding of the effect of gene-environment interplay on the risk for mental disorders. We start by briefly defining the G-E paradigm and its challenges and then discuss the different levels of regulation of gene expression and the corresponding data existing in humans (genome wide genotyping, transcriptomics, DNA methylation, chromatin modifications, chromosome conformational changes, non-coding RNAs, proteomics and metabolomics), discussing novel approaches to the application of these data in the study of the origins of mental health. Finally, we discuss the multilevel integration of diverse types of data. Advance in the use of functional genomics in the context of a G-E perspective improves the detection of vulnerabilities, informing the development of preventive and therapeutic interventions.
我们探讨了如何将整合人类和非人类模型系统数据集的功能基因组学方法应用于改善我们对基因-环境相互作用对精神障碍风险影响的理解。我们首先简要定义 G-E 范式及其挑战，然后讨论基因表达的不同调节水平及其在人类中存在的相应数据（全基因组基因分型、转录组学、DNA 甲基化、染色质修饰、染色体构象变化、非编码 RNA、蛋白质组学和代谢组学），讨论将这些数据应用于研究心理健康起源的新方法。最后，我们讨论了不同类型数据的多层次整合。在 G-E 视角下使用功能基因组学的进步提高了对脆弱性的检测，为预防和治疗干预措施的发展提供了信息。
