Analysis of neutrophil extracellular trap-related genes in Crohn's disease based on bioinformatics.

Crohn's disease (CD) presents with diverse clinical phenotypes due to persistent inflammation of the gastrointestinal tract. Its global incidence is on the rise. Neutrophil extracellular traps (NETs) are networks released by neutrophils that capture microbicidal proteins and oxidases targeting pathogens. Research has shown that NETs are implicated in the pathogenesis of several immune-mediated diseases such as rheumatoid arthritis, systemic lupus erythematosus and inflammatory bowel disease. The goal of this study was to identify a panel of NET-related genes to construct a diagnostic and therapeutic model for CD. Through analysis of the GEO database, we identified 1950 differentially expressed genes (DEGs) associated with CD. Gene enrichment and immune cell infiltration analyses indicate that neutrophil infiltrates and chemokine-related pathways are predominantly involved in CD, with other immune cells such as CD4 and M1 macrophages also playing a role in disease progression. Utilizing weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) networks, we identified six hub genes (SPP1, SOCS3, TIMP1, IRF1, CXCL2 and CD274). To validate the accuracy of our model, we performed external validation with statistical differences(p < 0.05). Additionally, immunohistochemical experiments demonstrated higher protein expression of the hub genes in colonic tissues from CD patients compared to healthy subjects (p < 0.05). In summary, we identified six effective hub genes associated with NETs as potential diagnostic markers for CD. These markers not only offer targets for future research but also hold promise for the development of novel therapeutic interventions for CD.

The expression of RBPJ and its potential role in rheumatoid arthritis.

BACKGROUND: Recombination signal-binding protein for immunoglobulin kappa J region (RBPJ) is a transcriptional regulator that plays an important role in maintaining immune homeostasis. This study aimed to estimate the expression of RBPJ in rheumatoid arthritis (RA) patients and investigate its relationship with RA. METHODS: A total of 83 newly diagnosed RA patients and 70 healthy controls were included. mRNA was extracted from peripheral blood mononuclear cells (PBMCs), and the expression of RBPJ was detected using quantitative real-time PCR (qRT‒PCR). An RA dataset (GSE89408) was obtained from the Gene Expression Omnibus (GEO) database, and RA synovial tissues were divided into two groups. The differentially expressed genes (DEGs) were selected with the "DESeq2" R package. RESULTS: RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR). RA synovial tissues from GSE89408 were classified into RBPJ-low (≤ 25%) and RBPJ-high (≥ 75%) groups according to RBPJ expression, and 562 DEGs were identified. Gene Ontology (GO) enrichment analyses revealed that the DEGs significantly affected the regulation of T cell activation and lymphocyte/mononuclear cell differentiation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the most enriched pathways of DEGs were the T cell receptor signaling pathway, Th1/2 and Th17 cell differentiation, the PI3K - Akt signaling pathway and cytokine‒cytokine receptor interaction. CytoHubba Plugin revealed that most of the top 10 genes were involved in osteoclast differentiation, the T cell receptor signaling pathway and cytokine‒cytokine receptor interaction. CONCLUSIONS: RBPJ expression was significantly lower in RA patients and negatively correlated with disease activity. GEO dataset analysis demonstrated that RBPJ may be involved in osteoclast differentiation, T cell activation and differentiation, and the T cell receptor signaling pathway. Our research may contribute to understanding the potential mechanisms by which RBPJ regulates T cell differentiation and cytokine‒cytokine receptor interaction in RA patients.

Involvement of CD44 and MAPK14-mediated ferroptosis in hemorrhagic shock.

To elucidate the induction of ferroptotic pathways and the transcriptional modulation of pivotal genes in the context of hemorrhagic shock. The R software was used to analyze the GSE64711 dataset, isolating genes relevant to ferroptosis. Enrichment analyses and protein interaction networks were assembled. Using WGCNA hub genes were identified and intersected with ferroptosis-related genes, highlighting hub genes CD44 and MAPK14. In a rat hemorrhagic shock model, cardiac ROS, Fe2+, MDA, and GSH levels were assessed. Key ferroptotic proteins (SLC7A11/GPX4) in myocardial tissues were examined via western blot. Hub genes, CD44 and MAPK14, expressions were confirmed through immunohistochemistry. Analyzing the GSE64711 dataset revealed 337 differentially expressed genes, including 12 linked to ferroptosis. Enrichment analysis highlighted pathways closely related to ferroptosis. Using Genemania, we found these genes mainly affect ROS metabolism and oxidative stress response. WGCNA identified CD44 and MAPK14 as hub genes. Rat myocardial tissue validation showed significant cardiac damage and elevated ROS and MDA levels, and decreased GSH levels in the hemorrhagic shock model. The ferroptotic pathway SLC7A11/GPX4 was activated, and immunohistochemistry showed a significant increase in the expression levels of CD44 and MAPK14 in the hemorrhagic shock rat model. We demonstrated the presence of tissue ferroptosis in hemorrhagic shock by combining bioinformatics analysis with in vivo experimentation. Specifically, we observed the activation of the SLC7A11/GPX4 ferroptotic pathway. Further, CD44 and MAPK14 were identified as hub genes in hemorrhagic shock.

