Parkinson's disease is a common neurodegenerative disorder characterized by movement disorders, autonomic dysfunction, and sleep cognitive problems, affecting nearly 6 million people worldwide. Its neuropathological features include the loss of dopaminergic neurons and the aggregation of alpha synuclein within cells. Although neuroinflammation involving glial cells and immune cells is believed to be related to the pathogenesis of Parkinson's disease, further research is needed to determine whether these pathways are associated with sporadic diseases. In addition, the relative contributions of neurons and glial cells in Parkinson's pathology are still unclear. Although single-cell technology, including multi omics analysis, is gradually becoming a popular method for studying neurodegenerative diseases, these tools are only now beginning to be applied in Parkinson's disease research, especially utilizing human brain tissue.

On October 30, 2024, the Zhang Le research group at Yale University published a research paper titled "Single cell transcriptomic and proteomic analysis of Parkinson's disease brains" in Science Translational Medicine. The research team conducted single-cell transcriptomic and proteomic studies using prefrontal cortex brain tissue from late stage Parkinson's disease patients and age-matched control groups. It was found that the pathology of alpha synuclein was negatively correlated with the expression of chaperone proteins in excitatory neurons, and the interaction between neurons and astrocytes was selectively weakened, while neuroinflammation was exacerbated. This study reveals a unique perspective on transcriptional and protein changes associated with Parkinson's disease, and for the first time draws a single-cell map of the prefrontal cortex of the Parkinson's disease brain.Although multiple potential mechanisms have been proposed to explain the etiology of Parkinson's disease, there is currently no effective treatment that can prevent disease progression, partly due to the unclear cellular and molecular pathological structure of Parkinson's disease. In order to gain a deeper understanding of the pathological mechanisms of Parkinson's disease, this study utilized single-cell transcriptome technology to analyze approximately 80000 nuclei from the prefrontal cortex of late stage disease brains, identifying 8 major brain cell types and discovering unique cell types and transcriptome changes in the Parkinson's disease brain. Research has found that patients with Parkinson's disease have an increase in microglia and a significant increase in T cells residing in the brain, indicating the presence of significant neuroinflammation. In addition, the pathology of alpha synuclein in excitatory neurons is negatively correlated with the expression of molecular chaperones, indicating that the decrease in protein folding ability may be a key factor in disease progression. In terms of intercellular interactions, research has found that the interaction between neurons and astrocytes in the brain of Parkinson's disease is significantly reduced, and this reduction in intercellular communication is closely related to the exacerbation of neuroinflammation.

Using GWAS data from the Parkinson's disease genome-wide genotyping project, the research team conducted a multi tissue joint analysis, identified 48 genes, and evaluated the differential expression of these genes in various brain cell types in Parkinson's disease brains. The upregulated genes associated with Parkinson's disease include MAPT, TMEM163, and KAT8, which are mainly enriched in oligodendrocytes, while most downregulated genes are mainly concentrated in excitatory neurons, including LRC37A2, BCL7C, and LRRC37A2. The integrated study of genetics and mononuclear transcriptome analysis revealed the cellular heterogeneity and specificity of GWAS disease risk gene expression in Parkinson's disease.

To further investigate the differences in protein abundance between Parkinson's disease brains and healthy controls, researchers used label free quantitative mass spectrometry to analyze proteomic changes from the same donor, brain region, and tissue. By integrating proteomic and mononuclear transcriptome data, researchers identified 14 modules in the human brain proteomic dataset of Parkinson's disease. Among them, excitatory neuron specific marker genes were enriched in synapse related modules M1, M2, and M11, and SYN2 enrichment was also identified using single-cell RNA velocity analysis, indicating a significant increase in synaptic signals at both RNA and protein levels in the Parkinson's disease brain. Based on co expression analysis, these changes can be attributed to specific cell types identified through single-cell transcriptome analysis of the same Parkinson's disease brain, particularly synaptic pathways that are significantly affected in Parkinson's disease neurons.

Alzheimer's disease and Parkinson's disease are the two most common late onset neurodegenerative diseases, so understanding their similarities and differences at the transcriptome and proteomic levels is of great significance. By comparing this dataset with similar data from the Alzheimer's disease brain, the study revealed common features of the two diseases in glial cells (such as astrocytes and microglia), but showed significant differences at the neuronal level, indicating that Parkinson's disease and Alzheimer's disease have different etiologies. Further research suggests that the commonalities in gene expression profiles among Parkinson's disease, Alzheimer's disease, and other neurodegenerative diseases are mainly concentrated in non neuronal glial cells, particularly astrocytes and microglia, which may reflect similarities in immune activation responses.

This study presents for the first time a single-cell transcriptome and proteomic map of the brains of Parkinson's patients, providing valuable insights into the complex molecular and cellular pathology of late stage Parkinson's disease and demonstrating the role of different cell types in the progression of Parkinson's disease. By combining genomic, transcriptomic, and proteomic data, this study provides important references and valuable resources for developing new treatment strategies for Parkinson's disease in the future. At the same time, it provides a tool for evaluating overall neurodegenerative disease dysfunction, which can be cross compared with similar datasets including motor disorders, cognitive decline, Alzheimer's disease spectrum, and other Tau diseases to help better understand disease mechanisms and provide feasible targets for therapeutic interventions.

Assistant Professor Le Zhang, Associate Professor Sreeganga Chandra, and Professor David Hafler from Yale University School of Medicine are co corresponding authors of this article, and Dr. Zhu Biqing, a joint doctoral student in the laboratories of Hongyu Zhao and Le Zhang, is the first author of this article.