Neuroreport · 2026
A voxel-level degree centrality study in Parkinson's disease and the correlation with transcriptomes.
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He Yuan-Zhi, Li Si-Xian, Wang Hai-Yu, Wen Zhi
Аннотация
BACKGROUND: Altered degree centrality, a measure of brain network connectivity, has been linked to Parkinson's disease symptoms. However, it is unclear whether regional degree centrality differences between Parkinson's disease patients and healthy controls relate to spatial patterns of gene expression. The associated biological pathways and cell types also remain to be clarified.
OBJECTIVE: To investigate regional degree centrality differences between Parkinson's disease and healthy controls, and to explore their associations with brain-wide gene expression, enriched pathways, and specific cell types.
METHODS: Voxel-wise degree centrality maps were computed for each participant and compared between groups using two-sample t-tests. Partial least squares (PLS) regression was applied to link degree centrality alterations to gene expression data from the Allen Human Brain Atlas. Enrichment analyses were conducted using Metascape, and cell-type specificity was assessed to identify key cellular contributors.
RESULTS: Parkinson's disease patients showed significant degree centrality alterations relative to controls. These changes were spatially correlated with a gene expression pattern captured by PLS component 2 (PLS2). Enrichment analysis revealed that the associated genes were predominantly expressed in astrocytes, excitatory neurons, and inhibitory neurons, and were involved in synapse organization.
CONCLUSION: This study links functional network disruptions in Parkinson's disease to specific transcriptomic signatures, highlighting astrocytes and neurons as key contributors. These findings offer insight into the cellular and molecular mechanisms underlying brain connectivity changes in Parkinson's disease.
OBJECTIVE: To investigate regional degree centrality differences between Parkinson's disease and healthy controls, and to explore their associations with brain-wide gene expression, enriched pathways, and specific cell types.
METHODS: Voxel-wise degree centrality maps were computed for each participant and compared between groups using two-sample t-tests. Partial least squares (PLS) regression was applied to link degree centrality alterations to gene expression data from the Allen Human Brain Atlas. Enrichment analyses were conducted using Metascape, and cell-type specificity was assessed to identify key cellular contributors.
RESULTS: Parkinson's disease patients showed significant degree centrality alterations relative to controls. These changes were spatially correlated with a gene expression pattern captured by PLS component 2 (PLS2). Enrichment analysis revealed that the associated genes were predominantly expressed in astrocytes, excitatory neurons, and inhibitory neurons, and were involved in synapse organization.
CONCLUSION: This study links functional network disruptions in Parkinson's disease to specific transcriptomic signatures, highlighting astrocytes and neurons as key contributors. These findings offer insight into the cellular and molecular mechanisms underlying brain connectivity changes in Parkinson's disease.