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Medicine Sep 2023Although androgenetic alopecia (AGA) is classified as a non-inflammatory alopecia, histological evidence of microinflammation has long been recognized. However, changes...
BACKGROUND
Although androgenetic alopecia (AGA) is classified as a non-inflammatory alopecia, histological evidence of microinflammation has long been recognized. However, changes in the immune microenvironment, immune-related pathways and the expression of immune-related genes (IRGs) involved in AGA remain unclear.
METHODS
The microarray gene expression data (GSE36169) from patients with male AGA were analyzed. gene set enrichment analysis (GSEA) among statistically changed genes was done. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses among differentially expressed genes were performed. differentially expressed genes were screened to identify IRGs based on the ImmPort database. The cytohubba-MCC plugin of Cytoscape was applied to screen hub immune genes. The infiltration levels of 28 immune cells were quantified adopting single-sample GSEA (ssGSEA) algorithm. The microarray gene expression data (GSE90594) of male AGA was analyzed to validate hub IRGs genes and differential infiltrated immune cells.
RESULTS
The ssGSEA revealed γδT cell, central memory CD8+ T cell, mast cell, immature B cell, activated CD8+ T cell, effector memory CD4+ T cell, eosinophil and neutrophil were significantly increased infiltration in the bald scalp. GSEA showed statistically changed genes were most enriched in immune related pathways, including innate immune system, adaptive immune system, cytokine signaling, interferon-γ signaling, interferon signaling and interleukins signaling. The 4 hub IRGs, including matrix metallopeptidase 9, protein tyrosine phosphatase receptor type C, bone morphogenetic protein 2, and thrombospondin 1, were enriched in the pathways of allograft rejection, coagulation and interferon-γ response.
CONCLUSION
In summary, we proposed that the increase in γδ T cells, central memory CD8+ T cells, activated CD8+ T cell as well as the infiltration of mast cells contributed to immune microenvironment changes in male AGA. The 4 hub IRGs may be involved in the development and progression of hair loss in male AGA through interferon-γ signal pathways.
Topics: Humans; Male; Interferon-gamma; Alopecia; Mast Cells; Algorithms; Blood Coagulation
PubMed: 37746940
DOI: 10.1097/MD.0000000000035242 -
Journal of Cell Communication and... Sep 2023Hepatic ischemia-reperfusion (I/R) injury is a severe clinical syndrome, causing a profound medical and socioeconomic burden worldwide. This study aimed to explore...
Hepatic ischemia-reperfusion (I/R) injury is a severe clinical syndrome, causing a profound medical and socioeconomic burden worldwide. This study aimed to explore underlying biomarkers and treatment targets in the progression of hepatic I/R injury. We screened gene expression profiles of the hepatic I/R injury from the Gene Expression Omnibus (GEO) database, downloaded expression profiles data (GSE117066). Differentially expressed genes (DEGs) were identified through cluster of the PPI network, and enrichment pathways were conducted based on gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The bioinformatics analysis was used to identify biomarkers that alleviate hepatic I/R injury. Finally, the effects of hub gene were investigated by in vitro and in vivo experiments. A total of 162 DEGs (76 up-regulated and 86 down-regulated genes) were extracted between sham and I/R, and 248 DEGs (118 up-regulated and 130 down-regulated genes) were extracted between I/R and ischemic postconditioning (IPO). The cluster of the PPI network and maximal clique centrality (MCC) method of the common DEGs were performed to identify the phosphoserine aminotransferase 1 (PSAT1) as the potential gene for hepatic I/R injury. Then, the H-E, TUNEL and PCNA staining were indicated that the hepatic injury score was highest in I/R 6 h. The expression level of apoptosis-related proteins was consistent with the pathological results. Both gain- and loss-of-function assays demonstrated that hepatic I/R injury was alleviated by PSAT1. PSAT1 may play crucial roles in hepatic I/R injury and thus serves as a hub biomarker for hepatic I/R injury prognosis and individual-based treatment.
