Potential Value of Plasma-Based Biomarkers for Prediction of Episodic Memory Performance and Identification of Individuals with Amnestic Mild Cognitive Impairment

基于血浆的生物标志物在预测情景记忆表现和识别患有遗忘型轻度认知障碍个体方面的潜在价值

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Abstract

OBJECTIVE: Patients with amnestic mild cognitive impairment (aMCI) are thought to be highly susceptible to developing Alzheimer's disease (AD). The study aimed to investigate the possibilities of plasma-biomarkers for individual patient identification of aMCI and prediction of episodic memory. METHODS: We recruited 87 healthy controls and 68 aMCI patients in this study; and 22/68 aMCI patients completed 3-year follow-up visits, with six aMCI patients converting to AD. An ultrasensitive quantitative method was employed to measure the levels of plasma biomarkers. RESULTS: Relative to healthy controls, the aMCI patients showed significantly higher levels of plasma neurofilament light (NfL) and lower levels of plasma Aβ40, Aβ42 and Aβ42/Aβ40 ratio (all P values <0.01). Using multivariate relevance vector regression models, we further demonstrated plasma biomarkers could accurately predict baseline Rey's Auditory Verbal Learning Test-20 min delayed recall (AVLT-DR) scores (r = 0.362, P value <0.001) and 3-year longitudinal AVLT-DR changes (r = 0.365, P value <0.001) for individual aMCI patients; plasma-indicators contributed most to the predictions including total-tau and NfL. Finally, by using support vector machine model, the combination of plasma Aβ42/Aβ40, mini-mental state examination (MMSE) score, and hippocampal/parahippocampal volume had the highest accuracy of 77.42% (sensitivity = 72.06%, specificity = 81.61%) for identifying aMCI patients. CONCLUSION: We provided support to the use of plasma total-tau and NfL as simple biomarkers to predict the severity of episodic memory deficit for individual aMCI patients and aMCI progression, and further demonstrated that the combination of plasma Aβ42/Aβ40, hippocampal/parahippocampal volume, and MMSE score could serve as an integrated screening tool to select aMCI individuals.

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