Prediction of Mechanosensitive Genes in Vascular Endothelial Cells Under High Wall Shear Stress

Identification and experimental validation of KMO as a critical immune-associated mitochondrial gene in unstable atherosclerotic plaque

BACKGROUND

The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition.

METHODS

Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria.

RESULTS

The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice.

CONCLUSIONS

The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

Unleashing the Neurotherapeutic Potential: The Crucial Role of miR-206-3p in Facilitating Hsp90aa1-Mediated Central Nervous System Injuries During Heat Stroke

This study aims to explore the molecular mechanisms of miR-206-3p in regulating Hsp90aa1 and its involvement in the central nervous system (CNS) injury in heat stroke. Weighted gene co-expression network analysis (WGCNA) was performed on the GSE64778 dataset of heat stroke to identify module genes most closely associated with disease characteristics. Through the selection of key genes and predicting upstream miRNAs using RNAInter and miRWalk databases, the regulatory relationship between miR-206-3p and Hsp90aa1 was determined. Through in vitro experiments, various methods, including bioinformatics analysis, dual-luciferase reporter gene assay, RIP experiment, and RNA pull-down experiment, were utilized to validate this regulatory relationship. Furthermore, functional experiments, including CCK-8 assay to test neuron cell viability and flow cytometry to assess neuron apoptosis levels, confirmed the role of miR-206-3p. Transmission electron microscopy, real-time quantitative PCR, DCFH-DA staining, and ATP assay were employed to verify neuronal mitochondrial damage. Heat stroke rat models were constructed, and mNSS scoring and cresyl violet staining were utilized to assess neural functional impairment. Biochemical experiments were conducted to evaluate inflammation, brain water content, and histopathological changes in brain tissue using H&E staining. TUNEL staining was applied to detect neuronal apoptosis in brain tissue. RT-qPCR and Western blot were performed to measure gene and protein expression levels, further validating the regulatory relationship in vivo. Bioinformatics analysis indicated that miR-206-3p regulation of Hsp90aa1 may be involved in CNS injury in heat stroke. In vivo, animal experiments demonstrated that miR-206-3p and Hsp90aa1 co-localized in neurons of the rat hippocampal CA3 region, and with prolonged heat stress, the expression of miR-206-3p gradually increased while the expression of Hsp90aa1 gradually decreased. Further in vitro cellular mechanism validation and functional experiments confirmed that miR-206-3p could inhibit neuronal cell viability and promote apoptosis and mitochondrial damage by targeting Hsp90aa1. In vivo, experiments confirmed that miR-206-3p promotes CNS injury in heat stroke. This study revealed the regulatory relationship between miR-206-3p and Hsp90aa1, suggesting that miR-206-3p could regulate the expression of Hsp90aa1, inhibit neuronal cell viability, and promote apoptosis, thereby contributing to CNS injury in heat stroke.

Recent advances of mechanosensitive genes in vascular endothelial cells for the formation and treatment of atherosclerosis

Atherosclerotic cardiovascular disease and its complications are a high-incidence disease worldwide. Numerous studies have shown that blood flow shear has a huge impact on the function of vascular endothelial cells, and it plays an important role in gene regulation of pro-inflammatory, pro-thrombotic, pro-oxidative stress, and cell permeability. Many important endothelial cell mechanosensitive genes have been discovered, including KLK10, CCN gene family, NRP2, YAP, TAZ, HIF-1α, NF-κB, FOS, JUN, TFEB, KLF2/KLF4, NRF2, and ID1. Some of them have been intensively studied, whereas the relevant regulatory mechanism of other genes remains unclear. Focusing on these mechanosensitive genes will provide new strategies for therapeutic intervention in atherosclerotic vascular disease. Thus, this article reviews the mechanosensitive genes affecting vascular endothelial cells, including classical pathways and some newly screened genes, and summarizes the latest research progress on their roles in the pathogenesis of atherosclerosis to reveal effective therapeutic targets of drugs and provide new insights for anti-atherosclerosis.

Comprehensive molecular and cellular characterization of endoplasmic reticulum stress-related key genes in renal ischemia/reperfusion injury

Background

Renal ischemia-reperfusion injury (RIRI) is an inevitable complication in the process of kidney transplantation and lacks specific therapy. The study aims to determine the underlying mechanisms of RIRI to uncover a promising target for efficient renoprotection.

