Identification of MMP9 as a Novel Biomarker to Mitochondrial Metabolism Disorder and Oxidative Stress in Calcific Aortic Valve Stenosis

Effect of Sodium-Glucose Cotransporter-2 Inhibitors on the Progression of Aortic Stenosis

BACKGROUND

Aortic stenosis (AS) is the leading cause of valvular heart disease-related morbidity and mortality, but there are no medical treatments to slow its progression. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have pleiotropic effects which could be disease modifying in AS.

OBJECTIVES

The purpose of this study was to determine if SGLT2i usage is associated with slower progression of AS.

METHODS

A target trial emulation comparing the effect of the initiation of SGLT2i compared with no SGLT2i in patients with nonsevere AS was performed using retrospective electronic medical record data from the Yale New Haven Health System from January 2016 to September 2022. Patients with native aortic valve sclerosis or nonsevere AS with at least 12 months of echocardiographic follow-up were included. Patients were excluded if they had an estimated glomerular filtration rate <30 mL/min/1.73 m2 or had initiated SGLT2i >1 year before the index echocardiogram. The prespecified primary outcome was progression to severe AS.

RESULTS

A total of 458 patients prescribed SGLT2i and 11,240 patients never prescribed SGLT2i were included. Patients were on SGLT2i for a median of 0.9 years. Patients on SGLT2i were younger and had higher rates of diabetes and chronic kidney disease. Patients on SGLT2i were more likely to have ejection fraction ≤40%. There were no differences between groups in baseline AS severity (66% sclerosis, 23% mild stenosis, and 11% moderate in overall cohort). Patients ever prescribed SGLT2i were less likely to progress to severe AS (HR: 0.61; 95% CI: 0.39-0.94; P = 0.03) with a progressively lower risk among patients on SGLT2i for >3, 6, and 12 months (HR: 0.54, 0.48, and 0.27, respectively).

CONCLUSIONS

This retrospective, multicenter, observational study suggests that SGLT2i may slow the progression of nonsevere AS.

Bioinformatics Analysis of coagulation-related genes in lung adenocarcinoma: unveiling prognostic indicators and treatment pathways

Lung adenocarcinoma (LUAD) frequently precipitates a hypercoagulable state, resulting in venous thromboembolism and associated hemostatic complications. Furthermore, the coagulation cascade holds a pivotal role within the tumor microenvironment (TME) of LUAD. Utilizing unsupervised clustering of coagulation-related genes (CRG) and integrating clinical attributes, distinctions and correlations in clustering across various groups were assessed. Principal component analysis (PCA) was employed to derive the CRGscore for LUAD patients. Subsequently, a prognostic signature was established to contrast the impacts of immunological and pharmacological treatments across groups. The expression of PIK3CA, posited as a potential biomarker, was corroborated via immunohistochemistry(IHC) and Western blotting. This research delineated pronounced variances in immune signatures and prognostic categorizations among four coagulation-related subtypes, and delved into their associations with three gene cluster subtypes. A prognostic model based on coagulation-related scores was formulated for risk stratification and prognosis estimation. Disparities in immune infiltration, treatment modalities, and drug responsiveness among risk cohorts were discerned. Notably, an augmented expression of the coagulation-associated gene PIK3CA was observed in tumor samples. Coagulatory function is intimately linked with LUAD and its immune microenvironment, offering predictive potential for LUAD survival prognosis. Specifically, subgroups manifesting elevated PIK3CA expression might serve as foundational indicators for optimal treatment selection.

