Osteoarthritis (OA) is a comprehensive joint disorder. The specific genes that trigger OA and the strategies for its effective management are not fully understood. This study focuses on identifying key genes linked to iron metabolism that could influence both the diagnosis and therapeutic approaches for OA. Analysis of GEO microarray data and iron metabolism genes identified 15 ferroptosis-related DEGs, enriched in hypoxia and HIF-1 pathways. Ten key hub genes (ATM, GCLC, PSEN1, CYBB, ATG7, MAP1LC3B, PLIN2, GRN, APOC1, SIAH2) were identified. Through stepwise regression, we screened 4 out of the above 10 genes, namely, GCLC, GRN, APOC1, and SIAH2, to obtain the optimal model. AUROCs for diagnosis of OA for the four hub genes were 0.81 and 0.80 of training and validation sets, separately. According to immune infiltration results, OA was related to significantly increased memory B cells, M0 macrophages, regulatory T cells, and resting mast cells but decreased activated dendritic cells. The four hub genes showed a close relation to them. It is anticipated that this model will aid in diagnosing osteoarthritis by assessing the expression of specific genes in blood samples. Moreover, studying these hub genes may further elucidate the pathogenesis of osteoarthritis.

Renal cell carcinoma (RCC) is characterized by high mortality and morbidity rates. Vav guanine nucleotide exchange factors (VAVs), crucial for signal transduction between cell membrane receptors and intracellular mediators, have been implicated in carcinogenesis. However, their potential prognostic value in RCC remains unclear. The impact of 150 common VAV polymorphisms on RCC risk and survival was investigated in a cohort of 630 individuals. Publicly available gene expression datasets were utilized to analyze VAV gene expression in relation to patient outcomes. The VAV3 rs17019888 polymorphism was significantly associated with RCC risk and overall survival after adjusting for false discovery rates. Expression quantitative trait loci analysis revealed that the risk allele of rs17019888 is linked to reduced VAV3 expression. Analysis of 19 kidney cancer gene expression datasets revealed lower VAV3 expression in RCC tissues compared to normal tissues, with higher expression correlating with better prognosis. Gene set enrichment analysis demonstrated that VAV3 negatively regulates the ubiquitin-proteasome system, extracellular matrix and membrane receptors, inflammatory responses, matrix metalloproteinases, and cell cycle pathways. Furthermore, elevated VAV3 expression was associated with increased infiltration of B cells, macrophages, and neutrophils into the RCC tumor microenvironment. Our findings suggest that VAV3 gene variants influence RCC risk and survival, contributing to a favorable prognosis in RCC.

Advancements in sequencing technologies have facilitated omics level information generation for various diseases in human. High-throughput technologies have become a powerful tool to understand differential expression studies and transcriptional network analysis. An understanding of complex transcriptional networks in human diseases requires integration of datasets representing different RNA species including microRNA (miRNA) and messenger RNA (mRNA). This review emphasises on conceptual explanation of generalized workflow and methodologies to the miRNA mediated responses in human diseases by using different in silico analysis. Although, there have been many prior explorations in miRNA-mediated responses in human diseases, the advantages, limitations and overcoming the limitation through different statistical techniques have not yet been discussed. This review focuses on miRNAs as important gene regulators in human diseases, methodologies for miRNA-target gene prediction and data driven methods for enrichment and network analysis for miRnome-targetome interactions. Additionally, it proposes an integrative workflow to analyse structural components of networks obtained from high-throughput data. This review explains how to apply the existing methods to analyse miRNA-mediated responses in human diseases. It addresses unique characteristics of different analysis, its limitations and its statistical solutions influencing the choice of methods for the analysis through a workflow. Moreover, it provides an overview of promising common integrative approaches to comprehend miRNA-mediated gene regulatory events in biological processes in humans. The proposed methodologies and workflow shall help in the analysis of multi-source data to identify molecular signatures of various human diseases.

Given the importance of peroxisome proliferator-activated receptor (PPAR)-gamma in epidermal inflammation and carcinogenesis, we analyzed the transcriptomic changes observed in epidermal PPARγ-deficient mice (Pparg-/-epi). A gene set enrichment analysis revealed a close association with epithelial malignancy, inflammatory cell chemotaxis, and cell survival. Single-cell sequencing of Pparg-/-epi mice verified changes to the stromal compartment, including increased inflammatory cell infiltrates, particularly neutrophils, and an increase in fibroblasts expressing myofibroblast marker genes. A comparison of transcriptomic data from Pparg-/-epi and publicly available human and/or mouse actinic keratoses (AKs) and cutaneous squamous cell carcinomas (SCCs) revealed a strong correlation between the datasets. Importantly, PPAR signaling was the top common inhibited canonical pathway in AKs and SCCs. Both AKs and SCCs also had significantly reduced PPARG expression and PPARγ activity z-scores. Smaller reductions in PPARA expression and PPARα activity and increased PPARD expression but reduced PPARδ activation were also observed. Reduced PPAR activity was also associated with reduced PPARα/RXRα activity, while LPS/IL1-mediated inhibition of RXR activity was significantly activated in the tumor datasets. Notably, these changes were not observed in normal sun-exposed skin relative to non-exposed skin. Finally, Ppara and Pparg were heavily expressed in sebocytes, while Ppard was highly expressed in myofibroblasts, suggesting that PPARδ has a role in myofibroblast differentiation. In conclusion, these data provide strong evidence that PPARγ and possibly PPARα represent key tumor suppressors by acting as master inhibitors of the inflammatory changes found in AKs and SCCs.

