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

2020 ◽  
Author(s):  
Xiaoya Gao ◽  
Zifeng Huang ◽  
Cailing Feng ◽  
Chaohao Guan ◽  
Ruidong Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Synaptic Vesicle ◽  
Multinomial Logistic Regression ◽  
Vesicle Trafficking ◽  
Susceptibility Gene ◽  
Blood Levels ◽  
Ppi Networks ◽  
Postmortem Brains

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.

scholarly journals Integration of eQTL and Parkinson’s disease GWAS data implicates 11 disease genes

2019 ◽  
Author(s):  
Demis A. Kia ◽  
David Zhang ◽  
Sebastian Guelfi ◽  
Claudia Manzoni ◽  
Leon Hubbard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Candidate Genes ◽  
Gwas Data ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Protein Ubiquitination ◽  
Ppi Networks ◽  
Core Proteins

AbstractSubstantial genome-wide association study (GWAS) work in Parkinson’s disease (PD) has led to an increasing number of loci shown reliably and robustly to be associated with the increased risk of the disease. Prioritising causative genes and pathways from these studies has proven problematic. Here, we present a comprehensive analysis of PD GWAS data with expression and methylation quantitative trait loci (eQTL/mQTL) using Colocalisation analysis (Coloc) and transcriptome-wide association analysis (TWAS) to uncover putative gene expression and splicing mechanisms driving PD GWAS signals. Candidate genes were further characterised by determining cell-type specificity, weighted gene co-expression (WGNCA) and protein-protein interaction (PPI) networks.Gene-level analysis of expression revealed 5 genes (WDR6, CD38, GPNMB, RAB29, TMEM163) that replicated using both Coloc and TWAS analyses in both GTEx and Braineac expression datasets. A further 6 genes (ZRANB3, PCGF3, NEK1, NUPL2, GALC, CTSB) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell-types compared to neurons. The WGNCA analysis showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes related with protein ubiquitination (protein ubiquitination (p=7.47e-10) and ubiquitin-dependent protein catabolic process (p = 2.57e-17) in nucleus accumbens, caudate and putamen, while TMEM163 and ZRANB3 were both important in modules indicating regulation of signalling (p=1.33e-65] and cell communication (p=7.55e-35) in the frontal cortex and caudate respectively. PPI analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known Mendelian PD and parkinsonism proteins than would be expected by chance. The proteins core proteins this network were enriched for regulation of the ERBB receptor tyrosine protein kinase signalling pathways.Together, these results point to a number of candidate genes and pathways that are driving the associations observed in PD GWAS studies.

scholarly journals Multimodal Analysis Reveals New Genetic Effectors in Parkinson'S Disease-Related Gene LRRK2 Gly2019Ser Mutation

2021 ◽  
Author(s):  
Longping Yao ◽  
Shizhong Zhang
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Interaction Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
In The Wild ◽  
Potential Factors ◽  
Wild Group

Abstract BackgroundMutations in the LRRK2 gene, which encodes leucine-rich repeat kinase 2 (LRRK2), generate one of the most prevalent monogenic forms of Parkinson's disease (PD). Patients with autosomal dominant PD and apparent sporadic PD, who are clinically indistinguishable from those with idiopathic PD, are found to have LRRK2 mutations, particularly the most prevalent variant Gly2019Ser. Nonetheless, potential effectors of Gly2019Ser remain unknown.MethodsWe used the GEO database to undertake and evaluate a multitiered bioinformatic investigation to look into the gene expression implicated in the development of Parkinson's disease. Individual differences in gene expression were then confirmed in whole blood samples collected in the clinic. These genetic factors were also subjected to an interaction analysis and prediction. ResultsIn total, 607 genes in the LRRK2 Gly2019Ser mutation group expressed differently from those in the wild group. The following 10 top hub genes were discovered in protein-protein interaction (PPI) networks: CD44, CTGF, THBS1, VEGFA, SPP1, EGF, VCAM1, MMP3, CXCR4, and LOX. The gene expression of CD44, CTGF, THBS1, SPP1, EGF, and LOX was considerably higher in the LRRK2 Gly2019Ser mutant group than in the LRRK2 wild group. Meanwhile, CXCR4 gene expression in the LRRK2 Gly2019Ser mutant group was significantly lower than in the LRRK2 wild group. We then confirmed the expression of the hub genes in LRRK2 Gly2019Ser mutated iPSC-induced DA cells. As a result, the levels of CD44, CTGF, THBS1, VEGFA, SPP1 were positively correlated to the mutation of LRRK2, displayed promising effectors for discriminating the pathogenesis of PD. ConclusionsWe identified CD44, CTGF, THBS1, VEGFA, and SPP1 as the potential genetic effectors responding to the mutation of LRRK2. They could be a promising mechanism for discriminating the PD and potential factors contributing to the disease's development.

scholarly journals Parkinson's Disease-Associated LRRK2 Hyperactive Kinase Mutant Disrupts Synaptic Vesicle Trafficking in Ventral Midbrain Neurons

2017 ◽  
Vol 37 (47) ◽  
pp. 11366-11376 ◽  
Author(s):  
Ping-Yue Pan ◽  
Xianting Li ◽  
Jing Wang ◽  
James Powell ◽  
Qian Wang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Synaptic Vesicle ◽  
Vesicle Trafficking ◽  
Ventral Midbrain ◽  
Midbrain Neurons

Synaptic vesicle trafficking and Parkinson's disease

2011 ◽  
Vol 72 (1) ◽  
pp. 134-144 ◽  
Author(s):  
Giovanni Esposito ◽  
Fernandes Ana Clara ◽  
Patrik Verstreken
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Synaptic Vesicle ◽  
Vesicle Trafficking

A susceptibility gene for late-onset idiopathic Parkinson's disease

2002 ◽  
Vol 52 (5) ◽  
pp. 549-555 ◽  
Author(s):  
Andrew A. Hicks ◽  
Hjörvar Pétursson ◽  
Thorlákur Jónsson ◽  
Hreinn Stefánsson ◽  
Hrefna S. Jóhannsdóttir ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Late Onset ◽  
Susceptibility Gene ◽  
Idiopathic Parkinson’S Disease ◽  
Idiopathic Parkinson's Disease
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