PubMed: 36745318
DOI: 10.1007/s12079-023-00727-0 -
MBio Apr 2020The microcin C (McC) and related compounds are potent Trojan horse peptide-nucleotide antibiotics. The peptide part facilitates transport into sensitive cells. Inside...
The microcin C (McC) and related compounds are potent Trojan horse peptide-nucleotide antibiotics. The peptide part facilitates transport into sensitive cells. Inside the cell, the peptide part is degraded by nonspecific peptidases releasing an aspartamide-adenylate containing a phosphoramide bond. This nonhydrolyzable compound inhibits aspartyl-tRNA synthetase. In addition to the efficient export of McC outside the producing cells, special mechanisms have evolved to avoid self-toxicity caused by the degradation of the peptide part inside the producers. Here, we report that histidine-triad (HIT) hydrolases encoded in biosynthetic clusters of some McC homologs or by standalone genes confer resistance to McC-like compounds by hydrolyzing the phosphoramide bond in toxic aspartamide-adenosine, rendering them inactive. Uncovering the mechanisms of resistance is a required step for countering the looming antibiotic resistance crisis. In this communication, we show how universally conserved histidine-triad hydrolases provide resistance to microcin C, a potent inhibitor of bacterial protein synthesis.
Topics: Anti-Bacterial Agents; Bacterial Proteins; Bacteriocins; Biosynthetic Pathways; Drug Resistance, Bacterial; Escherichia coli; Hydrolases; Multigene Family; Myxococcales; Operon; Peptides
PubMed: 32265328
DOI: 10.1128/mBio.00497-20 -
Frontiers in Medicine 2021Lupus nephritis (LN) is a common and severe organ manifestation of systemic lupus erythematosus (SLE) and is a major cause of SLE related deaths. Early diagnosis is...
Lupus nephritis (LN) is a common and severe organ manifestation of systemic lupus erythematosus (SLE) and is a major cause of SLE related deaths. Early diagnosis is essential to improve the prognosis of patients with LN. To screen the potential biomarkers associated with LN, we downloaded the gene expression profile of GSE99967 from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to construct a gene co-expression network and identify gene modules associated with LN. Gene Ontology (GO) analysis was also applied to explore the biological function of genes and identify the key module. Differentially expressed genes (DEGs) were identified and Maximal Clique Centrality (MCC) values were calculated to screen hub genes. Furthermore, we selected promising biomarkers for real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) validation in independent cohorts. Our results indicated that five hub genes, including IFI44, IFIT3, HERC5, RSAD2, and DDX60 play vital roles in the pathogenesis of LN. Importantly, IFI44 may considered as a key biomarker in LN for its diagnostic capabilities, which is also a promising therapeutic target in the future.
PubMed: 34760904
DOI: 10.3389/fmed.2021.762848 -
Frontiers in Aging Neuroscience 2022Alzheimer's disease (AD) is becoming a more prevalent public health issue in today's culture. The experimental study of Coptidis Rhizoma (CR) and its chemical components...
BACKGROUND
Alzheimer's disease (AD) is becoming a more prevalent public health issue in today's culture. The experimental study of Coptidis Rhizoma (CR) and its chemical components in AD treatment has been widely reported, but the principle of multi-level and multi-mechanism treatment of AD urgently needs to be clarified.
OBJECTIVE
This study focuses on network pharmacology to clarify the mechanism of CR's multi-target impact on Alzheimer's disease.
METHODS
The Phytochemical-compounds of CR have been accessed from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) and Symmap database or HPLC determination. The values of Oral Bioavailability (OB) ≥ 30% and Drug Like (DL) ≥ 0.18 or blood ingredient were used to screen the active components of CR; the interactive network of targets and compounds were constructed by STRING and Cytoscape platform, and the network was analyzed by Molecular Complex Detection (MCODE); Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) and metabolic pathway enrichment of targets were carried out with Metascape, the Database for Annotation, Visualization and Integrated Discovery (DAVID) and MetaboAnalyst platform; Based on CytoHubba, the potential efficient targets were screened by Maximal Clique Centrality (MCC) and Degree, the correlation between potential efficient targets and amyloid β-protein (Aβ), Tau pathology was analyzed by Alzdata database, and the genes related to aging were analyzed by Aging Altas database, and finally, the core targets were obtained; the binding ability between ingredients and core targets evaluated by molecular docking, and the clinical significance of core targets was assessed with Gene Expression Omnibus (GEO) database.
