TRANSCRIPTOMICS ANALYSIS OF PARKINSON’S DISEASE USING GSE68719

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder which mainly affects voluntary movement control. This disease is identified by gradual degradation of dopaminergic neuron in substantia nigra i.e. lowering dopamine signaling in neural circuit. Less dopamine availability leads to disturbances on basal ganglia signaling which causes cardinal motor symptoms like posture instability, bradykinesia, muscular rigidity. Along with motor some non-motor symptoms like sleep disturbances, anxiety, depression, cognitive impairment and dementia etc. can also be seen in the advance stage of the disease. The defining feature of PD is aggregation of misfolded alpha-synuclein in intracellular inclusion which then leads to neuronal dysfunction and cell death by the mechanisms like mitochondrial impairment, neuroinflammation, oxidative stress etc. In PD neuronal degradation occurs due to combined effects of genetic susceptibility, environmental exposure, mitochondrial dysfunction, Oxidative stress and neuroinflammation. Some familial and sporadic form of this disease occurs due to genes like SNCA, LRRK2, PARK2, PINK1, and DJ-1. While environmental factors like heavy metals, pesticides increases neuronal injury due to oxidative and mitochondrial stress. By profiling messenger RNA expression, transcriptomic analysis gives insight of cellular pathways, regulatory networks, and disease progression, and it has become an important and efficient approach in modern molecular biology and disease research . Transcriptomic analysis is now more critical in Parkinson’s disease investigations, because for an early diagnosis, there are not enough dependable biomarkers, so people do not need to use invasive methods. By using the public resources like GSE68719, scientists are able to do bioinformatics analyses again on gene expression about Parkinson's. Differential expression tests can see if genes became more or less expressed due to this disease, and then pathway analysis tries to explain which signaling and biological processes are impacted most largely in such datasets. Volcano Plots are used to check the genes with larger fold change whereas Enrichment methods used to check biological roles and cell pathways. Overall, the main goals in analysing the DEGs with GSE68719 are to get better inside PD molecular processes, find possible biomarkers, locate disturbed functional pathways, and give a push for later research for diagnosis and treatment.