STAT4 and COL1A2 are potential diagnostic biomarkers and therapeutic targets for heart failure comorbided with depression

Evaluating Biomarkers as Tools for Early Detection and Prognosis of Heart Failure: A Comprehensive Review

There is a high prevalence of heart failure (HF) worldwide, which has significant consequences for healthcare costs, patient death and quality of life. Therefore, there has been much focus on finding and using biomarkers for early diagnosis, prognostication and therapy of HF. This overview of the research presents a thorough examination of the current state of HF biomarkers and their many uses. Their function in diagnosing HF, gauging its severity and monitoring its response to therapy are all discussed. Particularly promising in HF diagnosis and risk stratification are the cardiac-specific biomarkers, B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide. Markers of oxidative stress, extracellular matrix, renal function, inflammation and cardiac peptides have shown promise in evaluating HF severity and prognosis. MicroRNAs and insulin-like growth factor are two emerging biomarkers that have shown potential in helping with HF diagnosis and prognosis.

Enhancing the revelation of key genes and interaction networks in non-small cell lung cancer with major depressive disorder: A bioinformatics analysis

Background and Aims

Lung cancer is ranked as the second most prevalent form of cancer worldwide. Nonsmall cell lung cancer (NSCLC) represents the predominant histological subtype. Research suggests that one-third of lung cancer patients also experiencing depression. Antidepressants play an indispensable role in the management of NSCLC. Despite significant advancements in treatment, lung cancer patients still face a high mortality rate. Major depressive disorder (MDD) and related antidepressants involved in treatment efficacy and prognosis of NSCLC. However, there has been a lack of screening and analysis regarding genes and networks associated with both NSCLC and MDD.

Methods

To investigate the correlation between MDD and NSCLC, our discovery and validation analysis included four datasets from the Gene Expression Omnibus database from NSCLC or MDD. Differential gene expression (DEGs) analysis, GO and KEGG Pathway, and protein-protein interaction network analyzes to identify hub genes, networks, and associated observations link between MDD and NSCLC.

Results

The analysis of two datasets yielded a total of 84 downregulated and 52 upregulated DEGs. Pathway enrichment analyzes indicated that co-upregulated genes were enriched in the regulation of positive regulation of cellular development, collagen-containing extracellular matrix (ECM), cytokine binding, and axon guidance. We identified 20 key genes, which were further analyzed using the MCODE plugin to identify two core subnetworks. The integration of functionally similar genes provided valuable insights into the potential involvement of these hub genes in diverse biological processes including angiogenesis humoral immune response regulation inflammatory response organization ECM network.

Conclusion

We have identified a total of 136 DEGs that participate in multiple biological signaling pathways. A total of 20 hub genes have demonstrated robust associations, potentially indicating novel diagnostic and therapeutic targets for both diseases.

Unveiling Collagen's Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications

Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I-XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment.

Bioinformatics analysis and identification of potential key genes and pathways in the pathogenesis of nonischemic cardiomyopathy

Nonischemic cardiomyopathy (NICM) is a major cause of advanced heart failure, and the morbidity and mortality associated with NICM are serious medical problems. However, the etiology of NICM is complex and the related mechanisms involved in its pathogenesis remain unclear. The microarray datasets GSE1869 and GSE9128 retrieved from the Gene Expression Omnibus database were used to identify differentially expressed genes (DEGs) between NICM and normal samples. The co-expressed genes were identified using Venn diagrams. Kyoto Encyclopedia of Genes and Genomes pathway analyses and gene ontology enrichment were used to clarify biological functions and signaling pathways. Analysis of protein-protein interaction networks using Search Tool for the Retrieval of Interacting Genes/Proteins online to define the hub genes associated with NICM pathogenesis. A total of 297 DEGs were identified from GSE1869, 261 of which were upregulated genes and 36 were downregulated genes. A total of 360 DEGs were identified from GSE9128, 243 of which were upregulated genes and 117 were downregulated genes. In the 2 datasets, the screening identified 36 co-expressed DEGs. Kyoto Encyclopedia of Genes and Genomes pathway and gene ontology analysis showed that DEGs were mainly enriched in pantothenate and CoA biosynthesis, beta-alanine metabolism, kinetochore, G-protein beta/gamma-subunit complex, and other related pathways. The PPI network analysis revealed that DUSP6, EGR1, ZEB2, and XPO1 are the 4 hub genes of interest in the 2 datasets. Bioinformatics analysis of hub genes and key signaling pathways is an effective way to elucidate the mechanisms involved in the development of NICM. The results will facilitate further studies on the pathogenesis and therapeutic targets of NICM.