Identification of critical mitochondrial hub gene for facial nerve regeneration.

Mitochondria play a critical role in nerve regeneration, yet the impact of gene expression changes related to mitochondria in facial nerve regeneration remains unknown. To address this knowledge gap, we analyzed the expression profile of the facial motor nucleus (FMN) using data obtained from the Gene Expression Omnibus (GEO) database (GSE162977). By comparing different time points in the data, we identified differentially expressed genes (DEGs). Additionally, we collected mitochondria-related genes from the Gene Ontology (GO) database and intersected them with the DEGs, resulting in the identification of mitochondria-related DEGs (MIT-DEGs). To gain further insights, we performed functional enrichment and pathway analysis of the MIT-DEGs. To explore the interactions among these MIT-DEGs, we constructed a protein-protein interaction (PPI) network using the STRING database and identified hub genes using the Degree algorithm of Cytoscape software. To validate the relevance of these genes to nerve regeneration, we established a rat facial nerve injury (FNI) model and conducted a series of experiments. Through these experiments, we confirmed three MIT-DEGs (Myc, Lyn, and Cdk1) associated with facial nerve regeneration. Our findings provide valuable insights into the transcriptional changes of mitochondria-related genes in the FMN following FNI, which can contribute to the development of new treatment strategies for FNI.

Role of dysregulated macrophage subpopulation ratios and functional changes in the development of coronary atherosclerosis.

Coronary heart disease is one of the most significant risk factors affecting human health worldwide. Its pathogenesis is intricate, with atherosclerosis being widely regarded as the leading cause. Aberrant lipid metabolism in macrophages is recognized as one of the triggering factors in atherosclerosis development. To investigate the role of macrophages in the formation of coronary artery atherosclerosis, we utilized single-cell data from wild-type mice obtained from the aortic roots and ascending aortas after long-term high-fat diet feeding, as deposited in GSE131776. Seurat software was employed to refine the single-cell data in terms of scale and cell types, facilitating the identification of differentially expressed genes. Through the application of differential expression genes, we conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses at 0, 8 and 16 weeks, aiming to uncover pathways with the most pronounced functional alterations as the high-fat diet progressed. The AddModuleScore function was employed to score the expression of these pathways across different cell types. Subsequently, macrophages were isolated and further subdivided into subtypes, followed by an investigation into intercellular communication within these subtypes. Subsequent to this, we induced THP-1 cells to generate foam cells, validating critical genes identified in prior studies. The results revealed that macrophages underwent the most substantial functional changes as the high-fat diet progressed. Furthermore, two clusters were identified as potentially playing pivotal roles in macrophage functional regulation during high-fat diet progression. Additionally, macrophage subtypes displayed intricate functionalities, with mutual functional counterbalances observed among these subtypes. The proportions of macrophage subtypes and the modulation of anti-inflammatory and pro-inflammatory functions played significant roles in the development of coronary artery atherosclerosis.

MiR-431 promotes cardiomyocyte proliferation by targeting FBXO32 expression.

