Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer's disease by meta-analysis and adaptive boosting ensemble learning

A hypothesis about interrelations of epigenetic factors and transposable elements in memory formation

The review describes the hypothesis that the drivers of epigenetic regulation in memory formation are transposable elements that influence the expression of specific genes in the brain. The hypothesis is confirmed by research into transposon activation in neuronal stem cells during neuronal differentiation. These changes occur in the hippocampus dentate gyrus, where a pronounced activity of transposons and their insertion near neuron-specific genes have been detected. In experiments on changing the activity of histone acetyltransferase and inhibition of DNA methyltransferase and reverse transcriptase, the involvement of epigenetic factors and retroelements in the mechanisms of memory formation has been shown. Also, a number of studies on different animals have revealed the preservation of long-term memory without the participation of synaptic plasticity. The data obtained suggest that transposons, which are genome sensors highly sensitive to various environmental and internal influences, form memory at the nuclear coding level. Therefore, long-term memory is preserved after elimination of synaptic connections. This is confirmed by the fact that the proteins involved in memory formation, including the transfer of genetic information through synapses between neurons (Arc protein), originate from transposons. Long non-coding RNAs and microRNAs also originate from transposons; their role in memory consolidation has been described. Pathological activation of transposable elements is a likely cause of neurodegenerative diseases with memory impairment. Analysis of the scientific literature allowed us to identify changes in the expression of 40 microRNAs derived from transposons in Alzheimer's disease. For 24 of these microRNAs, the mechanisms of regulation of genes involved in the functioning of the brain have been described. It has been suggested that the microRNAs we identified could become potential tools for regulating transposon activity in the brain in order to improve memory.

miR-92a-3p and miR-320a are Upregulated in Plasma Neuron-Derived Extracellular Vesicles of Patients with Frontotemporal Dementia

Despite the efforts to identify fluid biomarkers to improve diagnosis of Frontotemporal dementia (FTD), only a few candidates have been described in recent years. In a previous study, we identified three circulating miRNAs (miR-92a-3p, miR-320a and miR-320b) differentially expressed in FTD patients with respect to healthy controls and/or Alzheimer's disease (AD) patients. Now, we investigated whether those changes could be due to miRNAs contained in neuron-derived extracellular vesicles (NDEVs). We also evaluated miRNAs content in total plasma EVs and in CSF samples. The analysis of plasma NDEVs carried out on 40 subjects including controls (n = 13), FTD (n = 13) and AD (n = 14) patients, showed that both miR-92a-3p and miR-320a levels were triplicated in the FTD group if compared with CT and AD patients. Increased levels of the same miRNAs were found also in CSF derived from FTD group compared to CTs. No differences were observed in expression levels of miR-320b among the three groups. Worthy of note, all miRNAs analysed were increased in an FTD cell model, MAPT IVS10 + 16 neurons. Our results suggest that miR-92a and miR-320a in NDEVs could be proposed as FTD biomarkers.

AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

A meta-analysis of differentially expressed circulatory micro-RNAs in chronic traumatic encephalopathy and other tauopathies: A significant role of miR-181c-5p

BACKGROUND

Micro-RNA (miRs) targeting kinases and phosphatases regulate the hyper-phosphorylation of tau protein, which is a characteristic feature of Chronic Traumatic Encephalopathy (CTE).

PRIMARY OBJECTIVE

Identification of lead dysregulated miR expressed in CTE, and other similar tauopathies.

METHODS

A search strategy was devised using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to mine into multiple indexing databases such as Web of Science, Google Scholar, and PubMed spanning from 2005 to June 2022. Seven articles were screened out of 34,221 publications based on inclusion criteria and were categorized into two groups i.e., (1) CTE and its risk factors and (2) Age-related neurodegenerative disorders.

RESULTS

Statistical analysis [RevMan 5.4.1] results showed that the overall risk ratio (RR) of the first group is significant (RR = 0.62, 95% CI = [0.38, 1.00], z = 1.95, p = 0.05) whereas, the second group favours the control population (RR = 1.64, 95% CI = [0.85, 3.16], z = 1.14, p = 0.14).