OBJECTIVE: This study aims to explore the potential mechanism by which Botulinum toxin type A (BoNT/ A) inhibits microglial inflammatory activation through P2X7 receptors (P2X7R).
BACKGROUND: BoNT/A is a promising analgesic drug, and previous studies have established that it alleviates Neuropathic Pain (NP) by inhibiting microglial inflammatory activation. This study examined the biomarkers and potential mechanisms by which BoNT/A relieves neuropathic pain by mediating microglial P2X7R and analyzing transcriptome sequencing data from mouse BV-2 microglial cells.
OBJECTIVE: The P2X7R agonist Bz-ATP was used to induce microglial inflammatory activation, whilst RNAseq technology was used to explore the biomarkers and potential mechanisms through which BoNT/A suppresses microglial inflammation.
METHODS: RNA sequencing was performed on three BV-2 cell samples treated with a P2X7R specific activator (Bz-ATP) and three BV-2 cell samples pre-treated with BoNT/A. Only data that successfully passed quality control measures were included in subsequent analysis. Initially, Differentially Expressed Genes (DEGs) were identified from BoNT/A and control samples, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Biomarkers were then identified by constructing a Protein- Protein Interaction (PPI) network and utilizing the CytoHubba plug-in in Cytoscape software. Lastly, enrichment analysis and regulatory network analysis were performed to elucidate the potential mechanism of BoNT/A in the treatment of NP.
RESULTS: 93 DEGs related to the \"cell component size regulation\" GO term and enriched in the \"axon guidance\" KEGG pathway were identified. Subsequently, 6 biomarkers were identified, namely PTPRF, CHDH, CKM, Ky, Sema3b, and Sema3f, which were enriched in pathways related to biosynthesis and metabolism, disease progression, signal transduction, and organelle function, including the \"ribosome\" and \"Wnt signaling pathway.\" Finally, a competing endogenous RNA (ceRNAs) network was constructed from 6 mRNAs, 66 miRNAs, and 31 lncRNAs, forming a complex relationship network.
CONCLUSIONS: Six genes (PTPRF, Sema3b, Sema3f, CHDH, CKM, and Ky) were identified as biomarkers of microglial inflammatory activation following BoNT/A treatment. This finding may provide a valuable reference for the relief and treatment of neuropathic pain.

Prostate cancer (PCa) is the second most prevalent malignancy in men worldwide. The risk factors for PCa include obesity, age and family history. Increased visceral fat has been associated with high PCa risk, which has prompted previous researchers to investigate the influence of body composition and fat distribution on PCa prognosis. However, there is a lack of studies focusing on the mechanisms and interactions between periprostatic adipose tissue (PPAT) and PCa cells. The present study investigated the association between the composition of pelvic adipose tissue and PCa aggressiveness to understand the role played by this tissue in PCa progression. Moreover, PPAT-conditioned medium (CM) was prepared to assess the influence of the PPAT secretome on the pathophysiology of PCa. The present study included 50 patients with localized PCa who received robot-assisted radical prostatectomy. Medical records were collected, magnetic resonance imaging scans were analyzed and body compositions were calculated to identify the associations between adipose tissue volume and clinical PCa aggressiveness. In addition, CM was prepared from PPAT and perivesical adipose tissue (PVAT) collected from 25 patients during surgery, and its effects on the PCa cell lines C4-2 and LNCaP, and the prostate epithelial cell line PZ-HPV-7, were investigated using a cell proliferation assay and RNA sequencing (RNA-seq). The results revealed that the initial prostate-specific antigen level was significantly correlated with pelvic and periprostatic adipose tissue volumes. In addition, PPAT volume was significantly higher in patients with extracapsular tumor extension. PCa cell proliferation was significantly reduced when the cells were cultured in PPAT-CM compared with when they were cultured in control- and PVAT-CM. RNA-seq revealed that immune responses, and the cell death and apoptosis pathways were enriched in PPAT-CM-cultured cells indicating that the cytokines or other factors secreted from PPAT-CM induced PCa cell apoptosis. These findings revealed that the PPAT secretome may inhibit PCa cell proliferation by activating immune responses and promoting cancer cell apoptosis. This mechanism may act as a first-line defense during the early stages of PCa.

