Regional gene expression patterns are associated with task-specific brain activation during reward and emotion processing measured with functional MRI
2022-07-07 | journal article; research paper. A publication with affiliation to the University of Göttingen.
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Regional gene expression patterns are associated with task-specific brain activation during reward and emotion processing measured with functional MRI
Komorowski, A.; Murgaš, M.; Vidal, R. ; Singh, A. ; Gryglewski, G.; Kasper, S. & Wiltfang, J. et al. (2022)
Human Brain Mapping,. DOI: https://doi.org/10.1002/hbm.26001
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Details
- Authors
- Komorowski, Arkadiusz; Murgaš, Matej; Vidal, Ramon ; Singh, Aditya ; Gryglewski, Gregor; Kasper, Siegfried; Wiltfang, Jens ; Lanzenberger, Rupert; Goya-Maldonado, Roberto
- Abstract
- The exploration of the spatial relationship between gene expression profiles and task-evoked response patterns known to be altered in neuropsychiatric disorders, for example depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in cellular localization processes, metabolism, translation, and synapse regulation. An overlap of these genes with risk genes from major depressive disorder genome-wide association studies revealed the involvement of the master regulators TCF4 and PAX6 in emotion and reward processing. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.
- Issue Date
- 7-July-2022
- Journal
- Human Brain Mapping
- ISSN
- 1065-9471; 1097-0193
- eISSN
- 1097-0193
- Language
- English
- Sponsor
- Open-Access-Publikationsfonds 2022