A comparison of the Montreal Cognitive Assessment and standard cognitive measures in the National Alzheimer’s Coordinating Center and Knight Alzheimer’s Disease Research Center cohorts

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AbstractBackgroundThe Montreal Cognitive Assessment (MoCA) could be described as a “sampling” of more comprehensive cognitive measures. We investigated the utility of the MoCA in predicting disease progression in the National Alzheimer’s Coordinating Center (NACC) sample in comparison to standard comprehensive cognitive measures collected in the NACC Uniform Dataset 3 (UDS 3). In addition, using the imaging biomarker‐rich cohorts at the Knight Alzheimer Disease Research Center (ADRC), we compared the sensitivity of the MoCA and UDS 3 measures to APOE 4 status, amyloid PET, tau PET, and structural MRI.MethodAnalysis One: In cognitively normal older adults from the NACC cohort (n=6,273, 2.3 +/‐ 0.9 years follow‐up), survival and receiver operating characteristic (ROC) analyses compared the MoCA and UDS 3 measures on their ability to classify disease progression, defined as change in Clinical Dementia Rating (CDR) status from 0 to >0. Analysis Two: In Knight ADRC participants (n = 445), regression models compared the sensitivity of the MoCA and standard cognitive measures to AD biomarkers in all participants and separately in CDR 0s.ResultDisease progression analyses in the NACC sample resulted in an area under the curve (AUC) estimate for the MoCA of 0.69 for the total score and 0.55‐0.73 for domain scores. For the UDS 3 measures, AUCs ranged from 0.57‐0.73. A cognitive composite similar to a “PACC” yielded an AUC of 0.71. Sensitivity to AD biomarkers including amyloid PET, tau PET, cortical thickness, and APOE 4 status was similar for both the MoCA and UDS 3 measures (all p’s < 0.001). Analyses of CDR 0 participants produced small but significant relationships only with tau PET and cortical thickness (p’s 0.01 – 0.02) for both MoCA and UDS 3 tests.ConclusionNeither the MoCA nor UDS 3 cognitive measures demonstrated adequate classification of disease progression. Correlations with biomarkers suggests that the MoCA is capable of tracking pathological indicators of AD in individuals with symptomatic disease. However, in cognitively normal participants, both the MoCA and UDS 3 measures were weakly correlated with indicators of neurodegeneration. More sensitive measures or improved assessment methodology is required to reliably detect AD pathology prior to clinical diagnosis.