BACKGROUND: The induction of cardiomyocyte (CM) proliferation is a promising approach for cardiac regeneration following myocardial injury. MicroRNAs (miRNAs) have been reported to regulate CM proliferation. In particular, miR-431 expression decreases during cardiac development, according to Gene Expression Omnibus (GEO) microarray data. However, whether miR-431 regulates CM proliferation has not been thoroughly investigated. METHODS: We used integrated bioinformatics analysis of GEO datasets to identify the most significantly differentially expressed miRNAs. Real-time quantitative PCR and fluorescence in situ hybridization were performed to determine the miRNA expression patterns in hearts. Gain- and loss-of-function assays were conducted to detect the role of miRNA in CM proliferation. Additionally, we detected whether miR-431 affected CM proliferation in a myocardial infarction model. The TargetScan, miRDB and miRWalk online databases were used to predict the potential target genes of miRNAs. Luciferase reporter assays were used to study miRNA interactions with the targeting mRNA. RESULTS: First, we found a significant reduction in miR-431 levels during cardiac development. Then, by overexpression and inhibition of miR-431, we demonstrated that miR-431 promotes CM proliferation in vitro and in vivo, as determined by immunofluorescence assays of 5-ethynyl-2'-deoxyuridine (EdU), pH3, Aurora B and CM count, whereas miR-431 inhibition suppresses CM proliferation. Then, we found that miR-431 improved cardiac function post-myocardial infarction. In addition, we identified FBXO32 as a direct target gene of miR-431, with FBXO32 mRNA and protein expression being suppressed by miR-431. FBXO32 inhibited CM proliferation. Overexpression of FBXO32 blocks the enhanced effect of miR-431 on CM proliferation, suggesting that FBXO32 is a functional target of miR-431 during CM proliferation. CONCLUSION: In summary, miR-431 promotes CM proliferation by targeting FBXO32, providing a potential molecular target for preventing myocardial injury.

Protective mechanism of TCF7L1 against retinal photoreceptor cell injury following retinitis pigmentosa based on the GEO database.

Recent studies have reported the promising value of differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) for identifying disease biomarkers. Based on this method, this study intends to characterize the hub genes and pathways related to retinal photoreceptor cell (PRC) injury in the context of retinitis pigmentosa (RP). A total of 53 coexpression modules were identified by WGCNA, among which lightpink4, darkolivegreen, tan4, blue2, skyblue2, and navajowhite2 ranked at the top. By analyzing the RP microarrays retrieved from the GEO database, 338 differentially expressed genes (DEGs) were identified in the RP samples. Forty-five candidate genes were selected from these DEGs by intersection with the genes in the coexpression modules. These intersection genes were subjected to GO and KEGG analyses. Furthermore, the genes and pathways involved in PRC damage were identified based on analyses utilizing GeneCards and STRING tools. Transcription factor 7-like 1 (TCF7L1, also called TCF3) was suggested to participate in the RP-associated PRC damage through the Wnt signaling pathway. It was validated in a blue light-irradiated cell model that TCF7L1 overexpression boosted PRC viability and repressed apoptosis. Inhibition of the Wnt signaling pathway also contributed to protective effects. Together, the data mentioned above supported the conclusion that either elevation of TCF7L1 or blockade of the Wnt signaling pathway could prevent RP progression by protecting PRCs from damage.

Genome-Scale Investigation of the Regulation of azoR Expression in Escherichia coli Using Computational Analysis and Transposon Mutagenesis.

Bacterial azoreductases are enzymes that catalyze the reduction of ingested or industrial azo dyes. Although azoreductase genes have been well identified and characterized, the regulation of their expression has not been systematically investigated. To determine how different factors affect the expression of azoR, we extracted and analyzed transcriptional data from the Gene Expression Omnibus (GEO) resource, then confirmed computational predictions by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results showed that azoR expression was lower with higher glucose concentration, agitation speed, and incubation temperature, but higher at higher culture densities. Co-expression and clustering analysis indicated ten genes with similar expression patterns to azoR: melA, tpx, yhbW, yciK, fdnG, fpr, nfsA, nfsB, rutF, and chrR (yieF). In parallel, constructing a random transposon library in E. coli K-12 and screening 4320 of its colonies for altered methyl red (MR)-decolorizing activity identified another set of seven genes potentially involved in azoR regulation. Among these genes, arsC, relA, plsY, and trmM were confirmed as potential azoR regulators based on the phenotypic decolorization activity of their transposon mutants, and the expression of arsC and relA was confirmed, by qRT-PCR, to significantly increase in E. coli K-12 in response to different MR concentrations. Finally, the significant decrease in azoR transcription upon transposon insertion in arsC and relA (as compared to its expression in wild-type E. coli) suggests their probable involvement in azoR regulation. In conclusion, combining in silico analysis and random transposon mutagenesis suggested a set of potential regulators of azoR in E. coli.

Low-density lipoprotein receptor-related protein 5/6 promotes endometrial cancer progression and cancer cell immune escape.

