Differential Expression of mRNAs in the Brain Tissues of Patients with Alzheimer's Disease Based on GEO Expression Profile and Its Clinical Significance

Identification of toll-like receptor 2 as a key regulator of neuronal apoptosis in vascular dementia by bioinformatics analysis and experimental validation

BACKGROUND

Vascular dementia (VaD), the second most prevalent type of dementia, lacks a well-defined cause and effective treatment. Our objective was to utilize bioinformatics analysis to discover the fundamental disease-causing genes and pathological mechanisms in individuals diagnosed with VaD.

METHODS

To identify potential pathogenic genes associated with VaD, we conducted weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein-protein interaction (PPI) analysis. The exploration of potential biological mechanisms involved the utilization of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Moreover, a bilateral common carotid artery stenosis (BCAS) mouse model of VaD was established, and the expression of the hub gene, its relationship with cognitive function and its potential pathogenic mechanism were verified by cognitive behavior tests, cerebral blood flow measurement, Western blotting, and immunofluorescence experiments.

RESULTS

This study identified 293 DEGs from the brain cortex of VaD patients and healthy controls, among these genes, the Toll-like receptor 2 (TLR2) gene was identified as hub gene, and it was associated with the apoptosis-related pathway PI3K/AKT.The BCAS model demonstrated that the use of TLR2 inhibitors greatly enhanced the cognitive function of the mice (p < 0.05). Additionally, there was a notable decrease in the number of apoptotic cells in the brain cortex of the mice (p < 0.01). Moreover, significant alterations in the levels of proteins related to the PI3K/AKT pathway and cleaved-caspase3 proteins were detected (p < 0.05).

CONCLUSIONS

TLR2 plays a role in the pathophysiology of VaD by enhancing the neuronal apoptotic pathway, suggesting it could be a promising therapeutic target.

Amino Acid Transporters Proteins Involved in the Glutamate-Glutamine Cycle and Their Alterations in Murine Models of Alzheimer's Disease

The brain's ability to integrate external stimuli and generate responses is highly complex. While these mechanisms are not completely understood, current evidence suggests that alterations in cellular metabolism and microenvironment are involved in some dysfunctions as complex as Alzheimer's disease. This pathology courses with defects in the establishment of chemical synapses, which is dependent on the production and supply of neurotransmitters like glutamate and its recycling through the glutamate-glutamine cycle. Alterations in the expression and function of the amino acid transporters proteins involved in this cycle have recently been reported in different stages of Alzheimer's disease. Most of these data come from patients in advanced stages of the disease or post-mortem, due to the ethical and technical limitations of human studies. Therefore, genetically modified mouse models have been an excellent tool to analyze metabolic and even behavioral parameters that are very similar to those that develop in Alzheimer's disease, even at presymptomatic stages. Hence, this paper analyzes the role of glutamate metabolism and its intercellular trafficking in excitatory synapses from different approaches using transgenic mouse models; such an analysis will contribute to our present understanding of AD.

Surface protein profiling and subtyping of extracellular vesicles in body fluids reveals non-CSF biomarkers of Alzheimer's disease

Noninvasive and effortless diagnosis of Alzheimer's disease (AD) remains challenging. Here we report the multiplexed profiling of extracellular vesicle (EV) surface proteins at the single EV level in five types of easily accessible body fluids using a proximity barcoding assay (PBA). A total of 183 surface proteins were detected on the EVs from body fluids collected from APP/PS1 transgenic mice and patients with AD. The AD-associated differentially expressed EV proteins could discriminate between the control and AD/AD model samples with high accuracy. Based on machine learning predictive models, urinary EV proteins exhibited the highest diagnostic potential compared to those on other biofluid EVs, both in mice and humans. Single EV analysis further revealed AD-associated EV subpopulations in the tested body fluids, and a urinary EV subpopulation with the signature proteins PLAU, ITGAX and ANXA1 could diagnose patients with AD in blinded datasets with 88% accuracy. Our results suggest that EVs and their subpopulations from noninvasive body fluids, particularly urine, are potential diagnostic biomarkers for AD.

Identification of immune-associated genes in vascular dementia by integrated bioinformatics and inflammatory infiltrates

OBJECTIVE

Dysregulation of the immune system plays a vital role in the pathological process of vascular dementia, and this study aims to spot critical biomarkers and immune infiltrations in vascular dementia employing a bioinformatics approach.

