Incipient Alzheimer's disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses

Unlocking hope: GSK-3 inhibitors and Wnt pathway activation in Alzheimer's therapy

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterised by progressive cognitive decline and the accumulation of amyloid-β plaques and tau tangles. The Wnt signalling pathway known for its crucial role in neurodevelopment and adult neurogenesis has emerged as a potential target for therapeutic intervention in AD. Glycogen synthase kinase-3 beta (GSK-3β), a key regulator of the Wnt pathway, plays a pivotal role in AD pathogenesis by promoting tau hyperphosphorylation and neuroinflammation. Several preclinical studies have demonstrated that inhibiting GSK-3β leads to the activation of Wnt pathway thereby promoting neuroprotective effects, and mitigating cognitive deficits in AD animal models. The modulation of Wnt signalling appears to have multifaceted benefits including the reduction of amyloid-β production, tau hyperphosphorylation, enhancement of synaptic plasticity, and inhibition of neuroinflammation. These findings suggest that targeting GSK-3β to activate Wnt pathway may represent a novel approach for slowing or halting the progression of AD. This hypothesis reviews the current state of research exploring the activation of Wnt pathway through the inhibition of GSK-3β as a promising therapeutic strategy in AD.

An integrated approach to identifying sex-specific genes, transcription factors, and pathways relevant to Alzheimer's disease

BACKGROUND

Age represents a significant risk factor for the development of Alzheimer's disease (AD); however, recent research has documented an influencing role of sex in several features of AD. Understanding the impact of sex on specific molecular mechanisms associated with AD remains a critical challenge to creating tailored therapeutic interventions.

METHODS

The exploration of the sex-based differential impact on disease (SDID) in AD used a systematic review to first select transcriptomic studies of AD with data regarding sex in the period covering 2002 to 2021 with a focus on the primary brain regions affected by AD - the cortex (CT) and the hippocampus (HP). A differential expression analysis for each study and two tissue-specific meta-analyses were then performed. Focusing on the CT due to the presence of significant SDID-related alterations, a comprehensive functional characterization was conducted: protein-protein network interaction and over-representation analyses to explore biological processes and pathways and a VIPER analysis to estimate transcription factor activity.

RESULTS

We selected 8 CT and 5 HP studies from the Gene Expression Omnibus (GEO) repository for tissue-specific meta-analyses. We detected 389 significantly altered genes in the SDID comparison in the CT. Generally, female AD patients displayed more affected genes than males; we grouped said genes into six subsets according to their expression profile in female and male AD patients. Only subset I (repressed genes in female AD patients) displayed significant results during functional profiling. Female AD patients demonstrated more significant impairments in biological processes related to the regulation and organization of synapsis and pathways linked to neurotransmitters (glutamate and GABA) and protein folding, Aβ aggregation, and accumulation compared to male AD patients. These findings could partly explain why we observe more pronounced cognitive decline in female AD patients. Finally, we detected 23 transcription factors with different activation patterns according to sex, with some associated with AD for the first time. All results generated during this study are readily available through an open web resource Metafun-AD (https://bioinfo.cipf.es/metafun-ad/).

CONCLUSION

Our meta-analyses indicate the existence of differences in AD-related mechanisms in female and male patients. These sex-based differences will represent the basis for new hypotheses and could significantly impact precision medicine and improve diagnosis and clinical outcomes in AD patients.

Regulation of cell distancing in peri-plaque glial nets by Plexin-B1 affects glial activation and amyloid compaction in Alzheimer's disease

Communication between glial cells has a profound impact on the pathophysiology of Alzheimer's disease (AD). We reveal here that reactive astrocytes control cell distancing in peri-plaque glial nets, which restricts microglial access to amyloid deposits. This process is governed by guidance receptor Plexin-B1 (PLXNB1), a network hub gene in individuals with late-onset AD that is upregulated in plaque-associated astrocytes. Plexin-B1 deletion in a mouse AD model led to reduced number of reactive astrocytes and microglia in peri-plaque glial nets, but higher coverage of plaques by glial processes, along with transcriptional changes signifying reduced neuroinflammation. Additionally, a reduced footprint of glial nets was associated with overall lower plaque burden, a shift toward dense-core-type plaques and reduced neuritic dystrophy. Altogether, our study demonstrates that Plexin-B1 regulates peri-plaque glial net activation in AD. Relaxing glial spacing by targeting guidance receptors may present an alternative strategy to increase plaque compaction and reduce neuroinflammation in AD.

KRIT1 in vascular biology and beyond

KRIT1 is a 75 kDa scaffolding protein which regulates endothelial cell phenotype by limiting the response to inflammatory stimuli and maintaining a quiescent and stable endothelial barrier. Loss-of-function mutations in KRIT1 lead to the development of cerebral cavernous malformations (CCM), a disease marked by the formation of abnormal blood vessels which exhibit a loss of barrier function, increased endothelial proliferation, and altered gene expression. While many advances have been made in our understanding of how KRIT1, and the functionally related proteins CCM2 and PDCD10, contribute to the regulation of blood vessels and the vascular barrier, some important open questions remain. In addition, KRIT1 is widely expressed and KRIT1 and the other CCM proteins have been shown to play important roles in non-endothelial cell types and tissues, which may or may not be related to their role as pathogenic originators of CCM. In this review, we discuss some of the unsettled questions regarding the role of KRIT1 in vascular physiology and discuss recent advances that suggest this ubiquitously expressed protein may have a role beyond the endothelial cell.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

Pin1-catalyzed conformational regulation after phosphorylation: A distinct checkpoint in cell signaling and drug discovery

Protein phosphorylation is one of the most common mechanisms regulating cellular signaling pathways, and many kinases and phosphatases are proven drug targets. Upon phosphorylation, protein functions can be further regulated by the distinct isomerase Pin1 through cis-trans isomerization. Numerous protein targets and many important roles have now been elucidated for Pin1. However, no tools are available to detect or target cis and trans conformation events in cells. The development of Pin1 inhibitors and stereo- and phospho-specific antibodies has revealed that cis and trans conformations have distinct and often opposing cellular functions. Aberrant conformational changes due to the dysregulation of Pin1 can drive pathogenesis but can be effectively targeted in age-related diseases, including cancers and neurodegenerative disorders. Here, we review advances in understanding the roles of Pin1 signaling in health and disease and highlight conformational regulation as a distinct signal transduction checkpoint in disease development and treatment.

SCG5 and MITF may be novel markers of copper metabolism immunorelevance in Alzheimer's disease

The slow-developing neurological disorder Alzheimer's disease (AD) has no recognized etiology. A bioinformatics investigation verified copper metabolism indicators for AD development. GEO contributed AD-related datasets GSE1297 and GSE5281. Differential expression analysis and WGCNA confirmed biomarker candidate genes. Each immune cell type in AD and control samples was scored using single sample gene set enrichment analysis. Receiver Operating Characteristic (ROC) analysis, short Time-series Expression Miner (STEM) grouping, and expression analysis between control and AD samples discovered copper metabolism indicators that impacted AD progression. We test clinical samples and cellular function to ensure study correctness. Biomarker-targeting miRNAs and lncRNAs were predicted by starBase. Trust website anticipated biomarker-targeting transcription factors. In the end, Cytoscape constructed the TF/miRNA-mRNA and lncRNA-miRNA networks. The DGIdb database predicted biomarker-targeted drugs. We identified 57 differentially expressed copper metabolism-related genes (DE-CMRGs). Next, fourteen copper metabolism indicators impacting AD progression were identified: CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38. A TF/miRNA-mRNA regulation network was then established with two miRNAs (hsa-miR-34a-5p and 34c-5p), six TFs (NFKB1, RELA, MYC, HIF1A, JUN, and SP1), and four biomarkers. The DGIdb database contained 171 drugs targeting ten copper metabolism-relevant biomarkers (BRCA1, MITF, NFKBIA, CD38, CCK2, HPRT1, SPHK1, LDHA, SCG5, and SYT1). Copper metabolism biomarkers CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38 alter AD progression, laying the groundwork for disease pathophysiology and novel AD diagnostic and treatment.

