Differential Expression Research Articles

ASS1 is a hub gene and possible therapeutic target for regulating metabolic dysfunction-associated steatotic liver disease modulated by a carbohydrate-restricted diet.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease globally. A low-carbohydrate diet (LCD) offers benefits to MASLD patients, albeit its exact mechanism is not fully understood. Using public liver transcriptome data from MASLD patients before/after LCD intervention, we applied differential expression analysis and machine learning to identify key genes. We initially identified 162 differentially expressed genes in the GSE107650 dataset. Secondly, employing two machine learning algorithms, we found that PRAMENP, LEAP2, LOC105379013, and argininosuccinate synthetase 1 (ASS1) are potential hub genes. Additionally, protein-protein interaction and single-cell RNA location analyses suggested that ASS1 was the most crucial hub gene. Then, L1000CDS2 analysis of the gene-expression signatures was employed for drug repurposing studies. CGP71683, an appetite suppressant, was predicted to improve MASLD and may mimic the ASS1 expression pattern induced by an LCD. Molecular dynamics confirmed spontaneous, stable CGP71683-ASS1 complex formation. Overall, this work based on analysis of machine learning algorithms, essential gene identification, and drug repurposing studies suggested that ASS1 is an essential gene in MASLD and CGP71683 is a potential drug candidate for treating MASLD by targeting ASS1 and mimicking the beneficial effects of an LCD. However, due to the inherent limitations of a purely computational approach, further experimental investigation is necessary to validate the anticipated results.

Renal ischemia alters the mRNA and miRNA profile of vasculature-related genes in scattered tubular-like cells from female pigs.

Background: Scattered tubular-like cells (STCs) are renal tubular cells that survive episodes of renal injury and acquire progenitor-like characteristics to repair other damaged kidney cells. STCs release pro-angiogenic factors in culture and induce microvascular proliferation in injured murine kidneys in vivo. Renovascular disease (RVD) compromises the reparative capacity of STCs, but the underlying mechanisms remain unknown. We hypothesized that RVD alters the expression of vasculature-related genes in swine STCs and impair their vasculoprotective properties. Methods: CD24+/CD133+ STCs were harvested from female pig kidneys after 10 weeks of RVD or sham (n=6 each) and the mRNA profiles of vasculature-related genes were analyzed using mRNA and microRNA seq (n=3/group). STC expression of candidate differentially expressed (DE) genes and their capacity to induce human umbilical endothelial cells (HUVECs) to form tube-like networks were subsequently assessed in vitro before and after miRNA modulation (n=6 each). Results: mRNA-seq identified 67 upregulated and 42 downregulated vasculature-related genes in RVD-STCs. Four miRNAs were upregulated and 12 downregulated in RVD-STCs and found to target 31.3% to 40.5% of DE vasculature-related genes. Modulation in vitro of representative miRNAs decreased RVD-STC expression of anti-angiogenic and increased expression of pro-angiogenic target genes, respectively. Further, this restored the ability of STCs to induce HUVEC tube formation on Matrigel that was impaired in RVD. Conclusions: Chronic renal ischemia alters the expression of vasculature-related genes in swine STCs, likely through post-transcriptional mechanisms, impairing their pro-angiogenic activity. These observations may contribute to develop novel approaches to preserve the reparative capacity of STCs in individuals with RVD.

Transcriptomics of Various Diseases Reveals the Core Role of Immune System Pathways in Retinal Damage Repair and Nerve Regeneration.

Retinal ganglion cells (RGCs) are the only neuronal bridges connecting retinal inputs to the brain's visual processing centers, enabling visual perception. The axon of RGCs forms the optic nerve, which transmits visual information to the visual cortex. Damage to RGCs and their axons results in irreversible visual impairment. Acute retinal damage is commonly induced by conditions such as optic nerve compression, glaucoma, and optic neuritis, for which effective clinical treatments are currently unavailable. Therefore, understanding the response of RGCs and their axons to injury is crucial for the development of potential treatments. This study utilizes multiple models including optic nerve crush (ONC), acute intraocular pressure (IOP) elevation, and local lipopolysaccharide (LPS) injection into the optic nerve to mimic eye diseases. Three days post-surgery, mice underwent retinal isolation followed by bulk-RNA sequencing to analyze differential gene expression among models. Using thresholds of |Log2 fold change (FC)|> 2 and p-value < 0.05, the significant gene expression changes observed in each model were as follows: ONC (upregulated, 456; downregulated, 84), IOP (upregulated, 1946; downregulated, 655), and LPS (upregulated, 219; downregulated, 94). Gene ontology (GO) analysis of the upregulated genes unexpectedly revealed that immune system pathways were the primary shared targets across all three models. In contrast, the downregulated genes exhibited model-specific enrichment: synaptic components and functions in IOP, neurogenesis and neuronal development in ONC, and inflammation and antioxidant in LPS. These findings were further confirmed by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. This suggests that managing immune activation is essential for treating acute retinal injury, and therapeutic strategies should address model-specific targets as well. Notably, 39 genes intersected across the models, and the protein-protein interaction (PPI) network identified Ccl5 as a key hub gene, underscoring its critical role in the pathophysiology of all three diseases.