METHODS

We acquired gene expression profiles from the Gene Expression Database. The gene expression data were analyzed using the bioinformatics method to identify candidate immune-related central genes for the diagnosis of vascular dementia. and the diagnostic value of nomograms and Receiver Operating Characteristic (ROC) curves were evaluated. We also examined the role of the VaD hub genes. Using the database and potential therapeutic drugs, we predicted the miRNA and lncRNA controlling the Hub genes. Immune cell infiltration was initiated to examine immune cell dysregulation in vascular dementia.

RESULTS

1321 immune genes were included in the combined immune dataset, and 2816 DEGs were examined in GSE122063. Twenty potential genes were found using differential gene analysis and co-expression network analysis. PPI network design and functional enrichment analysis were also done using the immune system as the main subject. To create the nomogram for evaluating the diagnostic value, four potential core genes were chosen by machine learning. All four putative center genes and nomograms have a solid diagnostic value (AUC ranged from 0.81 to 0.92). Their high confidence level became unquestionable by validating each of the four biomarkers using a different dataset. According to GeneMANIA and GSEA enrichment investigations, the pathophysiology of VaD is strongly related to inflammatory responses, drug reactions, and central nervous system degeneration. The data and Hub genes were used to construct a ceRNA network that includes three miRNAs, 90 lncRNA, and potential VaD therapeutics. Immune cells with varying dysregulation were also found.

CONCLUSION

Using bioinformatic techniques, our research identified four immune-related candidate core genes (HMOX1, EBI3, CYBB, and CCR5). Our study confirms the role of these Hub genes in the onset and progression of VaD at the level of immune infiltration. It predicts potential RNA regulatory pathways control VaD progression, which may provide ideas for treating clinical disease.

Molecular Mechanisms for Changing Brain Connectivity in Mice and Humans

The goal of this study was to examine commonalities in the molecular basis of learning in mice and humans. In previous work we have demonstrated that the anterior cingulate cortex (ACC) and hippocampus (HC) are involved in learning a two-choice visuospatial discrimination task. Here, we began by looking for candidate genes upregulated in mouse ACC and HC with learning. We then determined which of these were also upregulated in mouse blood. Finally, we used RT-PCR to compare candidate gene expression in mouse blood with that from humans following one of two forms of learning: a working memory task (network training) or meditation (a generalized training shown to change many networks). Two genes were upregulated in mice following learning: caspase recruitment domain-containing protein 6 (Card6) and inosine monophosphate dehydrogenase 2 (Impdh2). The Impdh2 gene product catalyzes the first committed step of guanine nucleotide synthesis and is tightly linked to cell proliferation. The Card6 gene product positively modulates signal transduction. In humans, Card6 was significantly upregulated, and Impdh2 trended toward upregulation with training. These genes have been shown to regulate pathways that influence nuclear factor kappa B (NF-κB), a factor previously found to be related to enhanced synaptic function and learning.

Comprehensive analysis of mRNAs in the cerebral cortex in APP/PS1 double-transgenic mice with Alzheimer's disease based on high-throughput sequencing of N4-acetylcytidine

N4-acetylcytidine (ac4C), a significant modified nucleoside, participates in the development of many diseases. Messenger RNAs (mRNAs) contain most of the information of the genome and are the molecules that transmit information from genes to proteins. Alzheimer's disease (AD) is a progressive neurodegenerative disease in which fibrillar amyloid plaques are present. However, it remains unknown how mRNA ac4C modification affects the development of AD. In the current study, ac4C-modified mRNAs were comprehensively analyzed in AD mice by ac4C-RIP-seq and RNA-seq. Next, a protein-protein interaction (PPI) network was constructed to examine the relationships between the genes with differential ac4C modification levels and their RNA expression levels. The differentially expressed genes (DEGs) acquired above were subjected to Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to further analyze the molecular mechanisms in AD. In total, 3312 significant ac4C peaks were found on 2512 mRNAs, 1241 of which were hyperacetylated and 1271 of which were hypoacetylated. In addition, 956 mRNAs with differential expression were found, including 520 upregulated mRNAs and 436 downregulated mRNAs. Overall, 134 mRNAs with simultaneous changes at the ac4C levels as well as RNA expression levels were identified via joint analysis. Then, through PPI network construction and functional enrichment analysis, 37 key mRNAs were screened, which were predominantly enriched in GABAergic synapses and the PI3K/AKT signaling pathway. The significant difference in the abundance of mRNA ac4C modification indicates that this modification is associated with AD progression, which may provide insight for more investigations of the potential mechanisms.

Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease

Proteomic studies for Alzheimer's disease (AD) are instrumental in identifying AD pathways but often focus on single tissues and sporadic AD cases. Here, we present a proteomic study analyzing 1305 proteins in brain tissue, cerebrospinal fluid (CSF), and plasma from patients with sporadic AD, TREM2 risk variant carriers, patients with autosomal dominant AD (ADAD), and healthy individuals. We identified 8 brain, 40 CSF, and 9 plasma proteins that were altered in individuals with sporadic AD, and we replicated these findings in several external datasets. We identified a proteomic signature that differentiated TREM2 variant carriers from both individuals with sporadic AD and healthy individuals. The proteins associated with sporadic AD were also altered in patients with ADAD, but with a greater effect size. Brain-derived proteins associated with ADAD were also replicated in additional CSF samples. Enrichment analyses highlighted several pathways, including those implicated in AD (calcineurin and Apo E), Parkinson's disease (α-synuclein and LRRK2), and innate immune responses (SHC1, ERK-1, and SPP1). Our findings suggest that combined proteomics across brain tissue, CSF, and plasma can be used to identify markers for sporadic and genetically defined AD.

A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy

Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.

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

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

Identification and Validation of Aging-Related Genes in Alzheimer’s Disease

Aging is recognized as the key risk factor for Alzheimer’s disease (AD). This study aimed to identify and verify potential aging-related genes associated with AD using bioinformatics analysis. Aging-related differential expression genes (ARDEGs) were determined by the intersection of limma test, weighted correlation network analysis (WGCNA), and 1153 aging and senescence-associated genes. Potential biological functions and pathways of ARDEGs were determined by GO, KEGG, GSEA, and GSVA. Then, LASSO algorithm was used to identify the hub genes and the diagnostic ability of the five ARDEGs in discriminating AD from the healthy control samples. Further, the correlation between hub ARDEGs and clinical characteristics was explored. Finally, the expression level of the five ARDEGs was validated using other four GEO datasets and blood samples of patients with AD and healthy individuals. Five ARDEGs (GFAP, PDGFRB, PLOD1, MAP4K4, and NFKBIA) were obtained. For biological function analysis, aging, cellular senescence, and Ras protein signal transduction regulation were enriched. Diagnostic ability of the five ARDEGs in discriminating AD from the control samples demonstrated a favorable diagnostic value. Eventually, quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) validation test revealed that compared with healthy controls, the mRNA expression level of PDGFRB, PLOD1, MAP4K4, and NFKBIA were elevated in AD patients. In conclusion, this study identified four ARDEGs (PDGFRB, PLOD1, MAP4K4, and NFKBIA) associated with AD. They provide an insight into potential novel biomarkers for diagnosing AD and monitoring progression.

Identification of Differential Genes of DNA Methylation Associated With Alzheimer's Disease Based on Integrated Bioinformatics and Its Diagnostic Significance

Background

Alzheimer's disease (AD) is a common neurodegenerative disease. The pathogenesis is complex and has not been clearly elucidated, and there is no effective treatment. Recent studies have demonstrated that DNA methylation is closely associated with the pathogenesis of AD, which sheds light on investigating potential biomarkers for the diagnosis of early AD and related possible therapeutic approaches.

Methods

Alzheimer's disease patients samples and healthy controls samples were collected from two datasets in the GEO database. Using LIMMA software package in R language to find differentially expressed genes (DEGs). Afterward, DEGs have been subjected to enrichment analysis of GO and KEGG pathways. The PPI networks and Hub genes were created and visualized based on the STRING database and Cytoscape. ROC curves were further constructed to analyze the accuracy of these genes for AD diagnosis.

Results

Analysis of the GSE109887 and GSE97760 datasets showed 477 significant DEGs. GO and KEGG enrichment analysis showed terms related to biological processes related to these genes. The top ten Hub genes were found on the basis of the PPI network using the CytoHubba plugin, and the AUC areas of these top ranked genes were all greater than 0.7, showing satisfactory diagnostic accuracy.

