Arnatkeviciute Aurina, Markello Ross D, Fulcher Ben D, Misic Bratislav, Fornito Alex
Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia.
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
Biol Psychiatry. 2023 Mar 1;93(5):391-404. doi: 10.1016/j.biopsych.2022.10.016. Epub 2022 Nov 5.
Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.
现代全脑转录图谱为研究脑组织结构的分子关联提供了前所未有的机会，这些关联可通过非侵入性神经成像进行量化。然而，将神经成像数据与转录组学测量相结合并非易事，需要仔细考虑才能做出有效的推断。在本文中，我们回顾了近期的研究工作，探讨了各种方法选择如何影响成像转录组分析的三个主要阶段，包括：1）转录图谱数据的处理；2）将转录测量与独立得出的神经成像表型相关联；3）通过基因富集分析评估已确定关联的功能意义。我们的目标是促进这一快速发展领域中标准化和可重复方法的开发。我们确定了方法变异性的来源、可能影响研究结果的关键选择，以及减轻假阳性和/或虚假结果的注意事项。最后，我们概述了在所有三个分析阶段都实施当前最佳实践程序的免费开源工具箱。
