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Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias
- Source :
- Proteomes, Vol 6, Iss 3, p 32 (2018), Proteomes
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.
- Subjects :
- 0301 basic medicine
Functional impairment
Demographics
Clinical Biochemistry
lcsh:QR1-502
Review
Computational biology
Disease
Diagnostic tools
Biochemistry
cerebrospinal fluid
lcsh:Microbiology
03 medical and health sciences
proteomics
Structural Biology
Lc ms ms
Medicine
LC-MS/MS
Molecular Biology
plasma
business.industry
neurodegeneration
biomarkers
Clinical disease
3. Good health
030104 developmental biology
business
Alzheimer’s disease
serum
Subjects
Details
- Language :
- English
- ISSN :
- 22277382
- Volume :
- 6
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Proteomes
- Accession number :
- edsair.doi.dedup.....bf24c4ea903d8f8b986bc0fc10275a0b