Conclusion

The study identified the top 10 Hub genes associated with AD-related DNA methylation, of which RPSA, RPS23, and RPLP0 have high diagnostic accuracy and excellent AD biomarker potential.

Platelet Activating Factor Receptor Exaggerates Microglia-Mediated Microenvironment by IL10-STAT3 Signaling: A Novel Potential Biomarker and Target for Diagnosis and Treatment of Alzheimer's Disease

Background

Early diagnosis and effective intervention are the keys to delaying the progression of Alzheimer's Disease (AD). Therefore, we aimed to identify new biomarkers for the early diagnosis of AD through bioinformatic analysis and elucidate the possible underlying mechanisms.

Methods and Results

GSE1297, GSE63063, and GSE110226 datasets from the GEO database were used to screen the highly differentially expressed genes. We identified a potential biomarker, Platelet activating factor receptor (PTAFR), significantly upregulated in the brain tissue, peripheral blood, and cerebrospinal fluid of AD patients. Furthermore, PTAFR levels in the plasma and brain tissues of APP/PS1 mice were significantly elevated. Simultaneously, PTAFR could mediate the inflammatory responses to exaggerate the microenvironment, particularly mediated by the microglia through the IL10-STAT3 pathway. In addition, PTAFR was a putative target of anti-AD compounds, including EGCG, donepezil, curcumin, memantine, and Huperzine A.

Conclusion

PTAFR was a potential biomarker for early AD diagnosis and treatment which correlated with the microglia-mediated microenvironment. It is an important putative target for the development of a novel strategy for clinical treatment and drug discovery for AD.

Identification and Analysis of BCAS4/hsa-miR-185-5p/SHISA7 Competing Endogenous RNA Axis in Late-Onset Alzheimer’s Disease Using Bioinformatic and Experimental Approaches

Alzheimer’s disease (AD) is a heterogeneous degenerative brain disorder with a rising prevalence worldwide. SHISA7 (CKAMP59) has emerged as one of the most intriguing new members of the SHISA family, in that, unlike other CKAMP counterparts, it exhibits a direct function in inhibitory synaptic GABAAR regulation. We used bioinformatics and experimental methods in this research to explore competing endogenous RNA (ceRNA) regulation of BCAS4 and SHISA7 in tau pathogenesis and their capacity as peripheral biomarkers linked to an abnormal inflammatory response in AD. The Gene Expression Omnibus database included two microarray datasets, including information on mRNAs (GSE106241) and miRNAs (GSE157239) from individuals with AD with different degrees of AD-associated neurofibrillary pathology in the temporal cortex (TC) tissue specimens and corresponding controls were downloaded from the Gene Expression Omnibus database. The limma package in the R software was used to identify differently expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) associated with AD-related neurofibrillary pathology. Additionally, we used the quantitative polymerase chain reaction technique to examine the expression of the BCAS4/hsa-miR-185-5p/SHISA7 ceRNA axis in the peripheral blood (PB) of fifty AD patients and fifty control subjects. BCAS4 was shown to act as a ceRNA to control the SHISA7 expression throughout AD-associated neurofibrillary pathology in TC tissue specimens by sponging hsa-miR-185-5p, based on our bioinformatics study. Furthermore, in PB specimens from individuals suffering from AD and normal controls, we found no substantial differences in BCAS4 expression patterns. SHISA7 expression in AD patients’ PB was found to be reduced, as was the case in the TC. On the other hand, we discovered reduced amounts of hsa-miR-185-5p in AD patients’ PB samples compared to control subjects, unlike in TC tissue, where it had been demonstrated to be overexpressed. BCAS4 and SHISA7 expression levels showed a strong positive correlation, suggesting the presence of an interconnected network, most likely as a result of ceRNA regulation among PB specimens. The present study is the first evidence to highlight the expression of the BCAS4/miR-185-5p/SHISA7 ceRNA axis in the brain and PB of AD patients, and offers a new viewpoint on molecular processes underlying AD pathogenic mechanisms.

