Altered expression of diabetes-related genes in Alzheimer's disease brains: the Hisayama study

Omics-derived biological modules reflect metabolic brain changes in Alzheimer's disease

INTRODUCTION

Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive.

METHODS

Here, we integrated [18F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n = 445) and cognitively impaired (CI, n = 749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis.

RESULTS

Our results showed that multiple transcriptomic modules are associated with brain [18F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t(223) = 4.86, P value < 0.001) and zinc-finger-related regulatory units (peak-t(223) = 3.90, P value < 0.001).

DISCUSSION

By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD.

HIGHLIGHTS

We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [18F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [18F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [18F]FDG-PET metabolism.

A novel insight into neurological disorders through HDAC6 protein-protein interactions

Due to its involvement in physiological and pathological processes, histone deacetylase 6 (HDAC6) is considered a promising pharmaceutical target for several neurological manifestations. However, the exact regulatory role of HDAC6 in the central nervous system (CNS) is still not fully understood. Hence, using a semi-automated literature screening technique, we systematically collected HDAC6-protein interactions that are experimentally validated and reported in the CNS. The resulting HDAC6 network encompassed 115 HDAC6-protein interactions divided over five subnetworks: (de)acetylation, phosphorylation, protein complexes, regulatory, and aggresome-autophagy subnetworks. In addition, 132 indirect interactions identified through HDAC6 inhibition were collected and categorized. Finally, to display the application of our HDAC6 network, we mapped transcriptomics data of Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis on the network and highlighted that in the case of Alzheimer's disease, alterations predominantly affect the HDAC6 phosphorylation subnetwork, whereas differential expression within the deacetylation subnetwork is observed across all three neurological disorders. In conclusion, the HDAC6 network created in the present study is a novel and valuable resource for the understanding of the HDAC6 regulatory mechanisms, thereby providing a framework for the integration and interpretation of omics data from neurological disorders and pharmacodynamic assessments.

Molecular mechanisms linking type 2 diabetes mellitus and late-onset Alzheimer's disease: A systematic review and qualitative meta-analysis

Research evidence indicating common metabolic mechanisms through which type 2 diabetes mellitus (T2DM) increases risk of late-onset Alzheimer's dementia (LOAD) has accumulated over recent decades. The aim of this systematic review is to provide a comprehensive review of common mechanisms, which have hitherto been discussed in separate perspectives, and to assemble and evaluate candidate loci and epigenetic modifications contributing to polygenic risk linkages between T2DM and LOAD. For the systematic review on pathophysiological mechanisms, both human and animal studies up to December 2023 are included. For the qualitative meta-analysis of genomic bases, human association studies were examined; for epigenetic mechanisms, data from human studies and animal models were accepted. Papers describing pathophysiological studies were identified in databases, and further literature gathered from cited work. For genomic and epigenomic studies, literature mining was conducted by formalised search codes using Boolean operators in search engines, and augmented by GeneRif citations in Entrez Gene, and other sources (WikiGenes, etc.). For the systematic review of pathophysiological mechanisms, 923 publications were evaluated, and 138 gene loci extracted for testing candidate risk linkages. 3 57 publications were evaluated for genomic association and descriptions of epigenomic modifications. Overall accumulated results highlight insulin signalling, inflammation and inflammasome pathways, proteolysis, gluconeogenesis and glycolysis, glycosylation, lipoprotein metabolism and oxidation, cell cycle regulation or survival, autophagic-lysosomal pathways, and energy. Documented findings suggest interplay between brain insulin resistance, neuroinflammation, insult compensatory mechanisms, and peripheral metabolic dysregulation in T2DM and LOAD linkage. The results allow for more streamlined longitudinal studies of T2DM-LOAD risk linkages.

DNA methylation of imprint control regions associated with Alzheimer's disease in non-Hispanic Blacks and non-Hispanic Whites

Alzheimer's disease (AD) prevalence is twice as high in non-Hispanic Blacks (NHBs) as in non-Hispanic Whites (NHWs). The objective of this study was to determine whether aberrant methylation at imprint control regions (ICRs) is associated with AD. Differentially methylated regions (DMRs) were bioinformatically identified from whole-genome bisulfite sequenced DNA derived from brain tissue of 9 AD (5 NHBs and 4 NHWs) and 8 controls (4 NHBs and 4 NHWs). We identified DMRs located within 120 regions defined as candidate ICRs in the human imprintome ( https://genome.ucsc.edu/s/imprintome/hg38.AD.Brain_track ). Eighty-one ICRs were differentially methylated in NHB-AD, and 27 ICRs were differentially methylated in NHW-AD, with two regions common to both populations that are proximal to the inflammasome gene, NLRP1, and a known imprinted gene, MEST/MESTIT1. These findings indicate that early developmental alterations in DNA methylation of regions regulating genomic imprinting may contribute to AD risk and that this epigenetic risk differs between NHBs and NHWs.

Shared genetic aetiology of Alzheimer's disease and age-related macular degeneration by APOC1 and APOE genes

Background

Alzheimer's disease (AD) and age-related macular degeneration (AMD) share similar pathological features, suggesting common genetic aetiologies between the two. Investigating gene associations between AD and AMD may provide useful insights into the underlying pathogenesis and inform integrated prevention and treatment for both diseases.

Methods

A stratified quantile-quantile (QQ) plot was constructed to detect the pleiotropy among AD and AMD based on genome-wide association studies data from 17 008 patients with AD and 30 178 patients with AMD. A Bayesian conditional false discovery rate-based (cFDR) method was used to identify pleiotropic genes. UK Biobank was used to verify the pleiotropy analysis. Biological network and enrichment analysis were conducted to explain the biological reason for pleiotropy phenomena. A diagnostic test based on gene expression data was used to predict biomarkers for AD and AMD based on pleiotropic genes and their regulators.

Results

Significant pleiotropy was found between AD and AMD (significant leftward shift on QQ plots). APOC1 and APOE were identified as pleiotropic genes for AD-AMD (cFDR <0.01). Network analysis revealed that APOC1 and APOE occupied borderline positions on the gene co-expression networks. Both APOC1 and APOE genes were enriched on the herpes simplex virus 1 infection pathway. Further, machine learning-based diagnostic tests identified that APOC1, APOE (areas under the curve (AUCs) >0.65) and their upstream regulators, especially ZNF131, ADNP2 and HINFP, could be potential biomarkers for both AD and AMD (AUCs >0.8).

Conclusion

In this study, we confirmed the genetic pleiotropy between AD and AMD and identified APOC1 and APOE as pleiotropic genes. Further, the integration of multiomics data identified ZNF131, ADNP2 and HINFP as novel diagnostic biomarkers for AD and AMD.

