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Zhuang D, Yu N, Han S, Zhang X, Ju C. The Kv7 channel opener Retigabine reduces neuropathology and alleviates behavioral deficits in APP/PS1 transgenic mice. Behav Brain Res 2024; 471:115137. [PMID: 38971432 DOI: 10.1016/j.bbr.2024.115137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 06/19/2024] [Accepted: 07/01/2024] [Indexed: 07/08/2024]
Abstract
Hyperexcitability of neuronal networks is central to the pathogenesis of Alzheimer's disease (AD). Pharmacological activation of Kv7 channels is an effective way to reduce neuronal firing. Our results showed that that pharmacologically activating the Kv7 channel with Retigabine (RTG) can alleviate cognitive impairment in mice without affecting spontaneous activity. RTG could also ameliorate damage to the Nissl bodies in cortex and hippocampal CA and DG regions in 9-month-old APP/PS1 mice. Additionally, RTG could reduce the Aβ plaque number in the hippocampus and cortex of both 6-month-old and 9-month-old mice. By recordings of electroencephalogram, we showed that a decrease in the number of abnormal discharges in the brains of the AD model mice when the Kv7 channel was opened. Moreover, Western blot analysis revealed a reduction in the expression of the p-Tau protein in both the hippocampus and cortex upon Kv7 channel opening. These findings suggest that Kv7 channel opener RTG may ameliorate cognitive impairment in AD, most likely by reducing brain excitability.
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Affiliation(s)
- Dongpei Zhuang
- Department of Pharmacology, School of Pharmacy, Qingdao University Qingdao Medical College, China.
| | - Nan Yu
- Department of Pharmacy, Qingdao Eighth People's Hospital, China.
| | - Shuo Han
- Department of Pharmacology, School of Pharmacy, Qingdao University Qingdao Medical College, China.
| | - Xinyao Zhang
- Department of Pharmacology, School of Pharmacy, Qingdao University Qingdao Medical College, China.
| | - Chuanxia Ju
- Department of Pharmacology, School of Pharmacy, Qingdao University Qingdao Medical College, China.
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2
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Stam CJ, de Haan W. Network Hyperexcitability in Early-Stage Alzheimer's Disease: Evaluation of Functional Connectivity Biomarkers in a Computational Disease Model. J Alzheimers Dis 2024; 99:1333-1348. [PMID: 38759000 PMCID: PMC11191539 DOI: 10.3233/jad-230825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/18/2024] [Indexed: 05/19/2024]
Abstract
Background There is increasing evidence from animal and clinical studies that network hyperexcitability (NH) may be an important pathophysiological process and potential target for treatment in early Alzheimer's disease (AD). Measures of functional connectivity (FC) have been proposed as promising biomarkers for NH, but it is unknown which measure has the highest sensitivity for early-stage changes in the excitation/inhibition balance. Objective We aim to test the performance of different FC measures in detecting NH at the earliest stage using a computational approach. Methods We use a whole brain computational model of activity dependent degeneration to simulate progressive AD pathology and NH. We investigate if and at what stage four measures of FC (amplitude envelope correlation corrected [AECc], phase lag index [PLI], joint permutation entropy [JPE] and a new measure: phase lag time [PLT]) can detect early-stage AD pathophysiology. Results The activity dependent degeneration model replicates spectral changes in line with clinical data and demonstrates increasing NH. Compared to relative theta power as a gold standard the AECc and PLI are shown to be less sensitive in detecting early-stage NH and AD-related neurophysiological abnormalities, while the JPE and the PLT show more sensitivity with excellent test characteristics. Conclusions Novel FC measures, which are better in detecting rapid fluctuations in neural activity and connectivity, may be superior to well-known measures such as the AECc and PLI in detecting early phase neurophysiological abnormalities and in particular NH in AD. These markers could improve early diagnosis and treatment target identification.
