Abstract
A better and non-invasive characterization of the preclinical phases of Alzheimer’s disease (AD) is important to advance its diagnosis and obtain more effective benefits from potential treatments. The TgF344-AD rat model has been well characterized and shows molecular, behavioral and brain connectivity alterations that resemble the silent period of the pathology. Our aim was to longitudinally investigate functional brain connectivity in established resting-state networks (RSNs) obtained by independent component analysis (ICA) in a cohort of TgF344-AD and control rats every 3 months, from 5 to 18 months of age, to cover different stages of the disease. Before each acquisition, working memory performance was evaluated by the delayed non match-to-sample (DNMS) task. Differences in the temporal evolution were observed between groups in the amplitude and shape of the somatosensorial and sensorimotor networks but not in the whole default mode network (DMN). Subsequent high dimensional ICA analysis showed early alterations in the anterior DMN subnetwork activity of TgF344-AD rats compared to controls. Performance of DNMS task was positively correlated with somatosensorial network at 5 months of age in the wild-type (WT) animals but not in the Tg-F344 rats. At different time points, DMN showed negative correlation with cognitive performance in the control group while in the transgenic group the correlation was positive. In addition, behavioral differences observed at 5 months of age correlated with alterations in the posterior DMN subnetwork. We have demonstrated that functional connectivity using ICA represents a useful biomarker also in animal models of AD such as the TgF344AD rats, as it allows the identification of alterations associated with the progression of the disease, detecting differences in specific networks even at very early stages.
Highlights
Alzheimer’s disease (AD) is a progressive age-related neurodegenerative disease, which has become the most common form of dementia in elderly populations
The default mode network (DMN) is characterized in rats by the activation of: (1) the medial prefrontal cortex, the most important association cortical area in the rat, showing connections with a great number of cortical and subcortical structures, responsible for decision making, planning of the actions and working memory functions; (2) the cingulate cortex, playing a critical role in stimulus-reinforcement learning and reward-guided selection of actions; and (3) the retrosplenial cortex involved in a variety of cognitive tasks including memory, navigation, and prospective thinking (Hamani et al, 2014; Sierakowiak et al, 2015; Bajic et al, 2016; Hsu et al, 2016)
We evaluated connectivity between pairs of subnetworks (Supplementary Figure S3) and we found a significant decrease of connectivity between the anterior and posterior DMN subnetworks at t4 in the transgenic animals compared to controls
Summary
Alzheimer’s disease (AD) is a progressive age-related neurodegenerative disease, which has become the most common form of dementia in elderly populations. Evidences of early brain changes associated to AD have been suggested decades prior to its clinical diagnosis (Sperling et al, 2011; Vos et al, 2013; Dubois et al, 2016) but the late appearance of AD symptoms hinders the study of the disease progression in human cohorts In this line, the use of transgenic animal models of AD is of great utility, especially in order to tackle the early and silent phases of the disease and to study its longitudinal progression (Leon et al, 2010; Do Carmo et al, 2013; Sabbagh et al, 2013; Galeano et al, 2014). TgF344-AD rats of 9 months exhibited significant cerebrovascular dysfunction dependent on vessel amyloid load and impaired theta-gamma phase-amplitude coupling, indicating neuronal network dysfunction in the early stage of tau and Aβ pathologies (Joo et al, 2017)
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