Systemic Treatment with siRNA Targeting Gamma-Secretase Activating Protein Inhibits Amyloid-β Accumulation in Alzheimer's Disease

Amyloid-β (Aβ) peptide aggregation in the brain is a key factor in Alzheimer's disease. However, direct inhibition of β-secretase or γ-secretase proves ineffective in reducing Aβ accumulation and improving cognition in Alzheimer's. Recent findings suggest that inhibiting gamma-secretase activating protein (GSAP) can decrease Aβ generation without affecting crucial γ-secretase substrates. Dimerization of Lep9R3LC (diLep9R3LC) was confirmed by Ellman's test. The peptide-small interfering RNA (siRNA) complex ratio, particle size, and surface charge were analyzed using electrophoretic mobility shift assay, and dynamic light scattering, respectively. In a 3xTg mice model of Alzheimer's disease, diLep9R3LC:siRNA complexes were intravenously administered twice a week for 8 weeks. Assessments included gene silencing, protein expression, and behavioral improvement using reverse transcription polymerase chain reaction, quantitative polymerase chain reaction, western blotting, Y-maze, and object recognition tests. The efficacy of Lep9R3LC dimerization was ~80% after a 3-d reaction by Ellman's test. In N2a cells, diLep9R3LC:siGSAP complexes achieved ~70% silencing at 48 h posttransfection. In 7-month-old male 3xTg mice, GSAP knockdown was ~30% in the cortex and ~50% in the hippocampus. The behavior improved in mice treated with diLep9R3LC:siGSAP complexes, showing a 60% increase in entries and an 80% increase object recognition. A novel dipeptide, diLep9R3LC, complexed with siRNA targeting GSAP (siGSAP), efficiently delivers siRNA to the mouse brain, targeting the hippocampus. The treatment inhibits Aβ accumulation, reduces GSK-3β-associated with tau hyperphosphorylation, and improves Alzheimer's behavior. Our findings highlight diLep9R3LC:siGSAP's potential for Alzheimer's and as a siRNA carrier for central nervous system-related diseases.

Progress and trends in neurological disorders research based on deep learning

In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging, offering unprecedented opportunities for the diagnosis and treatment of neurological disorders (NDs). This comprehensive review explores the multifaceted role of DL techniques in leveraging vast datasets to advance our understanding of NDs and improve clinical outcomes. Beginning with a systematic literature review, we delve into the utilization of DL, particularly focusing on multimodal neuroimaging data analysis-a domain that has witnessed rapid progress and garnered significant scientific interest. Our study categorizes and critically analyses numerous DL models, including Convolutional Neural Networks (CNNs), LSTM-CNN, GAN, and VGG, to understand their performance across different types of Neurology Diseases. Through particular analysis, we identify key benchmarks and datasets utilized in training and testing DL models, shedding light on the challenges and opportunities in clinical neuroimaging research. Moreover, we discuss the effectiveness of DL in real-world clinical scenarios, emphasizing its potential to revolutionize ND diagnosis and therapy. By synthesizing existing literature and describing future directions, this review not only provides insights into the current state of DL applications in ND analysis but also covers the way for the development of more efficient and accessible DL techniques. Finally, our findings underscore the transformative impact of DL in reshaping the landscape of clinical neuroimaging, offering hope for enhanced patient care and groundbreaking discoveries in the field of neurology. This review paper is beneficial for neuropathologists and new researchers in this field.

Sensitivity of substrate translocation in chaperone-mediated autophagy to Alzheimer's disease progression

Alzheimer's disease (AD) is a progressive brain disorder marked by abnormal protein accumulation and resulting proteotoxicity. This study examines Chaperone-Mediated Autophagy (CMA), particularly substrate translocation into lysosomes, in AD. The study observes: (1) Increased substrate translocation activity into lysosomes, vital for CMA, aligns with AD progression, highlighted by gene upregulation and more efficient substrate delivery. (2) This CMA phase strongly correlates with AD's clinical symptoms; more proteotoxicity links to worse dementia, underscoring the need for active degradation. (3) Proteins like GFAP and LAMP2A, when upregulated, almost certainly indicate AD risk, marking this process as a significant AD biomarker. Based on these observations, this study proposes the following hypothesis: As AD progresses, the aggregation of pathogenic proteins increases, the process of substrate entry into lysosomes via CMA becomes active. The genes associated with this process exhibit heightened sensitivity to AD. This conclusion stems from an analysis of over 10,000 genes and 363 patients using two AI methodologies. These methodologies were instrumental in identifying genes highly sensitive to AD and in mapping the molecular networks that respond to the disease, thereby highlighting the significance of this critical phase of CMA.

In-depth investigation of the effect of pH on the autofluorescence properties of DPF3b and DPF3a amyloid fibrils

Double PHD fingers 3 (DPF3) protein exists as two splicing variants, DPF3b and DPF3a, the involvement of which in human cancer and neurodegeneration is beginning to be increasingly recognised. Both isoforms have recently been identified as intrinsically disordered proteins able to undergo amyloid fibrillation. Upon their aggregation, DPF3 proteins exhibit an intrinsic fluorescence in the visible range, referred to as deep-blue autofluorescence (dbAF). Comprehension of such phenomenon remaining elusive, we investigated in the present study the influence of pH on the optical properties of DPF3b and DPF3a fibrils. By varying the excitation wavelength and the pH condition, the two isoforms were revealed to display several autofluorescence modes that were defined as violet, deep-blue, and blue-green according to their emission range. Complementarily, analysis of excitation spectra and red edge shift plots allowed to better decipher their photoselection mechanism and to highlight isoform-specific excitation-emission features. Furthermore, the observed violation to Kasha-Vavilov's rule was attributed to red edge excitation shift effects, which were impacted by pH-mediated H-bond disruption, leading to changes in intramolecular charge and proton transfer, or π-electrons delocalisation. Finally, emergence of different autofluorescence emitters was likely related to structurally distinct fibrillar assemblies between isoforms, as well as to discrepancies in the amino acid composition of their aggregation prone regions.

G-protein coupled receptors regulates Tauopathy in neurodegeneration

In Alzheimer's disease, the microtubule-associated protein, Tau misfolds to form aggregates and filaments in the intra- and extracellular region of neuronal cells. Microglial cells are the resident brain macrophage cells involved in constant surveillance and activated by the extracellular deposits. Purinergic receptors are involved in the chemotactic migration of microglial cells towards the site of inflammation. From our recent study, we have observed that the microglial P2Y12 receptor is involved in phagocytosis of full-length Tau species such as monomers, oligomers and aggregates by actin-driven chemotaxis. This study shows the interaction of repeat-domain of Tau (TauRD) with the microglial P2Y12 receptor and the corresponding residues for interaction have been analyzed by various in-silico approaches. In the cellular studies, TauRD was found to interact with microglial P2Y12R and induces its cellular expression confirmed by co-immunoprecipitation and western blot analysis. Furthermore, the P2Y12R-mediated TauRD internalization has demonstrated activation of microglia with an increase in the Iba1 level, and TauRD becomes accumulated at the peri-nuclear region for the degradation.

