Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease

Alzheimer's Disease and Epilepsy: Exploring Shared Pathways and Promising Biomarkers for Future Treatments

Background: Alzheimer's disease (AD) and epilepsy represent two complex neurological disorders with distinct clinical manifestations, yet recent research has highlighted their intricate interplay. This review examines the association between AD and epilepsy, with particular emphasis on late-onset epilepsy of unknown etiology, increasingly acknowledged as a prodrome of AD. It delves into epidemiology, pathogenic mechanisms, clinical features, diagnostic characteristics, treatment strategies, and emerging biomarkers to provide a comprehensive understanding of this relationship. Methods: A comprehensive literature search was conducted, identifying 128 relevant articles published between 2018 and 2024. Results: Findings underscore a bidirectional relationship between AD and epilepsy, indicating shared pathogenic pathways that extend beyond traditional amyloid-beta and Tau protein pathology. These pathways encompass neuroinflammation, synaptic dysfunction, structural and network alterations, as well as molecular mechanisms. Notably, epileptic activity in AD patients may exacerbate cognitive decline, necessitating prompt detection and treatment. Novel biomarkers, such as subclinical epileptiform activity detected via advanced electroencephalographic techniques, offer promise for early diagnosis and targeted interventions. Furthermore, emerging therapeutic approaches targeting shared pathogenic mechanisms hold potential for disease modification in both AD and epilepsy. Conclusions: This review highlights the importance of understanding the relationship between AD and epilepsy, providing insights into future research directions. Clinical data and diagnostic methods are also reviewed, enabling clinicians to implement more effective treatment strategies.

ZCCHC17 knockdown phenocopies Alzheimer's disease-related loss of synaptic proteins and hyperexcitability

ZCCHC17 is a master regulator of synaptic gene expression and has recently been shown to play a role in splicing of neuronal mRNA. We previously showed that ZCCHC17 protein declines in Alzheimer's disease (AD) brain tissue before there is significant gliosis and neuronal loss, that ZCCHC17 loss partially replicates observed splicing abnormalities in AD brain tissue, and that maintenance of ZCCHC17 levels is predicted to support cognitive resilience in AD. Here, we assessed the functional consequences of reduced ZCCHC17 expression in primary cortical neuronal cultures using siRNA knockdown. Consistent with its previously identified role in synaptic gene expression, loss of ZCCHC17 led to loss of synaptic protein expression. Patch recording of neurons shows that ZCCHC17 loss significantly disrupted the excitation/inhibition balance of neurotransmission, and favored excitatory-dominant synaptic activity as measured by an increase in spontaneous excitatory post synaptic currents and action potential firing rate, and a decrease in spontaneous inhibitory post synaptic currents. These findings are consistent with the hyperexcitable phenotype seen in AD animal models and in patients. We are the first to assess the functional consequences of ZCCHC17 knockdown in neurons and conclude that ZCCHC17 loss partially phenocopies AD-related loss of synaptic proteins and hyperexcitability.

Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease

INTRODUCTION

Sleep disturbances are common in Alzheimer's disease (AD) and may reflect pathologic changes in brain networks. To date, no studies have examined changes in sleep functional connectivity (FC) in AD or their relationship with network hyperexcitability and cognition.

METHODS

We assessed electroencephalogram (EEG) sleep FC in 33 healthy controls, 36 individuals with AD without epilepsy, and 14 individuals with AD and epilepsy.

RESULTS

AD participants showed increased gamma connectivity in stage 2 sleep (N2), which was associated with longitudinal cognitive decline. Network hyperexcitability in AD was associated with a distinct sleep connectivity signature, characterized by decreased N2 delta connectivity and reversal of several connectivity changes associated with AD. Machine learning algorithms using sleep connectivity features accurately distinguished diagnostic groups and identified "fast cognitive decliners" among study participants who had AD.

DISCUSSION

Our findings reveal changes in sleep functional networks associated with cognitive decline in AD and may have implications for disease monitoring and therapeutic development.

HIGHLIGHTS

Brain functional connectivity (FC) in Alzheimer's disease is altered during sleep. Sleep FC measures correlate with cognitive decline in AD. Network hyperexcitability in AD has a distinct sleep connectivity signature.

