Skip to main content
Dryad logo

Latent atrophy factors related to phenotypical variants of posterior cortical atrophy

Citation

Groot, Colin (2020), Latent atrophy factors related to phenotypical variants of posterior cortical atrophy, Dryad, Dataset, https://doi.org/10.5061/dryad.jdfn2z37p

Abstract

Objective: To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria; dorsal, ventral, dominant-parietal and caudal, we assessed associations between latent atrophy factors and cognition.

Methods: We employed a data-driven Bayesian modelling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multi-center cohort of 119 individuals with PCA (age:64±7, 38% male, MMSE:21±5, 71% amyloid-β-positive, 29% amyloid-β status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field-strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a-priori classification. Individual factor expressions were correlated to four PCA-specific cognitive domains (object-perception, space-perception, non-visual/parietal functions and primary visual processing) using general linear models.

Results: The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. We found that object-perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space-perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the vast majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiological phenotype.

Conclusion: Our results indicate that particular brain-behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain-regions and symptoms, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.