Analysis of microRNA and Gene Expression Profiles in Alzheimer's Disease: A Meta-Analysis Approach

Age-Related Aspects of Sex Differences in Event-Related Brain Oscillatory Responses: A Turkish Study

Earlier research has suggested gender differences in event-related potentials/oscillations (ERPs/EROs). Yet, the alteration in event-related oscillations (EROs) in the delta and theta frequency bands have not been explored between genders across the three age groups of adulthood, i.e., 18-50, 51-65, and >65 years. Data from 155 healthy elderly participants who underwent a neurological examination, comprehensive neuropsychological assessment (including attention, memory, executive function, language, and visuospatial skills), and magnetic resonance imaging (MRI) from past studies were used. The delta and theta ERO powers across the age groups and between genders were compared and correlational analyses among the ERO power, age, and neuropsychological tests were performed. The results indicated that females displayed higher theta ERO responses than males in the frontal, central, and parietal regions but not in the occipital location between 18 and 50 years of adulthood. The declining theta power of EROs in women reached that of men after the age of 50 while the theta ERO power was more stable across the age groups in men. Our results imply that the cohorts must be recruited at specified age ranges across genders, and clinical trials using neurophysiological biomarkers as an intervention endpoint should take gender into account in the future.

miRNAs in cerebrospinal fluid associated with Alzheimer's disease: A systematic review and pathway analysis using a data mining and machine learning approach

Alzheimer's disease (AD) is the most common type and accounts for 60%-70% of the reported cases of dementia. MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene expression regulation. Although the diagnosis of AD is primarily clinical, several miRNAs have been associated with AD and considered as potential markers for diagnosis and progression of AD. We sought to match AD-related miRNAs in cerebrospinal fluid (CSF) found in the GeoDataSets, evaluated by machine learning, with miRNAs listed in a systematic review, and a pathway analysis. Using machine learning approaches, we identified most differentially expressed miRNAs in Gene Expression Omnibus (GEO), which were validated by the systematic review, using the acronym PECO-Population (P): Patients with AD, Exposure (E): expression of miRNAs, Comparison (C): Healthy individuals, and Objective (O): miRNAs differentially expressed in CSF. Additionally, pathway enrichment analysis was performed to identify the main pathways involving at least four miRNAs selected. Four miRNAs were identified for differentiating between patients with and without AD in machine learning combined to systematic review, and followed the pathways analysis: miRNA-30a-3p, miRNA-193a-5p, miRNA-143-3p, miRNA-145-5p. The pathways epidermal growth factor, MAPK, TGF-beta and ATM-dependent DNA damage response, were regulated by these miRNAs, but only the MAPK pathway presented higher relevance after a randomic pathway analysis. These findings have the potential to assist in the development of diagnostic tests for AD using miRNAs as biomarkers, as well as provide understanding of the relationship between different pathophysiological mechanisms of AD.

ReHoGCNES-MDA: prediction of miRNA-disease associations using homogenous graph convolutional networks based on regular graph with random edge sampler

Numerous investigations increasingly indicate the significance of microRNA (miRNA) in human diseases. Hence, unearthing associations between miRNA and diseases can contribute to precise diagnosis and efficacious remediation of medical conditions. The detection of miRNA-disease linkages via computational techniques utilizing biological information has emerged as a cost-effective and highly efficient approach. Here, we introduced a computational framework named ReHoGCNES, designed for prospective miRNA-disease association prediction (ReHoGCNES-MDA). This method constructs homogenous graph convolutional network with regular graph structure (ReHoGCN) encompassing disease similarity network, miRNA similarity network and known MDA network and then was tested on four experimental tasks. A random edge sampler strategy was utilized to expedite processes and diminish training complexity. Experimental results demonstrate that the proposed ReHoGCNES-MDA method outperforms both homogenous graph convolutional network and heterogeneous graph convolutional network with non-regular graph structure in all four tasks, which implicitly reveals steadily degree distribution of a graph does play an important role in enhancement of model performance. Besides, ReHoGCNES-MDA is superior to several machine learning algorithms and state-of-the-art methods on the MDA prediction. Furthermore, three case studies were conducted to further demonstrate the predictive ability of ReHoGCNES. Consequently, 93.3% (breast neoplasms), 90% (prostate neoplasms) and 93.3% (prostate neoplasms) of the top 30 forecasted miRNAs were validated by public databases. Hence, ReHoGCNES-MDA might serve as a dependable and beneficial model for predicting possible MDAs.

MiRNA let-7d-5p Alleviates Inflammatory Responses by Targeting Map3k1 and Inactivating ERK/p38 MAPK Signaling in Microglia

Alzheimer's disease (AD) is the most common form of dementia. Aberrant regulation of microRNAs (miRNAs) has been implicated in the pathogenesis of AD. In a large case-control study recruiting 208 patients with AD and 205 elderly control subjects, miRNA-let-7d-5p attracted our attention for its downregulated level in patients with AD. However, the biological functions of let-7d-5p in AD pathogenesis have not been investigated. This study emphasized the functions and mechanisms of let-7d-5p in the pathogenesis of AD. Mouse microglial BV2 cells treated with amyloid-β (Aβ)1-42 were used as in vitro AD inflammation models. We reported that let-7d-5p was downregulated in Aβ1-42-stimulated BV2 cells, and upregulation of let-7d-5p promoted the transversion of microglial cells from Ml phenotype to M2 phenotype. Then, the binding relationship between let-7d-5p and Map3k1 was verified by luciferase reporter assays. Mechanistically, let-7d-5p could target Map3k1 3'UTR to inactivate ERK/p38 MAPK signaling. Therefore, it was suggested that let-7d-5p might be a novel modulator of microglial neuroinflammation and serve as a novel target for diagnosis and treatment of AD.

Gene Co-Expression Analysis of Multiple Brain Tissues Reveals Correlation of FAM222A Expression with Multiple Alzheimer's Disease-Related Genes

Background

Alzheimer's disease (AD) is the most common form of dementia in the elderly marked by central nervous system (CNS) neuronal loss and amyloid plaques. FAM222A, encoding an amyloid plaque core protein, is an AD brain atrophy susceptibility gene that mediates amyloid-β aggregation. However, the expression interplay between FAM222A and other AD-related pathway genes is unclear.

Objective

Our goal was to study FAM222A's whole-genome co-expression profile in multiple tissues and investigate its interplay with other AD-related genes.

Methods

We analyzed gene expression correlations in Genotype-Tissue Expression (GTEx) tissues to identify FAM222A co-expressed genes and performed functional enrichment analysis on identified genes in CNS system.

Results

Genome-wide gene expression profiling identified 673 genes significantly correlated with FAM222A (p < 2.5×10-6) in 48 human tissues, including 298 from 13 CNS tissues. Functional enrichment analysis revealed that FAM222A co-expressed CNS genes were enriched in multiple AD-related pathways. Gene co-expression network analysis for identified genes in each brain region predicted other disease associated genes with similar biological function. Furthermore, co-expression of 25 out of 31 AD-related pathways genes with FAM222A was replicated in brain samples from 107 aged subjects from the Aging, Dementia and TBI Study.

Conclusion

This gene co-expression study identified multiple AD-related genes that are associated with FAM222A, indicating that FAM222A and AD-associated genes can be active simultaneously in similar biological processes, providing evidence that supports the association of FAM222A with AD.

Epigenetics of Alzheimer’s Disease: Past, Present and Future

Alzheimer’s disease (AD) exemplifies a looming epidemic lacking effective treatment and manifests with the accumulation of neurofibrillary tangles, amyloid-β plaques, neuroinflammation, behavioral changes, and acute cognitive impairments. It is a complex, multifactorial disorder that arises from the intricate interaction between environment and genetic factors, restrained via epigenetic machinery. Though the research progress has improved the understanding of clinical manifestations and disease advancement, the causal mechanism of detrimental consequences remains undefined. Despite the substantial improvement in recent diagnostic modalities, it is challenging to distinguish AD from other forms of dementia. Accurate diagnosis is a major glitch in AD as it banks on the symptoms and clinical criteria. Several studies are underway in exploring novel and reliable biomarkers for AD. In this direction, epigenetic alterations have transpired as key modulators in AD pathogenesis with the impeding inferences for the management of this neurological disorder. The present chapter aims to discuss the significance of epigenetic modifications reported in the pathophysiology of AD such as DNA methylation, hydroxy-methylation, methylation of mtDNA, histone modifications, and noncoding RNAs. Additionally, the chapter also describes the possible therapeutic avenues that target epigenetic modifications in AD.

