qEEG Analysis in the Diagnosis of Alzheimers Disease; a Comparison of Functional Connectivity and Spectral Analysis

Alzheimers disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients brains are in a phase-locked state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimers detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.

Type I Interferon Signaling Drives Microglial Dysfunction and Senescence in Human iPSC Models of Down Syndrome and Alzheimers Disease

Microglia are critical for brain development and play a central role in Alzheimers disease (AD) etiology. Down syndrome (DS), also known as trisomy 21, is the most common genetic origin of intellectual disability and the most common risk factor for AD. Surprisingly, little information is available on the impact of trisomy of human chromosome 21 (Hsa21) on microglia in DS brain development and AD in DS (DSAD). Using our new induced pluripotent stem cell (iPSC)-based human microglia-containing cerebral organoid and chimeric mouse brain models, here we report that DS microglia exhibit enhanced synaptic pruning function during brain development. Consequently, electrophysiological recordings demonstrate that DS microglial mouse chimeras show impaired synaptic neurotransmission, as compared to control microglial chimeras. Upon being exposed to human brain tissue-derived soluble pathological tau, DS microglia display dystrophic phenotypes in chimeric mouse brains, recapitulating microglial responses seen in human AD and DSAD brain tissues. Further flow cytometry, single-cell RNA-sequencing, and immunohistological analyses of chimeric mouse brains demonstrate that DS microglia undergo cellular senescence and exhibit elevated type I interferon signaling after being challenged by pathological tau. Mechanistically, we find that shRNA-mediated knockdown of Hsa21encoded type I interferon receptor genes, IFNARs, rescues the defective DS microglial phenotypes both during brain development and in response to pathological tau. Our findings provide first in vivo evidence supporting a paradigm shifting theory that human microglia respond to pathological tau by exhibiting accelerated senescence and dystrophic phenotypes. Our results further suggest that targeting IFNARs may improve microglial functions during DS brain development and prevent human microglial senescence in DS individuals with AD.

Neurons burdened by DNA double strand breaks incite microglia activation through antiviral-like signaling in neurodegeneration.

DNA double strand breaks (DSBs) are linked to aging, neurodegeneration, and senescence. However, the role played by neurons burdened with DSBs in disease-associated neuroinflammation is not well understood. Here, we isolate neurons harboring DSBs from the CK-p25 mouse model of neurodegeneration through fluorescence-activated nuclei sorting (FANS), and characterize their transcriptomes using single-nucleus, bulk, and spatial sequencing techniques. We find that neurons harboring DSBs enter a late-stage DNA damage response marked by the activation of senescent and antiviral-like immune pathways. We identify the NFkB transcription factor as a master regulator of immune gene expression in DSB-bearing neurons, and find that the expression of cytokines like Cxcl10 and Ccl2 develop in DSB-bearing neurons before glial cell types. Alzheimers Disease pathology is significantly associated with immune activation in excitatory neurons, and direct purification of DSB-bearing neurons from Alzheimers Disease brain tissue further validates immune gene upregulation. Spatial transcriptomics reveal that regions of brain tissue dense with DSB-bearing neurons also harbor signatures of inflammatory microglia, which is ameliorated by NFkB knock down in neurons. Inhibition of NFkB or depletion of Ccl2 and Cxcl10 in DSB-bearing neurons also reduces microglial activation in organotypic brain slice culture. In conclusion, we find that in the context of age-associated neurodegenerative disease, DSBs activate immune pathways in neurons, which in turn adopt a senescence associated secretory phenotype to elicit microglia activation. These findings highlight a novel role for neurons in the mechanism of age-associated neuroinflammation.

Artificial intelligence for diagnosis and prognosis in neuroimaging for dementia; a systematic review

Introduction Recent developments in artificial intelligence (AI) and neuroimaging offer new opportunities for improving diagnosis and prognosis of dementia. To synthesise the available literature, we performed a systematic review. Methods We systematically reviewed primary research publications up to January 2021, using AI for neuroimaging to predict diagnosis and/or prognosis in cognitive neurodegenerative diseases. After initial screening, data from each study was extracted, including: demographic information, AI methods, neuroimaging features, and results. Results We found 2709 reports, with 252 eligible papers remaining following screening. Most studies relied on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset (n=178) with no other individual dataset used more than 5 times. Algorithmic classifiers, such as support vector machine (SVM), were the most commonly used AI method (47%) followed by discriminative (32%) and generative (11%) classifiers. Structural MRI was used in 71% of studies with a wide range of accuracies for the diagnosis of neurodegenerative diseases and predicting prognosis. Lower accuracy was found in studies using a multi-class classifier or an external cohort as the validation group. There was improvement in accuracy when neuroimaging modalities were combined, e.g. PET and structural MRI. Only 17 papers studied non-Alzheimers disease dementias. Conclusion The use of AI with neuroimaging for diagnosis and prognosis in dementia is a rapidly emerging field. We make a number of recommendations addressing the definition of key clinical questions, heterogeneity of AI methods, and the availability of appropriate and representative data. We anticipate that addressing these issues will enable the field to move towards meaningful clinical translation.

