Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer’s disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer’s disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer’s pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer’s disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer’s Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure—analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity ‘overload’ that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both.

Functionally related brain regions are selectively vulnerable to Alzheimer's disease pathophysiology. However, molecular markers of this pathophysiology (i.e., beta-amyloid and tau aggregates) have discrepant spatial and temporal patterns of progression within these selectively vulnerable brain regions. Existing reductionist pathophysiologic models cannot account for these large-scale spatiotemporal inconsistencies. Within the framework of the recently proposed cascading network failure model of Alzheimer's disease, however, these large-scale patterns are to be expected. This model postulates the following: 1) a tau-associated, circumscribed network disruption occurs in brain regions specific to a given phenotype in clinically normal individuals; 2) this disruption can trigger phenotype independent, stereotypic, and amyloid-associated compensatory brain network changes indexed by changes in the default mode network; 3) amyloid deposition marks a saturation of functional compensation and portends an acceleration of the inciting phenotype specific, and tau-associated, network failure. With the advent of in vivo molecular imaging of tau pathology, combined with amyloid and functional network imaging, it is now possible to investigate the relationship between functional brain networks, tau, and amyloid across the disease spectrum within these selectively vulnerable brain regions. In a large cohort (n = 218) spanning the Alzheimer's disease spectrum from young, amyloid negative, cognitively normal subjects to Alzheimer's disease dementia, we found several distinct spatial patterns of tau deposition, including 'Braak-like' and 'non-Braak-like', across functionally related brain regions. Rather than arising focally and spreading sequentially, elevated tau signal seems to occur system-wide based on inferences made from multiple cross-sectional analyses we conducted looking at regional patterns of tau signal. Younger age-of-disease-onset was associated with 'non-Braak-like' patterns of tau, suggesting an association with atypical clinical phenotypes. As predicted by the cascading network failure model of Alzheimer's disease, we found that amyloid is a partial mediator of the relationship between functional network failure and tau deposition in functionally connected brain regions. This study implicates large-scale brain networks in the pathophysiology of tau deposition and offers support to models incorporating large-scale network physiology into disease models linking tau and amyloid, such as the cascading network failure model of Alzheimer's disease.