Identification and mechanistic analysis of shared biomarkers and pathogenesis in acute pancreatitis and sepsis based on differential gene expression and protein interaction networks

Acute pancreatitis (AP) is a common gastrointestinal inflammatory disease that requires hospitalization, with 40–70% of patients in moderate to severe stages potentially developing sepsis, which is closely related to high mortality rates and poor prognosis. Therefore, early identification of AP patients at risk of developing sepsis is crucial for reducing mortality. This study aims to identify core genes associated with sepsis to provide new core genes for early warning and management of patients with acute pancreatitis. The study utilized the GSE54514, GSE57065, GSE95233, and GSE194331 datasets for analysis, employing weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network construction. Six core genes were identified using two machine learning methods and validated with the GSE3644 and GSE28750 datasets. The analysis revealed that the identified core genes (NDUFA1, COX7A2, COX7B, UQCRQ, SNRPG, and NDUFA4) are related to the oxidative phosphorylation (OxPhos) pathway, and significant differences were observed in the immune cell composition between AP and sepsis patients. SNRPG may play a role in the progression from AP to sepsis by regulating NDUFA4, linking it to cellular metabolism and redox balance. The newly identified core genes and their associated molecular mechanisms provide important clinical insights into the progression of acute pancreatitis to sepsis, potentially offering new research directions for future therapeutic strategies. Clinical trial number: This study was approved by the Ethics Committee of (Municipal Hospital affiliated to Taizhou University), in accordance with the Declaration of Helsinki. Approval number: LWSL202400220.

Integrative Analysis the Role of ENG as a Metabolic and Macrophage-Related Gene in Hepatocellular Carcinoma.

High levels of M2 macrophages often correlate with poor prognosis. Endoglin (ENG) is a potential target for anti-angiogenesis therapy in various cancers, but the link between M2 macrophages and metabolism-related genes (MRGs) in hepatocellular carcinoma (HCC) is unclear. We employed cibersort analysis to identify genes associated with M2 macrophages and metabolic reprogramming in HCC, utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. TCGA data were stratified basis on ENG expression levels, and the relationships between ENG and relevant genes were assessed alongside clinical features. Furthermore, we validated ENG expression in HCC tissues and its correlation with M2 macrophages via qRT-PCR, Western blotting (WB), and immunohistochemistry (IHC). Patients with high ENG expression presented superior overall survival (OS) and longer progression-free survival (PFS). Univariate and multivariate regression analyses identified ENG as an independent prognostic predictor. Moreover, GSEA, GO, and KEGG analyses suggested a correlation between ENG-related gene expression and immunity, particularly TAMs. Additionally, ENG was found to reshape the tumor microenvironment (TME) of HCC and influence the response to immunotherapy. Single-cell analysis revealed the differential expression and distribution of ENG in the TME. In vitro experiments demonstrated lower ENG expression in HCC tissues than in paracancerous tissues, with a concomitant correlation with M2 macrophages. ENG emerges as a novel predictive marker for HCC, could reshap the TME and impacts the response to immunotherapy and provides a fresh perspective for investigating combined immunotherapy targeting MRGs in HCC.

