Probing molecular pathways: Illuminating the connection between COVID-19 and Alzheimer's disease through the endocannabinoid system dynamics.

Our study investigates the molecular link between COVID-19 and Alzheimer's disease (AD). We aim to elucidate the mechanisms by which COVID-19 may influence the onset or progression of AD. Using bioinformatic tools, we analyzed gene expression datasets from the Gene Expression Omnibus (GEO) database, including GSE147507, GSE12685, and GSE26927. Intersection analysis was utilized to identify common differentially expressed genes (CDEGs) and their shared biological pathways. Consensus clustering was conducted to group AD patients based on gene expression, followed by an analysis of the immune microenvironment and variations in shared pathway activities between clusters. Additionally, we identified transcription factor-binding sites shared by CDEGs and genes in the common pathway. The activity of the pathway and the expression levels of the CDEGs were validated using GSE164805 and GSE48350 datasets. Six CDEGs (MAL2, NECAB1, SH3GL2, EPB41L3, MEF2C, and NRGN) were identified, along with a downregulated pathway, the endocannabinoid (ECS) signaling pathway, common to both AD and COVID-19. These CDEGs showed a significant correlation with ECS activity (p < 0.05) and immune functions. The ECS pathway was enriched in healthy individuals' brains and downregulated in AD patients. Validation using GSE164805 and GSE48350 datasets confirmed the differential expression of these genes in COVID-19 and AD tissues. Our findings reveal a potential pathogenetic link between COVID-19 and AD, mediated by CDEGs and the ECS pathway. However, further research and multicenter evidence are needed to translate these findings into clinical applications.

Integrating Multi-omics Data for Alzheimer's Disease to Explore Its Biomarkers Via the Hypergraph-Regularized Joint Deep Semi-Non-Negative Matrix Factorization Algorithm.

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disorder. Its etiology may be associated with genetic, environmental, and lifestyle factors. With the advancement of technology, the integration of genomics, transcriptomics, and imaging data related to AD allows simultaneous exploration of molecular information at different levels and their interaction within the organism. This paper proposes a hypergraph-regularized joint deep semi-non-negative matrix factorization (HR-JDSNMF) algorithm to integrate positron emission tomography (PET), single-nucleotide polymorphism (SNP), and gene expression data for AD. The method employs matrix factorization techniques to nonlinearly decompose the original data at multiple layers, extracting deep features from different omics data, and utilizes hypergraph mining to uncover high-order correlations among the three types of data. Experimental results demonstrate that this approach outperforms several matrix factorization-based algorithms and effectively identifies multi-omics biomarkers for AD. Additionally, single-cell RNA sequencing (scRNA-seq) data for AD were collected, and genes within significant modules were used to categorize different types of cell clusters into high and low-risk cell groups. Finally, the study extensively explores the differences in differentiation and communication between these two cell types. The multi-omics biomarkers unearthed in this study can serve as valuable references for the clinical diagnosis and drug target discovery for AD. The realization of the algorithm in this paper code is available at https://github.com/ShubingKong/HR-JDSNMF .

Constitutive NOS Production Is Modulated by Alzheimer's Disease Pathology Depending on APOE Genotype.

Both the endothelial (eNOS) and the neuronal (nNOS) isoforms of constitutive Nitric Oxide Synthase have been implicated in vascular dysfunctions in Alzheimer's disease (AD). We aimed to explore the relationship between amyloid pathology and NO dynamics by comparing the cerebrospinal fluid (CSF) levels of nNOS and eNOS of 8 healthy controls (HC) and 27 patients with a clinical diagnosis of Alzheimer's disease and isolated CSF amyloid changes, stratified according to APOE ε genotype (APOE ε3 = 13, APOE ε4 = 14). Moreover, we explored the associations between NOS isoforms, CSF AD biomarkers, age, sex, cognitive decline, and blood-brain barrier permeability. In our cohort, both eNOS and nNOS levels were increased in APOE ε3 with respect to HC and APOE ε4. CSF eNOS inversely correlated with CSF Amyloid-ß42 selectively in carriers of APOE ε3; CSF nNOS was negatively associated with age and CSF p-tau only in the APOE ε4 subgroup. Increased eNOS could represent compensative vasodilation to face progressive Aß-induced vasoconstriction in APOE ε3, while nNOS could represent the activation of NO-mediated plasticity strategies in the same group. Our results confirm previous findings that the APOE genotype is linked with different vascular responses to AD pathology.

