Bao Jingxuan, Wen Junhao, Chang Changgee, Mu Shizhuo, Chen Jiong, Shivakumar Manu, Cui Yuhan, Erus Guray, Yang Zhijian, Yang Shu, Wen Zixuan, Zhao Yize, Kim Dokyoon, Duong-Tran Duy, Saykin Andrew J, Zhao Bingxin, Davatzikos Christos, Long Qi, Shen Li
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Graduate Group in Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Nat Commun. 2025 Apr 14;16(1):3524. doi: 10.1038/s41467-025-57636-6.
Brain imaging genomics has manifested considerable potential in illuminating the genetic determinants of human brain structure and function. This has propelled us to develop the GIANT (Genetically Informed brAiN aTlas) that accounts for genetic and neuroanatomical variations simultaneously. Integrating voxel-wise heritability and spatial proximity, GIANT clusters brain voxels into genetically informed regions, while retaining fundamental anatomical knowledge. Compared to conventional (non-genetics) brain atlases, GIANT exhibits smaller intra-region variations and larger inter-region variations in terms of voxel-wise heritability. As a result, GIANT yields increased regional SNP heritability, enhanced polygenicity, and its polygenic risk score explains more brain volumetric variation than traditional neuroanatomical brain atlases. We provide extensive validation to GIANT and demonstrate its neuroanatomical validity, confirming its generalizability across populations with diverse genetic ancestries and various brain conditions. Furthermore, we present a comprehensive genetic architecture of the GIANT regions, covering their functional annotation at the molecular levels, their associations with other complex traits/diseases, and the genetic and phenotypic correlations among GIANT-defined imaging endophenotypes. In summary, GIANT constitutes a brain atlas that captures the complexity of genetic and neuroanatomical heterogeneity, thereby enhancing the discovery power and applicability of imaging genomics investigations in biomedical science.
脑成像基因组学在揭示人类脑结构和功能的遗传决定因素方面已展现出巨大潜力。这促使我们开发了GIANT（基因信息脑图谱），它能同时考虑遗传和神经解剖学变异。GIANT整合了体素水平的遗传力和空间邻近性，将脑体素聚类为基因信息区域，同时保留了基本的解剖学知识。与传统（非遗传学）脑图谱相比，就体素水平的遗传力而言，GIANT在区域内变异较小，而在区域间变异较大。因此，GIANT产生了更高的区域单核苷酸多态性遗传力、更强的多基因性，并且其多基因风险评分比传统神经解剖学脑图谱能解释更多的脑容量变异。我们对GIANT进行了广泛验证，并证明了其神经解剖学有效性，证实了它在具有不同遗传血统和各种脑部状况的人群中的通用性。此外，我们展示了GIANT区域的全面遗传结构，涵盖了它们在分子水平的功能注释、与其他复杂性状/疾病的关联，以及GIANT定义的成像内表型之间的遗传和表型相关性。总之，GIANT构成了一个脑图谱，它捕捉了遗传和神经解剖学异质性的复杂性，从而增强了成像基因组学研究在生物医学科学中的发现能力和适用性。