Single-cell hdWGCNA reveals a novel diagnostic model and signature genes of macrophages associated with chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory system-related mortality worldwide. Although COPD is associated with immune regulation, its underlying mechanisms remain unclear. Cells from the single-cell RNA sequencing (scRNA-seq) datasets were subjected to clustering analysis and cell type identification to isolate immune cell subgroups specifically expressed in COPD. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was used to identify hub genes related to the immune cell subpopulations. Machine learning algorithms were applied to identify diagnostic genes in the immune cell subpopulations and construct clinical diagnostic models for COPD. In bulk RNA sequencing data, AUC curves were used to assess the stability of the diagnostic models in predicting COPD. Through 2 rounds of clustering analysis, the macrophage subgroups 1, 2, 7, 11, and 13 which specifically expressed in COPD (COPD_Mφ) were identified. HdWGCNA analysis revealed a hub set of genes closely related to COPD_Mφ from black, blue, yellow, and brown modules. Nonnegative Matrix Factorization (NMF) analysis separated the COPD samples into 2 clusters, with significant increases in the infiltration of Monocytic_lineage, Myeloid_dendritic_cells, and Neutrophils in cluster 1 (P < 0.001). Univariate logistic regression and LASSO regression analyses identified 11 feature genes associated with COPD_Mφ, including CST3, LGALS3, CSTB, S100A10, CYBA, S100A11, ARPC3, FTH1, PFN1, MAN2B1, and RPL39. The RF and convolutional neural network (CNN) models constructed using these feature genes effectively distinguished between normal and COPD patients. Among them, S100A10, RPL39, and FTH1 exhibited differential expression between COPD patients and normal individuals and could serve as potential clinical diagnostic markers for COPD. The study provides new insights into the immune mechanisms of COPD and lays the theoretical foundation for its future clinical diagnosis and personalized treatment.

Differential Expression of Disulfidptosis-Related Genes in Spinal Cord Injury and Their Role in the Immune Microenvironment.

Spinal cord injury (SCI) often results in severe sensory, motor, and autonomic dysfunction, with limited treatment options due to complex underlying mechanisms. Disulfidptosis, a recently discovered form of cell death driven by disulfide bond accumulation, has been linked to various diseases, but its role in SCI remains unexplored. This study investigates the involvement of disulfidptosis-related genes (DRGs) in SCI to identify potential diagnostic markers and therapeutic targets. Using SCI datasets from the Gene Expression Omnibus (GEO), we conducted differential gene expression analysis, identifying key disulfidptosis-related differentially expressed genes (DRDEGs). Further analysis through gene set enrichment (GSEA) and Bayesian pathway enrichment highlighted significant involvement in pathways such as NF-κB, PI3K/Akt, and MAPK, with an emphasis on nephrin family interactions. Three core DRDEGs-HK2, Map3k8, and S100a6-were identified, and a diagnostic model built on these genes demonstrated strong predictive performance (AUC: 0.896 in training, 0.850 in validation). Additionally, real-time PCR (qRT-PCR) in an animal model validated the elevated expression of these DRDEGs in SCI samples. This research provides novel insights into disulfidptosis in SCI, suggesting these genes as promising targets for improved diagnostic and therapeutic strategies.

Bioinformatics analysis of oxidative phosphorylation-related differentially expressed genes in osteoporosis

BackgroundOsteoporosis (OP) is a common metabolic bone disease characterized by decreased bone mass and increased fracture risk. Recent studies suggest that oxidative phosphorylation (OXPHOS) plays a crucial role in the pathogenesis of OP. This study aims to investigate the differential expression and potential functional roles of OXPHOS-related genes in OP.MethodsWe downloaded gene expression data from two OP-related datasets, GSE56815 and GSE7429, using the GEOquery package. We also collected OXPHOS-related genes from the GeneCards and MsigDB databases. The limma package was used for differential expression analysis of GSE56815, and differentially expressed genes (DEGs) were identified. We intersected these DEGs with OXPHOS-related genes to identify OXPHOS-related differentially expressed genes. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were conducted using the clusterProfiler package. Additionally, we performed gene set enrichment analysis (GSEA). The Mann–Whitney U test analyzed differences in the expression of OXPHOSRDEGs, and their diagnostic potential was assessed by Receiver Operating Characteristic (ROC) curves. Correlation analysis, Protein–Protein Interaction (PPI) network construction, mRNA-miRNA, mRNA-TF interaction network construction, and immune infiltration analysis using CIBERSORT were also conducted. RAW264.7 cells were induced in vitro for 3 days to differentiate towards osteoblasts, and RT-PCR assay was used to verify the differentiation and detect the differential expression of target genes.ResultsOur results identified 31 DEGs in GSE56815, with 26 upregulated and 5 downregulated genes. Among these, we identified 10 OXPHOSRDEGs: VPS35, TBC1D2, UBQLN2, SH3GLB2, WWP1, NFKBIA, MFSD10, SLC2 A3, RP2, and ZNF91. GO and KEGG enrichment analyses revealed significant involvement of these genes in mechanisms such as the positive regulation of the protein catabolic process and the endocytosis pathway. ROC analysis demonstrated high diagnostic accuracy for VPS35 (AUC = 0.832) and TBC1D2 (AUC = 0.751). Correlation analysis indicated strong relationships between certain OXPHOSRDEGs. The PPI network highlighted 8 hub genes with significant functional similarity among them.ConclusionThis study systematically elucidates the differential expression and potential mechanisms of OXPHOS-related genes in OP through comprehensive bioinformatics analyses. The identified key genes offer valuable insights into the molecular underpinnings of OP and present potential diagnostic biomarkers and therapeutic targets for further investigation.