Vascular Heparan Sulfate and Amyloid-ß in Alzheimer's Disease Patients.

Alzheimer's disease (AD) is a debilitating neurodegenerative disease characterized by the accumulation of extracellular amyloid-ß peptides (Aß) within the cerebral parenchyma and vasculature, which is known as cerebral amyloid angiopathy (CAA). This study utilized confocal imaging to investigate heparan sulfate (HS) expression within the cerebrovasculature and its associations with Aß, gender, and ApoE4 genotype in AD. Our investigation revealed elevated levels of HS in the cerebrovasculature of AD patients with severe CAA. Additionally, these patients exhibited higher HS colocalization with Aß in the cerebrovasculature, including both endothelial and vascular smooth muscle cell compartments. Intriguingly, a reversal in the polarized expression of HS within the cerebrovasculature was detected in AD patients with severe CAA. Furthermore, male patients exhibited lower levels of both parenchymal and cerebrovascular HS. Additionally, ApoE4 carriers displayed heightened cerebrovascular Aß expression and a tendency of elevated cerebrovascular HS levels in AD patients with severe CAA. Overall, these findings reveal potential intricate interplay between HS, Aß, ApoE, and vascular pathology in AD, thereby underscoring the potential roles of cerebrovascular HS in CAA development and AD pathology. Further study of the underlying mechanisms may present novel therapeutic avenues for AD treatment.

Effects of a High-Fat Diet on Insulin-Related miRNAs in Plasma and Brain Tissue in APPSwe/PS1dE9 and Wild-Type C57BL/6J Mice.

Insulin resistance (IR)-related miRNAs have been associated with the development and progression of Alzheimer's disease (AD). The dietary modulation of these miRNAs could become a potential strategy to manage AD. The aim of this study was to evaluate the effect of a high-fat diet (HFD), which aggravates AD-related pathogenic processes, on serum, cortex and hippocampus IR-related miRNA expression. C57BL/6J WT and APPSwe/PS1dE9 mice were fed either an HFD or a conventional diet till 6 months of age. The mice fed with the HFD showed a significant increase in body weight and worsening glucose and insulin metabolism. miR-19a-3p was found to be up-regulated in the cortex, hippocampus and serum of APP/PS1 mice and in the serum and hippocampus of WT mice fed with the HFD. miR-34a-5p and miR-146a-5p were up-regulated in the serum of both groups of mice after consuming the HFD. Serum miR-29c-3p was overexpressed after consuming the HFD, along with hippocampal miR-338-3p and miR-125b-5p, only in WT mice. The HFD modulated the expression of peripheral and brain miRNAs related to glucose and insulin metabolism, suggesting the potential role of these miRNAs not only as therapeutic targets of AD but also as peripheral biomarkers for monitoring AD.

Transcriptome and Animal Model Integration Reveals Inhibition of Calcium Homeostasis-Associated Gene ITPKB Alleviates Amyloid Plaque Deposition.

Alzheimer's disease (AD) is a severe neurological illness that causes memory loss and is a global problem. The calcium hypothesis recently steadily evolved in AD. The prospective targets for calcium homeostasis therapy, however, are limited, and gene expression-level research connected to calcium homeostasis in AD remains hazy. In this study, we analyzed the microarray dataset (GSE132903) taken from the Gene Expression Omnibus (GEO) database to investigate calcium homeostasis-related genes for AD. Using immunoblot analysis, we examined the association of ITPKB with inflammation in AD. Additionally, the immunofluorescence technique was employed to assess the impact of pharmacological inhibition of ITPKB on the amyloid-ß (Aß) plaque deposition in APP/PS1 mice. This article's further exploration of calcium homeostasis-related genes has propelled the validation of the calcium homeostasis theory in AD.

