Identification of key transcriptome biomarkers based on a vital gene module associated with pathological changes in Alzheimer's disease

Analysis of the mechanism of fibrauretine alleviating Alzheimer's disease based on transcriptomics and proteomics

The dried rattan stem of the Fibraurea Recisa Pierre plant contains the active ingredient known as fibrauretine (FN). Although it greatly affects Alzheimer's disease (AD), the mechanism of their effects still remains unclear. Proteomics and transcriptomics analysis methods were used in this study to determine the mechanism of FN in the treatment of AD. AD model is used through bilateral hippocampal injection of Aβ1-40. After successful modeling, FN was given for 30 days. The results showed that FN could improve the cognitive dysfunction of AD model rats, reduce the expression of Aβ and P-Tau, increase the content of acetylcholine and reduce the activity of acetylcholinesterase. The Kyoto Encyclopedia of Genes and Genomes enriched differentially expressed genes and proteins are involved in signaling pathways including metabolic pathway, AD, pathway in cancer, PI3K-AKT signaling pathway, and cAMP signaling pathway. Transcriptomics and proteomics sequencing resulted in 19 differentially expressed genes and proteins. Finally, in contrast to the model group, after FN treatment, the protein expressions and genes associated with the PI3K-AKT pathway were significantly improved in RT-qPCR and Western blot and assays. This is consistent with the findings of transcriptomic and proteomic analyses. Our study found that, FN may improve some symptoms of AD model rats through PI3K-AKT signaling pathway.

A systematic review and meta-analysis of tau phosphorylation in mouse models of familial Alzheimer's disease

Transgenic models of familial Alzheimer's disease (AD) serve as valuable tools for probing the molecular mechanisms associated with amyloid-beta (Aβ)-induced pathology. In this meta-analysis, we sought to evaluate levels of phosphorylated tau (p-tau) and explore potential age-related variations in tau hyperphosphorylation, within mouse models of AD. The PubMed and Scopus databases were searched for studies measuring soluble p-tau in 5xFAD, APPswe/PSEN1de9, J20 and APP23 mice. Data were extracted and analyzed using standardized procedures. For the 5xFAD model, the search yielded 36 studies eligible for meta-analysis. Levels of p-tau were higher in 5xFAD mice relative to control, a difference that was evident in both the carboxy-terminal (CT) and proline-rich (PR) domains of tau. Age negatively moderated the relationship between genotype and CT phosphorylated tau in studies using hybrid mice, female mice, and preparations from the neocortex. For the APPswe/PSEN1de9 model, the search yielded 27 studies. Analysis showed tau hyperphosphorylation in transgenic vs. control animals, evident in both the CT and PR regions of tau. Age positively moderated the relationship between genotype and PR domain phosphorylated tau in the neocortex of APPswe/PSEN1de9 mice. A meta-analysis was not performed for the J20 and APP23 models, due to the limited number of studies measuring p-tau levels in these mice (<10 studies). Although tau is hyperphosphorylated in both 5xFAD and APPswe/PSEN1de9 mice, the effects of ageing on p-tau are contingent upon the model being examined. These observations emphasize the importance of tailoring model selection to the appropriate disease stage when considering the relationship between Aβ and tau, and suggest that there are optimal intervention points for the administration of both anti-amyloid and anti-tau therapies.

miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer's disease

BACKGROUND

Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers.

METHODS

We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification.

RESULTS

Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs.

CONCLUSIONS

Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Identification of microRNA-mRNA Regulatory Networks with Therapeutic Values in Alzheimer's Disease by Bioinformatics Analysis

Background

Alzheimer's disease (AD) is the most prevalent neurological disorder worldwide, affecting approximately 24 million individuals. Despite more than a century of research on AD, its pathophysiology is still not fully understood.

Objective

Recently, genetic studies of AD have focused on analyzing the general expression profile by employing high-throughput genomic techniques such as microarrays. Current research has leveraged bioinformatics advancements in genetic science to build upon previous efforts.

