Journal
NETWORK NEUROSCIENCE
Volume 3, Issue 3, Pages 744-762Publisher
MIT PRESS
DOI: 10.1162/netn_a_00094
Keywords
Allen Human Brain Atlas; mRNA expression; Mapper; fMRI; Dopamine Topological Data Analysis
Categories
Funding
- Imperial NIHR Biomedical Research Centre [NIHR-BRC-P68711]
- Compagnia di San Paolo
- EPSRC [EP/N014529/1]
- IntesaSanpaolo Innovation Center
- NIHR-BRC at South London and Maudsley NHS Foundation Trust and King's College London
- EPSRC [EP/N014529/1] Funding Source: UKRI
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Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges. Author SummaryIn this paper, we described a gene co-expression analysis pipeline that produces networks that we show to be closely related to either brain function and to neurotransmitter pathways. Our results suggest that this pipeline could be developed into a platform enabling the exploration of the effects of physiological and pathological alterations to specific gene sets, including profiling drugs effects.
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