Identification and immunoinfiltration analysis of key genes in ulcerative colitis using WGCNA

Objective

Ulcerative colitis (UC) is a chronic non-specific inflammatory bowel disease characterized by an unclear pathogenesis. This study aims to screen out key genes related to UC pathogenesis.

Methods

Bioinformatics analysis was conducted for screening key genes linked to UC pathogenesis, and the expression of the screened key genes was verified by establishing a UC mouse model.

Results

Through bioinformatics analysis, five key genes were obtained. Subsequent infiltration analysis revealed seven significantly different immune cell types between the UC and general samples. Additionally, animal experiment results illustrated markedly decreased body weight, visible colonic shortening and damage, along with a significant increase in the DAI score of the DSS-induced mice in the UC group in comparison with the NC group. In addition, H&E staining results demonstrated histological changes including marked inflammatory cell infiltration, loss of crypts, and epithelial destruction in the colon mucosa epithelium. qRT-PCR analysis indicated a down-regulation of ABCG2 and an up-regulation of IL1RN, REG4, SERPINB5 and TRIM29 in the UC mouse model. Notably, this observed trend showed a significant dependence on the concentration of DSS, with the mouse model of UC induced by 7% DSS demonstrating a more severe disease state compared to that induced by 5% DSS.

Conclusion

ABCG2, IL1RN, REG4, SERPINB5 and TRIM29 were screened out as key genes related to UC by bioinformatics analysis. The expression of ABCG2 was down-regulated, and that of IL1RN, REG4, SERPINB5 and TRIM29 were up-regulated in UC mice as revealed by animal experiments.

Smart carbon-based sensors for the detection of non-coding RNAs associated with exposure to micro(nano)plastics: an artificial intelligence perspective

Micro(nano)plastics (MNPs) are pervasive environmental pollutants that individuals eventually consume. Despite this, little is known about MNP's impact on public health. In this article, we assess the evidence for potentially harmful consequences of MNPs in the human body, concentrating on molecular toxicity and exposure routes. Since MNPs are present in various consumer products, foodstuffs, and the air we breathe, exposure can occur through ingestion, inhalation, and skin contact. MNPs exposure can cause mitochondrial oxidative stress, inflammatory lesions, and epigenetic modifications, releasing specific non-coding RNAs in circulation, which can be detected to diagnose non-communicable diseases. This article examines the most fascinating smart carbon-based nanobiosensors for detecting circulating non-coding RNAs (lncRNAs and microRNAs). Carbon-based smart nanomaterials offer many advantages over traditional methods, such as ease of use, sensitivity, specificity, and efficiency, for capturing non-coding RNAs. In particular, the synthetic methods, conjugation chemistries, doping, and in silico approach for the characterization of synthesized carbon nanodots and their adaptability to identify and measure non-coding RNAs associated with MNPs exposure is discussed. Furthermore, the article provides insights into the use of artificial intelligence tools for designing smart carbon nanomaterials.

Methylation and transcriptomic expression profiles of HUVEC in the oxygen and glucose deprivation model and its clinical implications in AMI patients