Cholecystokinin (CCK): a neuromodulator with therapeutic potential in Alzheimer's and Parkinson's disease

Cholecystokinin (CCK) is a neuropeptide modulating digestion, glucose levels, neurotransmitters and memory. Recent studies suggest that CCK exhibits neuroprotective effects in Alzheimer's disease (AD) and Parkinson's disease (PD). Thus, we review the physiological function and therapeutic potential of CCK. The neuropeptide facilitates hippocampal glutamate release and gates GABAergic basket cell activity, which improves declarative memory acquisition, but inhibits consolidation. Cortical CCK alters recognition memory and enhances audio-visual processing. By stimulating CCK-1 receptors (CCK-1Rs), sulphated CCK-8 elicits dopamine release in the substantia nigra and striatum. In the mesolimbic pathway, CCK release is triggered by dopamine and terminates reward responses via CCK-2Rs. Importantly, activation of hippocampal and nigral CCK-2Rs is neuroprotective by evoking AMPK activation, expression of mitochondrial fusion modulators and autophagy. Other benefits include vagus nerve/CCK-1R-mediated expression of brain-derived neurotrophic factor, intestinal protection and suppression of inflammation. We also discuss caveats and the therapeutic combination of CCK with other peptide hormones.

Cross-species comparative hippocampal transcriptomics in Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial pathology, with most cases having a sporadic origin. Recently, knock-in (KI) mouse models, such as the novel humanized amyloid-β (hAβ)-KI, have been developed to better resemble sporadic human AD.

METHODS

Here, we compared hippocampal publicly available transcriptomic profiles of transgenic (5xFAD and APP/PS1) and KI (hAβ-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients.

RESULTS

The three mouse models presented more Gene Ontology biological processes terms and enriched signaling pathways in common with LOAD than with EOAD individuals. Experimental validation of consistently dysregulated genes revealed five altered in mice (SLC11A1, S100A6, CD14, CD33, and C1QB) and three in humans (S100A6, SLC11A1, and KCNK). Finally, we identified 17 transcription factors potentially acting as master regulators of AD.

CONCLUSION

Our cross-species analyses revealed that the three mouse models presented a remarkable similarity to LOAD, with the hAβ-KI being the more specific one.

Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis

SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.

Probiotic Clostridium butyricum ameliorates cognitive impairment in obesity via the microbiota-gut-brain axis

Obesity is a risk factor for cognitive dysfunction and neurodegenerative disease, including Alzheimer's disease (AD). The gut microbiota-brain axis is altered in obesity and linked to cognitive impairment and neurodegenerative disorders. Here, we targeted obesity-induced cognitive impairment by testing the impact of the probiotic Clostridium butyricum, which has previously shown beneficial effects on gut homeostasis and brain function. Firstly, we characterized and analyzed the gut microbial profiles of participants with obesity and the correlation between gut microbiota and cognitive scores. Then, using an obese mouse model induced by a Western-style diet (high-fat and fiber-deficient diet), the effects of Clostridium butyricum on the microbiota-gut-brain axis and hippocampal cognitive function were evaluated. Finally, fecal microbiota transplantation was performed to assess the functional link between Clostridium butyricum remodeling gut microbiota and hippocampal synaptic protein and cognitive behaviors. Our results showed that participants with obesity had gut microbiota dysbiosis characterized by an increase in phylum Proteobacteria and a decrease in Clostridium butyricum, which were closely associated with cognitive decline. In diet-induced obese mice, oral Clostridium butyricum supplementation significantly alleviated cognitive impairment, attenuated the deficit of hippocampal neurite outgrowth and synaptic ultrastructure, improved hippocampal transcriptome related to synapses and dendrites; a comparison of the effects of Clostridium butyricum in mice against human AD datasets revealed that many of the genes changes in AD were reversed by Clostridium butyricum; concurrently, Clostridium butyricum also prevented gut microbiota dysbiosis, colonic barrier impairment and inflammation, and attenuated endotoxemia. Importantly, fecal microbiota transplantation from donor-obese mice with Clostridium butyricum supplementation facilitated cognitive variables and colonic integrity compared with from donor obese mice, highlighting that Clostridium butyricum's impact on cognitive function is largely due to its ability to remodel gut microbiota. Our findings provide the first insights into the neuroprotective effects of Clostridium butyricum on obesity-associated cognitive impairments and neurodegeneration via the gut microbiota-gut-brain axis.

Transcriptome analysis of the cerebral cortex of acrylamide-exposed wild-type and IL-1β-knockout mice

Acrylamide is an environmental electrophile that has been produced in large amounts for many years. There is concern about the adverse health effects of acrylamide exposure due to its widespread industrial use and also presence in commonly consumed foods and others. IL-1β is a key cytokine that protects the brain from inflammatory insults, but its role in acrylamide-induced neurotoxicity remains unknown. We reported recently that deletion of IL-1β gene exacerbates ACR-induced neurotoxicity in mice. The aim of this study was to identify genes or signaling pathway(s) involved in enhancement of ACR-induced neurotoxicity by IL-1β gene deletion or ACR-induced neurotoxicity to generate a hypothesis mechanism explaining ACR-induced neurotoxicity. C57BL/6 J wild-type and IL-1β KO mice were exposed to ACR at 0, 12.5, 25 mg/kg by oral gavage for 7 days/week for 4 weeks, followed by extraction of mRNA from mice cerebral cortex for RNA sequence analysis. IL-1β deletion altered the expression of genes involved in extracellular region, including upregulation of PFN1 gene related to amyotrophic lateral sclerosis and increased the expression of the opposite strand of IL-1β. Acrylamide exposure enhanced mitochondria oxidative phosphorylation, synapse and ribosome pathways, and activated various pathways of different neurodegenerative diseases, such as Alzheimer disease, Parkinson disease, Huntington disease, and prion disease. Protein network analysis suggested the involvement of different proteins in related to learning and cognitive function, such as Egr1, Egr2, Fos, Nr4a1, and Btg2. Our results identified possible pathways involved in IL-1β deletion-potentiated and ACR-induced neurotoxicity in mice.

Reduced gray matter volume in the default-mode network associated with insulin resistance

Insulin resistance may lead to structural and functional abnormalities of the human brain. However, the mechanism by which insulin resistance impairs the brain remains elusive. In this study, we used two large neuroimaging databases to investigate the brain regions where insulin resistance was associated with the gray matter volume and to examine the resting-state functional connectivity between these brain regions and each hypothalamic nucleus. Insulin resistance was associated with reduced gray matter volume in the regions of the default-mode and limbic networks in the cerebral cortex in older adults. Resting-state functional connectivity was prominent between these networks and the paraventricular nucleus of the hypothalamus, a hypothalamic interface connecting functionally with the cerebral cortex. Furthermore, we found a significant correlation in these networks between insulin resistance-related gray matter volume reduction and network paraventricular nucleus of the hypothalamus resting-state functional connectivity. These results suggest that insulin resistance-related gray matter volume reduction in the default-mode and limbic networks emerged through metabolic homeostasis mechanisms in the hypothalamus.

Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network

Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.

Neurodegenerative Disease Associated Pathways in the Brains of Triple Transgenic Alzheimer's Model Mice Are Reversed Following Two Weeks of Peripheral Administration of Fasudil

The pan Rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor fasudil acts as a vasodilator and has been used as a medication for post-cerebral stroke for the past 29 years in Japan and China. More recently, based on the involvement of ROCK inhibition in synaptic function, neuronal survival, and processes associated with neuroinflammation, it has been suggested that the drug may be repurposed for neurodegenerative diseases. Indeed, fasudil has demonstrated preclinical efficacy in many neurodegenerative disease models. To facilitate an understanding of the wider biological processes at play due to ROCK inhibition in the context of neurodegeneration, we performed a global gene expression analysis on the brains of Alzheimer's disease model mice treated with fasudil via peripheral IP injection. We then performed a comparative analysis of the fasudil-driven transcriptional profile with profiles generated from a meta-analysis of multiple neurodegenerative diseases. Our results show that fasudil tends to drive gene expression in a reverse sense to that seen in brains with post-mortem neurodegenerative disease. The results are most striking in terms of pathway enrichment analysis, where pathways perturbed in Alzheimer's and Parkinson's diseases are overwhelmingly driven in the opposite direction by fasudil treatment. Thus, our results bolster the repurposing potential of fasudil by demonstrating an anti-neurodegenerative phenotype in a disease context and highlight the potential of in vivo transcriptional profiling of drug activity.

Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Proteomic analysis of anti-aging effects of Dendrobium nobile Lindl. alkaloids in aging-accelerated SAMP8 mice

Senescence-accelerated mouse prone 8 (SAMP8) mice exhibit cognitive defects and neuron loss with aging, and were used to study anti-aging effects of Dendrobium nobile alkaloids (DNLA). DNLA (20 and 40 mg/kg) were orally administered to SAMP8 mice from 6 to 10 months of age. At 10-month of age, behavioral tests via Y-maze and Open-field and neuron damage via Nissl staining were evaluated. Protein was extracted and subjected to phosphorylated proteomic analysis followed by bioinformatic analysis. The cognitive deficits and neuron loss in hippocampus and cortex of aged SAMP8 mice were improved by DNLA. Hippocampal proteomic analysis revealed 196 differentially expressed protein/genes in SAMP8 compared to age-matched senescence-accelerated resistant SAMR1 mice. Gene Oncology enriched the tubulin binding, microtubule binding, and other activities. Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed endocytosis, mRNA surveillance, tight junction, protein processing in endoplasmic reticulum, aldosterone synthesis and secretion, and glucagon signaling pathway changes. Upregulated protein/genes in the hippocampus of SAMP8 mice, such as Lmtk3, Usp10, Dzip1, Csnk2b, and Rtn1, were attenuated by DNLA; whereas downregulated protein/genes, such as Kctd16, Psd3, Bsn, Atxn2l, and Kif1a, were rescued by DNLA. The aberrant protein/gene expressions of SAMP8 mice were correlated with transcriptome changes of Alzheimer's disease in the Gene Expression Omnibus (GEO) database, and the scores were attenuated by DNLA. Thus, DNLA improved cognitive dysfunction and ameliorated neuronal injury in aged SAMP8 mice, and attenuated aberrant protein/gene expressions.

Development and validation of a 13-gene signature associated with immune function for the detection of Alzheimer's disease

Current knowledge of Alzheimer's disease (AD) etiology and effective therapy remains limited. Thus, the identification of biomarkers is crucial to improve the detection and treatment of patients with AD. Using robust rank aggregation method to analyze the microarray data from Gene Expression Omnibus database, we identified 1138 differentially expressed genes in AD. We then explored 13 hub genes by weighted gene co-expression network analysis, least absolute shrinkage, and selection operator, and logistic regression in the training dataset. The detection model, which composed of CD163, CDC42SE1, CECR6, CSF1R, CYP27A1, EIF4E3, H2AFJ, IFIT2, IL10RA, KIAA1324, PSTPIP1, SLA, and TBC1D2 genes, along with APOE gene, showed that the area under the curve for detecting AD was 0.821 (95% confidence interval [CI] = 0.782-0.861) and the model was validated in ADNI dataset (area under the curve = 0.776; 95%CI = 0.686-0.865). Notably, the 13 genes in the model were highly enriched in immune function. These findings have implications for the detection and therapeutic target of AD.

Overexpression of Parkin in the Neuronal Progenitor Cells from a Patient with Parkinson's Disease Shifts the Transcriptome Towards the Normal State

Parkinson's disease (PD) is a neurodegenerative pathology caused by the progressive loss of dopaminergic neurons in the substantia nigra. Juvenile PD is known to be strongly associated with mutations in the PARK2 gene encoding E3 ubiquitin ligase Parkin. Despite numerous studies, molecular mechanisms that trigger PD remain largely unknown. Here, we compared the transcriptome of the neural progenitor (NP) cell line, derived from a PD patient with PARK2 mutation resulting in Parkin loss, with the transcriptome of the same NPs but expressing transgenic Parkin. We found that Parkin overexpression led to the substantial recovery of the transcriptome of NPs to a normal state indicating that alterations of transcription in PD-derived NPs were mainly caused by PARK2 mutations. Among genes significantly dysregulated in PD-derived NPs, 106 genes unambiguously restored their expression after reestablishing of the Parkin level. Based on the selected gene sets, we revealed the enriched Gene Ontology (GO) pathways including signaling, neurotransmitter transport and metabolism, response to stimulus, and apoptosis. Strikingly, dopamine receptor D4 that was previously associated with PD appears to be involved in the maximal number of GO-enriched pathways and therefore may be considered as a potential trigger of PD progression. Our findings may help in the screening for promising targets for PD treatment.

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

ApoE Modifier Alleles for Alzheimer's Disease Discovered by Information Theory Dependency Measures: MIST Software Package

Information theory-based measures of variable dependency (previously published) have been implemented into a software package, MIST. The design of the software and its potential uses are described, and a demonstration is presented in the discovery of modifier alleles of the ApoE gene in affecting Alzheimer's disease (AD) by analyzing the UK Biobank dataset. The modifier genes uncovered overlap strongly with genes found to be associated with AD. Others include many known to influence AD. We discuss a range of uses of the dependency calculations using MIST that can uncover additional genetic effects in similar complex datasets, like higher degrees of interaction and phenotypic pleiotropy.

Identification of TAC1 Associated with Alzheimer's Disease Using a Robust Rank Aggregation Approach

BACKGROUND

Alzheimer's disease (AD) brings heavy burden to society and family. There is an urgent need to find effective methods for disease diagnosis and treatment. The robust rank aggregation (RRA) approach that could aggregate the resulting gene lists has been widely utilized in genomic data analysis.

OBJECTIVE

To identify hub genes using RRA approach in AD.

METHODS

Seven microarray datasets in frontal cortex from GEO database were used to identify differential expressed genes (DEGs) in AD patients using RRA approach. STRING was performed to explore the protein-to-protein interaction (PPI). Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were utilized for enrichment analysis. Human Gene Connectome and Gene Set Enrichment Analysis were used for functional annotation. Finally, the expression levels of hub genes were validated in the cortex of 5xFAD mice by quantitative real-time polymerase chain reaction.

RESULTS

After RRA analysis, 473 DEGs (216 upregulated and 257 downregulated) were identified in AD samples. PPI showed that DEGs had a total of 416 nodes and 2750 edges. These genes were divided into 17 clusters, each of which contains at least three genes. After functional annotation and enrichment analysis, TAC1 is identified as the hub gene and may be related to synaptic function and inflammation. In addition, Tac1 was found downregulated in cortices of 5xFAD mice.

CONCLUSION

In the current study, TAC1 is identified as a key gene in the frontal cortex of AD, providing insight into the possible pathogenesis and potential therapeutic targets for this disease.