Impact of genetic predisposition to late-onset neurodegenerative diseases on early life outcomes and brain structure.

Most patients with late-onset neurodegenerative diseases such as Alzheimer's and Parkinson's have a complex aetiology resulting from numerous genetic risk variants of small effects located across the genome, environmental factors, and the interaction between genes and environment. Over the last decade, genome-wide association studies (GWAS) and post-GWAS analyses have shed light on the polygenic architecture of these diseases, enabling polygenic risk scores (PRS) to estimate an individual's relative genetic liability for presenting with the disease. PRS can screen and stratify individuals based on their genetic risk, potentially years or even decades before the onset of clinical symptoms. An emerging body of evidence from various research studies suggests that genetic susceptibility to late-onset neurodegenerative diseases might impact early life outcomes, including cognitive function, brain structure and function, and behaviour. This article summarises recent findings exploring the potential impact of genetic susceptibility to neurodegenerative diseases on early life outcomes. A better understanding of the impact of genetic susceptibility to neurodegenerative diseases early in life could be valuable in disease screening, detection, and prevention and in informing treatment strategies before significant neural damage has occurred. However, ongoing studies have limitations. Overall, our review found several studies focused on APOE haplotypes and Alzheimer's risk, but a limited number of studies leveraging polygenic risk scores or focused on genetic susceptibility to other late-onset conditions.

The following article for this Special Issue was previously published and can be found in its respective issue online: "Detection of early Alzheimer's disease-like molecular alterations in a mouse model expressing human ApoE4".

Detection of early Alzheimer's disease-like molecular alterations in a mouse model expressing human ApoE4 (Published in JNC 166.3 issue) https://onlinelibrary.wiley.com/doi/10.1111/jnc.15904.

Exploring Acori Tatarinowii Rhizoma and Polygalae Radix in Alzheimer's: Network pharmacology and molecular docking analysis.

Explore Acori Tatarinowii Rhizoma (ATR) and Polygalae Radix (PR) mechanisms in Alzheimer's disease (AD) treatment through network pharmacology. ATR-PR was investigated in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, Batman, and Traditional Chinese Medicines Integrated Database (TCMID) to gather information on its chemical components and target proteins. Target genes associated with AD were retrieved from the GeneCards and National Center for Biotechnology Information (NCBI) databases. The integration of these datasets with potential targets facilitated the construction of an AD and ATR-PR protein-protein interaction (PPI) network using the STRING database. The resulting network identified the core active ingredients and main targets of ATR-PR in AD treatment. Cluster analysis of the PPI network was performed using Cytoscape 3.7.1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Metascape database. Molecular docking simulations revealed potential interactions between the main active ingredients and core targets. Our analysis identified 8 putative components and 455 targets of ATR-PR. We systematically searched for 1306 genes associated with AD, conducted Venn diagram analysis resulting in 156 common targets, and constructed a PPI network with 57 key targets. GO functional analysis highlighted the primary biological processes associated with oxidative stress. KEGG pathway enrichment analysis revealed the involvement of 64 signaling pathways, with the PI3K/Akt signaling pathway playing a key role. Molecular docking analysis indicated a high affinity between the potential targets of ATR-PR and the main compounds of AD. This study sheds light on the complex network of interactions involving ATR-PR in the context of AD. The identified targets, pathways, and interactions provide a foundation for understanding the potential therapeutic mechanisms. The involvement of oxidative stress-related processes and the crucial role of the PI3K/Akt signaling pathway suggest avenues for targeted therapeutic interventions in Alzheimer's disease treatment. Our proposition of the combined use of ATR-PR has emerged as a potential treatment strategy for AD, supported by a network pharmacology approach. This framework provides a robust foundation for future clinical applications and experimental research in the pursuit of effective Alzheimer's disease treatments.