Cortical lipid metabolic pathway alteration of early Alzheimer's disease and candidate drugs screen

BACKGROUND

Lipid metabolism changes occur in early Alzheimer's disease (AD) patients. Yet little is known about metabolic gene changes in early AD cortex.

METHODS

The lipid metabolic genes selected from two datasets (GSE39420 and GSE118553) were analyzed with enrichment analysis. Protein-protein interaction network construction and correlation analyses were used to screen core genes. Literature analysis and molecular docking were applied to explore potential therapeutic drugs.

RESULTS

60 lipid metabolic genes differentially expressed in early AD patients' cortex were screened. Bioinformatics analyses revealed that up-regulated genes were mainly focused on mitochondrial fatty acid oxidation and mediating the activation of long-chain fatty acids, phosphoproteins, and cholesterol metabolism. Down-regulated genes were mainly focused on lipid transport, carboxylic acid metabolic process, and neuron apoptotic process. Literature reviews and molecular docking results indicated that ACSL1, ACSBG2, ACAA2, FABP3, ALDH5A1, and FFAR4 were core targets for lipid metabolism disorder and had a high binding affinity with compounds including adenosine phosphate, oxidized Photinus luciferin, BMS-488043, and candidate therapeutic drugs especially bisphenol A, benzo(a)pyrene, ethinyl estradiol.

CONCLUSIONS

AD cortical lipid metabolism disorder was associated with the dysregulation of the PPAR signaling pathway, glycerophospholipid metabolism, adipocytokine signaling pathway, fatty acid biosynthesis, fatty acid degradation, ferroptosis, biosynthesis of unsaturated fatty acids, and fatty acid elongation. Candidate drugs including bisphenol A, benzo(a)pyrene, ethinyl estradiol, and active compounds including adenosine phosphate, oxidized Photinus luciferin, and BMS-488043 have potential therapeutic effects on cortical lipid metabolism disorder of early AD.

Identification of disease-specific bio-markers through network-based analysis of gene co-expression: A case study on Alzheimer's disease

Finding biomarker genes for complex diseases attracts persistent attention due to its application in clinics. In this paper, we propose a network-based method to obtain a set of biomarker genes. The key idea is to construct a gene co-expression network among sensitive genes and cluster the genes into different modules. For each module, we can identify its representative, i.e., the gene with the largest connectivity and the smallest average shortest path length to other genes within the module. We believe these representative genes could serve as a new set of potential biomarkers for diseases. As a typical example, we investigated Alzheimer's disease, obtaining a total of 16 potential representative genes, three of which belong to the non-transcriptome. A total of 11 out of these genes are found in literature from different perspectives and methods. The incipient groups were classified into two different subtypes using machine learning algorithms. We subjected the two subtypes to Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes analysis with healthy groups and moderate groups, respectively. The two sub-type groups were involved in two different biological processes, demonstrating the validity of this approach. This method is disease-specific and independent; hence, it can be extended to classify other kinds of complex diseases.

Updates on mouse models of Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease in the United States (US). Animal models, specifically mouse models have been developed to better elucidate disease mechanisms and test therapeutic strategies for AD. A large portion of effort in the field was focused on developing transgenic (Tg) mouse models through over-expression of genetic mutations associated with familial AD (FAD) patients. Newer generations of mouse models through knock-in (KI)/knock-out (KO) or CRISPR gene editing technologies, have been developed for both familial and sporadic AD risk genes with the hope to more accurately model proteinopathies without over-expression of human AD genes in mouse brains. In this review, we summarized the phenotypes of a few commonly used as well as newly developed mouse models in translational research laboratories including the presence or absence of key pathological features of AD such as amyloid and tau pathology, synaptic and neuronal degeneration as well as cognitive and behavior deficits. In addition, advantages and limitations of these AD mouse models have been elaborated along with discussions of any sex-specific features. More importantly, the omics data from available AD mouse models have been analyzed to categorize molecular signatures of each model reminiscent of human AD brain changes, with the hope to guide future selection of most suitable models for specific research questions to be addressed in the AD field.

Glioblastoma and its treatment are associated with extensive accelerated brain aging

Progressive neurocognitive dysfunction is the leading cause of a reduced quality of life in patients with primary brain tumors. Understanding how the human brain responds to cancer and its treatment is essential to improve the associated cognitive sequelae. In this study, we performed integrated transcriptomic and tissue analysis on postmortem normal-appearing non-tumor brain tissue from glioblastoma (GBM) patients that had received cancer treatments, region-matched brain tissue from unaffected control individuals and Alzheimer's disease (AD) patients. We show that normal-appearing non-tumor brain regions of patients with GBM display hallmarks of accelerated aging, in particular mitochondrial dysfunction, inflammation, and proteostasis deregulation. The extent and spatial pattern of this response decreased with distance from the tumor. Gene set enrichment analyses and a direct comparative analysis with an independent cohort of brain tissue samples from AD patients revealed a significant overlap in differentially expressed genes and a similar biological aging trajectory. Additionally, these responses were validated at the protein level showing the presence of increased lysosomal lipofuscin, phosphorylated microtubule-associated protein Tau, and oxidative DNA damage in normal-appearing brain areas of GBM patients. Overall, our data show that the brain of GBM patients undergoes accelerated aging and shared AD-like features, providing the basis for novel or repurposed therapeutic targets for managing brain tumor-related side effects.

Intersectin - many facets of a scaffold protein

Intersectin (ITSN) is a multi-domain scaffold protein with a diverse array of functions including regulation of endocytosis, vesicle transport, and activation of various signal transduction pathways. There are two ITSN genes located on chromosomes 21 and 2 encoding for proteins ITSN1 and ITSN2, respectively. Each ITSN gene encodes two major isoforms, ITSN-Long (ITSN-L) and ITSN-Short (ITSN-S), due to alternative splicing. ITSN1 and 2, collectively referred to as ITSN, are implicated in many physiological and pathological processes, such as neuronal maintenance, actin cytoskeletal rearrangement, and tumor progression. ITSN is mis-regulated in many tumors, such as breast, lung, neuroblastomas, and gliomas. Altered expression of ITSN is also found in several neurodegenerative diseases, such as Down Syndrome and Alzheimer's disease. This review summarizes recent studies on ITSN and provides an overview of the function of this important family of scaffold proteins in various biological processes.

