Multimodal analysis of gene expression from postmortem brains and blood identifies synaptic vesicle trafficking genes to be associated with Parkinson’s disease

Author:

Gao Xiaoya1,Huang Zifeng2,Feng Cailing2,Guan Chaohao2,Li Ruidong3,Xie Haiting4,Chen Jian4,Li Mingchun4,Que Rongfang2,Deng Bin4,Cao Peihua5,Li Mengyan6,Lu Jianjun7,Huang Yihong8,Li Minzi9,Yang Weihong2,Yang Xiaohua2,Wen Chunyan2,Liang Xiaomei2,Yang Qin4,Chao Yin-Xia10,Chan Ling-Ling10,Yenari Midori A11,Jin Kunlin12,Chaudhuri K Ray13,Zhang Jing14,Tan Eng-King15,Wang Qing16ORCID

Affiliation:

1. Department of Neurology, Zhujiang Hospital, Southern Medical University, China

2. Department of Neurology, Zhujiang Hospital of Southern Medical University, China

3. Genetics, Genomics, and Bioinformatics Program, Department of Botany and Plant Sciences of University of California, USA

4. Department of Neurology of Zhujiang Hospital of Southern Medical University, China

5. Clinical Research Centre of Zhujiang Hospital of Southern Medical University, China

6. Department of Neurology of First Municipal Hospital of Guangzhou, China

7. Laboratory for Neuromodulation of Guangdong Second Provincial General Hospital, China

8. Department of Neurology of Fifth Affiliated Hospital of Southern Medical University, China

9. Department of Neurology, Zhujiang Hospital of Southern Medical University, Guanghzou, China

10. Department of Neurology of National Neuroscience Institute, Singapore General Hospital, Duke-NUS Medical School

11. University of California, San Francisco, USA

12. Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX 76107, USA

13. International Parkinson Foundation Centre of Excellence at Kings College Hospital and research director at Kings College Hospital, and Kings College, Denmark Hill, London, SE5 9RS UK

14. Department of Pathology, University of Washington School of Medicine (USA)

15. Department of Neurology, National Neuroscience Institute, Singapore General Hospital, and a professor in the Duke-NUS Medical School, Singapore

16. Head of Department of Neurology, Zhujiang Hospital, Southern Medical University, China

Abstract

Abstract Objective We aimed to identify key susceptibility gene targets in multiple datasets generated from postmortem brains and blood of Parkinson’s disease (PD) patients and healthy controls (HC). Methods We performed a multitiered analysis to integrate the gene expression data using multiple-gene chips from 244 human postmortem tissues. We identified hub node genes in the highly PD-related consensus module by constructing protein–protein interaction (PPI) networks. Next, we validated the top four interacting genes in 238 subjects (90 sporadic PD, 125 HC and 23 Parkinson’s Plus Syndrome (PPS)). Utilizing multinomial logistic regression analysis (MLRA) and receiver operating characteristic (ROC), we analyzed the risk factors and diagnostic power for discriminating PD from HC and PPS. Results We identified 1333 genes that were significantly different between PD and HCs based on seven microarray datasets. The identified MEturquoise module is related to synaptic vesicle trafficking (SVT) dysfunction in PD (P < 0.05), and PPI analysis revealed that SVT genes PPP2CA, SYNJ1, NSF and PPP3CB were the top four hub node genes in MEturquoise (P < 0.001). The levels of these four genes in PD postmortem brains were lower than those in HC brains. We found lower blood levels of PPP2CA, SYNJ1 and NSF in PD compared with HC, and lower SYNJ1 in PD compared with PPS (P < 0.05). SYNJ1, negatively correlated to PD severity, displayed an excellent power to discriminating PD from HC and PPS. Conclusions This study highlights that SVT genes, especially SYNJ1, may be promising markers in discriminating PD from HCs and PPS.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Natural Science Foundations of Guangdong of China

Initiated Foundation of Zhujiang Hospital

Scientific Research Foundation of Guangzhou

National Medical Research Council

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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