Method

Four bulk RNA-seq datasets including 495 renal samples of pre- and post-reperfusion were collected from the GEO database. The machine learning algorithms were utilized to ascertain pivotal endoplasmic reticulum stress genes. Then, we incorporated correlation analysis and determined the interaction pathways of these key genes. Considering the heterogeneous nature of bulk-RNA analysis, the single-cell RNA-seq analysis was performed to investigate the mechanisms of key genes at the single-cell level. Besides, 4-PBA was applied to inhibit endoplasmic reticulum stress and hence validate the pathological role of these key genes in RIRI. Finally, three clinical datasets with transcriptomic profiles were used to assess the prognostic role of these key genes in renal allograft outcomes after RIRI.

Results

In the bulk-RNA analysis, endoplasmic reticulum stress was identified as the top enriched pathway and three endoplasmic reticulum stress-related genes (PPP1R15A, JUN, and ATF3) were ranked as top performers in both LASSO and Boruta analyses. The three genes were found to significantly interact with kidney injury-related pathways, including apoptosis, inflammatory response, oxidative stress, and pyroptosis. For oxidative stress, these genes were more strongly related to oxidative markers compared with antioxidant markers. In single-cell transcriptome, the three genes were primarily upregulated in endothelium, distal convoluted tubule cells, and collecting duct principal cells among 12 cell types of renal tissues in RIRI. Furthermore, distal convoluted tubule cells and collecting duct principal cells exhibited pro-inflammatory status and the highest pyroptosis levels, suggesting their potential as main effectors of three key genes for mediating RIRI-associated injuries. Importantly, inhibition of these key genes using 4-phenyl butyric acid alleviated functional and histological damage in a mouse RIRI model. Finally, the three genes demonstrated highly prognostic value in predicting graft survival outcomes.

Conclusion

The study identified three key endoplasmic reticulum stress-related genes and demonstrated their prognostic value for graft survival, providing references for individualized clinical prevention and treatment of postoperative complications after renal transplantation.

Periodic Mechanical Stress Inhibits the Development of Osteoarthritis via Regulating ATF3-Akt Axis

Purpose

The development of osteoarthritis (OA) has been linked to mechanical factors. Studies suggest that periodic mechanical stress (PMS) may be a factor contributing to cartilage repair and the onset of OA. Therefore, this study was designed to explore the effects and underlying mechanisms of PMS on OA development.

Patients and Methods

Firstly, surgery and interleukin (IL)-1β were used for the establishment of rat/cell models of OA, respectively. Subsequently, activating transcription factor (ATF) 3 expression was knocked down in OA rats, and OA chondrocytes were treated with different heights (0, 1, 2, 4, 8 cm) of PMS or si-ATF. Safranin O staining was used to observe the histological changes in the rat knee joint, and enzyme-linked immunosorbent assay (ELISA) was performed to detect levels of tumor necrosis factor (TNF)-α, IL-6, and IL-8 in vivo and in vitro. Further, the expression of extracellular matrix (ECM) proteins in the rat knee joint was assessed immunohistochemistry. Flow cytometry was used to evaluate chondrocyte apoptosis. Lastly, Western blot was performed to detect the expression of related proteins of the protein kinase B (Akt) signaling pathway and ECM.

Results

The OA rat model was successfully constructed. Further experiments indicated that the knockdown of ATF3 not only alleviated joint swelling, pain, inflammatory response and pathological damage, but also promoted ECM synthesis and the phosphorylation of Akt in OA rats. In vitro experiments showed that PMS (4 cm) effectively inhibited cell apoptosis, decreased the levels of TNF-α, IL-6 and IL-8, promoted ECM synthesis, and activated the Akt signaling pathway in osteoarthritic chondrocytes. However, ATF3 overexpression reversed the positive effects of PMS on osteoarthritic chondrocytes.

Conclusion

PMS can effectively inhibit the development of OA, and its protective effects may be attributed to the down-regulation of ATF3 expression and activation of the Akt signaling pathway.

PATHOPHYSIOLOGICAL MECHANISMS OF DEEP VEIN THROMBOSIS

Deep venous thrombosis is a frequent multifactorial disease and most of the time is triggered by the interaction between acquired risk factors, particularly immobility, and hereditary risk factors such as thrombophilias. The mechanisms underlying deep venous thrombosis are not fully elucidated; however, in recent years the role of venous flow, endothelium, platelets, leukocytes, and the interaction between inflammation and hemostasis has been determined. Alteration of venous blood flow produces endothelial activation, favoring the adhesion of platelets and leukocytes, which, through tissue factor expression and neutrophil extracellular traps formation, contribute to the activation of coagulation, trapping more cells, such as red blood cells, monocytes, eosinophils, lymphocytes. The coagulation factor XI-driven propagation phase of blood coagulation plays a major role in venous thrombus growth, but a minor role in hemostasis. In this work, the main mechanisms involved in the pathophysiology of deep vein thrombosis are described.

Identification of brain endothelial cell-specific genes and pathways in ischemic stroke by integrated bioinformatical analysis

BACKGROUND

Ischemic stroke (IS) is a life-threatening condition with limited treatment options; thus, finding the potential key genes for novel therapeutic targets is urgently needed. This study aimed to explore novel candidate genes and pathways of brain microvessel endothelial cells (ECs) in IS by bioinformatics analysis.

MATERIALS AND METHODS

The gene expression profiles of brain tissues or brain ECs in IS mice were downloaded from the online gene expression omnibus (GEO) to obtain the differentially expressed genes (DEGs) by R software. Functional enrichment analyses were used to cluster the functions and signaling pathways of the DEGs, while DEG-associated protein-protein interaction network was performed to identify hub genes. The target microRNAs and competitive endogenous RNA networks of key hub genes were constructed by Cytoscape.

RESULTS

Totally 84 DEGs were obtained from 6 brain tissue samples and 4 brain vascular EC samples both from IS mice in the datasets GSE74052 and GSE137482, with significant enrichment in immune responses, such as immune system processes and T-cell activation. Eight hub genes filtered by Cytoscape were validated by two other GEO datasets, wherein key genes of interest were verified by reverse transcription-polymerase chain reaction using an in vitro ischemic model of EC cultures. Our data indicated that AURKA and CENPF might be potential therapeutic target genes for IS, and Malat1/Snhg12/Xist-miR-297b-3p-CENPF, as well as Mir17 hg-miR-34b-3p-CENPF, might be RNA regulatory pathways to control IS progression.

CONCLUSIONS

Our work identified two brain EC-specific expressed genes in IS, namely, AURKA and CENPF, as potential gene targets for IS treatment. In addition, we presented miR-297b-3p/miR-34b-3p-CENPF as the potential RNA regulatory axes to prevent pathogenesis of IS.

Parkinson's disease patients combined with constipation tend to have higher serum expression of microRNA 29c, prominent neuropsychiatric disorders, possible RBD conversion, and a substandard quality of life

INTRODUCTION

The symptom of constipation has been confirmed as an early diagnose criteria for Parkinson's disease (PD). Furthermore, evidences suggest that pathogenesis of PD initiates in gut, rather than brain. If so, identifying biomarkers for constipation in PD might have potentials to assist early diagnosis and initial treatment.

METHOD

We first identified that microRNA 29c (miR-29c) was dysregulated both in PD and constipation patients through bioinformatics analysis. Then, serological analysis of the expression of miR-29c in 67 PD patients with constipation (PD-C), 51 PD patients without constipation (PD-NC), and 50 healthy controls (HC) was carried out by qPCR. Demographic and clinical features were also compared. Patients in PD-C group were further classified into two groups: those with prodromal stage constipation (PD-C-Pro) (n = 36) and those with clinical stage constipation (PD-C-Clinic) (n = 31), to explore their different characteristics.

RESULTS

The levels of miR-29c in PD-C group were higher than that in PD-NC group, both higher than HC group. PD-C-Pro group's miR-29c levels were statistically higher compared with PD-C-Clinic group's. What is more, PD-C group had higher scores of MDS-UPDRS-I, NMSS, NMSS3, NMSS4, NMSS6, NMSS9, SCOPA-AUT, HAMD, HAMA, RBDSQ, CSS, and PACQOL compared with PD-NC party. Relative to the PD-C-Clinic, patients in PD-C-Pro group had higher MDS-UPDRS-I, NMSS, NMSS3, HAMD, and HAMA scores, and were more likely to have RBD.