Deep learning-driven risk-based subtyping of cognitively impaired individuals

Quantifying heterogeneity in Alzheimers disease (AD) risk is critical for individualized care and management. Recent attempts to assess AD heterogeneity have used structural (magnetic resonance imaging (MRI)-based) or functional (Ab-42; or tau) imaging, which focused on generating quartets of atrophy patterns and protein spreading, respectively. Here we present a computational framework that facilitated the identification of subtypes based on their risk of progression to AD. We used cerebrospinal fluid (CSF) measures of Ab-42; from the Alzheimers Disease Neuroimaging Initiative (ADNI) (n=544, discovery cohort) as well as the National Alzheimer's Coordinating Center (NACC) (n=508, validation cohort), and risk-stratified individuals with mild cognitive impairment (MCI) into quartiles (high-risk (H), intermediate-high risk (IH), intermediate-low risk (IL), and low-risk (L)). Patients were divided into subgroups utilizing patterns of brain atrophy found in each of these risk-stratified quartiles. We found H subjects to have a greater risk of AD progression compared to the other subtypes at 2- and 4-years in both the discovery and validation cohorts (ADNI: H subtype versus all others, p < 0.05 at 2 and 4 years; NACC: H vs. IL and LR at 2 years, p < 0.05, and a trend toward higher risk vs. IH, and p < 0.05 vs. IH, and L risk groups at 48 months with a trend toward lower survival vs. IL). Using MRI-based neural models that fused various deep neural networks with survival analysis, we then predicted MCI to AD conversion. We used these models to identify subtype-specific regions that demonstrate the largest levels of atrophy-related importance, which had minimal overlap (Average pairwise Jaccard Similarity in regions between the top 5 subtypes, 0.25+/-0.05 (+/- std)). Neuropathologic changes characteristic of AD were present across all subtypes in comparable proportions (Chi-square test, p>0.05 for differences in ADNC, n=31). Our risk-based approach to subtyping individuals provides an objective means to intervene and tailor care management strategies at early stages of cognitive decline.

Emerging evolution trends of application of natural products in Alzheimer’s disease

The main objective of this review was to explore the research foci and emerging trends of application of natural products in AD from 1990 to 2019 and evaluated publications qualitatively and quantitatively. CiteSpace V. 4.0 was used to identify top authors, journals, institutions, countries, keywords, co-cited articles, and trends and obtain the visual knowledge maps. Results revealed that the USA, People’s Republic of China and India were the major research countries in this field, while the Western Europe and North America were the areas with frequent international cooperation. Moreover, there was a close collaboration between universities and research institutes. The J Alzheimers Dis was the most productive journal. Alzheimers disease, natural product, brain, central nervous system, disease, and oxidative stress are some of the high centrality and high frequency keywords in the co-occurrence analysis; Indicating Alzheimers disease and its pathogenesis and natural product remain the hotspots in the field. This paper provides an insight into the application of natural products in AD, and provides useful information for AD researchers to find potential collaborators and cooperative institutions.

Reducing voltage-dependent potassium channel Kv3.4 levels ameliorates synapse loss in a mouse model of Alzheimers disease

Synapse loss is associated with cognitive decline in Alzheimers disease (AD) and owing to their plastic nature, synapses are an ideal target for therapeutic intervention. Oligomeric amyloid beta (Ab) around amyloid plaques is known to contribute to synapse loss in mouse models and is associated with synapse loss in human AD brain tissue, but the mechanisms leading from Ab; to synapse loss remain unclear. Recent data suggest that the fast-activating and -inactivating voltage-gated potassium channel subtype 3.4 (Kv3.4) may play a role in Ab-mediated neurotoxicity. Here, we tested whether this channel could also be involved in Ab synaptotoxicity. Using adeno-associated virus and CRISPR (clustered regularly interspaced short palindromic repeats) technology, we reduced Kv3.4 expression in neurons of the somatosensory cortex of APP/PS1 mice. These mice express human familial AD associated mutations in amyloid precursor protein and presenilin 1 and develop amyloid plaques and plaque-associated synapse loss similar to that observed in AD brain. We observe that reducing Kv3.4 levels ameliorates dendritic spine loss and changes spine morphology compared to control virus. In support of translational relevance, Kv3.4 protein was observed in human AD and control brain and is associated with synapses in human iPSC-derived cortical neurons. Interestingly, we observe a decrease in Kv3.4 expression in iPSC derived cortical neurons when they are challenged with human Alzheimers disease derived brain homogenate. These results suggest that approaches to reduce Kv3.4 expression and/or function could be protective against Ab-induced synaptic alterations.

