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Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
Jiang, Lin1,2; Peng, Yueheng1,2; He, Runyang1,2; Yang, Qingqing1,2; Yi, Chanlin1,2; Li, Yuqin1,2; Zhu, Bin1,2; Si, Yajing3; Zhang, Tao4; Biswal, Bharat B.5; Yao, Dezhong1,2,6,7; Xiong, Lan8; Li, Fali1,2,7,9; Xu, Peng1,2,7,10,11
2023-06-08
Source PublicationResearch
ISSN2096-5168
Volume6
Abstract

Human cognition is usually underpinned by intrinsic structure and functional neural co-activation in spatially distributed brain regions. Owing to lacking an effective approach to quantifying the covarying of structure and functional responses, how the structural–functional circuits interact and how genes encode the relationships, to deepen our knowledge of human cognition and disease, are still unclear. Here, we propose a multimodal covariance network (MCN) construction approach to capture interregional covarying of the structural skeleton and transient functional activities for a single individual. We further explored the potential association between brain-wide gene expression patterns and structural–functional covarying in individuals involved in a gambling task and individuals with major depression disorder (MDD), adopting multimodal data from a publicly available human brain transcriptomic atlas and 2 independent cohorts. MCN analysis showed a replicable cortical structural–functional fine map in healthy individuals, and the expression of cognition- and disease phenotype-related genes was found to be spatially correlated with the corresponding MCN differences. Further analysis of cell type-specific signature genes suggests that the excitatory and inhibitory neuron transcriptomic changes could account for most of the observed correlation with task-evoked MCN differences. In contrast, changes in MCN of MDD patients were enriched for biological processes related to synapse function and neuroinflammation in astrocytes, microglia, and neurons, suggesting its promising application in developing targeted therapies for MDD patients. Collectively, these findings confirmed the correlations of MCN-related differences with brain-wide gene expression patterns, which captured genetically validated structural–functional differences at the cellular level in specific cognitive processes and psychiatric patients.

DOI10.34133/research.0171
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:001024412000003
PublisherAMER ASSOC ADVANCEMENT SCIENCE, 1200 NEW YORK AVE, NW, WASHINGTON, DC 20005
Scopus ID2-s2.0-85166356659
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorYao, Dezhong; Xiong, Lan; Li, Fali; Xu, Peng
Affiliation1.The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
2.School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
3.School of Psychology, Xinxiang Medical University, Xinxiang, 453003, China
4.School of Science, Xihua University, Chengdu, 610039, China
5.Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, United States
6.School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China
7.Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 2019RU035, China
8.Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
9.Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macao
10.Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, 610041, China
11.Rehabilitation Center, Qilu Hospital of Shandong University, Jinan, 250012, China
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Jiang, Lin,Peng, Yueheng,He, Runyang,et al. Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations[J]. Research, 2023, 6.
APA Jiang, Lin., Peng, Yueheng., He, Runyang., Yang, Qingqing., Yi, Chanlin., Li, Yuqin., Zhu, Bin., Si, Yajing., Zhang, Tao., Biswal, Bharat B.., Yao, Dezhong., Xiong, Lan., Li, Fali., & Xu, Peng (2023). Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations. Research, 6.
MLA Jiang, Lin,et al."Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations".Research 6(2023).
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