Methods

Data from the GSE118553 dataset used in this investigation, and the analyses carried out using programs such as Limma and BioBase. Differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRs) associated with AD identified in the studied areas of the brain. Target genes of the DEmiRs identified using the MultiMiR package. Gene ontology (GO) completed using the Enrichr website, and the protein-protein interaction (PPI) network for these genes drawn using STRING and Cytoscape software.

Results

The findings introduced DEGs including CTNNB1, PAK2, MAP2K1, PNPLA6, IGF1R, FOXL2, DKK3, LAMA4, PABPN1, and GDPD5, and DEmiRs linked to AD (miR-106A, miR-1826, miR-1253, miR-10B, miR-18B, miR-101-2, miR-761, miR-199A1, miR-379 and miR-668), (miR-720, miR-218-2, miR-25, miR-602, miR-1226, miR-548K, miR-H1, miR-410, miR-548F2, miR-181A2), (miR-1470, miR-651, miR-544, miR-1826, miR-195, miR-610, miR-599, miR-323, miR-587 and miR-340), and (miR-1282, miR-1914, miR-642, miR-1323, miR-373, miR-323, miR-1322, miR-612, miR-606 and miR-758) in cerebellum, frontal cortex, temporal cortex, and entorhinal cortex, respectively.

Conclusions

The majority of the genes and miRNAs identified by our findings may be employed as biomarkers for prediction, diagnosis, or therapy response monitoring.

Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication

Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects.

miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer's disease

Background

Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers.

Methods

We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification.

Results

Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules, and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and apoE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs.

Conclusions

Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication

Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects.

One-Sentence Summary

A brain-penetrant inhibitor of G9a methylase blocks G9a translational mechanism to reverse Alzheimer's disease related proteome for effective therapy.

Longitudinal APOE4- and amyloid-dependent changes in the blood transcriptome in cognitively intact older adults

BACKGROUND

Gene expression is dysregulated in Alzheimer's disease (AD) patients, both in peripheral blood and post mortem brain. We investigated peripheral whole-blood gene (co)expression to determine molecular changes prior to symptom onset.

METHODS

RNA was extracted and sequenced for 65 cognitively healthy F-PACK participants (65 (56-80) years, 34 APOE4 non-carriers, 31 APOE4 carriers), at baseline and follow-up (interval: 5.0 (3.4-8.6) years). Participants received amyloid PET at both time points and amyloid rate of change derived. Accumulators were defined with rate of change ≥ 2.19 Centiloids. We performed differential gene expression and weighted gene co-expression network analysis to identify differentially expressed genes and networks of co-expressed genes, respectively, with respect to traits of interest (APOE4 status, amyloid accumulation (binary/continuous)), and amyloid positivity status, followed by Gene Ontology annotation.

RESULTS

There were 166 significant differentially expressed genes at follow-up compared to baseline in APOE4 carriers only, whereas 12 significant differentially expressed genes were found only in APOE4 non-carriers, over time. Among the significant genes in APOE4 carriers, several had strong evidence for a pathogenic role in AD based on direct association scores generated from the DISQOVER platform: NGRN, IGF2, GMPR, CLDN5, SMIM24. Top enrichment terms showed upregulated mitochondrial and metabolic pathways, and an exacerbated upregulation of ribosomal pathways in APOE4 carriers compared to non-carriers. Similarly, there were 33 unique significant differentially expressed genes at follow-up compared to baseline in individuals classified as amyloid negative at baseline and positive at follow-up or amyloid positive at both time points and 32 unique significant differentially expressed genes over time in individuals amyloid negative at both time points. Among the significant genes in the first group, the top five with the highest direct association scores were as follows: RPL17-C18orf32, HSP90AA1, MBP, SIRPB1, and GRINA. Top enrichment terms included upregulated metabolism and focal adhesion pathways. Baseline and follow-up gene co-expression networks were separately built. Seventeen baseline co-expression modules were derived, with one significantly negatively associated with amyloid accumulator status (r² =  - 0.25, p = 0.046). This was enriched for proteasomal protein catabolic process and myeloid cell development. Thirty-two follow-up modules were derived, with two significantly associated with APOE4 status: one downregulated (r² =  - 0.27, p = 0.035) and one upregulated (r² = 0.26, p = 0.039) module. Top enrichment processes for the downregulated module included proteasomal protein catabolic process and myeloid cell homeostasis. Top enrichment processes for the upregulated module included cytoplasmic translation and rRNA processing.