Transcriptomic profiles of Crandell-Rees feline kidney cells infected with Varicellovirus felidalpha-1 (FHV-1) field and vaccine strains

BackgroundVaricellovirus felidalpha-1 (FHV-1, previously Felid alphaherpesvirus-1) is a significant cause of upper respiratory tract disease in feline populations. Cats infected with FHV-1 show clinical signs that vary in severity. This can be due to differences in host responses and virus strain virulence. Investigating the gene transcription profiles during infections using FHV-1 strains could inform our understanding of host and viral factors contributing to disease outcomes. This study characterised the transcriptomes of Crandell–Rees feline kidney (CRFK) cells infected with field or vaccine FHV-1 strains to better understand the host response during infection.MethodsCrandell–Rees feline kidney cells were infected with either the FHV-1 F2 vaccine strain or the 384/75 field strain associated with severe disease. The transcriptomes were characterised using RNA-sequencing. To determine the host cellular transcription profile, the total transcripts were mapped to the cat genome and compared to uninfected cells. To characterise the viral transcription profile, the total reads were mapped to each FHV-1 strain. The differentially expressed host genes between infection strains were compared and further analysed using the PANTHER database to examine host pathway regulation.ResultsThe findings in this study show the differential host gene expressions induced by FHV-1 compared to uninfected CRFK cells. Genes encoding histone proteins were upregulated, while genes involved in cell adhesion and migration processes were downregulated during infections with FHV-1. Comparative analysis between field and vaccine strains showed similarities and differences in host gene expressions. Notably, upregulated genes unique to the field strain were associated with regulatory proteins involved in the cell cycle, while downregulated host genes in field and vaccine strains showed distinct host gene and pathway expressions involved in immune activation.ConclusionsThis study demonstrates the host and viral gene expressions during FHV-1 infection shows the distinct host responses to field and vaccine strains using an in vitro model. These findings provide a foundation for future transcriptomic investigations in other cell types, including ex-vivo explants systems, to enhance our understanding of host and viral factors contributing to disease outcomes.

A detailed transcriptome study uncovers the epigenetic characteristics associated with Aromatase inhibitor-induced masculinization in Takifugu rubripes larvae gonads

BackgroundTakifugu rubripes is an economically valuable fish species in Asia. The implementation of all-male culture for T. rubripes is highly anticipated in aquaculture. Aromatase inhibitor (AI, letrozole) treatment was found to be an efficient method to induced masculinization in T. rubripes, as reported in our previous study. Here, to further explore the underlying regulation mechanism of AI-induced masculinization, a whole-transcriptome analysis comparing was conducted between AI-induced masculinized XX (AI-XX) gonads and control (Con) gonads in T. rubripes.ResultsIn Con-XX/Con-XY comparison, 1,172 differential expression (DE) mRNAs, 129 DEmiRNAs, 210 DElncRNAs, and 4 DEcircRNAs were identified. In the Con-XX/AI-XX comparison, 1,329 DEmRNAs, 174 DEmiRNAs, 6 DEcircRNAs and 280 DElncRNAs were found. Con-XX/Con-XY and Con-XX/AI-XX comparisons shared 690 DEmRNAs, 50 DEmiRNAs, 3 DEcircRNAs, and 105 DElncRNAs. The analyses of protein-protein interaction (PPI) and competitive endogenous RNA (ceRNA) network identified interactions among these shared DERNAs. Kcnh2b, trim27, cnnm2b, reln, cckbra, pkd1l2, steap4, gsg1l, hamp, and foxg1c were predicted as the top ten of hub genes. miRNAs included miRNA-27 family and miRNA-489 family showed targeting relationship with hub genes. GO and KEGG functional enrichment analysis showed that the targeted genes were mainly enriched in GO:0065008 regulation of biological quality and TGF-beta signaling pathway. qPCR validation confirmed the differential expression of selected mRNAs, and ncRNAs.ConclusionsThis research comprehensively reveals the potential regulatory effects of ncRNAs on cellular motility, fate regulation, and hormonal regulation during gonadal masculinization in T. rubripes. It may provide significant insights into the regulation mechanisms underlying sex reversal in fish.

