Zhao Xingzhong, Yang Anyi, Zhang Zi-Chao, Yang Yucheng T, Zhao Xing-Ming
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.
Brief Bioinform. 2023 Mar 19;24(2). doi: 10.1093/bib/bbad060.
Brain imaging genomics is an emerging interdisciplinary field, where integrated analysis of multimodal medical image-derived phenotypes (IDPs) and multi-omics data, bridging the gap between macroscopic brain phenotypes and their cellular and molecular characteristics. This approach aims to better interpret the genetic architecture and molecular mechanisms associated with brain structure, function and clinical outcomes. More recently, the availability of large-scale imaging and multi-omics datasets from the human brain has afforded the opportunity to the discovering of common genetic variants contributing to the structural and functional IDPs of the human brain. By integrative analyses with functional multi-omics data from the human brain, a set of critical genes, functional genomic regions and neuronal cell types have been identified as significantly associated with brain IDPs. Here, we review the recent advances in the methods and applications of multi-omics integration in brain imaging analysis. We highlight the importance of functional genomic datasets in understanding the biological functions of the identified genes and cell types that are associated with brain IDPs. Moreover, we summarize well-known neuroimaging genetics datasets and discuss challenges and future directions in this field.
脑成像基因组学是一个新兴的跨学科领域,它对多模态医学图像衍生表型(IDP)和多组学数据进行综合分析,弥合宏观脑表型与其细胞和分子特征之间的差距。这种方法旨在更好地解释与脑结构、功能和临床结果相关的遗传结构和分子机制。最近,来自人类大脑的大规模成像和多组学数据集的可用性为发现导致人类脑结构和功能IDP的常见遗传变异提供了机会。通过与来自人类大脑的功能多组学数据进行综合分析,已确定一组关键基因、功能基因组区域和神经元细胞类型与脑IDP显著相关。在这里,我们回顾了多组学整合在脑成像分析中的方法和应用的最新进展。我们强调功能基因组数据集在理解与脑IDP相关的已识别基因和细胞类型的生物学功能方面的重要性。此外,我们总结了著名的神经成像遗传学数据集,并讨论了该领域的挑战和未来方向。