Identification of Molecular Signatures and Candidate Drugs in Vascular Dementia by Bioinformatics Analyses

Vascular dementia (VaD) is considered to be the second most common form of dementia after Alzheimer’s disease, and no specific drugs have been approved for VaD treatment. We aimed to identify shared transcriptomic signatures between the frontal cortex and temporal cortex in VaD by bioinformatics analyses. Gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) and hub gene identification, hub gene–transcription factor interaction, hub gene–microRNA interaction, and hub gene–drug interaction analyses were performed. We identified 159 overlapping differentially expressed genes (DEGs) between the frontal cortex and temporal cortex that were enriched mainly in inflammation and innate immunity, synapse pruning, regeneration, positive regulation of angiogenesis, response to nutrient levels, and positive regulation of the digestive system process. We identified 10 hub genes in the PPI network (GNG13, CD163, C1QA, TLR2, SST, C1QB, ITGB2, CCR5, CRH, and TAC1), four central regulatory transcription factors (FOXC1, CREB1, GATA2, and HINFP), and four microRNAs (miR-27a-3p, miR-146a-5p, miR-335-5p, and miR-129-2-3p). Hub gene–drug interaction analysis found four drugs (maraviroc, cenicriviroc, PF-04634817, and efalizumab) that could be potential drugs for VaD treatment. Together, our results may contribute to understanding the underlying mechanisms in VaD and provide potential targets and drugs for therapeutic intervention.

The bioinformatic approach identifies PARM1 as a new potential prognostic factor in osteosarcoma

Objective

To explore the key factors affecting the prognosis of osteosarcoma patients.

Methods

Based on the GEO dataset and differential expression analysis of normal and osteosarcoma tissues, the gene modules related to the prognosis of osteosarcoma patients were screened by WGCNA, and intersecting genes were taken with differential genes, and the risk prognosis model of osteosarcoma patients was constructed by LASSO regression analysis of intersecting genes, and the prognosis-related factors of osteosarcoma patients were obtained by survival analysis, followed by target for validation, and finally, the expression of prognostic factors and their effects on osteosarcoma cell migration were verified by cellular assays and lentiviral transfection experiments.

Results

The prognosis-related gene module of osteosarcoma patients were intersected with differential genes to obtain a total of 9 common genes. PARM1 was found to be a prognostic factor in osteosarcoma patients by LASSO regression analysis, followed by cellular assays to verify that PARM1 was lowly expressed in osteosarcoma cells and that overexpression of PARM1 in osteosarcoma cells inhibited cell migration. Pan-cancer analysis showed that PARM1 was lowly expressed in most cancers and that low expression of PARM1 predicted poor prognosis for patients.

Conclusion

The data from this study suggest that PARM1 is closely associated with the prognosis of osteosarcoma patients, and PARM1 may serve as a novel potential prognostic target for osteosarcoma, providing a heartfelt direction for the prevention and treatment of osteosarcoma.

Immune abnormalities and differential gene expression in the hippocampus and peripheral blood of patients with Alzheimer's disease

Background

Despite decades of research, no precise mechanisms of Alzheimer's disease (AD) development have been elucidated. This study aimed to investigate novel diagnostic biomarkers in both peripheral blood cells and hippocampus tissue, and the pathogenesis of memory impairment in AD.

Methods

mRNA microarray data, including hippocampus samples (GSE1297 and GSE5281) and peripheral blood mononuclear cells (PBMCs) (GSE63060 and GSE63061), associated with AD were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AD and normal-aging samples were screened through a comprehensive analysis of multiple gene expression spectra after gene reannotation and batch normalization. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to analyze hub genes and to discover potential biomarkers related to AD. Protein-protein interaction (PPI) network maps were constructed to visualize the correlation between possible genes. The CIBERSORT algorithm was built to explore the patterns of PBMC infiltration to investigate the role of inflammation in the pathogenesis of AD.

Results

The bioinformatics analysis indicated 1,261 DEGs in the hippocampal samples and 290 in PBMCs when comparing patients with AD with normal-aging individuals. We selected 28 genes co-expressed in the hippocampus and PBMCs. A functional analysis of differential genes revealed that they were primarily involved in neuronal death, immune response, and mitochondrial function. Further, immune cell infiltration patterns demonstrated that the levels of naive CD4⁺ T cells, resting natural killer cells, M0 macrophages, and activated mast cells were higher in the peripheral blood of patients with AD, while resting memory CD4⁺ T cells were significantly lower.

Conclusions

The key gene changes present in both the hippocampus and PBMCs highly suggest their utility as an AD biomarker. In addition, according to our present results, immune abnormalities may have an important role in AD pathophysiology. When patients display these peripheral blood immune abnormalities, they may be recognized as being at high risk of developing AD.