The use of immunohistochemical labeling to identify patterns of proliferation and protein expression in smooth muscle tumors of the uterus

ABSTRACT Leiomyomas (fibroids) are the most common benign tumors of the uterus and are present in greater than half the female population over 50 years old in the United States. Leiomyosarcomas are the malignant variation of leiomyomas and, while far less common, have a high mortality rate. Differential protein expression between both benign and malignant tumors and normal tissue samples forms the basis of many treatment strategies. This study evaluated protein expression of several markers using immunohistochemistry (IHC) methods on 74 leiomyomas, 14 uterine leiomyosarcomas, and 26 normal uterine myometrial samples which had been formalin-fixed and paraffin-embedded. Markers included the Ki-67 proliferation marker, estrogen receptor (ER), progesterone receptor (PR), aldehyde dehydrogenase (ALDH), B-cell lymphoma 2 (BCL-2), and cytokeratin 8/18 (CK 8/18). The Ki-67 positivity was significantly higher in leiomyosarcomas when compared with benign uterine tissues and was also higher in leiomyomas than in normal uterine smooth muscle. ER and PR were highly expressed in benign tissues but exhibited reduced expression in malignant lesions. Both CK 8/18 and ALDH were expressed in a significantly higher proportion of normal myometrial tissues as compared with leiomyomas and leiomyosarcomas. Conversely, BCL-2 expression in normal tissues was lower than in both leiomyomas and leiomyosarcomas with leiomyosarcomas producing the highest expression. The Ki-67 value can reliably differentiate between benign and malignant smooth muscle uterine tissues. Because CK 8/18 and ALDH were more frequently or strongly expressed in normal myometrium vs. leiomyoma or leiomyosarcoma, pathological changes to the cells may be the cause for a reduction in protein production. Future investigations may determine that upregulation of either of these two markers in leiomyomas or leiomyosarcomas could lead to slower tumor growth.

Genome-wide identification and unveiling the role of MAP kinase cascade genes involved in sugarcane response to abiotic stressors

BackgroundThe MAP Kinase cascade system is a conserved signaling mechanism essential for plant development, growth, and stress tolerance. Thus far, genes from the MAPK cascade have been identified in several plant species but remain uncharacterized in the polyploid Saccharum spp. Hybrid R570 genome.ResultsThis study identified 89 ScMAPK, 24 ScMAPKK, and 107 ScMAPKKK genes through genome-wide analysis. Phylogenetic classification revealed that four subgroups were present in each ScMAPK and ScMAPKK family, and three sub-families (ZIK-like, RAF-like, and MEKK-like) presented in the ScMAPKKK family. Conserved motif and gene structure analysis supported the evolutionary relationships of the three families inferred from the phylogenetic analysis. All of the ScMAPK, ScMAPKK and ScMAPKKK genes were mapped on four scaffolds (Scaffold_88/89/91/92) and nine chromosomes (1–8, 10). Collinearity and gene duplication analysis identified 169 pairs of allelic and non-allelic segmentally duplicated MAPK cascade genes, contributing to their expansion. Additionally, 13 putative ‘ss-miRNAs’ were predicted to target 87 MAPK cascade genes, with ‘ssp-miR168a’ alone regulating 45 genes. qRT-PCR analysis revealed differential gene expression under abiotic stressors. ScMAPK07, ScMAPK66, and ScRAF43 were down-regulated and acted as negative regulators. Conversely, ScMAPKK13, ScRAF10, and ScZIK18 were up-regulated at specific time points under drought, with ScZIK18 exhibiting strong defense. Under NaCl stress, most genes were down-regulated, except for slight increases in ScZIK18 and ScMAPKK13, suggesting a positive role in salt stress response. Under CaCl2 stress, five genes were significantly down-regulated, while ScRAF43 remained unchanged, reflecting their negative roles in stress adaptation and resource conservation.ConclusionThis study provides insights into MAPK cascade gene evolution and function in sugarcane, highlighting distinct regulatory roles in abiotic stress responses. Interestingly, some genes acted as negative regulators, serving as a mechanism to balance stress responses and prevent overactivation. In contrast, others contributed to defense mechanisms, offering potential targets for stress resilience improvement.Clinical Trail NumberThis study contains no clinical trials. Not applicable.

