Responsive Expression of MafF to β-Amyloid-Induced Oxidative Stress

Neurodegeneration and demyelination in multiple sclerosis

Progressive multiple sclerosis (PMS) is an immune-initiated neurodegenerative condition that lacks effective therapies. Although peripheral immune infiltration is a hallmark of relapsing-remitting MS (RRMS), PMS is associated with chronic, tissue-restricted inflammation and disease-associated reactive glial states. The effector functions of disease-associated microglia, astrocytes, and oligodendrocyte lineage cells are beginning to be defined, and recent studies have made significant progress in uncovering their pathologic implications. In this review, we discuss the immune-glia interactions that underlie demyelination, failed remyelination, and neurodegeneration with a focus on PMS. We highlight the common and divergent immune mechanisms by which glial cells acquire disease-associated phenotypes. Finally, we discuss recent advances that have revealed promising novel therapeutic targets for the treatment of PMS and other neurodegenerative diseases.

Identification of gene signature markers in gestational hypertension and early-onset pre-eclampsia

INTRODUCTION

Hypertensive disorders in pregnancy (HDP) are the leading cause of perinatal mortality worldwide. Inflammatory responses induced by insufficient placental perfusion have become a focal point in understanding the pathogenesis and aetiology of HDP and developing reliable and consistent biomarkers. Therefore, this study aims to identify gene signatures linked to the pathophysiology of HDP (gestational hypertension and early and late-onset pre-eclampsia).

METHODS

RNA was extracted from the maternal serum from the blood samples collected from different groups of HDP patients. A multiplex inflammation panel (255 inflammatory and housekeeping genes) and further gene expression analysis using NanoString Digital Direct Detection were done. The prominent expressions of these genes were further validated through qPCR techniques.

RESULTS

NanoString analysis identified nine unique, significantly expressed genes (MAPK1, MAPK3, MAFF, HLA-DRA, IL12B, RHOA, MASP2, MEF2A and NR3C1) between specific group comparisons of different HPD classes and the normotensive groups. The qPCR showed that the HLA-DRA gene was significantly upregulated in the early-onset pre-eclamptic and gestational hypertensive group compared to its respective normotensive group. In contrast, MAFF and MEF2A were significantly downregulated in both HDPs compared to their controls. The MAPK1 gene was significantly higher in the early-onset group compared to the gestational hypertensive and normotensive groups.

DISCUSSION

The upregulation of these distinctive genes in hypertensive groups compared to normotensives confirmed their diagnostic potential. Therefore, HLA-DRA, MAFF and MEF2A could be candidate markers of HDP, while the MAPK1 gene could be a differentiating marker between early-onset pre-eclampsia and gestational hypertension.

Nuclear factor E2-associated factor 2 and musculoaponeurotic fibrosarcoma K mediate regulation glutathione peroxidase of Cristaria plicata after microcystin-induced oxidative stress

Nuclear factor E2-associated factor 2 (Nrf2)/Antioxidant Response Element (ARE) signaling pathway is an endogenous antioxidant pathway that protects cells from oxidative damage. This pathway is triggered when aquatic organisms are exposed to environmental toxicants. In this study, CpMafK (musculoaponeurotic fibrosarcoma K of Cristaria plicata) mRNA expression in hepatopancreas and gills were up regulated after Cristaria plicata (C. plicata) was exposed to microcystin (MC), which showed that CpMafK protected C. plicata from MC. After MC treatment and CpNrf2 (Nrf2 of Cristaria plicata) knockdown, the mRNA expression of CpMafK was down regulated. After MC treatment and CpMafK knockdown, the mRNA expression of CpNrf2 was down regulated. Indicating that the expression of CpNrf2 was positively correlated with CpMafK. CpGPx (GPx of Cristaria plicata) mRNA was also down regulated with the down regulation of CpMafK and CpNrf2. CpGPx promoter contains a variety of transcription factor binding sites, including Nrf2, ARE elements, etc. Gel blocking experiments showed that CpNrf2/CpMafK heterodimers were bound to CpGPx promoters in vitro. Dual luciferase reporter assay showed that CpNrf2/CpMafK heterodimer negatively regulated CpGPx promoter in cells. In conclusion, Nrf2 and MafK mediate regulation of GPx play a crucial role in protecting bivalves from MC.

Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles in silico

BACKGROUND

Preclinical models like cancer cell lines and patient-derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions.

AIMS

Here we evaluated how well preclinical models recapitulate human cancer and non-diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue-specific genes.

METHODS

By using publicly available gene expression profiles across multiple sources, we evaluated cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles in silico.

RESULTS

We found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that glioblastoma (GBM) PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue-specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue-specific patterns are better preserved in GBM PDX models than in GBM cell lines.

CONCLUSION

Future studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

Synthesis of Lathyrol PROTACs and Evaluation of Their Anti-Inflammatory Activities

Lathyrol is a core scaffold structure of many lathyrane diterpenoids with potent anti-inflammatory activity isolated from Euphorbia lathyrism. It was chosen as a framework to design and synthesize a series of proteolysis targeting chimeras. A total of 15 derivatives were obtained. Compound 13 exhibited inhibitory activity on LPS-induced NO production in RAW264.7 cells (IC₅₀ = 5.30 ± 1.23 μM) with low cytotoxicity. Furthermore, compound 13 significantly degraded v-maf musculoaponeurotic fibrosarcoma oncogene homologue F (MAFF) protein, a target of lathyrane diterpenoid, concentration- and time-dependently. The mechanism of action of 13 is related to activating the Keap1/Nrf2 pathway. It also inhibited the expression of NF-κB, blocked the nuclear translocation of NF-κB, and activated autophagy in LPS-induced RAW264.7 cells. Based on the results obtained, compound 13 might be a promising anti-inflammatory agent.

Reduced SUMOylation of Nrf2 signaling contributes to its inhibition induced by amyloid-β

Oxidative stress induced by amyloid-β (Aβ) has been considered as one of the important mechanisms in the development of Alzheimer disease (AD). The inhibition of endogenous antioxidant Nrf2 signaling in the brain of AD patients aggravates the oxidative damage, however, the causes of Nrf2 signaling inhibition are unclear. It is reported that smallubiquitin-like modification (SUMOylation) is involved in the process of oxidative injury. To investigate whether and how SUMOylation was involved in the inhibition of Nrf2 signaling pathway induced by Aβ, Aβ intrahippocampal injection rat model and Aβ treated SH-SY5Y cell model were used in the current study. Small interfering RNA and lentivirus transfection were used to intervene SUMOylation, and the level of SUMOylation was assessed by immunoprecipitation. The present in vivo and in vitro studies revealed that SUMOylation levels of Nrf2 and MafF, as well as the overall SUMOylation level were reduced under long-term Aβ insult. Meanwhile, the binding of Nrf2 to MafF was decreased, accompanied by low interaction with antioxidant response element (ARE) area of gene. Down-regulation of SUMO protein exacerbated the Aβ-induced inhibition of Nrf2 signaling pathway, while, enhancement of SUMOylation of Nrf2 and MafF by overexpression of Ubc9 reversed this process. These results imply that reduction in SUMOylation induced by Aβ contributed to the inhibition of Nrf2 signaling, and SUMOylation might be a potential therapeutic target of AD.

Human microRNA-4433 (hsa-miR-4443) Targets 18 Genes to be a Risk Factor of Neurodegenerative Diseases

BACKGROUND

Neurodegenerative diseases, such as Alzheimer's disease patients (AD), Huntington's disease (HD) and Parkinson's disease (PD), are common causes of morbidity, mortality, and cognitive impairment in older adults.

