The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Metabolomic profiling to develop blood biomarkers for Parkinson's disease
Open accessAbstract
The development of biomarkers for the diagnosis and monitoring disease progression in Parkinson's disease (PD) is of great importance since diagnosis based on clinical parameters has a considerable error rate. In this study, we utilized metabolomic profiling using high performance liquid chromatography coupled with electrochemical coulometric array detection (LCECA) to look for biomarkers in plasma useful for the diagnosis of PD. We examined 25 controls and 66 PD patients. We also measured 8-hydroxy-2-deoxyguanosine (8-OHdG) levels as a marker of oxidative damage to DNA. We initially examined the profiles of unmedicated PD subjects compared to controls to rule out confounding effects of symptomatic medications. We found a complete separation of the two groups. We then determined the variables, which played the greatest role in separating the two groups and applied them to PD subjects taking dopaminergic medications. Using these parameters, we achieved a complete separation of the PD patients from controls. 8-OHdG levels were significantly increased in PD patients, but overlapped controls. Two other markers of oxidative damage were measured in our LCECA profiles. Uric acid was significantly reduced while glutathione was significantly increased in PD patients. These findings show that metabolomic profiling with LCECA coulometric array has great promise for developing biomarkers for both the diagnosis, as well as monitoring disease progression in PD.
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Metadata
- Authors
- Bogdanov, M., Matson, W. R., Wang, L., Matson, T., Saunders-Pullman, R., Bressman, S. S., & Beal, M. F.
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-02-01
- Volume
- 131
- Issue
- 2
- Pages
- 389-396
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W2117524242
- Cited by
- 401
- References
- 43
- FWCI
- 20.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
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