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Affiliation(s)
- Cornelis Jan Stam
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
| | - Willem de Haan
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (Amsterdam UMC), Amsterdam, The Netherlands
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3
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Caiola HO, Wu Q, Soni S, Wang XF, Monahan K, Pang ZP, Wagner GC, Zhang H. Neuronal connectivity, behavioral, and transcriptional alterations associated with the loss of MARK2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.569759. [PMID: 38105965 PMCID: PMC10723285 DOI: 10.1101/2023.12.05.569759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Neuronal connectivity is essential for adaptive brain responses and can be modulated by dendritic spine plasticity and the intrinsic excitability of individual neurons. Dysregulation of these processes can lead to aberrant neuronal activity, which has been associated with numerous neurological disorders including autism, epilepsy, and Alzheimer's disease. Nonetheless, the molecular mechanisms underlying aberrant neuronal connectivity remains unclear. We previously found that the serine/threonine kinase Microtubule Affinity Regulating Kinase 2 (MARK2), also known as Partitioning Defective 1b (Par1b), is important for the formation of dendritic spines in vitro. However, despite its genetic association with several neurological disorders, the in vivo impact of MARK2 on neuronal connectivity and cognitive functions remains unclear. Here, we demonstrate that loss of MARK2 in vivo results in changes to dendritic spine morphology, which in turn leads to a decrease in excitatory synaptic transmission. Additionally, loss of MARK2 produces substantial impairments in learning and memory, anxiety, and social behavior. Notably, MARK2 deficiency results in heightened seizure susceptibility. Consistent with this observation, RNAseq analysis reveals transcriptional changes in genes regulating synaptic transmission and ion homeostasis. These findings underscore the in vivo role of MARK2 in governing synaptic connectivity, cognitive functions, and seizure susceptibility.
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Monteverdi A, Palesi F, Schirner M, Argentino F, Merante M, Redolfi A, Conca F, Mazzocchi L, Cappa SF, Cotta Ramusino M, Costa A, Pichiecchio A, Farina LM, Jirsa V, Ritter P, Gandini Wheeler-Kingshott CAM, D’Angelo E. Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias. Front Aging Neurosci 2023; 15:1204134. [PMID: 37577354 PMCID: PMC10419271 DOI: 10.3389/fnagi.2023.1204134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission. Methods We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks. Results The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles. Discussion These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.
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Affiliation(s)
- Anita Monteverdi
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Michael Schirner
- Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Francesca Argentino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Mariateresa Merante
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Laura Mazzocchi
- Advanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Stefano F. Cappa
- IRCCS Mondino Foundation, Pavia, Italy
- University Institute of Advanced Studies (IUSS), Pavia, Italy
| | | | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Anna Pichiecchio
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, INSERM, INS, Aix Marseille University, Marseille, France
| | - Petra Ritter
- Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Egidio D’Angelo
- Unit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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5
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Corniello C, Dono F, Evangelista G, Consoli S, De Angelis S, Cipollone S, Liviello D, Polito G, Melchiorre S, Russo M, Granzotto A, Anzellotti F, Onofrj M, Thomas A, Sensi SL. Diagnosis and treatment of late-onset myoclonic epilepsy in Down syndrome (LOMEDS): A systematic review with individual patients' data analysis. Seizure 2023; 109:62-67. [PMID: 37267668 DOI: 10.1016/j.seizure.2023.05.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 05/18/2023] [Accepted: 05/20/2023] [Indexed: 06/04/2023] Open
Abstract
INTRODUCTION The late onset myoclonic epilepsy in Down Syndrome (LOMEDS) is a peculiar epilepsy type characterized by cortical myoclonus and generalized tonic-clonic seizures (GTCS), in people suffering from cognitive decline in Down syndrome (DS). In this review, we analyzed available data on the diagnostic and therapeutic management of individuals with LOMEDS. METHODS We performed a systematic search of the literature to identify the diagnostic and therapeutic management of patients with LOMEDS. The following databases were used: PubMed, Google Scholar, EMBASE, CrossRef. The protocol was registered on PROSPERO (registration code: CRD42023390748). RESULTS Data from 46 patients were included. DS was diagnosed according to the patient's clinical and genetic characteristics. Diagnosis of Alzheimer's dementia (AD) preceded the onset of epilepsy in all cases. Both myoclonic seizures (MS) and generalized tonic-clonic seizures (GTCS) were reported, the latter preceding the onset of MS in 28 cases. EEG was performed in 45 patients, showing diffuse theta/delta slowing with superimposed generalized spike-and-wave or polyspike-and-wave. A diffuse cortical atrophy was detected in 34 patients on neuroimaging. Twenty-seven patients were treated with antiseizure medication (ASM) monotherapy, with reduced seizure frequency in 17 patients. Levetiracetam and valproic acid were the most used ASMs. Up to 41% of patients were unresponsive to first-line treatment and needed adjunctive therapy for seizure control. CONCLUSIONS AD-related pathological changes in the brain may play a role in LOMEDS onset, although the mechanism underlying this phenomenon is still unknown. EEG remains the most relevant investigation to be performed. A significant percentage of patients developed a first-line ASM refractory epilepsy. ASMs which modulate the glutamatergic system may represent a good therapeutic option.
