Antibody-mediated targeting of human microglial leukocyte Ig-like receptor B4 attenuates amyloid pathology in a mouse model.

Microglia help limit the progression of Alzheimer's disease (AD) by constraining amyloid-ß (Aß) pathology, effected through a balance of activating and inhibitory intracellular signals delivered by distinct cell surface receptors. Human leukocyte Ig-like receptor B4 (LILRB4) is an inhibitory receptor of the immunoglobulin (Ig) superfamily that is expressed on myeloid cells and recognizes apolipoprotein E (ApoE) among other ligands. Here, we find that LILRB4 is highly expressed in the microglia of patients with AD. Using mice that accumulate Aß and carry a transgene encompassing a portion of the LILR region that includes LILRB4, we corroborated abundant LILRB4 expression in microglia wrapping around Aß plaques. Systemic treatment of these mice with an anti-human LILRB4 monoclonal antibody (mAb) reduced Aß load, mitigated some Aß-related behavioral abnormalities, enhanced microglia activity, and attenuated expression of interferon-induced genes. In vitro binding experiments established that human LILRB4 binds both human and mouse ApoE and that anti-human LILRB4 mAb blocks such interaction. In silico modeling, biochemical, and mutagenesis analyses identified a loop between the two extracellular Ig domains of LILRB4 required for interaction with mouse ApoE and further indicated that anti-LILRB4 mAb may block LILRB4-mApoE by directly binding this loop. Thus, targeting LILRB4 may be a potential therapeutic avenue for AD.

Profiling of long non-coding RNAs in hippocampal-entorhinal system subfields: impact of RN7SL1 on neuroimmune response modulation in Alzheimer's disease.

Alzheimer's disease (AD) is recognized as the predominant cause of dementia, and neuroimmune processes play a pivotal role in its pathological progression. The involvement of long non-coding RNAs (lncRNAs) in AD has attracted widespread attention. Herein, transcriptomic analysis of 262 unique samples extracted from five hippocampal-entorhinal system subfields of individuals with AD pathology and without AD pathology revealed distinctive lncRNA expression profiles. Through differential expression and coexpression analyses, we identified 16 pivotal lncRNAs. Notably, RN7SL1 knockdown significantly modulated microglial responses upon oligomeric amyloid-ß stimulation, resulting in a considerable decrease in proinflammatory cytokine production and subsequent neuronal damage. These findings highlight RN7SL1 as an essential neuroimmune-related lncRNA that could serve as a prospective target for AD diagnosis and treatment.

The concept of resilience to Alzheimer's Disease: current definitions and cellular and molecular mechanisms.

Some individuals are able to maintain their cognitive abilities despite the presence of significant Alzheimer's Disease (AD) neuropathological changes. This discrepancy between cognition and pathology has been labeled as resilience and has evolved into a widely debated concept. External factors such as cognitive stimulation are associated with resilience to AD, but the exact cellular and molecular underpinnings are not completely understood. In this review, we discuss the current definitions used in the field, highlight the translational approaches used to investigate resilience to AD and summarize the underlying cellular and molecular substrates of resilience that have been derived from human and animal studies, which have received more and more attention in the last few years. From these studies the picture emerges that resilient individuals are different from AD patients in terms of specific pathological species and their cellular reaction to AD pathology, which possibly helps to maintain cognition up to a certain tipping point. Studying these rare resilient individuals can be of great importance as it could pave the way to novel therapeutic avenues for AD.

[Neuropathology of Disorders Leading to Dementia].

