Towards a Better Understanding of GABAergic Remodeling in Alzheimer’s Disease

Govindpani, Karan; Guzmán, Beatriz Calvo‐Flores; Vinnakota, Chitra; Waldvogel, Henry J.; Faull, Richard L.M.; Kwakowsky, Andrea

doi:10.3390/ijms18081813

Cited by 167 publications

(109 citation statements)

References 343 publications

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“…Analysis of the indexes for temporal-scale-dependent complexity has shown that this reduction of complexity especially concentrates in fast wave components (34,36). Studies of neurotransmitter changes in AD have reported that dysfunction of the gamma-aminobutyric acid (GABA) signaling system, which is caused by the deposition of amyloid-b and tau proteins, leads to reduced oscillatory gamma band activity (68)(69)(70). The impairment of gamma oscillatory activity might lead the complexity at faster temporal scales more than slower temporal scales (34,36).…”

Section: Resultsmentioning

confidence: 99%

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease

et al. 2020

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Electroencephalography (EEG) has long been studied as a potential diagnostic method for Alzheimer's disease (AD). The pathological progression of AD leads to cortical disconnection. These disconnections may manifest as functional connectivity alterations, measured by the degree of synchronization between different brain regions, and alterations in complex behaviors produced by the interaction among widespread brain regions. Recently, machine learning methods, such as clustering algorithms and classification methods, have been adopted to detect disease-related changes in functional connectivity and classify the features of these changes. Although complexity of EEG signals can also reflect AD-related changes, few machine learning studies have focused on the changes in complexity. Therefore, in this study, we compared the ability of EEG signals to detect characteristics of AD using different machine learning approaches one focused on functional connectivity and the other focused on signal complexity. We examined functional connectivity, estimated by phase lag index (PLI) in EEG signals in healthy older participants [healthy control (HC)] and patients with AD. We estimated signal complexity using multi-scale entropy. Utilizing a support vector machine, we compared the identification accuracy of AD based on functional connectivity at each frequency band and complexity component. Additionally, we evaluated the relationship between synchronization and complexity. The identification accuracy of functional connectivity of the alpha, beta, and gamma bands was significantly high (AUC 1.0), and the identification accuracy of complexity was sufficiently high (AUC 0.81). Moreover, the relationship between functional connectivity and complexity exhibited various temporal-scale-andregional-specific dependency in both HC participants and patients with AD. In conclusion, the combination of functional connectivity and complexity might reflect complex pathological process of AD. Applying a combination of both machine learning methods

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Section: Resultsmentioning

confidence: 99%

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease

et al. 2020

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“…It is now well-known that GABA, in addition to glutamate, maintains the excitatory/inhibitory balance, and plays a compensatory role in memory processing (Lanctôt, Herrmaan, Mazzotta, Khan, & Ingber, 2004;Obata, 2013). The importance of GABAergic pathways in remodeling of the AD brain has also been suggested and highlights its role in compensating for the learning and memory impairments in the early stages of AD (Govindpani et al, 2017). Therefore, the GABAergic system is an essential target for the design of novel disease-modifying drugs, although its role in the disease pathogenesis and the cellular changes underlying AD has not been extensively studied (Calvo-Flores Guzmán et al, 2018).…”

Section: Gammapyrone Effects On the Gabaergic System In A Male Ratmentioning

confidence: 99%

GABA‐containing compound gammapyrone protects against brain impairments in Alzheimer’s disease model male rats and prevents mitochondrial dysfunction in cell culture