CONCLUSIONS

We show that there are longitudinal gene expression changes that implicate a disrupted immune system, protein removal, and metabolism in cognitively intact individuals who carry APOE4 or who accumulate in cortical amyloid. This provides insight into the pathophysiology of AD, whilst providing novel targets for drug and therapeutic development.

Gα13-Mediated Signaling Cascade Is Related to the Tau Pathology Caused by Anesthesia and Surgery in 5XFAD Transgenic Mice

BACKGROUND

Our previous studies indicated that anesthesia and surgery could aggravate cognitive impairment of 5XFAD transgenic (Tg) mice, and this aggravation was associated with tau hyperphosphorylation. We previously identified that GNA13 (the gene encoding Gα13) was a hub gene with tau hyperphosphorylation.

OBJECTIVE

This study aims to further investigate the mechanism that whether the Gα13-mediated signaling pathway acts as an instigator to regulate cofilin activation and autophagy impairment in this process.

METHODS

5XFAD Tg mice and their littermate (LM) mice were randomly allocated into four groups: LM Control group, LM Anesthesia/Surgery group, AD Control group, and AD Anesthesia/Surgery group. For mice in the Anesthesia/Surgery groups, abdominal surgery was performed under 1.4% isoflurane anesthesia followed by sustaining anesthetic inhalation for up to 2 h.

RESULTS

Compared with the AD Control group, protein levels of Gα13, ROCK2, LPAR5, and p-tau/tau46 ratio were increased, while p-cofilin/cofilin protein expression ratio was decreased in the AD Anesthesia/Surgery group. However, the differences in these protein levels were not significant among LM groups.

CONCLUSION

This study demonstrated that anesthesia and surgery might exacerbate p-tau accumulation in 5XFAD Tg mice but not in LM mice. And this might be closely related to cofilin activation via Gα13-mediated signaling cascade.

Identification of potentially functional modules and diagnostic genes related to amyotrophic lateral sclerosis based on the WGCNA and LASSO algorithms

Amyotrophic lateral sclerosis (ALS) is a genetically and phenotypically heterogeneous disease results in the loss of motor neurons. Mounting information points to involvement of other systems including cognitive impairment. However, neither the valid biomarker for diagnosis nor effective therapeutic intervention is available for ALS. The present study is aimed at identifying potentially genetic biomarker that improves the diagnosis and treatment of ALS patients based on the data of the Gene Expression Omnibus. We retrieved datasets and conducted a weighted gene co-expression network analysis (WGCNA) to identify ALS-related co-expression genes. Functional enrichment analysis was performed to determine the features and pathways of the main modules. We then constructed an ALS-related model using the least absolute shrinkage and selection operator (LASSO) regression analysis and verified the model by the receiver operating characteristic (ROC) curve. Besides we screened the non-preserved gene modules in FTD and ALS-mimic disorders to distinct ALS-related genes from disorders with overlapping genes and features. Altogether, 4198 common genes between datasets with the most variation were analyzed and 16 distinct modules were identified through WGCNA. Blue module had the most correlation with ALS and functionally enriched in pathways of neurodegeneration-multiple diseases', 'amyotrophic lateral sclerosis', and 'endocytosis' KEGG terms. Further, some of other modules related to ALS were enriched in 'autophagy' and 'amyotrophic lateral sclerosis'. The 30 top of hub genes were recruited to a LASSO regression model and 5 genes (BCLAF1, GNA13, ARL6IP5, ARGLU1, and YPEL5) were identified as potentially diagnostic ALS biomarkers with validating of the ROC curve and AUC value.