Ang-1 and VEGF: central regulators of angiogenesis

Angiopoietin-1 (Ang-1) and Vascular Endothelial Growth Factor (VEGF) are central regulators of angiogenesis and are often inactivated in various cardiovascular diseases. VEGF forms complexes with ETS transcription factor family and exerts its action by downregulating multiple genes. Among the target genes of the VEGF-ETS complex, there are a significant number encoding key angiogenic regulators. Phosphorylation of the VEGF-ETS complex releases transcriptional repression on these angiogenic regulators, thereby promoting their expression. Ang-1 interacts with TEK, and this phosphorylation release can be modulated by the Ang-1-TEK signaling pathway. The Ang-1-TEK pathway participates in the transcriptional activation of VEGF genes. In summary, these elements constitute the Ang-1-TEK-VEGF signaling pathway. Additionally, Ang-1 is activated under hypoxic and inflammatory conditions, leading to an upregulation in the expression of TEK. Elevated TEK levels result in the formation of the VEGF-ETS complex, which, in turn, downregulates the expression of numerous angiogenic genes. Hence, the Ang-1-dependent transcriptional repression is indirect. Reduced expression of many target genes can lead to aberrant angiogenesis. A significant overlap exists between the target genes regulated by Ang-1-TEK-VEGF and those under the control of the Ang-1-TEK-TSP-1 signaling pathway. Mechanistically, this can be explained by the replacement of the VEGF-ETS complex with the TSP-1 transcriptional repression complex at the ETS sites on target gene promoters. Furthermore, VEGF possesses non-classical functions unrelated to ETS and DNA binding. Its supportive role in TSP-1 formation may be exerted through the VEGF-CRL5-VHL-HIF-1α-VH032-TGF-β-TSP-1 axis. This review assesses the regulatory mechanisms of the Ang-1-TEK-VEGF signaling pathway and explores its significant overlap with the Ang-1-TEK-TSP-1 signaling pathway.

Notoginsenoside R1 improves intestinal microvascular functioning in sepsis by targeting Drp1-mediated mitochondrial quality imbalance

CONTEXT

Sepsis can result in critical organ failure, and notoginsenoside R1 (NGR1) offers mitochondrial protection.

OBJECTIVE

To determine whether NGR1 improves organ function and prognosis after sepsis by protecting mitochondrial quality.

MATERIALS AND METHODS

A sepsis model was established in C57BL/6 mice using cecum ligation puncture (CLP) and an in vitro model with lipopolysaccharide (LPS, 10 µg/mL)-stimulated primary intestinal microvascular endothelial cells (IMVECs) and then determine NGR1's safe dosage. Groups for each model were: in vivo-a control group, a CLP-induced sepsis group, and a CLP + NGR1 treatment group (30 mg/kg/d for 3 d); in vitro-a control group, a LPS-induced sepsis group, and a LPS + NGR1 treatment group (4 μM for 30 min). NGR1's effects on survival, intestinal function, mitochondrial quality, and mitochondrial dynamic-related protein (Drp1) were evaluated.

RESULTS

Sepsis resulted in approximately 60% mortality within 7 days post-CLP, with significant reductions in intestinal microvascular perfusion and increases in vascular leakage. Severe mitochondrial quality imbalance was observed in IMVECs. NGR1 (IC50 is 854.1 μM at 30 min) targeted Drp1, inhibiting mitochondrial translocation, preventing mitochondrial fragmentation and restoring IMVEC morphology and function, thus protecting against intestinal barrier dysfunction, vascular permeability, microcirculatory flow, and improving sepsis prognosis.

DISCUSSION AND CONCLUSIONS

Drp1-mediated mitochondrial quality imbalance is a potential therapeutic target for sepsis. Small molecule natural drugs like NGR1 targeting Drp1 may offer new directions for organ protection following sepsis. Future research should focus on clinical trials to evaluate NGR1's efficacy across various patient populations, potentially leading to novel treatments for sepsis.

Multiomics identification of ALDH9A1 as a crucial immunoregulatory molecule involved in calcific aortic valve disease

Mitochondrial dysfunction and immune cell infiltration play crucial yet incompletely understood roles in the pathogenesis of calcific aortic valve disease (CAVD). This study aimed to identify immune-related mitochondrial genes critical to the pathological process of CAVD using multiomics approaches. The CIBERSORT algorithm was employed to evaluate immune cell infiltration characteristics in CAVD patients. An integrative analysis combining weighted gene coexpression network analysis (WGCNA), machine learning, and summary data-based Mendelian randomization (SMR) was performed to identify key mitochondrial genes implicated in CAVD. Spearman's rank correlation analysis was also performed to assess the relationships between key mitochondrial genes and infiltrating immune cells. Compared with those in normal aortic valve tissue, an increased proportion of M0 macrophages and resting memory CD4 T cells, along with a decreased proportion of plasma cells and activated dendritic cells, were observed in CAVD patients. Additionally, eight key mitochondrial genes associated with CAVD, including PDK4, LDHB, SLC25A36, ALDH9A1, ECHDC2, AUH, ALDH2, and BNIP3, were identified through the integration of WGCNA and machine learning methods. Subsequent SMR analysis, incorporating multiomics data, such as expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (mQTLs), revealed a significant causal relationship between ALDH9A1 expression and a reduced risk of CAVD. Moreover, ALDH9A1 expression was inversely correlated with M0 macrophages and positively correlated with M2 macrophages. These findings suggest that increased ALDH9A1 expression is significantly associated with a reduced risk of CAVD and that it may exert its protective effects by modulating mitochondrial function and immune cell infiltration. Specifically, ALDH9A1 may contribute to the shift from M0 macrophages to anti-inflammatory M2 macrophages, potentially mitigating the pathological progression of CAVD. In conclusion, ALDH9A1 represents a promising molecular target for the diagnosis and treatment of CAVD. However, further validation through in vivo and n vitro studies is necessary to confirm its role in CAVD pathogenesis and therapeutic potential.