The study investigated the potential association of the low-density lipoprotein (LDL) genome with endometrial cancer progression based on the Gene Expression Omnibus data set and The Cancer Genome Atlas data set. Differential and weighted gene coexpression network analysis was performed on endometrial cancer transcriptome datasets GSE9750 and GSE106191. The protein-protein interaction network was built using LDL-receptor proteins and the top 50 tumor-associated genes. Low-density lipoprotein-related receptors 5/6 (LRP5/6) in endometrial cancer tissues were correlated with oncogenes, cell cycle-related genes, and immunological checkpoints using Spearman correlation. MethPrimer predicted the LRP5/6 promoter CpG island. LRP2, LRP6, LRP8, LRP12, low-density lipoprotein receptor-related protein-associated protein, and LRP5 were major LDL-receptor-related genes associated with endometrial cancer. LRP5/6 was enriched in various cancer-related pathways and may be a key LDL-receptor-related gene in cancer progression. LRP5/6 may be involved in the proliferation process of endometrial cancer cells by promoting the expression of cell cycle-related genes. LRP5/6 may be involved in the proliferation of endometrial cancer cells by promoting the expression of cell cycle-related genes. LRP5/6 may promote the immune escape of cancer cells by promoting the expression of immune checkpoints, promoting endometrial cancer progression. The MethPrimer database predicted that the LRP5/6 promoter region contained many CpG islands, suggesting that DNA methylation can occur in the LRP5/6 promoter region. LRP5/6 may aggravate endometrial cancer by activating the phosphoinositide 3-kinase/protein kinase B pathway.

Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics.

BACKGROUND: Mounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses are not fully understood. Our study aimed to find potential crucial genes in psoriasis and UC through machine learning and integrated bioinformatics. METHODS: The overlapping differentially expressed genes (DEGs) of the datasets GSE13355 and GSE87466 were identified. Then the functional enrichment analysis was performed. The overlapping genes in LASSO, SVM-RFE and key module in WGCNA were considered as potential crucial genes. The receiver operator characteristic (ROC) curve was used to estimate their diagnostic confidence. The CIBERSORT was conducted to evaluate immune cell infiltration. Finally, the datasets GSE30999 and GSE107499 were retrieved to validate. RESULTS: 112 overlapping DEGs were identified in psoriasis and UC and the functional enrichment analysis revealed they were closely related to the inflammatory and immune response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, and SLAMF7, were ultimately identified as potential crucial genes. ROC curves showed they all had high confidence in the test and validation datasets. CIBERSORT analysis indicated there was a correlation between infiltrating immune cells and potential crucial genes. CONCLUSION: In our study, we focused on the comprehensive understanding of pathogeneses in psoriasis and UC. The identification of eight potential crucial genes may contribute to not only understanding the common mechanism, but also identifying occult UC in psoriasis patients, even serving as therapeutic targets in the future.

Investigation into the role of H2-Ab1 in vascular remodeling in pulmonary arterial hypertension via Bioinformatics.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive disease of vascular remodeling characterized by persistent pulmonary arterial pressure elevation, which can lead to right heart failure and premature death. Given the complex pathogenesis and poor prognosis of PAH, the identification and investigation of biomarkers become increasingly critical for advancing further understanding of the disease. METHODS: PAH-related datasets, GSE49114, GSE180169 and GSE154959, were downloaded from the publicly available GEO database. By performing WGCNA on the GSE49114 dataset, a total of 906 PAH-related key module genes were screened out. By carrying out differential analysis on the GSE180169 dataset, a total of 576 differentially expressed genes were identified. Additionally, the GSE154959 single-cell sequencing dataset was also subjected to differential analysis, leading to the identification of 34 DEGs within endothelial cells. By taking intersection of the above three groups of DEGs, five PAH-related hub genes were screened out, namely Plvap, Cyp4b1, Foxf1, H2-Ab1, and H2-Eb1, among which H2-Ab1 was selected for subsequent experiments. RESULTS: A SuHx mouse model was prepared using the SU5416/hypoxia method, and the successful construction of the model was evaluated through Hematoxylin-Eosin staining, hemodynamic detection, fulton index, and Western Blot (WB). The results of WB and qRT-PCR demonstrated a significant upregulation of H2-Ab1 expression in SuHx mice. Consistent with the results of bioinformatics analysis, a time-dependent increase was observed in H2-Ab1 expression in hypoxia-treated mouse pulmonary artery endothelial cells (PAECs). To investigate whether H2-Ab1 affects the development and progression of PAH, we knocked down H2-Ab1 expression in PAECs, and found that its knockdown inhibited the viability, adhesion, migration, and angiogenesis, while concurrently promoted the apoptosis of PAECs. CONCLUSION: H2-Ab1 could regulate the proliferation, apoptosis, adhesion, migration, and angiogenesis of PAECs.

