Frontiers in NeuroscienceBioinformaticsPeer-reviewed journal article
Transcriptomic signatures associated with regional cortical thickness changes in Parkinson's disease
Arlin KeoiD, Oleh DzyubachykiD, Jeroen van der GrondiD, Jacobus Johannes van HilteniD, Marcel J. T. ReindersiD, Ahmed Essam MahfouziD
Abstract
Cortical atrophy is a common manifestation in Parkinsons disease, particularly in later disease stages. Here, we investigated patterns of cortical thickness using T1-weighted anatomical MRI data of 149 Parkinsons disease patients and 369 controls. To elucidate the molecular underpinnings of cortical thickness changes in Parkinsons disease, we performed an integrated analysis of brain-wide healthy transcriptomic data from the Allen Human Brain Atlas and neuroimaging features. For this purpose, we used partial least squares regression to identify gene expression patterns correlated with cortical thickness changes. In addition, we identified gene expression patterns underlying the relationship between cortical thickness and clinical domains of Parkinsons disease. Our results show that genes whose expression in the healthy brain is associated with cortical thickness changes in Parkinsons disease are enriched in biological pathways related to sumoylation, regulation of mitotic cell cycle, mitochondrial translation, DNA damage responses, and ER-Golgi traffic. The associated pathways were highly related to each other and all belong to cellular maintenance mechanisms. The expression of genes within most pathways was negatively correlated with cortical thickness changes, showing higher expression in regions associated with decreased cortical thickness (atrophy). On the other hand, sumoylation pathways were positively correlated with cortical thickness changes, showing higher expression in regions with increased cortical thickness (hypertrophy). Our findings suggest that alterations in the balanced interplay of these mechanisms play a role in changes of cortical thickness in Parkinsons disease and possibly influence motor and cognitive functions.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 10
- FWCI
- 0.36
- Field percentile
- top 38%
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