title: Untangling Alzheimer's Disease Clinicoanatomical Heterogeneity Through Selective Network Vulnerability - An Effort to Understand a Complex Disease.
abstract: Alzheimer's disease (AD) is a clinically, anatomically and biologically heterogeneous disorder encompassing a wide spectrum of cognitive profiles, ranging from the typical amnestic syndrome to visuospatial changes in posterior cortical atrophy, language deficits in primary progressive aphasia and behavioural/executive dysfunctions in anterior variants. With the emergence of functional imaging and neural network analysis using graph theory for instance, some authors have hypothesized that this phenotypic variability is produced by the differential involvement of large-scale neural networks - a model called 'molecular nexopathy'. At the moment, however, the hypothesized mechanisms underlying AD's divergent network degeneration remain speculative and mostly involve selective premorbid network vulnerability. Herein we present an overview of AD's clinicoanatomical variability, outline functional imaging and graph theory contributions to our understanding of the disease and discuss ongoing debates regarding the biological roots of its heterogeneity. We finally discuss the clinical promises of statistical signal processing disciplines (graph theory and information theory) in predicting the trajectory of AD variants. This paper aims to raise awareness about AD clinicoanatomical heterogeneity and outline how statistical signal processing methods could lead to a better understanding, diagnosis and treatment of AD variants in the future.
authors.affiliation: Clinique Interdisciplinaire de Mémoire (CIME), CHU de Québec, 1401, 18ième rue, Québec, Canada, G1J 1Z4. david.bergeron.5@ulaval.ca.
authors.forename: David
authors.initials: D
authors.lastname: Bergeron
authors.forename: Reda
authors.initials: R
authors.lastname: Bensaïdane
authors.forename: Robert
authors.initials: R
authors.lastname: Laforce
mesh_terms: D000544:Alzheimer Disease / Q000150:complications* / Q000000981:diagnostic imaging; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology*; D003072:Cognition Disorders / Q000000981:diagnostic imaging / Q000209:etiology; D006801:Humans; D008279:Magnetic Resonance Imaging; D009415:Nerve Net / Q000473:pathology*; D009434:Neural Pathways / Q000473:pathology*; D012815:Signal Processing, Computer-Assisted