Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

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.

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

Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.

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.

Mitochondrial fission is a critical modulator of mutant APP-induced neural toxicity.

Alterations in mitochondrial fission may contribute to the pathophysiology of several neurodegenerative diseases, including Alzheimer's disease (AD). However, we understand very little about the normal functions of fission or how fission disruption may interact with AD-associated proteins to modulate pathogenesis. Here we show that loss of the central mitochondrial fission protein dynamin-related protein 1 (Drp1) in CA1 and other forebrain neurons markedly worsens the learning and memory of mice expressing mutant human amyloid precursor protein (hAPP) in neurons. In cultured neurons, Drp1KO and hAPP converge to produce mitochondrial Ca2+ (mitoCa2+) overload, despite decreasing mitochondria-associated ER membranes (MAMs) and cytosolic Ca2+. This mitoCa2+ overload occurs independently of ATP levels. These findings reveal a potential mechanism by which mitochondrial fission protects against hAPP-driven pathology.

Developmental Pathogenicity of 4-Repeat Human Tau Is Lost with the P301L Mutation in Genetically Matched Tau-Transgenic Mice.

Tau is a microtubule-associated protein that becomes dysregulated in a group of neurodegenerative diseases called tauopathies. Differential tau isoforms, expression levels, promoters, and disruption of endogenous genes in transgenic mouse models of tauopathy make it difficult to draw definitive conclusions about the biological role of tau in these models. We addressed this shortcoming by characterizing the molecular and cognitive phenotypes associated with the pathogenic P301L tau mutation (rT2 mice) in relation to a genetically matched transgenic mouse overexpressing nonmutant (NM) 4-repeat (4R) human tau (rT1 mice). Both male and female mice were included in this study. Unexpectedly, we found that 4R NM human tau (hTau) exhibited abnormal dynamics in young mice that were lost with the P301L mutation, including elevated protein stability and hyperphosphorylation, which were associated with cognitive impairment in 5-month-old rT1 mice. Hyperphosphorylation of NM hTau was observed as early as 4 weeks of age, and transgene suppression for the first 4 or 12 weeks of life prevented abnormal molecular and cognitive phenotypes in rT1, demonstrating that NM hTau pathogenicity is specific to postnatal development. We also show that NM hTau exhibits stronger binding to microtubules than P301L hTau, and is associated with mitochondrial abnormalities. Overall, our genetically matched mice have revealed that 4R NM hTau overexpression is pathogenic in a manner distinct from classical aging-related tauopathy, underlining the importance of assaying the effects of transgenic disease-related proteins at appropriate stages in life.SIGNIFICANCE STATEMENT Due to differences in creation of transgenic lines, the pathological properties of the P301L mutation confers to the tau protein in vivo have remained elusive, perhaps contributing to the lack of disease-modifying therapies for tauopathies. In an attempt to characterize P301L-specific effects on tau biology and cognition in novel genetically matched transgenic mouse models, we surprisingly found that nonmutant human tau has development-specific pathogenic properties of its own. Our findings indicate that overexpression of 4-repeat human tau during postnatal development is associated with excessive microtubule binding, which may disrupt important cellular processes, such as mitochondrial dynamics, leading to elevated stability and hyperphosphorylation of tau, and eventual cognitive impairments.

Taking the sublexical route: brain dynamics of reading in the semantic variant of primary progressive aphasia.

Reading aloud requires mapping an orthographic form to a phonological one. The mapping process relies on sublexical statistical regularities (e.g. 'oo' to |uː|) or on learned lexical associations between a specific visual form and a series of sounds (e.g. yacht to/jɑt/). Computational, neuroimaging, and neuropsychological evidence suggest that sublexical, phonological and lexico-semantic processes rely on partially distinct neural substrates: a dorsal (occipito-parietal) and a ventral (occipito-temporal) route, respectively. Here, we investigated the spatiotemporal features of orthography-to-phonology mapping, capitalizing on the time resolution of magnetoencephalography and the unique clinical model offered by patients with semantic variant of primary progressive aphasia (svPPA). Behaviourally, patients with svPPA manifest marked lexico-semantic impairments including difficulties in reading words with exceptional orthographic to phonological correspondence (irregular words). Moreover, they present with focal neurodegeneration in the anterior temporal lobe, affecting primarily the ventral, occipito-temporal, lexical route. Therefore, this clinical population allows for testing of specific hypotheses on the neural implementation of the dual-route model for reading, such as whether damage to one route can be compensated by over-reliance on the other. To this end, we reconstructed and analysed time-resolved whole-brain activity in 12 svPPA patients and 12 healthy age-matched control subjects while reading irregular words (e.g. yacht) and pseudowords (e.g. pook). Consistent with previous findings that the dorsal route is involved in sublexical, phonological processes, in control participants we observed enhanced neural activity over dorsal occipito-parietal cortices for pseudowords, when compared to irregular words. This activation was manifested in the beta-band (12-30 Hz), ramping up slowly over 500 ms after stimulus onset and peaking at ∼800 ms, around response selection and production. Consistent with our prediction, svPPA patients did not exhibit this temporal pattern of neural activity observed in controls this contrast. Furthermore, a direct comparison of neural activity between patients and controls revealed a dorsal spatiotemporal cluster during irregular word reading. These findings suggest that the sublexical/phonological route is involved in processing both irregular and pseudowords in svPPA. Together these results provide further evidence supporting a dual-route model for reading aloud mediated by the interplay between lexico-semantic and sublexical/phonological neurocognitive systems. When the ventral route is damaged, as in the case of neurodegeneration affecting the anterior temporal lobe, partial compensation appears to be possible by over-recruitment of the slower, serial attention-dependent, dorsal one.