DNA hypomethylation promotes the expression of CASPASE-4 which exacerbates inflammation and amyloid-β deposition in Alzheimer's disease

Alzheimer's disease (AD) is the sixth leading cause of death in the USA. It is established that neuroinflammation contributes to the synaptic loss, neuronal death, and symptomatic decline of AD patients. Accumulating evidence suggests a critical role for microglia, innate immune phagocytes of the brain. For instance, microglia release pro-inflammatory products such as IL-1β which is highly implicated in AD pathobiology. The mechanisms underlying the transition of microglia to proinflammatory promoters of AD remain largely unknown. To address this gap, we performed reduced representation bisulfite sequencing (RRBS) to profile global DNA methylation changes in human AD brains compared to no disease controls. We identified differential DNA methylation of CASPASE-4 (CASP4), which when expressed promotes the generation of IL-1β and is predominantly expressed in immune cells. DNA upstream of the CASP4 transcription start site was hypomethylated in human AD brains, which was correlated with increased expression of CASP4. Furthermore, microglia from a mouse model of AD (5xFAD) express increased levels of CASP4 compared to wild-type (WT) mice. To study the role of CASP4 in AD, we developed a novel mouse model of AD lacking the mouse ortholog of CASP4 and CASP11, which is encoded by mouse Caspase-4 (5xFAD/Casp4-/-). The expression of CASP11 was associated with increased accumulation of pathologic protein aggregate amyloid-β (Aβ) and increased microglial production of IL-1β in 5xFAD mice. Utilizing RNA-sequencing, we determined that CASP11 promotes unique transcriptomic phenotypes in 5xFAD mouse brains, including alterations of neuroinflammatory and chemokine signaling pathways. Notably, in vitro, CASP11 promoted generation of IL-1β from macrophages in response to cytosolic Aβ through cleavage of downstream effector Gasdermin D (GSDMD). Therefore, here we unravel the role for CASP11 and GSDMD in the generation of IL-1β in response to Aβ and the progression of pathologic inflammation in AD. Overall, our results demonstrate that overexpression of CASP4 due to differential DNA methylation in AD microglia contributes to the progression of AD pathobiology. Thus, we identify CASP4 as a potential target for immunotherapies for the treatment and prevention of AD.

Pathological phenotypes of astrocytes in Alzheimer's disease

Astrocytes are involved in various processes in the central nervous system (CNS). As the most abundant cell type in the CNS, astrocytes play an essential role in neuronal maintenance and support, synaptic activity, neuronal metabolism, and amyloid-beta (Aβ) clearance. Alzheimer's disease (AD) is a neurodegenerative disorder associated with cognitive and behavioral impairment. The transformation of astrocytes is involved in various neurodegenerative diseases, such as AD. Since astrocytes have functional diversity and morphological and physiological heterogeneity in the CNS, AD-related astrocytes might show various pathological phenotypes during AD. Astrocytes developing pathological phenotypes could contribute to AD progression. In this review, we provide an overview of the pathological phenotypes of astrocytes in the context of AD, highlighting recent findings in human and mouse AD.

Integrative multi-omics analysis reveals the critical role of the PBXIP1 gene in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder, and its strongest risk factor is aging. A few studies have explored the relationship between aging and AD, while the underlying mechanism remains unclear. We assembled data across multi-omics (i.e., epigenetics, transcriptomics, and proteomics, based on frozen tissues from the dorsolateral prefrontal cortex) and neuropathological and clinical traits from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). Aging was assessed using six DNA methylation clocks (including the Horvath clock, Hannum clock, Levine clock, HorvathSkin clock, Lin clock, and Cortical clock) that capture mortality risk in literature. After accounting for age, we first identified a gene module (including 263 genes) that was related to the integrated aging measure of six clocks, as well as three neuropathological traits of AD (i.e., β-amyloid, Tau tangles, and tangle density). Interestingly, among 20 key genes with top intramodular connectivity of the module, PBXIP1 was the only one that was significantly associated with all three neuropathological traits of AD at the protein level after Bonferroni correction. Furthermore, PBXIP1 was associated with the clinical diagnosis of AD in both ROSMAP and three independent datasets. Moreover, PBXIP1 may be related to AD through its role in astrocytes and hippocampal neurons, and the mTOR pathway. The results suggest the critical role of PBXIP1 in AD and support the potential and feasibility of using multi-omics data to investigate mechanisms of complex diseases. However, more validations in different populations and experiments in vitro and in vivo are required in the future.

Investigation of Potential Drug Targets Involved in Inflammation Contributing to Alzheimer's Disease Progression

Alzheimer's disease has become a major public health issue. While extensive research has been conducted in the last few decades, few drugs have been approved by the FDA to treat Alzheimer's disease. There is still an urgent need for understanding the disease pathogenesis, as well as identifying new drug targets for further drug discovery. Alzheimer's disease is known to arise from a build-up of amyloid beta (Aβ) plaques as well as tangles of tau proteins. Along similar lines to Alzheimer's disease, inflammation in the brain is known to stem from the degeneration of tissue and build-up of insoluble materials. A minireview was conducted in this work assessing the genes, proteins, reactions, and pathways that link brain inflammation and Alzheimer's disease. Existing tools in Systems Biology were implemented to build protein interaction networks, mainly for the classical complement pathway and G protein-coupled receptors (GPCRs), to rank the protein targets according to their interactions. The top 10 protein targets were mainly from the classical complement pathway. With the consideration of existing clinical trials and crystal structures, proteins C5AR1 and GARBG1 were identified as the best targets for further drug discovery, through computational approaches like ligand-protein docking techniques.

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.

Cell-free RNA signatures predict Alzheimer's disease

There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.

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.

Comprehensive analyses of brain cell communications based on multiple scRNA-seq and snRNA-seq datasets for revealing novel mechanism in neurodegenerative diseases

AIMS

Complex cellular communications between glial cells and neurons are critical for brain normal function and disorders, and single-cell level RNA-sequencing datasets display more advantages for analyzing cell communications. Therefore, it is necessary to systematically explore brain cell communications when considering factors such as sex and brain region.

METHODS

We extracted a total of 1,039,459 cells derived from 28 brain single-cell RNA-sequencing (scRNA-seq) or single-nucleus RNA-sequencing (snRNA-seq) datasets from the GEO database, including 12 human and 16 mouse datasets. These datasets were further divided into 71 new sub-datasets when considering disease, sex, and region conditions. In the meanwhile, we integrated four methods to evaluate ligand-receptor interaction score among six major brain cell types (microglia, neuron, astrocyte, oligodendrocyte, OPC, and endothelial cell).

RESULTS

For Alzheimer's disease (AD), disease-specific ligand-receptor pairs when compared with normal sub-datasets, such as SEMA4A-NRP1, were identified. Furthermore, we explored the sex- and region-specific cell communications and identified that WNT5A-ROR1 among microglia cells displayed close communications in male, and SPP1-ITGAV displayed close communications in the meninges region from microglia to neurons. Furthermore, based on the AD-specific cell communications, we constructed a model for AD early prediction and confirmed the predictive performance using multiple independent datasets. Finally, we developed an online platform for researchers to explore brain condition-specific cell communications.

CONCLUSION

This research provided a comprehensive study to explore brain cell communications, which could reveal novel biological mechanisms involved in normal brain function and neurodegenerative diseases such as AD.

The major TMEM106B dementia risk allele affects TMEM106B protein levels, fibril formation, and myelin lipid homeostasis in the ageing human hippocampus

BACKGROUND

The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases.

METHODS

Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Fibrillar C-terminal TMEM106B fragments were isolated using sarkosyl fractionation and quantified by immunoblotting.

RESULTS

Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. TMEM106B, a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with ageing was specific to carriers of the rs1990622-A allele in the TMEM106B gene that increases risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Rs1990622-A was also associated with higher TMEM106B fibril content. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype.