SCUBE1 Promotes Gestational Diabetes Mellitus: A Bioinformatics and Experimental Investigation.

Gestational diabetes mellitus (GDM) is one of the most common metabolic diseases in pregnant women, posing significant risks to the life and health of both mothers and fetuses. With improving living standards, the incidence of GDM is increasing rapidly. Therefore, understanding the underlying mechanism of GDM is of paramount importance. We downloaded two datasets from the Gene Expression Omnibus (GEO) database, containing sequencing data specifically related to "gestational diabetes" and "placenta". By merging these two datasets, a mRNA expression dataset was obtained and subjected to bioinformatics analyses. To screen out corresponding genes, differential analysis and weighted correlation network analysis (WGCNA) were carried out. Lasso, support vector machine and random forest analyses were subsequently performed for identifying key genes from the differentially expressed genes (DEGs) jointly screened out through differential analysis and WGCNA. Afterwards, immunoinfiltration and correlation analysis were performed to screen immune cells that play a role in disease progression and explore the correlation between the screened key genes and immune cells, after which Western Blot, quantitative real-time polymerase chain reaction, Immunohistochemistry, methyl thiazolyl tetrazolium, flow cytometry, scratch and Transwell assays were, respectively, performed for verification. For further verification, we found that the expression levels of MAP6D1 and SCUBE1 in embryonic tissues of GDM patients was higher compared to those of healthy pregnant women, which was consistent with the results of bioinformatics analysis. Consequently, SCUBE1 was selected for follow-up experiment. In order to explore the role of SCUBE1 in the development of GDM, we treated the trophoblastic cells HTR-8/SVneo with high glucose, and on this basis downregulated the expression of SCUBE1. Through further analysis, we observed that SCUBE1 had a role in reducing cell activity, migration and invasion, and promoting cell apoptosis. In summary, SCUBE1 promotes the development of GDM by increasing cell apoptosis and reducing cell activity, migration, and invasion.

Bioinformatic analysis of the role of immune checkpoint genes and immune infiltration in the pathogenesis and development of premature ovarian insufficiency.

PURPOSE: With advances in immunology, increasing evidence suggests that immunity is involved in premature ovarian insufficiency (POI) pathogenesis. This study investigated the roles of immune checkpoint genes and immune cell infiltration in POI pathogenesis and development. METHODS: The GSE39501 dataset and immune checkpoint genes were obtained from the Gene Expression Omnibus database and related literature. The two datasets were intersected to obtain immune checkpoint-related differentially expressed genes (ICRDEGs), which were analyzed using Gene Ontology and Kyoto Encyclopedia of Gene and Genomes enrichment analysis, weighted correlation network analysis, protein-protein interaction and related microRNAs, transcription factors, and RNA binding proteins. The immune cell infiltration of ICRDEGs was explored, and receiver operating characteristic curves were used to validate the diagnostic value of ICRDEGs in POI. RESULTS: We performed ICRDEG functional enrichment analysis and found that these genes were closely related to immune processes, such as T cell activation. Specifically, they are enriched in various biological processes and pathways, such as cell adhesion molecule and T cell receptor signaling pathways. Weighted correlation network analysis identified seven hub genes: Cd200, Cd274, Cd28, neurociliary protein-1, Cd276, Cd40lg, and Cd47. Furthermore, we identified 112 microRNAs, 17 RNA-binding proteins, and 101 transcription factors. Finally, immune infiltration analysis showed a clear positive correlation between hub genes and multiple immune cell types. CONCLUSION: Bioinformatic analysis identified seven potential ICRDEGs associated with POI, among which the immune checkpoint molecules CD200 and neurociliary protein-1 may be involved in the pathogenesis of POI.

Screening of liothyronine network pharmacology role in the treatment of ischemic stroke and molecular mechanism.