Identification of SLITRK6 as a Novel Biomarker in hepatocellular carcinoma by comprehensive bioinformatic analysis

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the adult liver and morbidity are increasing in recent years, however, there is still no effective strategy to prevent and diagnose HCC. Therefore, it is urgent to research the effective biomarker to predict clinical outcomes of HCC tumorigenesis. In the current study, differentially expressed genes in HCC and normal tissues were investigated using the Gene Expression Omnibus (GEO) dataset GSE144269 and The Cancer Genome Atlas (TCGA). Gene differential expression analysis and weighted correlation network analysis (WGCNA) methods were used to identify nine and 16 key gene modules from the GEO dataset and TCGA dataset, respectively, in which the green module in the GEO dataset and magenta module in TCGA were significantly correlated with HCC occurrence. Third, the enrichment score of gene function annotation results showed that these two key modules focus on the positive regulation of inflammatory response and cell differentiation, etc. Besides, PPI network analysis, mutation analysis, and survival analysis found that SLITRK6 had high connectivity, and its mutation significantly impacted overall survival. In addition, SLITRK6 was found to be low expressed in tumor cells. To summarize, SLITRK6 mutation was found to significantly affect the occurrence and prognosis of HCC. SLITRK6 was confirmed as a new potential gene target for HCC, which may provide a new theoretical basis for personalized diagnosis and chemotherapy of HCC in the future.

Reduced Blood RGS2 Expression in Mild Cognitive Impairment Patients

Regulator of G protein signaling 2 (RGS2) is a gene involved in neuronal plasticity and synaptic signaling, whose expression in the brain is altered in neuropsychiatric and neurodegenerative disorders. Microarray data from large datasets suggested reduced RGS2 mRNA levels in the post-mortem brain tissue and blood of Alzheimer’s disease (AD) patients. The results were previously confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) only ex vivo in lymphoblastoid cell lines derived from AD patients and controls. In this study, we compared RGS2 mRNA levels in peripheral blood samples from 69 mild cognitive impairment (MCI) patients to 50 age- and sex-matched non-cognitively impaired controls, out of which 25 patients were monitored at 1 year. We found that RGS2 was indeed downregulated in the peripheral blood of these patients (FR = −1.60, p < 0.001), and despite disease-specific therapy, RGS2 transcript levels continued to decrease at 1 year. The results suggest that RGS2 seems to be involved in AD pathology and progression and can be introduced in a panel of blood AD biomarkers.

New RNA-Based Breakthroughs in Alzheimer's Disease Diagnosis and Therapeutics

Dementia is described as the fifth leading cause of death worldwide and Alzheimer’s disease (AD) is recognized as the most common, causing a huge impact on health costs and quality of patients’ lives. The main hallmarks that are commonly associated with the pathologic process are amyloid deposition, pathologic Tau phosphorylation and neurodegeneration. It is still unclear how these events are linked to the disease progression, due to the complex pathologic mechanisms. Nevertheless, several hypotheses have been proposed for a better understanding of AD. The AD diagnosis is performed by using a combination of several tools to detect β-amyloid peptide (Aβ) deposits and modifications in cognitive performance, sometimes being expensive and invasive. In the treatment field, there is still an absence of effective treatments to delay or stop the progression of the disease, with most of the approved drugs used to relieve symptoms, and all of them with significant adverse side effects. Considering all limitations, the need to establish new and more effective diagnostic and therapeutic strategies becomes clear. This review aims not only to describe the disease and its impact but also to collect the currently available diagnostic and therapeutic strategies, highlighting new promising RNA-based strategies for AD.

Single-Cell RNA Sequencing of Peripheral Blood Reveals Immune Cell Signatures in Alzheimer's Disease

The peripheral immune system is thought to affect the pathology of the central nervous system in Alzheimer’s disease (AD). However, current knowledge is inadequate for understanding the characteristics of peripheral immune cells in AD. This study aimed to explore the molecular basis of peripheral immune cells and the features of adaptive immune repertoire at a single cell level. We profiled 36,849 peripheral blood mononuclear cells from AD patients with amyloid-positive status and normal controls with amyloid-negative status by 5’ single-cell transcriptome and immune repertoire sequencing using the cell ranger standard analysis procedure. We revealed five immune cell subsets: CD4+ T cells, CD8+ T cells, B cells, natural killer cells, and monocytes–macrophages cells, and disentangled the characteristic alterations of cell subset proportion and gene expression patterns in AD. Thirty-one cell type-specific key genes, comprising abundant human leukocyte antigen genes, and multiple immune-related pathways were identified by protein–protein interaction network and pathway enrichment analysis. We also found high-frequency amplification clonotypes in T and B cells and decreased diversity in T cells in AD. As clone amplification suggested the activation of an adaptive immune response against specific antigens, we speculated that the peripheral adaptive immune response, especially mediated by T cells, may have a role in the pathogenesis of AD. This finding may also contribute to further research regarding disease mechanism and the development of immune-related biomarkers or therapy.

