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Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249784/
https://www.ncbi.nlm.nih.gov/pubmed/37303601
http://dx.doi.org/10.34133/research.0171
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author 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
author_facet 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
author_sort Jiang, Lin
collection PubMed
description 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.
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spelling pubmed-102497842023-06-09 Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations 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 Research (Wash D C) Research Article 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. AAAS 2023-06-08 /pmc/articles/PMC10249784/ /pubmed/37303601 http://dx.doi.org/10.34133/research.0171 Text en Copyright © 2023 Lin Jiang et al. https://creativecommons.org/licenses/by/4.0/Exclusive licensee Science and Technology Review Publishing House. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0(CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
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
Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title_full Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title_fullStr Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title_full_unstemmed Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title_short Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations
title_sort transcriptomic and macroscopic architectures of multimodal covariance network reveal molecular–structural–functional co-alterations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249784/
https://www.ncbi.nlm.nih.gov/pubmed/37303601
http://dx.doi.org/10.34133/research.0171
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