Browsing by Author "Kostadinova, Ralitsa V."

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    Influence of tau on non‐traditional memory scores in early‐onset Alzheimer’s disease
    (Wiley, 2025-01-09) Kostadinova, Ralitsa V.; Bushnell, Justin; Hammers, Dustin B.; Apostolova, Liana G.; Clark, David G.; Neurology, School of Medicine
    Background: A common neuropsychological test for assessing episodic memory is the Rey Auditory Verbal Learning Test (RAVLT), a sequence of 8 word‐list learning and recall tasks (five learning trials, immediate recall of an intrusion list, short‐delay and long‐delay recall). There is extensive research correlating patterns of RAVLT performance with clinical dementia syndromes, but little work relating these patterns to biomarkers in early‐onset dementia. Here, we analyze the relationship between patterns of tau deposition and RAVLT performance in early‐onset populations. Method: We transcribed RAVLT recordings from 249 subjects in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS). We calculated three composite scores from scores on the individual RAVLT tasks: learning ratio, raw learning score, and recency ratio. We then performed principle components analysis (PCA) on tau measurements in 108 regions of interest, identifying five components accounting for 90.9% of the variance. We entered RAVLT composite scores as dependent variables in a series of linear regression models. The PCA components, along with diagnostic syndrome and nuisance variables (age, sex, education), were entered as independent variables. Result: Principal component 1 loaded positively in all ROIs in both hemispheres, with weaker loadings in the motor strip, occipital region, and subcortical nuclei. Principal component 5 loaded positively on left > right temporal lobes and white matter. These two were significant predictors of both learning ratio and raw learning score, showing that an increase in tau affects the performance of these RAVLT metrics. Loadings for principal component 4 were more complex, but in general were positive in the right > left hemisphere, including parietal lobes and superior temporal gyri, with negative loadings elsewhere in the temporal lobes. This component was a significant predictor of recency ratio. In all cases, regression coefficients were negative, indicating that tau within ROIs with positive loadings was negatively correlated with the memory score in question. Conclusion: RAVLT measures are sensitive to the effects of tau deposition in early‐onset Alzheimer’s disease. Further work is needed to evaluate these scores as predictors of specific forms of pathology in early‐onset dementia.
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    Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer’s Disease
    (Taylor & Francis, 2023) Hammers, Dustin B.; Kostadinova, Ralitsa V.; Spencer, Robert J.; Ikanga, Jean N.; Unverzagt, Frederick W.; Risacher, Shannon L.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.