Dementia is characterized by acquired cognitive dysfunction caused by various neurological disorders. Many neurological conditions can cause dementia, including neurodegenerative diseases, vascular disorders, infections, inflammation, demyelination, intoxication, metabolic disorders, tumors, and head trauma. Despite recent developments in biomarkers and imaging techniques, neuropathological examination is necessary for the final diagnosis. Moreover, approximately 11% of the patients with dementia have dual or triple pathological conditions. The coexistence of neurological diseases makes it difficult for neurologists to diagnose patients accurately. Degenerative diseases are characterized by neuronal loss with gliosis in distinct parts of the brain, the presence of neuronal or glial inclusions, and abnormal protein accumulation. Senile plaques and neurofibrillary tangles are neuropathological hallmarks of Alzheimer's disease. These findings are characterized by the presence of amyloid ß protein (Aß) and phosphorylated tau protein, respectively. Although vascular dementia is common, it may be difficult to identify the relationship between vascular lesions and cognitive impairment. The incidence of sporadic Aß-type cerebral amyloid angiopathy (CAA) tends to increase with age and causes dementia due to vascular dysfunction and leukoencephalopathy. Furthermore, patients with CAA can develop inflammation. Clinical neurologists should possess a neuropathological perspective for the appropriate diagnosis and management of patients with dementia.

Regional MRI volumetry using NeuroQuant versus visual rating scales in patients with cognitive impairment and dementia.

BACKGROUND AND PURPOSE: The aims were to compare the novel regional brain volumetric measures derived by the automatic software NeuroQuant (NQ) with clinically used visual rating scales of medial temporal lobe atrophy (MTA), global cortical atrophy-frontal (GCA-f), and posterior atrophy (PA) brain regions, assessing their diagnostic validity, and to explore if combining automatic and visual methods would increase diagnostic prediction accuracy. METHODS: Brain magnetic resonance imaging (MRI) examinations from 86 patients with subjective and mild cognitive impairment (i.e., non-dementia, n = 41) and dementia (n = 45) from the Memory Clinic at Oslo University Hospital were assessed using NQ volumetry and with visual rating scales. Correlations, receiver operating characteristic analyses calculating area under the curves (AUCs) for diagnostic accuracy, and logistic regression analyses were performed. RESULTS: The correlations between NQ volumetrics and visual ratings of corresponding regions were generally high between NQ hippocampi/temporal volumes and MTA (r = -0.72/-0.65) and between NQ frontal volume and GCA-f (r = -0.62) but lower between NQ parietal/occipital volumes and PA (r = -0.49/-0.37). AUCs of each region, separating non-dementia from dementia, were generally comparable between the two methods, except that NQ hippocampi volume did substantially better than visual MTA (AUC = 0.80 vs. 0.69). Combining both MRI methods increased only the explained variance of the diagnostic prediction substantially regarding the posterior brain region. CONCLUSIONS: The findings of this study encourage the use of regional automatic volumetry in locations lacking neuroradiologists with experience in the rating of atrophy typical of neurodegenerative diseases, and in primary care settings.

Prominent tauopathy and intracellular ß-amyloid accumulation triggered by genetic deletion of cathepsin D: implications for Alzheimer disease pathogenesis.

BACKGROUND: Cathepsin D (CatD) is a lysosomal protease that degrades both the amyloid-ß protein (Aß) and the microtubule-associated protein, tau, which accumulate pathognomonically in Alzheimer disease (AD), but few studies have examined the role of CatD in the development of Aß pathology and tauopathy in vivo. METHODS: CatD knockout (KO) mice were crossed to human amyloid precursor protein (hAPP) transgenic mice, and amyloid burden was quantified by ELISA and immunohistochemistry (IHC). Tauopathy in CatD-KO mice, as initially suggested by Gallyas silver staining, was further characterized by extensive IHC and biochemical analyses. Controls included human tau transgenic mice (JNPL3) and another mouse model of a disease (Krabbe A) characterized by pronounced lysosomal dysfunction. Additional experiments examined the effects of CatD inhibition on tau catabolism in vitro and in cultured neuroblastoma cells with inducible expression of human tau. RESULTS: Deletion of CatD in hAPP transgenic mice triggers large increases in cerebral Aß, manifesting as intense, exclusively intracellular aggregates; extracellular Aß deposition, by contrast, is neither triggered by CatD deletion, nor affected in older, haploinsufficient mice. Unexpectedly, CatD-KO mice were found to develop prominent tauopathy by just ∼ 3 weeks of age, accumulating sarkosyl-insoluble, hyperphosphorylated tau exceeding the pathology present in aged JNPL3 mice. CatD-KO mice exhibit pronounced perinuclear Gallyas silver staining reminiscent of mature neurofibrillary tangles in human AD, together with widespread phospho-tau immunoreactivity. Striking increases in sarkosyl-insoluble phospho-tau (∼ 1250%) are present in CatD-KO mice but notably absent from Krabbe A mice collected at an identical antemortem interval. In vitro and in cultured cells, we show that tau catabolism is slowed by blockade of CatD proteolytic activity, including via competitive inhibition by Aß42. CONCLUSIONS: Our findings support a major role for CatD in the proteostasis of both Aß and tau in vivo. To our knowledge, the CatD-KO mouse line is the only model to develop detectable Aß accumulation and profound tauopathy in the absence of overexpression of hAPP or human tau with disease-associated mutations. Given that tauopathy emerges from disruption of CatD, which can itself be potently inhibited by Aß42, our findings suggest that impaired CatD activity may represent a key mechanism linking amyloid accumulation and tauopathy in AD.