Endothelial DR6 in blood-brain barrier malfunction in Alzheimer's disease.

The impairment of the blood-brain barrier (BBB) has been increasingly recognised as a critical element in the early pathogenesis of Alzheimer's disease (AD), prompting a focus on brain endothelial cells (BECs), which serve as the primary constituents of the BBB. Death receptor 6 (DR6) is highly expressed in brain vasculature and acts downstream of the Wnt/ß-catenin pathway to promote BBB formation during development. Here, we found that brain endothelial DR6 levels were significantly reduced in a murine model of AD (APPswe/PS1dE9 mice) at the onset of amyloid-ß (Aß) accumulation. Toxic Aß25-35 oligomer treatment recapitulated the reduced DR6 in cultured BECs. We further showed that suppressing DR6 resulted in BBB malfunction in the presence of Aß25-35 oligomers. In contrast, overexpressing DR6 increased the level of BBB functional proteins through the activation of the Wnt/ß-catenin and JNK pathways. More importantly, DR6 overexpression in BECs was sufficient to rescue BBB dysfunction in vitro. In conclusion, our findings provide new insight into the role of endothelial DR6 in AD pathogenesis, highlighting its potential as a therapeutic target to tackle BBB dysfunction in early-stage AD progression.

DEAD Box Helicase 24 Is Increased in the Brain in Alzheimer's Disease and AppN-LF Mice and Influences Presymptomatic Pathology.

At the time of diagnosis, Alzheimer's disease (AD) patients already suffer from significant neuronal loss. The identification of proteins that influence disease progression before the onset of symptoms is thus an essential part of the development of new effective drugs and biomarkers. Here, we used an unbiased 18O labelling proteomics approach to identify proteins showing altered levels in the AD brain. We studied the relationship between the protein with the highest increase in hippocampus, DEAD box Helicase 24 (DDX24), and AD pathology. We visualised DDX24 in the human brain and in a mouse model for Aß42-induced AD pathology-AppNL-F-and studied the interaction between Aß and DDX24 in primary neurons. Immunohistochemistry in the AD brain confirmed the increased levels and indicated an altered subcellular distribution of DDX24. Immunohistochemical studies in AppNL-F mice showed that the increase of DDX24 starts before amyloid pathology or memory impairment is observed. Immunocytochemistry in AppNL-F primary hippocampal neurons showed increased DDX24 intensity in the soma, nucleus and nucleolus. Furthermore, siRNA targeting of DDX24 in neurons decreased APP and Aß42 levels, and the addition of Aß42 to the medium reduced DDX24. In conclusion, we have identified DDX24 as a protein with a potential role in Aß-induced AD pathology.

Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer's Disease Neuroimaging Initiative cohort.

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.

Central inhibition of stearoyl-CoA desaturase has minimal effects on the peripheral metabolic symptoms of the 3xTg Alzheimer's disease mouse model.

Evidence from genetic and epidemiological studies point to lipid metabolism defects in both the brain and periphery being at the core of Alzheimer's disease (AD) pathogenesis. Previously, we reported that central inhibition of the rate-limiting enzyme in monounsaturated fatty acid synthesis, stearoyl-CoA desaturase (SCD), improves brain structure and function in the 3xTg mouse model of AD (3xTg-AD). Here, we tested whether these beneficial central effects involve recovery of peripheral metabolic defects, such as fat accumulation and glucose and insulin handling. As early as 3 months of age, 3xTg-AD mice exhibited peripheral phenotypes including increased body weight and visceral and subcutaneous white adipose tissue as well as diabetic-like peripheral gluco-regulatory abnormalities. We found that intracerebral infusion of an SCD inhibitor that normalizes brain fatty acid desaturation, synapse loss and learning and memory deficits in middle-aged memory-impaired 3xTg-AD mice did not affect these peripheral phenotypes. This suggests that the beneficial effects of central SCD inhibition on cognitive function are not mediated by recovery of peripheral metabolic abnormalities. Given the widespread side-effects of systemically administered SCD inhibitors, these data suggest that selective inhibition of SCD in the brain may represent a clinically safer and more effective strategy for AD.

