BACKGROUND: Memory assessment is a key factor for the diagnosis of cognitive impairment. However, memory performance over time may be quite heterogeneous within diagnostic groups.

METHOD: To identify latent trajectories in memory performance and their associated risk factors, we analyzed data from Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who were classified either as cognitively normal or as Mild Cognitive Impairment (MCI) at baseline and were administered the Rey Auditory Verbal Learning test (RAVLT) for up to 9 years. Group-based trajectory modeling on the 30-minute RAVLT delayed recall score was applied separately to the two baseline diagnostic groups.

RESULTS: There were 219 normal subjects with mean age 75.9 (range from 59.9 to 89.6) and 52.5% male participants, and 372 MCI subjects with mean age 74.8 (range from 55.1 to 89.3) and 63.7% male participants included in the analysis. For normal subjects, six trajectories were identified. Trajectories were classified into three types, determined by the shape, each of which may comprise more than one trajectory: stable (~30% of subjects), curvilinear decline (~ 28%), and linear decline (~ 42%). Notably, none of the normal subjects assigned to the stable stratum progressed to dementia during the study period. In contrast, all trajectories identified for the MCI group tended to decline, although some participants were later re-diagnosed with normal cognition. Age, sex, and education were significantly associated with trajectory membership for both diagnostic groups, while APOE ɛ4 was only significantly associated with trajectories among MCI participants.

CONCLUSION: Memory trajectory is a strong indicator of dementia risk. If likely trajectory of memory performance can be identified early, such work may allow clinicians to monitor or predict progression of individual patient cognition. This work also shows the importance of longitudinal cognitive testing and monitoring.

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Published in PLOS One, v. 14, no. 2, e0212435, p. 1-16.

© 2019 Ding et al.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Funding Information

Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (NIH Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). This study was also supported by National Institute on Aging (NIA) NIA P30 AG028383.

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Data obtained were collected and owned by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Researchers may request and access the data through the ADNI website (http://adni.loni.usc.edu/).