CONCLUSIONS

Our study demonstrates that TMEM106B protein abundance is increased with brain ageing in humans, establishes that dementia risk allele rs1990622-A predisposes to TMEM106B fibril formation in the hippocampus, and provides the first evidence that rs1990622-A affects brain lipid homeostasis, particularly myelin lipids. Our data suggests that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

Gene expression analysis reveals GRIN1, SYT1, and SYN2 as significant therapeutic targets and drug repurposing reveals lorazepam and lorediplon as potent inhibitors to manage Alzheimer's disease

Alzheimer's disease (AD) is a slowly progressive neurodegenerative disease and a leading cause of dementia. We aim to identify key genes for the development of therapeutic targets and biomarkers for potential treatments for AD. Meta-analysis was performed on six microarray datasets and identified the differentially expressed genes between healthy and Alzheimer's disease samples. Thereafter, we filtered out the common genes which were present in at least four microarray datasets for downstream analysis. We have constructed a gene-gene network for the common genes and identified six hub genes. Furthermore, we investigated the regulatory mechanisms of these hub genes by analysing their interaction with miRNAs and transcription factors. The gene ontology analysis results highlighted the enriched terms significantly associated with hub genes. Through an extensive literature survey, we found that three of the hub genes including GRIN1, SYN2, and SYT1 were critically involved in disease development. To leverage existing drugs for potential repurposing, we predicted drug-gene interaction using the drug-gene interaction database, and performed molecular docking studies. The docking results revealed that the drug compounds had strong interactions and favorable binding with selected hub genes. Lorazepam exhibits a binding energy of -7.3 kcal/mol with GRIN1, Lorediplon exhibits binding energies of -7.7 kcal/mol and -6.3 kcal/mol with the SYT1, and SYN2 respectively. In addition, 100 ns molecular dynamics simulations were carried out for the top complexes and apo protein as well. Furthermore, the MM-PBSA free energy calculations also revealed that these complexes are stable and had favorable energies. According to our study, the identified hub gene could serve as a biomarker as well as a therapeutic target for AD, and the proposed repurposed drug molecules appear to have promising efficacy in treating the disease.Communicated by Ramaswamy H. Sarma.

Differential Gene Expression in Activated Microglia Treated with Adenosine A2A Receptor Antagonists Highlights Olfactory Receptor 56 and T-Cell Activation GTPase-Activating Protein 1 as Potential Biomarkers of the Polarization of Activated Microglia

Microglial activation often accompanies the plastic changes occurring in the brain of patients with neurodegenerative diseases. A2A and A3 adenosine receptors have been proposed as therapeutic targets to combat neurodegeneration. RNAseq was performed using samples isolated from lipopolysaccharide/interferon-γ activated microglia treated with SCH 58261, a selective A2A receptor antagonist, and with both SCH 58261 and 2-Cl-IB-MECA, a selective A3 receptor agonist. None of the treatments led to any clear microglial phenotype when gene expression for classical biomarkers of microglial polarization was assessed. However, many of the downregulated genes were directly or indirectly related to immune system-related events. Searching for genes whose expression was both significantly and synergistically affected when treated with the two adenosine receptor ligands, the AC122413.1 and Olfr56 were selected among those that were, respectively, upregulated and downregulated. We therefore propose that the products of these genes, olfactory receptor 56 and T-cell activation GTPase-activating protein 1, deserve attention as potential biomarkers of phenotypes that occur upon microglial activation.

DNA hypomethylation promotes the expression of CASPASE-4 which exacerbates neuroinflammation and amyloid-β deposition in Alzheimer's disease The Ohio State University College of Medicine

Alzheimer's Disease (AD) is the 6th leading cause of death in the US. It is established that neuroinflammation contributes to the synaptic loss, neuronal death, and symptomatic decline of AD patients. Accumulating evidence suggests a critical role for microglia, innate immune phagocytes of the brain. For instance, microglia release proinflammatory products such as IL-1β which is highly implicated in AD pathobiology. The mechanisms underlying the transition of microglia to proinflammatory promoters of AD remain largely unknown. To address this gap, we performed Reduced Representation Bisulfite Sequencing (RRBS) to profile global DNA methylation changes in human AD brains compared to no disease controls. We identified differential DNA methylation of CASPASE-4 (CASP4), which when expressed, can be involved in generation of IL-1β and is predominantly expressed in immune cells. DNA upstream of the CASP4 transcription start site was hypomethylated in human AD brains, which was correlated with increased expression of CASP4. Furthermore, microglia from a mouse model of AD (5xFAD) express increased levels of CASP4 compared to wild-type (WT) mice. To study the role of CASP4 in AD, we developed a novel mouse model of AD lacking the mouse ortholog of CASP4, CASP11, which is encoded by mouse Caspase-4 (5xFAD/Casp4-/-). The expression of CASP11 was associated with increased accumulation of pathologic protein aggregate amyloid-β (Aβ) and increased microglial production of IL-1β in 5xFAD mice. Utilizing RNA sequencing, we determined that CASP11 promotes unique transcriptomic phenotypes in 5xFAD mouse brains, including alterations of neuroinflammatory and chemokine signaling pathways. Notably, in vitro, CASP11 promoted generation of IL-1β from macrophages in response to cytosolic Aβ through cleavage of downstream effector Gasdermin D (G SDMD). We describe a role for CASP11 and GSDMD in the generation of IL-1β in response to Aβ and the progression of pathologic inflammation in AD. Overall, our results demonstrate that overexpression of CASP4 due to differential methylation in AD microglia contributes to the progression of AD pathobiology, thus identifying CASP4 as a potential target for immunotherapies for the treatment of AD.

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.

The role of the ATP-Binding Cassette A1 (ABCA1) in neurological disorders: a mechanistic review

INTRODUCTION

Cholesterol homeostasis is critical for normal brain function. It is tightly controlled by various biological elements. ATP-binding cassette transporter A1 (ABCA1) is a membrane transporter that effluxes cholesterol from cells, particularly astrocytes, into the extracellular space. The recent studies pertaining to ABCA1's role in CNS disorders were included in this study.

AREAS COVERED

In this comprehensive literature review, preclinical and human studies showed that ABCA1 has a significant role in the following diseases or disorders: Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, neuropathy, anxiety, depression, psychosis, epilepsy, stroke, and brain ischemia and trauma.

EXPERT OPINION

ABCA1 via modulating normal and aberrant brain functions such as apoptosis, phagocytosis, BBB leakage, neuroinflammation, amyloid β efflux, myelination, synaptogenesis, neurite outgrowth, and neurotransmission promotes beneficial effects in aforementioned diseases. ABCA1 is a key molecule in the CNS. By boosting its expression or function, some CNS disorders may be resolved. In preclinical studies, liver X receptor agonists have shown promise in treating CNS disorders via ABCA1 and apoE enhancement.

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.

Astrocytic uptake of neuronal corpses promotes cell-to-cell spreading of tau pathology

Tau deposits in astrocytes are frequently found in Alzheimer's disease (AD) and other tauopathies. Since astrocytes do not express tau, the inclusions have been suggested to be of neuronal origin. However, the mechanisms behind their appearance and their relevance for disease progression remain unknown. Here we demonstrate, using a battery of experimental techniques that human astrocytes serve as an intermediator, promoting cell-to-cell spreading of pathological tau. Human astrocytes engulf and process, but fail to fully degrade dead neurons with tau pathology, as well as synthetic tau fibrils and tau aggregates isolated from AD brain tissue. Instead, the pathogenic tau is spread to nearby cells via secretion and tunneling nanotube mediated transfer. By performing co-culture experiments we could show that tau-containing astrocytes induce tau pathology in healthy human neurons directly. Furthermore, our results from a FRET based seeding assay, demonstrated that the tau proteoforms secreted by astrocytes have an exceptional seeding capacity, compared to the original tau species engulfed by the cells. Taken together, our study establishes a central role for astrocytes in mediating tau pathology, which could be of relevance for identifying novel treatment targets for AD and other tauopathies.