Persistent ∆FosB expression limits recurrent seizure activity and provides neuroprotection in the dentate gyrus of APP mice

Recurrent seizures lead to accumulation of the activity-dependent transcription factor ∆FosB in hippocampal dentate granule cells in both mouse models of epilepsy and mouse models of Alzheimer's disease (AD), which is also associated with increased incidence of seizures. In patients with AD and related mouse models, the degree of ∆FosB accumulation corresponds with increasing severity of cognitive deficits. We previously found that ∆FosB impairs spatial memory in mice by epigenetically regulating expression of target genes such as calbindin that are involved in synaptic plasticity. However, the suppression of calbindin in conditions of neuronal hyperexcitability has been demonstrated to provide neuroprotection to dentate granule cells, indicating that ∆FosB may act over long timescales to coordinate neuroprotective pathways. To test this hypothesis, we used viral-mediated expression of ∆JunD to interfere with ∆FosB signaling over the course of several months in transgenic mice expressing mutant human amyloid precursor protein (APP), which exhibit spontaneous seizures and develop AD-related neuropathology and cognitive deficits. Our results demonstrate that persistent ∆FosB activity acts through discrete modes of hippocampal target gene regulation to modulate neuronal excitability, limit recurrent seizure activity, and provide neuroprotection to hippocampal dentate granule cells in APP mice.

Dynamic functional connectivity is modulated by the amount of p-Tau231 in blood in cognitively intact participants

INTRODUCTION

Electrophysiology and plasma biomarkers are early and non-invasive candidates for Alzheimer's disease detection. The purpose of this paper is to evaluate changes in dynamic functional connectivity measured with magnetoencephalography, associated with the plasma pathology marker p-tau231 in unimpaired adults.

METHODS

73 individuals were included. Static and dynamic functional connectivity were calculated using leakage corrected amplitude envelope correlation. Each source's strength entropy across trials was calculated. A data-driven statistical analysis was performed to find the association between functional connectivity and plasma p-tau231 levels. Regression models were used to assess the influence of other variables over the clusters' connectivity.

RESULTS

Frontotemporal dynamic connectivity positively associated with p-tau231 levels. Linear regression models identified pathological, functional and structural factors that influence dynamic functional connectivity.

DISCUSSION

These results expand previous literature on dynamic functional connectivity in healthy individuals at risk of AD, highlighting its usefulness as an early, non-invasive and more sensitive biomarker.

Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition

BACKGROUND

The hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social and demographic heterogeneities on this hypothesis remains to be addressed.

METHODS

We inferred regional inhibition by fitting a biophysical whole-brain model (dynamic mean field model with realistic inter-areal connectivity) to fMRI data from 414 participants, including patients with Alzheimer's disease, behavioral variant frontotemporal dementia, and controls. We then investigated the effect of disease condition, and demographic and clinical variables on the local inhibitory feedback, a variable related to the maintenance of balanced neural excitation/inhibition.

RESULTS

Decreased local inhibitory feedback was inferred from the biophysical modeling results in dementia patients, specific to brain areas presenting neurodegeneration. This loss of local inhibition correlated positively with years with disease, and showed differences regarding the gender and geographical origin of the patients. The model correctly reproduced known disease-related changes in functional connectivity.

CONCLUSIONS

Results suggest a critical link between abnormal neural and circuit-level excitability levels, the loss of grey matter observed in dementia, and the reorganization of functional connectivity, while highlighting the sensitivity of the underlying biophysical mechanism to demographic and clinical heterogeneities in the patient population.

Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.

Local signal variability and functional connectivity: Sensitive measures of the excitation-inhibition ratio?

A novel network version of permutation entropy, the inverted joint permutation entropy (JPEinv), holds potential as non-invasive biomarker of abnormal excitation-inhibition (E-I) ratio in Alzheimer's disease (AD). In this computational modelling study, we test the hypotheses that this metric, and related measures of signal variability and functional connectivity, are sensitive to altered E-I ratios. The E-I ratio in each neural mass of a whole-brain computational network model was systematically varied. We evaluated whether JPEinv, local signal variability (by permutation entropy) and functional connectivity (by weighted symbolic mutual information (wsMI)) were related to E-I ratio, on whole-brain and regional level. The hub disruption index can identify regions primarily affected in terms of functional connectivity strength (or: degree) by the altered E-I ratios. Analyses were performed for a range of coupling strengths, filter and time-delay settings. On whole-brain level, higher E-I ratios were associated with higher functional connectivity (by JPEinv and wsMI) and lower local signal variability. These relationships were nonlinear and depended on the coupling strength, filter and time-delay settings. On regional level, hub-like regions showed a selective decrease in functional degree (by JPEinv and wsMI) upon a lower E-I ratio, and non-hub-like regions showed a selective increase in degree upon a higher E-I ratio. These results suggest that abnormal functional connectivity and signal variability, as previously reported in patients across the AD continuum, can inform us about altered E-I ratios.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-10003-x.

