Disrupted myelination network in the cingulate cortex of Parkinson's disease. Issue 3 (8th April 2022)

• Record Type: Journal Article
• Authors: Xie, Song; Yang, Jiajun; Huang, Shenghui; Fan, Yuanlan; Xu, Tao; He, Jiangshuang; Guo, Jiahao; Ji, Xiang; Wang, Zhibo; Li, Peijun; Chen, Jiangfan; Zhang, Yi
• Is Part Of: IET systems biology. Volume 16:Issue 3/4(2022)
• Page Start: 98
• Page End: 119
• Publication Date: 2022-04-08
• Subjects: cingulate cortex -- demyelination -- gene regulatory network -- parkinson's disease; Systems biology -- Periodicals; Cell physiology -- Periodicals; Biological systems -- Mathematical models -- Periodicals; Genetics -- Mathematical models -- Periodicals; Computational biology -- Periodicals; 573
• DOI: 10.1049/syb2.12043
• Languages: English
• ISSNs: 1751-8849

Abstract

Abstract: The cingulate cortex is part of the conserved limbic system, which is considered as a hub of emotional and cognitive control. Accumulating evidence suggested that involvement of the cingulate cortex is significant for cognitive impairment of Parkinson's disease (PD). However, mechanistic studies of the cingulate cortex in PD pathogenesis are limited. Here, transcriptomic and regulatory network analyses were conducted for the cingulate cortex in PD. Enrichment and clustering analyses showed that genes involved in regulation of membrane potential and glutamate receptor signalling pathway were upregulated. Importantly, myelin genes and the oligodendrocyte development pathways were markedly downregulated, indicating disrupted myelination in PD cingulate cortex. Cell‐type‐specific signatures revealed that myelinating oligodendrocytes were the major cell type damaged in the PD cingulate cortex. Furthermore, downregulation of myelination pathways in the cingulate cortex were shared and validated in another independent RNAseq cohort of dementia with Lewy bodies (DLB). In combination with ATACseq data, gene regulatory networks (GRNs) were further constructed for 32 transcription factors (TFs) and 466 target genes among differentially expressed genes (DEGs) using a tree‐based machine learning algorithm. Several transcription factors, including Olig2, Sox8, Sox10, E2F1, and NKX6‐2, were highlighted as key nodes in a sub‐network, which control many overlapping downstream targets associated with myelin formation and gliogenesis. In addition, the authors have validated a subset of DEGs by qPCRs in two PD mouse models. Notably, seven of these genes, TOX3, NECAB2 NOS1, CAPN3, NR4A2, E2F1 and FOXP2, have been implicated previously in PD or neurodegeneration and are worthy of further studies as novel candidate genes. Together, our findings provide new insights into the role of remyelination as a promising new approach to treat PD after demyelination.