Bioinformatics investigation on blood-based gene expressions of Alzheimer's disease revealed ORAI2 gene biomarker susceptibility: An explainable artificial intelligence-based approach

The progressive, chronic nature of Alzheimer's disease (AD), a form of dementia, defaces the adulthood of elderly individuals. The pathogenesis of the condition is primarily unascertained, turning the treatment efficacy more arduous. Therefore, understanding the genetic etiology of AD is essential to identifying targeted therapeutics. This study aimed to use machine-learning techniques of expressed genes in patients with AD to identify potential biomarkers that can be used for future therapy. The dataset is accessed from the Gene Expression Omnibus (GEO) database (Accession Number: GSE36980). The subgroups (AD blood samples from frontal, hippocampal, and temporal regions) are individually investigated against non-AD models. Prioritized gene cluster analyses are conducted with the STRING database. The candidate gene biomarkers were trained with various supervised machine-learning (ML) classification algorithms. The interpretation of the model prediction is perpetrated with explainable artificial intelligence (AI) techniques. This experiment revealed 34, 60, and 28 genes as target biomarkers of AD mapped from the frontal, hippocampal, and temporal regions. It is identified ORAI2 as a shared biomarker in all three areas strongly associated with AD's progression. The pathway analysis showed that STIM1 and TRPC3 are strongly associated with ORAI2. We found three hub genes, TPI1, STIM1, and TRPC3, in the network of the ORAI2 gene that might be involved in the molecular pathogenesis of AD. Naive Bayes classified the samples of different groups by fivefold cross-validation with 100% accuracy. AI and ML are promising tools in identifying disease-associated genes that will advance the field of targeted therapeutics against genetic diseases.

Sex, Age, and Regional Differences in CHRM1 and CHRM3 Genes Expression Levels in the Human Brain Biopsies: Potential Targets for Alzheimer's Disease-related Sleep Disturbances

BACKGROUND

Cholinergic hypofunction and sleep disturbance are hallmarks of Alzheimer's disease (AD), a progressive disorder leading to neuronal deterioration. Muscarinic acetylcholine receptors (M1-5 or mAChRs), expressed in hippocampus and cerebral cortex, play a pivotal role in the aberrant alterations of cognitive processing, memory, and learning, observed in AD. Recent evidence shows that two mAChRs, M1 and M3, encoded by CHRM1 and CHRM3 genes, respectively, are involved in sleep functions and, peculiarly, in rapid eye movement (REM) sleep.

METHODS

We used twenty microarray datasets extrapolated from post-mortem brain tissue of nondemented healthy controls (NDHC) and AD patients to examine the expression profile of CHRM1 and CHRM3 genes. Samples were from eight brain regions and stratified according to age and sex.

RESULTS

CHRM1 and CHRM3 expression levels were significantly reduced in AD compared with ageand sex-matched NDHC brains. A negative correlation with age emerged for both CHRM1 and CHRM3 in NDHC but not in AD brains. Notably, a marked positive correlation was also revealed between the neurogranin (NRGN) and both CHRM1 and CHRM3 genes. These associations were modulated by sex. Accordingly, in the temporal and occipital regions of NDHC subjects, males expressed higher levels of CHRM1 and CHRM3, respectively, than females. In AD patients, males expressed higher levels of CHRM1 and CHRM3 in the temporal and frontal regions, respectively, than females.

CONCLUSION

Thus, substantial differences, all strictly linked to the brain region analyzed, age, and sex, exist in CHRM1 and CHRM3 brain levels both in NDHC subjects and in AD patients.

Tau Loss of Function, by Deletion or Aggregation, Contributes to Peripheral Insulin Resistance

BACKGROUND

Several epidemiological data revealed an association between Alzheimer's disease (AD) and type 2 diabetes. Researchers concentrated on brain insulin resistance with little emphasis on the link between systemic insulin resistance and AD, despite the fact that the incidence of type 2 diabetes is higher in AD patients and that impairment in insulin signaling is a risk factor for AD.

OBJECTIVE

The goal of this study is to determine the role of systemic insulin resistance in the pathogenesis of Alzheimer's disease by evaluating the consequences of tau loss-of-function on peripheral insulin sensitivity.

METHODS

Primary hepatocytes isolated from transgenic mouse models (Tau KO, P301 L) and wild type mice (C57BL/6) were evaluated for their insulin sensitivity using glucose uptake assays as well as biochemical analysis of insulin signaling markers.

RESULTS

Our data show that tau deletion or loss of function promotes peripheral insulin resistance as seen in primary hepatocytes isolated from Tau KO and P301 L mice, respectively. Furthermore, exposure of wild-type primary hepatocytes to sub-toxic concentrations of tau oligomers results in a dose-dependent inhibition of glucose uptake, associated with downregulation of insulin signaling. Tau oligomers-induced inactivation of insulin signaling proteins was rescued by inhibition of p38 MAPK, suggesting the involvement of p38 MAPK.

CONCLUSIONS

This is the first study testing tau role in peripheral insulin resistance at the cellular level using multiple transgenic mouse models. Moreover, this study suggests that tau should be functional for insulin sensitivity, therefore, any loss of function by deletion or aggregation would result in insulin resistance.

Changes of tRNA-Derived Fragments by Alzheimer's Disease in Cerebrospinal Fluid and Blood Serum

BACKGROUND

Alzheimer's disease (AD) is the most common type of dementia, affecting individuals over 65. AD is also a multifactorial disease, with disease mechanisms incompletely characterized, and disease-modifying therapies are marginally effective. Biomarker signatures may shed light on the diagnosis, disease mechanisms, and the development of therapeutic targets. tRNA-derived RNA fragments (tRFs), a family of recently discovered small non-coding RNAs, have been found to be significantly enhanced in human AD hippocampus tissues. However, whether tRFs change in body fluids is unknown.

OBJECTIVE

To investigate whether tRFs in body fluids are impacted by AD.

METHODS

We first used T4 polynucleotide kinase-RNA-seq, a modified next-generation sequencing technique, to identify detectable tRFs in human cerebrospinal fluid and serum samples. The detectable tRFs were then compared in these fluids from control, AD, and mild cognitive impairment patients using tRF qRT-PCR. The stability of tRFs in serum was also investigated by checking the change in tRFs in response to protein digestion or exosome lysis.

RESULTS

Among various tRFs, tRF5-ProAGG seemed to be impacted by AD in both cerebrospinal fluid and serum. AD-impacted serum tRF5-ProAGG showed a correlation with the AD stage. Putative targets of tRF5-ProAGG in the hippocampus were also predicted by a computational algorithm, with some targets being validated experimentally and one of them being in a negative correlation with tRF5-ProAGG even using a small size of samples.

CONCLUSIONS

tRF5-ProAGG showed the potential as an AD biomarker and may play a role in disease progression.