Amplification-free microRNA profiling with femtomolar sensitivity on a plasmonic enhanced fluorescence nano-chip

MicroRNAs (miRNAs) are a class of small, non-coding RNA molecules involved in the regulation of gene expression, thus considered as promising biomarkers for cancer, cardiovascular diseases, neurodegenerative diseases, etc. However, quantitative analysis of miRNAs faces challenges owing to their high homology, small size & ultra-low abundance, and disease occurrence is often related to abnormal expression of multiple miRNAs where method for parallel miRNAs analysis is required. In this work, multiplexed analysis of miRNAs was established on a plasmonic nano-chip capable of fluorescence enhancement in the near-infrared region. Combined with polyadenylation at the hydroxyl terminate of target miRNA to afford abundant sites for fluorophore labeling, our assay achieved amplification-free detection of miRNAs from nM to fM with the limit of detection down to ca. 5 fM. A miRNA panel was constructed to detect 10 miRNAs differentially expressed in MCF-7 and A549 cell lines and validated with qRT-PCR, demonstrating the practical application of this method. This scalable platform can be customized for different miRNA panels, facilitating multiple miRNA profiling for various diseases.

Prioritization of risk genes for Alzheimer's disease: an analysis framework using spatial and temporal gene expression data in the human brain based on support vector machine

Background: Alzheimer's disease (AD) is a complex disorder, and its risk is influenced by multiple genetic and environmental factors. In this study, an AD risk gene prediction framework based on spatial and temporal features of gene expression data (STGE) was proposed. Methods: We proposed an AD risk gene prediction framework based on spatial and temporal features of gene expression data. The gene expression data of providers of different tissues and ages were used as model features. Human genes were classified as AD risk or non-risk sets based on information extracted from relevant databases. Support vector machine (SVM) models were constructed to capture the expression patterns of genes believed to contribute to the risk of AD. Results: The recursive feature elimination (RFE) method was utilized for feature selection. Data for 64 tissue-age features were obtained before feature selection, and this number was reduced to 19 after RFE was performed. The SVM models were built and evaluated using 19 selected and full features. The area under curve (AUC) values for the SVM model based on 19 selected features (0.740 [0.690-0.790]) and full feature sets (0.730 [0.678-0.769]) were very similar. Fifteen genes predicted to be risk genes for AD with a probability greater than 90% were obtained. Conclusion: The newly proposed framework performed comparably to previous prediction methods based on protein-protein interaction (PPI) network properties. A list of 15 candidate genes for AD risk was also generated to provide data support for further studies on the genetic etiology of AD.

Exosomal Circular Ribonucleic Acid-Microribonucleic Acid Expression Profile from Plasma in Alzheimer's Disease Patients by Bioinformatics and Integrative Analysis

OBJECTIVE

Alzheimer's disease is a neurodegenerative sickness and increasing with age throughout the world. A substantial body of evidence suggests the role of exosomal noncoding ribonucleic acids in the development of Alzheimer's disease, but the regulatory mechanisms mediated by these noncoding ribonucleic acids remain extensively unknown. Using plasma samples from Alzheimer's disease patients, this study explored the exosomal circular ribonucleic acid-microribonucleic acid profiles.

MATERIALS AND METHODS

The ArrayExpress platform was used to convey data from 3 samples from each group (healthy, mild cognitive impairment, and Alzheimer's disease). Using plasma exosomes, differentially expressed microribonucleic acids and differentially expressed circular ribonucleic acids were compared between the Alzheimer's disease and mild cognitive impairment groups. Afterward, to define pathways, gene ontologies, and networks, differentially expressed microribonucleic acids and differentially expressed circular ribonucleic acids common to both mild cognitive impairment and Alzheimer's disease groups were analyzed. Eventually, the selection of hub genes and protein-protein interaction network was analyzed.

RESULTS

A total of common 19 (7 upregulated and 12 downregulated) differentially expressed microribonucleic acids and 24 differentially expressed circular ribonucleic acids were recognized. A total of 4559 target genes were predicted for upregulated differentially expressed microribonucleic acids, while 6504 target genes were identified for downregulated differentially expressed microribonucleic acids, and most of the target genes involved in the phosphoinositide 3-kinases-Akt pathway and that were mostly regulated by hsa-mir-374a-3p, mir-196a-5p, let-205-5p, mir-185-3p, mir-374a-5p, mir-615-3p, let-7c-5p, mir-185-5p. Additionally, 9 hub genes (HSP90AA, ACTB, MAPK1, GSK3B, CCNE2, CDK6, AKT1, IGF1R, CCND1) were revealed as the genes considerably related to Alzheimer's disease by a protein-protein interaction network using the cytohubba in Cytoscape software.

CONCLUSION

Our findings provide a new perspective on how microribonucleic acids could connect with circular ribonucleic acids in the pathogenesis of Alzheimer's disease.

Insights into Sex and Gender Differences in Brain and Psychopathologies Using Big Data

The societal implication of sex and gender (SG) differences in brain are profound, as they influence brain development, behavior, and importantly, the presentation, prevalence, and therapeutic response to diseases. Technological advances have enabled speed up identification and characterization of SG differences during development and in psychopathologies. The main aim of this review is to elaborate on new technological advancements, such as genomics, imaging, and emerging biobanks, coupled with bioinformatics analyses of data generated from these technologies have facilitated the identification and characterization of SG differences in the human brain through development and psychopathologies. First, a brief explanation of SG concepts is provided, along with a developmental and evolutionary context. We then describe physiological SG differences in brain activity and function, and in psychopathologies identified through imaging techniques. We further provide an overview of insights into SG differences using genomics, specifically taking advantage of large cohorts and biobanks. We finally emphasize how bioinformatics analyses of big data generated by emerging technologies provides new opportunities to reduce SG disparities in health outcomes, including major challenges.

Exploring the mechanism of action of Hedyotis diffusa Willd on acne using network analysis

In this study, we used a network pharmacological method to explore the active ingredients of Hedyotis diffusa Willd (HDW) in the treatment of acne and elucidated the physiological mechanisms in the human body in which they are involved. We identified the active compounds of HDW that are expected to act effectively in the human body using the Traditional Chinese Medicine Systems Pharmacology database and analysis platform and extracted potential interacting proteins for each active compound using the Swiss Target Prediction platform. Next, we analyzed the potential mechanisms of action of the protein targets shared by HDW and each standard drug on acne and assessed the possibility of spontaneous occurrence of the binding between proteins and active compounds through the molecular docking process. Seven active compounds were selected according to the oral bioavailability and drug-likeness criteria of the Traditional Chinese Medicine Systems Pharmacology database and analysis platform. Subsequently, 300 protein targets were collected from the Swiss Target Prediction. Using the Search Tool for the Retrieval of Interacting Genes/Proteins database, a protein-protein interaction network was constructed by analyzing the relationship between HDW, acne, and each standard drug. By analyzing the gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway, the "positive regulation of lipid metabolic process" was found to be the most involved pathway shared by HDW, acne, and isotretinoin. An analysis of the protein targets shared by the antibiotic agents with HDW and acne found that "cholesterol storage" in tetracycline, "icosacoid transport" in azithromycin, "steroid hydroxylase activity" in erythromycin, "positive regulation of leukocyte tethering or rolling" in clindamycin, "response to UV-A" in minocycline, "steroid 11-beta-monooxygenase activity" in doxycycline, and "neutrophil-mediated immunity" in trimethoprim were the most involved. Virtual molecular docking analysis showed that all proteins spontaneously bound to their corresponding active compounds. Our analysis suggests that HDW can, directly and indirectly, suppress sebum secretion and exert antiinflammatory effects on acne. Further, HDW may regulate free radicals and suppress apoptosis. Therefore, HDW can be used as an alternative or supplement to standard drugs for acne treatment in patients who cannot use standard treatments due to side effects.