OBJECTIVE: The present study aimed to elucidate mechanisms of liothyronine on the treatment of ischemic stroke (IS). METHODS: Differential analysis based on R limma package was used to identify differentially expressed genes, which were then mapped into the connectivity map database for identification of liothyronine associated with IS. Tumor necrosis factor (TNF) signaling pathway was verified through pathway enrichment analysis via Enrichr online. Ischemia stroke mouse model was built up for further analysis. Infarct area and regional cerebral blood flow (rCBF) were measured by 2, 3, 5-triphenyltetrazolium chloride and laser Doppler flowmetry, respectively. Light microscope was used for the evaluation of body weight and dark neurons. Serum TXB2 , 6-Keto-PGF1a , TNF-α, and interleukin-6 (IL-6) levels in mice were measured using enzyme-linked immuno sorbent assay. In addition, relative protein expression levels of brain-derived neurotrophic factor, nestin, and Sox2 were detected by Western blot analysis. RESULTS: Liothyronine with a negative connectivity was identified as one promising treatment for IS through TNF signaling pathway. The experimental results showed that liothyronine treatment significantly meliorated infarct area and the number of dark neurons in IS mice. Liothyronine greatly ameliorated the expression levels of TXB2 and 6-Keto-PGF1a . Besides, rCBF and body weight change of IS mice were increased gradually with increase of drug concentration. Based on pathway enrichment analysis, anti-inflammatory response (TNF-α and IL-6) relevant to TNF signaling pathway was identified, which was further validated in vitro. Furthermore, proteins as neural stem cell markers made a difference with liothyronine treatment. CONCLUSION: Liothyronine may be a novel therapeutic component to exploit an effective medicine for the treatment of IS.

Construction and evaluation of a metabolic correlation diagnostic model for diabetes based on machine learning algorithms.

BACKGROUND: Diabetes mellitus (DM) is a prevalent chronic disease marked by significant metabolic dysfunctions. Understanding its molecular mechanisms is vital for early diagnosis and treatment strategies. METHODS: We used datasets GSE7014, GSE25724, and GSE156248 from the GEO database to build a diagnostic model for DM using Random Forest (RF) and LASSO regression models. GSE20966 served as a validation cohort. DM patients were classified into two subtypes for functional enrichment analysis. Expression levels of key diagnostic genes were validated using quantitative real-time PCR (qRT-PCR) on Peripheral Blood Mononuclear Cells (PBMCs) from DM patients and healthy controls, focusing on CXCL12 and PPP1R12B with GAPDH as the internal control. RESULTS: After de-batching the datasets, we identified 131 differentially expressed genes (DEGs) between DM and control groups, with 70 up-regulated and 61 down-regulated. Enrichment analysis revealed significant down-regulation in the IL-12 signaling pathway, JAK signaling post-IL-12 stimulation, and the ferroptosis pathway in DM. Five genes (CXCL12, MXRA5, UCHL1, PPP1R12B, and C7) were identified as having diagnostic value. The diagnostic model showed high accuracy in both the training and validation cohorts. The gene set also enabled the subclassification of DM patients into groups with distinct functional traits. qRT-PCR results confirmed the bioinformatics findings, particularly the up-regulation of CXCL12 and PPP1R12B in DM patients. CONCLUSION: Our study pinpointed seven energy metabolism-related genes differentially expressed in DM and controls, with five holding diagnostic value. Our model accurately diagnosed DM and facilitated patient subclassification, offering new insights into DM pathogenesis.

Prognostic analysis of uveal melanoma based on the characteristic genes of M2-type macrophages in the tumor microenvironment.

Uveal melanoma arises from stromal melanocytes and is the most prevalent primary intraocular tumor in adults. It poses a significant diagnostic and therapeutic challenge due to its high malignancy and early onset of metastases. In recent years, there has been a growing interest in the role of diverse immune cells in tumor cell development and metastasis. Using The Cancer Genome Atlas and the gene expression omnibus databases, and the CIBERSORT method, we investigated the topography of intra-tumor immune infiltration in uveal melanoma in this research. We evaluated the prognosis of uveal melanoma patients using the M2 macrophage immune cell infiltration score in conjunction with clinical tumor patient data. We built a prognostic model based on the distinctive genes of M2 macrophages and combined it with patients' clinical data in the database; we ran a survival prognostic analysis to authenticate the model's accuracy. The functional study revealed the importance of macrophage-associated genes in the development of uveal melanoma. Moreover, the reliability of our prediction model was verified by combining tumor mutational load, immune checkpoint, and drug sensitivity, respectively. Our study provides a reference for the follow-up study of uveal melanoma.