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Affiliation(s)
- Clarissa Corniello
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy
| | - Fedele Dono
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy.
| | - Giacomo Evangelista
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | - Stefano Consoli
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | - Sibilla De Angelis
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy
| | - Sara Cipollone
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy
| | - Davide Liviello
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Epilepsy Center, "SS Annunziata" Hospital, Chieti, Italy
| | - Gaetano Polito
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Sara Melchiorre
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | - Alberto Granzotto
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | | | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | - Astrid Thomas
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Science, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Behavioral Neurology and Molecular Neurology Units, Center for Advanced Studies and Technology - CAST, University "G. d'Annunzio" of Chieti-Pescara, Italy; Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Italy
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6
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Stam CJ, van Nifterick AM, de Haan W, Gouw AA. Network Hyperexcitability in Early Alzheimer's Disease: Is Functional Connectivity a Potential Biomarker? Brain Topogr 2023:10.1007/s10548-023-00968-7. [PMID: 37173584 DOI: 10.1007/s10548-023-00968-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/26/2023] [Indexed: 05/15/2023]
Abstract
Network hyperexcitability (NH) is an important feature of the pathophysiology of Alzheimer's disease. Functional connectivity (FC) of brain networks has been proposed as a potential biomarker for NH. Here we use a whole brain computational model and resting-state MEG recordings to investigate the relation between hyperexcitability and FC. Oscillatory brain activity was simulated with a Stuart Landau model on a network of 78 interconnected brain regions. FC was quantified with amplitude envelope correlation (AEC) and phase coherence (PC). MEG was recorded in 18 subjects with subjective cognitive decline (SCD) and 18 subjects with mild cognitive impairment (MCI). Functional connectivity was determined with the corrected AECc and phase lag index (PLI), in the 4-8 Hz and the 8-13 Hz bands. The excitation/inhibition balance in the model had a strong effect on both AEC and PC. This effect was different for AEC and PC, and was influenced by structural coupling strength and frequency band. Empirical FC matrices of SCD and MCI showed a good correlation with model FC for AEC, but less so for PC. For AEC the fit was best in the hyperexcitable range. We conclude that FC is sensitive to changes in E/I balance. The AEC was more sensitive than the PLI, and results were better for the thetaband than the alpha band. This conclusion was supported by fitting the model to empirical data. Our study justifies the use of functional connectivity measures as surrogate markers for E/I balance.
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Affiliation(s)
- C J Stam
- Department of Neurology, Amsterdam Neuroscience, Clinical Neurophysiology and MEG Center, Vrij Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
| | - A M van Nifterick
- Department of Neurology, Amsterdam Neuroscience, Clinical Neurophysiology and MEG Center, Vrij Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - W de Haan
- Department of Neurology, Amsterdam Neuroscience, Clinical Neurophysiology and MEG Center, Vrij Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - A A Gouw
- Department of Neurology, Amsterdam Neuroscience, Clinical Neurophysiology and MEG Center, Vrij Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
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7
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Ali AB, Islam A, Constanti A. The fate of interneurons, GABA A receptor sub-types and perineuronal nets in Alzheimer's disease. Brain Pathol 2022; 33:e13129. [PMID: 36409151 PMCID: PMC9836378 DOI: 10.1111/bpa.13129] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/12/2022] [Indexed: 11/23/2022] Open
Abstract
Alzheimer's disease (AD) is the most common neurological disease, which is associated with gradual memory loss and correlated with synaptic hyperactivity and abnormal oscillatory rhythmic brain activity that precedes phenotypic alterations and is partly responsible for the spread of the disease pathology. Synaptic hyperactivity is thought to be because of alteration in the homeostasis of phasic and tonic synaptic inhibition, which is orchestrated by the GABAA inhibitory system, encompassing subclasses of interneurons and GABAA receptors, which play a vital role in cognitive functions, including learning and memory. Furthermore, the extracellular matrix, the perineuronal nets (PNNs) which often go unnoticed in considerations of AD pathology, encapsulate the inhibitory cells and neurites in critical brain regions and have recently come under the light for their crucial role in synaptic stabilisation and excitatory-inhibitory balance and when disrupted, serve as a potential trigger for AD-associated synaptic imbalance. Therefore, in this review, we summarise the current understanding of the selective vulnerability of distinct interneuron subtypes, their synaptic and extrasynaptic GABAA R subtypes as well as the changes in PNNs in AD, detailing their contribution to the mechanisms of disease development. We aim to highlight how seemingly unique malfunction in each component of the interneuronal GABA inhibitory system can be tied together to result in critical circuit dysfunction, leading to the irreversible symptomatic damage observed in AD.