Inflammatory gene expression profiling in peripheral blood from patients with Alzheimer's disease reveals key pathways and hub genes with potential diagnostic utility: a preliminary study

BACKGROUND

Alzheimer's disease (AD) is an age-related neurodegenerative disease caused by central nervous system disorders. Late-onset Alzheimer disease (LOAD) is the most common neurodegenerative disorder worldwide. Differences at the expression level of certain genes, resulting from either genetic variations or environmental interactions, might be one of the mechanisms underlying differential risks for developing AD. Peripheral blood genome transcriptional profiling may provide a powerful and minimally invasive tool for the identification of novel targets beyond Aβ and tau for AD research.

METHODS

This preliminary study explores molecular pathogenesis of LOAD-related inflammation through next generation sequencing, to assess RNA expression profiles in peripheral blood from five patients with LOAD and 10 healthy controls.

RESULTS

The analysis of RNA expression profiles revealed 94 genes up-regulated and 147 down-regulated. Gene function analysis, including Gene Ontology (GO) and KOBAS-Kyoto Encyclopedia of DEGs and Genomes (KEGG) pathways indicated upregulation of interferon family (INF) signaling, while the down-regulated genes were mainly associated with the cell cycle process. KEGG metabolic pathways mapping showed gene expression alterations in the signaling pathways of JAK/STAT, chemokines, MAP kinases and Alzheimer disease. The results of this preliminary study provided not only a comprehensive picture of gene expression, but also the key processes associated with pathology for the regulation of neuroinflammation, to improve the current mechanisms to treat LOAD.

Advances in multiplex PCR for Alzheimer's disease diagnostics targeting CDK genes

Alzheimer's disease (AD) is a common neurodegenerative disease that lacks biomarkers for diagnosis. Biomarkers for accurate detection of AD are required for potential therapeutic approaches. Recent studies in mammalian cells have demonstrated an association between the expression of cell cycle proteins and AD occurrence. Therefore, we aimed to identify a potent biomarker among relevant cell cycle-regulating proteins such as cyclin-dependent kinases (CDKs) for the diagnosis of AD. We also developed a multiplex-PCR-based diagnostic method, which showed the rapid and accurate detection of AD biomarkers. Genome-wide association study (GWAS) results showed increased gene expression of CDKs in an AD mouse model. Based on genomic analysis, our multiplex-PCR method, which contained optimized primer sets and PCR conditions targeting genes of CDKs, accurately matched RT-PCR results in the AD mouse model. Interestingly, validation by in silico meta-analysis for the expression of each CDK gene showed significant expression in moderate and severe groups of AD patients. Accordingly, clinical applications relying on the diagnosis of AD using our results may shed light on AD therapeutics.

Dysregulated gene-associated biomarkers for Alzheimer's disease and aging

Alzheimer’s disease (AD), the most common type of dementia, is a neurodegenerative disorder with a hidden onset, including difficult early detection and diagnosis. Nevertheless, the new crucial biomarkers for the diagnosis and pathogenesis of AD need to be explored further. Here, the common differentially expressed genes (DEGs) were identified through a comprehensive analysis of gene expression profiles from the Gene Expression Omnibus (GEO) database. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these DEGs were mainly associated with biological processes, cellular components, and molecular functions, which are involved in multiple cellular functions. Next, we found that 9 of the 24 genes showed the same regulatory changes in the blood of patients with AD compared to those in the GEO database, and 2 of the 24 genes showed a significant correlation with Montreal Cognitive Assessment scores. Finally, we determined that mice with AD and elderly mice had the same regulatory changes in the identified DEGs in both the blood and hippocampus. Our study identified several potential core biomarkers of AD and aging, which could contribute to the early detection, differential diagnosis, treatment, and pathological analysis of AD.