Combining Blood-Based Biomarkers and Structural MRI Measurements to Distinguish Persons with and without Significant Amyloid Plaques.

Background: Amyloid-ß (Aß) plaques play a pivotal role in Alzheimer's disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing Aß plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of Aß plaques. Objective: To develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma Aß42/40 ratio. Methods: We extracted hippocampal multivariate morphometry statistics from MR images and together with plasma Aß42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimer's Institute (BAI), including prediction accuracy, precision, recall rate, F1 score, and AUC score. Results: Results from ADNI (mean age 72.6, Aß+ rate 49.5%) and BAI (mean age 66.2, Aß+ rate 36.9%) datasets revealed the integrated multimodal (IMM) model's superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma Aß42/40 (0.73 and 0.81) predictors. CONCLUSIONS: Our IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimer's disease diagnostics, leveraging diverse pathologic features related to Aß plaques and structural MRI.

Frontal Cortex Lipid Alterations During the Onset of Alzheimer's Disease.

Background: Although sporadic Alzheimer's disease (AD) is a neurodegenerative disorder of unknown etiology, familial AD is associated with specific gene mutations. A commonality between these forms of AD is that both display multiple pathogenic events including cholinergic and lipid dysregulation. Objective: We aimed to identify the relevant lipids and the activity of their related receptors in the frontal cortex and correlating them with cognition during the progression of AD. Methods: MALDI-mass spectrometry imaging (MSI) and functional autoradiography was used to evaluate the distribution of phospholipids/sphingolipids and the activity of cannabinoid 1 (CB1), sphingosine 1-phosphate 1 (S1P1), and muscarinic M2/M4 receptors in the frontal cortex (FC) of people that come to autopsy with premortem clinical diagnosis of AD, mild cognitive impairment (MCI), and no cognitive impairment (NCI). Results: MALDI-MSI revealed an increase in myelin-related lipids, such as diacylglycerol (DG) 36:1, DG 38:5, and phosphatidic acid (PA) 40:6 in the white matter (WM) in MCI compared to NCI, and a downregulation of WM phosphatidylinositol (PI) 38:4 and PI 38:5 levels in AD compared to NCI. Elevated levels of phosphatidylcholine (PC) 32:1, PC 34:0, and sphingomyelin 38:1 were observed in discrete lipid accumulations in the FC supragranular layers during disease progression. Muscarinic M2/M4 receptor activation in layers V-VI decreased in AD compared to MCI. CB1 receptor activity was upregulated in layers V-VI, while S1P1 was downregulated within WM in AD relative to NCI. Conclusions: FC WM lipidomic alterations are associated with myelin dyshomeostasis in prodromal AD, suggesting WM lipid maintenance as a potential therapeutic target for dementia.