CONCLUSION

We observed that among all other dysregulated miRs, miR-181c-5p is significantly overexpressed in Alzhimers disease (AD) and CTE. Further, we found that miR-210-3p is also upregulated notably in all groups. In sum, we conclude that these miRs can be considered as potential target and biomarker in the diagnosis and treatment of various tauopathies.

Peripheral blood MicroRNAs as biomarkers of schizophrenia: expectations from a meta-analysis that combines deep learning methods

OBJECTIVES

This study aimed at identifying reliable differentially expressed miRNAs (DEMs) for schizophrenia in blood via meta-analyses combined with deep learning methods.

METHODS

First, we meta-analysed published DEMs. Then, we enriched the pool of schizophrenia-associated miRNAs by applying two computational learning methods to identify candidate biomarkers and verified the results in external datasets.

RESULTS

In total, 27 DEMs were found to be statistically significant (p < .05). Ten candidate schizophrenia-associated miRNAs were identified through computational learning methods. The diagnostic efficiency was verified on a blood-miRNA dataset (GSE54578) with a random forest (RF) model and achieved an area under the curve (AUC) of 0.83 ± 0.14. Moreover, 855 experimentally validated target genes for these candidate miRNAs were retrieved, and 11 hub genes were identified. Enrichment analysis revealed that the main functions in which the target genes were enriched were those related to cell signalling, prenatal infections, cancers, cell deaths, oxidative stress, endocrine disorders, transcription regulation, and kinase activities. The diagnostic ability of the hub genes was reflected in a comparably good average AUC of 0.77 ± 0.09 for an external dataset (GSE38484).

CONCLUSIONS

A meta-analysis that combines computational and mathematical methods provides a reliable tool for identifying candidate biomarkers of schizophrenia.

Differential Expression of miRNAs in Amyotrophic Lateral Sclerosis Patients

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease that affects nerve cells in the brain and spinal cord, causing loss of muscle control, muscle atrophy and in later stages, death. Diagnosis has an average delay of 1 year after symptoms onset, which impairs early management. The identification of a specific disease biomarker could help decrease the diagnostic delay. MicroRNA (miRNA) expression levels have been proposed as ALS biomarkers, and altered function has been reported in ALS pathogenesis. The aim of this study was to assess the differential expression of plasma miRNAs in ALS patients and two control populations (healthy controls and ALS-mimic disorders). For that, 16 samples from each group were pooled, and then 1008 miRNAs were assessed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). From these, ten candidate miRNAs were selected and validated in 35 ALS patients, 16 ALS-mimic disorders controls and 15 healthy controls. We also assessed the same miRNAs in two different time points of disease progression. Although we were unable to determine a miRNA signature to use as disease or condition marker, we found that miR-7-2-3p, miR-26a-1-3p, miR-224-5p and miR-206 are good study candidates to understand the pathophysiology of ALS.

Targeting epigenetics: A novel promise for Alzheimer's disease treatment

So far, the search for a cure for Alzheimer Disease (AD) has been unsuccessful. The only approved drugs attenuate some symptoms, but do not halt the progress of this disease, which affects 50 million people worldwide and will increase its incidence in the coming decades. Such scenario demands new therapeutic approaches to fight against this devastating dementia. In recent years, multi-omics research and the analysis of differential epigenetic marks in AD subjects have contributed to our understanding of AD; however, the impact of epigenetic research is yet to be seen. This review integrates the most recent data on pathological processes and epigenetic changes relevant for aging and AD, as well as current therapies targeting epigenetic machinery in clinical trials. Evidence shows that epigenetic modifications play a key role in gene expression, which could provide multi-target preventative and therapeutic approaches in AD. Both novel and repurposed drugs are employed in AD clinical trials due to their epigenetic effects, as well as increasing number of natural compounds. Given the reversible nature of epigenetic modifications and the complexity of gene-environment interactions, the combination of epigenetic-based therapies with environmental strategies and drugs with multiple targets might be needed to properly help AD patients.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