Microglia specific deletion of miR-155 in Alzheimer's disease mouse models reduces amyloid-β pathology but causes hyperexcitability and seizures

Alzheimer's Disease (AD) is characterized by the accumulation of extracellular amyloid-β (Aβ) as well as CNS and systemic inflammation. Microglia, the myeloid cells resident in the CNS, use microRNAs to rapidly respond to inflammatory signals. MicroRNAs (miRNAs) modulate inflammatory responses in microglia, and miRNA profiles are altered in Alzheimer's disease (AD) patients. Expression of the pro-inflammatory miRNA, miR-155, is increased in the AD brain. However, the role of miR-155 in AD pathogenesis is not well-understood. We hypothesized that miR-155 participates in AD pathophysiology by regulating microglia internalization and degradation of Aβ. We used CX3CR1CreER/+ to drive-inducible, microglia-specific deletion of floxed miR-155 alleles in two AD mouse models. Microglia-specific inducible deletion of miR-155 in microglia increased anti-inflammatory gene expression while reducing insoluble Aβ1-42 and plaque area. Yet, microglia-specific miR-155 deletion led to early-onset hyperexcitability, recurring spontaneous seizures, and seizure-related mortality. The mechanism behind hyperexcitability involved microglia-mediated synaptic pruning as miR-155 deletion altered microglia internalization of synaptic material. These data identify miR-155 as a novel modulator of microglia Aβ internalization and synaptic pruning, influencing synaptic homeostasis in the setting of AD pathology.

Analysis of gene expression profiles in Alzheimer's disease patients with different lifespan: A bioinformatics study focusing on the disease heterogeneity

Objective

Alzheimer's disease (AD) as the most frequent neurodegenerative disease is featured by gradual decline of cognition and social function in the elderly. However, there have been few studies focusing on AD heterogeneity which exists both genetically and clinically, leading to the difficulties of AD researches. As one major kind of clinical heterogeneity, the lifespan of AD patients varies significantly. Aiming to investigate the potential driving factors, the current research identified the differentially expressed genes (DEGs) between longer-lived AD patients and shorter-lived ones via bioinformatics analyses.

Methods

Qualified datasets of gene expression profiles were identified in National Center of Biotechnology Information Gene Expression Omnibus (NCBI-GEO). The data of the temporal lobes of patients above 60 years old were used. Two groups were divided according to the lifespan: the group ≥85 years old and the group <85 years old. Then GEO2R online software and R package of Robust Rank Aggregation (RRA) were used to screen DEGs. Bioinformatic tools were adopted to identify possible pathways and construct protein-protein interaction network.

Result

Sixty-seven AD cases from four qualified datasets (GSE28146, GSE5281, GSE48350, and GSE36980) were included in this study. 740 DEGs were identified with 361 upregulated and 379 downregulated when compared longer-lived AD patients with shorter-lived ones. These DEGs were primarily involved in the pathways directly or indirectly associated with the regulation of neuroinflammation and cancer pathogenesis, as shown by pathway enrichment analysis. Among the DEGs, the top 15 hub genes were identified from the PPI network. Notably, the same bioinformatic procedures were conducted in 62 non-AD individuals (serving as controls of AD patients in the four included studies) with distinctly different findings from AD patients, indicating different regulatory mechanisms of lifespan between non-AD controls and AD, reconfirming the necessity of the present study.

Conclusion

These results shed some lights on lifespan-related regulatory mechanisms in AD patients, which also indicated that AD heterogeneity should be more taken into account in future investigations.

Bioinformatics approach to analyse COVID-19 biomarkers accountable for generation of intracranial aneurysm in COVID-19 patients

COVID-19 became a health emergency on January 30, 2020. SARS-CoV-2 is the causative agent of the coronavirus disease known as COVID-19 and can develop cardiometabolic and neurological disorders. Intracranial aneurysm (IA) is considered the most significant reason for hemorrhagic stroke,and it accounts for approximately 85% of all subarachnoid hemorrhages (SAH). Retinoid signaling abnormalities may explain COVID-19's pathogenesis with inhibition of AEH2, from which COVID-19 infection may enhance aneurysm formation and rupture due to abrupt blood pressure changes, endothelial cell injury, and systemic inflammation. The objective of this study was to investigate the potential biomarkers, differentially expressed genes (DEGs), and metabolic pathways associated with both COVID-19 and intracranial aneurysm (IA) using simulation databases like DIsGeNET. The purpose was to confirm prior findings and gain a comprehensive understanding of the underlying mechanisms that contribute to the development of these conditions. We combined the regulated genes to describe intracranial aneurysm formation in COVID-19. To determine DEGs in COVID-19 and IA patient tissues, we compared gene expression transcriptomic datasets from healthy and diseased individuals. There were 41 differentially expressed genes (DEGs) shared by both the COVID-19 and IA datasets (27 up-regulated genes and 14 down-regulated genes). Using protein-protein interaction analysis, we were able to identify hub proteins (C3, NCR1, IL10RA, OXTR, RSAD2, CD38, IL10RB, MX1, IL10, GFAP, IFIT3, XAF1, USP18, OASL, IFI6, EPSTI1, CMPK2, and ISG15), which were not described as key proteins for both COVID-19 and IA before. We also used Gene Ontology analysis (6 significant ontologies were validated), Pathway analysis (the top 20 were validated), TF-Gene interaction analysis, Gene miRNA analysis, and Drug-Protein interaction analysis methods to comprehend the extensive connection between COVID-19 and IA. In Drug-Protein interaction analysis, we have gotten the following three drugs: LLL-3348, CRx139, and AV41 against IL10 which was both common for COVID-19 and IA disease. Our study with different cabalistic methods has showed the interaction between the proteins and pathways with drug analysis which may direct further treatment development for certain diseases.

Epigenetic Changes in Prion and Prion-like Neurodegenerative Diseases: Recent Advances, Potential as Biomarkers, and Future Perspectives

Prion diseases are transmissible spongiform encephalopathies (TSEs) caused by a conformational conversion of the native cellular prion protein (PrP^C) to an abnormal, infectious isoform called PrP^Sc. Amyotrophic lateral sclerosis, Alzheimer’s, Parkinson’s, and Huntington’s diseases are also known as prion-like diseases because they share common features with prion diseases, including protein misfolding and aggregation, as well as the spread of these misfolded proteins into different brain regions. Increasing evidence proposes the involvement of epigenetic mechanisms, namely DNA methylation, post-translational modifications of histones, and microRNA-mediated post-transcriptional gene regulation in the pathogenesis of prion-like diseases. Little is known about the role of epigenetic modifications in prion diseases, but recent findings also point to a potential regulatory role of epigenetic mechanisms in the pathology of these diseases. This review highlights recent findings on epigenetic modifications in TSEs and prion-like diseases and discusses the potential role of such mechanisms in disease pathology and their use as potential biomarkers.

MicroRNA: A Linking between Astrocyte Dysfunction, Mild Cognitive Impairment, and Neurodegenerative Diseases

Simple Summary

Neurodegenerative diseases are complex neurological disorders with a high incidence worldwide in older people, increasing hospital visits and requiring expensive treatments. As a precursor phase of neurodegenerative diseases, cognitive impairment needs to be studied to understand the factors that influence its development and improve patients’ quality of life. The present review compiles possible factors and biomarkers for diagnosing mild cognitive impairment based on the most recent studies involving miRNAs. These molecules can direct the gene expression in multiple cells, affecting their behavior under certain conditions, such as stressing factors. This review encourages further research into biomarkers that identify cognitive impairment in cellular models such as astrocytes, which are brain cells capable of maintaining the optimal conditions for the central nervous system functioning.

Abstract

The importance of miRNAs in cellular processes and their dysregulation has taken significant importance in understanding different pathologies. Due to the constant increase in the prevalence of neurodegenerative diseases (ND) worldwide and their economic impact, mild cognitive impairment (MCI), considered a prodromal phase, is a logical starting point to study this public health problem. Multiple studies have established the importance of miRNAs in MCI, including astrocyte regulation during stressful conditions. Additionally, the protection mechanisms exerted by astrocytes against some damage in the central nervous system (CNS) lead to astrocytic reactivation, in which a differential expression of miRNAs has been shown. Nevertheless, excessive reactivation can cause neurodegeneration, and a clear pattern defining the equilibrium point between a neuroprotective or detrimental astrocytic phenotype is unknown. Therefore, the miRNA expression has gained significant attention to understand the maintenance of brain balance and improve the diagnosis and treatment at earlier stages in the ND. Here, we provide a comprehensive review of the emerging role of miRNAs in cellular processes that contribute to the loss of cognitive function, including lipotoxicity, which can induce chronic inflammation, also considering the fundamental role of astrocytes in brain homeostasis.

