Subtype-specific patterns of tau pathology in Alzheimer's and related disorders
Poster No:
299
Submission Type:
Abstract Submission
Authors:
Diana Hobbs1, Stephanie Doering1, Austin McCullough1, Pete Millar1, Shaney Flores1, Sarah Keefe1, Aristeidis Sotiras1, Tammie Benzinger1, Gregory Day2, Brian Gordon1
Institutions:
1Washington University School of Medicine, St. Louis, MO, 2Mayo Clinic, Jacksonville, FL
First Author:
Co-Author(s):
Introduction:
Alzheimer disease (AD) encompasses a range of neurodegenerative disorders marked by progressive cognitive decline (Hardy and Selkoe, 2002). Notably, atypical presentations like Posterior Cortical Atrophy (PCA) and Logopenic Variant Primary Progressive Aphasia (lvPPA) exhibit distinct clinical and neuroimaging profiles. PCA predominantly affects the posterior parietal and occipital lobes, leading to visuospatial deficits, while lvPPA primarily manifests as a language impairment rooted in the temporoparietal region (Crutch et al., 2017; Gorno-Tempini et al., 2011). Unraveling the intricate biological underpinnings of these variants is crucial for understanding the heterogeneity within AD (Jack Jr. et al., 2010).
Methods:
Participants diagnosed with AD dementia (n=54, female=25, Age: 75.23 ± 6.52), PCA (n = 9, female=8, Age: 62.78 ± 7.21), and lvPPA (n = 6, female=2, Age: 66.33 ± 6.38) from the Knight Alzheimer Disease Research Center (Knight ADRC) underwent 18F-AV-1451 tau-PET imaging. Standard uptake value ratios (SUVRs) highlighting tau deposition were mapped to the cortical surface (Figure 1A), along with nine other biological properties: gene expression, myelin, cortical thickness, sensorimotor association axis, evolutionary expansion, cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of glucose (CMRglu) (Figure 1B). Correlation matrices and generalized linear models (GLMs) were conducted to assess the relationships between patterns of tau accumulation and biological properties.
Results:
A correlation matrix (Figure 2A) shows the strongest positive associations (p<0.05) between patterns of evolutionary expansion and tau accumulation in those with AD (r=0.53), PCA (r=0.29), and lvPPA (r= 0.56), as well as gene expression in PCA (r=0.51). Conversely, the strongest negative associations were observed in AD (r=-0.38, r=-0.15) and lvPPA (r=-0.18, r=-0.28) for CBF and myelin mapping, respectively, and in PCA (r=-0.25, -0.23) for cortical thickness and sensorimotor association axis. GLMs demonstrated significant relationships between cerebrovascular health and evolutionary expansion with measures of tau across all groups. AD (r=-0.52) and PCA (r=-0.19) exhibited negative associations with gene expression and myelin mapping, respectively, when considering all biological variables. Additionally, lvPPA (r=0.39) displayed positive association with patterns of the sensorimotor association cortex.
Conclusions:
These results elucidate distinct tau deposition patterns in AD, PCA, and lvPPA, and provide comprehensive insights into their subtype-specific pathophysiology. The correlation matrix and GLMs underscore the significance of evolutionary expansion and cerebrovascular health in influencing tau accumulation across all groups. Noteworthy associations, both positive and negative, highlight the complex interplay of gene expression, myelin mapping, and cortical thickness with tau pathology in specific variants. These findings contribute to our understanding of the heterogeneity within AD spectrum disorders and emphasize the multifaceted nature of neurodegenerative processes. Further research in this direction holds promise for refining diagnostic and therapeutic strategies tailored to the distinct neurobiological profiles observed in AD, PCA, and lvPPA.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging
Modeling and Analysis Methods:
PET Modeling and Analysis 2
Neuroinformatics and Data Sharing:
Brain Atlases
Novel Imaging Acquisition Methods:
PET
Keywords:
Aging
Computational Neuroscience
Data analysis
Degenerative Disease
Design and Analysis
Multivariate
Positron Emission Tomography (PET)
Other - Alzheimer Disease; Posterior Cortical Atrophy; Logopenic Variant Primary Progressive Aphasia
1|2Indicates the priority used for review
Provide references using author date format
Crutch, S.J. (2017), "Consensus classification of posterior cortical atrophy", Alzheimers Dementia, vol. 13, no. 8, pp. 870-884.
Gorno-Tempini, M.L. (2011), "Classification of primary progressive aphasia and its variants", Neurology, vol. 76, no. 11, pp. 1006-1014.
Jack Jr., C.R. (2010), "Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade", Lancet Neurology, vol. 9, no. 1, pp. 119-128.