Artificial intelligence-driven meta-analysis of brain gene expression identifies novel gene candidates and a role for mitochondria in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia. There is no treatment and AD models have focused on a small subset of genes identified in familial AD. Microarray studies have identified thousands of dysregulated genes in the brains of patients with AD yet identifying the best gene candidates to both model and treat AD remains a challenge. We performed a meta-analysis of microarray data from the frontal cortex (n = 697) and cerebellum (n = 230) of AD patients and healthy controls. A two-stage artificial intelligence approach, with both unsupervised and supervised machine learning, combined with a functional network analysis was used to identify functionally connected and biologically relevant novel gene candidates in AD. We found that in the frontal cortex, genes involved in mitochondrial energy, ATP, and oxidative phosphorylation, were the most significant dysregulated genes. In the cerebellum, dysregulated genes were involved in mitochondrial cellular biosynthesis (mitochondrial ribosomes). Although there was little overlap between dysregulated genes between the frontal cortex and cerebellum, machine learning models comprised of this overlap. A further functional network analysis of these genes identified that two downregulated genes, ATP5L and ATP5H, which both encode subunits of ATP synthase (mitochondrial complex V) may play a role in AD. Combined, our results suggest that mitochondrial dysfunction, particularly a deficit in energy homeostasis, may play an important role in AD.

Hallmarks of neurodegenerative disease: A systems pharmacology perspective

Age-related central neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are a rising public health concern and have been plagued by repeated drug development failures. The complex nature and poor mechanistic understanding of the etiology of neurodegenerative diseases has hindered the discovery and development of effective disease-modifying therapeutics. Quantitative systems pharmacology models of neurodegeneration diseases may be useful tools to enhance the understanding of pharmacological intervention strategies and to reduce drug attrition rates. Due to the similarities in pathophysiological mechanisms across neurodegenerative diseases, especially at the cellular and molecular levels, we envision the possibility of structural components that are conserved across models of neurodegenerative diseases. Conserved structural submodels can be viewed as building blocks that are pieced together alongside unique disease components to construct quantitative systems pharmacology (QSP) models of neurodegenerative diseases. Model parameterization would likely be different between the different types of neurodegenerative diseases as well as individual patients. Formulating our mechanistic understanding of neurodegenerative pathophysiology as a mathematical model could aid in the identification and prioritization of drug targets and combinatorial treatment strategies, evaluate the role of patient characteristics on disease progression and therapeutic response, and serve as a central repository of knowledge. Here, we provide a background on neurodegenerative diseases, highlight hallmarks of neurodegeneration, and summarize previous QSP models of neurodegenerative diseases.

The three-dimensional landscape of cortical chromatin accessibility in Alzheimer's disease

To characterize the dysregulation of chromatin accessibility in Alzheimer's disease (AD), we generated 636 ATAC-seq libraries from neuronal and nonneuronal nuclei isolated from the superior temporal gyrus and entorhinal cortex of 153 AD cases and 56 controls. By analyzing a total of ~20 billion read pairs, we expanded the repertoire of known open chromatin regions (OCRs) in the human brain and identified cell-type-specific enhancer-promoter interactions. We show that interindividual variability in OCRs can be leveraged to identify cis-regulatory domains (CRDs) that capture the three-dimensional structure of the genome (3D genome). We identified AD-associated effects on chromatin accessibility, the 3D genome and transcription factor (TF) regulatory networks. For one of the most AD-perturbed TFs, USF2, we validated its regulatory effect on lysosomal genes. Overall, we applied a systematic approach to understanding the role of the 3D genome in AD. We provide all data as an online resource for widespread community-based analysis.

An in-silico approach to studying a very rare neurodegenerative disease using a disease with higher prevalence with shared pathways and genes: Cerebral adrenoleukodystrophy and Alzheimer’s disease

Cerebral adrenoleukodystrophy (cALD) is a rare neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Another neurodegenerative disease with a high prevalence, Alzheimer’s disease (AD), shares many common features with cALD such as cognitive impairment and the alleviation of symptoms by erucic acid. We investigated cALD and AD in parallel to study the shared pathological pathways between a rare disease and a more common disease. The approach may expand the biological understandings and reveal novel therapeutic targets. Gene set enrichment analysis (GSEA) and weighted gene correlation network analysis (WGCNA) were conducted to identify both the resemblance in gene expression patterns and genes that are pathologically relevant in the two diseases. Within differentially expressed genes (DEGs), GSEA identified 266 common genes with similar up- or down-regulation patterns in cALD and AD. Among the interconnected genes in AD data, two gene sets containing 1,486 genes preserved in cALD data were selected by WGCNA that may significantly affect the development and progression of cALD. WGCNA results filtered by functional correlation via protein–protein interaction analysis overlapping with GSEA revealed four genes (annexin A5, beta-2-microglobulin, CD44 molecule, and fibroblast growth factor 2) that showed robust associations with the pathogeneses of cALD and AD, where they were highly involved in inflammation, apoptosis, and the mitogen-activated protein kinase pathway. This study provided an integrated strategy to provide new insights into a rare disease with scant publicly available data (cALD) using a more prevalent disorder with some pathological association (AD), which suggests novel druggable targets and drug candidates.

Oxidative Stress Kinase Activation and Impaired Insulin Receptor Signaling Precede Overt Alzheimer’s Disease Neuropathology

Background: The cascade of events that lead to Alzheimer’s disease (AD) consists of several possible underlying signal transduction pathways. Apoptosis signal-regulating kinase 1 (ASK1) and insulin receptor (IR) signaling are implicated in AD. Objective: We aimed to determine whether ASK1 activation and IR signaling impairment occurred prior to and during overt AD. Methods: Immunostaining, immunoblotting, and quantitative PCR were used to assess the levels of ASK1 and IR signaling intermediates. Glucose uptake was determined in AD-patient derived inducible pluripotent stem cells (iPSCs). Results: ASK1 signaling was activated in postmortem brain tissues acquired from APOE4 carriers, a causative heritable factor, and in brain tissues of AD subjects in comparison with those harboring the normal APOE3 variant, which was manifested with an increased phosphorylated ASK1 (p-ASK1) and reduced thioredoxin 1 (TRX1). ASK1 downstream signaling effectors were also significantly elevated in these APOE4 carriers and AD brain tissues. Increased insulin receptor substrate 1 (IRS1) phosphorylation at serine residues, and decreased p-AKT1, p-IRβ, and GLUT3 expression were present in all APOE4 carriers and AD samples, suggesting impaired IR signaling leading to insulin resistance. ASK1 activation, IR signaling impairment, and GLUT3 reduction were also present in young AD transgenic mice prior to AD syndromes, AD mice at AD neuropathology onset, and AD iPSCs and their derived neurons prior to p-Tau aggregation. Conclusion: We conclude that the activation of oxidative stress-responsive kinases and reduced IR signaling precede and are persistent in AD pathogenesis. Our data further suggest possible crosstalk between ASK1 signaling and insulin resistance in AD etiology.