The Role of microRNAs in Epigenetic Regulation of Signaling Pathways in Neurological Pathologies

In recent times, there has been a significant increase in researchers' interest in the functions of microRNAs and the role of these molecules in the pathogenesis of many multifactorial diseases. This is related to the diagnostic and prognostic potential of microRNA expression levels as well as the prospects of using it in personalized targeted therapy. This review of the literature analyzes existing scientific data on the involvement of microRNAs in the molecular and cellular mechanisms underlying the development of pathologies such as Alzheimer's disease, cerebral ischemia and reperfusion injury, and dysfunction of the blood-brain barrier.

Obesity, Cardiovascular and Neurodegenerative Diseases: Potential Common Mechanisms

The worldwide increase in the incidence of obesity and cardiovascular and neurodegenerative diseases, e.g. Alzheimer's disease, is related to many factors, including an unhealthy lifestyle and aging populations. However, the interconnection between these diseases is not entirely clear, and it is unknown whether common mechanisms underlie these conditions. Moreover, there are currently no fully effective therapies for obesity and neurodegeneration. While there has been extensive research in preclinical models addressing these issues, the experimental findings have not been translated to the clinic. Another challenge relates to the time of onset of individual diseases, which may not be easily identified, since there are no specific indicators or biomarkers that define disease onset. Hence knowing when to commence preventive treatment is unclear. This is especially pertinent in neurodegenerative diseases, where the onset of the disease may be subtle and occur decades before the signs and symptoms manifest. In metabolic and cardiovascular disorders, the risk may occur in-utero, in line with the concept of fetal programming. This review provides a brief overview of the link between obesity, cardiovascular and neurodegenerative diseases and discusses potential common mechanisms including the role of the gut microbiome.

Multidimensional biomarkers for multiple system atrophy: an update and future directions

Multiple system atrophy (MSA) is a fatal progressive neurodegenerative disease. Biomarkers are urgently required for MSA to improve the diagnostic and prognostic accuracy in clinic and facilitate the development and monitoring of disease-modifying therapies. In recent years, significant research efforts have been made in exploring multidimensional biomarkers for MSA. However, currently few biomarkers are available in clinic. In this review, we systematically summarize the latest advances in multidimensional biomarkers for MSA, including biomarkers in fluids, tissues and gut microbiota as well as imaging biomarkers. Future directions for exploration of novel biomarkers and promotion of implementation in clinic are also discussed.

The let-7b-5p, miR-326, and miR-125a-3p are associated with left ventricular systolic dysfunction in post-myocardial infarction

Background

Acute ST-elevation myocardial infarction (STEMI) can lead to adverse cardiac remodeling, resulting in left ventricular systolic dysfunction (LVSd) and heart failure. Epigenetic regulators, such as microRNAs, may be involved in the physiopathology of LVSd.

Objective

This study explored microRNAs in peripheral blood mononuclear cells (PBMC) of post-myocardial infarction patients with LVSd.

Methods

Post-STEMI patients were grouped as having (LVSd, n = 9) or not LVSd (non-LVSd, n = 16). The expression of 61 microRNAs was analyzed in PBMC by RT-qPCR and the differentially expressed microRNAs were identified. Principal Component Analysis stratified the microRNAs based on the development of dysfunction. Predictive variables of LVSd were investigated through logistic regression analysis. A system biology approach was used to explore the regulatory molecular network of the disease and an enrichment analysis was performed.