Deciphering the heterogeneity of epithelial cells in pancreatic ductal adenocarcinoma: implications for metastasis and immune evasion

ObjectiveThis study examines the cellular heterogeneity of epithelial cells within pancreatic ductal adenocarcinoma (PDAC) and their contributions to tumor progression, metastasis, and immunosuppressive interactions using single-cell RNA sequencing.MethodsSingle-cell RNA-sequencing data from two datasets (GSE154778 and GSE158356) were integrated using the Harmony algorithm, followed by quality control, clustering, and differential gene expression analysis. Distinct subpopulations of epithelial cells were identified, and their gene expression profiles were analyzed. To assess the malignancy of these subpopulations, single-cell copy number variation (CNV) analysis and trajectory analysis were conducted. Additionally, intercellular communication was examined using the CellChat platform.ResultsThe analysis revealed pronounced heterogeneity among PDAC epithelial cells, with specific subpopulations exhibiting distinct roles in tumor proliferation, extracellular matrix remodeling, and metastatic dissemination. Subpopulations 4 and 6 were characterized by increased CNV levels and a more malignant phenotype, suggesting an enhanced capacity for metastasis. Single-cell trajectory analysis, along with CellChat, mapped the temporal evolution of epithelial cells, identifying key regulatory genes such as DCBLD2 and JUN. A prognostic model incorporating five key genes, including KLF6, was developed and demonstrated strong predictive accuracy for patient outcomes. Notably, KLF6 emerged as a critical prognostic marker associated with immune modulation, particularly through interactions with M2 macrophages.ConclusionThe study highlights the pronounced heterogeneity of epithelial cells in PDAC and their distinct contributions to tumor progression, metastasis, and immune modulation. Through single-cell transcriptomic and CNV analyses, we identified epithelial subpopulations with varying malignant potentials and distinct interactions with the tumor microenvironment. Among these, KLF6 emerged as a key regulator associated with immune modulation and metastasis. Our findings emphasize the significance of epithelial cell heterogeneity in shaping pancreatic cancer progression. These insights provide a foundation for future investigations into novel prognostic markers and therapeutic strategies.

Elucidating the role of lipid metabolism dysregulation in the transition from oral lichen planus to oral squamous cell carcinoma

BackgroundOral Lichen Planus (OLP) is a chronic inflammatory disorder that may progress to Oral Squamous Cell Carcinoma (OSCC). Lipid metabolism dysregulation has been implicated in tumor development and immune response modulation. This study aims to explore the role of lipid metabolism, particularly the lipids diacylglycerol (DAG), triacylglycerol (TAG), and phosphatidylcholine (PC), in the progression from OLP to OSCC, and to identify potential therapeutic targets for prevention and treatment.MethodsWe performed a Mendelian randomization (MR) analysis to investigate the causal relationships between lipid metabolism and the risk of OLP and OSCC. Differential gene expression analysis was conducted to identify key genes related to lipid metabolism. The interactions of lipid species and key genes were examined using drug databases (DrugBank, DGIdb, and TCMSP) to explore potential drug candidates. Enrichment analysis of signaling pathways, including PPAR signaling, was also conducted to understand the underlying mechanisms.ResultsOur MR analysis revealed that DAG exerts a protective effect in OLP (OR < 1), but its role shifts to a risk factor in OSCC (OR > 1), potentially by altering the tumor immune microenvironment. TAG and PI dysregulation also plays a critical role in tumorigenesis. Gene expression analysis identified several key lipid metabolism-related genes, including SLC27A6, FABP3, FABP4, ADIPOQ, and PLIN1, whose expression differed between OLP and OSCC, highlighting their importance in tumor progression. These genes were enriched in the PPAR signaling pathway, suggesting its involvement in tumor growth and immune modulation. Potential drug candidates, such as palm acid (PA), Imatinib, and Curcumin, were identified through drug-repurposing strategies.ConclusionLipid metabolism dysregulation plays a crucial role in the progression of OLP to OSCC. Targeting key lipid metabolism pathways and genes, such as DAG, TAG, PI, and the PPAR pathway, may offer promising strategies for early diagnosis and therapeutic intervention. This study provides novel insights into the molecular mechanisms of OLP-to-OSCC progression and suggests potential drug candidates, including natural compounds, for future clinical applications. Further research is needed to validate these findings in clinical settings.Clinical trial numberNot applicable.

Variability in sensitivity to inflammation in muscle and lung of patients with COPD may underlie susceptibility to lung function decline

BackgroundMuscle wasting and weakness (sarcopenia) are commonly associated with COPD causing frailty and reduced quality of life. The contribution of inflammation to muscle loss and the susceptibility to rapid lung...

Heterogeneity-preserving discriminative feature selection for disease-specific subtype discovery

Disease-specific subtype identification can deepen our understanding of disease progression and pave the way for personalized therapies, given the complexity of disease heterogeneity. Large-scale transcriptomic, proteomic, and imaging datasets create opportunities for discovering subtypes but also pose challenges due to their high dimensionality. To mitigate this, many feature selection methods focus on selecting features that distinguish known diseases or cell states, yet often miss features that preserve heterogeneity and reveal new subtypes. To overcome this gap, we develop Preserving Heterogeneity (PHet), a statistical methodology that employs iterative subsampling and differential analysis of interquartile range, in conjunction with Fisher’s method, to identify a small set of features that enhance subtype clustering quality. Here, we show that this method can maintain sample heterogeneity while distinguishing known disease/cell states, with a tendency to outperform previous differential expression and outlier-based methods, indicating its potential to advance our understanding of disease mechanisms and cell differentiation.