Modelling the Human Blood-Brain Barrier in Huntington Disease

While blood–brain barrier (BBB) dysfunction has been described in neurological disorders, including Huntington’s disease (HD), it is not known if endothelial cells themselves are functionally compromised when promoting BBB dysfunction. Furthermore, the underlying mechanisms of BBB dysfunction remain elusive given the limitations with mouse models and post mortem tissue to identify primary deficits. We established models of BBB and undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived brain-like microvascular endothelial cells (iBMEC) from HD patients or unaffected controls. We demonstrated that HD-iBMECs have abnormalities in barrier properties, as well as in specific BBB functions such as receptor-mediated transcytosis.

Patient-Derived Fibroblasts With Presenilin-1 Mutations, That Model Aspects of Alzheimer’s Disease Pathology, Constitute a Potential Object for Early Diagnosis

Alzheimer’s disease (AD), a neurodegenerative disorder that can occur in middle or old age, is characterized by memory loss, a continuous decline in thinking, behavioral and social skills that affect the ability of an individual to function independently. It is divided into sporadic and familial subtypes. Early-onset familial AD (FAD) is linked to mutations in genes coding for the amyloid-β protein precursor (AβPP), presenilin 1 (PS1), and presenilin 2 (PS2), which lead to alterations in AβPP processing, generation of the Amyloid-β peptide and hyperphosphorylation of tau protein. Identification of early biomarkers for AD diagnosis represents a challenge, and it has been suggested that molecular changes in neurodegenerative pathways identified in the brain of AD patients can be detected in peripheral non-neural cells derived from familial or sporadic AD patients. In the present study, we determined the protein expression, the proteomic and in silico characterization of skin fibroblasts from FAD patients with PS1 mutations (M146L or A246E) or from healthy individuals. Our results shown that fibroblasts from AD patients had increased expression of the autophagy markers LC3II, LAMP2 and Cathepsin D, a significant increase in total GSK3, phosphorylated ERK1/2 (Thr202/Tyr204) and phosphorylated tau (Thr231, Ser396, and Ser404), but no difference in the phosphorylation of Akt (Ser473) or the α (Ser21) and β (Ser9) GSK3 isoforms, highlighting the relevant role of abnormal protein post-translational modifications in age-related neurodegenerative diseases, such as AD. Both 2-DE gels and mass spectrometry showed significant differences in the expression of the signaling pathways associated with protein folding and the autophagic pathway mediated by chaperones with the expression of HSPA5, HSPE1, HSPD1, HSP90AA1, and HSPE1 and reticular stress in the FAD samples. Furthermore, expression of the heat shock proteins HSP90 and HSP70 was significantly higher in the cells from AD patients as confirmed by Western blot. Taken together our results indicate that fibroblasts from patients with FAD-PS1 present alterations in signaling pathways related to cellular stress, autophagy, lysosomes, and tau phosphorylation. Fibroblasts can therefore be useful in modeling pathways related to neurodegeneration, as well as for the identification of early AD biomarkers.

Differentially Expressed miRNAs in Age-Related Neurodegenerative Diseases: A Meta-Analysis

To date, no neurodegenerative diseases (NDDs) have cures, and the underlying mechanism of their pathogenesis is undetermined. As miRNAs extensively regulate all biological processes and are crucial regulators of healthy brain function, miRNAs differentially expressed in NDDs may provide insight into the factors that contribute to the emergence of protein inclusions and the propagation of deleterious cellular environments. A meta-analysis of miRNAs dysregulated in Alzheimer’s disease, Parkinson’s disease, multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, dementia with Lewy bodies and frontotemporal lobar degeneration (TDP43 variant) was performed to determine if diseases within a proteinopathy have distinct or shared mechanisms of action leading to neuronal death, and if proteinopathies can be classified on the basis of their miRNA profiles. Our results identified both miRNAs distinct to the anatomy, disease type and pathology, and miRNAs consistently dysregulated within single proteinopathies and across neurodegeneration in general. Our results also highlight the necessity to minimize the variability between studies. These findings showcase the need for more transcriptomic research on infrequently occurring NDDs, and the need for the standardization of research techniques and platforms utilized across labs and diseases.

Plasma microRNA vary in association with the progression of Alzheimer's disease

Introduction

Early intervention in Alzheimer's disease (AD) requires the development of an easily administered test that is able to identify those at risk. Focusing on microRNA robustly detected in plasma and standardizing the analysis strategy, we sought to identify disease‐stage specific biomarkers.

Methods

Using TaqMan microfluidics arrays and a statistical consensus approach, we assessed plasma levels of 185 neurodegeneration‐related microRNA, in cohorts of cognitively normal amyloid β‐positive (CN‐Aβ+), mild cognitive impairment (MCI), and Alzheimer's disease (AD) participants, relative to their respective controls.

Results

Distinct disease stage microRNA biomarkers were identified, shown to predict membership of the groups (area under the curve [AUC] >0.8) and were altered dynamically with AD progression in a longitudinal study. Bioinformatics demonstrated that these microRNA target known AD‐related pathways, such as the Phosphoinositide 3‐kinase (PI3K‐Akt) signalling pathway. Furthermore, a significant correlation was found between miR‐27a‐3p, miR‐27b‐3p, and miR‐324‐5p and amyloid beta load.

Discussion

Our results show that microRNA signatures alter throughout the progression of AD, reflect the underlying disease pathology, and may prove to be useful diagnostic markers.

Systematic Review: microRNAs as Potential Biomarkers in Mild Cognitive Impairment Diagnosis

The rate of progression from Mild Cognitive Impairment (MCI) to Alzheimer's disease (AD) is estimated at >10% per year, reaching up to 80-90% after 6 years. MCI is considered an indicator of early-stage AD. In this context, the diagnostic screening of MCI is crucial for detecting individuals at high risk of AD before they progress and manifest further severe symptoms. Typically, MCI has been determined using neuropsychological assessment tools such as the Montreal Cognitive Assessment (MoCA) or Mini-Mental Status Examination (MMSE). Unfortunately, other diagnostic methods are not available or are unable to identify MCI in its early stages. Therefore, identifying new biomarkers for MCI diagnosis and prognosis is a significant challenge. In this framework, miRNAs in serum, plasma, and other body fluids have emerged as a promising source of biomarkers for MCI and AD-related cognitive impairments. Interestingly, miRNAs can regulate several signaling pathways via multiple and diverse targets in response to pathophysiological stimuli. This systematic review aims to describe the current state of the art regarding AD-related target genes modulated by differentially expressed miRNAs in peripheral fluids samples in MCI subjects to identify potential miRNA biomarkers in the early stages of AD. We found 30 articles that described five miRNA expression profiles from peripheral fluid in MCI subjects, showing possible candidates for miRNA biomarkers that may be followed up as fluid biomarkers or therapeutic targets of early-stage AD. However, additional research is needed to validate these miRNAs and characterize the precise neuropathological mechanisms.

Identification of altered exosomal microRNAs and mRNAs in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by decreased memory and cognitive functions. Exosomes carry a variety of important information such as proteins, lipids, DNA and RNA of mother cells. It is reported that exosomes play critical roles in nervous system physiology and neurodegenerative diseases. However, the functions of exosomes in AD progression are not fully elucidated. In this study, we detected the expression pattern of mRNAs and miRNAs in exosomes derived from the AD and health mice. A total of 1320 mRNAs and 29 miRNAs were differentially expressed in exosomes between the two groups. Subsequently, the downregulation of Chi3l1 and upregulation of Rhog in AD mice were verified by qRT-PCR. Meanwhile, the downregulation of miR-148a-5p and upregulation of miR-27a-5p in AD group were also tested by qRT-PCR. The functions of differentially expressed mRNAs and potential target genes of miRNAs were determined by GO and KEGG analysis. According to the ceRNA hypothesis, we established an integrated ceRNA network of circRNA-lncRNA-miRNA-mRNA. In conclusion, exosomal lncRNAs, mRNAs, circRNAs and miRNAs were identified to participate in the progression of AD which might be possible biomarkers and therapeutic targets for AD.