Six mitophagy-related hub genes as peripheral blood biomarkers of Alzheimer's disease and their immune cell infiltration correlation

Background

Alzheimer's disease (AD), a neurodegenerative disorder with progressive symptoms, seriously endangers human health worldwide. AD diagnosis and treatment are challenging, but molecular biomarkers show diagnostic potential. This study aimed to investigate AD biomarkers in the peripheral blood.

Method

Utilizing three microarray datasets, we systematically analyzed the differences in expression and predictive value of mitophagy-related hub genes (MRHGs) in the peripheral blood mononuclear cells of patients with AD to identify potential diagnostic biomarkers. Subsequently, a protein-protein interaction network was constructed to identify hub genes, and functional enrichment analyses were performed. Using consistent clustering analysis, AD subtypes with significant differences were determined. Finally, infiltration patterns of immune cells in AD subtypes and the relationship between MRHGs and immune cells were investigated by two algorithms, CIBERSORT and single-sample gene set enrichment analysis (ssGSEA).

Results

Our study identified 53 AD- and mitophagy-related differentially expressed genes and six MRHGs, which may be potential biomarkers for diagnosing AD. Functional analysis revealed that six MRHGs significantly affected biologically relevant functions and signaling pathways such as IL-4 Signaling Pathway, RUNX3 Regulates Notch Signaling Pathway, IL-1 and Megakaryocytes in Obesity Pathway, and Overview of Leukocyteintrinsic Hippo Pathway. Furthermore, CIBERSORT and ssGSEA algorithms were used for all AD samples to analyze the abundance of infiltrating immune cells in the two disease subtypes. The results showed that these subtypes were significantly related to immune cell types such as activated mast cells, regulatory T cells, M0 macrophages, and neutrophils. Moreover, specific MRHGs were significantly correlated with immune cell levels.

Conclusion

Our findings suggest that MRHGs may contribute to the development and prognosis of AD. The six identified MRHGs could be used as valuable diagnostic biomarkers for further research on AD. This study may provide new promising diagnostic and therapeutic targets in the peripheral blood of patients with AD.

Identifying Effective Feature Selection Methods for Alzheimer's Disease Biomarker Gene Detection Using Machine Learning

Alzheimer's disease (AD) is a complex genetic disorder that affects the brain and has been the focus of many bioinformatics research studies. The primary objective of these studies is to identify and classify genes involved in the progression of AD and to explore the function of these risk genes in the disease process. The aim of this research is to identify the most effective model for detecting biomarker genes associated with AD using several feature selection methods. We compared the efficiency of feature selection methods with an SVM classifier, including mRMR, CFS, the Chi-Square Test, F-score, and GA. We calculated the accuracy of the SVM classifier using validation methods such as 10-fold cross-validation. We applied these feature selection methods with SVM to a benchmark AD gene expression dataset consisting of 696 samples and 200 genes. The results indicate that the mRMR and F-score feature selection methods with SVM classifier achieved a high accuracy of around 84%, with a number of genes between 20 and 40. Furthermore, the mRMR and F-score feature selection methods with SVM classifier outperformed the GA, Chi-Square Test, and CFS methods. Overall, these findings suggest that the mRMR and F-score feature selection methods with SVM classifier are effective in identifying biomarker genes related to AD and could potentially lead to more accurate diagnosis and treatment of the disease.

Identifying important gene signatures of BMI using network structure-aided nonparametric quantile regression

We focus on identifying genomics risk factors of higher body mass index (BMI) incorporating a priori information, such as biological pathways. However, the commonly used methods to incorporate prior information provide a model for the mean function of the outcome and rely on unmet assumptions. To address these concerns, we propose a method for nonparametric additive quantile regression with network regularization to incorporate the information encoded by known networks. To account for nonlinear associations, we approximate the unknown additive functional effect of each predictor with the expansion of a B-spline basis. We implement the group Lasso penalty to obtain a sparse model. We define the network-constrained penalty by the totalℓ 2 $$ {\ell}_2 $$ norm of the difference between the effect functions of any two linked genes in the known network. We further propose an efficient computation procedure to solve the optimization problem that arises in our model. Simulation studies show that our proposed method performs well in identifying more truly associated genes and less falsely associated genes than alternative approaches. We apply the proposed method to analyze the microarray gene-expression dataset in the Framingham Heart Study and identify several 75 percentile BMI associated genes. In conclusion, our proposed approach efficiently identifies the outcome-associated variables in a nonparametric additive quantile regression framework by leveraging known network information.

Aging gene signature of IL-7 receptor alpha low effector memory CD8+ T cells is associated with neurocognitive functioning in Alzheimer's disease

CD45RA+ effector memory (EM) CD8+ T cell expansion was reported in Alzheimer's disease (AD). Such cells are IL-7 receptor alpha (IL-7Rα)low EM CD8+ T cells, which expand with age and have a unique aging gene signature (i.e., IL-7Rαlow aging genes). Here we investigated whether IL-7Rαlow aging genes and previously reported AD and memory (ADM) genes overlapped with clinical significance in AD patients. RT-qPCR analysis of 40 genes, including 29 ADM, 9 top IL-7Ralow aging and 2 control genes, showed 8 differentially expressed genes between AD and cognitively normal groups; five (62.5%) of which were top IL-7Rαlow aging genes. Over-representation analysis revealed that these genes were highly present in molecular and biological pathways associated with AD. Distinct expression levels of these genes were associated with neuropsychological testing performance in 3 subgroups of dementia participants. Our findings support the possible implication of the IL-7Rαlow aging gene signature with AD.

Revealing cell vulnerability in Alzheimer's disease by single-cell transcriptomics

Alzheimer's disease (AD) is a neurodegenerative disorder that by affecting specific brain cell types and regions cause severe pathological and functional changes in memory neural circuits. A comprehensive knowledge of the pathogenic mechanisms underlying AD requires a deeper understanding of the cell-specific pathological responses through integrative molecular analyses. Recent application of high-throughput single-cell transcriptomics to postmortem tissue has proved powerful to unravel cell susceptibility and biological networks responding to amyloid and tau pathologies. Here, we review single-cell transcriptomic studies successfully applied to decipher cell-specific gene expression programs and pathways in the brain of AD patients. Transcriptional information reveals both specific and common gene signatures affecting the major cerebral cell types, including astrocytes, endothelial cells, microglia, neurons, and oligodendrocytes. Cell type-specific transcriptomes associated with AD pathology and clinical symptoms are related to common biological networks affecting, among others pathways, synaptic function, inflammation, proteostasis, cell death, oxidative stress, and myelination. The general picture that emerges from systems-level single-cell transcriptomics is a spatiotemporal pattern of cell diversity and biological pathways, and novel cell subpopulations affected in AD brain. We argue that broader implementation of cell transcriptomics in larger AD human cohorts using standardized protocols is fundamental for reliable assessment of temporal and regional cell-type gene profiling. The possibility of applying this methodology for personalized medicine in clinics is still challenging but opens new roads for future diagnosis and treatment in dementia.