CONCLUSION

Our results indicated that miR-29c seems to be an underlying cause for developing constipation in patients with PD and PD-C identifies a group of patients with more severe non-motor impairment, prominent neuropsychiatric disorders, and possible RBD conversion as well as a substandard quality of life. We further confirmed that there is a close relationship between symptoms representing the same pathological origin, especially constipation and RBD.

Parkinson's Disease Gene Biomarkers Screened by the LASSO and SVM Algorithms

Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Various evidence has revealed the possible penetration of peripheral immune cells in the substantia nigra, which may be essential for PD. Our study uses machine learning (ML) to screen for potential PD genetic biomarkers. Gene expression profiles were screened from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) were selected for the enrichment analysis. A protein-protein interaction (PPI) network was built with the STRING database (Search Tool for the Retrieval of Interacting Genes), and two ML approaches, namely least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE), were employed to identify candidate genes. The external validation dataset further tested the expression degree and diagnostic value of candidate biomarkers. To assess the validity of the diagnosis, we determined the receiver operating characteristic (ROC) curve. A convolution tool was employed to evaluate the composition of immune cells by CIBERSORT, and we performed correlation analyses on the basis of the training dataset. Twenty-seven DEGs were screened in the PD and control samples. Our results from the enrichment analysis showed a close association with inflammatory and immune-associated diseases. Both the LASSO and SVM algorithms screened eight and six characteristic genes. AGTR1, GBE1, TPBG, and HSPA6 are overlapping hub genes strongly related to PD. Our results of the area under the ROC (AUC), including AGTR1 (AUC = 0.933), GBE1 (AUC = 0.967), TPBG (AUC = 0.767), and HSPA6 (AUC = 0.633), suggested that these genes have good diagnostic value, and these genes were significantly associated with the degree of immune cell infiltration. AGTR1, GBE1, TPBG, and HSPA6 were identified as potential biomarkers in the diagnosis of PD and provide a novel viewpoint for further study on PD immune mechanism and therapy.

Novel Diagnostic Biomarkers Related to Oxidative Stress and Macrophage Ferroptosis in Atherosclerosis

Atherosclerosis (AS) is a chronic inflammatory disease, which has a complex interplay between altered immune metabolism and oxidative stress. Therefore, we aimed to determine the oxidative stress and immune-related biomarkers in AS. Differential gene expression analyses are based on the GSE100927 dataset in the Gene Expression Omnibus (GEO), and 389 oxidative stress (OS) genes are identified based on gene set enrichment analysis (GSEA). We identified 74 differentially expressed genes related to oxidative stress (DEOSGs). “CIBERSORT” and “WGCNA” R Packages were used to compare the differences in immune infiltration levels between AS and control samples. The DEOSGs (N = 74) were intersected with the key module's genes of WGCNA (N = 972), and 27 differentially expressed immune-related oxidative stress genes (DEIOSGs) were obtained. To identify the pivotal genes, a protein-protein interaction (PPI) network was constructed using the STRING database and the Cytoscape software. MMP9, ALOX5, NCF2, NCF, and NCF4 were identified as diagnostic markers of AS, and we validated them in the GSE57691 dataset. The expression levels of the five diagnostic genes were significantly highly expressed in the AS group. Correlation analysis and single-cell analysis revealed that five diagnostic genes were mainly correlated with macrophages M1. We, respectively, intersected differentially expressed genes (DEGs) with ferroptosis gene set, necroptosis gene set, and pyroptosis gene set. The findings suggested that ALOX5 and NCF2 were differentially expressed genes of ferroptosis. High expression of five hub genes in RAW264.7 macrophages were confirmed by PCR. High ALOX5 and NCF2 expression levels in plaque tissues were confirmed by immunohistochemistry (IHC) and western blotting. Our study identified that MMP9, ALOX5, NCF2, NCF1, and NCF4 were diagnostic genes of AS and associated with oxidative stress. ALOX5 and NCF2 may be involved in the formation of the necrotic core in AS by regulating macrophage ferroptosis.