Identification of Hub Genes Related to Alzheimer's Disease and Major Depressive Disorder

BackgroundAlthough many studies reported a close relationship between depression and Alzheimer's disease (AD), the underlying pathophysiological mechanism remains unclear. The present study aimed to investigate the mechanism of AD and major depressive disorder (MDD). Method: The datasets were downloaded from the Gene Expression Omnibus. After screening differentially expressed genes (DEGs), gene ontology and pathway analysis were performed and protein-protein interaction, TF-target gene, and miRNA-target gene networks were established. Results: 171 DEGs of AD-related datasets and 79 DEGs shared by AD and MDD were detected. Functional analysis revealed that AD and MDD common genes were significantly enriched in circadian entrainment and long-term depression signaling pathways. Five hub genes were identified after construction of networks and validation of hub gene signatures. In conclusion, DYNC1H1, MAPRE3, TTBK2, ITGB1, and WASL may be potential targets for the diagnosis and treatment of AD and MDD.

Immune and Inflammatory Pathways Implicated by Whole Blood Transcriptomic Analysis in a Diverse Ancestry Alzheimer's Disease Cohort

BACKGROUND

Significant work has identified genetic variants conferring risk and protection for Alzheimer's disease (AD), but functional effects of these variants is lacking, particularly in under-represented ancestral populations. Expression studies performed in easily accessible tissue, such as whole blood, can recapitulate some transcriptional changes occurring in brain and help to identify mechanisms underlying neurodegenerative processes.

OBJECTIVE

We aimed to identify transcriptional differences between AD cases and controls in a cohort of diverse ancestry.

METHODS

We analyzed the protein coding transcriptome using RNA sequencing from peripheral blood collected from 234 African American (AA) (115 AD, 119 controls) and 240 non-Hispanic Whites (NHW) (121 AD, 119 controls). To identify case-control differentially expressed genes and pathways, we performed stratified, joint, and interaction analyses using linear regression models within and across ancestral groups followed by pathway and gene set enrichment analyses.

RESULTS

Overall, we identified 418 (291 upregulated, 127 downregulated) and 488 genes (352 upregulated, 136 downregulated) differentially expressed in the AA and NHW datasets, respectively, with only 16 genes commonly differentially expressed in both ancestral groups. Joint analyses provided greater power to detect case-control differences and identified 1,102 differentially expressed genes between cases and controls (812 upregulated, 290 downregulated). Interaction analysis identified only 27 genes with different effects in AA compared to NHW. Pathway and gene-set enrichment analyses revealed differences in immune response-related pathways that were enriched across the analyses despite different underlying gene sets.

CONCLUSION

These results support the hypothesis of converging underlying pathophysiological processes in AD across ancestral groups.

Predictive Potential of Circulating Ube2h mRNA as an E2 Ubiquitin-Conjugating Enzyme for Diagnosis or Treatment of Alzheimer's Disease

Neurodegenerative disorders are caused by neuronal cell death, miscommunications between synapse, and abnormal accumulations of proteins in the brain. Alzheimer’s disease (AD) is one of the age-related disorders, which are the most common degenerative disorders today, and strongly affects memory consolidation and cognitive function in the brain. Amyloid-β and tau proteins are triggers for AD pathogenesis, and usually used as AD candidate biomarkers in the clinical research. Especially, clinical exam, brain imaging and molecular biological methods are being used to diagnosis for AD. Genome-wide association study (GWAS) is a new biomedical method, and its use contributes to understanding many human diseases, including brain diseases. Here, we identified ubiquitin conjugating enzyme E2 (Ube2) gene expression in neurons through GWAS. The subfamilies of Ube2’s genetic expression and inborn errors affect the ubiquitin proteasome system (UPS), leading to protein degradation in the brain. We found that only Ube2h mRNA transcription was significantly increased in the blood from AD, however we did not find any change of Ube2 subfamily genes’ expression in the blood and brain tissue. These data may provide information for diagnosis or clinical approach, and suggest that cell-free circulating Ube2h mRNA is a novel potential biomarker for AD.

Comparison of serum protein profiles between major depressive disorder and bipolar disorder

BACKGROUND

Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders.

METHODS

Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted.

RESULTS

Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10^- 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10^- 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p = 1.5 × 10^- 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different.

CONCLUSIONS

Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.