Diagnosing epileptic seizures in patients with Alzheimer's disease and deciding on the appropriate treatment plan

INTRODUCTION

Alzheimer's disease (AD) is the predominant cause of dementia and a significant contributor to morbidity among the elderly. Patients diagnosed with AD face an increased risk of epileptic seizures.

AREAS COVERED

Herein, the authors review the challenges in the diagnosis of seizures in patients with AD, the risks of seizures related to medications used in AD and the pharmacological treatment of seizures in AD. The authors also provide the reader with their expert opinion on the subject matter and future perspectives.

EXPERT OPINION

Healthcare professionals should maintain a vigilant approach to suspecting seizures in AD patients. Acute symptomatic seizures triggered by metabolic disturbances, infections, toxins, or drug-related factors often have a low risk of recurrence. In such cases, addressing the underlying cause may suffice without initiating antiseizure medications (ASMs). However, unprovoked seizures in certain AD patients carry a higher risk of recurrence over time, warranting the use of ASMs. Although data is limited, both lamotrigine and levetiracetam appear to be reasonable choices for controlling seizures in elderly AD patients. Decisions should be informed by the best available evidence, the treating physician's clinical experience, and the patient's preferences.

Hub overload and failure as a final common pathway in neurological brain network disorders

Understanding the concept of network hubs and their role in brain disease is now rapidly becoming important for clinical neurology. Hub nodes in brain networks are areas highly connected to the rest of the brain, which handle a large part of all the network traffic. They also show high levels of neural activity and metabolism, which makes them vulnerable to many different types of pathology. The present review examines recent evidence for the prevalence and nature of hub involvement in a variety of neurological disorders, emphasizing common themes across different types of pathology. In focal epilepsy, pathological hubs may play a role in spreading of seizure activity, and removal of such hub nodes is associated with improved outcome. In stroke, damage to hubs is associated with impaired cognitive recovery. Breakdown of optimal brain network organization in multiple sclerosis is accompanied by cognitive dysfunction. In Alzheimer's disease, hyperactive hub nodes are directly associated with amyloid-beta and tau pathology. Early and reliable detection of hub pathology and disturbed connectivity in Alzheimer's disease with imaging and neurophysiological techniques opens up opportunities to detect patients with a network hyperexcitability profile, who could benefit from treatment with anti-epileptic drugs.

Neurophysiological trajectories in Alzheimer's disease progression

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Neurophysiological trajectories in Alzheimer's disease progression

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Epilepsy and epileptiform activity in late-onset Alzheimer disease: clinical and pathophysiological advances, gaps and conundrums

A growing body of evidence has demonstrated a link between Alzheimer disease (AD) and epilepsy. Late-onset epilepsy and epileptiform activity can precede cognitive deterioration in AD by years, and its presence has been shown to predict a faster disease course. In animal models of AD, amyloid and tau pathology are linked to cortical network hyperexcitability that precedes the first signs of memory decline. Thus, detection of epileptiform activity in AD has substantial clinical importance as a potential novel modifiable risk factor for dementia. In this Review, we summarize the epidemiological evidence for the complex bidirectional relationship between AD and epilepsy, examine the effect of epileptiform activity and seizures on cognition in people with AD, and discuss the precision medicine treatment strategies based on the latest research in human and animal models. Finally, we outline some of the unresolved questions of the field that should be addressed by rigorous research, including whether particular clinicopathological subtypes of AD have a stronger association with epilepsy, and the sequence of events between epileptiform activity and amyloid and tau pathology.

