Examining the diagnostic value of the mnemonic discrimination task for classification of cognitive status and amyloid-beta burden.

Alzheimer's disease (AD) is the most common type of dementia, characterized by early memory impairments and gradual worsening of daily functions. AD-related pathology, such as amyloid-beta (Aβ) plaques, begins to accumulate many years before the onset of clinical symptoms. Predicting risk for AD via related pathology is critical as the preclinical stage could serve as a therapeutic time window, allowing for early management of the disease and reducing health and economic costs. Current methods for detecting AD pathology, however, are often expensive and invasive, limiting wide and easy access to a clinical setting. A non-invasive, cost-efficient platform, such as computerized cognitive tests, could be potentially useful to identify at-risk individuals as early as possible. In this study, we examined the diagnostic value of an episodic memory task, the mnemonic discrimination task (MDT), for predicting risk of cognitive impairment or Aβ burden. We constructed a random forest classification algorithm, utilizing MDT performance metrics and various neuropsychological test scores as input features, and assessed model performance using area under the curve (AUC). Models based on MDT performance metrics achieved classification results with an AUC of 0.83 for cognitive status and an AUC of 0.64 for Aβ status. Our findings suggest that mnemonic discrimination function may be a useful predictor of progression to prodromal AD or increased risk of Aβ load, which could be a cost-efficient, noninvasive cognitive testing solution for potentially wide-scale assessment of AD pathological and cognitive risk.
Competing Interests: Declaration of competing interest M.A.Y. is inventor on Augmem™ technology and is co-founder and chief scientific advisor of Augnition Labs, LLC, which is developing a commercial platform for mnemonic discrimination to aid in diagnosis. Augnition Labs took no part in funding or directing the science presented in this paper. No other conflicts of interest are reported. The opinions and assertions herein do not necessarily reflect the official policy or position of the Uniformed Services University, the Department of Defense, or the Henry M. Jackson Foundation for the Advancement of Military Medicine.
(Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)