Imaging synaptic microstructure and synaptic loss in vivo in early Alzheimers Disease

Background Synaptic loss and neurite dystrophy are early events in Alzheimers Disease (AD). We aimed to characterise early synaptic microstructural changes in vivo. Methods MRI neurite orientation dispersion and density imaging (NODDI) and diffusion tensor imaging (DTI) were used to image cortical microstructure in both sporadic, late onset, amyloid PET positive AD patients and healthy controls (total n = 28). We derived NODDI measures of grey matter extracellular free water (FISO), neurite density (NDI) and orientation dispersion (ODI), which provides an index of neurite branching and orientation, as well as more conventional DTI measures of fractional anisotropy (FA), mean/axial/radial diffusivity (MD, AD, RD, respectively). We also performed [11C]UCB-J PET, which provides a specific measure of the density of pre-synaptic vesicular protein SV2A. Both sets of measures were compared to regional brain volumes. Results The AD patients showed expected relative decreases in regional brain volumes (range, -6 to -23%) and regional [11C]UCB-J densities (range, -2 to -25%). Differences between AD and controls were greatest in the hippocampus. NODDI microstructural measures showed greater FISO (range, +26 to +44%) in AD, with little difference in NDI (range, -1 to +7%) and mild focal changes in ODI (range, -4 to +3%). Regionally greater FISO and lower [11C]UCB-J binding were correlated across grey matter in patients (most strongly in the caudate, r2 = 0.37, p = 0.001). FISO and DTI RD were strongly positively associated, particularly in the hippocampus (r2 = 0.98, p < 7.4 x 10-9). After 12-18 months we found a 5% increase in FISO in the temporal lobe, but little change across all ROIs in NDI and ODI. An exploratory analysis showed higher parietal lobe FISO was associated with lower language scores in people with AD. Conclusions We interpreted the increased extracellular free water as a possible consequence of glial activation. The dynamic range of disease-associated differences and the feasibility of measuring FISO on commercially available imaging systems makes it a potential surrogate for pathology related to synapse loss that could be used to support early-stage evaluations of novel therapeutics for AD.

Efficacy of Probucol on cognitive function in Alzheimers disease: Study protocol for a double-blind, placebo-controlled, randomised phase II trial (PIA Study)

Preclinical, clinical and epidemiological studies support the hypothesis that aberrant systemic metabolism of amyloid-beta (Aβ) in the peripheral circulation is causally related to the development of Alzheimers disease (AD). Specifically, recent studies suggest that increased plasma concentrations of lipoprotein-Aβ compromises the brain microvasculature, resulting in extravasation and retention of the lipoprotein-Aβ moiety. The latter results in an inflammatory response and neurodegeneration ensues. Probucol, a historic cholesterol-lowering drug, has been shown in murine models to suppress lipoprotein-Aβ secretion, concomitant with maintaining blood-brain-barrier function and suppressing neurovascular inflammation. Probucol has also been shown to protect cognitive function in dietary-induced amyloidogenic mice. This protocol details the Probucol in Alzheimers Study (PIA-study), a double-blind, randomised, placebo-controlled drug intervention trial investigating if Probucol attenuates cognitive decline in patients with mild-to-moderate AD. Objectives: The primary objective of the 104-week study is to assess whether Probucol supports cognitive function and delays brain atrophy in AD patients. A secondary objective is to determine whether Probucol treatment will reduce cerebral amyloid burden.

Astrocytic urea cycle detoxifies Aβ-derived ammonia while impairing memory in Alzheimers Disease

Alzheimers disease (AD) is one of the foremost neurodegenerative diseases, characterized by beta-amyloid (Aβ) plaques and significant progressive memory loss. In AD, astrocytes are known to take up and clear Aβ plaques. However, how Aβ induces pathogenesis and memory impairment in AD remains elusive. We report that normal astrocytes show non-cyclic urea metabolism, whereas Aβ-treated astrocytes show switched-on urea cycle with upregulated enzymes and accumulated entering-metabolite aspartate, starting-substrate ammonia, end-product urea, and side-product putrescine. Gene-silencing of astrocytic ornithine decarboxylase-1 (ODC1), facilitating ornithine-to-putrescine conversion, boosts urea cycle and eliminates aberrant putrescine and its toxic by-products ammonia, H2O2, and GABA to recover from reactive astrogliosis and memory impairment in AD model. Our findings implicate that astrocytic urea cycle exerts opposing roles of beneficial Aβ detoxification and detrimental memory impairment in AD. We propose ODC1-inhibition as a promising therapeutic strategy for AD to facilitate removal of toxic molecules and prevent memory loss.