Co-expression network analysis of frontal cortex during the progression of Alzheimer's disease

Mechanisms of Alzheimer's disease (AD) and its putative prodromal stage, amnestic mild cognitive impairment (aMCI), involve the dysregulation of multiple candidate molecular pathways that drive selective cellular vulnerability in cognitive brain regions. However, the spatiotemporal overlap of markers for pathway dysregulation in different brain regions and cell types presents a challenge for pinpointing causal versus epiphenomenal changes characterizing disease progression. To approach this problem, we performed Weighted Gene Co-expression Network Analysis and STRING interactome analysis of gene expression patterns quantified in frontal cortex samples (Brodmann area 10) from subjects who died with a clinical diagnosis of no cognitive impairment, aMCI, or mild/moderate AD. Frontal cortex was chosen due to the relatively protracted involvement of this region in AD, which might reveal pathways associated with disease onset. A co-expressed network correlating with clinical diagnosis was functionally associated with insulin signaling, with insulin (INS) being the most highly connected gene within the network. Co-expressed networks correlating with neuropathological diagnostic criteria (e.g., NIA-Reagan Likelihood of AD) were associated with platelet-endothelium-leucocyte cell adhesion pathways and hypoxia-oxidative stress. Dysregulation of these functional pathways may represent incipient alterations impacting disease progression and the clinical presentation of aMCI and AD.

Identification of circRNA-miRNA-mRNA networks to explore the molecular mechanism and immune regulation of postoperative neurocognitive disorder

Postoperative neurocognitive disorder (PND) is a common complication in older patients. However, its pathogenesis has still remained elusive. Recent studies have shown that circular RNA (circRNA) plays an important role in the development of neurodegenerative diseases, such as PND after surgery. CircRNA, as a competitive endogenous RNA (ceRNA), mainly acts as a molecular sponge for miRNA to "adsorb" microRNA (miRNA) and to reduce the inhibitory effects of miRNAs on target mRNA. The sequencing data of circRNA were obtained from the Gene Expression Omnibus (GEO) database. By bioinformatic methods, circAtlas, miRDB, miRTarBase and miRwalk databases were applied to construct circRNA-miRNA-mRNA networks and screen differentially expressed mRNAs. To improve the accuracy of the data, we randomly divided aging mice into control (non-PND group) and PND groups, and used high-throughput sequencing to analyze their brain hippocampal tissue for analysis. Three key genes were cross-detected in the data of both groups, which were Unc13c, Tbx20 and St8sia2 (as hub genes), providing new targets for PND treatment. According to the results of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, immune cell infiltration analysis, gene set enrichment analysis (GSEA), Connectivity Map (CMap) analysis, quantitative real-time polymerase chain reaction (qRT-PCR), the genes that were not related to the central nervous system were removed, and finally, mmu_circ_0000331/miR-1224-3p/Unc13c and mmu_circ_0000406/miR-24-3p/St8sia2 ceRNA networks were identified. In addition, the CMap method was used to select the top 4 active compounds with the largest negative correlation absolute values, including cimaterol, Rucaparib, FG-7142, and Hydrocortisone.

Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases

Micro-RNAs (miRNAs) are short (∼21 nt) non-coding RNAs that regulate gene expression through the degradation or translational repression of mRNAs. Accumulating evidence points to a role of miRNA regulation in the pathogenesis of a wide range of neurodegenerative (ND) diseases such as, for example, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and Huntington disease (HD). Several systems level studies aimed to explore the role of miRNA regulation in NDs, but these studies remain challenging. Part of the problem may be related to the lack of sufficiently rich or homogeneous data, such as time series or cell-type-specific data obtained in model systems or human biosamples, to account for context dependency. Part of the problem may also be related to the methodological challenges associated with the accurate system-level modeling of miRNA and mRNA data. Here, we critically review the main families of machine learning methods used to analyze expression data, highlighting the added value of using shape-analysis concepts as a solution for precisely modeling highly dimensional miRNA and mRNA data such as the ones obtained in the study of the HD process, and elaborating on the potential of these concepts and methods for modeling complex omics data.

Active Compounds and Targets of Yuanzhi Powder in Treating Alzheimer's Disease and Its Relationship with Immune Infiltration Based on HPLC Fingerprint and Network Pharmacology

Background

Yuanzhi powder (YZP) has been extensively investigated as a natural prescription with therapeutic benefits for Alzheimer's disease (AD). However, its active compounds and underlying immune mechanism for treating AD are still unclear. This study aimed to investigate the immune mechanism of YZP against AD through high-performance liquid chromatography (HPLC)-based network pharmacology and gene chip technology.