Latest advances in mechanisms of epileptic activity in Alzheimer's disease and dementia with Lewy Bodies

Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) stand as the prevailing sources of neurodegenerative dementia, impacting over 55 million individuals across the globe. Patients with AD and DLB exhibit a higher prevalence of epileptic activity compared to those with other forms of dementia. Seizures can accompany AD and DLB in early stages, and the associated epileptic activity can contribute to cognitive symptoms and exacerbate cognitive decline. Aberrant neuronal activity in AD and DLB may be caused by several mechanisms that are not yet understood. Hyperexcitability could be a biomarker for early detection of AD or DLB before the onset of dementia. In this review, we compare and contrast mechanisms of network hyperexcitability in AD and DLB. We examine the contributions of genetic risk factors, Ca2+ dysregulation, glutamate, AMPA and NMDA receptors, mTOR, pathological amyloid beta, tau and α-synuclein, altered microglial and astrocytic activity, and impaired inhibitory interneuron function. By gaining a deeper understanding of the molecular mechanisms that cause neuronal hyperexcitability, we might uncover therapeutic approaches to effectively ease symptoms and slow down the advancement of AD and DLB.

Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG

BACKGROUND

Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency.

METHODS

Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score.

RESULTS

The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%.

CONCLUSION

The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.

Network Hyperexcitability in Early-Stage Alzheimer's Disease: Evaluation of Functional Connectivity Biomarkers in a Computational Disease Model

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.

Aberrant DJ-1 expression underlies L-type calcium channel hypoactivity in dendrites in tuberous sclerosis complex and Alzheimer's disease

L-type voltage-gated calcium (Ca2+) channels (L-VGCC) dysfunction is implicated in several neurological and psychiatric diseases. While a popular therapeutic target, it is unknown whether molecular mechanisms leading to disrupted L-VGCC across neurodegenerative disorders are conserved. Importantly, L-VGCC integrate synaptic signals to facilitate a plethora of cellular mechanisms; however, mechanisms that regulate L-VGCC channel density and subcellular compartmentalization are understudied. Herein, we report that in disease models with overactive mammalian target of rapamycin complex 1 (mTORC1) signaling (or mTORopathies), deficits in dendritic L-VGCC activity are associated with increased expression of the RNA-binding protein (RBP) Parkinsonism-associated deglycase (DJ-1). DJ-1 binds the mRNA coding for the alpha and auxiliary Ca2+ channel subunits CaV1.2 and α2δ2, and represses their mRNA translation, only in the disease states, specifically preclinical models of tuberous sclerosis complex (TSC) and Alzheimer's disease (AD). In agreement, DJ-1-mediated repression of CaV1.2/α2δ2 protein synthesis in dendrites is exaggerated in mouse models of AD and TSC, resulting in deficits in dendritic L-VGCC calcium activity. Finding of DJ-1-regulated L-VGCC activity in dendrites in TSC and AD provides a unique signaling pathway that can be targeted in clinical mTORopathies.

Dynamic functional connectivity MEG features of Alzheimer's disease

Dynamic resting state functional connectivity (RSFC) characterizes time-varying fluctuations of functional brain network activity. While many studies have investigated static functional connectivity, it has been unclear whether features of dynamic functional connectivity are associated with neurodegenerative diseases. Popular sliding-window and clustering methods for extracting dynamic RSFC have various limitations that prevent extracting reliable features to address this question. Here, we use a novel and robust time-varying dynamic network (TVDN) approach to extract the dynamic RSFC features from high resolution magnetoencephalography (MEG) data of participants with Alzheimer's disease (AD) and matched controls. The TVDN algorithm automatically and adaptively learns the low-dimensional spatiotemporal manifold of dynamic RSFC and detects dynamic state transitions in data. We show that amongst all the functional features we investigated, the dynamic manifold features are the most predictive of AD. These include: the temporal complexity of the brain network, given by the number of state transitions and their dwell times, and the spatial complexity of the brain network, given by the number of eigenmodes. These dynamic features have higher sensitivity and specificity in distinguishing AD from healthy subjects than the existing benchmarks do. Intriguingly, we found that AD patients generally have higher spatial complexity but lower temporal complexity compared with healthy controls. We also show that graph theoretic metrics of dynamic component of TVDN are significantly different in AD versus controls, while static graph metrics are not statistically different. These results indicate that dynamic RSFC features are impacted in neurodegenerative disease like Alzheimer's disease, and may be crucial to understanding the pathophysiological trajectory of these diseases.