Identification of mitophagy-related biomarkers and immune infiltration in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a life-threatening and debilitating mental health condition. Mitophagy, a form of selective autophagy that eliminates dysfunctional mitochondria, is associated with depression. However, studies on the relationship between mitophagy-related genes (MRGs) and MDD are scarce. This study aimed to identify potential mitophagy-related biomarkers for MDD and characterize the underlying molecular mechanisms. METHODS: The gene expression profiles of 144 MDD samples and 72 normal controls were retrieved from the Gene Expression Omnibus database, and the MRGs were extracted from the GeneCards database. Consensus clustering was used to determine MDD clusters. Immune cell infiltration was evaluated using CIBERSORT. Functional enrichment analyses were performed to determine the biological significance of mitophagy-related differentially expressed genes (MR-DEGs). Weighted gene co-expression network analysis, along with a network of protein-protein interactions (PPI), was used to identify key modules and hub genes. Based on the least absolute shrinkage and selection operator analysis and univariate Cox regression analysis, a diagnostic model was constructed and evaluated using receiver operating characteristic curves and validated with training data and external validation data. We reclassified MDD into two molecular subtypes according to biomarkers and evaluated their expression levels. RESULTS: In total, 315 MDD-related MR-DEGs were identified. Functional enrichment analyses revealed that MR-DEGs were mainly enriched in mitophagy-related biological processes and multiple neurodegenerative disease pathways. Two distinct clusters with diverse immune infiltration characteristics were identified in the 144 MDD samples. MATR3, ACTL6A, FUS, BIRC2, and RIPK1 have been identified as potential biomarkers of MDD. All biomarkers showed varying degrees of correlation with immune cells. In addition, two molecular subtypes with distinct mitophagy gene signatures were identified. CONCLUSIONS: We identified a novel five-MRG gene signature that has excellent diagnostic performance and identified an association between MRGs and the immune microenvironment in MDD.

Novel insights into molecular signatures and pathogenic cell populations shared by systemic lupus erythematosus and vascular dementia.

Although vascular dementia (VD) and systemic lupus erythematosus (SLE) may share immune-mediated pathophysiologic processes, the underlying mechanisms are unclear. This study investigated shared gene signatures in SLE versus VD, as well as their potential molecular mechanisms. Bulk RNA sequencing (RNAseq) and single-cell or single-nucleus RNAseq (sc/snRNAseq) datasets from SLE blood samples and VD brain samples were obtained from Gene Expression Omnibus. The identification of genes associated with both SLE and VD was performed using the weighted gene co-expression network analysis (WGCNA) and machine learning algorithms. For the sc/snRNAseq data, an unbiased clustering pipeline based on Seurat and CellChat was used to determine the cellular landscape profile and examine intracellular communication, respectively. The results were subsequently validated using a mice model of SLE with cognitive dysfunction (female MRL/lpr mice). WGCNA and machine learning identified C1QA, LY96, CD163, and MS4A4A as key genes for SLE and VD. sc/snRNAseq analyses revealed that CD163 and MS4A4A were upregulated in mononuclear phagocytes (MPs) from SLE and VD samples and were associated with monocyte-macrophage differentiation. Intriguingly, LGALS9-associated molecular pathway, as the only signaling pathway common between SLE and VD via CellChat analysis, exhibited significant upregulation in cortical microglia of MRL/lpr mice. Our analyses identified C1QA, LY96, CD163, and MS4A4A as potential biomarkers for SLE and VD. Moreover, the upregulation of CD163/MS4A4A and activation of LGALS9 signaling in MPs may contribute to the pathogenesis of VD with SLE. These findings offer novel insight into the mechanisms underlying VD in SLE patients.

Identification and validation of core genes in tumor-educated platelets for human gastrointestinal tumor diagnosis using network-based transcriptomic analysis.

Gastrointestinal (GI) tumors have increasing incidence worldwide with their underlying mechanisms still not being fully understood. The use of tumor-educated platelets (TEPs) in liquid biopsy is a newly-emerged blood-based cancer diagnostic method. Herein, we aimed to investigate the genomic changes of TEPs in GI tumor development and their potential functions using network-based meta-analysis combined with bioinformatic methods. We used a total of three eligible RNA-seq datasets, which were integrated using multiple meta-analysis methods on the NetworkAnalyst website, and identified 775 DEGs (differentially expressed genes; 51 up-regulated and 724 down-regulated genes) in GI tumor relative to healthy control (HC) samples. These TEP DEGs were mostly enriched in bone marrow-derived cell types and associated with gene ontology (GO) of "carcinoma" and could affect pathways of "Integrated Cancer Pathway" and "Generic transcription pathway" respectively for highly and lowly expressed DEGs. Combined network-based meta-analysis and protein-protein interaction (PPI) analysis identified cyclin dependent kinase 1 (CDK1) and heat shock protein family A (Hsp70) member 5 (HSPA5) to be the hub genes with the highest degree centrality (DC), being up-regulated and down-regulated in TEPs, respectively. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that the hub genes were primarily related to cell cycle and division, nucleobase-containing compound and carbohydrate transport, and endoplasmic reticulum unfolded protein response. Additionally, the nomogram model suggested that the two-gene signature owns extraordinary predictive power for GI tumor diagnosis. Further, the two-gene signature was demonstrated to have potential value for metastatic GI tumor diagnosis. The expression levels of CDK1 and HSPA5 in clinical platelet samples were verified to be consistent with the results from bioinformatic analysis. This study identified a two-gene signature encompassing CDK1 and HSPA5 that can be used as a biomarker for GI tumor diagnosis and maybe even cancer-associated thrombosis (CAT)-related prognosis.

