A genetically informed brain atlas for enhancing brain imaging genomics

Jingxuan Bao, Junhao Wen, Changgee Chang, Shizhuo Mu, Jiong Chen, Manu Shivakumar, Yuhan Cui, Guray Erus, Zhijian Yang, Shu Yang, Zixuan Wen, Yize Zhao, Dokyoon Kim, Duy Duong-Tran, Andrew J. Saykin, Bingxin Zhao, Christos Davatzikos, Qi Long () and Li Shen ()
Additional contact information
Jingxuan Bao: University of Pennsylvania Perelman School of Medicine
Junhao Wen: Columbia University
Changgee Chang: Indiana University School of Medicine
Shizhuo Mu: University of Pennsylvania Perelman School of Medicine
Jiong Chen: University of Pennsylvania Perelman School of Medicine
Manu Shivakumar: University of Pennsylvania Perelman School of Medicine
Yuhan Cui: University of Pennsylvania Perelman School of Medicine
Guray Erus: University of Pennsylvania Perelman School of Medicine
Zhijian Yang: University of Pennsylvania Perelman School of Medicine
Shu Yang: University of Pennsylvania Perelman School of Medicine
Zixuan Wen: University of Pennsylvania Perelman School of Medicine
Yize Zhao: Yale University School of Public Health
Dokyoon Kim: University of Pennsylvania Perelman School of Medicine
Duy Duong-Tran: University of Pennsylvania Perelman School of Medicine
Andrew J. Saykin: Indiana University
Bingxin Zhao: University of Pennsylvania
Christos Davatzikos: University of Pennsylvania Perelman School of Medicine
Qi Long: University of Pennsylvania Perelman School of Medicine
Li Shen: University of Pennsylvania Perelman School of Medicine

Nature Communications, 2025, vol. 16, issue 1, 1-18

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-57636-6

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