Identification of Diagnostic Genes of Aortic Stenosis That Progresses from Aortic Valve Sclerosis

Background

Aortic valve sclerosis (AVS) is a pathological state that can progress to aortic stenosis (AS), which is a high-mortality valvular disease. However, effective medical therapies are not available to prevent this progression. This study aimed to explore potential biomarkers of AVS-AS advancement.

Methods

A microarray dataset and an RNA-sequencing dataset were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened from AS and AVS samples. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning model construction were conducted to identify diagnostic genes. A receiver operating characteristic (ROC) curve was generated to evaluate diagnostic value. Immune cell infiltration was then used to analyze differences in immune cell proportion between tissues. Finally, immunohistochemistry was applied to further verify protein concentration of diagnostic factors.

Results

A total of 330 DEGs were identified, including 92 downregulated and 238 upregulated genes. The top 5% of DEGs (n = 17) were screened following construction of a PPI network. IL-7 and VCAM-1 were identified as the most significant candidate genes via least absolute shrinkage and selection operator (LASSO) regression. The diagnostic value of the model and each gene were above 0.75. Proportion of anti-inflammatory M2 macrophages was lower, but the fraction of pro-inflammatory gamma-delta T cells was elevated in AS samples. Finally, levels of IL-7 and VCAM-1 were validated to be higher in AS tissue than in AVS tissue using immunohistochemistry.

Conclusion

IL-7 and VCAM-1 were identified as biomarkers during the disease progression. This is the first study to analyze gene expression differences between AVS and AS and could open novel sights for future studies on alleviating or preventing the disease progression.

The role of matrix metalloproteinase 9 in fibrosis diseases and its molecular mechanisms

Fibrosis is a process of tissue repair that results in the slow creation of scar tissue to replace healthy tissue and can affect any tissue or organ. Its primary feature is the massive deposition of extracellular matrix (mainly collagen), eventually leading to tissue dysfunction and organ failure. The progression of fibrotic diseases has put a significant strain on global health and the economy, and as a result, there is an urgent need to find some new therapies. Previous studies have identified that inflammation, oxidative stress, some cytokines, and remodeling play a crucial role in fibrotic diseases and are essential avenues for treating fibrotic diseases. Among them, matrix metalloproteinases (MMPs) are considered the main targets for the treatment of fibrotic diseases since they are the primary driver involved in ECM degradation, and tissue inhibitors of metalloproteinases (TIMPs) are natural endogenous inhibitors of MMPs. Through previous studies, we found that MMP-9 is an essential target for treating fibrotic diseases. However, it is worth noting that MMP-9 plays a bidirectional regulatory role in different fibrotic diseases or different stages of the same fibrotic disease. Previously identified MMP-9 inhibitors, such as pirfenidone and nintedanib, suffer from some rather pronounced side effects, and therefore, there is an urgent need to investigate new drugs. In this review, we explore the mechanism of action and signaling pathways of MMP-9 in different tissues and organs, hoping to provide some ideas for developing safer and more effective biologics.

Huanglian Jiedu Wan intervened with "Shi-Re Shanghuo" syndrome through regulating immune balance mediated by biomarker succinate

With increasing stress in daily life and work, subhealth conditions induced by "Shi-Re Shanghuo" syndrome was gradually universal. "Huanglian Jiedu Wan" (HLJDW) was the first new syndrome Chinese medicine approved for the treatment of "Shi-Re Shanghuo" with promising clinical efficacy. Preliminary small-sample clinical studies have identified some notable biomarkers (succinate, 4-hydroxynonenal, etc.). However, the correlation and underlying mechanism between these biomarkers of HLJDW intervention on "Shi-Re Shanghuo" syndrome remained ambiguous. Therefore, this study was designed as a randomized, double-blind, multicenter, placebo-controlled Phase II clinical trial, employing integrated analysis techniques such as non-targeted and targeted metabolomics, salivary microbiota, proteomics, parallel peaction monitoring, molecular docking and surface plasmon resonance (SPR). The results of the correlation analysis indicated that HLJDW could mediate the balance between inflammation and immunity through succinate produced via host and microbial source to intervene "Shi-Re Shanghuo" syndrome. Further through the HIF1α/MMP9 pathway, succinate regulated downstream arachidonic acid metabolism, particularly the lipid peroxidation product 4-hydroxynonenal. Finally, an animal model of recurrent oral ulcers induced by "Shi-Re Shang Huo" was established and HLJDW was used for intervention, key essential indicators (succinate, glutamine, 4-hydroxynonenal, arachidonic acid metabolism) essential in the potential pathway HIF1α/MMP9 discovered in clinical practice were validated. The results were found to be consistent with our clinical findings. Taken together, succinate was observed as an important signal that triggered immune responses, which might serve as a key regulatory metabolic switch or marker of "Shi-Re Shanghuo" syndrome treated with HLJDW.

β-asarone improves cognitive impairment and alleviates autophagy in mice with vascular dementia via the cAMP/PKA/CREB pathway

BACKGROUND

Vascular dementia (VD) is the second most common type of dementia after Alzheimer's disease. β-asarone, a major component of Acorus tatarinowii Schott, is important in neurodegenerative and neurovascular diseases. Studies have confirmed that β-asarone can mitigate autophagy and reduce damage in hypoxic cells. We also reported that β-asarone improves learning and memory. This study further clarifies whether β-asarone attenuates cerebral ischaemic injury by acting through the cAMP/PKA/CREB pathway in VD model mice.

METHODS

Here, genes and potential pathways that may be targeted by β-asarone for the treatment of transient cerebral ischaemia (TCI) and cognitive impairment (CI) were obtained using network pharmacology. The two-vessel occlusion method was used to establish the VD model. The Morris water maze test was used to evaluate the effects on memory. Then, the protein levels of mitofusin-2 (Mfn2), brain-derived neurotrophic factor (BDNF), optic atrophy 1 (OPA1), cyclic adenosine monophosphate (cAMP), myelin basic protein (MBP), matrix metalloproteinase-9 (MMP9) and neuron specific enolase (NSE) were determined by ELISA. The levels of superoxide dismutase (SOD) and malonaldehyde (MDA) were measured using commercial kits. Then, qRT-PCR was employed to investigate the expression of the candidate genes screened from the protein-protein interaction (PPI) network. Furthermore, the expression of the autophagy-related proteins Beclin-1, (microtubule-associated protein light chain 3) LC3, p62, postsynaptic density protein 95 (PSD95), protein kinase A (PKA), pPKA, cyclic-AMP response binding protein (CREB), and pCREB was determined by western blotting. The expression of autophagy-related proteins, PSD95 and translocase of outer mitochondrial membrane 20 (TOM20) was determined by immunofluorescence analyses.

RESULTS

The network pharmacological analysis showed 234 targets related to β-asarone, 1,118 genes related to TCI and 2,039 genes associated with CI. Our results confirm that β-asarone treatment not only alleviated brain damage in the VD model by improving mitochondrial and synaptic function, reducing neuronal injury and upregulating the expression of antioxidants but also effectively improved the cognitive behaviour of VD model mice. Moreover, β-asarone downregulated VD-induced RELA and CCND1 mRNA expression. In addition, we validated that β-asarone increased the phosphorylation of PKA and CREB and upregulated cAMP protein expression. The results showed that the cAMP/PKA/CREB signalling pathway was upregulated. Moreover, β-asarone administration decreased the protein expression levels of Beclin-1 and LC3 and increased the expression levels of p62 in VD model mice.

CONCLUSIONS

β-asarone inhibits Beclin-1-dependent autophagy and upregulates the cAMP/PKA/CREB signalling pathway to attenuate mitochondrial and synaptic damage from cerebral ischaemia and improve learning and cognitive abilities in VD model mice.

Retracted: Identification of MMP9 as a Novel Biomarker to Mitochondrial Metabolism Disorder and Oxidative Stress in Calcific Aortic Valve Stenosis

[This retracts the article DOI: 10.1155/2022/3858871.].

Influence of Aortic Valve Stenosis and Wall Shear Stress on Platelets Function

Aortic valve stenosis (AS) is a common heart valve disease in the elderly population, and its pathogenesis remains an interesting area of research. The degeneration of the aortic valve leaflets gradually progresses to valve sclerosis. The advanced phase is marked by the presence of extracellular fibrosis and calcification. Turbulent, accelerated blood flow generated by the stenotic valve causes excessive damage to the aortic wall. Elevated shear stress due to AS leads to the degradation of high-molecular weight multimers of von Willebrand factor, which may involve bleeding in the mucosal tissues. Conversely, elevated shear stress has been associated with the release of thrombin and the activation of platelets, even in individuals with acquired von Willebrand syndrome. Moreover, turbulent blood flow in the aorta may activate the endothelium and promote platelet adhesion and activation on the aortic valve surface. Platelets release a wide range of mediators, including lysophosphatidic acid, which have pro-osteogenic effects in AS. All of these interactions result in blood coagulation, fibrinolysis, and the hemostatic process. This review summarizes the current knowledge on high shear stress-induced hemostatic disorders, the influence of AS on platelets and antiplatelet therapy.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications

BACKGROUND

A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers.

METHODS

The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database.

RESULTS

The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI.

CONCLUSION

This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

The Complex Relationship between Hypoxia Signaling, Mitochondrial Dysfunction and Inflammation in Calcific Aortic Valve Disease: Insights from the Molecular Mechanisms to Therapeutic Approaches

Calcific aortic valve stenosis (CAVS) is among the most common causes of cardiovascular mortality in an aging population worldwide. The pathomechanisms of CAVS are such a complex and multifactorial process that researchers are still making progress to understand its physiopathology as well as the complex players involved in CAVS pathogenesis. Currently, there is no successful and effective treatment to prevent or slow down the disease. Surgical and transcatheter valve replacement represents the only option available for treating CAVS. Insufficient oxygen availability (hypoxia) has a critical role in the pathogenesis of almost all CVDs. This process is orchestrated by the hallmark transcription factor, hypoxia-inducible factor 1 alpha subunit (HIF-1α), which plays a pivotal role in regulating various target hypoxic genes and metabolic adaptations. Recent studies have shown a great deal of interest in understanding the contribution of HIF-1α in the pathogenesis of CAVS. However, it is deeply intertwined with other major contributors, including sustained inflammation and mitochondrial impairments, which are attributed primarily to CAVS. The present review aims to cover the latest understanding of the complex interplay effect of hypoxia signaling pathways, mitochondrial dysfunction, and inflammation in CAVS. We propose further hypotheses and interconnections on the complexity of these impacts in a perspective of better understanding the pathophysiology. These interplays will be examined considering recent studies that shall help us better dissect the molecular mechanism to enable the design and development of potential future therapeutic approaches that can prevent or slow down CAVS processes.

Screening of immune-related secretory proteins linking chronic kidney disease with calcific aortic valve disease based on comprehensive bioinformatics analysis and machine learning

BACKGROUND

Chronic kidney disease (CKD) is one of the most significant cardiovascular risk factors, playing vital roles in various cardiovascular diseases such as calcific aortic valve disease (CAVD). We aim to explore the CKD-associated genes potentially involving CAVD pathogenesis, and to discover candidate biomarkers for the diagnosis of CKD with CAVD.

METHODS

Three CAVD, one CKD-PBMC and one CKD-Kidney datasets of expression profiles were obtained from the GEO database. Firstly, to detect CAVD key genes and CKD-associated secretory proteins, differentially expressed analysis and WGCNA were carried out. Protein-protein interaction (PPI), functional enrichment and cMAP analyses were employed to reveal CKD-related pathogenic genes and underlying mechanisms in CKD-related CAVD as well as the potential drugs for CAVD treatment. Then, machine learning algorithms including LASSO regression and random forest were adopted for screening candidate biomarkers and constructing diagnostic nomogram for predicting CKD-related CAVD. Moreover, ROC curve, calibration curve and decision curve analyses were applied to evaluate the diagnostic performance of nomogram. Finally, the CIBERSORT algorithm was used to explore immune cell infiltration in CAVD.

RESULTS

The integrated CAVD dataset identified 124 CAVD key genes by intersecting differential expression and WGCNA analyses. Totally 983 CKD-associated secretory proteins were screened by differential expression analysis of CKD-PBMC/Kidney datasets. PPI analysis identified two key modules containing 76 nodes, regarded as CKD-related pathogenic genes in CAVD, which were mostly enriched in inflammatory and immune regulation by enrichment analysis. The cMAP analysis exposed metyrapone as a more potential drug for CAVD treatment. 17 genes were overlapped between CAVD key genes and CKD-associated secretory proteins, and two hub genes were chosen as candidate biomarkers for developing nomogram with ideal diagnostic performance through machine learning. Furthermore, SLPI/MMP9 expression patterns were confirmed in our external cohort and the nomogram could serve as novel diagnosis models for distinguishing CAVD. Finally, immune cell infiltration results uncovered immune dysregulation in CAVD, and SLPI/MMP9 were significantly associated with invasive immune cells.

CONCLUSIONS

We revealed the inflammatory-immune pathways underlying CKD-related CAVD, and developed SLPI/MMP9-based CAVD diagnostic nomogram, which offered novel insights into future serum-based diagnosis and therapeutic intervention of CKD with CAVD.

Porphyromonas gingivalis outer membrane vesicles exacerbate retinal microvascular endothelial cell dysfunction in diabetic retinopathy

Diabetic retinopathy (DR) is one of the leading causes of blindness. Periodontitis is one of the highest oral incidences and has been closely related to various systemic conditions through Porphyromonas gingivalis (P. gingivalis). P. gingivalis OMVs, derived from P. gingivalis, can cause endothelial dysfunction and potentially affect microvascular diseases. Current epidemiological studies provide limited evidence suggesting that periodontitis is associated with DR. However, there is a lack of basic research elucidating how periodontitis affects the severity of DR. This study aimed to explore the potential of P. gingivalis OMVs to contribute to the pathogenesis of DR and explore how it affect the retinal microvascular endothelium. The results demonstrated that P. gingivalis OMVs accelerated the blood-retinal barrier damage in DR mice. In vitro studies showed that the expression of inflammatory factors in human retinal microvascular endothelial cells (HRMECs) was increased after P. gingivalis OMVs stimulation, and the increased reactive oxygen species production, mitochondrial dysfunction, apoptosis, and altered endothelial permeability were observed in HRMECs under P. gingivalis OMVs stimulation. In addition, we found that protease-activated receptor-2 (PAR-2) regulated OMVs-induced TNF-α, MMP-9 mRNA expression, cell death, and endothelial permeability. Overall, we suggested that P. gingivalis OMVs induced mitochondria-related cell death of HRMECs and accelerated endothelial dysfunction, thus aggravating DR, in which PAR-2 plays a potential role. This study is the first research report to delineate the potential molecular mechanism of P. gingivalis OMVs on DR pathogenesis, which uniquely focused on elucidating the possible impact of periodontal pathogen derivatives on DR progression.

Identification of key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head based on machine learning

BACKGROUND

This study was aimed to identify key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head (SONFH) based on machine learning algorithm.

METHODS

The SONFH dataset GSE123568 (including 30 SONFH patients and 10 controls) was used in this study. The differentially expressed genes (DEGs) were selected between SONFH and control groups, which were subjected to WGCNA. Ferroptosis-related genes were downloaded from FerrDb V2, which were then compared with DEGs and module genes. Two machine learning algorithms were utilized to identify key ferroptosis-related genes, and the underlying mechanisms were analyzed by GSEA. Correlation analysis between key ferroptosis-related genes and immune cells was analyzed by Spearman method. The drug-gene relationships were predicted in CTD.

RESULTS

Total 2030 DEGs were obtained. WGCNA identified two key modules and obtained 1561 module genes. Finally, 43 intersection genes were identified as disease-related ferroptosis-related genes. After LASSO regression and RFE-SVM algorithms, 4 intersection genes (AKT1S1, BACH1, MGST1 and SETD1B) were considered as key ferroptosis-related gene. The 4 genes were correlated with osteoclast differentiation pathway. Twenty immune cells with significant differences were obtained between the groups, and the 4 key ferroptosis-related genes were correlated with most immune cells. In CTD, 41 drug-gene relationship pairs were finally obtained.

CONCLUSIONS

The 4 key ferroptosis-related genes, AKT1S1, BACH1, MGST1 and SETD1B, were identified to play a critical role in SONFH progression through osteoclast differentiation and immunologic mechanisms. Additionally, all the 4 genes had good disease prediction effect and could act as biomarkers for the diagnosis and treatment of SONFH.