UNASSIGNED: Ulcerative colitis (UC) and Crohn\'s disease (CD) are chronic inflammatory bowel diseases (IBDs) with an incompletely understood etiology and pathogenesis. Identification of suitable drug targets and assessment of disease severity are crucial for optimal management.
UNASSIGNED: Using RNA sequencing, we investigated differential gene expression in peripheral blood samples from IBD patients and non-inflamed controls, analyzed pathway enrichment, and identified genes whose expression correlated with endoscopic disease severity.
UNASSIGNED: Neutrophil degranulation emerged as the most significant pathway across all IBD sample types. Signaling by interleukins was prominent in patients with active intestinal inflammation but also enriched in CD and UC patients without intestinal inflammation. Nevertheless, genes correlated to endoscopic disease severity implicated the primary cilium in CD patients and translation and focal adhesion in UC patients. Moreover, several of these genes were located in genome-wide associated loci linked to IBD, cholesterol levels, blood cell counts, and levels of markers assessing liver and kidney function. These genes also suggested connections to intestinal epithelial barrier dysfunction, contemporary IBD drug treatment, and new actionable drug targets. A large number of genes associated with endoscopic disease severity corresponded to noncoding RNAs.
UNASSIGNED: This study revealed biological pathways associated with IBD disease state and endoscopic disease severity, thus providing insights into the underlying mechanisms of IBD pathogenesis as well as identifying potential biomarkers and therapies. Peripheral blood might constitute a suitable noninvasive diagnostic sample type, in which gene expression profiles might serve as indicators of ongoing mucosal inflammation, and thus guide personalized treatment decisions.

Breastfeeding by mothers with gestational diabetes mellitus (GDM) has been shown to reduce maternal insulin demands and diminish the risks of diabetes in infants, leading to improved long-term health outcomes. Milk fat globule membrane (MFGM) proteins play a crucial role in influencing the immunity and cognitive development of infants. Understanding the alterations in MFGM proteins in breastmilk from mothers with GDM is essential for enhancing their self-efficacy and increase breastfeeding rates. The objective of this study is to investigate and compare MFGM proteins in milk from mothers with GDM and without based on tandem mass tag (TMT) labeling and liquid chromatography tandem mass spectrometry (LC-MS) techniques. A total of 5402 proteins were identified, including 4 upregulated proteins and 24 downregulated proteins. These significantly altered proteins were found to be associated with human diseases, cellular processes, and metabolism pathways. Additionally, the oxidative phosphorylation pathway emerged as the predominant pathway through Gene Set Enrichment Analysis (GSEA) involving all genes.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social and communication difficulties, along with repetitive behaviors. While genetic factors play a significant role in ASD, the precise genetic landscape remains complex and not fully understood, particularly in non-syndromic cases. The study performed an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB were utilized to identify relevant gene subset and genetic variations associated with non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis were conducted to elucidate the biological significance of the identified genes. The integrity of ASD-related gene subset and the distribution of their variations were statistically assessed. A subset of twenty overlapping genes potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment of biological processes related to neuronal development and differentiation, synaptic function, and social skills, highlighting their importance in ASD pathogenesis. PPI network analysis demonstrated functional relationships among the identified genes. Analysis of genetic variations showed predominance of rare variants and database-specific distribution patterns. The results provide valuable insights into the genetic landscape of ASD and outline the genes and biological processes involved in the condition, while taking into account that the study relied exclusively on in silico analyses, which may be subject to biases inherent to database methodologies. Further research incorporating multi-omics data and experimental validation is warranted to enhance our understanding of non-syndromic ASD genetics and facilitate the development of targeted research, interventions and therapies.

OBJECTIVE: To explore the pathogenic mechanisms of Candida albicans (C. albicans), focusing on its impact on human health, particularly through invasive infections in the gastrointestinal and respiratory tracts.
METHODS: In this study, we evaluated the demographic and clinical profiles of 7 pneumonia patients. Meanwhile, we used Gene Set Enrichment Analysis (GSEA) and Evolutionary Dynamics method to analyze the role of candidalysin in C. albicans pathogenicity.
RESULTS: By analyzing genomic data and conducting biomedical text mining, we identified novel mutation sites in the candidalysin coding gene ECE1-III, shedding light into the genetic diversity within C. albicans strains and their potential implications for antifungal resistance. Our results revealed significant associations between C. albicans and respiratory as well as gastrointestinal diseases, emphasizing the fungus\'s role in the pathogenesis of these diseases. Additionally, we identified a new mutation site in the C. albicans strain YF2-5, isolated from patients with pneumonia. This mutation may be associated with its heightened pathogenicity.
CONCLUSIONS: Our research advances the understanding of C. albicans pathogenicity and opens new avenues for developing targeted antifungal therapies. By focusing on the molecular basis of fungal virulence, we aim to contribute to the development of more effective treatment strategies, addressing the challenge of multidrug resistance in invasive fungal infections.