Modification of astrocytic Cx43 hemichannel activity in animal models of AD: modulation by adenosine A2A receptors

Increasing evidence implicates astrocytic dysfunction in Alzheimer's disease (AD), a neurodegenerative disorder characterised by progressive cognitive loss. The accumulation of amyloid-β (Aβ) plaques is a histopathological hallmark of AD and associated with increased astrocyte reactivity. In APP/PS1 mice modelling established AD (9 months), we now show an altered astrocytic morphology and enhanced activity of astrocytic hemichannels, mainly composed by connexin 43 (Cx43). Hemichannel activity in hippocampal astrocytes is also increased in two models of early AD: (1) mice with intracerebroventricular (icv) administration of Aβ1-42, and (2) hippocampal slices superfused with Aβ1-42 peptides. In hippocampal gliosomes of APP/PS1 mice, Cx43 levels were increased, whereas mice administered icv with Aβ1-42 only displayed increased Cx43 phosphorylation levels. This suggests that hemichannel activity might be differentially modulated throughout AD progression. Additionally, we tested if adenosine A2A receptor (A2AR) blockade reversed alterations of astrocytic hemichannel activity and found that the pharmacological blockade or genetic silencing (global and astrocytic) of A2AR prevented Aβ-induced hemichannel dysregulation in hippocampal slices, although A2AR genetic silencing increased the activity of astroglial hemichannels in control conditions. In primary cultures of astrocytes, A2AR-related protective effect was shown to occur through a protein kinase C (PKC) pathway. Our results indicate that the dysfunction of hemichannel activity in hippocampal astrocytes is an early event in AD, which is modulated by A2AR.

Alzheimer's disease phenotypes show different sleep architecture

INTRODUCTION

Sleep-wake disturbances are a prominent feature of Alzheimer's disease (AD). Atypical (non-amnestic) AD syndromes have different patterns of cortical vulnerability to AD. We hypothesized that atypical AD also shows differential vulnerability in subcortical nuclei that will manifest as different patterns of sleep dysfunction.

METHODS

Overnight electroencephalography monitoring was performed on 48 subjects, including 15 amnestic, 19 atypical AD, and 14 controls. AD was defined based on neuropathological or biomarker confirmation. We compared sleep architecture by visual scoring and spectral power analysis in each group.

RESULTS

Overall, AD cases showed increased sleep fragmentation and N1 sleep compared to controls. Compared to atypical AD groups, typical AD showed worse N3 sleep dysfunction and relatively preserved rapid eye movement (REM) sleep.

DISCUSSION

Results suggest differing effects of amnestic and atypical AD variants on slow wave versus REM sleep, respectively, corroborating the hypothesis of differential selective vulnerability patterns of the subcortical nuclei within variants. Optimal symptomatic treatment for sleep dysfunction in clinical phenotypes may differ.

HIGHLIGHTS

Alzheimer's disease (AD) variants show distinct patterns of sleep impairment. Amnestic/typical AD has worse N3 slow wave sleep (SWS) impairment compared to atypical AD. Atypical AD shows more rapid eye movement deficits than typical AD. Selective vulnerability patterns in subcortical areas may underlie sleep differences. Relatively preserved SWS may explain better memory scores in atypical versus typical AD.

Adenosine A2A Receptor Up-Regulation Pre-Dates Deficits of Synaptic Plasticity and of Memory in Mice Exposed to Aβ1-42 to Model Early Alzheimer's Disease

The intracerebroventricular (icv) injection of amyloid peptides (Aβ) models Alzheimer's disease (AD) in mice, as typified by the onset within 15 days of deficits of memory and of hippocampal long-term potentiation (LTP) that are prevented by the blockade of adenosine A2A receptors (A2AR). Since A2AR overfunction is sufficient to trigger memory deficits, we tested if A2AR were upregulated in hippocampal synapses before the onset of memory deficits to support the hypothesis that A2AR overfunction could be a trigger of AD. Six to eight days after Aβ-icv injection, mice displayed no alterations of hippocampal dependent memory; however, they presented an increased excitability of hippocampal synapses, a slight increase in LTP magnitude in Schaffer fiber-CA1 pyramid synapses and an increased density of A2AR in hippocampal synapses. A2AR blockade with SCH58261 (50 nM) normalized excitability and LTP in hippocampal slices from mice sacrificed 7-8 days after Aβ-icv injection. Fifteen days after Aβ-icv injection, mice displayed evident deficits of hippocampal-dependent memory deterioration, with reduced hippocampal CA1 LTP but no hyperexcitability and a sustained increase in synaptic A2AR, which blockade restored LTP magnitude. This shows that the upregulation of synaptic A2AR precedes the onset of deterioration of memory and of hippocampal synaptic plasticity, supporting the hypothesis that the overfunction of synaptic A2AR could be a trigger of memory deterioration in AD.

