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Gene Expression Profiling of Post Mortem Midbrain of Parkinson's Disease Patients and Healthy Controls.

Michele SalemiMaria RavoGiuseppe LanzaFrancesca A SchillaciGiovanna Maria VentolaGiovanna MarcheseMaria Grazia SalluzzoGraziella CappellettiRaffaele Ferri
Published in: International journal of molecular sciences (2024)
Parkinson's disease (PD) stands as the most prevalent degenerative movement disorder, marked by the degeneration of dopaminergic neurons in the substantia nigra of the midbrain. In this study, we conducted a transcriptome analysis utilizing post mortem mRNA extracted from the substantia nigra of both PD patients and healthy control (CTRL) individuals. Specifically, we acquired eight samples from individuals with PD and six samples from CTRL individuals, with no discernible pathology detected in the latter group. RNA sequencing was conducted using the TapeStation 4200 system from Agilent Technologies. A total of 16,148 transcripts were identified, with 92 mRNAs displaying differential expression between the PD and control groups. Specifically, 33 mRNAs were significantly up-regulated, while 59 mRNAs were down-regulated in PD compared to the controls. The identification of statistically significant signaling pathways, with an adjusted p -value threshold of 0.05, unveiled noteworthy insights. Specifically, the enriched categories included cardiac muscle contraction (involving genes such as ATPase Na + /K + transporting subunit beta 2 ( ATP1B2 ), solute carrier family 8 member A1 ( SLC8A1 ), and cytochrome c oxidase subunit II ( COX2 )), GABAergic synapse (involving GABA type A receptor-associated protein-like 1 ( GABARAPL1 ), G protein subunit beta 5 ( GNB5 ), and solute carrier family 38 member 2 ( SLC38A2 ), autophagy (involving GABARAPL1 and tumor protein p53-inducible nuclear protein 2 ( TP53INP2 )), and Fc gamma receptor (FcγR) mediated phagocytosis (involving amphiphysin ( AMPH )). These findings uncover new pathophysiological dimensions underlying PD, implicating genes associated with heart muscle contraction. This knowledge enhances diagnostic accuracy and contributes to the advancement of targeted therapies.
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