Reduced synchrony in alpha oscillations during life predicts post mortem neurofibrillary tangle density in early-onset and atypical Alzheimer's disease.

INTRODUCTION: Neurophysiological manifestations selectively associated with amyloid beta and tau depositions in Alzheimer's disease (AD) are useful network biomarkers to identify peptide specific pathological processes. The objective of this study was to validate the associations between reduced neuronal synchrony within alpha oscillations and neurofibrillary tangle (NFT) density in autopsy examination, in patients with AD. METHODS: In a well-characterized clinicopathological cohort of AD patients (n = 13), we quantified neuronal synchrony within alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillations, using magnetoencephalography during the disease course, within six selected neocortical and hippocampal regions, including angular gyrus, superior temporal gurus, middle frontal gyrus, primary motor cortex, CA1, and subiculum, and correlated these with regional NFT density quantified at histopathological examination. RESULTS: Abnormal synchrony in alpha, but not in delta-theta, significantly predicted the NFT density at post mortem neuropathological examination. DISCUSSION: Reduced alpha synchrony is a sensitive neurophysiological index associated with pathological tau, and a potential network biomarker for clinical trials, to gauge the extent of network dysfunction and the degree of rescue in treatments targeting tau pathways in AD.

Impaired Lung Function, Lung Disease, and Risk of Incident Dementia.

Rationale: Growing evidence suggests that compromised lung health may be linked to dementia and worsening cognitive ability. Objectives: To test the hypothesis that impaired lung function or lung disease in midlife is associated with greater risk of incident dementia and mild cognitive impairment (MCI) later in life. Methods: A total of 14,184 Atherosclerosis Risk in Communities study participants who underwent spirometry and were asked about lung health (1987-1989) were followed. Dementia and MCI were defined by hospitalization diagnosis codes (1987-2013) in the whole cohort and with adjudication among 42% who attended a comprehensive neurocognitive examination (2011-2013). Measurements and Main Results: In analysis using adjudicated outcomes, odds of dementia or MCI were higher among participants with restrictive (multivariable-adjusted odds ratio, 1.58; 95% confidence interval, 1.14-2.19) and obstructive lung disease (multivariable-adjusted odds ratio, 1.33; 95% confidence interval, 1.07-1.64), compared with those without disease or respiratory symptoms. Associations were similar in analyses restricted to nonsmokers, and present for both Alzheimer's disease-related dementia and cerebrovascular etiologies. Low FEV1% predicted and FVC% predicted were also associated with increased dementia risk. Conclusions: Midlife lung disease and reduced lung function were associated with modestly increased odds of dementia and MCI later in life. Magnitudes of association were more pronounced for restrictive impairment than for obstructive lung disease. These associations were present in smokers and nonsmokers. If the observed associations are causal, policy and public health efforts to reduce smoking and improve air quality may have the added benefit of preventing the development of dementia and MCI.

Distinct spatiotemporal patterns of neuronal functional connectivity in primary progressive aphasia variants.