Recent Advances in Drug Delivery Systems Targeting Insulin Signalling for the Treatment of Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the accumulation of neurofibrillary tangles and amyloid-ß plaques. Recent research has unveiled the pivotal role of insulin signaling dysfunction in the pathogenesis of AD. Insulin, once thought to be unrelated to brain function, has emerged as a crucial factor in neuronal survival, synaptic plasticity, and cognitive processes. Insulin and the downstream insulin signaling molecules are found mainly in the hippocampus and cortex. Some molecules responsible for dysfunction in insulin signaling are GSK-3ß, Akt, PI3K, and IRS. Irregularities in insulin signaling or insulin resistance may arise from changes in the phosphorylation levels of key molecules, which can be influenced by both stimulation and inactivity. This, in turn, is believed to be a crucial factor contributing to the development of AD, which is characterized by oxidative stress, neuroinflammation, and other pathological hallmarks. Furthermore, this route is known to be indirectly influenced by Nrf2, NF-κB, and the caspases. This mini-review delves into the intricate relationship between insulin signaling and AD, exploring how disruptions in this pathway contribute to disease progression. Moreover, we examine recent advances in drug delivery systems designed to target insulin signaling for AD treatment. From oral insulin delivery to innovative nanoparticle approaches and intranasal administration, these strategies hold promise in mitigating the impact of insulin resistance on AD. This review consolidates current knowledge to shed light on the potential of these interventions as targeted therapeutic options for AD.

Landscape of brain myeloid cell transcriptome along the spatiotemporal progression of Alzheimer's disease reveals distinct sequential responses to Aß and tau.

Human microglia are critically involved in Alzheimer's disease (AD) progression, as shown by genetic and molecular studies. However, their role in tau pathology progression in human brain has not been well described. Here, we characterized 32 human donors along progression of AD pathology, both in time-from early to late pathology-and in space-from entorhinal cortex (EC), inferior temporal gyrus (ITG), prefrontal cortex (PFC) to visual cortex (V2 and V1)-with biochemistry, immunohistochemistry, and single nuclei-RNA-sequencing, profiling a total of 337,512 brain myeloid cells, including microglia. While the majority of microglia are similar across brain regions, we identified a specific subset unique to EC which may contribute to the early tau pathology present in this region. We calculated conversion of microglia subtypes to diseased states and compared conversion patterns to those from AD animal models. Targeting genes implicated in this conversion, or their upstream/downstream pathways, could halt gene programs initiated by early tau progression. We used expression patterns of early tau progression to identify genes whose expression is reversed along spreading of spatial tau pathology (EC > ITG > PFC > V2 > V1) and identified their potential involvement in microglia subtype conversion to a diseased state. This study provides a data resource that builds on our knowledge of myeloid cell contribution to AD by defining the heterogeneity of microglia and brain macrophages during both temporal and regional pathology aspects of AD progression at an unprecedented resolution.

White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition.

BACKGROUND: White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS: In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS: Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION: Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.

Amyloid-ß prediction machine learning model using source-based morphometry across neurocognitive disorders.

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aß) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aß-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aß-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.

Cerebrospinal fluid amyloid-ß and cerebral microbleed are associated with distinct neuropsychiatric sub-syndromes in cognitively impaired patients.

BACKGROUND: Neuropsychiatric symptoms (NPS) are prevalent in cognitively impaired individuals including Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI). Whereas several studies have reported the associations between NPS with AD pathologic biomarkers and cerebral small vessel disease (SVD), but it remains unknown whether AD pathology and SVD contribute to different sub-syndromes independently or aggravate same symptoms synergistically. METHOD: We included 445 cognitively impaired individuals (including 316 MCI and 129 AD) with neuropsychiatric, cerebrospinal fluid (CSF) biomarkers (Aß42, p-tau, and t-tau) and multi-model MRI data. Psychiatric symptoms were accessed by using the Neuropsychiatric Inventory (NPI). Visual assessment of SVD (white matter hyperintensity, microbleed, perivascular space, lacune) on MRI images was performed by experienced radiologist. Linear regression analyses were conducted to test the association between neuropsychiatric symptoms with AD pathology and CSVD burden after adjustment for age, sex, education, apolipoprotein E (APOE) ε4 carrier status, and clinical diagnosis. RESULTS: The NPI total scores were related to microbleed (estimate 2.424; 95% CI [0.749, 4.099]; P =0.005). Considering the sub-syndromes, the hyperactivity was associated with microbleed (estimate 0.925; 95% CI [0.115, 1.735]; P =0.025), whereas the affective symptoms were correlated to CSF level of Aß42 (estimate -0.006; 95% CI [-0.011, -0.002]; P =0.005). Furthermore, we found the apathy sub-syndrome was associated with CSF t-tau/Aß42 (estimate 0.636; 95% CI [0.078, 1.194]; P =0.041) and microbleed (estimate 0.693; 95% CI [0.046, 1.340]; P =0.036). In addition, we found a significant interactive effect between CSF t-tau/Aß42 and microbleed (estimate 0.993; 95% CI [0.360, 1.626]; P =0.019) on severity of apathy sub-syndrome. CONCLUSION: Our study showed that CSF Aß42 was associated with affective symptoms, but microbleed was correlated with hyperactivity and apathy, suggesting the effect of AD pathology and SVD on different neuropsychiatric sub-syndromes.

