Abstract
It has been revealed that intersubject variability (ISV) in intrinsic functional connectivity (FC) is associated with a wide variety of cognitive and behavioral performances. However, the underlying organizational principle of ISV in FC and its related gene transcriptional profiles remain unclear. Using resting-state fMRI data from the Human Connectome Project (299 adult participants) and microarray gene expression data from the Allen Human Brain Atlas, we conducted a transcription-neuroimaging association study to investigate the spatial configurations of ISV in intrinsic FC and their associations with spatial gene transcriptional profiles. We found that the multimodal association cortices showed the greatest ISV in FC, while the unimodal cortices and subcortical areas showed the least ISV. Importantly, partial least squares regression analysis revealed that the transcriptional profiles of genes associated with human accelerated regions (HARs) could explain 31.29% of the variation in the spatial distribution of ISV in FC. The top-related genes in the transcriptional profiles were enriched for the development of the central nervous system, neurogenesis and the cellular components of synapse. Moreover, we observed that the effect of gene expression profile on the heterogeneous distribution of ISV in FC was significantly mediated by the cerebral blood flow configuration. These findings highlighted the spatial arrangement of ISV in FC and their coupling with variations in transcriptional profiles and cerebral blood flow supply.
Original language | English |
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Article number | 118743 |
Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | NeuroImage |
Volume | 245 |
Early online date | 17 Nov 2021 |
DOIs | |
Publication status | Published - 15 Dec 2021 |
Bibliographical note
Funding Information:Funding: This work was supported by the National Natural Science Foundation of China (NSFC) (No. 61772569 , 71701219 ), the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515012148 ), and the Fundamental Research Funds for the Central Universities (No. 19wkzd20 ).
Funding Information:
Data of the current study were provided by a public dataset Human Connectome Project (HCP). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California.
Funding Information:
Funding: This work was supported by the National Natural Science Foundation of China (NSFC) (No. 61772569, 71701219), the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515012148), and the Fundamental Research Funds for the Central Universities (No. 19wkzd20). Data of the current study were provided by a public dataset Human Connectome Project (HCP). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California. Conceptualization: Liangfang Li, Yongbin Wei, Zhengjia Dai; Formal analysis: Liangfang Li, Jinbo Zhang; Funding acquisition: Zhengjia Dai; Investigation: Liangfang Li, Junji Ma, Yangyang Yi; Methodology: Liangfang Li, Yongbin Wei, Jinbo Zhang, Zhengjia Dai; Writing ? original draft: Liangfang Li, Zhengjia Dai; Writing ? review & editing: Liangfang Li, Yongbin Wei, Jinbo Zhang, Junji Ma, Yangyang Yi, Yue Gu, Liman Man Wai Li, Ying Lin, Zhengjia Dai. Data of the current study were obtained from a public dataset Human Connectome Project (HCP). The HCP project was approved by the Institutional Review Board of Washington University in St. Louis. All participants had provided written informed content. The HCP data is publicly available in the database of Human Connectome Project: https://db.humanconnectome.org/data/projects/HCP_1200. The microarray gene expression data is publicly available in Allen Human Brain Atlas dataset: http://human.brain-map.org/static/download. The cerebral blood flow map can be obtained from Satterthwaite et al. (2014). We also uploaded de-identified FC matrices of available participants (https://zenodo.org/record/5607652) in the present study. Detailed documented code for measures calculation, statistical analysis, and figure generation was available with this article (https://github.com/LiangfangLi/ISVGeneExpression).
Publisher Copyright:
© 2021
Funding
Funding: This work was supported by the National Natural Science Foundation of China (NSFC) (No. 61772569 , 71701219 ), the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515012148 ), and the Fundamental Research Funds for the Central Universities (No. 19wkzd20 ). Data of the current study were provided by a public dataset Human Connectome Project (HCP). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California. Funding: This work was supported by the National Natural Science Foundation of China (NSFC) (No. 61772569, 71701219), the Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515012148), and the Fundamental Research Funds for the Central Universities (No. 19wkzd20). Data of the current study were provided by a public dataset Human Connectome Project (HCP). HCP funding was provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute of Mental Health (NIMH), and the National Institute of Neurological Disorders and Stroke (NINDS). HCP data are disseminated by the Laboratory of Neuro Imaging at the University of Southern California. Conceptualization: Liangfang Li, Yongbin Wei, Zhengjia Dai; Formal analysis: Liangfang Li, Jinbo Zhang; Funding acquisition: Zhengjia Dai; Investigation: Liangfang Li, Junji Ma, Yangyang Yi; Methodology: Liangfang Li, Yongbin Wei, Jinbo Zhang, Zhengjia Dai; Writing ? original draft: Liangfang Li, Zhengjia Dai; Writing ? review & editing: Liangfang Li, Yongbin Wei, Jinbo Zhang, Junji Ma, Yangyang Yi, Yue Gu, Liman Man Wai Li, Ying Lin, Zhengjia Dai. Data of the current study were obtained from a public dataset Human Connectome Project (HCP). The HCP project was approved by the Institutional Review Board of Washington University in St. Louis. All participants had provided written informed content. The HCP data is publicly available in the database of Human Connectome Project: https://db.humanconnectome.org/data/projects/HCP_1200. The microarray gene expression data is publicly available in Allen Human Brain Atlas dataset: http://human.brain-map.org/static/download. The cerebral blood flow map can be obtained from Satterthwaite et al. (2014). We also uploaded de-identified FC matrices of available participants (https://zenodo.org/record/5607652) in the present study. Detailed documented code for measures calculation, statistical analysis, and figure generation was available with this article (https://github.com/LiangfangLi/ISVGeneExpression).
Funders | Funder number |
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Guangdong Basic and Applied Basic Research Foundation | 2019A1515012148 |
National Institute of Mental Health | |
National Institute of Neurological Disorders and Stroke | |
National Institute of Dental and Craniofacial Research | |
University of Southern California | |
National Natural Science Foundation of China | 61772569, 71701219 |
National Natural Science Foundation of China | |
Fundamental Research Funds for the Central Universities | 19wkzd20 |
Fundamental Research Funds for the Central Universities |
Keywords
- Functional connectivity
- Gene expression
- Intersubject variability
- Metabolism
- Resting-state fMRI