Primary progressive aphasia is a syndrome characterized by progressive loss of language abilities with three main phenotypic clinical presentations, including logopenic, non-fluent/agrammatic, and semantic variants. Previous imaging studies have shown unique anatomic impacts within language networks in each variant. However, direct measures of spontaneous neuronal activity and functional integrity of these impacted neural networks in primary progressive aphasia are lacking. The aim of this study was to characterize the spatial and temporal patterns of resting state neuronal synchronizations in primary progressive aphasia syndromes. We hypothesized that resting state brain oscillations will show unique deficits within language network in each variant of primary progressive aphasia. We examined 39 patients with primary progressive aphasia including logopenic variant (n = 14, age = 61 ± 9 years), non-fluent/agrammatic variant (n = 12, age = 71 ± 8 years) and semantic variant (n = 13, age = 65 ± 7 years) using magnetoencephalographic imaging, compared to a control group that was matched in age and gender to each primary progressive aphasia subgroup (n = 20, age = 65 ± 5 years). Each patient underwent a complete clinical evaluation including a comprehensive battery of language tests. We examined the whole-brain resting state functional connectivity as measured by imaginary coherence in each patient group compared to the control cohort, in three frequency oscillation bands-delta-theta (2-8 Hz); alpha (8-12 Hz); beta (12-30 Hz). Each variant showed a distinct spatiotemporal pattern of altered functional connectivity compared to age-matched controls. Specifically, we found significant hyposynchrony of alpha and beta frequency within the left posterior temporal and occipital cortices in patients with the logopenic variant, within the left inferior frontal cortex in patients with the non-fluent/agrammatic variant, and within the left temporo-parietal junction in patients with the semantic variant. Patients with logopenic variant primary progressive aphasia also showed significant hypersynchrony of delta-theta frequency within bilateral medial frontal and posterior parietal cortices. Furthermore, region of interest-based analyses comparing the spatiotemporal patterns of variant-specific regions of interest identified in comparison to age-matched controls showed significant differences between primary progressive aphasia variants themselves. We also found distinct patterns of regional spectral power changes in each primary progressive aphasia variant, compared to age-matched controls. Our results demonstrate neurophysiological signatures of network-specific neuronal dysfunction in primary progressive aphasia variants. The unique spatiotemporal patterns of neuronal synchrony signify diverse neurophysiological disruptions and pathological underpinnings of the language network in each variant.

Clinicopathological correlations in behavioural variant frontotemporal dementia.

Accurately predicting the underlying neuropathological diagnosis in patients with behavioural variant frontotemporal dementia (bvFTD) poses a daunting challenge for clinicians but will be critical for the success of disease-modifying therapies. We sought to improve pathological prediction by exploring clinicopathological correlations in a large bvFTD cohort. Among 438 patients in whom bvFTD was either the top or an alternative possible clinical diagnosis, 117 had available autopsy data, including 98 with a primary pathological diagnosis of frontotemporal lobar degeneration (FTLD), 15 with Alzheimer's disease, and four with amyotrophic lateral sclerosis who lacked neurodegenerative disease-related pathology outside of the motor system. Patients with FTLD were distributed between FTLD-tau (34 patients: 10 corticobasal degeneration, nine progressive supranuclear palsy, eight Pick's disease, three frontotemporal dementia with parkinsonism associated with chromosome 17, three unclassifiable tauopathy, and one argyrophilic grain disease); FTLD-TDP (55 patients: nine type A including one with motor neuron disease, 27 type B including 21 with motor neuron disease, eight type C with right temporal lobe presentations, and 11 unclassifiable including eight with motor neuron disease), FTLD-FUS (eight patients), and one patient with FTLD-ubiquitin proteasome system positive inclusions (FTLD-UPS) that stained negatively for tau, TDP-43, and FUS. Alzheimer's disease was uncommon (6%) among patients whose only top diagnosis during follow-up was bvFTD. Seventy-nine per cent of FTLD-tau, 86% of FTLD-TDP, and 88% of FTLD-FUS met at least 'possible' bvFTD diagnostic criteria at first presentation. The frequency of the six core bvFTD diagnostic features was similar in FTLD-tau and FTLD-TDP, suggesting that these features alone cannot be used to separate patients by major molecular class. Voxel-based morphometry revealed that nearly all pathological subgroups and even individual patients share atrophy in anterior cingulate, frontoinsula, striatum, and amygdala, indicating that degeneration of these regions is intimately linked to the behavioural syndrome produced by these diverse aetiologies. In addition to these unifying features, symptom profiles also differed among pathological subtypes, suggesting distinct anatomical vulnerabilities and informing a clinician's prediction of pathological diagnosis. Data-driven classification into one of the 10 most common pathological diagnoses was most accurate (up to 60.2%) when using a combination of known predictive factors (genetic mutations, motor features, or striking atrophy patterns) and the results of a discriminant function analysis that incorporated clinical, neuroimaging, and neuropsychological data.

Incidence and impact of subclinical epileptiform activity in Alzheimer's disease.