Methods

Active components of YZP were obtained from HPLC and public databases. Subsequently, GSE5281, GSE28146, GSE29378, and GSE97760 from the Gene Expression Omnibus (GEO) database were downloaded to extract AD difference genes (DEGs). The active components-targets network and protein interaction network were then constructed by Cytoscape. The biological processes and signaling pathways, which implicate the targets of YZP for AD, were analyzed using the ClueGo Cytoscape plug-in. Molecular docking experiments were performed to verify the affinity of targets and ligands. Ultimately, the link between the hub genes and immune cell infiltration was assessed via CIBERSORT.

Results

83 YZP active compounds and 641 DEGs associated with AD, including quercetin, berberine, 3,6′-disinapoylsucrose, coptisine, and palmatine, were evaluated. We showed that FOS, CCL2, and GJA1 were the core targets and that the gap junction is an essential signaling pathway in YZP for AD. Furthermore, the AD group had a higher infiltration level of naïve B cells and resting CD4 memory T cells, as determined by the CIBERSORT. Notably, the immune cells-targets network demonstrates that GJA1 and GRM1 are intimately related to naïve B cells and plasma cells.

Conclusions

YZP may help treat AD by targeting proteins with key active compounds to regulate naïve B cells and plasma cells. Our results demonstrate a new immune mechanism for treating AD with YZP.

Key gene network related to primary ciliary dyskinesia in hippocampus of patients with Alzheimer’s disease revealed by weighted gene co-expression network analysis

Background

Alzheimer’s disease (AD) is closely related to aging, showing an increasing incidence rate for years. As one of the main brain regions involved in AD, hippocampus has been extensively studied due to its association with many human diseases. However, little is known about its association with primary ciliary dyskinesia (PCD).

Material and Methods

The microarray data of hippocampus on AD were retrieved from the Gene Expression Omnibus (GEO) database to construct the co-expression network by weighted gene co-expression network analysis (WGCNA). The gene network modules associated with AD screened with the common genes were further annotated based on Gene Ontology (GO) database and enriched based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The protein-protein interaction (PPI) network was constructed based on STRING database to identify the hub genes in the network.

Results

Genes involved in PCD were identified in the hippocampus of AD patients. Functional analysis revealed that these genes were mainly enriched in ciliary tissue, ciliary assembly, axoneme assembly, ciliary movement, microtubule based process, microtubule based movement, organelle assembly, axoneme dynamin complex, cell projection tissue, and microtubule cytoskeleton tissue. A total of 20 central genes, e.g., DYNLRB2, ZMYND10, DRC1, DNAH5, WDR16, TTC25, and ARMC4 were identified as hub genes related to PCD in hippocampus of AD patients.

Conclusion

Our study demonstrated that AD and PCD have common metabolic pathways. These common pathways provide novel evidence for further investigation of the pathophysiological mechanism and the hub genes suggest new therapeutic targets for the diagnosis and treatment of AD and PCD.

Subjects

Bioinformatics, Cell Biology, Molecular Biology, Neurology.

High-Throughput Sequencing to Investigate lncRNA-circRNA-miRNA-mRNA Networks Underlying the Effects of Beta-Amyloid Peptide and Senescence on Astrocytes

Astrocytes are widely distributed in the central nervous system and play an essential role in the function of neuronal cells. Associations between astrocytes and Alzheimer’s disease (AD) have been noted, and recent work has implicated circular RNA (circRNA) and long non-coding RNA (lncRNA) in the development of AD. However, few reports have investigated which lncRNA and circRNA are involved in the influence of amyloid beta (Aβ) and senescence on astrocytes. This study therefore examines changes at the transcriptome level to explore the effects of Aβ and senescence on astrocytes. Primary cultured astrocytes were treated with Aβ and cultured for 90 days in vitro, and high-throughput sequencing was performed to identify differentially expressed RNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that differentially expressed genes were associated with the focal adhesion signaling pathway, extracellular matrix receptor signaling pathway, and the extracellular matrix. The protein–protein interaction network was then constructed, and 103 hub genes were screened out; most of these were strongly associated with the expression of the extracellular matrix, extracellular matrix receptor signaling pathway, and focal adhesion. Two competing endogenous RNA networks were constructed based on the selected hub gene and differential RNAs, and we identified multiple competing endogenous RNA regulatory axes that were involved in the effects of Aβ and senescence on astrocytes. This is the first study to explore the molecular regulation mechanism of Aβ and senescence on primary astrocytes from the perspective of the whole transcriptome. In uncovering the signaling pathways and biological processes involved in the effects of Aβ and senescence on astrocytes, this work provides novel insights into the pathogenesis of AD at the level of competing endogenous RNA network regulation.