Dysregulated AEBP1 and COLEC12 Genes in Late-Onset Alzheimer's Disease: Insights from Brain Cortex and Peripheral Blood Analysis.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive impairment, often accompanied by alterations in mood, confusion, and, ultimately, a state of acute mental disturbance. The cerebral cortex is considered a promising area for investigating the underlying causes of AD by analyzing transcriptional patterns, which could be complemented by investigating blood samples obtained from patients. We analyzed the RNA expression profiles of three distinct areas of the brain cortex, including the frontal cortex (FC), temporal cortex (TC), and entorhinal cortex (EC) in patients with AD. Functional enrichment analysis was performed on the differentially expressed genes (DEGs) across the three regions. The two genes with the most significant expression changes in the EC region were selected for assessing mRNA expression levels in the peripheral blood of late-onset AD patients using quantitative PCR (qPCR). We identified eight shared DEGs in these regions, including AEBP1 and COLEC12, which exhibited prominent changes in expression. Functional enrichment analysis uncovered a significant association of these DEGs with the transforming growth factor-ß (TGF-ß) signaling pathway and processes related to angiogenesis. Importantly, we established a robust connection between the up-regulation of AEBP1 and COLEC12 in both the brain and peripheral blood. Furthermore, we have demonstrated the potential of AEBP1 and COLEC12 genes as effective diagnostic tools for distinguishing between late-onset AD patients and healthy controls. This study unveils the intricate interplay between AEBP1 and COLEC12 in AD and underscores their potential as markers for disease detection and monitoring.

Exploring Imaging Genetic Markers of Alzheimer's Disease Based on a Novel Nonlinear Correlation Analysis Algorithm.

Alzheimer's disease (AD) is an irreversible neurological disorder characterized by insidious onset. Identifying potential markers in its emergence and progression is crucial for early diagnosis and treatment. Imaging genetics typically merges genetic variables with multiple imaging parameters, employing various association analysis algorithms to investigate the links between pathological phenotypes and genetic variations, and to unearth molecular-level insights from brain images. However, most existing imaging genetics algorithms based on sparse learning assume a linear relationship between genetic factors and brain functions, limiting their ability to discern complex nonlinear correlation patterns and resulting in reduced accuracy. To address these issues, we propose a novel nonlinear imaging genetic association analysis method, Deep Self-Reconstruction-based Adaptive Sparse Multi-view Deep Generalized Canonical Correlation Analysis (DSR-AdaSMDGCCA). This approach facilitates joint learning of the nonlinear relationships between pathological phenotypes and genetic variations by integrating three different types of data: structural magnetic resonance imaging (sMRI), single-nucleotide polymorphism (SNP), and gene expression data. By incorporating nonlinear transformations in DGCCA, our model effectively uncovers nonlinear associations across multiple data types. Additionally, the DSR algorithm clusters samples with identical labels, incorporating label information into the nonlinear feature extraction process and thus enhancing the performance of association analysis. The application of the DSR-AdaSMDGCCA algorithm on real data sets identified several AD risk regions (such as the hippocampus, parahippocampus, and fusiform gyrus) and risk genes (including VSIG4, NEDD4L, and PINK1), achieving maximum classification accuracy with the fewest selected features compared to baseline algorithms. Molecular biology enrichment analysis revealed that the pathways enriched by these top genes are intimately linked to AD progression, affirming that our algorithm not only improves correlation analysis performance but also identifies biologically significant markers.

