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. 2021 Feb 8;13(1):36.
doi: 10.1186/s13195-021-00776-w.

Detecting Alzheimer's disease biomarkers with a brief tablet-based cognitive battery: sensitivity to Aβ and tau PET

Elena Tsoy  1 , Amelia Strom  1 , Leonardo Iaccarino  1 , Sabrina J Erlhoff  1 , Collette A Goode  1 , Anne-Marie Rodriguez  1 , Gil D Rabinovici  1   2 , Bruce L Miller  1   3 , Joel H Kramer  1   3 , Katherine P Rankin  1 , Renaud La Joie  1 , Katherine L Possin  4   5
Affiliations

Detecting Alzheimer's disease biomarkers with a brief tablet-based cognitive battery: sensitivity to Aβ and tau PET

Elena Tsoy et al. Alzheimers Res Ther. .

Abstract

Background: β-amyloid (Aβ) and tau positron emission tomography (PET) detect the pathological changes that define Alzheimer's disease (AD) in living people. Cognitive measures sensitive to Aβ and tau burden may help streamline identification of cases for confirmatory AD biomarker testing.

Methods: We examined the association of Brain Health Assessment (BHA) tablet-based cognitive measures with dichotomized Aβ -PET status using logistic regression models in individuals with mild cognitive impairment (MCI) or dementia (N = 140; 43 Aβ-, 97 Aβ+). We also investigated the relationship between the BHA tests and regional patterns of tau-PET signal using voxel-wise regression analyses in a subsample of 60 Aβ+ individuals with MCI or dementia.

Results: Favorites (associative memory), Match (executive functions and speed), and Everyday Cognition Scale scores were significantly associated with Aβ positivity (area under the curve [AUC] = 0.75 [95% CI 0.66-0.85]). We found significant associations with tau-PET signal in mesial temporal regions for Favorites, frontoparietal regions for Match, and occipitoparietal regions for Line Orientation (visuospatial skills) in a subsample of individuals with MCI and dementia.

Conclusion: The BHA measures are significantly associated with both Aβ and regional tau in vivo imaging markers and could be used for the identification of patients with suspected AD pathology in clinical practice.

Keywords: Alzheimer’s disease; Biomarkers; Mild cognitive impairment; Neuropsychology; Positron emission tomography; Psychometrics.

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Conflict of interest statement

None reported.

Figures

Fig. 1
Fig. 1
Sample selection flowchart. Abbreviations: BHA, Brain Health Assessment
Fig. 2
Fig. 2
Receiver operating characteristic curves predicting Aβ+ PET status. Legend: Blue lines are based on BHA measures only (Favorites, Match, and BHS-ECog) and orange lines are based on the BHA measures and an amnestic clinical phenotype. Abbreviations: BHA, Brain Health Assessment
Fig. 3
Fig. 3
Voxel-wise results of independent regressions between BHA tests and Flortaucipir PET SUVR. Legend: Left column shows voxel-wise associations between individual BHA tests and Flortaucipir SUVR without covariates. Middle column shows voxel-wise associations between individual BHA tests and Flortaucipir SUVR with inclusion of age as a covariate. Voxel-wise associations are shown at uncorrected P < .001 in blue and at FWE-corrected P < .05 in red. Right column illustrates scatter plots and modeled regression lines (including covariates of CDR Sum of Boxes, clinical phenotype [dummy-coded: 0 = non-amnestic MCI/atypical dementia, 1 = amnestic MCI/amnestic-predominant dementia], and time difference between PET acquisition and BHA completion) on the associations between individual BHA tests and Flortaucipir SUVR in significant clusters at P < .001 uncorrected threshold. Abbreviations: BHA, Brain Health Assessment; CDR-SB, Clinical Dementia Rating Scale Sum of Boxes; FWE, family-wise error; MCI, mild cognitive impairment; PET, positron emission tomography; SUVR, standard uptake value ratio
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