Background: Styrene is a ubiquitous volatile organic compound linked to hematologic and vascular alterations; however, the molecular mechanisms connecting exposure to atherosclerosis remain poorly characterized. Methods: We integrated peripheral blood mononuclear cell transcriptomic profiles (GSE23746) with toxicogenomic data from the Comparative Toxicogenomics Database, applying support vector machine recursive feature elimination and least absolute shrinkage and selection operator machine learning algorithms to identify core targets at the styrene-atherosclerosis intersection. Immune infiltration was assessed using CIBERSORT and single-sample gene set enrichment analysis, and molecular docking evaluated binding potential. results: Four model genes—CCND3, CCR1, MYC, and MYD88—were identified and constituted a diagnostic signature with high accuracy (area under the curve > 0.9). These genes were enriched in IL-17 and NF-κB inflammatory pathways and correlated with distinct immune cell alterations, particularly mast cells and T cell subsets. Molecular docking revealed direct, moderate binding of styrene to CCND3. Results: Four model genes—CCND3, CCR1, MYC, and MYD88—were identified and constituted a diagnostic signature with high accuracy (area under the curve > 0.9). These genes were enriched in IL-17 and NF-κB inflammatory pathways and correlated with distinct immune cell alterations, particularly neutrophils and T cell subsets. Molecular docking predicted direct, moderate-affinity binding of styrene to CCND3 (Vina score = −6.4 kcal/mol), involving multiple contacts within the cyclin domain. Discussion: The convergence of transcriptomic screening and molecular docking identifies CCND3 as a putative target for styrene-protein interaction and suggests a mechanistic hypothesis linking styrene to atherosclerosis via inflammatory and immune dysregulation. The computational framework provides a basis for future experimental validation. Conclusion: This computational framework generates the hypothesis that styrene may contribute to atherosclerosis through coordinated perturbations of immune signaling and cell cycle regulation, with CCND3 representing a candidate molecular target for future experimental validation in styrene-exposed populations.
Objective: Steroid-induced Osteonecrosis of the Femoral Head (SONFH) is a disabling disorder arising from chronic glucocorticoid exposure. Cuproptosis, a copper- dependent form of cell death, has been implicated in various diseases, but its role in SONFH remains unclear. This study aimed to characterize cuproptosis-related molecular subtypes and develop a predictive model for SONFH. Methods: Using the GSE123568 cohort (30 SONFH cases, 10 controls), we analyzed Differentially Expressed Cuproptosis-related Genes (DE-CRGs) and immune infiltration via CIBERSORT. Unsupervised clustering and Weighted Gene Coexpression Network Analysis (WGCNA) identified molecular subtypes and module genes. Three machine learning models (Random Forest (RF), Generalized Linear Models (GLMs), Support Vector Machines (SVMs)) were compared; the RF model was validated using a nomogram, calibration, decision curve analysis, and the GSE74089 cohort. Target genes were confirmed by immunohistochemistry on clinical femoral head tissue. Results: NLRP3, NFE2L2, and PDHB were differentially expressed in SONFH and confirmed by immunohistochemistry. Two molecular clusters with distinct immune infiltration profiles were identified. The RF model performed best (AUC = 0.889), and five predictive genes—KCNE3, SOD1, ACAP1, ALDH2, and ITGAL—were selected. The nomogram demonstrated high predictive accuracy in external validation. Discussion: These findings reveal the potential role of cuproptosis-related genes in SONFH pathogenesis and immune regulation, providing biomarkers for molecular subtyping and risk prediction. Conclusion: NLRP3, NFE2L2, and PDHB are key modulators of SONFH pathogenesis, and the 5-gene RF-based nomogram offers a novel, effective diagnostic approach for clinical application.
Objective: Non-Alcoholic Fatty Liver Disease (NAFLD) poses a significant global health burden, yet causal relationships with modifiable dietary factors remain incompletely defined. This Mendelian Randomization (MR) study evaluated the causal associations between dietary exposures and NAFLD risk, as well as related hepatic traits. Methods: We performed univariable, Bayesian Weighted MR (BWMR), and Multivariable MR (MVMR) analyses using genetic variants as instrumental variables. Data from 335,394 to 462,630 European-ancestry individuals (IEU OpenGWAS) were analyzed for 20 dietary exposures. Outcomes included NAFLD diagnosis, liver volume, liver fat content, and percent liver fat. Primary analysis used Inverse-Variance Weighted (IVW) regression, supplemented by sensitivity analyses (MR-Egger, MR-PRESSO) to assess pleiotropy and heterogeneity. Results: Genetically predicted higher alcohol intake frequency (OR = 1.348, 95% CI = 1.110-1.638, P = 0.003) and salt added to food (OR = 1.544, 95% CI = 1.160-2.054, P = 0.003) significantly increased NAFLD risk in IVW analysis. These findings were robust in BWMR and MVMR analyses adjusting for potential confounders. Cheese (OR = 0.718) and dried fruit intake (OR = 0.406) showed protective associations. Alcohol frequency positively correlated with liver volume (β = 0.152, P = 0.002), while added salt was associated with increased liver volume (β = 0.244, P = 0.002) and liver fat content (β = 0.196, P = 0.038). Sensitivity analyses revealed no significant horizontal pleiotropy (MR-Egger intercept P > 0.05) or heterogeneity affecting primary results. Discussion: We identified alcohol intake frequency and dietary salt as genetically determined risk factors for NAFLD through MR analysis, while suggesting potential protective associations of cheese and dried fruit intake. By integrating BWMR and MVMR approaches with hepatic steatosis indices, we further revealed positive correlations between these exposures and liver volume/fat content, providing evidence-based dietary insights for NAFLD prevention. Conclusion: This MR study provides genetic evidence supporting potential causal associations of alcohol consumption frequency and dietary salt intake with NAFLD risk. It further associates these exposures with adverse changes in liver morphology and fat content. These findings highlight the importance of moderating the frequency of alcohol intake and salt consumption in NAFLD prevention strategies.
Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease with heterogeneous clinical manifestations, and its molecular mechanisms remain incompletely understood. Objective: To identify core genes associated with RA and evaluate their diagnostic utility, with an emphasis on immune relevance and causality. Methods: Differential expression analysis and weighted gene coexpression network analysis were used to prioritize hub genes. Functional enrichment and protein-protein interaction analyses supported biological interpretation. A nomogram and receiver operating characteristic analysis were used to evaluate diagnostic performance, and immune cell infiltration was analyzed to identify immune-associated core genes. The causal effect of titin on the risk of RA was estimated using genome-wide association study data and two-sample Mendelian randomization. Validation was conducted in independent public transcriptomic datasets and single-cell RNA sequencing (scRNA-seq) of synovial tissue. Results: Titin (TTN) was prioritized as an RA-associated core gene and demonstrated favorable diagnostic performance. TTN expression was consistently higher in RA than in controls across validation datasets. Public external validation datasets supported increased TTN expression in RA, and scRNA-seq analysis suggested enrichment of TTN expression in synovial T cells. Mendelian randomization supported a causal association between genetically predicted TTN and RA risk. Discussion: Collectively, evidence from bulk transcriptomics, immune cell infiltration profiling, single-cell localization, external validation, and genetic inference supports TTN as a previously underexplored candidate RA-associated biomarker with potential immune relevance. These findings extend current RA biomarker discovery by linking diagnostic performance with immune context and genetic support. Further mechanistic studies are needed to clarify whether TTN is involved in RA immunopathology or reflects inflammation-related tissue remodeling. Conclusion: Integrative analyses identify TTN as a potential RA-associated diagnostic biomarker requiring further experimental and clinical validation. Further studies are needed to clarify its mechanistic role and clinical utility in RA.
Background: Wild-type FLT3 (WT-FLT3) has emerged as a relevant molecular target in Acute Myeloid Leukemia (AML), with increasing evidence implicating its role in leukemic proliferation and resistance, even in the absence of FLT3 mutations. Although gilteritinib is an approved FLT3 inhibitor, its efficacy in WT-FLT3 AML remains limited, underscoring the need for alternative strategies. Method: We filtered 1,737 FDA-approved anticancer agents from the Selleckchem database using computational techniques to identify possible WT-FLT3 inhibitors. A total of 118 druglike compounds were docked against the WT-FLT3 binding site as determined by gilteritinib using AutoDock Vina; ADMET screening and MD simulations of 150 ns were executed on hit compounds using the ADMETSar server and GROMACS software, respectively. results: 118 drugs were druglike while 56 of them returned binding energy (BE) between -8.0 and -10.3 kcal/mol. However, amlexanox (-9.5), sanguinarine (-10.3), crizotinib (-9.5), (s)-crizotinib (-9.7), and rutaecarpine (-10.0) showed the best binding potentials. Also, they exhibited acceptable ADMET profile, structural stability, and dynamics. However, amlexanox stood out as the most stable and stronger candidate for therapeutic applications against FLT 3 Results: In the end, 56 compounds with binding energies between -8.0 and -10.3 kcal/- mol were obtained, while the control, gilteritinib, returned -6.4 kcal/mol. Among this subset, Amlexanox (-9.5), sanguinarine (-10.3), crizotinib (-9.7), (S)-crizotinib (-9.7), and rutaecarpine (-10.0) showed high predicted affinity. Predictions from ADMET and 150 ns MD simulations indicated that amlexanox had stable, specific interactions with the WT-FLT3 active site, superior ADMET, and a concentrated free-energy basin with increased conformational stability. In contrast, sanguinarine and others raised significant toxicity risks. Conclusion: These results suggest amlexanox is a potential new repurposing agent as a WT-FLT3 inhibitor in AML. This potential outcome needs urgent experimental confirmation through in vitro and in vivo models.
