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    The 12-Word Philadelphia Verbal Learning Test Performances in Older Adults: Brain MRI and Cerebrospinal Fluid Correlates and Regression-Based Normative Data

    Gifford, Katherine A.
    Liu, Dandan
    Neal, Jacquelyn E.
    Babicz, Michelle A.
    Thompson, Jennifer L.
    Walljasper, Lily E.
    Turchan, Maxim
    Pechman, Kimberly R.
    Osborn, Katie E.
    Acosta, Lealani Mae Y.
    Bell, Susan P.
    Hohman, Timothy J.
    Jefferson, Angela L.
    : https://ir.vanderbilt.edu/xmlui/handle/1803/9893
    : 2018

    Abstract

    Background/Aims: This study evaluated neuroimaging and biological correlates, psychometric properties, and regression-based normative data of the 12-word Philadelphia Verbal Learning Test (PVLT), a list-learning test. Methods: Vanderbilt Memory and Aging Project participants free of clinical dementia and stroke (n = 230, aged 73 +/- 7 years) completed a neuropsychological protocol and brain MRI. A subset (n = 111) underwent lumbar puncture for analysis of Alzheimer's disease (AD) and axonal integrity cerebrospinal fluid (CSF) biomarkers. Regression models related PVLT indices to MRI and CSF biomarkers adjusting for age, sex, race/ethnicity, education, APOE-epsilon 4 carrier status, cognitive status, and intracranial volume (MRI models). Secondary analyses were restricted to participants with normal cognition (NC; n = 127), from which regression-based normative data were generated. Results: Lower PVLT performances were associated with smaller medial temporal lobe volumes (p < 0.05) and higher CSF tau concentrations (p < 0.04). Among NC, PVLT indices were associated with white matter hyperintensities on MRI and an axonal injury biomarker (CSF neurofilament light; p < 0.03). Conclusion: The PVLT appears sensitive to markers of neurodegeneration, including temporal regions affected by AD. Conversely, in cognitively normal older adults, PVLT performance seems to relate to white matter disease and axonal injury, perhaps reflecting non-AD pathways to cognitive change. Enhanced normative data enrich the clinical utility of this tool. (C) 2018 The Author(s) Published by S. Karger AG, Basel
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    • Neurology

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