OBJECTIVE

We aimed to understand the transcriptome characteristics of the cortex of neurodegenerative diseases and to provide an insight into the target genes of differently expressed microRNAs in the occurrence and development of neurodegenerative diseases.

METHODS

The Limma package of R software was used to analyze GSE33000, GSE157239, GSE64977 and GSE72962 datasets to identify the differentially expressed genes (DEGs) and microRNAs in the cortex of neurodegenerative diseases. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis and gene interaction network analysis, were used to explore the biological functions of DEGs. Weighted gene co-expression network analysis (WGCNA) was used to cluster DEGs into modules. RNA22, miRDB, miRNet 2.0 and TargetScan7 databases were performed to predict the target genes of microRNAs.

RESULTS

Among 310 Alzheimer's disease (AD) patients, 157 Huntington's disease (HD) patients and 157 non-demented control (Con) individuals, 214 co-DEGs were identified. Those co-DEGs were filtered into 2 different interaction network complexes, representing immune-related genes and synapserelated genes. The WGCNA results identified five modules: yellow, blue, green, turquoise, and brown. Most of the co-DEGs were clustered into the turquoise module and blue module, which respectively regulated synapse-related function and immune-related function. In addition, human microRNA-4433 (hsa-miR-4443), which targets 18 co-DEGs, was the only 1 co-up-regulated microRNA identified in the cortex of neurodegenerative diseases.

CONCLUSION

214 DEGs and 5 modules regulate the immune-related and synapse-related function of the cortex in neurodegenerative diseases. Hsa-miR-4443 targets 18 co-DEGs and may be a potential molecular mechanism in neurodegenerative diseases' occurrence and development.

Identification of hsa-miR-365b-5p's role in Alzheimer's disease: a combined analysis of miRNA and mRNA microarrays

BACKGROUND

Alzheimer's disease is a prevalent health problem with a heavy global burden. Definitely diagnosed by autopsy, the clear mechanism of Alzheimer's disease pathogenesis process needs to be illustrated. MicroRNAs are suggested to be involved in many diseases. We aimed to investigate the role of microRNA in Alzheimer's disease.

METHODS

We attempted to discover the role of microRNA in Alzheimer's disease by microarray bioinformatics analysis using autopsy sample data from the GEO database. Temporal cortex samples were included in this study. Bioinformatics analyses and visualization were processed based on R.

RESULTS

After filtering out significantly differential expressed microRNAs and genes, enrichment analyses of both microRNAs and genes were conducted, respectively. Then, we constructed a transcription factor- microRNA-mRNA network and a protein-protein interaction network. In parallel, we used the receiver operating characteristic curve to evaluate the diagnostic value of microRNA. Based on the evidence, we finally identified hsa-miR-365b-5p as a key target in Alzheimer's disease.

CONCLUSIONS

Hsa-miR-365b-5p act as a key target in Alzheimer's disease. It regulates Alzheimer's disease pathogenesis process via neuroinflammation, Wnt and oxidative stress pathway which provides a potential target for Alzheimer's disease treatment.

Min pig skeletal muscle response to cold stress

The increased sensitivity of pigs to ambient temperature is due to today's intensive farming. Frequent climate disasters increase the pressure on healthy pig farming. Min pigs are an indigenous pig breed in China with desirable cold resistance characteristics, and hence are ideal for obtaining cold-resistant pig breeds. Therefore, it is important to discover the molecular mechanisms that are activated in response to cold stress in the Min pig. Here, we conducted a transcriptomic analysis of the skeletal muscle of Min pigs under chronic low-temperature acclimation (group A) and acute short cold stress (group B). Cold exposure caused more genes to be upregulated. Totals of 125 and 96 differentially expressed genes (DEGs) were generated from groups A and B. Sixteen common upregulated DEGs were screened; these were concentrated in oxidative stress (SRXN1, MAFF), immune and inflammatory responses (ITPKC, AREG, MMP25, FOSL1), the nervous system (RETREG1, GADD45A, RCAN1), lipid metabolism (LRP11, LIPG, ITGA5, AMPD2), solute transport (SLC19A2, SLC28A1, SLCO4A1), and fertility (HBEGF). There were 102 and 73 genes that were specifically differentially expressed in groups A and B, respectively. The altered mRNAs were enriched in immune, endocrine, and cancer pathways. There were 186 and 91 differentially expressed lncRNAs generated from groups A and B. Analysis of the target genes suggested that they may be involved in regulating the MAPK signaling pathway for resistance to cold. The results of this study provide a comprehensive overview of cold exposure-induced transcriptional patterns in skeletal muscle of the Min pig. These results can guide future molecular studies of cold stress response in pigs for improving cold tolerance as a goal in breeding programs.

Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease

To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10^-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.

Identification of diagnostic signatures associated with immune infiltration in Alzheimer’s disease by integrating bioinformatic analysis and machine-learning strategies

Objective

As a chronic neurodegenerative disorder, Alzheimer’s disease (AD) is the most common form of progressive dementia. The purpose of this study was to identify diagnostic signatures of AD and the effect of immune cell infiltration in this pathology.

Methods

The expression profiles of GSE109887, GSE122063, GSE28146, and GSE1297 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between AD and control brain samples. Functional enrichment analysis was performed to reveal AD-associated biological functions and key pathways. Besides, we applied the Least Absolute Shrinkage Selection Operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) analysis to screen potential diagnostic feature genes in AD, which were further tested in AD brains of the validation cohort (GSE5281). The discriminatory ability was then assessed by the area under the receiver operating characteristic curves (AUC). Finally, the CIBERSORT algorithm and immune cell infiltration analysis were employed to assess the inflammatory state of AD.

Results

A total of 49 DEGs were identified. The functional enrichment analysis revealed that leukocyte transendothelial migration, cytokine receptor interaction, and JAK-STAT signaling pathway were enriched in the AD group. MAF basic leucine zipper transcription factor F (MAFF), ADCYAP1, and ZFP36L1 were identified as the diagnostic biomarkers of AD with high discriminatory ability (AUC = 0.850) and validated in AD brains (AUC = 0.935). As indicated from the immune cell infiltration analysis, naive B cells, plasma cells, activated/resting NK cells, M0 macrophages, M1 macrophages, resting CD4⁺ T memory cells, resting mast cells, memory B cells, and resting/activated dendritic cells may participate in the development of AD. Additionally, all diagnostic signatures presented different degrees of correlation with different infiltrating immune cells.

Conclusion

MAFF, ADCYAP1, and ZFP36L1 may become new candidate biomarkers of AD, which were closely related to the pathogenesis of AD. Moreover, the immune cells mentioned above may play crucial roles in disease occurrence and progression.

Establishment and Analysis of a Combined Diagnostic Model of Alzheimer's Disease With Random Forest and Artificial Neural Network

Alzheimer's disease (AD) is a neurodegenerative condition that causes cognitive decline over time. Because existing diagnostic approaches for AD are limited, improving upon previously established diagnostic models based on genetic biomarkers is necessary. Firstly, four AD gene expression datasets were collected from the Gene Expression Omnibus (GEO) database. Two datasets were used to establish diagnostic models, and the other two datasets were used to verify the model effect. We merged GSE5281 with GSE44771 as the training dataset and found 120 DEGs. Then, we used random forest (RF) to screen 6 key genes (KLF15, MAFF, ITPKB, SST, DDIT4, and NRXN3) as being critical for separating AD and normal samples. The weights of these key genes were measured, and a diagnostic model was created using an artificial neural network (ANN). The area under the curve (AUC) of the model is 0.953, while the accuracy is 0.914. In the final step, two validation datasets were utilized to assess AUC performance. In GSE109887, our model had an AUC of 0.854, and in GSE132903, it had an AUC of 0.810. To summarize, we successfully identified key gene biomarkers and developed a new AD diagnostic model.