Recent advances in deciphering hippocampus complexity using single-cell transcriptomics

Single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq) technologies have emerged as revolutionary and powerful tools, which have helped in achieving significant progress in biomedical research over the last decade. scRNA-seq and snRNA-seq resolve heterogeneous cell populations from different tissues and help reveal the function and dynamics at the single-cell level. The hippocampus is an essential component for cognitive functions, including learning, memory, and emotion regulation. However, the molecular mechanisms underlying the activity of hippocampus have not been fully elucidated. The development of scRNA-seq and snRNA-seq technologies provides strong support for attaining an in-depth understanding of hippocampal cell types and gene expression regulation from the single-cell transcriptome profiling perspective. This review summarizes the applications of scRNA-seq and snRNA-seq in the hippocampus to further expand our knowledge of the molecular mechanisms related to hippocampal development, health, and diseases.

Identification of gene networks mediating regional resistance to tauopathy in late-onset Alzheimer’s disease

Neurofibrillary lesions composed of tau protein aggregates are defining hallmarks of Alzheimer’s Disease. Despite tau filaments appearing to spread between networked brain regions in a prion-like manner, certain areas including cerebellum resist trans-synaptic spread of tauopathy and degeneration of their constituent neuronal cell bodies. To identify molecular correlates of resistance, we derived and implemented a ratio of ratios approach for disaggregating gene expression data on the basis of regional vulnerability to tauopathic neurodegeneration. When applied to vulnerable pre-frontal cortex as an internal reference for resistant cerebellum, the approach segregated adaptive changes in expression into two components. The first was enriched for neuron-derived transcripts associated with proteostasis including specific members of the molecular chaperone family and was unique to resistant cerebellum. When produced as purified proteins, each of the identified chaperones depressed aggregation of 2N4R tau in vitro at sub-stoichiometric concentrations, consistent with the expression polarity deduced from ratio of ratios testing. In contrast, the second component enriched for glia- and microglia-derived transcripts associated with neuroinflammation, segregating these pathways from susceptibility to tauopathy. These data support the utility of ratio of ratios testing for establishing the polarity of gene expression changes with respect to selective vulnerability. The approach has the potential to identify new targets for drug discovery predicated on their ability to promote resistance to disease in vulnerable neuron populations.

Exploiting machine learning models to identify novel Alzheimer’s disease biomarkers and potential targets

We still do not have an effective treatment for Alzheimer's disease (AD) despite it being the most common cause of dementia and impaired cognitive function. Thus, research endeavors are directed toward identifying AD biomarkers and targets. In this regard, we designed a computational method that exploits multiple hub gene ranking methods and feature selection methods with machine learning and deep learning to identify biomarkers and targets. First, we used three AD gene expression datasets to identify 1/ hub genes based on six ranking algorithms (Degree, Maximum Neighborhood Component (MNC), Maximal Clique Centrality (MCC), Betweenness Centrality (BC), Closeness Centrality, and Stress Centrality), 2/ gene subsets based on two feature selection methods (LASSO and Ridge). Then, we developed machine learning and deep learning models to determine the gene subset that best distinguishes AD samples from the healthy controls. This work shows that feature selection methods achieve better prediction performances than the hub gene sets. Beyond this, the five genes identified by both feature selection methods (LASSO and Ridge algorithms) achieved an AUC = 0.979. We further show that 70% of the upregulated hub genes (among the 28 overlapping hub genes) are AD targets based on a literature review and six miRNA (hsa-mir-16-5p, hsa-mir-34a-5p, hsa-mir-1-3p, hsa-mir-26a-5p, hsa-mir-93-5p, hsa-mir-155-5p) and one transcription factor, JUN, are associated with the upregulated hub genes. Furthermore, since 2020, four of the six microRNA were also shown to be potential AD targets. To our knowledge, this is the first work showing that such a small number of genes can distinguish AD samples from healthy controls with high accuracy and that overlapping upregulated hub genes can narrow the search space for potential novel targets.

Clusters of co-abundant proteins in the brain cortex associated with fronto-temporal lobar degeneration

BACKGROUND

Frontotemporal lobar degeneration (FTLD) is characterized pathologically by neuronal and glial inclusions of hyperphosphorylated tau or by neuronal cytoplasmic inclusions of TDP43. This study aimed at deciphering the molecular mechanisms leading to these distinct pathological subtypes.

METHODS

To this end, we performed an unbiased mass spectrometry-based proteomic and systems-level analysis of the middle frontal gyrus cortices of FTLD-tau (n = 6), FTLD-TDP (n = 15), and control patients (n = 5). We validated these results in an independent patient cohort (total n = 24).

RESULTS

The middle frontal gyrus cortex proteome was most significantly altered in FTLD-tau compared to controls (294 differentially expressed proteins at FDR = 0.05). The proteomic modifications in FTLD-TDP were more heterogeneous (49 differentially expressed proteins at FDR = 0.1). Weighted co-expression network analysis revealed 17 modules of co-regulated proteins, 13 of which were dysregulated in FTLD-tau. These modules included proteins associated with oxidative phosphorylation, scavenger mechanisms, chromatin regulation, and clathrin-mediated transport in both the frontal and temporal cortex of FTLD-tau. The most strongly dysregulated subnetworks identified cyclin-dependent kinase 5 (CDK5) and polypyrimidine tract-binding protein 1 (PTBP1) as key players in the disease process. Dysregulation of 9 of these modules was confirmed in independent validation data sets of FLTD-tau and control temporal and frontal cortex (total n = 24). Dysregulated modules were primarily associated with changes in astrocyte and endothelial cell protein abundance levels, indicating pathological changes in FTD are not limited to neurons.

CONCLUSIONS

Using this innovative workflow and zooming in on the most strongly dysregulated proteins of the identified modules, we were able to identify disease-associated mechanisms in FTLD-tau with high potential as biomarkers and/or therapeutic targets.

Metabolic Syndrome as a Risk Factor for Alzheimer's Disease: A Focus on Insulin Resistance

Alzheimer's disease (AD) is the main type of dementia and is a disease with a profound socioeconomic burden due to the lack of effective treatment. In addition to genetics and environmental factors, AD is highly associated with metabolic syndrome, defined as the combination of hypertension, hyperlipidemia, obesity and type 2 diabetes mellitus (T2DM). Among these risk factors, the connection between AD and T2DM has been deeply studied. It has been suggested that the mechanism linking both conditions is insulin resistance. Insulin is an important hormone that regulates not only peripheral energy homeostasis but also brain functions, such as cognition. Insulin desensitization, therefore, could impact normal brain function increasing the risk of developing neurodegenerative disorders in later life. Paradoxically, it has been demonstrated that decreased neuronal insulin signalling can also have a protective role in aging and protein-aggregation-associated diseases, as is the case in AD. This controversy is fed by studies focused on neuronal insulin signalling. However, the role of insulin action on other brain cell types, such as astrocytes, is still unexplored. Therefore, it is worthwhile exploring the involvement of the astrocytic insulin receptor in cognition, as well as in the onset and/or development of AD.