OBJECTIVE: Seizures are more frequent in patients with Alzheimer's disease (AD) and can hasten cognitive decline. However, the incidence of subclinical epileptiform activity in AD and its consequences are unknown. Motivated by results from animal studies, we hypothesized higher than expected rates of subclinical epileptiform activity in AD with deleterious effects on cognition. METHODS: We prospectively enrolled 33 patients (mean age, 62 years) who met criteria for AD, but had no history of seizures, and 19 age-matched, cognitively normal controls. Subclinical epileptiform activity was assessed, blinded to diagnosis, by overnight long-term video-electroencephalography (EEG) and a 1-hour resting magnetoencephalography exam with simultaneous EEG. Patients also had comprehensive clinical and cognitive evaluations, assessed longitudinally over an average period of 3.3 years. RESULTS: Subclinical epileptiform activity was detected in 42.4% of AD patients and 10.5% of controls (p = 0.02). At the time of monitoring, AD patients with epileptiform activity did not differ clinically from those without such activity. However, patients with subclinical epileptiform activity showed faster declines in global cognition, determined by the Mini-Mental State Examination (3.9 points/year in patients with epileptiform activity vs 1.6 points/year in patients without; p = 0.006), and in executive function (p = 0.01). INTERPRETATION: Extended monitoring detects subclinical epileptiform activity in a substantial proportion of patients with AD. Patients with this indicator of network hyperexcitability are at risk for accelerated cognitive decline and might benefit from antiepileptic therapies. These data call for more sensitive and comprehensive neurophysiological assessments in AD patient evaluations and impending clinical trials. Ann Neurol 2016;80:858-870.

Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer's disease.

SEE SARAZIN ET AL DOI101093/BRAIN/AWW041 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: The advent of the positron emission tomography tracer (18)F-AV1451 provides the unique opportunity to visualize the regional distribution of tau pathology in the living human brain. In this study, we tested the hypothesis that tau pathology is closely linked to symptomatology and patterns of glucose hypometabolism in Alzheimer's disease, in contrast to the more diffuse distribution of amyloid-ß pathology. We included 20 patients meeting criteria for probable Alzheimer's disease dementia or mild cognitive impairment due to Alzheimer's disease, presenting with a variety of clinical phenotypes, and 15 amyloid-ß-negative cognitively normal individuals, who underwent (18)F-AV1451 (tau), (11)C-PiB (amyloid-ß) and (18)F-FDG (glucose metabolism) positron emission tomography, apolipoprotein E (APOE) genotyping and neuropsychological testing. Voxel-wise contrasts against controls (at P < 0.05 family-wise error corrected) showed that (18)F-AV1451 and (18)F-FDG patterns in patients with posterior cortical atrophy ('visual variant of Alzheimer's disease', n = 7) specifically targeted the clinically affected posterior brain regions, while (11)C-PiB bound diffusely throughout the neocortex. Patients with an amnestic-predominant presentation (n = 5) showed highest (18)F-AV1451 retention in medial temporal and lateral temporoparietal regions. Patients with logopenic variant primary progressive aphasia ('language variant of Alzheimer's disease', n = 5) demonstrated asymmetric left greater than right hemisphere (18)F-AV1451 uptake in three of five patients. Across 30 FreeSurfer-defined regions of interest in 16 Alzheimer's disease patients with all three positron emission tomography scans available, there was a strong negative association between (18)F-AV1451 and (18)F-FDG uptake (Pearson's r = -0.49 ± 0.07, P < 0.001) and less pronounced positive associations between (11)C-PiB and (18)F-FDG (Pearson's r = 0.16 ± 0.09, P < 0.001) and (18)F-AV1451 and (11)C-PiB (Pearson's r = 0.18 ± 0.09, P < 0.001). Voxel-wise linear regressions thresholded at P < 0.05 (uncorrected) showed that, across all patients, younger age was associated with greater (18)F-AV1451 uptake in wide regions of the neocortex, while older age was associated with increased (18)F-AV1451 in the medial temporal lobe. APOE ϵ4 carriers showed greater temporal and parietal (18)F-AV1451 uptake than non-carriers. Finally, worse performance on domain-specific neuropsychological tests was associated with greater (18)F-AV1451 uptake in key regions implicated in memory (medial temporal lobes), visuospatial function (occipital, right temporoparietal cortex) and language (left > right temporoparietal cortex). In conclusion, tau imaging-contrary to amyloid-ß imaging-shows a strong regional association with clinical and anatomical heterogeneity in Alzheimer's disease. Although preliminary, these results are consistent with and expand upon findings from post-mortem, animal and cerebrospinal fluid studies, and suggest that the pathological aggregation of tau is closely linked to patterns of neurodegeneration and clinical manifestations of Alzheimer's disease.