An in vitro strategy using multiple human induced pluripotent stem cell-derived models to assess the toxicity of chemicals: A case study on paraquat

Most OECD guidelines for chemical risk assessment include tests performed on animals, raising financial, ethical and scientific concerns. Thus, the development of human-based models for toxicity testing is highly encouraged. Here, we propose an in vitro multi-organ strategy to assess the toxicity of chemicals. Human induced pluripotent stem cells (hiPSCs)-derived models of the brain, blood-brain barrier, kidney, liver and vasculature were generated and exposed to paraquat (PQ), a widely employed herbicide with known toxic effects in kidneys and brain. The models showed differential cytotoxic sensitivity to PQ after acute exposure. TempO-Seq™ analysis with a set of 3565 probes revealed the deregulation of oxidative stress, unfolded protein response and Estrogen Receptor-mediated signaling pathways, in line with the existing knowledge on PQ mechanisms of action. The main advantages of this strategy are to assess chemical toxicity on multiple tissues/organs in parallel, exclusively in human cells, eliminating the interspecies bias, allowing a better evaluation of the differential sensitivity of the models representing the diverse organs, and increasing the chance to identify toxic compounds. Furthermore, although we focused on the mechanisms of action of PQ shared by the different models, this strategy would also allow for organ-specific toxicity testing, by including more cell type-specific probes for TempO-Seq analyses. In conclusion, we believe this strategy will participate in the further improvement of chemical risk assessment for human health.

The NRF2-Dependent Transcriptional Regulation of Antioxidant Defense Pathways: Relevance for Cell Type-Specific Vulnerability to Neurodegeneration and Therapeutic Intervention

Oxidative stress has been implicated in the etiology and pathobiology of various neurodegenerative diseases. At baseline, the cells of the nervous system have the capability to regulate the genes for antioxidant defenses by engaging nuclear factor erythroid 2 (NFE2/NRF)-dependent transcriptional mechanisms, and a number of strategies have been proposed to activate these pathways to promote neuroprotection. Here, we briefly review the biology of the transcription factors of the NFE2/NRF family in the brain and provide evidence for the differential cellular localization of NFE2/NRF family members in the cells of the nervous system. We then discuss these findings in the context of the oxidative stress observed in two neurodegenerative diseases, Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS), and present current strategies for activating NFE2/NRF-dependent transcription. Based on the expression of the NFE2/NRF family members in restricted populations of neurons and glia, we propose that, when designing strategies to engage these pathways for neuroprotection, the relative contributions of neuronal and non-neuronal cell types to the overall oxidative state of tissue should be considered, as well as the cell types which have the greatest intrinsic capacity for producing antioxidant enzymes.

A Hypoxia Gene-Based Signature to Predict the Survival and Affect the Tumor Immune Microenvironment of Osteosarcoma in Children

Osteosarcoma is a quickly developing, malignant cancer of the bone, which is associated with a bad prognosis. In osteosarcoma, hypoxia promotes the malignant phenotype, which results in a cascade of immunosuppressive processes, poor prognosis, and a high risk of metastasis. Nonetheless, additional methodologies for the study of hyperoxia in the tumor microenvironment also need more analysis. We obtained 88 children patients with osteosarcoma from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database and 53 children patients with RNA sequence and clinicopathological data from the Gene Expression Omnibus (GEO). We developed a four-gene signature related to hypoxia to reflect the immune microenvironment in osteosarcoma that predicts survival. A high-risk score indicated a poor prognosis and immunosuppressive microenvironment. The presence of the four-gene signature related to hypoxia was correlated with clinical and molecular features and was an important prognostic predictor for pediatric osteosarcoma patients. In summary, we established and validated a four-gene signature related to hypoxia to forecast recovery and presented an independent prognostic predictor representing overall immune response strength within the osteosarcoma microenvironment.