Improving the Classification of Alzheimer's Disease Using Hybrid Gene Selection Pipeline and Deep Learning

Alzheimer’s is a progressive, irreversible, neurodegenerative brain disease. Even with prominent symptoms, it takes years to notice, decode, and reveal Alzheimer’s. However, advancements in technologies, such as imaging techniques, help in early diagnosis. Still, sometimes the results are inaccurate, which delays the treatment. Thus, the research in recent times focused on identifying the molecular biomarkers that differentiate the genotype and phenotype characteristics. However, the gene expression dataset’s generated features are huge, 1,000 or even more than 10,000. To overcome such a curse of dimensionality, feature selection techniques are introduced. We designed a gene selection pipeline combining a filter, wrapper, and unsupervised method to select the relevant genes. We combined the minimum Redundancy and maximum Relevance (mRmR), Wrapper-based Particle Swarm Optimization (WPSO), and Auto encoder to select the relevant features. We used the GSE5281 Alzheimer’s dataset from the Gene Expression Omnibus We implemented an Improved Deep Belief Network (IDBN) with simple stopping criteria after choosing the relevant genes. We used a Bayesian Optimization technique to tune the hyperparameters in the Improved Deep Belief Network. The tabulated results show that the proposed pipeline shows promising results.

Upregulation of miR‑335 exerts protective effects against sepsis‑induced myocardial injury

Septicemia is associated with excessive inflammation, oxidative stress and apoptosis, causing myocardial injury that results in high mortality and disability rates worldwide. The abnormal expression of multiple microRNAs (miRNAs/miRs) is associated with more severe sepsis‑induced myocardial injury (SIMI) and miR‑335 has been shown to protect cardiomyocytes from oxidative stress. The present study aimed to investigate the role of miR‑335 in SIMI. An SIMI model was established by cecal ligation and puncture (CLP) in mice. An miRNA‑335 precursor (pre‑miR‑335) was transfected to accelerate miR‑335 expression and an miR‑335 inhibitor (anti‑miR‑335) was used to inhibit miR‑335 expression. CLP or sham surgery was performed on pre‑miR‑335, anti‑miR‑335 and wild‑type mice and miR‑335 expression was determined by reverse transcription‑quantitative PCR. Inflammatory factors (TNF‑α, IL‑6 and IL‑10) and troponin (cTNI), brain natriuretic peptide (BNP), creatine kinase (CK), lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) were assessed using commercial kits. Apoptosis was detected by flow cytometry and cardiac function was assessed using a Langendorff isolated cardiac perfusion system. miR‑335 expression was upregulated and an elevation in inflammatory factors and cTNI, BNP, CK, LDH and AST was observed. Compared with the wild‑type control group, pre‑miR‑335 mice treated with CLP exhibited significantly reduced left ventricular development pressure, maximum pressure increased reduction rates, as well as decreased levels of TNF‑α, IL‑6 and IL‑10, myocardial injury and apoptosis; by contrast, these features were amplified in CLP‑treated anti‑miR‑335 mice. In conclusion, the upregulation of miR‑335 exerted ameliorative effects on myocardial injury following sepsis and may indicate a novel therapeutic intervention for SIMI.

The neurobiology of non-coding RNAs and Alzheimer's disease pathogenesis: Pathways, mechanisms and translational opportunities

In the past two decades, advances in sequencing technology and analysis of the human and mouse genome have led to the discovery of many non-protein-coding RNAs (ncRNAs) including: microRNA, small-interfering RNAs, piwi-associated small RNAs, transfer RNA-derived small RNAs, long-non-coding RNAs and circular RNAs. Compared with healthy controls, levels of some ncRNAs are significantly altered in the central nervous system and blood of patients affected by neurodegenerative disorders like Alzheimer's disease (AD). Although the mechanisms are still not fully elucidated, studies have revealed that these highly conserved ncRNAs are important modulators of gene expression, amyloid-β production, tau phosphorylation, inflammation, synaptic plasticity and neuronal survival, all features considered central to AD pathogenesis. Despite considerable difficulties due to their large heterogeneity, and the complexity of their regulatory pathways, research in this rapidly growing field suggests that ncRNAs hold great potential as biomarkers and therapeutic targets against AD. Herein, we summarize the current knowledge regarding the neurobiology of ncRNA in the context of AD pathophysiology.

A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach

Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the most common cause of dementia in the elderly. As the number of elderly individuals increases globally, the incidence and prevalence of AD are expected to increase. At present, AD is diagnosed clinically, according to accepted criteria. The essential elements in the diagnosis of AD include a patients history, a physical examination and neuropsychological testing, in addition to appropriate investigations such as neuroimaging. The omics-based approach is an emerging field of study that may not only aid in the diagnosis of AD but also facilitate the exploration of factors that influence the development of the disease. Omics techniques, including genomics, transcriptomics, proteomics and metabolomics, may reveal the pathways that lead to neuronal death and identify biomolecular markers associated with AD. This will further facilitate an understanding of AD neuropathology. In this review, omics-based approaches that were implemented in studies on AD were assessed from a bioinformatics perspective. Current state-of-the-art statistical and machine learning approaches used in the single omics analysis of AD were compared based on correlations of variants, differential expression, functional analysis and network analysis. This was followed by a review of the approaches used in the integration and analysis of multi-omics of AD. The strengths and limitations of multi-omics analysis methods were explored and the issues and challenges associated with omics studies of AD were highlighted. Lastly, future studies in this area of research were justified.

Hypermethylation of Mest promoter causes aberrant Wnt signaling in patients with Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that leads to dementia and behavioral changes. Extracellular deposition of amyloid plaques (Aβ) and intracellular deposition of neurofibrillary tangles in neurons are the major pathogenicities of AD. However, drugs targeting these therapeutic targets are not effective. Therefore, novel targets for the treatment of AD urgently need to be identified. Expression of the mesoderm-specific transcript (Mest) is regulated by genomic imprinting, where only the paternal allele is active for transcription. We identified hypermethylation on the Mest promoter, which led to a reduction in Mest mRNA levels and activation of Wnt signaling in brain tissues of AD patients. Mest knockout (KO) using the CRIPSR/Cas9 system in mouse embryonic stem cells and P19 embryonic carcinoma cells leads to neuronal differentiation arrest. Depletion of Mest in primary hippocampal neurons via lentivirus expressing shMest or inducible KO system causes neurodegeneration. Notably, depletion of Mest in primary cortical neurons of rats leads to tau phosphorylation at the S199 and T231 sites. Overall, our data suggest that hypermethylation of the Mest promoter may cause or facilitate the progression of AD.

Human-Specific Regulation of Neurotrophic Factors MANF and CDNF by microRNAs

Mesencephalic astrocyte derived neurotrophic factor (MANF) and cerebral dopamine neurotrophic factor (CDNF) are novel evolutionary conserved trophic factors, which exhibit cytoprotective activity via negative regulation of unfolded protein response (UPR) and inflammation. Despite multiple reports demonstrating detrimental effect of MANF/CDNF downregulation, little is known about the control of their expression. miRNAs-small non-coding RNAs-are important regulators of gene expression. Their dysregulation was demonstrated in multiple pathological processes and their ability to modulate levels of other neurotrophic factors, glial cell line-derived neurotrophic factor (GDNF) and brain-derived neurotrophic factor (BDNF), was previously reported. Here, for the first time we demonstrated direct regulation of MANF and CDNF by miRNAs. Using bioinformatic tools, reporter assay and analysis of endogenous MANF and CDNF, we identified that miR-144 controls MANF expression, and miR-134 and miR-141 downregulate CDNF levels. We also demonstrated that this effect is human-specific and is executed via predicted binding sites of corresponding miRNAs. Finally, we found that miR-382 suppressed hCDNF expression indirectly. In conclusion, we demonstrate for the first time direct regulation of MANF and CDNF expression by specific miRNAs, despite the fact their binding sites are not strongly evolutionary conserved. Furthermore, we demonstrate a functional effect of miR-144 mediated regulation of MANF on ER stress response markers. These findings emphasize that (1) prediction of miRNA targets based on evolutionary conservation may miss biologically meaningful regulatory pairs; and (2) interpretation of miRNA regulatory effects in animal models should be cautiously validated.