Brain rhythm attractor breakdown in Alzheimer's disease: Functional and pathologic implications.

This perspective binds emerging evidence on the bidirectional relationship between Alzheimer's disease (AD) and sleep disorders through a model of brain rhythm attractor breakdown. This approach explains behavioral-cognitive changes in AD across the sleep-wake cycle and supports a causal association between early brainstem tau pathology and subsequent cortical amyloid ß accumulation. Specifically, early tau dysregulation within brainstem-hypothalamic nuclei leads to breakdown of sleep-wake attractor networks, with patients displaying an attenuated range of behavioral and electrophysiological activity patterns, a "twilight zone" of constant activity between deep rest and full alertness. This constant cortical activity promotes activity-dependent amyloid ß accumulation in brain areas that modulate their activity across sleep-wake states, especially the medial prefrontal cortex. In addition, the accompanying breakdown of hippocampal-medial prefrontal cortex interplay across sleep stages could explain deficient memory consolidation through dysregulation of synaptic plasticity. Clinical implications include the potential therapeutic benefit of attractor consolidation (e.g., slow-wave sleep enhancers) in delaying AD progression.

Levetiracetam suppresses neuronal network dysfunction and reverses synaptic and cognitive deficits in an Alzheimer's disease model.

In light of the rising prevalence of Alzheimer's disease (AD), new strategies to prevent, halt, and reverse this condition are needed urgently. Perturbations of brain network activity are observed in AD patients and in conditions that increase the risk of developing AD, suggesting that aberrant network activity might contribute to AD-related cognitive decline. Human amyloid precursor protein (hAPP) transgenic mice simulate key aspects of AD, including pathologically elevated levels of amyloid-ß peptides in brain, aberrant neural network activity, remodeling of hippocampal circuits, synaptic deficits, and behavioral abnormalities. Whether these alterations are linked in a causal chain remains unknown. To explore whether hAPP/amyloid-ß-induced aberrant network activity contributes to synaptic and cognitive deficits, we treated hAPP mice with different antiepileptic drugs. Among the drugs tested, only levetiracetam (LEV) effectively reduced abnormal spike activity detected by electroencephalography. Chronic treatment with LEV also reversed hippocampal remodeling, behavioral abnormalities, synaptic dysfunction, and deficits in learning and memory in hAPP mice. Our findings support the hypothesis that aberrant network activity contributes causally to synaptic and cognitive deficits in hAPP mice. LEV might also help ameliorate related abnormalities in people who have or are at risk for AD.

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.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations.

BACKGROUND: Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS: We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS: Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOE and the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS: Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations.

BACKGROUND: Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS: We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS: Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOEand the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS: Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Multi-class Modeling Identifies Shared Genetic Risk for Late-onset Epilepsy and Alzheimer's Disease.

Background: Previous studies have established a strong link between late-onset epilepsy (LOE) and Alzheimer's disease (AD). However, their shared genetic risk beyond the APOE gene remains unclear. Our study sought to examine the shared genetic factors of AD and LOE, interpret the biological pathways involved, and evaluate how AD onset may be mediated by LOE and shared genetic risks. Methods: We defined phenotypes using phecodes mapped from diagnosis codes, with patients' records aged 60-90. A two-step Least Absolute Shrinkage and Selection Operator (LASSO) workflow was used to identify shared genetic variants based on prior AD GWAS integrated with functional genomic data. We calculated an AD-LOE shared risk score and used it as a proxy in a causal mediation analysis. We used electronic health records from an academic health center (UCLA Health) for discovery analyses and validated our findings in a multi-institutional EHR database (All of Us). Results: The two-step LASSO method identified 34 shared genetic loci between AD and LOE, including the APOE region. These loci were mapped to 65 genes, which showed enrichment in molecular functions and pathways such as tau protein binding and lipoprotein metabolism. Individuals with high predicted shared risk scores have a higher risk of developing AD, LOE, or both in their later life compared to those with low-risk scores. LOE partially mediates the effect of AD-LOE shared genetic risk on AD (15% proportion mediated on average). Validation results from All of Us were consistent with findings from the UCLA sample. Conclusions: We employed a machine learning approach to identify shared genetic risks of AD and LOE. In addition to providing substantial evidence for the significant contribution of the APOE-TOMM40-APOC1 gene cluster to shared risk, we uncovered novel genes that may contribute. Our study is one of the first to utilize All of Us genetic data to investigate AD, and provides valuable insights into the potential common and disease-specific mechanisms underlying AD and LOE, which could have profound implications for the future of disease prevention and the development of targeted treatment strategies to combat the co-occurrence of these two diseases.

Neurophysiological trajectories in Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-ß 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.