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Cell-Cell Communication Alterations via Intercellular Signaling Pathways in Substantia Nigra of Parkinson's Disease.
Huang, Maoxin; Xu, Liang; Liu, Jin; Huang, Pei; Tan, Yuyan; Chen, Shengdi.
  • Huang M; Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Xu L; Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, China.
  • Liu J; Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Huang P; Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Tan Y; Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Chen S; Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Aging Neurosci ; 14: 828457, 2022.
Article en En | MEDLINE | ID: mdl-35283752
ABSTRACT
Parkinson's disease (PD) is a neurodegenerative movement disorder characterized with dopaminergic neuron (DaN) loss within the substantia nigra (SN). Despite bulk studies focusing on intracellular mechanisms of PD inside DaNs, few studies have explored the pathogeneses outside DaNs, or between DaNs and other cells. Here, we set out to probe the implication of intercellular communication involving DaNs in the pathogeneses of PD at a systemic level with bioinformatics methods. We harvested three online published single-cell/single-nucleus transcriptomic sequencing (sc/snRNA-seq) datasets of human SN (GSE126838, GSE140231, and GSE157783) from the Gene Expression Omnibus (GEO) database, and integrated them with one of the latest integration algorithms called Harmony. We then applied CellChat, the latest cell-cell communication analytic algorithm, to our integrated dataset. We first found that the overall communication quantity was decreased while the overall communication strength was enhanced in PD sample compared with control sample. We then focused on the intercellular communication where DaNs are involved, and found that the communications between DaNs and other cell types via certain signaling pathways were selectively altered in PD, including some growth factors, neurotrophic factors, chemokines, etc. pathways. Our bioinformatics analysis showed that the alteration in intercellular communications involving DaNs might be a previously underestimated aspect of PD pathogeneses with novel translational potential.
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