Integrated Bioinformatics Analysis to Identify Alternative Therapeutic Targets for Alzheimer's Disease: Insights from a Synaptic Machinery Perspective

Alzheimer's disease (AD), the most common type of dementia, is a serious neurodegenerative disease that has no cure yet, but whose symptoms can be alleviated with available medications. Therefore, early and accurate diagnosis of the disease and elucidation of the molecular mechanisms involved in the progression of pathogenesis are critically important. This study aimed to identify dysregulated miRNAs and their target mRNAs through the integrated analysis of miRNA and mRNA expression profiling in AD patients versus unaffected controls. Expression profiles in postmortem brain samples from AD patients and healthy individuals were extracted from the Gene Expression Omnibus database and were analyzed using bioinformatics approaches to identify gene ontologies, pathways, and networks. Finally, the module analysis of the PPI network and hub gene selection was carried out. A total of five differentially expressed miRNAs were extracted from the miRNA dataset, and 4312 differentially expressed mRNAs were obtained from the mRNA dataset. By comparing the DEGs and the putative targets of the altered miRNAs, 116 (3 upregulated and 113 downregulated) coordinated genes were determined. Also, six hub genes (SNAP25, GRIN2A, GRIN2B, DLG2, ATP2B2, and SCN2A) were identified by constructing a PPI network. The results of the present study provide insight into mechanisms such as synaptic machinery and neuronal communication underlying AD pathogenesis, specifically concerning miRNAs.

Evaluating the Effect of 3'-UTR Variants in DICER1 and DROSHA on Their Tissue-Specific Expression by miRNA Target Prediction

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3'-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3'-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3'-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both "canonical" and "non-canonical" types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.

Profiling of Serum Exosome MiRNA Reveals the Potential of a MiRNA Panel as Diagnostic Biomarker for Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease in the older adults. Although much effort has been made in the analyses of diagnostic biomarkers, such as amyloid-β, tau, and neurofilament light chain, identifying peripheral blood-based biomarkers is in extremely urgent need for their minimal invasiveness and more convenience. Here we characterized the miRNA profile by RNA sequencing in human serum exosomes from AD patients and healthy controls (HC) to investigate its potential for AD diagnosis. Subsequently, Gene Ontology analysis and pathway analysis were performed for the targeted genes from the differentially expressed miRNAs. These basic functions were differentially enriched, including cell adhesion, regulation of transcription, and the ubiquitin system. Functional network analysis highlighted the pathways of proteoglycans in cancer, viral carcinogenesis, signaling pathways regulating pluripotency of stem cells, and cellular senescence in AD. A total of 24 miRNAs showed significantly differential expression between AD and HC with more than ± 2.0-fold change at p value < 0.05 and at least 50 reads for each sample. Logistic regression analysis established a model for AD prediction by serum exosomal miR-30b-5p, miR-22-3p, and miR-378a-3p. Sequencing results were validated using quantitative reverse transcription PCR. The data showed that miR-30b-5p, miR-22-3p, and miR-378a-3p were significantly deregulated in AD, with area under the curve (AUC) of 0.668, 0.637, and 0.718, respectively. The combination of the three miRs gained a better diagnostic capability with AUC of 0.880. This finding revealed a miR panel as potential biomarker in the peripheral blood to distinguish AD from HC.

Integrated miRNA-Seq and mRNA-Seq Study to Identify miRNAs Associated With Alzheimer's Disease Using Post-mortem Brain Tissue Samples

Alzheimer's disease (AD), the leading form of dementia, is associated with abnormal tau and β-amyloid accumulation in the brain. We conducted a miRNA-seq study to identify miRNAs associated with AD in the post-mortem brain from the inferior frontal gyrus (IFG, n = 69) and superior temporal gyrus (STG, n = 81). Four and 64 miRNAs were differentially expressed (adjusted p-value < 0.05) in AD compared to cognitively normal controls in the IFG and STG, respectively. We observed down-regulation of several miRNAs that have previously been implicated in AD, including hsa-miR-212-5p and hsa-miR-132-5p, in AD samples across both brain regions, and up-regulation of hsa-miR-146a-5p, hsa-miR-501-3p, hsa-miR-34a-5p, and hsa-miR-454-3p in the STG. The differentially expressed miRNAs were previously implicated in the formation of amyloid-β plaques, the dysregulation of tau, and inflammation. We have also observed differential expressions for dozens of other miRNAs in the STG, including hsa-miR-4446-3p, that have not been described previously. Putative targets of these miRNAs (adjusted p-value < 0.1) were found to be involved in Wnt signaling pathway, MAPK family signaling cascades, sphingosine 1-phosphate (S1P) pathway, adaptive immune system, innate immune system, and neurogenesis. Our results support the finding of dysregulated miRNAs previously implicated in AD and propose additional miRNAs that appear to be dysregulated in AD for experimental follow-up.

Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants

Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.

Changes in neurodegeneration-related miRNAs in brains from CAPN1-/- mice

Calpain-1 knock-out (KO) mice exhibit enhanced susceptibility to neurodegeneration due to the lack of the neuroprotective function of calpain-1. Dicer has been shown to play a fundamental role in the biogenesis of most miRNAs. Here, we identified 45 differentially expressed miRNAs (DE miRNAs) in the brain of calpain-1 KO mice, as compared to wild-type mice. In particular, among all the DE miRNAs, 7 neurodegeneration-related miRNAs were found to be down-regulated in calpain-1 KO mice. We also found that Dicer is cleaved by calpain-1 in mouse brain, which generates an active fragment of Dicer with RNAse III activity and increases miRNA formation. Levels of active Dicer were reduced in brain homogenates from calpain-1 KO mice and incubation with calpain-1 and calcium restored Dicer activity and miRNA expression. Our results indicate that calpain-1 deletion results in decreased levels of active Dicer and changes in neurodegenerative-related miRNAs. These findings could account for some of the pathological changes found in brain of various mammals, including humans, with calpain-1 mutations or down-regulation.

Identification of miRNA-Target Gene Pairs in the Parietal and Frontal Lobes of the Brain in Patients with Alzheimer's Disease Using Bioinformatic Analyses

Alzheimer's disease (AD) is a growing health concern worldwide. MicroRNAs (miRNAs) have been extensively studied in many diseases, including AD. To identify differentially expressed miRNAs (DEmiRNAs) and genes specific to AD, we used bioinformatic analyses to investigate candidate miRNA-mRNA pairs involved in the pathogenesis of AD. We focused on differentially expressed genes (DEGs) that are targets of DEmiRNAs. The GEO2R tool and the HISAT2-DESeq2 software were used to identify DEmiRNAs and DEGs. Bioinformatic tools available online, such as TAM and the Database for Annotation, Visualization and Integrated Discovery (DAVID), were used to perform functional annotation and enrichment analysis. Targets of miRNAs were predicted using the miRTarBase. The Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, which are available online, were utilized to construct protein-protein interaction (PPI) networks and identify hub genes. Furthermore, transcription factors (TFs) encoded by the DEGs were predicted using the TransmiR database and TF-miRNA-mRNA networks were constructed. Finally, the expression profile of a hub gene in peripheral blood mononuclear cells was compared between healthy individuals and AD patients. We identified 26 correlated miRNA-mRNA pairs. In the parietal lobe, miRNA-mRNA pairs involved in protein folding were enriched, and in the frontal lobe, miRNA-mRNA pairs involved in synaptic transmission, abnormal protein degradation, and apoptosis were enriched. In addition, HSP90AB1 in peripheral blood mononuclear cells was found to be significantly downregulated in AD patients, and this was consistent with its expression profile in the parietal lobe of AD patients. Our results provide brain region-specific changes in miRNA-mRNA associations in AD patients, further our understanding of potential underlying molecular mechanisms of AD, and reveal promising diagnostic and therapeutic targets for AD.

Ferroptosis-Related Genes in Neurodevelopment and Central Nervous System

Ferroptosis, first introduced as a new form of regulated cell death induced by erastin, is accompanied by the accumulation of iron and lipid peroxides, thus it can be inhibited either by iron chelators or by lipophilic antioxidants. In the past decade, multiple studies have introduced the potential importance of ferroptosis in many human diseases, including cancer and neurodegenerative diseases. In this review, we will discuss the genetic association of ferroptosis with neurological disorders and development of the central nervous system.

