BMC Neuroscience BioMed Central Poster presentation (original) (raw)

Characterizing the Expression Patterns of Parkinson’s Disease Associated Genes

Frontiers in Neuroscience, 2021

BackgroundThe expression pattern represents a quantitative phenotype that provides an in-depth view of the molecular mechanism in Parkinson’s disease (PD); however, the expression patterns of PD-associated genes (PAGs) and their relation to age at onset (AAO) remain unclear.MethodsThe known PD-causing genes and PD-risk genes, which were collected from latest published authoritative meta-analysis, were integrated as PAGs. The expression data from Genotype-Tissue Expression database, Allen Brian Map database, and BrainSpan database, were extracted to characterize the tissue specificity, inhibitory-excitatory neuron expression profile, and spatio-temporal expression pattern of PAGs, respectively. The AAO information of PD-causing gene was download from Gene4PD and MDSgene database.ResultsWe prioritized 107 PAGs and found that the PAGs were more likely to be expressed in brain-related tissues than non-brain tissues and that more PAGs had higher expression levels in excitatory neurons th...

A Multivariate Biomarker for Parkinson's Disease

ArXiv, 2016

In this study, we executed a genomic analysis with the objective of selecting a set of genes (possibly small) that would help in the detection and classification of samples from patients affected by Parkinson Disease. We performed a complete data analysis and during the exploratory phase, we selected a list of differentially expressed genes. Despite their association with the diseased state, we could not use them as a biomarker tool. Therefore, our research was extended to include a multivariate analysis approach resulting in the identification and selection of a group of 20 genes that showed a clear potential in detecting and correctly classify Parkinson Disease samples even in the presence of other neurodegenerative disorders. We will analyze the microarray expression data of patients affected by Parkinson's disease (PD) with the goal of identifying a biomarker for this condition. The expression dataset used in this research is the Parkinson_105_from_CEL.xls file (1) containin...

Bioinformatic Analysis of Genetic Factors from Human Blood Samples and Postmortem Brains in Parkinson’s Disease

Oxidative Medicine and Cellular Longevity

Parkinson’s disease (PD) is one of the most prevalent neurodegenerative disorders characterized by motor and nonmotor symptoms due to the selective loss of midbrain dopaminergic neurons. Pharmacological and surgical interventions have not been possible to cure PD; however, the cause of neurodegeneration remains unclear. Here, we performed and tested a multitiered bioinformatic analysis using the GEO and Proteinexchange database to investigate the gene expression involved in the pathogenesis of PD. Then we further validated individual differences in gene expression in whole blood samples that we collected in the clinic. We also made an interaction analysis and prediction for these genetic factors. There were in all 1045 genes expressing differently in PD compared with the healthy control group. Protein-protein interaction (PPI) networks showed 10 top hub genes: ACO2, MDH2, SDHA, ATP5A1, UQCRC2, PDHB, SUCLG1, NDUFS3, UQCRC1, and ATP5C1. We validated the ten hub gene expression in clin...