Network Hyperexcitability in Early Alzheimer's Disease: Is Functional Connectivity a Potential Biomarker?

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.

Resting-state oscillations reveal disturbed excitation-inhibition ratio in Alzheimer's disease patients

An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and non-invasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.

Regional Precuneus Cortical Hyperexcitability in Alzheimer's Disease Patients

OBJECTIVE

Neuronal excitation/inhibition (E/I) imbalance is a potential cause of neuronal network malfunctioning in Alzheimer's disease (AD), contributing to cognitive dysfunction. Here, we used a novel approach combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe cortical excitability in different brain areas known to be directly involved in AD pathology.

METHODS

We performed TMS-EEG recordings targeting the left dorsolateral prefrontal cortex (l-DLPFC), the left posterior parietal cortex (l-PPC), and the precuneus (PC) in a large sample of patients with mild-to-moderate AD (n = 65) that were compared with a group of age-matched healthy controls (n = 21).

RESULTS

We found that patients with AD are characterized by a regional cortical hyperexcitability in the PC and, to some extent, in the frontal lobe, as measured by TMS-evoked potentials. Notably, cortical excitability assessed over the l-PPC was comparable between the 2 groups. Furthermore, we found that the individual level of PC excitability was associated with the level of cognitive impairment, as measured with Mini-Mental State Examination, and with corticospinal fluid levels of Aβ₄₂ .

INTERPRETATION

Our data provide novel evidence that precuneus cortical hyperexcitability is a key feature of synaptic dysfunction in patients with AD. The current results point to the combined approach of TMS and EEG as a novel promising technique to measure hyperexcitability in patients with AD. This index could represent a useful biomarker to stage disease severity and evaluate response to novel therapies. ANN NEUROL 2023;93:371-383.

Etiology and Clinical Significance of Network Hyperexcitability in Alzheimer's Disease: Unanswered Questions and Next Steps

Cortical network hyperexcitability related to synaptic dysfunction in Alzheimer's disease (AD) is a potential target for therapeutic intervention. In recent years, there has been increased interest in the prevalence of silent seizures and interictal epileptiform discharges (IEDs, or seizure tendency), with both entities collectively termed "subclinical epileptiform activity" (SEA), on neurophysiologic studies in AD patients. SEA has been demonstrated to be common in AD, with prevalence estimates ranging between 22-54%. Converging lines of basic and clinical evidence imply that modifying a hyperexcitable state results in an improvement in cognition. In particular, though these results require further confirmation, post-hoc findings from a recent phase II clinical trial suggest a therapeutic effect with levetiracetam administration in patients with AD and IEDs. Here, we review key unanswered questions as well as potential clinical trial avenues. Specifically, we discuss postulated mechanisms and treatment of hyperexcitability in patients with AD, which are of interest in designing future disease-modifying therapies. Criteria to prompt screening and optimal screening methodology for hyperexcitability have yet to be defined, as does timing and personalization of therapeutic intervention.

The fate of interneurons, GABAA receptor sub-types and perineuronal nets in Alzheimer's disease

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 GABA_A inhibitory system, encompassing subclasses of interneurons and GABA_A 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 GABA_A 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.

Association between Subclinical Epileptiform Discharge and the Severity of Cognitive Decline in Alzheimer’s Disease: A Longitudinal Cohort Study