Microdose lithium improves behavioral deficits and modulates molecular mechanisms of memory formation in female SAMP-8, a mouse model of accelerated aging.

Alzheimer's disease (AD) is the most common neuronal disorder that leads to the development of dementia. Until nowadays, some therapies may alleviate the symptoms, but there is no pharmacological treatment. Microdosing lithium has been used to modify the pathological characteristics of the disease, with effects in both experimental and clinical conditions. The present work aimed to analyze the effects of this treatment on spatial memory, anxiety, and molecular mechanisms related to long-term memory formation during the aging process of a mouse model of accelerated aging (SAMP-8). Female SAMP-8 showed learning and memory impairments together with disruption of memory mechanisms, neuronal loss, and increased density of senile plaques compared to their natural control strain, the senescence-accelerated mouse resistant (SAMR-1). Chronic treatment with lithium promoted memory maintenance, reduction in anxiety, and maintenance of proteins related to memory formation and neuronal density. The density of senile plaques was also reduced. An increase in the density of gamma-aminobutyric acid A (GABAA) and α7 nicotinic cholinergic receptors was also observed and related to neuroprotection and anxiety reduction. In addition, this microdose of lithium inhibited the activation of glycogen synthase kinase-3beta (GSK-3ß), the classical mechanism of lithium cell effects, which could contribute to the preservation of the memory mechanism and reduction in senile plaque formation. This work shows that lithium effects in neuroprotection along the aging process are not related to a unique cellular mechanism but produce multiple effects that slowly protect the brain along the aging process.

Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts.

Amyloid-beta (Aß) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aß oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aß oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

Shaping the future of preclinical development of successful disease-modifying drugs against Alzheimer's disease: a systematic review of tau propagation models.

The transcellular propagation of the aberrantly modified protein tau along the functional brain network is a key hallmark of Alzheimer's disease and related tauopathies. Inoculation-based tau propagation models can recapitulate the stereotypical spread of tau and reproduce various types of tau inclusions linked to specific tauopathy, albeit with varying degrees of fidelity. With this systematic review, we underscore the significance of judicious selection and meticulous functional, biochemical, and biophysical characterization of various tau inocula. Furthermore, we highlight the necessity of choosing suitable animal models and inoculation sites, along with the critical need for validation of fibrillary pathology using confirmatory staining, to accurately recapitulate disease-specific inclusions. As a practical guide, we put forth a framework for establishing a benchmark of inoculation-based tau propagation models that holds promise for use in preclinical testing of disease-modifying drugs.

Glymphatic inhibition exacerbates tau propagation in an Alzheimer's disease model.