Differential dysregulation of CREB and synaptic genes in transgenic Drosophila melanogaster expressing shaggy (GSK3), TauWT, or Amyloid-beta

BACKGROUND

Tau, Amyloid-beta (Aβ₄₂), and Glycogen synthase kinase 3 (GSK3) contribute to synaptic dysfunction observed in Alzheimer's disease (AD), the most common form of dementia. In the current study, the effect of pan-neuronal expression of Tau^WT, Aβ₄₂, or shaggy (orthologue of GSK3) in Drosophila melanogaster was assessed on the locomotor function, ethanol sensitivity, synaptic genes and CREB expression. The effect of Tau^WT and Aβ₄₂ on the expression of shaggy was also determined.

METHODS AND RESULTS

Gene expression analysis was performed using quantitative real-time RT-PCR method. While syt1, SNAP25 and CREB (upstream transcription factor of syt1 and SNAP25) were upregulated in flies expressing Tau^WT or Aβ_42, a prominent decline was observed in those genes in shaggy expressing flies. Although all transgenic flies showed climbing disability and higher sensitivity to ethanol, abnormality in these features was significantly more prominent in transgenic flies expressing shaggy compared to Tau^WT or Aβ₄₂. Despite a significant upregulation of shaggy transcription in Tau^WT expressing flies, Aβ₄₂ transgenic flies witnessed no significant changes.

CONCLUSIONS

Tau^WT, Aβ₄₂, and shaggy may affect synaptic plasticity through dysregulation of synaptic genes and CREB, independently. However shaggy has more detrimental effect on synaptic genes expression, locomotor ability and sensitivity to ethanol. It is important when it comes to drug discovery. It appears that CREB is a direct effector of changes in synaptic genes expression as they showed similar pattern of alteration and it is likely to be a part of compensatory mechanisms independent of the GSK3/CREB pathway in Tau^WT or Aβ₄₂ expressing flies.

ADAM10- and γ-secretase-dependent cleavage of the transmembrane protein PTPRT attenuates neurodegeneration in the mouse model of Alzheimer's disease

PTPRT (receptor-type tyrosine-protein phosphatase T), a brain-specific type 1 transmembrane protein, plays an important role in neurodevelopment and synapse formation. However, whether abnormal PTPRT signaling is associated with Alzheimer's disease (AD) remains elusive. Here, we report that Ptprt mRNA expression is found to be downregulated in the brains of both human and mouse models of AD. We further identified that the PTPRT intracellular domain (PICD), which is released by ADAM10- and γ-secretase-dependent cleavage of PTPRT, efficiently translocates to the nucleus via a conserved nuclear localization signal (NLS). We show that inhibition of nuclear translocation of PICD leads to an accumulation of phosphorylated signal transducer and activator of transcription 3 (pSTAT3), a substrate of PTPRT-eventually resulting in neuronal cell death. Consistently, RNA sequencing reveals that overexpression of PICD leads to changes in the expression of genes that are functionally associated with synapse formation, cell adhesion, and protein dephosphorylation. Moreover, overexpression of PICD not only decreases the level of phospho-STAT3^Y705 and amyloid β production in the hippocampus of APP/PS1 mice but also partially improves synaptic function and behavioral deficits in this mouse model of AD. These findings suggest that a novel role of the ADAM 10- and γ-secretase-dependent cleavage of PTPRT may alleviate the AD-like neurodegenerative processes.

Type 2 Diabetes Mellitus and its comorbidity, Alzheimer's disease: Identifying critical microRNA using machine learning

MicroRNAs (miRNAs) are critical regulators of gene expression in healthy and diseased states, and numerous studies have established their tremendous potential as a tool for improving the diagnosis of Type 2 Diabetes Mellitus (T2D) and its comorbidities. In this regard, we computationally identify novel top-ranked hub miRNAs that might be involved in T2D. We accomplish this via two strategies: 1) by ranking miRNAs based on the number of T2D differentially expressed genes (DEGs) they target, and 2) using only the common DEGs between T2D and its comorbidity, Alzheimer's disease (AD) to predict and rank miRNA. Then classifier models are built using the DEGs targeted by each miRNA as features. Here, we show the T2D DEGs targeted by hsa-mir-1-3p, hsa-mir-16-5p, hsa-mir-124-3p, hsa-mir-34a-5p, hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-129-2-3p, and hsa-mir-146a-5p are capable of distinguishing T2D samples from the controls, which serves as a measure of confidence in the miRNAs' potential role in T2D progression. Moreover, for the second strategy, we show other critical miRNAs can be made apparent through the disease's comorbidities, and in this case, overall, the hsa-mir-103a-3p models work well for all the datasets, especially in T2D, while the hsa-mir-124-3p models achieved the best scores for the AD datasets. To the best of our knowledge, this is the first study that used predicted miRNAs to determine the features that can separate the diseased samples (T2D or AD) from the normal ones, instead of using conventional non-biology-based feature selection methods.

The major TMEM106B dementia risk allele affects TMEM106B protein levels and myelin lipid homeostasis in the ageing human hippocampus

Background The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases. Methods Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Results Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. Transmembrane protein 106B (TMEM106B), a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with age was specific to carriers of the rs1990622-A allele in the TMEM106B gene that is associated with increased risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype. Conclusions Our study provides the first evidence that TMEM106B protein abundance is increased with brain ageing in humans, and the first evidence that the major TMEM106B dementia risk allele affects brain lipid homeostasis, with a clear effect on myelin lipid content. Our data implies that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

Molecular subtypes of ALS are associated with differences in patient prognosis

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with poorly understood clinical heterogeneity, underscored by significant differences in patient age at onset, symptom progression, therapeutic response, disease duration, and comorbidity presentation. We perform a patient stratification analysis to better understand the variability in ALS pathology, utilizing postmortem frontal and motor cortex transcriptomes derived from 208 patients. Building on the emerging role of transposable element (TE) expression in ALS, we consider locus-specific TEs as distinct molecular features during stratification. Here, we identify three unique molecular subtypes in this ALS cohort, with significant differences in patient survival. These results suggest independent disease mechanisms drive some of the clinical heterogeneity in ALS.

Boosting of tau protein aggregation by CD40 and CD48 gene expression in Alzheimer's disease

Neurodegenerative diseases result from the interplay of abnormal gene expression and various pathological factors. Therefore, a disease-specific integrative genetic approach is required to understand the complexities and causes of target diseases. Recent studies have identified the correlation between genes encoding several transmembrane proteins, such as the cluster of differentiation (CD) and Alzheimer's disease (AD) pathogenesis. In this study, CD48 and CD40 gene expression in AD, a neurodegenerative disease, was analyzed to infer this link. Total RNA sequencing was performed using an Alzheimer's disease mouse model brain and blood, and gene expression was determined using a genome-wide association study (GWAS). We observed a marked elevation of CD48 and CD40 genes in Alzheimer's disease. Indeed, the upregulation of both CD48 and CD40 genes was significantly increased in the severe Alzheimer's disease group. With the elevation of CD48 and CD40 genes in Alzheimer's disease, associations of protein levels were also markedly increased in tissues. In addition, overexpression of CD48 and CD40 genes triggered tau aggregation, and co-expression of these genes accelerated aggregation. The nuclear factor kappa B (NF-ĸB) signaling pathway was enriched by CD48 and CD40 gene expression: it was also associated with tau pathology. Our data suggested that the CD48 and CD40 genes are novel AD-related genes, and this approach may be useful as a diagnostic or therapeutic target for the disease.