Circular RNA circ_0005835 promotes promoted neural stem cells proliferation and differentiate to neuron and inhibits inflammatory cytokines levels through miR-576-3p in Alzheimer's disease

Alzheimer's disease (AD) is the most frequent neurodegenerative disease and it is difficult to have an effective and simple method for AD early diagnosis. CircRNAs (circular RNAs) are novel discovered non-coding endogenous RNAs that affect cell apoptosis, differentiation, growth, metabolism, and metastasis. Recently, it has reported that circ_0005835 was one upregulated circRNA in the AD patients. However, the function role of circ_0005835 remains unknown. In our study, we found that circ_0005835 was upregulated in AD patients and cell models. Knockdown of circ_0005835 could downregulate neuroinflammation in BV2 cells. Moreover, knockdown of circ_0005835 promoted neural stem cells (NSC) proliferation and differentiate to neuron. These data mean that circ_0005835 plays important role in the development of AD. The miR-576-3p expression in serum was downregulated in the AD group compared to the health control group. Consistently, the level of circ_0005835 was overexpressed in the Aβ-treated in both SH-SY5Y and BV2 cells. Moreover, the expression of miR-576-3p was negatively correlated with circ_0005835 in AD patients. In addition, we performed the rescued experiments to show that knockdown of circ_0005835 could downregulate neuroinflammation through sponging miR-576-3p in BV2 cells. Inhibition of circ_0005835 promoted NSC proliferation and differentiate to neuron via sponging miR-576-3p. These data suggested that circ_0005835 promoted AD development through regulating miR-576-3p expression.

Molecular Insight Into the Therapeutic Potential of Long Non-coding RNA-Associated Competing Endogenous RNA Axes in Alzheimer's Disease: A Systematic Scoping Review

Alzheimer’s disease (AD) is a heterogeneous degenerative brain disorder with a rising prevalence worldwide. The two hallmarks that characterize the AD pathophysiology are amyloid plaques, generated via aggregated amyloid β, and neurofibrillary tangle, generated via accumulated phosphorylated tau. At the post-transcriptional and transcriptional levels, the regulatory functions of non-coding RNAs, in particular long non-coding RNAs (lncRNAs), have been ascertained in gene expressions. It is noteworthy that a number of lncRNAs feature a prevalent role in their potential of regulating gene expression through modulation of microRNAs via a process called the mechanism of competing endogenous RNA (ceRNA). Given the multifactorial nature of ceRNA interaction networks, they might be advantageous in complex disorders (e.g., AD) investigations at the therapeutic targets level. We carried out scoping review in this research to analyze validated loops of ceRNA in AD and focus on ceRNA axes associated with lncRNA. This scoping review was performed according to a six-stage methodology structure and PRISMA guideline. A systematic search of seven databases was conducted to find eligible articles prior to July 2021. Two reviewers independently performed publications screening and data extraction, and quantitative and qualitative analyses were conducted. Fourteen articles were identified that fulfill the inclusion criteria. Studies with different designs reported nine lncRNAs that were experimentally validated to act as ceRNA in AD in human-related studies, including BACE1-AS, SNHG1, RPPH1, NEAT1, LINC00094, SOX21-AS1, LINC00507, MAGI2-AS3, and LINC01311. The BACE1-AS/BACE1 was the most frequent ceRNA pair. Among miRNAs, miR-107 played a key role by regulating three different loops. Understanding the various aspects of this regulatory mechanism can help elucidate the unknown etiology of AD and provide new molecular targets for use in therapeutic and clinical applications.