RESULTS
19 active components correspond to 267 therapeutic targets for AD, of which 69 is potentially effective; in module analysis, RELA, TRAF2, STAT3, and so on are the critical targets of each module; among the six core targets, RELA, MAPK8, STAT3, and TGFB1 have clinical therapeutic significance; GO function, including 3050 biological processes (BP), 257 molecular functions (MF), 184 cellular components (CC), whose functions are mainly related to antioxidation, regulation of apoptosis and cell composition; the HIF-1 signaling pathway, glutathione metabolism is the most significant result of 134 KEGG signal pathways and four metabolic pathways, respectively; most of the active components have an excellent affinity in docking with critical targets.
CONCLUSION
The pharmacological target prediction of CR based on molecular network pharmacology paves the way for a multi-level networking strategy. The study of CR in AD treatment shows a bright prospect for curing neurodegenerative diseases.
PubMed: 35795239
DOI: 10.3389/fnagi.2022.890046 -
Frontiers in Cardiovascular Medicine 2022This study aimed to determine early diagnosis genes of acute myocardial infarction (AMI) and then validate their association with ferroptosis, immune checkpoints, and...
This study aimed to determine early diagnosis genes of acute myocardial infarction (AMI) and then validate their association with ferroptosis, immune checkpoints, and N6-methyladenosine (m6A), which may provide a potential method for the early diagnosis of AMI. Firstly, we downloaded microarray data from NCBI (GSE61144, GSE60993, and GSE42148) and identified differentially expressed genes (DEGs) in samples from healthy subjects and patients with AMI. Also, we performed systematic gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used STRING to predict protein interactions. Moreover, MCC and MCODE algorithms in the cytoHubba plug-in were used to screen nine key genes in the network. We then determined the diagnostic significance of the nine obtained DEGs by plotting receiver operating characteristic curves using a multiscale curvature classification algorithm. Meanwhile, we investigated the relationship between AMI and immune checkpoints, ferroptosis, and m6A. In addition, we further validated the key genes through the GSE66360 dataset and consequently obtained nine specific genes that can be used as early diagnosis biomarkers for AMI. Through screening, we identified 210 DEGs, including 53 downregulated and 157 upregulated genes. According to GO, KEGG, and key gene screening results, and could be used for early prediction of AMI. Finally, we found that AMI was associated with ferroptosis, immune checkpoints, and m6A and and are effective markers for the diagnosis of AMI, which can provide new prospects for future studies on the pathogenesis of AMI.
PubMed: 35224064
DOI: 10.3389/fcvm.2022.836067 -
Frontiers in Oncology 2021Most solid tumours are hypoxic. Tumour cell proliferation and metabolism accelerate oxygen consumption. The low oxygen supply due to vascular abnormalisation and the...