Integrative Computational Approach Revealed Crucial Genes Associated With Different Stages of Diabetic Retinopathy

The increased incidence of diabetic retinopathy (DR) and the legacy effect associated with it has raised a great concern toward the need to find early diagnostic and treatment strategies. Identifying alterations in genes and microRNAs (miRNAs) is one of the most critical steps toward understanding the mechanisms by which a disease progresses, and this can be further used in finding potential diagnostic and prognostic biomarkers and treatment methods. We selected different datasets to identify altered genes and miRNAs. The integrative analysis was employed to find potential candidate genes (differentially expressed and aberrantly methylated genes that are also the target of altered miRNAs) and early genes (genes showing altered expression and methylation pattern during early stage of DR) for DR. We constructed a protein-protein interaction (PPI) network to find hub genes (potential candidate genes showing a greater number of interactions) and modules. Gene ontologies and pathways associated with the identified genes were analyzed to determine their role in DR progression. A total of 271 upregulated-hypomethylated genes, 84 downregulated-hypermethylated genes, 11 upregulated miRNA, and 30 downregulated miRNA specific to DR were identified. 40 potential candidate genes and 9 early genes were also identified. PPI network analysis revealed 7 hub genes (number of interactions >5) and 1 module (score = 5.67). Gene ontology and pathway analysis predicted enrichment of genes in oxidoreductase activity, binding to extracellular matrix, immune responses, leukocyte migration, cell adhesion, PI3K-Akt signaling pathway, ECM receptor interaction, etc., and thus their association with DR pathogenesis. In conclusion, we identified 7 hub genes and 9 early genes that could act as a potential prognostic, diagnostic, or therapeutic target for DR, and a few early genes could also play a role in metabolic memory phenomena.

microRNA-Based Biomarkers in Alzheimer's Disease (AD)

Alzheimer's disease (AD) is a multifactorial, age-related neurological disease characterized by complex pathophysiological dynamics taking place at multiple biological levels, including molecular, genetic, epigenetic, cellular and large-scale brain networks. These alterations account for multiple pathophysiological mechanisms such as brain protein accumulation, neuroinflammatory/neuro-immune processes, synaptic dysfunction, and neurodegeneration that eventually lead to cognitive and behavioral decline. Alterations in microRNA (miRNA) signaling have been implicated in the epigenetics and molecular genetics of all neurobiological processes associated with AD pathophysiology. These changes encompass altered miRNA abundance, speciation and complexity in anatomical regions of the CNS targeted by the disease, including modified miRNA expression patterns in brain tissues, the systemic circulation, the extracellular fluid (ECF) and the cerebrospinal fluid (CSF). miRNAs have been investigated as candidate biomarkers for AD diagnosis, disease prediction, prognosis and therapeutic purposes because of their involvement in multiple brain signaling pathways in both health and disease. In this review we will: (i) highlight the significantly heterogeneous nature of miRNA expression and complexity in AD tissues and biofluids; (ii) address how information may be extracted from these data to be used as a diagnostic, prognostic and/or screening tools across the entire continuum of AD, from the preclinical stage, through the prodromal, i.e., mild cognitive impairment (MCI) phase all the way to clinically overt dementia; and (iii) consider how specific miRNA expression patterns could be categorized using miRNA reporters that span AD pathophysiological initiation and disease progression.

FGF2 Affects Parkinson's Disease-Associated Molecular Networks Through Exosomal Rab8b/Rab31

Ras-associated binding (Rab) proteins are small GTPases that regulate the trafficking of membrane components during endocytosis and exocytosis including the release of extracellular vesicles (EVs). Parkinson’s disease (PD) is one of the most prevalent neurodegenerative disorder in the elderly population, where pathological proteins such as alpha-synuclein (α-Syn) are transmitted in EVs from one neuron to another neuron and ultimately across brain regions, thereby facilitating the spreading of pathology. We recently demonstrated fibroblast growth factor-2 (FGF2) to enhance the release of EVs and delineated the proteomic signature of FGF2-triggered EVs in cultured primary hippocampal neurons. Out of 235 significantly upregulated proteins, we found that FGF2 specifically enriched EVs for the two Rab family members Rab8b and Rab31. Consequently, we investigated the interactions of Rab8b and Rab31 using a network analysis approach in order to estimate the global influence of their enrichment in EVs. To achieve this, we have demarcated a protein–protein interaction network (PPiN) for these Rabs and identified the proteins associated with PD in various cellular components of the central nervous system (CNS), in different brain regions, and in the enteric nervous system (ENS). A total of 126 direct or indirect interactions were reported for two Rab candidates, out of which 114 are Rab8b interactions and 54 are Rab31 interactions, ultimately resulting in an individual interaction score (IS) of 90.48 and 42.86%, respectively. Conclusively, these results for the first time demonstrate the relevance of FGF2-induced Rab-enrichment in EVs and its potential to regulate PD pathophysiology.

T Cell Responses to Neural Autoantigens Are Similar in Alzheimer's Disease Patients and Age-Matched Healthy Controls

Alzheimer's disease (AD), a chronic multifactorial and complex neurodegenerative disorder is a leading cause of dementia. Recently, neuroinflammation has been hypothesized as a contributing factor to AD pathogenesis. The role of adaptive immune responses against neuronal antigens, which can either confer protection or induce damage in AD, has not been fully characterized. Here, we measured T cell responses to several potential antigens of neural origin including amyloid precursor protein (APP), amyloid beta (Aβ), tau, α-synuclein, and transactive response DNA binding protein (TDP-43) in patients with AD and age-matched healthy controls (HC). Antigen-specific T cell reactivity was detected for all tested antigens, and response to tau-derived epitopes was particularly strong, but no significant differences between individuals with AD and age-matched HC were identified. We also did not observe any correlation between the antigen-specific T cell responses and clinical variables including age, gender, years since diagnosis and cognitive score. Additionally, further characterization did not reveal any differences in the relative frequency of major Peripheral Blood Mononuclear Cells (PBMC) subsets, or in the expression of genes between AD patients and HC. These observations have not identified a key role of neuronal antigen-specific T cell responses in AD.

Comparative transcriptome analysis of Parkinson's disease and Hutchinson-Gilford progeria syndrome reveals shared susceptible cellular network processes

BACKGROUND

Parkinson's Disease (PD) and Hutchinson-Gilford Progeria Syndrome (HGPS) are two heterogeneous disorders, which both display molecular and clinical alterations associated with the aging process. However, similarities and differences between molecular changes in these two disorders have not yet been investigated systematically at the level of individual biomolecules and shared molecular network alterations.

METHODS

Here, we perform a comparative meta-analysis and network analysis of human transcriptomics data from case-control studies for both diseases to investigate common susceptibility genes and sub-networks in PD and HGPS. Alzheimer's disease (AD) and primary melanoma (PM) were included as controls to confirm that the identified overlapping susceptibility genes for PD and HGPS are non-generic.

RESULTS

We find statistically significant, overlapping genes and cellular processes with significant alterations in both diseases. Interestingly, the majority of these shared affected genes display changes with opposite directionality, indicating that shared susceptible cellular processes undergo different mechanistic changes in PD and HGPS. A complementary regulatory network analysis also reveals that the altered genes in PD and HGPS both contain targets controlled by the upstream regulator CDC5L.

CONCLUSIONS

Overall, our analyses reveal a significant overlap of affected cellular processes and molecular sub-networks in PD and HGPS, including changes in aging-related processes that may reflect key susceptibility factors associated with age-related risk for PD.

Plasma microRNAs biomarkers in mild cognitive impairment among patients with type 2 diabetes mellitus

Objectives

To assess the potential value of some miRNAs as diagnostic biomarkers for mild cognitive impairment (MCI) among patients with type2 diabetes mellitus (T2DM) and to identify other risk factors for MCI among them.

Methods

This study enrolled 163 adults with T2DM using face to face interview. Cognitive function with its domains was assessed using Adenbrooke’s Cognitive Examination III (ACE III). Lipid profile, glycated hemoglobin, and miR-128, miR-132, miR- 874, miR-134, miR-323, and miR-382 expressions, using quantitative real-time PCR, were assessed.

