Brain excitability and connectivity of neuronal assemblies in Alzheimer's disease: From animal models to human findings
Highlights
► Early synaptic loss and dysfunction preceding plaque, tangle formation and neuronal loss, are the probable basis of cognitive impairment in AD. ► The pathological accumulation of oligomeric Aβ induces synaptic dysfunction and it elicits aberrant patterns of neuronal circuit activity. ► AD as disconnection syndrome. ► Functional neuroimaging techniques as promising diagnostic tools in the detection of AD.
Introduction
Alzheimer's disease (AD) represents the most common cause of dementia, accounting for 50–60% of all cases (Ferri et al., 2005), stemming from an age-related brain degeneration leading to progressive cognitive and behavioral impairments.
According to the World Alzheimer Report 2011 more than 36 million people in the world are presently affected by dementia, most suffering from AD. This number is expected to increase and the Alzheimer's Disease International estimated an escalation up to 115 million by 2050 with enormous social cost on both patient's families and National Health Service.
One of the most frightening aspects is that the cohort of initial symptoms heralding AD condition is preceded for a long time by a pre-symptomatic stage during which the disease hallmarks are already operative in destroying synapses and connections. The duration of pre-symptomatic stages is quite variable depending on the individual variability in the extent of defense properties including the amount of silent synapses for neuroplasticity mechanisms (for a review see Savioz et al., 2009). Along this track of reasoning, a paramount significance is represented by the Mild Cognitive Impairment (MCI; Petersen et al., 2001), a prodromal stage of the aging-related brain degeneration characterized by a measurable memory impairment (in this case is defined amnestic MCI), in some other cases associated with deficits in other cognitive domains, but not overt dementia (Petersen et al., 2001, Lautenschlager et al., 2005). For instance, the MCI subject is slightly cognitively impaired, but such impairment is not yet impacting with daily life skills and therefore the overall condition is not fulfilling the diagnosis of dementia. The estimated prevalence of MCI condition ranges from 10 to 20% in person older than 65 years of age (Petersen, 2011), and several longitudinal studies have shown that most persons with MCI are at increased risk for the development of dementia, with an annual MCI-to-AD conversion rate ranging from 6 to 40%, according to different series (Petersen et al., 2001, Jack et al., 2005). Indeed, in the MCI subjects the rate to AD progression is several tens of times higher than in the age/sex matched non-MCI elderly population. Recently (Albert et al., 2011), new criteria for MCI have been developed and the diagnosis – even in presence of little clinical deficits – is prompted when neuropsychological tests are associated to instrumental signs of neurodegeneration as revealed by cerebrospinal fluid (CSF), blood/flow brain measurements (PET/SPET) and volumetric Magnetic Resonance Imaging (MRI) markers combined to independent genetic risk factors (Rasquin et al., 2005, Alexopoulos et al., 2006, Dubois et al., 2007).
The most validated histopathological feature of AD brain is the presence of NeuroFibrillary Tangles (NFTs), intra-cellular fibers constituted by hyperphosphorylated aggregates of the microtubule-associated protein tau and extra-cellular deposition composed of amyloid-β (Aβ) peptide, neuritic plaques, somewhat triggering a progressive, selective and massive neuronal loss, primarily impacting on the hippocampal, mesial temporal and parietal cortices (Hardy and Revesz, 2012). These pathological features are based on animal models, follow-up studies in AD and autopsy studies performed on brains of patients in the advanced disease stage.
Now, neuroscientists are asking: What happens in the brain of a patient during early-stage of the disease, namely the pre-symptomatic one?
The classical amyloid hypothesis, which states that AD is caused by the accumulation of deposits containing pathological Aβ peptides, is partly challenged by the demonstrations that in experimental models Aβ induces disruption of connectivity within the neural circuitry, loss of synapses and reduction of synaptic plasticity in key brain regions well before plaque formation/deposition and death of neurons (Hsia et al., 1999, Chapman et al., 1999).
More recently, it has been investigated the effects of Aβ at the level on neuronal circuits (D’Amelio et al., 2011, Ma et al., 2010). In transgenic mice – harboring human Amyloid Precursor Protein (APP) mutant allele linked to familial AD – the accumulation of Aβ causes alterations of glutamatergic synaptic transmission and plasticity, which correlate with dendritic spine degeneration and deficit in hippocampal-dependent memory (D’Amelio et al., 2011).
The dendritic spine organization and its continuous modulation is the anatomical basis of the transient and time-varying connectivity among the neuronal assemblies when they cooperate within a given cognitive (e.g. learning), behavioral, sensory-motor and emotional tasks. This connectivity amongst different neuronal assemblies and networks is dynamically modulated in time (from a time window of weeks or days down to very brief one in the order of tens of milliseconds or even less) and plays a critical role in sustaining brain functions.
Growing evidence derived from neurophysiological studies on functional organization of human brain suggests that connectivity derangement largely contributes to the clinical AD phenotype (Minoshima et al., 1997, Kapogiannis and Mattson, 2011).
In this review, we will discuss recent findings of basic and clinical research indicating the effect of Aβ on neural networks and synaptic function in animal models, as well as the dynamic modifications of the neural network connectivity reported in early stages of AD as addressed via electroencephalographic recordings and other modern neurophysiological techniques.
Section snippets
Anatomy of neuronal circuits affected in AD
The hippocampal formation, including the hippocampus proper and the anatomically related regions (dentate gyrus, subiculum, presubiculum, parasubiculum and entorhinal cortex, Fig. 1), have been identified as the brain structure essential for memory function (Wang and Morris, 2010).
One of the most captivating features of hippocampal formation is its neuroanatomical organization (Amaral and Lavenex, 2007). It shows a highly dense associational intrinsic (Fig. 1) and extrinsic connections with
Lesson from animal models of AD
Animal models of human disease are an invaluable tool in basic and biomedical research being indispensable to closely follow-up in time the evolution of pathological processes that lead to specific AD-like phenotypes with a slow progression.
The mouse is the major species used in AD research, but significant additional insight has been provided from species such as the fruit fly Drosophila melanogaster, Caenorhabidtis elegans and two types of fish, the sea lamprey and the zebrafish (Götz and
How Aβ and tau attack the synapses?
The search for molecular mechanisms by which Aβ impairs synaptic transmission and plasticity and contributes to neurodegeneration, including synapse dysfunction, behavioral deficits and, ultimately, neuronal cell death, is the main interest among the basic and clinically oriented neuroscientists, and this field has grown over the last 10 years from a collection of tantalizing observations.
Here, we focus on the pathogenic interplay between Aβ, tau and synaptic ion channels, that all play a
Evidence for aberrant activity in neuronal networks of AD patients
The nature of AD symptomatology, which eventually affects many aspects of brain functions, in particular complex cognitive processes such as attention, visuospatial orientation, and language in addition to episodic memory, as well as the selective involvement of multiple cortical “convergence zones” (Arnold et al., 1991) have led to the conceptualization of AD syndrome as a disease of multiple, large-scale neural networks (Seeley et al., 2009).
By the time AD dementia is diagnosed clinically,
Acknowledgments
MDA is financially supported by PRIN 2009 (Projects for Research of National Interest) and by a grant from the Alzheimer's Association (NIRG-11-204588).
We are grateful to Dr. Annalisa Nobili for helpful discussion and revision of manuscript.
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