Results

The let-7b-5p (AUC: 0.807; 95% CI: 0.63-0.98; p = 0.013), miR-125a-3p (AUC: 0.800; 95% CI: 0.61-0.99; p = 0.036) and miR-326 (AUC: 0.783; 95% CI: 0.54-1.00; p = 0.028) were upregulated in LVSd (p < 0.05) and discriminated LVSd from non-LVSd. Multivariate logistic regression analysis showed let-7b-5p (OR: 16.00; 95% CI: 1.54-166.05; p = 0.020) and miR-326 (OR: 28.00; 95% CI: 2.42-323.70; p = 0.008) as predictors of LVSd. The enrichment analysis revealed association of the targets of these three microRNAs with immunological response, cell-cell adhesion, and cardiac changes.

Conclusion

LVSd alters the expression of let-7b-5p, miR-326, and miR-125a-3p in PBMC from post-STEMI, indicating their potential involvement in the cardiac dysfunction physiopathology and highlighting these miRNAs as possible LVSd biomarkers.

circRNA from APP Gene Changes in Alzheimer's Disease Human Brain

Alzheimer's disease (AD) is the most common cause of age-related dementia. Amyloid precursor protein (APP) is the precursor of Aβ peptides, and its role in AD has been widely investigated. Recently, it has been reported that a circular RNA (circRNA) originated from APP gene can serve as a template for Aβ synthesis, postulating it as an alternative pathway for the Aβ biogenesis. Moreover, circRNAs play important roles in brain development and in neurological diseases. Therefore, our aim was to study the expression of a circAPP (hsa_circ_0007556) and its linear cognate in AD human entorhinal cortex, a brain region most vulnerable to AD pathology. First, we confirmed the presence of circAPP (hsa_circ_0007556) in human entorhinal cortex samples using RT-PCR and Sanger sequencing of PCR products. Next, a 0.49-fold decrease in circAPP (hsa_circ_0007556) levels was observed in entorhinal cortex of AD cases compared to controls (p-value < 0.05) by qPCR. In contrast, APP mRNA expression did not show changes in the entorhinal cortex between AD cases and controls (Fold-change = 1.06; p-value = 0.81). A negative correlation was found between Aβ deposits and circAPP (hsa_circ_0007556) and APP expression levels (Rho Spearman = -0.56, p-value < 0.001 and Rho Spearman = -0.44, p-values < 0.001, respectively). Finally, by using bioinformatics tools, 17 miRNAs were predicted to bind circAPP (hsa_circ_0007556), and the functional analysis predicted that they were involved in some pathways, such as the Wnt-signaling pathway (p = 3.32 × 10^-6). Long-term potentiation (p = 2.86 × 10^-5), among others, is known to be altered in AD. To sum up, we show that circAPP (hsa_circ_0007556) is deregulated in the entorhinal cortex of AD patients. These results add to the notion that circAPP (hsa_circ_0007556) could be playing a role in the pathogenesis of AD disease.

Curcumin protects PC12 cells from a high glucose-induced inflammatory response by regulating the miR-218-5p/TLR4 axis

BACKGROUND

Curcumin exerts a protective effect on diabetic encephalopathy (DN), It is known for its potent neuroprotective, anti-inflammatory, antioxidant, and anticancer properties. However, the underlying mechanisms of curcumin's neuroprotective effects resulting from high glucose (HG)-induced injuries remain unknown. The purpose of this study is to identify the protective mechanism of Curcumin in the DN.

METHODS

In this study, pheochromocytoma cells (PC12 cells) were pretreated with different concentrations of Curcumin and then co-treated with Curcumin and glucose for 48 hours, and the cell viability was evaluated by CCK-8, the expression of the inflammatory mediators were detected by ELISA, the miR-218-5p and toll-like receptors (TLR4) level were examined by both quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, the potential target genes of miR-218-5p were identified using luciferase reporter assay.

RESULTS

The viability of PC12 cells treated with HG was significantly reduced in a dose- and time-dependent manner. Cotreatment of curcumin with HG significantly increased cell viability. Curcumin inhibited the expression of the inflammatory mediators, tumor necrosis factor-α (TNF-α) and interleukin 6 (IL-6), and induced the expression of the anti-inflammatory mediator interleukin-10 (IL-10). Curcumin upregulated the levels of miR-218-5p and downregulated the expression of TLR4 in HG-treated PC12 cells. The curcumin-induced anti-inflammatory effect was abrogated by a miR-218-5p inhibitor and overexpression of TLR4. The results suggest that curcumin ameliorates the inflammatory response by upregulating miR-218-5p levels in PC12 cells.

