Blood-based molecular signature of Alzheimer's disease via spectroscopy and metabolomics
| Autor: | Zdeněk Fišar, Kamila Syslová, Jiří Raboch, Roman Jirák, Jana Vondroušová, Lucie Habartová, Kateřina Hrubešová, Vladimír Setnička |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
030213 general clinical medicine
Metabolite Clinical Biochemistry Computational biology Disease 030204 cardiovascular system & hematology Spectrum Analysis Raman 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Metabolomics Alzheimer Disease medicine Humans Dementia Spectroscopy Spectral data Aged Aged 80 and over business.industry Circular Dichroism Discriminant Analysis Blood Proteins General Medicine Middle Aged medicine.disease Peripheral blood chemistry Raman optical activity business Biomarkers |
| Zdroj: | Clinical Biochemistry. 72:58-63 |
| ISSN: | 0009-9120 |
| DOI: | 10.1016/j.clinbiochem.2019.04.004 |
| Popis: | Objectives With over 35 million cases worldwide, Alzheimer's disease (AD) represents the main cause of dementia. The differentiation of AD from other types of dementia is challenging and its early diagnosis is complicated. The established biomarkers are not only based on the invasive collection of cerebrospinal fluid, but also lack sufficient sensitivity and specificity. Therefore, much current effort is aimed at the identification of new biomarkers of AD in peripheral blood. Design and methods We focused on blood-based analyses using chiroptical spectroscopy (Raman optical activity, electronic circular dichroism) supplemented with conventional vibrational spectroscopy (infrared, Raman) and metabolomics (high-performance liquid chromatography with a high-resolution mass detection). Results This unique approach enabled us to identify the spectral pattern of AD and variations in metabolite levels. Subsequent linear discriminant analysis of the spectral data resulted in differentiation between the AD patients and control subjects. Conclusions It may be stated that this less invasive approach has strong potential for the identification of disease-related changes within essential plasmatic biomolecules and metabolites. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect