Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke

Bioinformatics Analysis Reveals HIST1H2BH as a Novel Diagnostic Biomarker for Atrial Fibrillation-Related Cardiogenic Thromboembolic Stroke

Atrial fibrillation (AF) is a significant precursor to cerebral embolism. Our study sought to unearth new diagnostic biomarkers for atrial fibrillation-related cerebral embolism (AF-CE) by meticulously examining multiple GEO datasets and meta-analysis. The gene expression omnibus (GEO) database provided RNA sequencing data associated with AF and stroke. We began by pinpointing genes with varied expressions in AF-CE patient blood samples. A meta-analysis was subsequently undertaken using several RNA sequencing datasets to verify these genes. LASSO regression discerned key genes for AF-CE, with their diagnostic prowess verified through ROC curve examination. Active signaling pathways within stroke patients were discerned via GO and KEGG enrichment, with PPI interactions detailing gene interplay. Differential gene analysis revealed an upregulation of sixteen genes and a downregulation of four in stroke patient blood samples. Eight genes showcased varied expression in the meta-analysis. LASSO regression zeroed in on five of these, culminating in HIST1H2BH's identification as a characteristic gene. HIST1H2BH's prowess in predicting AF-CE was confirmed through ROC. Integrin signaling, platelet activation, ECM interactions, and the PI3K-Akt pathway were found active in stroke victims. HIST1H2BH's interaction with the notably upregulated ITGA2B was spotlighted by PPI. Additionally, HIST1H2BH exhibited links with NK cells and eosinophils. HIST1H2BH emerges as an insightful diagnostic beacon for AF-CE. Its presence, post AF, potentially modulates pathways, accentuating platelet activation and consequent thrombus generation, leading to cerebral embolism.

Novel insight into the role of A-kinase anchoring proteins (AKAPs) in ischemic stroke and therapeutic potentials

Ischemic stroke, a devastating disease associated with high mortality and disability worldwide, has emerged as an urgent public health issue. A-kinase anchoring proteins (AKAPs) are a group of signal-organizing molecules that compartmentalize and anchor a wide range of receptors and effector proteins and have a major role in stabilizing mitochondrial function and promoting neurodevelopmental development in the central nervous system (CNS). Growing evidence suggests that dysregulation of AKAPs expression and activity is closely associated with oxidative stress, ion disorder, mitochondrial dysfunction, and blood-brain barrier (BBB) impairment in ischemic stroke. However, the underlying mechanisms remain inadequately understood. This review provides a comprehensive overview of the composition and structure of A-kinase anchoring protein (AKAP) family members, emphasizing their physiological functions in the CNS. We explored in depth the molecular and cellular mechanisms of AKAP complexes in the pathological progression and risk factors of ischemic stroke, including hypertension, hyperglycemia, lipid metabolism disorders, and atrial fibrillation. Herein, we highlight the potential of AKAP complexes as a pharmacological target against ischemic stroke in the hope of inspiring translational research and innovative clinical approaches.

Deciphering the Role of microRNAs: Unveiling Clinical Biomarkers and Therapeutic Avenues in Atrial Fibrillation and Associated Stroke-A Systematic Review

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression by binding to target messenger RNAs (mRNAs). miRNAs have been implicated in a variety of cardiovascular and neurological diseases, such as myocardial infarction, cardiomyopathies of various geneses, rhythmological diseases, neurodegenerative illnesses and strokes. Numerous studies have focused on the expression of miRNA patterns with respect to atrial fibrillation (AF) or acute ischemic stroke (AIS) However, only a few studies have addressed the expression pattern of miRNAs in patients with AF and AIS in order to provide not only preventive information but also to identify therapeutic potentials. Therefore, the aim of this review is to summarize 18 existing manuscripts that have dealt with this combined topic of AF and associated AIS in detail and to shed light on the most frequently mentioned miRNAs-1, -19, -21, -145 and -146 with regard to their molecular mechanisms and targets on both the heart and the brain. From this, possible diagnostic and therapeutic consequences for the future could be derived.

Shared Genetic Features of Psoriasis and Myocardial Infarction: Insights From a Weighted Gene Coexpression Network Analysis

BACKGROUND

Increasing evidence suggests a higher propensity for acute myocardial infarction (MI) in patients with psoriasis. However, the shared mechanisms underlying this comorbidity in these patients remain unclear. This study aimed to explore the shared genetic features of psoriasis and MI and to identify potential biomarkers indicating their coexistence.

METHODS AND RESULTS

Data sets obtained from the gene expression omnibus were examined using a weighted gene coexpression network analysis approach. Hub genes were identified using coexpression modules and validated in other data sets and through in vitro cellular experiments. Bioinformatics tools, including the Human microRNA Disease Database, StarBase, and miRNet databases, were used to construct a ceRNA network and predict potential regulatory mechanisms. By applying weighted gene coexpression network analysis, we identified 2 distinct modules that were significant for both MI and psoriasis. Inflammatory and immune pathways were highlighted by gene ontology enrichment analysis of the overlapping genes. Three pivotal genes-Src homology and collagen 1, disruptor of telomeric silencing 1-like, and feline leukemia virus subgroup C cellular receptor family member 2-were identified as potential biomarkers. We constructed a ceRNA network that suggested the upstream regulatory roles of these genes in the coexistence of psoriasis and MI.

CONCLUSIONS

As potential therapeutic targets, Src homology and collagen 1, feline leukemia virus subgroup C cellular receptor family member 2, and disruptor of telomeric silencing 1-like provide novel insights into the shared genetic features between psoriasis and MI. This study paves the way for future studies focusing on the prevention of MI in patients with psoriasis.

Association of lipopolysaccharide with new-onset atrial fibrillation in ST-segment elevation myocardial infarction

Background

Lipopolysaccharide (LPS) is related to various cardiovascular diseases. However, the relationship between LPS and new-onset atrial fibrillation (NOAF) after ST-segment elevation myocardial infarction (STEMI) has yet to be elucidated. This study aimed to evaluate the impact of LPS on NOAF in STEMI patients.

Methods

This was a single-center retrospective observational study including 806 patients diagnosed with STEMI. LPS levels were determined using a commercial ELISA kit. NOAF was characterized by postadmission AF with the absence of any prior history of AF.

Results

A total of 806 participants were enrolled, with 752 individuals in the non-AF group (93.3%) and 54 individuals in the AF group (6.7%). Multivariable analysis showed that LPS (OR = 1.047; 95% CI: 1.029-1.065, P < 0.001) was an independent risk marker for NOAF. The analysis of the ROC demonstrated that LPS had an AUC of 0.717 in predicting NOAF. When LPS was added to the conventional model, the ability of the risk model to discriminate and reclassify NOAF was improved significantly (IDI 0.053, P = 0.001; NRI 0.510, P < 0.001).

Conclusion

Elevated LPS is associated with an increased risk of NOAF in STEMI patients. The integration of LPS can improve the ability to predict NOAF in STEMI patients.

miRNAs in Heart Development and Disease

Cardiovascular diseases (CVD) are a group of disorders that affect the heart and blood vessels. They include conditions such as myocardial infarction, coronary artery disease, heart failure, arrhythmia, and congenital heart defects. CVDs are the leading cause of death worldwide. Therefore, new medical interventions that aim to prevent, treat, or manage CVDs are of prime importance. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the posttranscriptional level and play important roles in various biological processes, including cardiac development, function, and disease. Moreover, miRNAs can also act as biomarkers and therapeutic targets. In order to identify and characterize miRNAs and their target genes, scientists take advantage of computational tools such as bioinformatic algorithms, which can also assist in analyzing miRNA expression profiles, functions, and interactions in different cardiac conditions. Indeed, the combination of miRNA research and bioinformatic algorithms has opened new avenues for understanding and treating CVDs. In this review, we summarize the current knowledge on the roles of miRNAs in cardiac development and CVDs, discuss the challenges and opportunities, and provide some examples of recent bioinformatics for miRNA research in cardiovascular biology and medicine.

Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning

Background

Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. Discovering platelet-related biomarkers, developing diagnostic models, and screening antiplatelet drugs are crucial for IS diagnosis and treatment.

Methods and results

Combining and normalizing GSE16561 and GSE22255 datasets identified 1,753 upregulated and 1,187 downregulated genes. Fifty-one genes in the platelet-related module were isolated using weighted gene co-expression network analysis (WGCNA) and other analyses, including 50 upregulated and one downregulated gene. Subsequent enrichment and network analyses resulted in 25 platelet-associated genes and six diagnostic markers for a risk assessment model. This model's area under the ROC curve outperformed single genes, and in the peripheral blood of the high-risk group, immune infiltration indicated a higher proportion of CD4, resting CD4 memory, and activated CD4 memory T cells, along with a lower proportion of CD8 T cells in comparison to the low-risk group. Utilizing the gene expression matrix and the CMap database, we identified two potential drugs for IS. Finally, a rat MACO/R model was used to validate the diagnostic markers' expression and the drugs' predicted anticoagulant effects.

Conclusion

We identified six IS platelet-related biomarkers (APP, THBS1, F13A1, SRC, PPBP, and VCL) for a robust diagnostic model. The drugs alpha-linolenic acid and ciprofibrate have potential antiplatelet effects in IS. This study advances early IS diagnosis and treatment.

Identification and validation of genes associated with aging-related cardiovascular disease

Aging is acknowledged as the most significant risk factor for cardiovascular disease (CVD). This study sought to identify and validate potential aging-related genes associated with CVD by using bioinformatics. The confluence of the limma test, weighted correlation network analysis (WGCNA), and 2129 aging and senescence-associated genes led to the identification of aging-related differential expression genes (ARDEGs). By using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), potential biological roles and pathways of ARDEGs were identified. To find the significantly different functions between CVD and non-cardiovascular disease (nCVD) and to reckon the processes score, enrichment analysis of all genes was carried out using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). By using GO and KEGG, potential biological roles and pathways of ARDEGs were identified. To evaluate the immune cell composition of the immune microenvironment, we performed an immune infiltration analysis on the dataset from the training group. We were able to acquire four ARDEGs (PTGS2, MMP9, HBEGF, and FN1). Aging, cellular senescence, and nitric oxide signal transduction were selected for biological function analysis. The diagnostic value of the four ARDEGs in distinguishing CVD from nCVD samples was deemed to be favorable. This research identified four ARDEGs that are associated with CVD. This study provides insight into prospective novel biomarkers for aging-related CVD diagnosis and progression monitoring.

Genetics in Ischemic Stroke: Current Perspectives and Future Directions

Ischemic stroke is a heterogeneous condition influenced by a combination of genetic and environmental factors. Recent advancements have explored genetics in relation to various aspects of ischemic stroke, including the alteration of individual stroke occurrence risk, modulation of treatment response, and effectiveness of post-stroke functional recovery. This article aims to review the recent findings from genetic studies related to various clinical and molecular aspects of ischemic stroke. The potential clinical applications of these genetic insights in stratifying stroke risk, guiding personalized therapy, and identifying new therapeutic targets are discussed herein.

Bioinformatics and functional experiments reveal that MRC2 inhibits atrial fibrillation via the PPAR signaling pathway

Background

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that requires improved clinical markers to increase diagnostic accuracy and provide insight into its pathogenesis. Although some biomarkers are available, new ones need to be discovered to better capture the complex physiology of AF. However, their limitations are still not fully addressed. Bioinformatics and functional studies can help find new clinical markers and improve the understanding of AF, meeting the need for early diagnosis and individualized treatment.

Methods

To identify AF-related differentially expressed genes (DEGs), We applied the messenger RNA (mRNA) expression profile retrieved in Series Matrix File format from the GSE143924 microarray dataset obtained from the Gene Expression Omnibus (GEO) database, and then used weighted gene co-expression network analysis (WGCNA) to identify the overlapping genes. These genes were analyzed by enrichment analysis, expression analysis and others to obtain the hub gene. Additionally, the potential signaling pathway of hub gene in AF was explored and verified by functional experiments, like quantitative real-time polymerase chain reaction (qRT-PCR), cell counting kit-8 (CCK-8), flow cytometry, and Western blotting (WB) assay.

Results

From the GSE143924 data (410 DEGs) and tan module (57 genes), 10 overlapping genes were identified. A central down-regulated gene in AF, MRC2, was identified through bioinformatics analysis. based on these results, it was hypothesized that the PPAR signaling pathway is related to the mechanism of action of MRC2 in AF. Moreover, over-MRC2 markedly reduced the growth speed of angiotensin II (Ang II)-induced human cardiac fibroblasts (HCFs) and increased apoptosis. Conversely, knockdown of MRC2 promoted HCFs cell proliferation number. Additionally, MRC2 over-expression increased the protein expression level of PPARα, PPARγ, CPT-1, and SIRT3 in Ang II-induced HCFs.

Conclusions

While meeting the need for new biomarkers in the diagnosis and prognosis of AF, this study reveals the inherent limitations of current biomarkers. We identified MRC2 as a key player as an inhibitory gene in AF, highlighting its role in suppressing AF progression through the PPAR signaling pathway. MRC2 may not only serve as a diagnostic indicator, but also as a promising therapeutic target for patients with AF, which is expected to be applied in clinical practice and open up new avenues for individualized interventions.

Long Non-coding RNA Involved in the Pathophysiology of Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is a prevalent and chronic cardiovascular disorder associated with various pathophysiological alterations, including atrial electrical and structural remodeling, disrupted calcium handling, autonomic nervous system dysfunction, aberrant energy metabolism, and immune dysregulation. Emerging evidence suggests that long non-coding RNAs (lncRNAs) play a significant role in the pathogenesis of AF.

OBJECTIVE

This discussion aims to elucidate the involvement of AF-related lncRNAs, with a specific focus on their role as miRNA sponges that modulate crucial signaling pathways, contributing to the progression of AF. We also address current limitations in AF-related lncRNA research and explore potential future directions in this field. Additionally, we summarize feasible strategies and promising delivery systems for targeting lncRNAs in AF therapy.

CONCLUSION

In conclusion, targeting AF-related lncRNAs holds substantial promise for future investigations and represents a potential therapeutic avenue for managing AF.

Genetic Architecture of Ischaemic Strokes after COVID-19 Shows Similarities with Large Vessel Strokes

We aimed to analyse whether patients with ischaemic stroke (IS) occurring within eight days after the onset of COVID-19 (IS-COV) are associated with a specific aetiology of IS. We used SUPERGNOVA to identify genome regions that correlate between the IS-COV cohort (73 IS-COV cases vs. 701 population controls) and different aetiological subtypes. Polygenic risk scores (PRSs) for each subtype were generated and tested in the IS-COV cohort using PRSice-2 and PLINK to find genetic associations. Both analyses used the IS-COV cohort and GWAS from MEGASTROKE (67,162 stroke patients vs. 454,450 population controls), GIGASTROKE (110,182 vs. 1,503,898), and the NINDS Stroke Genetics Network (16,851 vs. 32,473). Three genomic regions were associated (p-value < 0.05) with large artery atherosclerosis (LAA) and cardioembolic stroke (CES). We found four loci targeting the genes PITX2 (rs10033464, IS-COV beta = 0.04, p-value = 2.3 × 10-2, se = 0.02), previously associated with CES, HS6ST1 (rs4662630, IS-COV beta = -0.04, p-value = 1.3 × 10-3, se = 0.01), TMEM132E (rs12941838 IS-COV beta = 0.05, p-value = 3.6 × 10-4, se = 0.01), and RFFL (rs797989 IS-COV beta = 0.03, p-value = 1.0 × 10-2, se = 0.01). A statistically significant PRS was observed for LAA. Our results suggest that IS-COV cases are genetically similar to LAA and CES subtypes. Larger cohorts are needed to assess if the genetic factors in IS-COV cases are shared with the general population or specific to viral infection.

Construction and validation of a cuproptosis-related diagnostic gene signature for atrial fibrillation based on ensemble learning

BACKGROUND

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Nonetheless, the accurate diagnosis of this condition continues to pose a challenge when relying on conventional diagnostic techniques. Cell death is a key factor in the pathogenesis of AF. Existing investigations suggest that cuproptosis may also contribute to AF. This investigation aimed to identify a novel diagnostic gene signature associated with cuproptosis for AF using ensemble learning methods and discover the connection between AF and cuproptosis.

RESULTS

Two genes connected to cuproptosis, including solute carrier family 31 member 1 (SLC31A1) and lipoic acid synthetase (LIAS), were selected by integration of random forests and eXtreme Gradient Boosting algorithms. Subsequently, a diagnostic model was constructed that includes the two genes for AF using the Light Gradient Boosting Machine (LightGBM) algorithm with good performance (the area under the curve value > 0.75). The microRNA-transcription factor-messenger RNA network revealed that homeobox A9 (HOXA9) and Tet methylcytosine dioxygenase 1 (TET1) could target SLC31A1 and LIAS in AF. Functional enrichment analysis indicated that cuproptosis might be connected to immunocyte activities. Immunocyte infiltration analysis using the CIBERSORT algorithm suggested a greater level of neutrophils in the AF group. According to the outcomes of Spearman's rank correlation analysis, there was a negative relation between SLC31A1 and resting dendritic cells and eosinophils. The study found a positive relationship between LIAS and eosinophils along with resting memory CD4+ T cells. Conversely, a negative correlation was detected between LIAS and CD8+ T cells and regulatory T cells.

CONCLUSIONS

This study successfully constructed a cuproptosis-related diagnostic model for AF based on the LightGBM algorithm and validated its diagnostic efficacy. Cuproptosis may be regulated by HOXA9 and TET1 in AF. Cuproptosis might interact with infiltrating immunocytes in AF.

Identification of a miRNA-mRNA regulatory network for post-stroke depression: a machine-learning approach

Objective

The study aimed to explore the miRNA and mRNA biomarkers in post-stroke depression (PSD) and to develop a miRNA-mRNA regulatory network to reveal its potential pathogenesis.

Methods

The transcriptomic expression profile was obtained from the GEO database using the accession numbers GSE117064 (miRNAs, stroke vs. control) and GSE76826 [mRNAs, late-onset major depressive disorder (MDD) vs. control]. Differentially expressed miRNAs (DE-miRNAs) were identified in blood samples collected from stroke patients vs. control using the Linear Models for Microarray Data (LIMMA) package, while the weighted correlation network analysis (WGCNA) revealed co-expressed gene modules correlated with the subject group. The intersection between DE-miRNAs and miRNAs identified by WGCNA was defined as stroke-related miRNAs, whose target mRNAs were stroke-related genes with the prediction based on three databases (miRDB, miRTarBase, and TargetScan). Using the GSE76826 dataset, the differentially expressed genes (DEGs) were identified. Overlapped DEGs between stroke-related genes and DEGs in late-onset MDD were retrieved, and these were potential mRNA biomarkers in PSD. With the overlapped DEGs, three machine-learning methods were employed to identify gene signatures for PSD, which were established with the intersection of gene sets identified by each algorithm. Based on the gene signatures, the upstream miRNAs were predicted, and a miRNA-mRNA network was constructed.

Results

Using the GSE117064 dataset, we retrieved a total of 667 DE-miRNAs, which included 420 upregulated and 247 downregulated ones. Meanwhile, WGCNA identified two modules (blue and brown) that were significantly correlated with the subject group. A total of 117 stroke-related miRNAs were identified with the intersection of DE-miRNAs and WGCNA-related ones. Based on the miRNA-mRNA databases, we identified a list of 2,387 stroke-related genes, among which 99 DEGs in MDD were also embedded. Based on the 99 overlapped DEGs, we identified three gene signatures (SPATA2, ZNF208, and YTHDC1) using three machine-learning classifiers. Predictions of the three mRNAs highlight four miRNAs as follows: miR-6883-5p, miR-6873-3p, miR-4776-3p, and miR-6738-3p. Subsequently, a miRNA-mRNA network was developed.

Conclusion

The study highlighted gene signatures for PSD with three genes (SPATA2, ZNF208, and YTHDC1) and four upstream miRNAs (miR-6883-5p, miR-6873-3p, miR-4776-3p, and miR-6738-3p). These biomarkers could further our understanding of the pathogenesis of PSD.

Identification of key biomarkers associated with immune cells infiltration for myocardial injury in dermatomyositis by integrated bioinformatics analysis

BACKGROUND

Dermatomyositis (DM) is an acquired autoimmune disease that can cause damage to various organs, including the heart muscle. However, the mechanisms underlying myocardial injury in DM are not yet fully understood.

METHODS

In this study, we utilized publicly available datasets from the Gene Expression Omnibus (GEO) database to identify hub-genes that are enriched in the immune system process in DM and myocarditis. Weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) analysis, protein-protein interaction (PPI), and gene ontology (GO) analysis were employed to identify these hub-genes. We then used the CIBERSORT method to analyze immune cell infiltration in skeletal muscle specimens of DM and myocardium specimens of myocarditis respectively. Correlation analysis was performed to investigate the relationship between key genes and infiltrating immune cells. Finally, we predicted regulatory miRNAs of hub-genes through miRNet and validated their expression in online datasets and clinical samples.

RESULTS

Using integrated bioinformatics analysis, we identified 10 and 5 hub-genes that were enriched in the immune system process in the database of DM and myocarditis respectively. The subsequent intersections between hub-genes were IFIT3, OAS3, ISG15, and RSAD2. We found M2 macrophages increased in DM and myocarditis compared to the healthy control, associating with the expression of IFIT3, OAS3, ISG15, and RSAD2 in DM and myocarditis positively. Gene function enrichment analysis (GSEA) showed that IFIT3, OAS3, ISG15, and RSAD2 were mainly enriched in type I interferon (IFN) signaling pathway, cellular response to type I interferon, and response to type I interferon. Finally, we verified that the expression of miR-146a-5p was significantly higher in the DM with myocardial injury than those without myocardial injury (p = 0.0009).

CONCLUSION

Our findings suggest that IFIT3, OAS3, ISG15, and RSAD2 may play crucial roles in the underlying mechanism of myocardial injury in DM. Serum miR-146a-5p could be a potential biomarker for myocardial injury in DM.

Bone Morphogenetic Protein 10-A Novel Biomarker to Predict Adverse Outcomes in Patients With Atrial Fibrillation

Background Patients with atrial fibrillation (AF) face an increased risk of death and major adverse cardiovascular events (MACE). We aimed to assess the predictive value of the novel atrial-specific biomarker BMP10 (bone morphogenetic protein 10) for death and MACE in patients with AF in comparison with NT-proBNP (N-terminal prohormone of B-type natriuretic peptide). Methods and Results BMP10 and NT-proBNP were measured in patients with AF enrolled in Swiss-AF (Swiss Atrial Fibrillation Study), a prospective multicenter cohort study. A total of 2219 patients were included (median follow-up 4.3 years [interquartile range 3.9, 5.1], mean age 73±9 years, 73% male). In multivariable Cox proportional hazard models, the adjusted hazard ratio (aHR) associated with 1 ng/mL increase of BMP10 was 1.60 (95% CI, 1.37-1.87) for all-cause death, and 1.54 (95% CI, 1.35-1.76) for MACE. For all-cause death, the concordance index was 0.783 (95% CI, 0.763-0.809) for BMP10, 0.784 (95% CI, 0.765-0.810) for NT-proBNP, and 0.789 (95% CI, 0.771-0.815) for both biomarkers combined. For MACE, the concordance index was 0.732 (95% CI, 0.715-0.754) for BMP10, 0.747 (95% CI, 0.731-0.768) for NT-proBNP, and 0.750 (95% CI, 0.734-0.771) for both biomarkers combined. When grouping patients according to NT-proBNP categories (<300, 300-900, >900 ng/L), higher aHRs were observed in patients with high BMP10 in the categories of low NT-proBNP (all-cause death aHR, 2.28 [95% CI, 1.15-4.52], MACE aHR, 1.88 [95% CI, 1.07-3.28]) and high NT-proBNP (all-cause death aHR, 1.61 [95% CI, 1.14-2.26], MACE aHR, 1.38 [95% CI, 1.07-1.80]). Conclusions BMP10 strongly predicted all-cause death and MACE in patients with AF. BMP10 provided additional prognostic information in low- and high-risk patients according to NT-proBNP stratification. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.

microRNAs as Biomarkers of Endothelial Dysfunction and Therapeutic Target in the Pathogenesis of Atrial Fibrillation

The pathophysiology of atrial fibrillation (AF) may involve atrial fibrosis/remodeling and dysfunctional endothelial activities. Despite the currently available treatment approaches, the progression of AF, its recurrence rate, and the high mortality risk of related complications underlay the need for more advanced prognostic and therapeutic strategies. There is increasing attention on the molecular mechanisms controlling AF onset and progression points to the complex cell to cell interplay that triggers fibroblasts, immune cells and myofibroblasts, enhancing atrial fibrosis. In this scenario, endothelial cell dysfunction (ED) might play an unexpected but significant role. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level. In the cardiovascular compartment, both free circulating and exosomal miRNAs entail the control of plaque formation, lipid metabolism, inflammation and angiogenesis, cardiomyocyte growth and contractility, and even the maintenance of cardiac rhythm. Abnormal miRNAs levels may indicate the activation state of circulating cells, and thus represent a specific read-out of cardiac tissue changes. Although several unresolved questions still limit their clinical use, the ease of accessibility in biofluids and their prognostic and diagnostic properties make them novel and attractive biomarker candidates in AF. This article summarizes the most recent features of AF associated with miRNAs and relates them to potentially underlying mechanisms.

GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

BACKGROUND

Stroke attributable to atrial fibrillation (AF related stroke, AFST) accounts for 13 ~ 26% of ischemic stroke. It has been found that AFST patients have a higher risk of disability and mortality than those without AF. Additionally, it's still a great challenge to treat AFST patients because its exact mechanism at the molecular level remains unclear. Thus, it's vital to investigate the mechanism of AFST and search for molecular targets of treatment. Long non-coding RNAs (lncRNAs) are related to the pathogenesis of various diseases. However, the role of lncRNAs in AFST remains unclear. In this study, AFST-related lncRNAs are explored using competing endogenous RNA (ceRNA) network analysis and weighted gene co-expression network analysis (WGCNA).

METHODS

GSE66724 and GSE58294 datasets were downloaded from GEO database. After data preprocessing and probe reannotation, differentially expressed lncRNAs (DELs) and differentially expressed mRNAs (DEMs) between AFST and AF samples were explored. Then, functional enrichment analysis and protein-protein interaction (PPI) network analysis of the DEMs were performed. At the meantime, ceRNA network analysis and WGCNA were performed to identify hub lncRNAs. The hub lncRNAs identified both by ceRNA network analysis and WGCNA were further validated by Comparative Toxicogenomics Database (CTD).

RESULTS

In all, 19 DELs and 317 DEMs were identified between the AFST and AF samples. Functional enrichment analysis suggested that the DEMs associated with AFST were mainly enriched in the activation of the immune response. Two lncRNAs which overlapped between the three lncRNAs identified by the ceRNA network analysis and the 28 lncRNAs identified by the WGCNA were screened as hub lncRNAs for further validation. Finally, lncRNA GAS6-AS1 turned out to be associated with AFST by CTD validation.

CONCLUSION

These findings suggested that low expression of GAS6-AS1 might exert an essential role in AFST through downregulating its downstream target mRNAs GOLGA8A and BACH2, and GAS6-AS1 might be a potential target for AFST therapy.

Detection of Immune Microenvironment Changes and Immune-Related Regulators in Langerhans Cell Histiocytosis Bone Metastasis

The inflammation/immune response pathway is considered a key contributor to the development of Langerhans cell histiocytosis (LCH) bone metastasis. However, the dynamic changes in the immune microenvironment of LCH bone metastasis and critical regulators are still unclear. Expression profiling by arrays of GSE16395, GSE35340, and GSE122476 was applied to detect the immune microenvironment changes in the development of LCH bone metastasis. The single-cell high-throughput sequencing of GSE133704, involved in LCH bone lesions, was analyzed. The online database Metascape and gene set variation analysis (GSVA) algorithms were used to detect the gene function of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network of hub regulators was constructed by the STRING database. In these results, key immune cells, such as Tem cells, NK T cells, CD8(+) T cells, and Th1 cells, were identified in LCH bone metastasis. These genes, which include LAG3, TSPAN5, LPAR5, VEGFA, CXCL16, CD74, and MARCKS, may significantly correlate with the cellular infiltration of B cells, aDCs, pDCs, cytotoxic cells, T cells, CD8+ T cells, T helper cells, and Tcm cells. In conclusion, our study constructed an atlas of the immune microenvironment of LCH bone metastasis. Genes including LAG3, TSPAN5, LPAR5, VEGFA, CXCL16, CD74, and MARCKS may be involved in the development of LCH bone metastasis. The hub gene-immune cell interactive map may be a potential prognostic biomarker for the progression of LCH bone metastasis and synergetic targets for immunotherapy in LCH patients.

Integrative identification of hub genes in development of atrial fibrillation related stroke

BACKGROUND

As the most common arrhythmia, atrial fibrillation (AF) is associated with a significantly increased risk of stroke, which causes high disability and mortality. To date, the underlying mechanism of stroke occurring after AF remains unclear. Herein, we studied hub genes and regulatory pathways involved in AF and secondary stroke and aimed to reveal biomarkers and therapeutic targets of AF-related stroke.

METHODS

The GSE79768 and GSE58294 datasets were used to analyze AF- and stroke-related differentially expressed genes (DEGs) to obtain a DEG1 dataset. Weighted correlation network analysis (WGCNA) was used to identify modules associated with AF-related stroke in GSE66724 (DEG2). DEG1 and DEG2 were merged, and hub genes were identified based on protein-protein interaction networks. Gene Ontology terms were used to analyze the enriched pathways. The GSE129409 and GSE70887 were applied to construct a circRNA-miRNA-mRNA network in AF-related stroke. Hub genes were verified in patients using quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

We identified 3,132 DEGs in blood samples and 253 DEGs in left atrial specimens. Co-expressed hub genes of EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 were significantly associated with AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 pathway was explored as the regulating axis in AF-related stroke. The qRT-PCR results were consistent with the bioinformatic analysis.

CONCLUSIONS

Hub genes EIF4E3, ZNF595, ZNF700, MATR3, ACKR4, ANXA3, SEPSECS-AS1, and RNF166 have potential as novel biomarkers and therapeutic targets in AF-related stroke. The hsa_circ_0018657/hsa-miR-198/EIF4E3 axis could play an important role regulating the development of AF-related stroke.

Identification of genes and key pathways underlying the pathophysiological association between nonalcoholic fatty liver disease and atrial fibrillation

Background

Atrial fibrillation (AF) is one of the most prevalent sustained cardiac arrhythmias. The latest studies have revealed a tight correlation between nonalcoholic fatty liver disease (NAFLD) and AF. However, the exact molecular mechanisms underlying the association between NAFLD and AF remain unclear. The current research aimed to expound the genes and signaling pathways that are related to the mechanisms underlying the association between these two diseases.

Materials and methods

NAFLD- and AF- related differentially expressed genes (DEGs) were identified via bioinformatic analysis of the Gene Expression Omnibus (GEO) datasets GSE63067 and GSE79768, respectively. Further enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), the construction of a protein–protein interaction (PPI) network, the identification of significant hub genes, and receiver operator characteristic curve analysis were conducted. The gene-disease interactions were analyzed using the Comparative Toxicogenomics Database. In addition, the hub genes were validated by quantitative Real-Time PCR (qRT-PCR) in NAFLD cell model.

Results

A total of 45 co-expressed differentially expressed genes (co-DEGs) were identified between the NAFLD/AF and healthy control individuals. GO and KEGG pathway analyses revealed that the co-DEGs were mostly enriched in neutrophil activation involved in the immune response and cytokine-cytokine receptor interactions. Moreover, eight hub genes were selected owing to their high degree of connectivity and upregulation in both the NAFLD and AF datasets. These genes included CCR2, PTPRC, CXCR2, MNDA, S100A9, NCF2, S100A12, and S100A8.

Conclusions

In summary, we conducted the gene differential expression analysis, functional enrichment analysis, and PPI analysis of DEGs in AF and NAFLD, which provides novel insights into the identification of potential biomarkers and valuable therapeutic leads for AF and NAFLD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01300-1.

CXCR4 and TYROBP mediate the development of atrial fibrillation via inflammation

Atrial fibrillation (AF) is a rapid supraventricular arrhythmia. However, the pathogenesis of atrial fibrillation remains controversial. We obtained transcriptome expression profiles GSE41177, GSE115574 and GSE79768 from GEO database. WGCNA was performed, DEGs were screened, PPI network was constructed using STRING database. CTD database was used to identify the reference score of hub genes associated with cardiovascular diseases. Prediction of miRNAs of hub genes was performed by TargetScan. DIANA‐miRPath v3.0 was applied to make functional annotation of miRNA. The animal model of atrial fibrillation was constructed, RT‐PCR was used to verify the expression of hub genes. Immunofluorescence assay for THBS2 and VCAN was made to identify molecular. Design of BP neural network was made to explore the prediction relationship of CXCR4 and TYROBP on AF. The merged datasets contained 104 up‐regulated and 34 down‐regulated genes. GO and KEGG enrichment analysis results of DEGs showed they were mainly enriched in ‘regulation of release of sequestered calcium ion into cytosol’, ‘actin cytoskeleton organization’ and ‘focal adhesion’. The hub genes were CXCR4, SNAI2, S100A4, IGFBP3, CSNK2A1, CHGB, VCAN, APOE, C1QC and TYROBP, which were up‐regulated expression in the AF compared with control tissues. There was strong correlation among the CXCR4, TYROBP and AF based on the BP neural network. Through training, best training performance is 9.6474e‐05 at epoch 14, and the relativity was 0.99998. CXCR4 and TYROBP might be involved in the development of atrial fibrillation by affecting inflammation‐related signalling pathways and may serve as targets for early diagnosis and preventive treatment.

Stroke and Etiopathogenesis: What Is Known?

Background: A substantial portion of stroke risk remains unexplained, and a contribution from genetic factors is supported by recent findings. In most cases, genetic risk factors contribute to stroke risk as part of a multifactorial predisposition. A major challenge in identifying the genetic determinants of stroke is fully understanding the complexity of the phenotype. Aims: Our narrative review is needed to improve our understanding of the biological pathways underlying the disease and, through this understanding, to accelerate the identification of new drug targets. Methods: We report, the research in the literature until February 2022 in this narrative review. The keywords are stroke, causes, etiopathogenesis, genetic, epigenetic, ischemic stroke. Results: While better risk prediction also remains a long-term goal, its implementation is still complex given the small effect-size of genetic risk variants. Some authors encourage the use of stroke genetic panels for stroke risk assessment and further stroke research. In addition, new biomarkers for the genetic causes of stroke and new targets for gene therapy are on the horizon. Conclusion: We summarize the latest evidence and perspectives of ischemic stroke genetics that may be of interest to the physician and useful for day-to-day clinical work in terms of both prevention and treatment of ischemic stroke.

Chrysophanol exerts a protective effect against sepsis-induced acute myocardial injury through modulating the microRNA-27b-3p/Peroxisomal proliferating-activated receptor gamma axis

Sepsis, a leading contributor to the death of inpatients, results in severe organ dysfunction as complications. The heart is one of the major organs attacked by sepsis, and the effective control of the inflammatory cascade reaction in sepsis is of great significance in alleviating sepsis-associated acute myocardial injury (S-AMI). Chrysophanol, a natural anthraquinone, has been discovered to carry anti-inflammatory effects. The aim of this paper is to probe the impact of Chrysophanol on S-AMI. An S-AMI model was engineered in rats via CLP. Pathological alterations in the myocardial tissues of rats were monitored. qRT-PCR, ELISA, and western blot measured the profiles of miR-27b-3p, Peroxisomal proliferating-activated receptor gamma (PPARG), inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-8), and inflammatory response proteins (NF-κB-p65, MAPK-p38, JNK1/2). Besides, miR-27b-3p mimics were transfected into cardiomyocytes, and the proliferation and apoptosis of cardiomyocytes were examined through MTT and flow cytometry. As evidenced by the experimental outcomes, chrysophanol suppressed sepsis-mediated acute myocardial injury and LPS-mediated apoptosis in myocardial cells and lessened the release of pro-inflammatory cytokines and inflammatory response proteins. Moreover, chrysophanol cramped miR-27b-3p expression and heightened PPARG expression. miR-27b-3p targeted PPARG and restrained its expression. On the other hand, the PPARG agonist (RGZ) partially eliminated the apoptosis and pro-inflammatory responses of myocardial cells elicited by LPS. Therefore, this study revealed that Chrysophanol guarded against sepsis-mediated acute myocardial injury through dampening inflammation and apoptosis via the miR-27b-3p-PPARG axis, adding to the references for treating sepsis-AMI.

UBE2D1 and COX7C as Potential Biomarkers of Diabetes-Related Sepsis

Patients with diabetes are physiologically frail and more likely to suffer from infections and even life-threatening sepsis. This study aimed to identify and verify potential biomarkers of diabetes-related sepsis (DRS). Datasets GSE7014, GSE57065, and GSE95233 from the Gene Expression Omnibus were used to explore diabetes- and sepsis-related differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) and functional analyses were performed to explore potential functions and pathways associated with sepsis and diabetes. Weighted gene co-expression network analysis (WGCNA) was performed to identify diabetes- and sepsis-related modules. Functional enrichment analysis was performed to determine the characteristics and pathways of key modules. Intersecting DEGs that were also present in key modules were considered as common DEGs. Protein-protein interaction (PPI) network and key genes were analyzed to screen hub genes involved in DRS development. A mouse C57 BL/6J-DRS model and a neural network prediction model were constructed to verify the relationship between hub genes and DRS. In total, 7457 diabetes-related DEGs and 2606 sepsis-related DEGs were identified. GSEA indicated that gene datasets associated with diabetes and sepsis were mainly enriched in metabolic processes linked to inflammatory responses and reactive oxygen species, respectively. WGCNA indicated that grey60 and brown modules were diabetes- and sepsis-related key modules, respectively. Functional analysis showed that grey60 module genes were mainly enriched in cell morphogenesis, heart development, and the PI3K-Akt signaling pathway, whereas genes from the brown module were mainly enriched in organelle inner membrane, mitochondrion organization, and oxidative phosphorylation. UBE2D1, IDH1, DLD, ATP5C1, COX6C, and COX7C were identified as hub genes in the PPI network. Animal DRS and neural network prediction models indicated that the expression levels of UBE2D1 and COX7C in DRS models and samples were higher than control mice. UBE2D1 and COX7C were identified as potential biomarkers of DRS. These findings may help develop treatment strategies for DRS.

Role of hemoglobin alpha and hemoglobin beta in non-small-cell lung cancer based on bioinformatics analysis

The differentially expressed genes (DEGs) were identified and screened differentially in non-small-cell lung cancer (NSCLC) using information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases, and the correlation of DEGs in protein interaction, function, and pathway enrichment were analyzed to search for new biomarkers and potential therapeutic targets for NSCLC. Protein-protein interaction network (PPI) analysis showed that CDK1 and GNGT1 were the most significantly upregulated hub nodes, while FPR2 was the most significantly downregulated. Gene Ontology enrichment analysis showed that upregulated DEGs were significantly enriched in protein heterodimerization activity and other functions, while downregulated DEGs were enriched in functions such as heparin-binding. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that upregulation of DEGs were significantly associated with neuroactive ligand-receptor interaction pathways, while downregulation of DEGs were significantly associated with malaria pathways. According to the analysis results, we identified hemoglobin alpha (HBA) and hemoglobin beta (HBB) as the genes of interest for further study. Through tissue level and cell level experiments, we found that the expressions of HBA and HBB in NSCLC tissues were significantly lower than those in paracancerous tissues, and downregulation of HBA and HBB could significantly affect the proliferation ability of NSCLC cells. In addition, we also found that changes in HBA and HBB may affect NSCLC cells through the p38/MAPK pathway and JNK pathway, and ultimately affect the occurrence and development of NSCLC.

MiR-494-3p Upregulation Exacerbates Cerebral Ischemia Injury by Targeting Bhlhe40

PURPOSE

Cerebral ischemia is related to insufficient blood supply and is characterized by abnormal reactive oxygen species (ROS) production and cell apoptosis. Previous studies have revealed a key role for basic helix-loop-helix family member e40 (Bhlhe40) in oxidative stress and cell apoptosis. This study aimed to investigate the roles of miR-494-3p in cerebral ischemia/reperfusion (I/R) injury.

MATERIALS AND METHODS

A mouse middle cerebral artery occlusion (MCAO/R) model was established to mimic cerebral ischemia in vivo. Brain infarct area was assessed using triphenyl tetrazolium chloride staining. Oxygen-glucose deprivation/reoxygenation (OGD/R) operation was adopted to mimic neuronal injury in vitro. Cell apoptosis was analyzed by flow cytometry. The relationship between miR-494-3p and Bhlhe40 was validated by luciferase reporter and RNA immunoprecipitation assays.

RESULTS

Bhlhe40 expression was downregulated both in MCAO/R animal models and OGD/R-induced SH-SY5Y cells. Bhlhe40 overexpression inhibited cell apoptosis and reduced ROS production in SH-SY5Y cells after OGD/R treatment. MiR-494-3p was verified to bind to Bhlhe40 and negatively regulate Bhlhe40 expression. Additionally, cell apoptosis and ROS production in OGD/R-treated SH-SY5Y cells were accelerated by miR-494-3p overexpression. Rescue experiments suggested that Bhlhe40 could reverse the effects of miR-494-3p overexpression on ROS production and cell apoptosis.

CONCLUSION

MiR-494-3p exacerbates brain injury and neuronal injury by regulating Bhlhe40 after I/R.

Osteoarticular Involvement-Associated Biomarkers and Pathways in Psoriasis: The Shared Pathway With Ankylosing Spondylitis

Psoriatic arthritis (PsA) is a unique immune-mediated disease with cutaneous and osteoarticular involvement. However, only a few studies have explored the susceptibility of osteoarticular involvement in psoriasis (Ps) at the genetic level. This study investigated the biomarkers associated with osteoarticular participation and potential shared molecular mechanisms for PsA and ankylosing spondylitis (AS).

Effect of PITX2 genetic variants on the susceptibility to stroke in the Chinese Han population

PURPOSE

Stroke is a multifactorial and complex disease caused by the obstruction or rupture of cerebrovascular. To explore the influence of genetic factors on stroke susceptibility, we investigated the association between four single nucleotide polymorphisms (SNPs) in the paired-like homeodomain transcription factor 2 (PITX2) gene and stroke risk.

METHODS

A total of 977 volunteers including 476 stroke patients and 501 control individuals were recruited. The association between PITX2 polymorphisms and stroke risk was evaluated using genetic models and haplotype analyses. The strength of the association between each studied polymorphisms and stroke risk was evaluated by calculating odds ratios (ORs) and 95% confidence intervals (CIs). What's more, multifactor dimensionality reduction (MDR) was used to predict the interaction between SNPs.

RESULTS

Our study showed that rs6817105 in PITX2 was related to a significant increase in stroke susceptibility (OR = 1.42, 95% CI = 1.04-1.94, p = 0.028). Stratified analyses based on gender indicated that rs6817105, rs13143308, and rs6843082 polymorphisms were significantly associated with an increased risk of stroke in male (OR = 0.68, 95% CI = 0.47-0.99, p = 0.042; OR = 0.53, 95% CI = 0.30-0.96, p = 0.035; and OR = 0.55, 95% CI = 0.30-0.99, p = 0.047). Besides, SNP rs6817105 was significantly increased the risk of stroke in people at age over 65 years (OR = 1.87, 95% CI =1.12-3.11, p = 0.016). MDR showed that the interaction model of rs6817105 and rs3853445 emerged as the best predictor between the PITX2 gene and stroke susceptibility.

CONCLUSIONS

This study indicated that there was a significant association between the PITX2 gene and stroke risk, and provided some data as far as possible to support the prevention of stroke.

Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia in the world. Long noncoding RNA (lncRNA) has been found to play an important role in cardiovascular diseases including heart failure, myocardial infarction, and atherosclerosis. However, the role of lncRNA in AF has rarely been studied. The purpose of this study is to identify the expression profile of lncRNA in AF patients, explore the function of lncRNA in AF, and provide a potential scientific basis for the treatment of AF in the future.

METHODS

The lncRNA and mRNA expression profiles were obtained from the atrial appendage samples of GSE31821, GSE411774, GSE79768, and GSE115574 in the Gene Expression Omnibus (GEO) database. Functional analysis was performed via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). The "CIBERSORT" R kit was used to analyze 22 immune cell infiltrates in AF and sinus rhythm (SR) patients. The "CORRPLOT" R package was used to analyze the immune correlation between lncRNA and immune cells.

RESULTS

A total of 6 differentially expressed lncRNAs and 45 differentially expressed mRNAs were identified in the AF and SR groups. GO, KEGG, and GSVA results showed that abnormally expressed lncRNAs were involved in signaling pathways related to the atrium, including the Toll-like receptor signaling pathway and calcium signaling pathway. Immune cell infiltration analysis revealed that native B cells, follicular helper T cells, and resting dendritic cells may be involved in the AF process. In addition, LINC00844 was negatively correlated with resting dendritic cells.

CONCLUSION

The expression profile of lncRNA in AF patients was different from that in normal controls. The physiological functions of these differentially expressed lncRNAs may be related to the pathogenesis of AF, which provide a scientific basis for the prognosis and treatment of patients with AF.

Genome-Wide Association Study of the Relationship Between Matrix Metalloproteinases and Intracranial Aneurysms

Background and Purpose

Matrix metalloproteinases (MMPs) are expected to play an important role in extracellular matrix (ECM) remodeling in response to hemodynamic stress. We investigated the association between MMPs and intracranial aneurysms (IAs) via a genome-wide association study (GWAS) of IAs.

Methods

A GWAS data set of 250 IAs and 294 controls was used to analyze the genetic link between MMPs and IAs via single-nucleotide polymorphisms (SNPs), MMP gene families, and in silico functional analyses of gene ontology (GO) enrichment and protein–protein interaction (PPI).

Results

Forty-eight SNPs and 1 indel out of 342 markers of MMP genes were related to IAs. The rs2425024 SNP located on MMP24 was the most strongly associated with IAs (OR=0.43, CI=0.30–0.61, p=2.4×10^-6), suggesting a protective effect. The 16938619 SNP of MMP26 significantly increased the risk of an IA (OR=3.12, 95% CI=1.76–5.50, p=8.85×10^-5). Five MMP genes (MMP24, MMP13, MMP2, MMP17, and MMP1) increased the susceptibility to an IA. MMP24 was the gene most closely related to IAs (p=7.96×10^-7). GO analysis showed that collagen catabolism was the most-enhanced biological process. Further, metalloendopeptidase activity and ECM were predominantly detected in the cellular component and molecular function, respectively. PPI provided evidence that MMP2, TIMP2 (tissue inhibitor of metalloproteinase 2), and TIMP3 genes constitute a network for predicting IA formation.

Conclusions

The present results provide comprehensive insight into the occurrence of IAs associated with MMPs.

Ischemic Stroke Genetics: What Is New and How to Apply It in Clinical Practice?

The etiology of ischemic stroke is multifactorial. Although receiving less emphasis, genetic causes make a significant contribution to ischemic stroke genesis, especially in early-onset stroke. Several stroke classification systems based on genetic information corresponding to various stroke phenotypes were proposed. Twin and family history studies, as well as candidate gene approach, are common methods to discover genetic causes of stroke, however, both have their own limitations. Genome-wide association studies and next generation sequencing are more efficient, promising and increasingly used for daily diagnostics. Some monogenic disorders, despite covering only about 7% of stroke etiology, may cause well-known clinical manifestations that include stroke. Polygenic disorders are more frequent, causing about 38% of all ischemic strokes, and their identification is a rapidly developing field of modern stroke genetics. Current advances in human genetics provide opportunity for personalized prevention of stroke and novel treatment possibilities. Genetic risk scores (GRS) and extended polygenic risk scores (PRS) estimate cumulative contribution of known genetic factors to a specific outcome of stroke. Combining those scores with clinical information and risk factor profiles might result in better primary stroke prevention. Some authors encourage the use of stroke gene panels for stroke risk evaluation and further stroke research. Moreover, new biomarkers for stroke genetic causes and novel targets for gene therapy are on the horizon. In this article, we summarize the latest evidence and perspectives of ischemic stroke genetics that could be of interest to the practitioner and useful for day-to-day clinical work.

Bioinformatics Analysis of Autophagy and Mitophagy Markers Associated with Delayed Cerebral Ischemia Following Subarachnoid Hemorrhage

Objective

To evaluate the interactions among differentially expressed autophagy and mitophagy markers in subarachnoid hemorrhage (SAH) patients with delayed cerebral ischemia (DCI).

Methods

The expression data of autophagy and mitophagy-related makers in the cerebrospinal fluid (CSF) cells was analyzed by real-time reverse transcription-polymerase chain reaction and Western blotting. The markers included death-associated protein kinase (DAPK)-1, BCL2 interacting protein 3 like (BNIP3L), Bcl-1 antagonist X, PINK, Unc-51 like autophagy activating kinase 1, nuclear dot protein 52, and p62. In silico functional analyses including gene ontology enrichment and the protein-protein interaction network were performed.

Results

A total of 56 SAH patients were included and 22 (38.6%) of them experienced DCI. The DCI patients had significantly increased mRNA levels of DAPK1, BNIP3L, and PINK1, and increased expression of BECN1 compared to the non-DCI patients. The most enriched biological process was the positive regulation of autophagy, followed by the response to mitochondrial depolarization. The molecular functions ubiquitin-like protein ligase binding and ubiquitin-protein ligase binding were enriched. In the cluster of cellular components, Lewy bodies and the phagophore assembly site were enriched. BECN1 was the most connected gene among the differentially expressed markers related to autophagy and mitophagy in the development of DCI.

Conclusion

Our study may provide novel insight into mitochondrial dysfunction in DCI pathogenesis.

Long non-coding RNA SNHG7 upregulates FGF9 to alleviate oxygen and glucose deprivation-induced neuron cell injury in a miR-134-5p-dependent manner

Long non-coding RNA small nucleolar RNA host gene 7 (SNHG7) was reported to regulate the pathogenesis of ischemic stroke. The study aimed to disclose SNHG7 role in oxygen and glucose deprivation (OGD)-induced Neuro-2a (N2a) cell disorders. An OGD injury cell model was established using N2a cells. The expression of SNHG7, microRNA-134-5p (miR-134-5p) and fibroblast growth factor 9 (FGF9) was determined by quantitative real-time polymerase chain reaction. Protein expression was detected by western blot. Cell viability and Lactate Dehydrogenase (LDH) leakage were determined by cell counting kit-8 and LDH activity detection assays. Oxidative stress was investigated by Superoxide Dismutase and Catalase activity assays as well as Malondialdehyde and Reactive Oxygen Species detection kits. Cell apoptosis and caspase-3 activity were severally demonstrated by flow cytometry and caspase-3 activity assays. The interaction between miR-134-5p and SNHG7 or FGF9 was predicted by online databases, and identified by mechanism assays. OGD treatment decreased SNHG7 and FGF9 expression, but increased miR-134-5p expression. OGD treatment repressed cell viability, promoted LDH leakage and induced oxidative stress and apoptosis in N2a cells, which was rescued by SNHG7 overexpression. SNHG7 acted as a sponge for miR-134-5p, and regulated OGD-triggered cell damage by associating with miR-134-5p. Additionally, miR-134-5p depletion protected N2a cells from OGD-induced injury by targeting FGF9. Ectopic SNHG7 expression protected against OGD-induced neuronal cell injury by inducing FGF9 through sponging miR-134-5p, providing a novel therapeutic target for ischemic stroke.

Bioinformatics Identification of Ferroptosis-Related Biomarkers and Therapeutic Compounds in Ischemic Stroke

Background: Stroke is one of the most common deadly diseases with an estimated 780,000 new cases globally, of which ischemic stroke accounts for over 80% of all cases. Ferroptosis is a new form of programmed cell death that plays a vital role in many diseases, including ischemic stroke and heart diseases. The role of the ferroptosis-related gene in the diagnosis, prognosis, or therapy of ischemic stroke was not fully clarified.

Methods: Ferroptosis-related differentially expressed genes (DEGs) in ischemic stroke were identified by bioinformatic analysis of the GSE16561 and GSE22255 datasets. Subsequently, receiver operator characteristic (ROC) monofactor analysis was performed to evaluate the diagnostic value of ferroptosis-related biomarkers in ischemic stroke.

Results: A total of 10 ferroptosis-related DEGs were identified in ischemic stroke vs. normal control. GO and KEGG analysis revealed that these 10 ferroptosis-related DEGs were mainly enriched in response to oxidative stress, HIF-1 signaling pathway, ferroptosis, lipid, and atherosclerosis. Moreover, the random forest model suggested three ferroptosis-related biomarkers, namely, PTGS2, MAP1LC3B, and TLR4, for ischemic stroke. Interestingly, the expression of PTGS2, MAP1LC3B, and TLR4 was upregulated in ischemic stroke. ROC monofactor analysis demonstrated a good performance of MAP1LC3B, PTGS2, and TLR4 in the diagnosis of ischemic stroke. The expression and diagnostic value of MAP1LC3B, PTGS2, and TLR4 in ischemic stroke were also verified using GSE22255. We also revealed the transcription factor regulation network and co-expressed protein network of ferroptosis-related biomarkers. Several potential therapeutic compounds corresponding to MAP1LC3B, PTGS2, and TLR4 were also identified for ischemic stroke, including Zinc12503187 (Conivaptan), Zinc3932831 (Avodart), Zinc64033452 (Lumacaftor), Zinc11679756 (Eltrombopag), Zinc100378061 (Naldemedine), and Zinc3978005 (Dihydroergotamine).

Conclusion: Our results suggested MAP1LC3B, PTGS2, and TLR4 as potential diagnostic biomarkers for ischemic stroke, providing more evidence about the vital role of ferroptosis in ischemic stroke.

Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data

Artificial intelligence in healthcare can potentially identify the probability of contracting a particular disease more accurately. There are five common molecular subtypes of breast cancer: luminal A, luminal B, basal, ERBB2, and normal-like. Previous investigations showed that pathway-based microarray analysis could help in the identification of prognostic markers from gene expressions. For example, directed random walk (DRW) can infer a greater reproducibility power of the pathway activity between two classes of samples with a higher classification accuracy. However, most of the existing methods (including DRW) ignored the characteristics of different cancer subtypes and considered all of the pathways to contribute equally to the analysis. Therefore, an enhanced DRW (eDRW+) is proposed to identify breast cancer prognostic markers from multiclass expression data. An improved weight strategy using one-way ANOVA (F-test) and pathway selection based on the greatest reproducibility power is proposed in eDRW+. The experimental results show that the eDRW+ exceeds other methods in terms of AUC. Besides this, the eDRW+ identifies 294 gene markers and 45 pathway markers from the breast cancer datasets with better AUC. Therefore, the prognostic markers (pathway markers and gene markers) can identify drug targets and look for cancer subtypes with clinically distinct outcomes.

Bioinformatic analysis for potential biological processes and key targets of heart failure-related stroke

This study aimed to uncover underlying mechanisms and promising intervention targets of heart failure (HF)-related stroke. HF-related dataset GSE42955 and stroke-related dataset GSE58294 were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was conducted to identify key modules and hub genes. Gene Ontology (GO) and pathway enrichment analyses were performed on genes in the key modules. Genes in HF- and stroke-related key modules were intersected to obtain common genes for HF-related stroke, which were further intersected with hub genes of stroke-related key modules to obtain key genes in HF-related stroke. Key genes were functionally annotated through GO in the Reactome and Cytoscape databases. Finally, key genes were validated in these two datasets and other datasets. HF- and stroke-related datasets each identified two key modules. Functional enrichment analysis indicated that protein ubiquitination, Wnt signaling, and exosomes were involved in both HF- and stroke-related key modules. Additionally, ten hub genes were identified in stroke-related key modules and 155 genes were identified as common genes in HF-related stroke. OTU deubiquitinase with linear linkage specificity(OTULIN) and nuclear factor interleukin 3-regulated(NFIL3) were determined to be the key genes in HF-related stroke. Through functional annotation, OTULIN was involved in protein ubiquitination and Wnt signaling, and NFIL3 was involved in DNA binding and transcription. Importantly, OTULIN and NFIL3 were also validated to be differentially expressed in all HF and stroke groups. Protein ubiquitination, Wnt signaling, and exosomes were involved in HF-related stroke. OTULIN and NFIL3 may play a key role in HF-related stroke through regulating these processes, and thus serve as promising intervention targets.