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8
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Babiloni C. The Dark Side of Alzheimer's Disease: Neglected Physiological Biomarkers of Brain Hyperexcitability and Abnormal Consciousness Level. J Alzheimers Dis 2022; 88:801-807. [PMID: 35754282 DOI: 10.3233/jad-220582] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
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9
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Fortel I, Butler M, Korthauer LE, Zhan L, Ajilore O, Sidiropoulos A, Wu Y, Driscoll I, Schonfeld D, Leow A. Inferring excitation-inhibition dynamics using a maximum entropy model unifying brain structure and function. Netw Neurosci 2022; 6:420-444. [PMID: 35733430 PMCID: PMC9205431 DOI: 10.1162/netn_a_00220] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 12/07/2021] [Indexed: 11/04/2022] Open
Abstract
Neural activity coordinated across different scales from neuronal circuits to large-scale brain networks gives rise to complex cognitive functions. Bridging the gap between micro- and macroscale processes, we present a novel framework based on the maximum entropy model to infer a hybrid resting-state structural connectome, representing functional interactions constrained by structural connectivity. We demonstrate that the structurally informed network outperforms the unconstrained model in simulating brain dynamics, wherein by constraining the inference model with the network structure we may improve the estimation of pairwise BOLD signal interactions. Further, we simulate brain network dynamics using Monte Carlo simulations with the new hybrid connectome to probe connectome-level differences in excitation-inhibition balance between apolipoprotein E (APOE)-ε4 carriers and noncarriers. Our results reveal sex differences among APOE-ε4 carriers in functional dynamics at criticality; specifically, female carriers appear to exhibit a lower tolerance to network disruptions resulting from increased excitatory interactions. In sum, the new multimodal network explored here enables analysis of brain dynamics through the integration of structure and function, providing insight into the complex interactions underlying neural activity such as the balance of excitation and inhibition.
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Affiliation(s)
- Igor Fortel
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Mitchell Butler
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Laura E. Korthauer
- Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
- Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Yichao Wu
- Department of Math, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, USA
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
| | - Dan Schonfeld
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Alex Leow
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
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10
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Tok S, Maurin H, Delay C, Crauwels D, Manyakov NV, Van Der Elst W, Moechars D, Drinkenburg WHIM. Neurophysiological effects of human-derived pathological tau conformers in the APPKM670/671NL.PS1/L166P amyloid mouse model of Alzheimer's disease. Sci Rep 2022; 12:7784. [PMID: 35546164 PMCID: PMC9094605 DOI: 10.1038/s41598-022-11582-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 04/19/2022] [Indexed: 11/09/2022] Open
Abstract
Alzheimer’s Disease (AD) is a neurodegenerative disease characterized by two main pathological hallmarks: amyloid plaques and intracellular tau neurofibrillary tangles. However, a majority of studies focus on the individual pathologies and seldom on the interaction between the two pathologies. Herein, we present the longitudinal neuropathological and neurophysiological effects of a combined amyloid-tau model by hippocampal seeding of human-derived tau pathology in the APP.PS1/L166P amyloid animal model. We statistically assessed both neurophysiological and pathological changes using linear mixed modelling to determine if factors such as the age at which animals were seeded, genotype, seeding or buffer, brain region where pathology was quantified, and time-post injection differentially affect these outcomes. We report that AT8-positive tau pathology progressively develops and is facilitated by the amount of amyloid pathology present at the time of injection. The amount of AT8-positive tau pathology was influenced by the interaction of age at which the animal was injected, genotype, and time after injection. Baseline pathology-related power spectra and Higuchi Fractal Dimension (HFD) score alterations were noted in APP.PS1/L166P before any manipulations were performed, indicating a baseline difference associated with genotype. We also report immediate localized hippocampal dysfunction in the electroencephalography (EEG) power spectra associated with tau seeding which returned to comparable levels at 1 month-post-injection. Longitudinal effects of seeding indicated that tau-seeded wild-type mice showed an increase in gamma power earlier than buffer control comparisons which was influenced by the age at which the animal was injected. A reduction of hippocampal broadband power spectra was noted in tau-seeded wild-type mice, but absent in APP.PS1 animals. HFD scores appeared to detect subtle effects associated with tau seeding in APP.PS1 animals, which was differentially influenced by genotype. Notably, while tau histopathological changes were present, a lack of overt longitudinal electrophysiological alterations was noted, particularly in APP.PS1 animals that feature both pathologies after seeding, reiterating and underscoring the difficulty and complexity associated with elucidating physiologically relevant and translatable biomarkers of Alzheimer’s Disease at the early stages of the disease.
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Affiliation(s)
- S Tok
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium. .,Faculty of Science and Engineering, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.
| | - H Maurin
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - C Delay
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Crauwels
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - N V Manyakov
- Data Sciences, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W Van Der Elst
- Quantitative Sciences Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Moechars
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W H I M Drinkenburg
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium.,Faculty of Science and Engineering, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands
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