Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection

Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an i...

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Veröffentlicht in:Free radical biology & medicine 2018-08, Vol.124, p.388-394
Hauptverfasser: Peña-Bautista, Carmen, Vigor, Claire, Galano, Jean-Marie, Oger, Camille, Durand, Thierry, Ferrer, Inés, Cuevas, Ana, López-Cuevas, Rogelio, Baquero, Miguel, López-Nogueroles, Marina, Vento, Máximo, Hervás, David, García-Blanco, Ana, Cháfer-Pericás, Consuelo
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Sprache:eng
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Zusammenfassung:Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role. Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment. The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities. A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD. [Display omitted] •Lipid peroxidation as molecular mechanism involved in Alzheimer Disease.•Early and non-invasive Alzheimer Disease diagnostic model.•Plasma biomarkers determinations from a validated analytical method.•Statistical analysis based on elastic-net-penalized logistic regression.
ISSN:0891-5849
1873-4596
DOI:10.1016/j.freeradbiomed.2018.06.038