CXCL12/CXCR4 axis as a key mediator in atrial fibrillation via bioinformatics analysis and functional identification

Atrial fibrillation (AF) is an increasingly prevalent arrhythmia with significant health and socioeconomic impact. The underlying mechanism of AF is still not well understood. In this study, we sought to identify hub genes involved in AF, and explored their functions and underlying mechanisms based on bioinformatics analysis. Five microarray datasets in GEO were used to identify the differentially expressed genes (DEGs) by Robust Rank Aggregation (RRA), and hub genes were screened out using protein-protein interaction (PPI) network. AF model was established using a mixture of acetylcholine and calcium chloride (Ach-CaCl2) by tail vein injection. We totally got 35 robust DEGs that mainly involve in extracellular matrix formation, leukocyte transendothelial migration, and chemokine signaling pathway. Among these DEGs, we identified three hub genes involved in AF, of which CXCL12/CXCR4 axis significantly upregulated in AF patients stands out as one of the most potent targets for AF prevention, and its effect on AF pathogenesis and underlying mechanisms were investigated in vivo subsequently with the specific CXCR4 antagonist AMD3100 (6 mg/kg). Our results demonstrated an elevated transcription and translation of CXCL12/CXCR4 axis in AF patients and mice, accompanied with the anabatic atrial inflammation and fibrosis, thereby providing the substrate for AF maintenance. Blocking its signaling via AMD3100 administration in AF model mice reduced AF inducibility and duration, partly ascribed to decreased atrial inflammation and structural remodeling. Mechanistically, these effects were achieved by reducing the recruitment of CD3+ T lymphocytes and F4/80+ macrophages, and suppressing the hyperactivation of ERK1/2 and AKT/mTOR signaling in atria of AF model mice. In conclusion, this study provides new evidence that antagonizing CXCR4 prevents the development of AF, and suggests that CXCL12/CXCR4 axis may be a potential therapeutic target for AF.

Single-Nucleotide Polymorphisms in the 3' Untranslated Region of CORIN Associated With Cardiovascular Diseases in a Chinese Han Population: A Case-Control Study

Background: Corin is a transmembrane serine protease that activates pro-forms of atrial and brain natriuretic peptides. Numerous studies have indicated that corin played an important role in cardiovascular diseases (CVDs). However, there have been few studies about the correlation between single-nucleotide polymorphisms (SNPs) in the 3' untranslated region (3'UTR) of CORIN and CVDs. The aims of this study were to investigate the associations of three SNPs (rs3749585, rs4695253, and rs12641823) in the 3'UTR of CORIN with CVDs and to find the seed regions of microRNAs (miRNAs) that bind to SNPs of CORIN.

Methods and Results: A case–control study (n = 3,537) was performed in a Han population of northeastern China. CVDs included essential hypertension (EH), atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD). Genotyping was performed using high-resolution melt analysis. In the EH-control study, rs3749585^T was significantly associated with the risk of EH after adjusting for sex and age in allelic (p_adj = 0.049; OR: 1.113) and dominant (p_adj = 0.015, OR: 1.233) models. Rs4695253^T was significantly associated with the risk of EH in the recessive model after adjusting for sex and age (p_adj = 0.005, OR: 2.084). Rs3749585^T was significantly and negatively associated with AF in the dominant and additive models after adjusting for sex, age, EH, HF, T2DM, and CAD (dominant: p_adj = 0.009, OR: 0.762; additive: p_adj = 0.048, OR: 0.873). In the HF-control study and CAD-control study, none of the three SNPs was associated with HF and CAD after adjusting for covariates in any models (p_adj > 0.05). The levels of high-density lipoprotein (HDL) in rs4695253^CC+CT were lower than the levels of HDL in rs4695253^TT (42.47 ± 10.30 vs. 48.0 ± 10.24 mg/dl, p_adj = 0.008). The levels of total cholesterol (TC) in rs4695253^CC+CT were lower than the levels of TC in rs4695253^TT (164.01 ± 49.15 vs. 180.81 ± 43.92 mg/dl, p_adj = 0.036). Luciferase assay revealed that the relative luciferase activity of rs3749585^CC-transfected cells was significantly decreased by miR-494-3p, in comparison to cells transfected with rs3749585^TT (p < 0.001). A significant decrease in the relative luciferase activity of rs3749585^TT reporter was observed as compared with rs3749585^CC reporter in the presence of miR-1323 or miR-548o-3p (p = 0.017 and 0.012, respectively).

Conclusions: We found significant associations between rs3749585^T and rs4695253^T and EH, between rs4695253^T and the levels of TC and HDL, and between rs3749585^T and AF. Hsa-miR-494-3p may serve as a potential therapeutic target for EH and AF patients in the future.

Exploration of the Shared Gene Signatures and Molecular Mechanisms Between Systemic Lupus Erythematosus and Pulmonary Arterial Hypertension: Evidence From Transcriptome Data

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease that can affect multiple systems. Pulmonary arterial hypertension (PAH) has a close linkage with SLE. However, the inter-relational mechanisms between them are still unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in SLE and PAH.

Methods

The microarray data of SLE and PAH in the Gene Expression Omnibus (GEO) database were downloaded. The Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify the co-expression modules related to SLE and PAH. The shared genes existing in the SLE and PAH were performed an enrichment analysis by ClueGO software, and their unique genes were also performed with biological processes analyses using the DAVID website. The results were validated in another cohort by differential gene analysis. Moreover, the common microRNAs (miRNAs) in SLE and PAH were obtained from the Human microRNA Disease Database (HMDD) and the target genes of whom were predicted through the miRTarbase. Finally, we constructed the common miRNAs–mRNAs network with the overlapped genes in target and shared genes.

Results

Using WGCNA, four modules and one module were identified as the significant modules with SLE and PAH, respectively. A ClueGO enrichment analysis of shared genes reported that highly activated type I IFN response was a common feature in the pathophysiology of SLE and PAH. The results of differential analysis in another cohort were extremely similar to them. We also proposed a disease road model for the possible mechanism of PAH secondary to SLE according to the shared and unique gene signatures in SLE and PAH. The miRNA–mRNA network showed that hsa-miR-146a might regulate the shared IFN-induced genes, which might play an important role in PAH secondary to SLE.

Conclusion

Our work firstly revealed the high IFN response in SLE patients might be a crucial susceptible factor for PAH and identified novel gene candidates that could be used as biomarkers or potential therapeutic targets.

A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and results in a significantly increased ischemic stroke (IS) risk. IS risk stratification tools are widely being applied to guide anticoagulation treatment decisions and duration in patients with non-valvular AF (NVAF). The CHA₂DS₂-VASc score is largely validated and currently recommended by renowned guidelines. However, this score is heavily dependent on age, sex, and comorbidities, and exhibits only moderate predictive power. Finding effective and validated clinical biomarkers to assist in personalized IS risk evaluation has become one of the promising directions in the prevention and treatment of NVAF. A number of studies in recent years have explored differentially expressed biomarkers in NVAF patients with and without IS, and the potential role of various biomarkers for prediction or early diagnosis of IS in patients with NVAF. In this review, we describe the clinical application and utility of AF characteristics, cardiac imaging and electrocardiogram markers, arterial stiffness and atherosclerosis-related markers, circulating biomarkers, and novel genetic markers in IS diagnosis and management of patients with NVAF. We conclude that at present, there is no consensus understanding of a desirable biomarker for IS risk stratification in NVAF, and enrolling these biomarkers into extant models also remains challenging. Further prospective cohorts and trials are needed to integrate various clinical risk factors and biomarkers to optimize IS prediction in patients with NVAF. However, we believe that the growing insight into molecular mechanisms and in-depth understanding of existing and emerging biomarkers may further improve the IS risk identification and guide anticoagulation therapy in patients with NVAF.

MiR-494-3p alleviates acute lung injury through regulating NLRP3 activation by targeting CMPK2

Acute lung injury (ALI) is a severe respiratory disorder with a high rate of mortality, and is characterized by excessive cell apoptosis and inflammation. MicroRNAs (miRNAs) play pivotal roles in ALI. This study examined the biological function of miR-494-3p in cell apoptosis and inflammatory response in ALI. For this, mice were injected with lipopolysaccharide (LPS) to generate an in-vivo model of ALI (ALI mice), and WI-38 cells were stimulated with lipopolysaccharide (LPS) to generate an in-vitro model of ALI. We found that miR-494-3p was significantly downregulated in the ALI mice and in the in-vitro model. Overexpression of miR-494-3p inhibited inflammation and cell apoptosis in the LPS-induced WI-38 cells, and improved the symptoms of lung injury in the ALI mice. We then identified cytidine/uridine monophosphate kinase 2 (CMPK2) as a novel target of miR-494-3p in the WI-38 cells. Furthermore, miR-494-3p suppressed cell apoptosis and the inflammatory response in LPS-treated WI-38 cells through targeting CMPK2. The NLRP3 inflammasome is reportedly responsible for the activation of inflammatory processes. In our study, CMPK2 was confirmed to activate the NLRP3 inflammasome in LPS-treated WI-38 cells. In conclusion, miR-494-3p attenuates ALI through inhibiting cell apoptosis and the inflammatory response by targeting CMPK2, which suggests the value of miR-494-3p as a target for the treatment for ALI.

