Evaluating Alzheimer Disease tau burden and spread in relation to cognitive domain deficits
Poster No:
251
Submission Type:
Abstract Submission
Authors:
Stephanie Doering1, Austin McCullough1, Brian Gordon1, Nicole McKay1, Pete Millar2, Diana Hobbs3, Rohan Agrawal1, Andrew Aschenbrenner1, Jason Hassenstab2, John Morris4, Tammie Benzinger4
Institutions:
1Washington University School of Medicine, Saint Louis, MO, 2Washington University in St. Louis, St. Louis, MO, 3Washington University in St. Louis, St Louis, MO, 4Washington University School of Medicine, St. Louis, MO
First Author:
Co-Author(s):
Introduction:
Alzheimer Disease (AD) tau-protein pathological progression is characterized by a distinct spatiotemporal pattern in which (1) early tau burden continues to accumulate in early-impacted brain regions as well as (2) the simultaneous tau spread to additional brain regions. Specific cognitive domain deficits are shown to correlate with the spatial distribution of tau pathology; however, summary measures of tau in neuroimaging largely focus on tau burden in early regions of interest. Recent work suggests atypical variants of AD with unique spreading patterns of tau are reflective of the type of cognitive impairments. Summary measures evaluating tau burden for typical amnestic AD are therefore insufficient in capturing inter-individual differences in tau progression. In this work, we evaluate our previously proposed metric for calculating tau spread in relation to specific cognitive domain deficits.
Methods:
469 older participants and 39 younger controls (YC) were recruited with tau positron emission tomography (PET), amyloid PET, Clinical Dementia Rating® (CDR®), and neuropsychological testing with the Uniform Data Set (UDS-3) from the Washington University in St. Louis Knight Alzheimer Disease Research Center (Knight ADRC). Older participants were split into disease stage groups according to amyloid positivity and CDR score (Older Controls [OC], Preclinical, Symptomatic). Tau burden was calculated using Tau Index (TI) (Mishra et al., 2017), a summary measure of tau sensitive to preclinical regions of interest (ROIs). Tau spread was calculated using Tau Spatial Spread (TSS) (Figure 1), the proportion of voxels with significantly abnormal tau pathology relative to YC. Cognitive domain composites previously developed (McKay et al., 2023) and the Knight ADRC Preclinical Alzheimer Cognitive Composite (Knight ADRC PACC) were calculated relative to OC. Participant baseline cognitive domain scores were evaluated across disease stage and relative to both TI and TSS with nested linear regression models evaluated with AIC and Pearson correlation. Longitudinal analyses were conducted with linear mixed effects regression to determine whether baseline TI and TSS can predict the rate of decline for each cognitive domain. Gaussian Mixture Modeling and Estimated Marginal Means analyses were conducted for visualizations of the cognitive domain longitudinal trajectories.
Results:
Cognitive domain scores were significantly lower for symptomatic participants but no difference was found between OC and preclinical participants. All cognitive domains were correlated to both TI and TSS (Figure 2), however the working memory domain appears underpowered in our cohort. Baseline PACC and the Attentional domain demonstrate added benefit of modeling TSS in addition to TI according to the nested linear models. Episodic and Semantic Memory domains are inconclusive on whether there is added benefit of modeling TSS according to AIC. TI can predict the rate of decline in all domains but the effect is weak for the Working Memory domain. TSS can predict the rate of decline in the PACC, Episodic, and Semantic Memory domains, but not in the Working Memory domain or Attention domain.
Conclusions:
Overall, preclinical impairment in various cognitive domains is related to early tau pathology. Tau burden largely explains cognitive impairments, however tau spread captures additional impairment in the attentional domain (possibly due to the inclusion of neural correlates in later-stage regions) which may be attributed to the preclinical stage prior to episodic impairment. Tau burden can predict the trajectory of the rate of future cognitive decline across all domains, indicating it is a strong predictive biomarker. Tau spread, however, does not predict the rate of future decline in the attentional domain despite having added benefit at baseline. This may indicate that attentional deficits appear early in AD and therefore are largely observed at baseline impairment rather than future cognitive decline.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
PET Modeling and Analysis 2
Keywords:
Cognition
Degenerative Disease
Positron Emission Tomography (PET)
1|2Indicates the priority used for review
Provide references using author date format
Mishra, S. et al. (2017) ‘AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: Defining a summary measure’, NeuroImage, 161, pp. 171–178. Available at: https://doi.org/10.1016/j.neuroimage.2017.07.050.