Predictors for survival in patients with Alzheimer's disease: a large comprehensive meta-analysis.

The prevalence of Alzheimer's disease (AD) is increasing as the population ages, and patients with AD have a poor prognosis. However, knowledge on factors for predicting the survival of AD remains sparse. Here, we aimed to systematically explore predictors of AD survival. We searched the PubMed, Embase and Cochrane databases for relevant literature from inception to December 2022. Cohort and case-control studies were selected, and multivariable adjusted relative risks (RRs) were pooled by random-effects models. A total of 40,784 reports were identified, among which 64 studies involving 297,279 AD patients were included in the meta-analysis after filtering based on predetermined criteria. Four aspects, including demographic features (n = 7), clinical features or comorbidities (n = 13), rating scales (n = 3) and biomarkers (n = 3), were explored and 26 probable prognostic factors were finally investigated for AD survival. We observed that AD patients who had hyperlipidaemia (RR: 0.69) were at a lower risk of death. In contrast, male sex (RR: 1.53), movement disorders (including extrapyramidal signs) (RR: 1.60) and cancer (RR: 2.07) were detrimental to AD patient survival. However, our results did not support the involvement of education, hypertension, APOE genotype, Aß42 and t-tau in AD survival. Our study comprehensively summarized risk factors affecting survival in patients with AD, provided a better understanding on the role of different factors in the survival of AD from four dimensions, and paved the way for further research.

Polygenic risk associated with Alzheimer's disease and other traits influences genes involved in T cell signaling and activation.

Introduction: T cells, known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. T cell gene expression phenotypes can be regulated by disease-associated genetic variants. Many complex diseases are better represented by polygenic risk than by individual variants. Methods: We first compute a polygenic risk score (PRS) for Alzheimer's disease (AD) using genomic sequencing data from a cohort of Alzheimer's disease (AD) patients and age-matched controls, and validate the AD PRS against clinical metrics in our cohort. We then calculate the PRS for several autoimmune disease, neurological disorder, and immune function traits, and correlate these PRSs with T cell gene expression data from our cohort. We compare PRS-associated genes across traits and four T cell subtypes. Results: Several genes and biological pathways associated with the PRS for these traits relate to key T cell functions. The PRS-associated gene signature generally correlates positively for traits within a particular category (autoimmune disease, neurological disease, immune function) with the exception of stroke. The trait-associated gene expression signature for autoimmune disease traits was polarized towards CD4+ T cell subtypes. Discussion: Our findings show that polygenic risk for complex disease and immune function traits can have varying effects on T cell gene expression trends. Several PRS-associated genes are potential candidates for therapeutic modulation in T cells, and could be tested in in vitro applications using cells from patients bearing high or low polygenic risk for AD or other conditions.

Characterization of monoamine oxidase-B (MAO-B) as a biomarker of reactive astrogliosis in Alzheimer's disease and related dementias.

Reactive astrogliosis accompanies the two neuropathological hallmarks of Alzheimer's disease (AD)-Aß plaques and neurofibrillary tangles-and parallels neurodegeneration in AD and AD-related dementias (ADRD). Thus, there is growing interest in developing imaging and fluid biomarkers of reactive astrogliosis for AD/ADRD diagnosis and prognostication. Monoamine oxidase-B (MAO-B) is emerging as a target for PET imaging radiotracers of reactive astrogliosis. However, a thorough characterization of MAO-B expression in postmortem control and AD/ADRD brains is lacking. We sought to: (1) identify the primary cell type(s) expressing MAO-B in control and AD brains; (2) quantify MAO-B immunoreactivity in multiple brain regions of control and AD donors as a proxy for PET radiotracer uptake; (3) correlate MAO-B level with local AD neuropathological changes, reactive glia, and cortical atrophy; (4) determine whether the MAOB rs1799836 SNP genotype impacts MAO-B expression level; (5) compare MAO-B immunoreactivity across AD/ADRD, including Lewy body diseases (LBD) and frontotemporal lobar degenerations with tau (FTLD-Tau) and TDP-43 (FTLD-TDP). We found that MAO-B is mainly expressed by subpial and perivascular cortical astrocytes as well as by fibrous white matter astrocytes in control brains, whereas in AD brains, MAO-B is significantly upregulated by both cortical reactive astrocytes and white matter astrocytes across temporal, frontal, and occipital lobes. By contrast, MAO-B expression level was unchanged and lowest in cerebellum. Cortical MAO-B expression was independently associated with cortical atrophy and local measures of reactive astrocytes and microglia, and significantly increased in reactive astrocytes surrounding Thioflavin-S+ dense-core Aß plaques. MAO-B expression was not affected by the MAOB rs1799836 SNP genotype. MAO-B expression was also significantly increased in the frontal cortex and white matter of donors with corticobasal degeneration, Pick's disease, and FTLD-TDP, but not in LBD or progressive supranuclear palsy. These findings support ongoing efforts to develop MAO-B-based PET radiotracers to image reactive astrogliosis in AD/ADRD.