CONCLUSIONS

Our results indicate a protective role for curcumin in PC12 cells and suggest that it should be considered for the prophylactic treatment of DN in the future.

Cognitive dysfunction associated with COVID-19: Prognostic role of circulating biomarkers and microRNAs

COVID-19 is renowned as a multi-organ disease having subacute and long-term effects with a broad spectrum of clinical manifestations. The evolving scientific and clinical evidence demonstrates that the frequency of cognitive impairment after COVID-19 is high and it is crucial to explore more clinical research and implement proper diagnostic and treatment strategies. Several central nervous system complications have been reported as comorbidities of COVID-19. The changes in cognitive function associated with neurodegenerative diseases develop slowly over time and are only diagnosed at an already advanced stage of molecular pathology. Hence, understanding the common links between COVID-19 and neurodegenerative diseases will broaden our knowledge and help in strategizing prognostic and therapeutic approaches. The present review focuses on the diverse neurodegenerative changes associated with COVID-19 and will highlight the importance of major circulating biomarkers and microRNAs (miRNAs) associated with the disease progression and severity. The literature analysis showed that major proteins associated with central nervous system function, such as Glial fibrillary acidic protein, neurofilament light chain, p-tau 181, Ubiquitin C-terminal hydrolase L1, S100 calcium-binding protein B, Neuron-specific enolase and various inflammatory cytokines, were significantly altered in COVID-19 patients. Furthermore, among various miRNAs that are having pivotal roles in various neurodegenerative diseases, miR-146a, miR-155, Let-7b, miR-31, miR-16 and miR-21 have shown significant dysregulation in COVID-19 patients. Thus the review consolidates the important findings from the numerous studies to unravel the underlying mechanism of neurological sequelae in COVID-19 and the possible association of circulatory biomarkers, which may serve as prognostic predictors and therapeutic targets in future research.

Artificial Intelligence Predictor for Alzheimer’s Disease Trained on Blood Transcriptome: The Role of Oxidative Stress

Alzheimer’s disease (AD) is an incurable neurodegenerative disease diagnosed by clinicians through healthcare records and neuroimaging techniques. These methods lack sensitivity and specificity, so new antemortem non-invasive strategies to diagnose AD are needed. Herein, we designed a machine learning predictor based on transcriptomic data obtained from the blood of AD patients and individuals without dementia (non-AD) through an 8 × 60 K microarray. The dataset was used to train different models with different hyperparameters. The support vector machines method allowed us to reach a Receiver Operating Characteristic score of 93% and an accuracy of 89%. High score levels were also achieved by the neural network and logistic regression methods. Furthermore, the Gene Ontology enrichment analysis of the features selected to train the model along with the genes differentially expressed between the non-AD and AD transcriptomic profiles shows the “mitochondrial translation” biological process to be the most interesting. In addition, inspection of the KEGG pathways suggests that the accumulation of β-amyloid triggers electron transport chain impairment, enhancement of reactive oxygen species and endoplasmic reticulum stress. Taken together, all these elements suggest that the oxidative stress induced by β-amyloid is a key feature trained by the model for the prediction of AD with high accuracy.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Nucleic acid liquid biopsies in Alzheimer's disease: current state, challenges, and opportunities