Most solid tumours are hypoxic. Tumour cell proliferation and metabolism accelerate oxygen consumption. The low oxygen supply due to vascular abnormalisation and the high oxygen demand of tumour cells give rise to an imbalance, resulting in tumour hypoxia. Hypoxia alters cellular behaviour and is associated with extracellular matrix remodelling, enhanced tumour migration, and metastatic behaviour. In light of the foregoing, more research on the progressive and prognostic impacts of hypoxia on gliomas are crucial. In this study, we analysed the expression levels of 75 hypoxia-related genes in gliomas and found that a total of 26 genes were differentially expressed in The Cancer Genome Atlas (TCGA) database samples. We also constructed protein-protein interaction networks using the STRING database and Cytoscape. We obtained a total of 10 Hub genes using the MCC algorithm screening in the cytoHubba plugin. A prognostic risk model with seven gene signatures (PSMB6, PSMD9, UBB, PSMD12, PSMB10, PSMA5, and PSMD14) was constructed based on the 10 Hub genes using LASSO-Cox regression analysis. The model was verified to be highly accurate using subject work characteristic curves. The seven-gene signatures were then analysed by univariate and multivariate Cox. Notably, PSMB10, PSMD12, UBB, PSMA5, and PSMB6 were found to be independent prognostic predictive markers for glioma. In addition, PSMB6, PSMA5, UBB, and PSMD12 were lowly expressed, while PSMB10 was highly expressed, in the TCGA and GTEx integrated glioma samples and normal samples, which were verified through protein expression levels in the Human Protein Atlas database. This study found the prognostic predictive values of the hypoxia-related genes PSMB10, PSMD12, UBB, PSMA5, and PSMB6 for glioma and provided ideas and entry points for the progress of hypoxia-related glioma.
PubMed: 34868920
DOI: 10.3389/fonc.2021.726794 -
Heliyon Jan 2024Diabetic nephropathy (DN) is one of the most common microvascular complications of diabetes mellitus. Periodontitis (PD) is a microbially-induced chronic inflammatory...
Diabetic nephropathy (DN) is one of the most common microvascular complications of diabetes mellitus. Periodontitis (PD) is a microbially-induced chronic inflammatory disease that is thought to have a bidirectional relationship with diabetes mellitus. DN and PD are recognized as models associated with accelerated aging. This study is divided into two parts, the first of which explores the bidirectional causal relationship through Mendelian randomization (MR). The second part aims to investigate the relationship between PD and DN in terms of potential crosstalk genes, aging-related genes, biological pathways, and processes using bioinformatic methods. MR analysis showed no evidence to support a causal relationship between DN and PD ( = 0.34) or PD and DN ( = 0.77). Using the GEO database, we screened 83 crosstalk genes overlapping in two diseases. Twelve paired genes identified by Pearson correlation and the four hub genes in the key cluster were jointly evaluated as key crosstalk-aging genes. Using support vector machine recursive feature elimination (SVM-RFE) and maximal clique centrality (MCC) algorithms, feature selection established five genes as the key crosstalk-aging genes. Based on five key genes, an ANN diagnostic model with reliable diagnosis of two diseases was developed. Gene enrichment analysis indicates that AGE-RAGE pathway signaling, the complement system, and multiple immune inflammatory pathways may be involved in common features of both diseases. Immune infiltration analysis reveals that most immune cells are differentially expressed in PD and DN, with dendritic cells and T cells assuming vital roles in both diseases. Overall, although there is no causal link, CSF1R, CXCL6, VCAM1, JUN and IL1B may be potential crosstalk-aging genes linking PD and DN. The common pathways and markers explored in this study could contribute to a deeper understanding of the common pathogenesis of both diseases in the context of aging and provide a theoretical basis for future research.
PubMed: 38304805
DOI: 10.1016/j.heliyon.2024.e24872 -
Oncogene Jan 2022Merkel cell carcinoma (MCC) is a neuroendocrine tumor either induced by integration of the Merkel cell polyomavirus into the cell genome or by accumulation of...