Biomarker profiling to determine clinical impact of microRNAs in cognitive disorders.

Alzheimer's disease (AD) and post-stroke cognitive impairment (PSCI) are the leading causes of progressive dementia related to neurodegenerative and cerebrovascular injuries in elderly populations. Despite decades of research, patients with these conditions still lack minimally invasive, low-cost, and effective diagnostic and treatment methods. MicroRNAs (miRNAs) play a vital role in AD and PSCI pathology. As they are easily obtained from patients, miRNAs are promising candidates for the diagnosis and treatment of these two disorders. In this study, we performed complete sequencing analysis of miRNAs from 24 participants, split evenly into the PSCI, post-stroke non-cognitive impairment (PSNCI), AD, and normal control (NC) groups. To screen for differentially expressed miRNAs (DE-miRNAs) in patients, we predicted their target genes using bioinformatics analysis. Our analyses identified miRNAs that can distinguish between the investigated disorders; several of them were novel and never previously reported. Their target genes play key roles in multiple signaling pathways that have potential to be modified as a clinical treatment. In conclusion, our study demonstrates the potential of miRNAs and their key target genes in disease management. Further in-depth investigations with larger sample sizes will contribute to the development of precise treatments for AD and PSCI.

Unique transcriptional signatures correlate with behavioral and psychological symptom domains in Alzheimer's disease.

Despite the significant burden, cost, and worse prognosis of Alzheimer's disease (AD) with behavioral and psychological symptoms of dementia (BPSD), little is known about the molecular causes of these symptoms. Using antemortem assessments of BPSD in AD, we demonstrate that individual BPSD can be grouped into 4 domain factors in our cohort: affective, apathy, agitation, and psychosis. Then, we performed a transcriptome-wide analysis for each domain utilizing bulk RNA-seq of post-mortem anterior cingulate cortex (ACC) tissues. Though all 4 domains are associated with a predominantly downregulated pattern of hundreds of differentially expressed genes (DEGs), most DEGs are unique to each domain, with only 22 DEGs being common to all BPSD domains, including TIMP1. Weighted gene co-expression network analysis (WGCNA) yielded multiple transcriptional modules that were shared between BPSD domains or unique to each domain, and NetDecoder was used to analyze context-dependent information flow through the biological network. For the agitation domain, we found that all DEGs and a highly associated transcriptional module were functionally enriched for ECM-related genes including TIMP1, TAGLN, and FLNA. Another unique transcriptional module also associated with the agitation domain was enriched with genes involved in post-synaptic signaling, including DRD1, PDE1B, CAMK4, and GABRA4. By comparing context-dependent changes in DEGs between cases and control networks, ESR1 and PARK2 were implicated as two high-impact genes associated with agitation that mediated significant information flow through the biological network. Overall, our work establishes unique targets for future study of the biological mechanisms of BPSD and resultant drug development.