Alzheimer's disease (AD) is the most common neurodegenerative disease and affects persons of all races, ethnic groups, and sexes. The disease is characterized by neuronal loss leading to cognitive decline and memory loss. There is no cure and the effectiveness of existing treatments is limited and depends on the time of diagnosis. The long prodromal period, during which patients' ability to live a normal life is not affected despite neuronal loss, often leads to a delayed diagnosis because it can be mistaken for normal aging of the brain. In order to make a substantial impact on AD patient survival, early diagnosis may provide a greater therapeutic window for future therapies to slow AD-associated neurodegeneration. Current gold standards for disease detection include magnetic resonance imaging and positron emission tomography scans, which visualize amyloid β and phosphorylated tau depositions and aggregates. Liquid biopsies, already an active field of research in precision oncology, are hypothesized to provide early disease detection through minimally or non-invasive sample collection techniques. Liquid biopsies in AD have been studied in cerebrospinal fluid, blood, ocular, oral, and olfactory fluids. However, most of the focus has been on blood and cerebrospinal fluid due to biomarker specificity and sensitivity attributed to the effects of the blood-brain barrier and inter-laboratory variation during sample collection. Many studies have identified amyloid β and phosphorylated tau levels as putative biomarkers, however, advances in next-generation sequencing-based liquid biopsy methods have led to significant interest in identifying nucleic acid species associated with AD from liquid tissues. Differences in cell-free RNAs and DNAs have been described as potential biomarkers for AD and hold the potential to affect disease diagnosis, treatment, and future research avenues.

Anti-inflammatory effects of B vitamins protect against tau hyperphosphorylation and cognitive impairment induced by 1,2 diacetyl benzene: An in vitro and in silico study

1,2 diacetyl benzene (DAB) penetrates the blood-brain barrier, causing neuroinflammation, tau hyperphosphorylation, and cognitive impairment. Converging evidence supports the anti-inflammatory effects of B vitamins on cognitive impairment, but the effects of B vitamins on cognitive impairment induced by DAB remain unclear. Here, we investigated the anti-inflammatory properties of B vitamins in DAB-stimulated human neuroblastoma SH-SY5Y cells. In this in-silico analysis, we investigated the genes, transcription factors, miRNAs, and sponges linked with DAB, B vitamins and the pathogenesis of cognitive impairment. We found vitamins B1, B2, and B3 had anti-inflammatory properties in DAB-stimulated SH-SY5Y cells, possibly via inhibiting NF-κB activation. Furthermore, vitamins B1, B2, and B3 inhibited GSK-3β, β-amyloid, and tau hyperphosphorylation in SH-SY5Y cells. These vitamins can also modulate genes induced by DAB (IL1B, IL6, IL10, iNOS, COX2, NFκB, GSK3B, TNF, and APP) in SH-SY5Y cells. In silico analyses, inflammatory response related pathways, "Alzheimer's disease", "pathways of neurodegeneration-multiple disease", and "prolactin signaling pathway", were highlighted. Additionally, we explored a network-based approach to identify key genes, transcription factors, miRNAs, and pathways in cognitive impairment. The transcription factors NFKB2 and BATF3 were shown to be the most important in regulating genes. We also found eight significant miRNAs related to cognitive impairment, and these miRNAs were also validated by qPCR. Finally, we developed and tested in silico miRNA sponge sequences for these miRNAs.

Co-Expression Analysis of microRNAs and Proteins in Brain of Alzheimer's Disease Patients

Alzheimer's disease (AD) is the most common form of dementia globally; however, the aetiology of AD remains elusive hindering the development of effective therapeutics. MicroRNAs (miRNAs) are regulators of gene expression and have been of growing interest in recent studies in many pathologies including AD not only for their use as biomarkers but also for their implications in the therapeutic field. In this study, miRNA and protein profiles were obtained from brain tissues of different stage (Braak III-IV and Braak V-VI) of AD patients and compared to matched controls. The aim of the study was to identify in the late stage of AD, the key dysregulated pathways that may contribute to pathogenesis and then to evaluate whether any of these pathways could be detected in the early phase of AD, opening new opportunity for early treatment that could stop or delay the pathology. Six common pathways were found regulated by miRNAs and proteins in the late stage of AD, with one of them (Rap1 signalling) activated since the early phase. MiRNAs and proteins were also compared to explore an inverse trend of expression which could lead to the identification of new therapeutic targets. These results suggest that specific miRNA changes could represent molecular fingerprint of neurodegenerative processes and potential therapeutic targets for early intervention.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