Background: Alzheimer’s disease (AD) is the most common type of dementia. Aging is a risk factor for both AD and seizures. Subclinical epileptiform discharge (SED) has no evident clinical manifestation in patients with AD. Therefore, SED is liable to be overlooked in these patients since electroencephalography is not routinely performed in clinical settings. Previous studies about the association between SED and AD have yielded inconsistent results. Objective: The current study aimed to evaluate the prevalence of SED and its effect on AD severity and clinical outcomes. Methods: Patients with AD from Kaohsiung Municipal Ta-tung Hospital were included in this study. International 10–20 system scalp electroencephalography for 13 minutes was performed to detect SED. Clinical outcomes of patients with and without SED were assessed by neuropsychological tests [Cognitive Abilities Screening Instrument (CASI), Mini-Mental State Examination (MMSE), and Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB)]. Results: 288 patients (mean age 80.5 years, 60.4% female) were enrolled in this study. Fifty-seven (19.8%) out of 288 patients with AD had SED. The prevalence of SED increased with the severity of cognitive impairment. Compared with patients without SED, those with SED showed significantly greater decline in CASI (–9.32 versus –3.52 points, p = 0.0001) and MMSE (–2.52 versus –1.12 points, p = 0.0042) scores in one year. Conclusion: SED may play a significant role in AD progression and is a potential therapeutic target.

Normalized Theta but Increased Gamma Activity after Acetylcholinesterase Inhibitor Treatment in Alzheimer's Disease: Preliminary qEEG Study

Acetylcholinesterase inhibitors (AChE-I) are the core treatment of mild to severe Alzheimer's disease (AD). However, the efficacy of AChE-I treatment on electroencephalography (EEG) and cognition remains unclear. We aimed to investigate the EEG power and coherence changes, in addition to neuropsychological performance, following a one-year treatment. Nine de-novo AD patients and demographically-matched healthy controls (HC) were included. After baseline assessments, all AD participants started cholinergic therapy. We found that baseline and follow-up gamma power analyzes were similar between groups. Yet, within the AD group after AChE-I intake, individuals with AD displayed higher gamma power compared to their baselines (P < .039). Also, baseline gamma coherence analysis showed lower values in the AD than in HC (P < .048), while these differences disappeared with increased gamma values of AD patients at the follow-up. Within the AD group after AChE-I intake, individuals with AD displayed higher theta and alpha coherence compared to their baselines (all, P < .039). These increased results within the AD group may result from a subclinical epileptiform activity. Even though AChE-I is associated with lower mortality, our results showed a significant effect on EEG power yet can increase the subclinical epileptiform activity. It is essential to be conscious of the seizure risk that treatment may cause.

The clinical correlation between Alzheimer's disease and epilepsy

Alzheimer's disease and epilepsy are common nervous system diseases in older adults, and their incidence rates tend to increase with age. Patients with mild cognitive impairment and Alzheimer's disease are more prone to have seizures. In patients older than 65 years, neurodegenerative conditions accounted for ~10% of all late-onset epilepsy cases, most of which are Alzheimer's disease. Epilepsy and seizure can occur in the early and late stages of Alzheimer's disease, leading to functional deterioration and behavioral alterations. Seizures promote amyloid-β and tau deposits, leading to neurodegenerative processes. Thus, there is a bi-directional association between Alzheimer's disease and epilepsy. Epilepsy is a risk factor for Alzheimer's disease and, in turn, Alzheimer's disease is an independent risk factor for developing epilepsy in old age. Many studies have evaluated the shared pathogenesis and clinical relevance of Alzheimer's disease and epilepsy. In this review, we discuss the clinical associations between Alzheimer's disease and epilepsy, including their incidence, clinical features, and electroencephalogram abnormalities. Clinical studies of the two disorders in recent years are summarized, and new antiepileptic drugs used for treating Alzheimer's disease are reviewed.

The Significance of Subclinical Epileptiform Activity in Alzheimer's Disease: A Review

Hyperexcitability is a recently recognized contributor to the pathophysiology of Alzheimer's disease (AD). Subclinical epileptiform activity (SEA) is a neurophysiological sign of cortical hyperexcitability; however, the results of the studies in this field vary due to differences in the applied methodology. The aim of this review is to summarize the results of the related studies aiming to describe the characteristic features and significance of subclinical epileptiform discharges in the pathophysiologic process of AD from three different directions: (1) what SEA is; (2) why we should diagnose SEA, and (3) how we should diagnose SEA. We scrutinized both the completed and ongoing antiepileptic drug trials in AD where SEA served as a grouping variable or an outcome measure. SEA seems to appear predominantly in slow-wave sleep and in the left temporal region and to compromise cognitive functions. We clarify using supportive literature the high sensitivity of overnight electroencephalography (EEG) in the detection of epileptiform discharges. Finally, we present the most important research questions around SEA and provide an overview of the possible solutions.