Identification of Key lncRNAs in Gout Under Copper Death and Iron Death Mechanisms: A Study Based on ceRNA Network Analysis and Random Forest Algorithm.

This study focused on identifying potential key lncRNAs associated with gout under the mechanisms of copper death and iron death through ceRNA network analysis and Random Forest (RF) algorithm, which aimed to provide new insights into the molecular mechanisms of gout, and potential molecular targets for future therapeutic strategies of gout. Initially, we conducted an in-depth bioinformatics analysis of gout microarray chips to screen the key cuproptosis-related genes (CRGs) and key ferroptosis-related genes (FRGs). Using these data, we constructed a key ceRNA network for gout. Finally, key lncRNAs associated with gout were identified through the RF algorithm combined with ROC curves, and validated using the Comparative Toxicogenomics Database (CTD). We successfully identified NLRP3, LIPT1, and DBT as key CRGs associated with gout, and G6PD, PRKAA1, LIG3, PHF21A, KLF2, PGRMC1, JUN, PANX2, and AR as key FRGs associated with gout. The key ceRNA network identified four downregulated key lncRNAs (SEPSECS-AS1, LINC01054, REV3L-IT1, and ZNF883) along with three downregulated mRNAs (DBT, AR, and PRKAA1) based on the ceRNA theory. According to CTD validation inference scores and biological functions of target mRNAs, we identified a potential gout-associated lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis. This study identified the key lncRNA ZNF883 in the context of copper death and iron death mechanisms related to gout for the first time through the application of ceRNA network analysis and the RF algorithm, thereby filling a research gap in this field and providing new insights into the molecular mechanisms of gout. We further found that lncRNA ZNF883 might function in gout patients by regulating PRKAA1, the mechanism of which was potentially related to uric acid reabsorption in the proximal renal tubules and inflammation regulation. The proposed lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis might represent a potential RNA regulatory pathway for controlling the progression of gout disease. This discovery offered new molecular targets for the treatment of gout, and had significant implications for future therapeutic strategies in managing the gout.

Bioinformatics Analysis and Experimental Validation of Differential Genes and Pathways in Bone Nonunions.

Non-union fractures pose a significant clinical challenge, often leading to prolonged pain and disability. Understanding the molecular mechanisms underlying non-union fractures is crucial for developing effective therapeutic interventions. This study integrates bioinformatics analysis and experimental validation to unravel key genes and pathways associated with non-union fractures. We identified differentially expressed genes (DEGs) between non-union and fracture healing tissues using bioinformatics techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological processes and pathways involved. Common DEGs were identified, and a protein-protein interaction (PPI) network was constructed. Fibronectin-1 (FN1), Thrombospondin-1 (THBS1), and Biglycan (BGN) were pinpointed as critical target genes for non-union fracture treatment. Experimental validation involved alkaline phosphatase (ALP) and Alizarin Red staining to confirm osteogenic differentiation. Our analysis revealed significant alterations in pathways related to cell behavior, tissue regeneration, wound healing, infection, and immune responses in non-union fracture tissues. FN1, THBS1, and BGN were identified as key genes, with their upregulation indicating potential disruptions in the bone remodeling process. Experimental validation confirmed the induction of osteogenic differentiation. The study provides comprehensive insights into the molecular mechanisms of non-union fractures, emphasizing the pivotal roles of FN1, THBS1, and BGN in extracellular matrix dynamics and bone regeneration. The findings highlight potential therapeutic targets and pathways for further investigation. Future research should explore interactions between these genes, validate results using in vivo fracture models, and develop tailored treatment strategies for non-union fractures, promising significant advances in clinical management.