Results

MCI was detected among 59/163 (36.2%) patients with T2DM. Plasma expression of miR-132 was significantly higher in T2DM patients with MCI compared to those without MCI and to normal cognitive healthy individuals (median = 2, 1.1 and 1.2 respectively, P < 0.05. Logistic regression analysis showed that higher miR-132 expression with adjusted odds ratio (AOR): 1.2 (95% CI 1.0–1.3), female gender (AOR:2.1; 95%CI 1.0–4.3), education below postgraduate (secondary and university education with AOR: 9.5 & 19.4 respectively) were the significant predicting factors for MCI among T2DM patients. Using ROC curve, miR-132 was the only assayed miRNA that significantly differentiates T2DM patients with MCI from those with normal cognition with 72.3% sensitivity, 56.2% specificity, and 63.8% accuracy (P < 0.05). Other studied miRNAs showed lower sensitivity and specificity for detecting MCI among studied T2DM participants.

Conclusion

MCI affects nearly one-third of adult patients with T2DM. A significantly over expression of miR-132 was detected among T2DM with MCI compared to those with normal cognition.

Circulating miRNAs in Successful and Unsuccessful Aging. A Mini-review

Aging is a multifactorial process that affects the organisms at genetic, molecular and cellular levels. This process modifies several tissues with a negative impact on cells physiology, tissues and organs functionality, altering their regeneration capacity. The chronic low-grade inflammation typical of aging, defined as inflammaging, is a common biological factor responsible for the decline and beginning of the disease in age. A murine parabiosis model that combines the vascular system of old and young animals, suggests that soluble factors released by young individuals may improve the regenerative potential of old tissue. Therefore, circulating factors have a key role in the induction of aging phenotype. Moreover, lifestyle can influence the physiological status of multiple organs, via epigenetic mechanisms. Recently, microRNAs are considered potential sensors of aging.

Effect of C-phycocyanin on HDAC3 and miRNA-335 in Alzheimer's disease

BACKGROUND

Amyloid-beta (Aβ) plaque deposits and neurofibrillary tangles containing tau proteins are the key pathognomonic manifestations of Alzheimer's disease (AD). Lack of holistic drugs for AD has reinvigorated enthusiasm in the natural product-based therapies. In this study, our idea to decipher the beneficial effects of C-phycocyanin (CPC) in the management of AD is buoyed by its multifaceted and holistic therapeutic effects.

METHODS

We evaluated the effect of CPC treatment on epigenetic factors and inflammatory mediators in a mouse with oligomeric Aβ1-42-induced AD. Besides, the cognitive function was evaluated by the spatial memory performance on a radial arm maze.

RESULTS

The results showed cognitive deficit in the mice with AD along with upregulated HDAC3 expression and diminished miRNA-335 and brain-derived neurotrophic factor (BDNF) expressions. In addition, inflammation was provoked (manifested by increased interleukins (IL)-6 and IL-1β) and neuronal apoptosis was accelerated (indicated by increased Bax, caspase-3, and caspase-9 along with decreased Bcl2) in the hippocampus of the mice with AD. Interestingly, CPC treatment in the mice with AD improved spatial memory performance and decreased the perturbations in the epigenetic and inflammatory biofactors.

CONCLUSION

These results underscore that mitigation of inflammation via regulation of epigenetic factors might be the key pathway underlying the ameliorative effect of CPC against the aberrations in AD. Our findings provide the rationale for considering CPC as a viable therapeutic option in the management of AD.

A meta-analysis of gene expression data highlights synaptic dysfunction in the hippocampus of brains with Alzheimer's disease

Since the world population is ageing, dementia is going to be a growing concern. Alzheimer's disease is the most common form of dementia. The pathogenesis of Alzheimer's disease is extensively studied, yet unknown remains. Therefore, we aimed to extract new knowledge from existing data. We analysed about 2700 upregulated genes and 2200 downregulated genes from three studies on the CA1 of the hippocampus of brains with Alzheimer's disease. We found that only the calcium signalling pathway enriched by 48 downregulated genes was consistent between all three studies. We predicted miR-129 to target nine out of 48 genes. Then, we validated miR-129 to regulate six out of nine genes in HEK cells. We noticed that four out of six genes play a role in synaptic plasticity. Finally, we confirmed the upregulation of miR-129 in the hippocampus of brains of rats with scopolamine-induced amnesia as a model of Alzheimer's disease. We suggest that future research should investigate the possible role of miR-129 in synaptic plasticity and Alzheimer's disease. This paper presents a novel framework to gain insight into potential biomarkers and targets for diagnosis and treatment of diseases.

The Predicted Key Molecules, Functions, and Pathways That Bridge Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD)

To elucidate the key molecules, functions, and pathways that bridge mild cognitive impairment (MCI) and Alzheimer's disease (AD), we investigated open gene expression data sets. Differential gene expression profiles were analyzed and combined with potential MCI- and AD-related gene expression profiles in public databases. Then, weighted gene co-expression network analysis was performed to identify the gene co-expression modules. One module was significantly negatively associated with MCI samples, in which gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that these genes were related to cytosolic ribosome, ribosomal structure, oxidative phosphorylation, AD, and metabolic pathway. The other two modules correlated significantly with AD samples, in which functional and pathway enrichment analysis revealed strong relationships of these genes with cytoplasmic ribosome, protein binding, AD, cancer, and apoptosis. In addition, we regarded the core genes in the module network closely related to MCI and AD as bridge genes and submitted them to protein interaction network analysis to screen for major pathogenic genes according to the connectivity information. Among them, small nuclear ribonucleoprotein D2 polypeptide (SNRPD2), ribosomal protein S3a (RPS3A), S100 calcium binding protein A8 (S100A8), small nuclear ribonucleoprotein polypeptide G (SNRPG), U6 snRNA-associated Sm-like protein LSm3 (LSM3), ribosomal protein S27a (RPS27A), and ATP synthase F1 subunit gamma (ATP5C1) were not only major pathogenic genes of MCI, but also bridge genes. In addition, SNRPD2, RPS3A, S100A8, SNRPG, LSM3, thioredoxin (TXN), proteasome 20S subunit alpha 4 (PSMA4), annexin A1 (ANXA1), DnaJ heat shock protein family member A1 (DNAJA1), and prefoldin subunit 5 (PFDN5) were not only major pathogenic genes of AD, but also bridge genes. Next, we screened for differentially expressed microRNAs (miRNAs) to predict the miRNAs and transcription factors related the MCI and AD modules, respectively. The significance score of miRNAs in each module was calculated using a hypergeometric test to obtain the miRNApivot-Module interaction pair. Thirty-four bridge regulators were analyzed, among which hsa-miR-519d-3p was recognized as the bridge regulator between MCI and AD. Our study contributed to a better understanding of the pathogenic mechanisms of MCI and AD, and might lead to the development of a new strategy for clinical diagnosis and treatment.

A Systematic Bioinformatics Workflow With Meta-Analytics Identified Potential Pathogenic Factors of Alzheimer's Disease

Potential pathogenic factors, other than well-known APP, APOE4, and PSEN, can be further identified from transcriptomics studies of differentially expressed genes (DEGs) that are specific for Alzheimer’s disease (AD), but findings are often inconsistent or even contradictory. Evidence corroboration by combining meta-analysis and bioinformatics methods may help to resolve existing inconsistencies and contradictions. This study aimed to demonstrate a systematic workflow for evidence synthesis of transcriptomic studies using both meta-analysis and bioinformatics methods to identify potential pathogenic factors. Transcriptomic data were assessed from GEO and ArrayExpress after systematic searches. The DEGs and their dysregulation states from both DNA microarray and RNA sequencing datasets were analyzed and corroborated by meta-analysis. Statistically significant DEGs were used for enrichment analysis based on KEGG and protein–protein interaction network (PPIN) analysis based on STRING. AD-specific modules were further determined by the DIAMOnD algorithm, which identifies significant connectivity patterns between specific disease-associated proteins and non-specific proteins. Within AD-specific modules, the nodes of highest degrees (>95th percentile) were considered as potential pathogenic factors. After systematic searches of 225 datasets, extensive meta-analyses among 25 datasets (21 DNA microarray datasets and 4 RNA sequencing datasets) identified 9,298 DEGs. The dysregulated genes and pathways in AD were associated with impaired amyloid-β (Aβ) clearance. From the AD-specific module, Fyn, and EGFR were the most statistically significant and biologically relevant. This meta-analytical study suggested that the reduced Aβ clearance in AD pathogenesis was associated with the genes encoding Fyn and EGFR, which were key receptors in Aβ downstream signaling.