The obstructed coronary artery undergoes a series of pathological changes due to ischemic-hypoxic shocks during acute myocardial infarction (AMI). However, the altered DNA methylation levels in endothelial cells under these conditions and their implication for the etiopathology of AMI have not been investigated in detail. This study aimed to explore the relationship between DNA methylation and pathologically altered gene expression profile in human umbilical vein endothelial cells (HUVECs) subjected to oxygen-glucose deprivation (OGD), and its clinical implications in AMI patients. The Illumina Infinium MethylationEPIC BeadChip assay was used to explore the genome-wide DNA methylation profile using the Novaseq6000 platform for mRNA sequencing in 3 pairs of HUVEC-OGD and control samples. GO and KEGG pathway enrichment analyses, as well as correlation, causal inference test (CIT), and protein-protein interaction (PPI) analyses identified 22 hub genes that were validated by MethylTarget sequencing as well as qRT-PCR. ELISA was used to detect four target molecules associated with the progression of AMI. A total of 2,524 differentially expressed genes (DEGs) and 22,148 differentially methylated positions (DMPs) corresponding to 6,642 differentially methylated genes (DMGs) were screened (|Δβ|>0.1 and detection p < 0.05). After GO, KEGG, correlation, CIT, and PPI analyses, 441 genes were filtered. qRT-PCR confirmed the overexpression of VEGFA, CCL2, TSP-1, SQSTM1, BCL2L11, and TIMP3 genes, and downregulation of MYC, CD44, BDNF, GNAQ, RUNX1, ETS1, NGFR, MME, SEMA6A, GNAI1, IFIT1, and MEIS1. DNA fragments BDNF_1_ (r = 0.931, p < 0.0001) and SQSTM1_2_NEW (r = 0.758, p = 0.0043) were positively correlated with the expressions of corresponding genes, and MYC_1_ (r = -0.8245, p = 0.001) was negatively correlated. Furthermore, ELISA confirmed TNFSF10 and BDNF were elevated in the peripheral blood of AMI patients (p = 0.0284 and p = 0.0142, respectively). Combined sequencing from in vitro cellular assays with clinical samples, aiming to establish the potential causal chain of the causal factor (DNA methylation) - mediator (mRNA)-cell outcome (endothelial cell ischemic-hypoxic injury)-clinical outcome (AMI), our study identified promising OGD-specific genes, which provided a solid basis for screening fundamental diagnostic and prognostic biomarkers of coronary endothelial cell injury of AMI. Moreover, it furnished the first evidence that during ischemia and hypoxia, the expression of BNDF was regulated by DNA methylation in endothelial cells and elevated in peripheral blood.

Identification of Immuno-Inflammation-Related Biomarkers for Acute Myocardial Infarction Based on Bioinformatics

Purpose

Previous studies have confirmed that inflammation and immunity are involved in the pathogenesis of acute myocardial infarction (AMI). However, only few related genes are identified as biomarkers for the diagnosis and treatment of AMI.

Patients and Methods

GSE48060 and GSE60993 datasets were retrieved from Gene Expression Omnibus. The differentially expressed immuno-inflammation-related genes (DEIIRGs) were obtained from GSE48060, and the biomarkers for AMI were screened and validated using the "Neuralnet" package and GSE60993 dataset. Further, the biomarker-based nomogram was constructed, and miRNAs, transcription factors (TFs), and potential drugs targeting the biomarkers were explored. Furthermore, immune infiltration analysis was analyzed in AMI. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR).

Results

First, eight biomarkers were screened via bioinformatics, and the artificial neural network model indicated a higher prediction accuracy for AMI even in the validation dataset. Nomogram had accurate forecasting ability for AMI as well. The TFs GTF2I, PHOX2B, RUNX1, and FOS targeting hsa-miR-1297 could regulate the expressions of ADM and CBLB, and RORA could effectively interact with melatonin and citalopram. RT-qPCR results for ADM, PI3, MMP9, NRG1 and CBLB were consistent with those of bioinformatic analysis.

Conclusion

In conclusion, eight key immuno-inflammation-related genes, namely, SH2D1B, ADM, PI3, MMP9, NRG1, CBLB, RORA, and FASLG, may serve as the potential biomarkers for AMI, in which the downregulation of CBLB and upregulation of ADM, PI3, and NRG1 in AMI was detected for the first time, providing a new strategy for the diagnosis and treatment of AMI.

Perspectives of herbs and their natural compounds, and herb formulas on treating diverse diseases through regulating complicated JAK/STAT signaling