BACKGROUND: The aggregation and spread of misfolded amyloid structured proteins, such as tau and α-synuclein, are key pathological features associated with neurodegenerative disorders, including Alzheimer's and Parkinson's disease. These proteins possess a prion-like property, enabling their transmission from cell to cell leading to propagation throughout the central and peripheral nervous systems. While the mechanisms underlying their intracellular spread are still being elucidated, targeting the extracellular space has emerged as a potential therapeutic approach. The glymphatic system, a brain-wide pathway responsible for clearing extracellular metabolic waste from the central nervous system, has gained attention as a promising target for removing these toxic proteins. METHODS: In this study, we investigated the impact of long-term modulation of glymphatic function on tau aggregation and spread by chronically treating a mouse model of tau propagation with a pharmacological inhibitor of AQP4, TGN-020. Thy1-hTau.P301S mice were intracerebrally inoculated with tau into the hippocampus and overlying cortex, and subsequently treated with TGN-020 (3 doses/week, 50 mg/kg TGN-020, i.p.) for 10-weeks. During this time, animal memory was studied using cognitive behavioural tasks, and structural MR images were acquired of the brain in vivo prior to brain extraction for immunohistochemical characterisation. RESULTS: Our findings demonstrate increased tau aggregation in the brain and transhemispheric propagation in the hippocampus following the inhibition of glymphatic clearance. Moreover, disruption of the glymphatic system aggravated recognition memory in tau inoculated mice and exacerbated regional changes in brain volume detected in the model. When initiation of drug treatment was delayed for several weeks post-inoculation, the alterations were attenuated. CONCLUSIONS: These results indicate that by modulating AQP4 function and, consequently, glymphatic clearance, it is possible to modify the propagation and pathological impact of tau in the brain, particularly during the initial stages of the disease. These findings highlight the critical role of the glymphatic system in preserving healthy brain homeostasis and offer valuable insights into the therapeutic implications of targeting this system for managing neurodegenerative diseases characterized by protein aggregation and spread.

Disease and brain region specific immune response profiles in neurodegenerative diseases with pure and mixed protein pathologies.

The disease-specific accumulation of pathological proteins has long been the major focus of research in neurodegenerative diseases (ND), including Alzheimer's disease (AD) and related dementias (RD), but the recent identification of a multitude of genetic risk factors for ND in immune-associated genes highlights the importance of immune processes in disease pathogenesis and progression. Studies in animal models have characterized the local immune response to disease-specific proteins in AD and ADRD, but due to the complexity of disease processes and the co-existence of multiple protein pathologies in human donor brains, the precise role of immune processes in ND is far from understood. To better characterize the interplay between different extracellular and intracellular protein pathologies and the brain's intrinsic immune system in ND, we set out to comprehensively profile the local immune response in postmortem brain samples of individuals with "pure" beta-Amyloid and tau pathology (AD), "pure" α-Synuclein pathology in Lewy body diseases (LBD), as well as cases with Alzheimer's disease neuropathological changes (ADNC) and Lewy body pathology (MIX). Combining immunohistochemical profiling of microglia and digital image analysis, along with deep immunophenotyping using gene expression profiling on the NanoString nCounter® platform and digital spatial profiling on the NanoString GeoMx® platform we identified a robust immune activation signature in AD brain samples. This signature is maintained in persons with mixed pathologies, irrespective of co-existence of AD pathology and Lewy body (LB) pathology, while LBD brain samples with "pure" LB pathology exhibit an attenuated and distinct immune signature. Our studies highlight disease- and brain region-specific immune response profiles to intracellular and extracellular protein pathologies and further underscore the complexity of neuroimmune interactions in ND.

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.

Generating PET scan patterns in Alzheimer's by a mathematical model.

Alzheimer disease (AD) is the most common form of dementia. The cause of the disease is unknown, and it has no cure. Symptoms include cognitive decline, memory loss, and impairment of daily functioning. The pathological hallmarks of the disease are aggregation of plaques of amyloid-ß (Aß) and neurofibrillary tangles of tau proteins (τ), which can be detected in PET scans of the brain. The disease can remain asymptomatic for decades, while the densities of Aß and τ continue to grow. Inflammation is considered an early event that drives the disease. In this paper, we develop a mathematical model that can produce simulated patterns of (Aß,τ) seen in PET scans of AD patients. The model is based on the assumption that early inflammations, R and [Formula: see text], drive the growth of Aß and τ, respectively. Recently approved drugs can slow the progression of AD in patients, provided treatment begins early, before significant damage to the brain has occurred. In line with current longitudinal studies, we used the model to demonstrate how to assess the efficacy of such drugs when given years before the disease becomes symptomatic.