Identification of a 6-RBP gene signature for a comprehensive analysis of glioma and ischemic stroke: Cognitive impairment and aging-related hypoxic stress

There is mounting evidence that ischemic cerebral infarction contributes to vascular cognitive impairment and dementia in elderly. Ischemic stroke and glioma are two majorly fatal diseases worldwide, which promote each other's development based on some common underlying mechanisms. As a post-transcriptional regulatory protein, RNA-binding protein is important in the development of a tumor and ischemic stroke (IS). The purpose of this study was to search for a group of RNA-binding protein (RBP) gene markers related to the prognosis of glioma and the occurrence of IS, and elucidate their underlying mechanisms in glioma and IS. First, a 6-RBP (POLR2F, DYNC1H1, SMAD9, TRIM21, BRCA1, and ERI1) gene signature (RBPS) showing an independent overall survival prognostic prediction was identified using the transcriptome data from TCGA-glioma cohort (n = 677); following which, it was independently verified in the CGGA-glioma cohort (n = 970). A nomogram, including RBPS, 1p19q codeletion, radiotherapy, chemotherapy, grade, and age, was established to predict the overall survival of patients with glioma, convenient for further clinical transformation. In addition, an automatic machine learning classification model based on radiomics features from MRI was developed to stratify according to the RBPS risk. The RBPS was associated with immunosuppression, energy metabolism, and tumor growth of gliomas. Subsequently, the six RBP genes from blood samples showed good classification performance for IS diagnosis (AUC = 0.95, 95% CI: 0.902–0.997). The RBPS was associated with hypoxic responses, angiogenesis, and increased coagulation in IS. Upregulation of SMAD9 was associated with dementia, while downregulation of POLR2F was associated with aging-related hypoxic stress. Irf5/Trim21 in microglia and Taf7/Trim21 in pericytes from the mouse cerebral cortex were identified as RBPS-related molecules in each cell type under hypoxic conditions. The RBPS is expected to serve as a novel biomarker for studying the common mechanisms underlying glioma and IS.

Dysfunctional Glucose Metabolism in Alzheimer’s Disease Onset and Potential Pharmacological Interventions

Alzheimer’s disease (AD) is the most common age-related dementia. The alteration in metabolic characteristics determines the prognosis. Patients at risk show reduced glucose uptake in the brain. Additionally, type 2 diabetes mellitus increases the risk of AD with increasing age. Therefore, changes in glucose uptake in the cerebral cortex may predict the histopathological diagnosis of AD. The shifts in glucose uptake and metabolism, insulin resistance, oxidative stress, and abnormal autophagy advance the pathogenesis of AD syndrome. Here, we summarize the role of altered glucose metabolism in type 2 diabetes for AD prognosis. Additionally, we discuss diagnosis and potential pharmacological interventions for glucose metabolism defects in AD to encourage the development of novel therapeutic methods.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

The role of H3K9 acetylation and gene expression in different brain regions of Alzheimer's disease patients

Aims: To evaluate H3K9 acetylation and gene expression profiles in three brain regions of Alzheimer's disease (AD) patients and elderly controls, and to identify AD region-specific abnormalities. Methods: Brain samples of auditory cortex, hippocampus and cerebellum from AD patients and controls underwent chromatin immunoprecipitation sequencing, RNA sequencing and network analyses. Results: We found a hyperacetylation of AD cerebellum and a slight hypoacetylation of AD hippocampus. The transcriptome revealed differentially expressed genes in the hippocampus and auditory cortex. Network analysis revealed Rho GTPase-mediated mechanisms. Conclusions: These findings suggest that some crucial mechanisms, such as Rho GTPase activity and cytoskeletal organization, are differentially dysregulated in brain regions of AD patients at the epigenetic and transcriptomic levels, and might contribute toward future research on AD pathogenesis.

Transcriptional Profiling of Hippocampus Identifies Network Alterations in Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by rapid brain cell degeneration affecting different areas of the brain. Hippocampus is one of the earliest involved brain regions in the disease. Modern technologies based on high-throughput data have identified transcriptional profiling of several neurological diseases, including AD, for a better comprehension of genetic mechanisms of the disease. In this study, we investigated differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets of hippocampus of AD patients. The identified DEGs were submitted to Weighted correlation network analysis (WGCNA) and ClueGo to explore genes with a higher degree centrality and to comprehend their biological role. Subsequently, MCODE was used to identify subnetworks of interconnected DEGs. Our study found 40 down-regulated genes and 36 up-regulated genes as consensus DEGs. Analysis of the co-expression network revealed ACOT7, ATP8A2, CDC42, GAD1, GOT1, INA, NCALD, and WWTR1 to be genes with a higher degree centrality. ClueGO revealed the pathways that were mainly enriched, such as clathrin coat assembly, synaptic vesicle endocytosis, and DNA damage response signal transduction by p53 class mediator. In addition, we found a subnetwork of 12 interconnected genes (AMPH, CA10, CALY, NEFL, SNAP25, SNAP91, SNCB, STMN2, SV2B, SYN2, SYT1, and SYT13). Only CA10 and CALY are targets of known drugs while the others could be potential novel drug targets.

Improved cognitive impairments by silencing DMP1 via enhancing the proliferation of neural progenitor cell in Alzheimer-like mice

Alzheimer's disease (AD) is age-related progressive neurological dysfunction. Limited clinical benefits for current treatments indicate an urgent need for novel therapeutic strategies. Previous transcriptomic analysis showed that DMP1 expression level was increased in AD model animals whereas it can induce cell-cycle arrest in several cell lines. However, whether the cell-cycle arrest of neural progenitor cell induced by DMP1 affects cognitive function in Alzheimer-like mice still remains unknown. The objective of our study is to explore the issue. We found that DMP1 is correlated with cognitive function based on the clinical genomic analysis of ADNI database. The negative role of DMP1 on neural progenitor cell (NPC) proliferation was revealed by silencing and overexpressing DMP1 in vitro. Furthermore, silencing DMP1 could increase the number of NPCs and improve cognitive function in Alzheimer-like mice, through decreasing P53 and P21 levels, which suggested that DMP1-induced cell-cycle arrest could influence cognitive function.

Stress-Induced Depression and Alzheimer's Disease: Focus on Astrocytes

Neurodegenerative diseases and depression are multifactorial disorders with a complex and poorly understood physiopathology. Astrocytes play a key role in the functioning of neurons in norm and pathology. Stress is an important factor for the development of brain disorders. Here, we review data on the effects of stress on astrocyte function and evidence of the involvement of astrocyte dysfunction in depression and Alzheimer's disease (AD). Stressful life events are an important risk factor for depression; meanwhile, depression is an important risk factor for AD. Clinical data indicate atrophic changes in the same areas of the brain, the hippocampus and prefrontal cortex (PFC), in both pathologies. These brain regions play a key role in regulating the stress response and are most vulnerable to the action of glucocorticoids. PFC astrocytes are critically involved in the development of depression. Stress alters astrocyte function and can result in pyroptotic death of not only neurons, but also astrocytes. BDNF-TrkB system not only plays a key role in depression and in normalizing the stress response, but also appears to be an important factor in the functioning of astrocytes. Astrocytes, being a target for stress and glucocorticoids, are a promising target for the treatment of stress-dependent depression and AD.