JAK/STAT signaling pathways are closely associated with multiple biological processes involved in cell proliferation, apoptosis, inflammation, differentiation, immune response, and epigenetics. Abnormal activation of the STAT pathway can contribute to disease progressions under various conditions. Moreover, tofacitinib and baricitinib as the JAK/STAT inhibitors have been recently approved by the FDA for rheumatology disease treatment. Therefore, influences on the STAT signaling pathway have potential and perspective approaches for diverse diseases. Chinese herbs in traditional Chinese medicine (TCM), which are widespread throughout China, are the gold resources of China and have been extensively used for treating multiple diseases for thousands of years. However, Chinese herbs and herb formulas are characterized by complicated components, resulting in various targets and pathways in treating diseases, which limits their approval and applications. With the development of chemistry and pharmacology, active ingredients of TCM and herbs and underlying mechanisms have been further identified and confirmed by pharmacists and chemists, which improved, to some extent, awkward limitations, approval, and applications regarding TCM and herbs. In this review, we summarized various herbs, herb formulas, natural compounds, and phytochemicals isolated from herbs that have the potential for regulating multiple biological processes via modulation of the JAK/STAT signaling pathway based on the published work. Our study will provide support for revealing TCM, their active compounds that treat diseases, and the underlying mechanism, further improving the rapid spread of TCM to the world.

Single-Cell Transcriptomic Analysis Reveals Macrophage–Tumor Crosstalk in Hepatocellular Carcinoma

As one of the most malignant cancer, hepatocellular carcinoma (HCC) has a complex ecosystem featured by high heterogeneity. Cell crosstalk is demonstrated to be critical for HCC development. However, the cell communication orchestration in HCC remains largely unknown. Here, by analyzing the single-cell transcriptomes of the primary tumor tissues (n = 10) and tumor-adjacent tissues (n = 8) derived from 10 patients with HCC, we found that the proportions of plasmacytoid dendritic cells (pDCs) and natural killer (NK) cells were reduced and that the proportion of macrophages was increased in the immune component of the primary tumor, compared with those in the tumor-adjacent tissue. Furthermore, we found widespread communication between macrophage populations and other cell types, and this communication was remarkably strengthened in the primary tumor, especially with HCC malignant cells. In addition, the SPP1–CD44 axis was identified as a unique interaction between macrophages and HCC malignant cells. Our comprehensive portrait of cell communication patterns over the HCC ecosystem reveals further insights into immune infiltration.

Exploration of the molecular mechanisms, shared gene signatures, and MicroRNAs between systemic lupus erythematosus and diffuse large B cell lymphoma by bioinformatics analysis

BACKGROUND

Systemic lupus erythematosus (SLE) is a complex heterogeneous systemic autoimmune disease. Previous studies have shown that SLE may be related to diffuse large B cell lymphoma (DLBCL), but the mechanism of their relationship is still unclear. The present study aimed to explore the common genetic molecular mechanisms, core shared genes, and miRNAs between SLE and DLBCL as well as to investigate the diagnostic markers of DLBCL.

METHODS

The SLE and DLBCL microarray data were downloaded from the comprehensive Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules. Four core shared genes were screened out by various algorithms and validated in other cohorts. Finally, we constructed a common core gene-miRNA network using the human microRNA disease database (HMDD) and TarBase.

RESULTS

Using WGCNA, four modules were identified as important modules for SLE and DLBCL. Enrichment analysis of the shared genes showed that the highly activated NF-κB pathway was a common feature of the pathophysiology. Four core shared genes, namely, PSMB10, PSMB4, TAF10, and NFΚBIA, were screened out. These core shared genes were significantly upregulated in both diseases, and they may be potential diagnostic markers of DLBCL. The core gene-miRNA network showed that miR-155-5p, regulating the shared NF-κB pathway, may play an important role in the susceptibility of SLE patients to DLBCL.

CONCLUSION

The present study revealed that NF-κB pathway in SLE may be a crucial susceptible factor for DLBCL. In addition, we identified PSMB10, PSMB4, TAF10, NFΚBIA and miR-155 involved in the common pathogenesis as potential biomarkers and therapeutic targets for DLBCL.

EditorialSpecial issue on "Brain-body communication in health and diseases"

Bidirectional interaction between the brain and the peripheral organs plays a key role in homeostasis in the body. Abnormalities in brain-body communication potentially leads to a number of brain diseases, including psychiatric and neurodegenerative disorders. For example, dysbiosis of gut microbiota and altered levels of microbes-derived compounds plays an important role in the pathophysiology of a number of psychiatric disorders and neurodegenerative disorders. Furthermore, depression is the most common psychiatric symptom in patients with physical disorders, including pain and cardiovascular diseases. This special issue brings together current information on the brain-body communication in health and diseases.