Construction of mRNA Regulatory Networks Reveals the Key Genes in Atrial Fibrillation

Atrial fibrillation (AF), the most familiar heart rhythm disorder, is a major cause of stroke in the world, whereas the mechanism behind AF remains largely unclear. In the current study, we used the RNA-seq method to identify 275 positively regulated mRNAs and 117 negatively regulated mRNAs in AF compared to healthy controls. Through bioinformatic analysis, it indicated that these distinctively expressed genes took part in regulating multiple AF-related biological processes and pathways, such as platelet aggregation, platelet activation, pri-miRNA transcription, and transforming growth factor-beta (TGF-β) receptor signaling pathway. Protein-protein interaction (PPI) network analysis identified ITGB5, SRC, ACTG1, ILK, ITGA2B, ITGB3, TUBB4B, CDK11A, PAFAH1B1, CDK11B, and TUBG1 as hub regulators in AF. Moreover, the quantitative real-time PCR (qRT-PCR) assay was conducted and revealed that these hub genes were remarkably overexpressed in AF samples compared to normal samples. We believed that this study would enrich the understanding of the pathogenesis of AF and enable further research on the pathogenesis of AF.

Predicting the Key Genes Involved in Aortic Valve Calcification Through Integrated Bioinformatics Analysis

Background: Valvular heart disease is obtaining growing attention in the cardiovascular field and it is believed that calcific aortic valve disease (CAVD) is the most common valvular heart disease (VHD) in the world. CAVD does not have a fully effective treatment to delay its progression and the specific molecular mechanism of aortic valve calcification remains unclear.

Materials and Methods: We obtained the gene expression datasets GSE12644 and GSE51472 from the public comprehensive free database GEO. Then, a series of bioinformatics methods, such as GO and KEGG analysis, STING online tool, Cytoscape software, were used to identify differentially expressed genes in CAVD and healthy controls, construct a PPI network, and then identify key genes. In addition, immune infiltration analysis was used via CIBERSORT to observe the expression of various immune cells in CAVD.

Results: A total of 144 differential expression genes were identified in the CAVD samples in comparison with the control samples, including 49 up-regulated genes and 95 down-regulated genes. GO analysis of DEGs were most observably enriched in the immune response, signal transduction, inflammatory response, proteolysis, innate immune response, and apoptotic process. The KEGG analysis revealed that the enrichment of DEGs in CAVD were remarkably observed in the chemokine signaling pathway, cytokine-cytokine receptor interaction, and PI3K-Akt signaling pathway. Chemokines CXCL13, CCL19, CCL8, CXCL8, CXCL16, MMP9, CCL18, CXCL5, VCAM1, and PPBP were identified as the hub genes of CAVD. It was macrophages that accounted for the maximal proportion among these immune cells. The expression of macrophages M0, B cells memory, and Plasma cells were higher in the CAVD valves than in healthy valves, however, the expression of B cells naïve, NK cells activated, and macrophages M2 were lower.

Conclusion: We detected that chemokines CXCL13, CXCL8, CXCL16, and CXCL5, and CCL19, CCL8, and CCL18 are the most important markers of aortic valve disease. The regulatory macrophages M0, plasma cells, B cells memory, B cells naïve, NK cells activated, and macrophages M2 are probably related to the occurrence and the advancement of aortic valve stenosis. These identified chemokines and these immune cells may interact with a subtle adjustment relationship in the development of calcification in CAVD.

Roles of Fibroblast Growth Factors and Their Therapeutic Potential in Treatment of Ischemic Stroke

Stroke is the leading cause of death worldwide, and its treatment remains a challenge. Complex pathological processes are involved in stroke, which causes a reduction in the supply of oxygen and energy to the brain that triggers subsequent cascade events, such as oxidative stress, inflammatory responses and apoptosis, resulting in brain injury. Stroke is a devastating disease for which there are few treatments, but physical rehabilitation can help improve stroke recovery. Although there are very few treatments for stroke patients, the discovery of fibroblast growth factors (FGFs) in mammals has led to the finding that FGFs can effectively treat stroke in animal models. As presented in this review, FGFs play essential roles by functioning as homeostatic factors and controlling cells and hormones involved in metabolism. They could be used as effective therapeutic agents for stroke. In this review, we will discuss the pharmacological actions of FGFs on multiple targets, including their ability to directly promote neuron survival, enhance angiogenesis, protect against blood-brain barrier (BBB) disruption, and regulate microglial modulation, in the treatment of ischemic stroke and their theoretical mechanisms and actions, as well as the therapeutic potential and limitations of FGFs for the clinical treatment of stroke.

Identification and analysis of key genes associated with acute myocardial infarction by integrated bioinformatics methods

BACKGROUND

Acute myocardial infarction (AMI) is a common disease leading threat to human health around the world. Here we aimed to explore new biomarkers and potential therapeutic targets in AMI through adopting integrated bioinformatics tools.

METHODS

The gene expression Omnibus (GEO) database was used to obtain genes data of AMI and no-AMI whole blood. Furthermore, differentially expressed genes (DEGs) were screened using the "Limma" package in R 3.6.1 software. Functional and pathway enrichment analyses of DEGs were performed via "Bioconductor" and "GOplot" package in R 3.6.1 software. In order to screen hub DEGs, the STRING version 11.0 database, Cytoscape and molecular complex detection (MCODE) were applied. Correlation among the hub DEGs was evaluated using Pearson's correlation analysis.

RESULTS

By performing DEGs analysis, 289 upregulated and 62 downregulated DEGs were successfully identified from GSE66360, respectively. And they were mainly enriched in the terms of neutrophil activation, immune response, cytokine, nuclear factor kappa-B (NF-κB) signaling pathway, IL-17 signaling pathway, and tumor necrosis factor (TNF) signaling pathway. Based on the data of protein-protein interaction (PPI), the top 10 hub genes were ranked, including interleukin-8 (CXCL8), TNF, N-formyl peptide receptor 2 (FPR2), growth-regulated alpha protein (CXCL1), transcription factor AP-1 (JUN), interleukin-1 beta (IL1B), platelet basic protein (PPBP), matrix metalloproteinase-9 (MMP9), toll-like receptor 2 (TLR2), and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G). What's more, the results of correlation analysis demonstrated that there was positive correlation between the 10 hub DEGs.

CONCLUSION

Ten DEGs were identified as potential candidate diagnostic biomarkers for patients with AMI in present study. However, further experiments are needed to confirm the functional pathways and hub genes associated with AMI.

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

Background

Sphingolipid metabolism is among the top dysregulated pathways in non-small cell lung carcinomas (NSCLC). However, the molecular control of sphingolipid metabolic reprogramming in cancer progression remains unclear.

Methods

We first determined the correlation between sphingolipid metabolic gene expression and patient prognosis. We then carried out sphingolipidomics analysis of health individual and NSCLC patient sera as well as B3GNT5 and GAL3ST1 genetically perturbed NSCLC cell lines. We used these cell lines to perform tumorigenesis study to determine the cellular role of B3GNT5 and GAL3ST1 in cancer growth and progression.

Findings

The expression of B3GNT5 and GAL3ST1 among sphingolipid metabolic enzymes is most significantly associated with patient prognosis, whilst sphingolipidomics analysis of healthy individual and NSCLC patient sera identifies their metabolites, lacto/neolacto-series glycosphingolipid and sulfatide species, as potential biomarkers that were more effective than current clinical biomarkers for staging patients. Further network analysis of the sphingolipidomes reveals a circular network of coregulated sphingolipids, indicating that the lacto/neolacto-series glycosphingolipid/sulfatide balance functions as a checkpoint to determine sphingolipid metabolic reprograming during patient progression. Sphingolipidomics analysis of B3GNT5/GAL3ST1 genetically perturbed NSCLC cell lines confirms their key regulatory role in sphingolipid metabolism, while B3GNT5 and GAL3ST1 expression has an opposite role on tumorigenesis.

Interpretation

Our results provide new insights whereby B3GNT5 and GAL3ST1 differentially regulate sphingolipid metabolism in lung cancer growth and progression.

Funding

This work was supported by the Natural Science Foundation of China (81872142, 81920108028); Guangzhou Science and Technology Program (201904020008); Guangdong Science and Technology Department (2020A0505100029, 2019A1515011802, 2020A1515011280, 2020B1212060018, 2020B1212030004); China Postdoctoral Science Foundation (2019M650226, 2019M650227).

A 3' Untranslated Region Polymorphism of CTNNB1 (Rs2953) Alters MiR-3161 Binding and Affects the Risk of Ischemic Stroke and Coronary Artery Disease in Chinese Han Population

BACKGROUND

CTNNB1 is reported to be related to the pathological process of ischemic stroke (IS) and coronary artery disease (CAD). Polymorphism located in the 3' untranslated region (3'UTR) of a gene might affect gene expression by modifying binding sites for microRNAs (miRNAs). This study aimed to analyze the association between polymorphism rs2953, which locates in the 3'UTR of CTNNB1, and the risk of IS and CAD.

METHODS

The CTNNB1 messenger RNA (mRNA) expression level in peripheral venous blood was measured. In total, 533 patients with IS, 500 patients with CAD, and 531 healthy individuals were genotyped by Sequenom Mass-Array technology. The binding of miR-3161 to CTNNB1 was determined by dual-luciferase reporter assay.

RESULTS

The CTNNB1 mRNA expression level for the IS group was significantly lower than that for the control group. Rs2953 was significantly associated with both IS risk and CAD risk. Significant association was also found between polymorphism rs2953 and many conventional factors, such as serum lipid level, blood coagulation markers, blood glucose level, and homocysteine level in patients. Rs2953 T allele introduced a binding site to miRNA-3161 and thus decreased luciferase activity.

CONCLUSION

Polymorphism rs2953 is associated with the risk of both IS and CAD. Moreover, polymorphism rs2953 (T) introduces a binding site to miRNA-3161 and thus decreases luciferase activity in cell lines.