AGE-TXNIP axis drives inflammation in Alzheimer's by targeting Aβ to mitochondria in microglia

Alzheimer's disease (AD) is the most common form of dementia characterized by progressive memory loss and cognitive decline. Although neuroinflammation and oxidative stress are well-recognized features of AD, their correlations with the early molecular events characterizing the pathology are not yet well clarified. Here, we characterize the role of RAGE-TXNIP axis in neuroinflammation in relation to amyloid-beta (Aβ) burden in both in vivo and in vitro models. In the hippocampus of 5xFAD mice microglial activation, cytokine secretion, and glial fibrillary acidic protein-enhanced expression are paralleled with increased TXNIP expression. TXNIP silencing or its pharmacological inhibition prevents neuroinflammation in those mice. TXNIP is also associated with RAGE and Aβ. In particular, RAGE-TXNIP axis is required for targeting Aβ in mitochondria, leading to mitochondrial dysfunction and oxidative stress. Silencing of TXNIP or inhibition of RAGE activation reduces Aβ transport from the cellular surface to mitochondria, restores mitochondrial functionality, and mitigates Aβ toxicity. Furthermore, Aβ shuttling into mitochondria promotes Drp1 activation and exacerbates mitochondrial dysfunction, which induces NLRP3 inflammasome activation, leading to secretion of IL-1β and activation of the pyroptosis-associated protein Gasdermin D (GSDMD). Downregulation of RAGE-TXNIP axis inhibits Aβ-induced mitochondria dysfunction, inflammation, and induction of GSDMD. Herein we unveil a new pathway driven by TXNIP that links the mitochondrial transport of Aβ to the activation of Drp1 and the NLRP3 inflammasome, promoting the secretion of IL-1β and the pyroptosis pathway associated with GSDMD cleavage. Altogether these data shed new light on a novel mechanism of action of RAGE-TXNIP axis in microglia, which is intertwined with Aβ and ultimately causes mitochondria dysfunction and NLRP3 inflammasome cascade activation, suggesting TXNIP as a druggable target to be better deepened for AD.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.

Promoter Hypomethylation of TGFBR3 as a Risk Factor of Alzheimer’s Disease: An Integrated Epigenomic-Transcriptomic Analysis

Alzheimer’s disease (AD) is characterized by the abnormal deposition of amyloid-β (Aβ) plaques and tau tangles in the brain and accompanied with cognitive impairment. However, the fundamental cause of this disease remains elusive. To elucidate the molecular processes related to AD, we carried out an integrated analysis utilizing gene expression microarrays (GSE36980 and GSE5281) and DNA methylation microarray (GSE66351) in temporal cortex of AD patients from the Gene Expression Omnibus (GEO) database. We totally discovered 409 aberrantly methylated and differentially expressed genes. These dysregulated genes were significantly enriched in biological processes including cell part morphogenesis, chemical synaptic transmission and regulation of Aβ formation. Through convergent functional genomic (CFG) analysis, expression cross-validation and clinicopathological correlation analysis, higher TGFBR3 level was observed in AD and positively correlated with Aβ accumulation. Meanwhile, the promoter methylation level of TGFBR3 was reduced in AD and negatively associated with Aβ level and advanced Braak stage. Mechanically, TGFBR3 might promote Aβ production by enhancing β- and γ-secretase activities. Further investigation revealed that TGFBR3 may exert its functions via Synaptic vesicle cycle, Calcium signaling pathway and MAPK signal pathway by regulating hub genes GNB1, GNG3, CDC5L, DYNC1H1 and FBXW7. Overall, our findings highlighted TGFBR3 as an AD risk gene and might be used as a diagnostic biomarker and therapeutic target for AD treatment.

Detection of molecular signatures and pathways shared by Alzheimer's disease and type 2 diabetes

Alzheimer's disease (AD) and type 2 diabetes (T2D) are common in the general elderly population, conferring heavy individual, social, and economic stresses on families and society. Accumulating evidence indicates T2D to be a risk factor for AD. However, the underlying mechanisms for this association are largely unknown. This study aimed to identify the shared molecular signatures between AD and T2D through integrated analysis of temporal cortex gene expression data. Gene Ontology (GO) and pathway enrichment analysis, protein over-representation analysis, protein-protein interaction, DEG-transcription factor interactions, DEG-microRNA interactions, protein-drug interactions, gene-disease association analysis, and protein subcellular localization analysis of the common DEGs were performed. We identified 16 common DEGs between the two datasets, which were mainly enriched in the biological processes of apoptosis, autophagy, inflammation, and hemostasis. We also identified five hub proteins encoded by the DEGs, five central regulatory transcription factors, and six microRNAs. Protein-drug interaction analysis showed C1QB to be associated with different drugs. Gene-disease association analysis revealed that hub genes, SFN and ITGB2, were actively engaged in other diseases. Collectively, these findings provide new insights into shared molecular mechanisms between AD and T2D and provide novel candidate targets for therapeutic intervention.

Mechanisms underlying the pathophysiology of type 2 diabetes: From risk factors to oxidative stress, metabolic dysfunction, and hyperglycemia

Type 2 diabetes (T2D) is a complex multifactorial disease that emerges from the combination of genetic and environmental factors, and obesity, lifestyle, and aging are the most relevant risk factors. Hyperglycemia is the main metabolic feature of T2D as a consequence of insulin resistance and β-cell dysfunction. Among the cellular alterations induced by hyperglycemia, the overproduction of reactive oxygen species (ROS) and consequently oxidative stress, accompanied by a reduced antioxidant response and impaired DNA repair pathways, represent essential mechanisms underlying the pathophysiology of T2D and the development of late complications. Mitochondrial dysfunction, endoplasmic reticulum (ER) stress, and inflammation are also closely correlated with insulin resistance and β-cell dysfunction. This review focus on the mechanisms by which oxidative stress, mitochondrial dysfunction, ER stress, and inflammation are involved in the pathophysiology of T2D, highlighting the importance of the antioxidant response and DNA repair mechanisms counteracting the development of the disease. Moreover, we indicate evidence on how nutritional interventions effectively improve diabetes care. Additionally, we address key molecular characteristics and signaling pathways shared between T2D and Alzheimer's disease (AD), which might probably be implicated in the risk of T2D patients to develop AD.

Metabolic Features of Brain Function with Relevance to Clinical Features of Alzheimer and Parkinson Diseases

Brain metabolism is comprised in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Since the brain primarily relies on metabolism of glucose, ketone bodies, and amino acids, aspects of these metabolic processes in these disorders—and particularly how these altered metabolic processes are related to oxidative and/or nitrosative stress and the resulting damaged targets—are reviewed in this paper. Greater understanding of the decreased functions in brain metabolism in AD and PD is posited to lead to potentially important therapeutic strategies to address both of these disorders, which cause relatively long-lasting decreased quality of life in patients.

Applied machine learning in Alzheimer's disease research: omics, imaging, and clinical data

Alzheimer's disease (AD) remains a devastating neurodegenerative disease with few preventive or curative treatments available. Modern technology developments of high-throughput omics platforms and imaging equipment provide unprecedented opportunities to study the etiology and progression of this disease. Meanwhile, the vast amount of data from various modalities, such as genetics, proteomics, transcriptomics, and imaging, as well as clinical features impose great challenges in data integration and analysis. Machine learning (ML) methods offer novel techniques to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers. These directions have the potential to help us better manage the disease progression and develop novel treatment strategies. This mini-review paper summarizes different ML methods that have been applied to study AD using single-platform or multi-modal data. We review the current state of ML applications for five key directions of AD research: disease classification, drug repurposing, subtyping, progression prediction, and biomarker discovery. This summary provides insights about the current research status of ML-based AD research and highlights potential directions for future research.

