Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis
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 progr...
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| Format: | Article |
| Language: | English |
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AIMS Press
2019-12-01
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| Series: | AIMS Neuroscience |
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| Online Access: | https://www.aimspress.com/article/10.3934/Neuroscience.2019.4.333/fulltext.html |
| _version_ | 1811226144825933824 |
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| author | Marios G. Krokidis |
| author_facet | Marios G. Krokidis |
| author_sort | Marios G. Krokidis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T09:20:24Z |
| format | Article |
| id | doaj.art-623daee938d14e6cb33d6c1773f68903 |
| institution | Directory Open Access Journal |
| issn | 2373-8006 2373-7972 |
| language | English |
| last_indexed | 2024-04-12T09:20:24Z |
| publishDate | 2019-12-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Neuroscience |
| spelling | doaj.art-623daee938d14e6cb33d6c1773f689032022-12-22T03:38:41ZengAIMS PressAIMS Neuroscience2373-80062373-79722019-12-016433334510.3934/Neuroscience.2019.4.333Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysisMarios G. Krokidis0Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, GreeceParkinson’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.https://www.aimspress.com/article/10.3934/Neuroscience.2019.4.333/fulltext.htmlparkinson’s diseasenetwork analysisgene expressionbioinformaticsmicro-rnas |
| spellingShingle | Marios G. Krokidis Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis AIMS Neuroscience parkinson’s disease network analysis gene expression bioinformatics micro-rnas |
| title | Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis |
| title_full | Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis |
| title_fullStr | Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis |
| title_full_unstemmed | Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis |
| title_short | Identification of biomarkers associated with Parkinson’s disease by gene expression profiling studies and bioinformatics analysis |
| title_sort | identification of biomarkers associated with parkinson s disease by gene expression profiling studies and bioinformatics analysis |
| topic | parkinson’s disease network analysis gene expression bioinformatics micro-rnas |
| url | https://www.aimspress.com/article/10.3934/Neuroscience.2019.4.333/fulltext.html |
| work_keys_str_mv | AT mariosgkrokidis identificationofbiomarkersassociatedwithparkinsonsdiseasebygeneexpressionprofilingstudiesandbioinformaticsanalysis |