An integrated bioinformatics and machine learning approach to identifying biomarkers connecting parkinson’s disease with purine metabolism-related genes

BackgroundParkinson’s disease (PD), a prevalent neurodegenerative disorder in the aging population, poses significant challenges in unraveling its pathogenesis and progression. A key area of investigation is the disruption of oncological metabolic networks in PD, where diseased cells display distinct metabolic profiles compared to healthy counterparts. Of particular interest are Purine Metabolism Genes (PMGs), which play a pivotal role in nucleic acid synthesis.MethodsIn this study, bioinformatics analyses were employed to identify and validate PMGs associated with PD. A set of 20 candidate PMGs underwent differential expression analysis. GSEA and GSVA were conducted to explore the biological roles and pathways of these PMGs. Lasso regression and SVM-RFE methods were applied to identify hub genes and assess the diagnostic efficacy of the nine PMGs in distinguishing PD. The correlation between these hub PMGs and clinical characteristics was also explored. Validation of the expression levels of the nine identified PMGs was performed using the GSE6613 and GSE7621 datasets.ResultsThe study identified nine PMGs related to PD: NME7, PKM, RRM2, POLR3 C, POLA1, PDE6 C, PDE9 A, PDE11 A, and AMPD1. Biological function analysis highlighted their involvement in processes like neutrophil activation and immune response. The diagnostic potential of these nine PMGs in differentiating PD was found to be substantial.ConclusionsThis investigation successfully identified nine PMGs associated with PD, providing valuable insights into potential novel biomarkers for this condition. These findings contribute to a deeper understanding of PD’s pathogenesis and may aid in monitoring its progression, offering a new perspective in the study of neurodegenerative diseases.

LncRNA-CR848007.6 regulates the translatome of Cadmium malignant transformed 16HBE cells from a biomechanical perspective

Background: Previous studies found that cadmium (Cd) was an environmental toxicant that not only induces toxicological effects but also disrupts cellular biomechanics, affecting cell stiffness, motility, and mechanotransduction pathways. LncRNA-CR848007.6 played an important regulatory role in cadmium toxicology. However, whether its regulatory mechanism involves the biomechanics and changes of the translatome remains to be elucidated. Objective: This study aimed to explore the function and mechanism of LncRNA-CR848007.6 in translation regulation and biomechanical properties during cadmium malignant transformed human bronchial epithelial cells (16HBE cells) through translatome sequencing techniques and bioinformatics methods. Methods: RNA interference technology was applied to silence the expression of LncRNA-CR848007.6 in cadmium malignant transformed 16HBE cells. The libraries of mRNA and RNC were constructed, and Ion Proton™ Sequencer was used for transcriptome and translatome sequencing. Mechanical properties of cells, including stiffness and traction forces, were measured using atomic force microscopy and traction force microscopy. Transcriptome and translatome differential expressions were analyzed using R software. The cell cycle and apoptosis were detected by flow cytometry to verify the functions of LncRNA-CR848007.6 regulating the translatome of cadmium malignant transformed 16HBE cells. Results: Four libraries were obtained after sequencing, including 24062 genes from the transcriptome of the siR mR group cell and NC mR group cell, the translatome of siR RNC group cell and the NC-RNC group cell. It was found that there was little change in the number of transcriptome genes between the siR RNC group cell and NC-RNC group cell, with 19 differentially expressed genes downregulated and 0 differentially expressed genes upregulated. There were 114 genes in the translatome with a ration &lt; −2 and 65 genes in the translatome with a ratio &gt; 2. There was no intersection between the differential TR expression genes and differential mRNA expression genes. The GO analysis results showed significant changes in the translation ratio of cell cycle and mitotic-related pathways, but no enriched KEGG pathway appeared. The cell cycle progression was regulated and cell apoptosis was signficantly inhibited (P &lt; 0.05) after silencing lncRNA-CR848007.6 by siRNA in CdCl2 malignant transformed 16HBE cells. Transcriptome and translatome analyses revealed differential expression of genes involved in cytoskeletal organization and mechanosensitive signaling. Conclusion: LncRNA-CR848007.6 plays a critical role in modulating the biomechanical properties of cadmium-malignant transformed 16HBE cells, influencing cell stiffness and motility through translational regulation. This study provides insights into the biomechanical mechanisms underlying lncRNA-mediated cellular responses to cadmium toxicity.