MUTYH Actively Contributes to Microglial Activation and Impaired Neurogenesis in the Pathogenesis of Alzheimer's Disease

Oxidative stress is a major risk factor for Alzheimer's disease (AD), which is characterized by brain atrophy, amyloid plaques, neurofibrillary tangles, and loss of neurons. 8-Oxoguanine, a major oxidatively generated nucleobase highly accumulated in the AD brain, is known to cause neurodegeneration. In mammalian cells, several enzymes play essential roles in minimizing the 8-oxoguanine accumulation in DNA. MUTYH with adenine DNA glycosylase activity excises adenine inserted opposite 8-oxoguanine in DNA. MUTYH is reported to actively contribute to the neurodegenerative process in Parkinson and Huntington diseases and some mouse models of neurodegenerative diseases by accelerating neuronal dysfunction and microgliosis under oxidative conditions; however, whether or not MUTYH is involved in AD pathogenesis remains unclear. In the present study, we examined the contribution of MUTYH to the AD pathogenesis. Using postmortem human brains, we showed that various types of MUTYH transcripts and proteins are expressed in most hippocampal neurons and glia in both non-AD and AD brains. We further introduced MUTYH deficiency into App ^{NL-G-F/NL-G-F} knock-in AD model mice, which produce humanized toxic amyloid-β without the overexpression of APP protein, and investigated the effects of MUTYH deficiency on the behavior, pathology, gene expression, and neurogenesis. MUTYH deficiency improved memory impairment in App ^{NL-G-F/NL-G-F} mice, accompanied by reduced microgliosis. Gene expression profiling strongly suggested that MUTYH is involved in the microglial response pathways under AD pathology and contributes to the phagocytic activity of disease-associated microglia. We also found that MUTYH deficiency ameliorates impaired neurogenesis in the hippocampus, thus improving memory impairment. In conclusion, we propose that MUTYH, which is expressed in the hippocampus of AD patients as well as non-AD subjects, actively contributes to memory impairment by inducing microgliosis with poor neurogenesis in the preclinical AD phase and that MUTYH is a novel therapeutic target for AD, as its deficiency is highly beneficial for ameliorating AD pathogenesis.

Putative Factors Interfering Cell Cycle Re-Entry in Alzheimer's Disease: An Omics Study with Differential Expression Meta-Analytics and Co-Expression Profiling

BACKGROUND

Neuronal cell cycle re-entry (CCR) is a mechanism, along with amyloid-β (Aβ) oligomers and hyperphosphorylated tau proteins, contributing to toxicity in Alzheimer's disease (AD).

OBJECTIVE

This study aimed to examine the putative factors in CCR based on evidence corroboration by combining meta-analysis and co-expression analysis of omic data.

METHODS

The differentially expressed genes (DEGs) and CCR-related modules were obtained through the differential analysis and co-expression of transcriptomic data, respectively. Differentially expressed microRNAs (DEmiRNAs) were extracted from the differential miRNA expression studies. The dysregulations of DEGs and DEmiRNAs as binary outcomes were independently analyzed by meta-analysis based on a random-effects model. The CCR-related modules were mapped to human protein-protein interaction databases to construct a network. The importance score of each node within the network was determined by the PageRank algorithm, and nodes that fit the pre-defined criteria were treated as putative CCR-related factors.

RESULTS

The meta-analysis identified 18,261 DEGs and 36 DEmiRNAs, including genes in the ubiquitination proteasome system, mitochondrial homeostasis, and CCR, and miRNAs associated with AD pathologies. The co-expression analysis identified 156 CCR-related modules to construct a protein-protein interaction network. Five genes, UBC, ESR1, EGFR, CUL3, and KRAS, were selected as putative CCR-related factors. Their functions suggested that the combined effects of cellular dyshomeostasis and receptors mediating Aβ toxicity from impaired ubiquitination proteasome system are involved in CCR.

CONCLUSION

This study identified five genes as putative factors and revealed the significance of cellular dyshomeostasis in the CCR of AD.

Aconiti lateralis Radix Praeparata inhibits Alzheimer's disease by regulating the complex regulation network with the core of GRIN1 and MAPK1

CONTEXT

Current medicine for Alzheimer's disease (AD) cannot effectively reverse or block nerve injury. Traditional Chinese Medicine practice and research imply Aconiti lateralis Radix Praeparata (Fuzi) may meet this goal.

OBJECTIVE

Analysing the anti-AD effect of Fuzi and its potential molecular mechanism.

MATERIALS AND METHODS

AD model cells were treated with Fuzi in 0-300 mg/mL for 24 h in 37 °C. The cell viability (CV) and length of cell projections (LCP) for each group were observed, analysed, and standardised using control as a baseline (CV_s and LCP_s). The Fuzi and AD relevant genes were identified basing on databases, and the molecular mechanism of Fuzi anti-AD was predicted by network analysis.

RESULTS

Experiment results showed that Fuzi in 0.4 mg/mL boosted LCP (LCP_s = 1.2533, p ≤ 0.05), and in 1.6-100 mg/mL increased CV (CV_s from 1.1673 to 1.3321, p ≤ 0.05). Bioinformatics analysis found 17 Fuzi target genes (relevant scores ≥ 20), showing strong AD relevant signals (RMS_p ≤ 0.05, related scores ≥ 5), enriched in the pathways regulating axon growth, synaptic plasticity, cell survival, proliferation, apoptosis, and death (p ≤ 0.05). Especially, GRIN1 and MAPK1 interacted with APP protein and located in the key point of the "Alzheimer's disease" pathway.

DISCUSSION AND CONCLUSIONS

These results suggest that Fuzi may have therapeutic and prevention potential in AD, and GRIN1 and MAPK1 may be the core of the pathways of the Fuzi anti-AD process. Fuzi should be studied more extensively, especially for the prevention of AD.

Differential analysis of binarized single-cell RNA sequencing data captures biological variation

Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological variation rather than technical artifacts. We propose to use binarized expression profiles to identify the effects of biological variation in single-cell RNA sequencing data. Using 16 publicly available and simulated datasets, we show that a binarized representation of single-cell expression data accurately represents biological variation and reveals the relative abundance of transcripts more robustly than counts.

The Emerging Role of Metabolism in Brain-Heart Axis: New Challenge for the Therapy and Prevention of Alzheimer Disease. May Thioredoxin Interacting Protein (TXNIP) Play a Role?

Alzheimer disease (AD) is the most frequent cause of dementia and up to now there is not an effective therapy to cure AD. In addition, AD onset occurs decades before the diagnosis, affecting the possibility to set up appropriate therapeutic strategies. For this reason, it is necessary to investigate the effects of risk factors, such as cardiovascular diseases, in promoting AD. AD shows not only brain dysfunction, but also alterations in peripheral tissues/organs. Indeed, it exists a reciprocal connection between brain and heart, where cardiovascular alterations participate to AD as well as AD seem to promote cardiovascular dysfunction. In addition, metabolic dysfunction promotes both cardiovascular diseases and AD. In this review, we summarize the pathways involved in the regulation of the brain-heart axis and the effect of metabolism on these pathways. We also present the studies showing the role of the gut microbiota on the brain-heart axis. Herein, we propose recent evidences of the function of Thioredoxin Interacting protein (TXNIP) in mediating the role of metabolism on the brain-heart axis. TXNIP is a key regulator of metabolism at both cellular and body level and it exerts also a pathological function in several cardiovascular diseases as well as in AD.