The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Parkinson’s Disease: Biomarkers, Treatment, and Risk Factors
Open accessAbstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder caused mainly by lack of dopamine in the brain. Dopamine is a neurotransmitter involved in movement, motivation, memory, and other functions; its level is decreased in PD brain as a result of dopaminergic cell death. Dopamine loss in PD brain is a cause of motor deficiency and, possibly, a reason of the cognitive deficit observed in some PD patients. PD is mostly not recognized in its early stage because of a long latency between the first damage to dopaminergic cells and the onset of clinical symptoms. Therefore, it is very important to find reliable molecular biomarkers that can distinguish PD from other conditions, monitor its progression, or give an indication of a positive response to a therapeutic intervention. PD biomarkers can be subdivided into four main types: clinical, imaging, biochemical, and genetic. For a long time protein biomarkers, dopamine metabolites, amino acids, etc. in blood, serum, cerebrospinal liquid (CSF) were considered the most promising. Among the candidate biomarkers that have been tested, various forms of α-synuclein (α-syn), i.e., soluble, aggregated, post-translationally modified, etc. were considered potentially the most efficient. However, the encouraging recent results suggest that microRNA-based analysis may bring considerable progress, especially if it is combined with α-syn data. Another promising analysis is the advanced metabolite profiling of body fluids, called "metabolomics" which may uncover metabolic fingerprints specific for various stages of PD. Conventional pharmacological treatment of PD is based on the replacement of dopamine using dopamine precursors (levodopa, L-DOPA, L-3,4 dihydroxyphenylalanine), dopamine agonists (amantadine, apomorphine) and MAO-B inhibitors (selegiline, rasagiline), which can be used alone or in combination with each other. Potential risk factors include environmental toxins, drugs, pesticides, brain microtrauma, focal cerebrovascular damage, and genomic defects. This review covers molecules that might act as the biomarkers of PD. Then, PD risk factors (including genetics and non-genetic factors) and PD treatment options are discussed.
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Cites
Staging of brain pathology related to sporadic Parkinson’s disease
Braak, H., Tredici, K. D., Rüb, U., de Vos, R. A. I., Jansen Steur, E. N. H., & Braak, E. (2003) · Neurobiology of Aging · doi:10.1016/s0197-4580(02)00065-9 · Cited by 10,777
Hereditary Early-Onset Parkinson's Disease Caused by Mutations in PINK1
Valente, E. M., Abou-Sleiman, P. M., Caputo, V., Muqit, M. M. K., Harvey, K., Gispert, S., Ali, Z., Del Turco, D., Bentivoglio, A. R., Healy, D. G., et al. (2004) · Science · doi:10.1126/science.1096284 · Cited by 3,481
Direct brain infusion of glial cell line–derived neurotrophic factor in Parkinson disease
Gill, S. S., Patel, N. K., Hotton, G. R., O'Sullivan, K., McCarter, R., Bunnage, M., Brooks, D. J., Svendsen, C. N., & Heywood, P. (2003) · Nature Medicine · doi:10.1038/nm850 · Cited by 1,290
Ramirez, A., Heimbach, A., Gründemann, J., Stiller, B., Hampshire, D., Cid, L. P., Goebel, I., Mubaidin, A. F., Wriekat, A.-L., Roeper, J., et al. (2006) · Nature Genetics · doi:10.1038/ng1884 · Cited by 1,208
Prion-like spreading of pathological α-synuclein in brain
Masuda-Suzukake, M., Nonaka, T., Hosokawa, M., Oikawa, T., Arai, T., Akiyama, H., Mann, D. M. A., & Hasegawa, M. (2013) · Brain · doi:10.1093/brain/awt037 · Cited by 867
Imamura, K., Hishikawa, N., Sawada, M., Nagatsu, T., Yoshida, M., & Hashizume, Y. (2003) · Acta Neuropathologica · doi:10.1007/s00401-003-0766-2 · Cited by 791
Olanow, C. W., Kieburtz, K., Odin, P., Espay, A. J., Standaert, D. G., Fernandez, H. H., Vanagunas, A., Othman, A. A., Widnell, K. L., Robieson, W. Z., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70293-x · Cited by 716
Mechanisms of deep brain stimulation
Herrington, T. M., Cheng, J. J., & Eskandar, E. N. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00281.2015 · Cited by 551
Hypocretin (orexin) loss in Parkinson's disease
Fronczek, R., Overeem, S., Lee, S. Y. Y., Hegeman, I. M., van Pelt, J., van Duinen, S. G., Lammers, G. J., & Swaab, D. F. (2007) · Brain · doi:10.1093/brain/awm090 · Cited by 463
A phase I study of aromatic L-amino acid decarboxylase gene therapy for Parkinson’s disease
Muramatsu, S.-I., Fujimoto, K.-I., Kato, S., Mizukami, H., Asari, S., Ikeguchi, K., Kawakami, T., Urabe, M., Kume, A., Sato, T., et al. (2010) · Molecular Therapy · doi:10.1038/mt.2010.135 · Cited by 344
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Parkinson’s Disease: Pathogenesis and Clinical Aspects
(2018) · Codon Publications eBooks · doi:10.15586/codonpublications.parkinsonsdisease.2018 · Cited by 294
Picca, A., Guerra, F., Calvani, R., Romano, R., Coelho-Júnior, H. J., Bucci, C., & Marzetti, E. (2021) · Biomolecules · doi:10.3390/biom11101508 · Cited by 189
Gorecki, A. M., Preskey, L., Bakeberg, M. C., Kenna, J. E., Gildenhuys, C., MacDougall, G., Dunlop, S. A., Mastaglia, F. L., Akkari, P. A., Koengten, F., et al. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00839 · Cited by 184
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Metadata
- Authors
- Emamzadeh, F. N., & Surguchov, A.
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2018-08-30
- Volume
- 12
- Pages
- 612-612
- ISSN
- 1662-453X (ISSN-L)
- OpenAlex
- W2889197740
- Cited by
- 568
- References
- 13
- FWCI
- 24.90
- Type
- journal article
- Language
- en
- Open access
- gold
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