What is the context? Gastrointestinal (GI) tumors are now responsible for the majority of cancer-related mortalities worldwide.In the majority of cases of cancer, curative treatments are not recommended at the time of diagnosis. In this case, early screening and diagnosis is very important for overall tumor prognosis. Liquid biopsy emerged as a newly introduced minimally invasive approach for cancer diagnosis by detecting blood analytes as tumor-educated platelets (TEPs). Compared to tissue-based biopsies, liquid biopsies are less invasive, easy to access, convenient for serial tracking and better in eliminating intratumoral spatial heterogeneity. In recent years, specific gene signatures have been identified for cancer diagnosis, prognosis and prediction based on gene profiling data of TEPs. However, most of these studies were performed on the independent platelet profile datasets published on the Gene Expression Omnibus (GEO) database, which may harbor enormous heterogeneity. Additionally, few study revealed TEP mRNA functions and roles in GI tumors. Therefore, there's the need of using an integrated method to re-analyze these data, so we can gain new insights for GI tumor diagnosis.What is new? Herein, through network-based RNA-seq meta-analysis, we identified the CDK1-HSPA5 signature in TEPs that has the potential as a biomarker for diagnosing GI tumors. This is the first time, to our knowledge, that a shared transcriptional signature of tumor-educated platelets has been identified in human GI tumor patients based on meta-analysis. Additionally, we found the two-gene signature has potential value for metastatic GI tumor diagnosis. We also demonstrated that HSPA5 may have different roles in blood and tumor cells, so its expression deregulation in distinct types of tissue may have opposing diagnostic and prognostic values.What is the impact? Our work provides a novel biomarker for platelet-based GI tumor prediction and diagnosis, which may also be used as novel targets for thrombosis prevention during cancer development in the future.

Identifying pyroptosis- and inflammation-related genes in intracranial aneurysms based on bioinformatics analysis.

BACKGROUND: Intracranial aneurysm (IA) is the most common cerebrovascular disease, and subarachnoid hemorrhage caused by its rupture can seriously impede nerve function. Pyroptosis is an inflammatory mode of cell death whose underlying mechanisms involving the occurrence and rupture of IAs remain unclear. In this study, using bioinformatics analysis, we identified the potential pyroptosis-related genes (PRGs) and performed their inflammatory response mechanisms in IAs. METHODS: The mRNA expression matrix of the IA tissue was obtained from the Gene Expression Omnibus database, and 51 PRGs were obtained from previous articles collected from PubMed. The differentially expressed PRGs (DEPRGs) were performed using R software. Subsequently, we performed enrichment analysis, constructed a protein-protein interaction network, performed weighted gene coexpression network analysis (WGCNA) and external validation using another dataset, and identified a correlation between hub genes and immune cell infiltration. Finally, the expression and tissue distribution of these hub genes in IA tissues were detected using Western blotting and immunohistochemical (IHC) staining. RESULTS: In total, 12 DEPRGs associated with IA were identified in our analysis, which included 11 up-regulated and one down-regulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the DEPRGs were mostly enriched in the NOD-like receptor signaling pathway, interleukin-1 beta production, and the inflammasome complex. Three hub genes, NLRP3, IL1B and IL18, were identified using Cytoscape software and the WGCNA correlation module, and external validation revealed statistically significant differences between the expression of these hub genes in the ruptured and unruptured aneurysm groups (p < 0.05). Furthermore, all AUC values were > 0.75. Immune cell infiltration analysis suggested that the hub genes are related to CD8 T cell, macrophages and mast cells. Finally, IHC staining revealed that the protein levels of these hub genes were higher in ruptured and unruptured IA tissues than in normal tissues (p < 0.05). CONCLUSION: The results of bioinformatics analysis showed that pyroptosis is closely related to the formation and rupture of IA, and identified three potential hub genes involved in the pyroptosis and infiltration ofcells. Our findings may improve the understanding of the mechanisms underlying pyroptosis in IA.