Construction and diagnostic efficacy assessment of the urinary exosomal miRNA-mRNA network in children with IgA vasculitis nephritis.

This study aimed to comprehensively evaluate the diagnostic potential of urinary exosomal microRNA (miRNA) in IgA vasculitis (IgAV) kidney injury by meticulously comparing the miRNA expression profiles in urine exosomes between children diagnosed with IgAV and those with IgA vasculitis nephritis (IgAVN). Urine samples were obtained from children with IgAV who were treated at our hospital from October 2022 to October 2023. These samples were then categorized into the IgAV group and the IgAVN group. High-throughput sequencing and bioinformatics analysis techniques were employed to conduct a thorough analysis of the differentially expressed miRNAs between the two groups. Additionally, the correlation between urinary exosomal miRNA and clinical parameters was evaluated. A total of 57 urinary exosomal miRNAs exhibited differential expression between the IgAV and IgAVN groups. Specifically, in the IgAVN group, 42 miRNAs were upregulated, while 15 were downregulated. Lasso regression analysis and ROC analysis identified five candidate urinary exosomal miRNAs with high diagnostic accuracy. A prediction of 95 target genes related to the candidate miRNAs led to the construction of an exosomal miRNA-mRNA regulatory network consisting of four key miRNAs and ten hub genes. Gene function and metabolic pathway analyses indicated that these ten hub genes were predominantly enriched in pro-fibrotic and inflammatory pathways. The analysis incorporating clinical parameters demonstrated a significant correlation between hsa-miR-383-5p and urinary protein levels. This research identified exosomal miRNAs and mRNAs with differential expression patterns associated with IgAVN and constructed the corresponding exosomal miRNA-mRNA network. It was determined that hsa-miR-3065-5p, hsa-miR-383-5p, hsa-miR-25-3p, and hsa-miR-450b-5p might mediate the pathogenesis of IgAVN by targeting pro-fibrotic and inflammatory pathways. Among them, exosomal hsa-miR-383-5p is highly likely to serve as a novel non-invasive biomarker for assessing the disease status of IgAVN, thereby offering new perspectives on the non-invasive diagnosis and treatment of IgAVN.

Dynamic transcriptome and metabolome analyses of two sweet corn lines under artificial aging treatment

BackgroundStrong tolerance to seed aging is an important agricultural trait for sweet corn production. Previous studies have primarily focused on the QTLs for the seed vigor. However, there were few researches involving in the metabolome and transcriptome of artificial aging seeds.ResultsUsing two inbred lines with significant differences in seed artificial aging tolerance, RNA sequencing and non-targeted metabolomic analysis were employed to extensively evaluate transcripts and metabolites in seeds that underwent artificial aging. Fourteen common transcripts and 16 common metabolites with sustained differential expression were identified in the two lines, suggesting their potential necessity in seed response to artificial aging. Enrichment analysis of differentially expressed genes (DEGs) in the transcriptome at different stages revealed significant enrichment KEGG pathways, “Oxidative phosphorylation” was the common pathway in the 0d vs 3d comparison for K107 and L155. The identical enriched KEGG pathways were observed in the 3d vs 6d comparison for K107 and 0d vs 6d comparison for L155, indicating a slower transcriptomic response in the aging-tolerance line. DEGs at 0 days between the two lines had been enriched in the “Terpenoid backbone biosynthesis” and “Ribosome” pathways, while at 6 days, the enrichment pathway were “Sulfur metabolism”, “Linoleic acid metabolism”, and “Plant hormone signal transduction”. A total of 312 differentially expressed metabolites (DEMs) were found at 0, 3 and 6 days after seed aging treatment, and they shared enriched metabolic pathway of “ABC transporters”. The KEGG enrichment of DEGs and DEMs shared the common pathway, namely “Linoleic acid metabolism”. Among these, the most abundant metabolites were Glutathione, Adenosine, Trehalose, and 10E,12Z-Octadecadienoic acid. Focusing on the ascorbate–glutathione pathway revealed that the difference in ROS production and the ROS scavenging capability mediated by glutathione S-transferase (GST) genes were important factors contributing to the differing seed aging tolerance in the two lines.ConclusionIn summary, these results contribute to a deeper understanding of the overall mechanisms underlying artificial aging tolerance in sweet corn seeds. The findings of this study are expected to provide valuable insights for the storage of sweet corn seeds.