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

Abstract

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 clinical PD patients and showed the expression of MDH2 was significantly different compared with healthy control. Besides, we also identified the expression of G6PD, GRID2, RIPK2, CUL4B, BCL6, MRPS31, GPI, and MAP 2 K1 were all significantly increased, and levels of MAPK, ELAVL1, RAB14, KLF9, ARF1, ARFGAP1, ATG7, ABCA7, SFT2D2, E2F2, MAPK7, and UHRF1 were all significantly decreased in PD. Among them, to our knowledge, we presently have the most recent and conclusive evidence that GRID2, RIPK2, CUL4B, E2F2, and ABCA7 are possible PD indicators. We confirmed several genetic factors which may be involved in the pathogenesis of PD. They could be promising markers for discriminating the PD and potential factors that may affect PD development.