A Novel Method for Predicting the Human Inherent Clearance and Its Application in the Study of the Pharmacokinetics and Drug-Drug Interaction between Azidothymidine and Fluconazole Mediated by UGT Enzyme

In order to improve the benefit–risk ratio of pharmacokinetic (PK) research in the early development of new drugs, in silico and in vitro methods were constructed and improved. Models of intrinsic clearance rate (CL_int) were constructed based on the quantitative structure–activity relationship (QSAR) of 7882 collected compounds. Moreover, a novel in vitro metabolic method, the Bio-PK dynamic metabolic system, was constructed and combined with a physiology-based pharmacokinetic model (PBPK) model to predict the metabolism and the drug–drug interaction (DDI) of azidothymidine (AZT) and fluconazole (FCZ) mediated by the phase II metabolic enzyme UDP-glycosyltransferase (UGT) in humans. Compared with the QSAR models reported previously, the goodness of fit of our CL_int model was slightly improved (determination coefficient (R²) = 0.58 vs. 0.25–0.45). Meanwhile, compared with the predicted clearance of 61.96 L/h (fold error: 2.95–3.13) using CL_int (8 µL/min/mg) from traditional microsomal experiment, the predicted clearance using CL_int (25 μL/min/mg) from Bio-PK system was increased to 143.26 L/h (fold error: 1.27–1.36). The predicted C_max and AUC (the area under the concentration–time curve) ratio were 1.32 and 1.84 (fold error: 1.36 and 1.05) in a DDI study with an inhibition coefficient (Ki) of 13.97 μM from the Bio-PK system. The results indicate that the Bio-PK system more truly reflects the dynamic metabolism and DDI of AZT and FCZ in the body. In summary, the novel in silico and in vitro method may provide new ideas for the optimization of drug metabolism and DDI research methods in early drug development.

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.

A Review of miRNAs as Biomarkers and Effect of Dietary Modulation in Obesity Associated Cognitive Decline and Neurodegenerative Disorders

There has been a progressive increase in the prevalence of obesity and its comorbidities such as type 2 diabetes and cardiovascular diseases worldwide. Recent studies have suggested that the crosstalk between adipose tissue and central nervous system (CNS), through cellular mediators and signaling pathways, may causally link obesity with cognitive decline and give rise to neurodegenerative disorders. Several mechanisms have been proposed in obesity, including inflammation, oxidative stress, insulin resistance, altered lipid and cholesterol homeostasis, which may result in neuroinflammation, altered brain insulin signaling, amyloid-beta (Aβ) deposition and neuronal cell death. Since obesity is associated with functional and morphological alterations in the adipose tissues, the resulting peripheral immune response augments the development and progression of cognitive decline and increases susceptibility of neurodegenerative disorders, such as Alzheimer's Disease (AD) and Parkinson's Disease (PD). Studies have also elucidated an important role of high fat diet in the exacerbation of these clinical conditions. However, the underlying factors that propel and sustain this obesity associated cognitive decline and neurodegeneration, remains highly elusive. Moreover, the mechanisms linking these phenomena are not well-understood. The cumulative line of evidence have demonstrated an important role of microRNAs (miRNAs), a class of small non-coding RNAs that regulate gene expression and transcriptional changes, as biomarkers of pathophysiological conditions. Despite the lack of utility in current clinical practices, miRNAs have been shown to be highly specific and sensitive to the clinical condition being studied. Based on these observations, this review aims to assess the role of several miRNAs and aim to elucidate underlying mechanisms that link obesity with cognitive decline and neurodegenerative disorders. Furthermore, this review will also provide evidence for the effect of dietary modulation which can potentially ameliorate cognitive decline and neurodegenerative diseases associated with obesity.