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Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis

Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Greece

Special Issues: Novel modeling methodologies for the neuropathological dimensions of Parkinson’s disease

Parkinson’s disease (PD) is associated with a selective loss of the neurons in the midbrain area called the substantia nigra pars compacta and the loss of projecting nerve fibers in the striatum. Predominant pathological hallmarks of PD are the degeneration of discrete neuronal populations and progressive accumulation of α-synuclein–containing intracytoplasmic inclusions called Lewy bodies and dystrophic Lewy neuritis. There is currently no therapy to terminate or delay the neurodegenerative process as the exact mechanisms underlying the pathogenesis of PD require further investigation. The identification and validation of novel biomarkers for the diagnosis of PD is a great challenge using contemporary approaches and optimizing sampling handling as well as interpretation using bioinformatics analysis. In this review, recent evidences associated with multi-omic data-sets and molecular mechanisms underlying PD are examined. A combined mapping of several transcriptional evidences could establish a patient-specific signature for early diagnose of PD though eligible systems biology tools, which can also help develop effective drug-based therapeutic approaches.
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Keywords Parkinson’s disease; network analysis; gene expression; bioinformatics; micro-RNAs

Citation: Marios G. Krokidis. Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis. AIMS Neuroscience, 2019, 6(4): 333-345. doi: 10.3934/Neuroscience.2019.4.333


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