Merkel cell carcinoma (MCC) is a neuroendocrine tumor either induced by integration of the Merkel cell polyomavirus into the cell genome or by accumulation of UV-light-associated mutations (VP-MCC and UV-MCC). Whether VP- and UV-MCC have the same or different cellular origins is unclear; with mesenchymal or epidermal origins discussed. DNA-methylation patterns have a proven utility in determining cellular origins of cancers. Therefore, we used this approach to uncover evidence regarding the cell of origin of classical VP- and UV-MCC cell lines, i.e., cell lines with a neuroendocrine growth pattern (n = 9 and n = 4, respectively). Surprisingly, we observed high global similarities in the DNA-methylation of UV- and VP-MCC cell lines. CpGs of lower methylation in VP-MCC cell lines were associated with neuroendocrine marker genes such as SOX2 and INSM1, or linked to binding sites of EZH2 and SUZ12 of the polycomb repressive complex 2, i.e., genes with an impact on carcinogenesis and differentiation of neuroendocrine cancers. Thus, the observed differences appear to be rooted in viral compared to mutation-driven carcinogenesis rather than distinct cells of origin. To test this hypothesis, we used principal component analysis, to compare DNA-methylation data from different epithelial and non-epithelial neuroendocrine cancers and established a scoring model for epithelial and neuroendocrine characteristics. Subsequently, we applied this scoring model to the DNA-methylation data of the VP- and UV-MCC cell lines, revealing that both clearly scored as epithelial cancers. In summary, our comprehensive analysis of DNA-methylation suggests a common epithelial origin of UV- and VP-MCC cell lines.
Topics: Carcinoma, Merkel Cell; DNA Methylation; High-Throughput Screening Assays; Humans; Tumor Virus Infections
PubMed: 34667274
DOI: 10.1038/s41388-021-02064-1 -
Nutrients Apr 2023Insulin resistance (IR) is a major contributing factor to the pathogenesis of metabolic syndrome and type 2 diabetes mellitus (T2D). Adipocyte metabolism is known to...
BACKGROUND
Insulin resistance (IR) is a major contributing factor to the pathogenesis of metabolic syndrome and type 2 diabetes mellitus (T2D). Adipocyte metabolism is known to play a crucial role in IR. Therefore, the aims of this study were to identify metabolism-related proteins that could be used as potential biomarkers of IR and to investigate the role of N-methyladenosine (mA) modification in the pathogenesis of this condition.
METHODS
RNA-seq data on human adipose tissue were retrieved from the Gene Expression Omnibus database. The differentially expressed genes of metabolism-related proteins (MP-DEGs) were screened using protein annotation databases. Biological function and pathway annotations of the MP-DEGs were performed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Key MP-DEGs were screened, and a protein-protein interaction (PPI) network was constructed using STRING, Cytoscape, MCODE, and CytoHubba. LASSO regression analysis was used to select primary hub genes, and their clinical performance was assessed using receiver operating characteristic (ROC) curves. The expression of key MP-DEGs and their relationship with mA modification were further verified in adipose tissue samples collected from healthy individuals and patients with IR.
RESULTS
In total, 69 MP-DEGs were screened and annotated to be enriched in pathways related to hormone metabolism, low-density lipoprotein particle and carboxylic acid transmembrane transporter activity, insulin signaling, and AMPK signaling. The MP-DEG PPI network comprised 69 nodes and 72 edges, from which 10 hub genes (, , , , , , , , , and ) were identified. was chosen as the key gene because it had the highest maximal clique centrality (MCC) score. , , and were selected as primary genes by LASSO analysis. According to the ROC curves, , , , and could be used as potential biomarkers to detect IR with good sensitivity and accuracy (AUC = 0.80, 95% CI: 0.67-0.94; AUC = 0.86, 95% CI: 0.74-0.94; AUC = 0.83, 95% CI: 0.64-0.92; AUC = 0.78, 95% CI: 0.64-0.92). The expression of , , , and was significantly correlated with that of , , , , , and ( < 0.05). In validation clinical samples, the was moderately effective for detecting IR (AUC = 0.78, 95% CI: 0.69-0.80), and its expression was positively correlated with the methylation levels of (r = 0.359, = 0.001).
CONCLUSION
Metabolism-related proteins play critical roles in IR. Moreover, and are potential biomarkers of IR and may be involved in the development of T2D via their mA modification. These findings offer reliable biomarkers for the early detection of T2D and promising therapeutic targets.
Topics: Humans; Gene Regulatory Networks; Gene Expression Profiling; Insulin Resistance; Diabetes Mellitus, Type 2; Biomarkers; Computational Biology; Alpha-Ketoglutarate-Dependent Dioxygenase FTO; Methyltransferases
PubMed: 37111057
DOI: 10.3390/nu15081839