Piļipenko

Narbute

Amara

et al. 2019

J of Neuroscience Research

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Neuroinflammation, oxidative stress, decreased glucose/energy metabolism, and disrupted neurotransmission are changes that occur early in sporadic Alzheimer’s disease (AD), manifesting as mild cognitive impairment. Recently, the imbalanced function of the gamma‐aminobutyric acid (GABA) system was identified as a critical factor in AD progression. Thus, maintaining balance among neurotransmitter systems, particularly the GABA system, can be considered a beneficial strategy to slow AD progression. The present study investigated the effects of the compound gammapyrone, a molecule containing three GABA moieties: “free” moiety attached to the position 4 of the 1,4‐dihydropyridine (DHP) ring, and two “crypto” moieties as part of the DHP scaffold. The “free” and “crypto” GABA moieties are linked by a peptide bond (–CONH–), resulting in a peptide‐mimicking structure. In a nontransgenic male rat AD model generated by intracerebroventricular (icv) streptozocin (STZ) administration, gammapyrone (0.1 and 0.5 mg/kg ip) mitigated the impairment of spatial learning and memory, prevented astroglial and microglial neuroinflammation, and normalized acetylcholine breakdown and GABA biosynthesis. In PC12 cells, gammapyrone protected against oxidative stress, mitochondrial dysfunction and apoptosis caused by the mitochondrial toxin di‐2‐ethylhexyl phthalate (DEHP). Gammapyrone did not bind to GABA‐A and GABA‐B receptors in vitro; therefore, we cannot attribute its neuroprotective action to a specific interaction with GABA receptors. Nevertheless, we suggest that the peptide‐like regulatory mechanisms of gammapyrone or its allosteric modulatory properties are essential for the observed effects. Since, the icv STZ model resembles the early stages of AD, gammapyrone, and/or its congeners could be useful in the design of anti‐dementia drugs.

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“…It is important to point out that, other potential factors might also contribute to the altered extrasynaptic GABA levels, from changes in GABA uptake and clearance processes. Furthermore, remodeling of GABA A R subunit expression, along with alteration of the expression of GABA transporters (GATs) in the AD brain, may buffer changes in synaptic GABA levels, and ultimately, affect the total levels of extrasynaptic GABA [16][17][18][19][20]. test (* p = 0.0382, ** p = 0.0025; NC n = 4, ACSF-injected n = 4, and Aβ 1-42 -injected n = 5).…”

Section: Resultsmentioning

confidence: 99%

“…However, other neuropathological processes are likely to contribute to the dysfunctional E/I network balance in the hippocampus that leads to cognitive deterioration. Although cognitive decline in AD has been largely related to Aβ oligomers and the glutamatergic system through multiple interactions [31,32], there is growing evidence to suggest that cognitive decline in the AD brain is influenced and also partly precipitated by altered GABAergic function [19], and this has been linked to cognitive decline [33]. In the extrasynaptic space, Aβ 1-42 mediates increase in ambient GABA levels which chronically activates tonic inhibitory currents in the hippocampus, that are involved in the maintenance of the excitatory network and synchronization, and in turn might contribute to the cognitive deficits -but the exact mechanism requires further elucidation.…”

Section: Resultsmentioning

confidence: 99%

Amyloid-Beta1-42 -Induced Increase in GABAergic Tonic Conductance in Mouse Hippocampal CA1 Pyramidal Cells

et al. 2020

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Alzheimer’s disease (AD) is a complex and chronic neurodegenerative disorder that involves a progressive and severe decline in cognition and memory. During the last few decades a considerable amount of research has been done in order to better understand tau-pathology, inflammatory activity and neuronal synapse loss in AD, all of them contributing to cognitive decline. Early hippocampal network dysfunction is one of the main factors associated with cognitive decline in AD. Much has been published about amyloid-beta1-42 (Aβ1-42)-mediated excitotoxicity in AD. However, increasing evidence demonstrates that the remodeling of the inhibitory gamma-aminobutyric acid (GABAergic) system contributes to the excitatory/inhibitory (E/I) disruption in the AD hippocampus, but the underlying mechanisms are not well understood. In the present study, we show that hippocampal injection of Aβ1-42 is sufficient to induce cognitive deficits 7 days post-injection. We demonstrate using in vitro whole-cell patch-clamping an increased inhibitory GABAergic tonic conductance mediated by extrasynaptic type A GABA receptors (GABAARs), recorded in the CA1 region of the mouse hippocampus following Aβ1-42 micro injection. Such alterations in GABA neurotransmission and/or inhibitory GABAARs could have a significant impact on both hippocampal structure and function, causing E/I balance disruption and potentially contributing to cognitive deficits in AD.

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Towards a Better Understanding of GABAergic Remodeling in Alzheimer’s Disease

Cited by 167 publications

References 343 publications

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease

GABA‐containing compound gammapyrone protects against brain impairments in Alzheimer’s disease model male rats and prevents mitochondrial dysfunction in cell culture

Amyloid-Beta1-42 -Induced Increase in GABAergic Tonic Conductance in Mouse Hippocampal CA1 Pyramidal Cells

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