Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease characterized by synovial inflammation, progressive joint destruction, and systemic immune dysregulation. Recent findings suggest that disturbed metal homeostasis and regulated cell death pathways, including ferroptosis (iron-dependent lipid peroxidation) and cuproptosis (copper-dependent mitochondrial proteotoxic stress), contribute to RA pathogenesis. In this study, we used an integrative bioinformatic approach combining weighted gene co-expression network analysis (WGCNA), differential expression analysis, functional enrichment, protein-protein interaction (PPI) network construction, and immune cell infiltration deconvolution to identify key metal-dependent cell death regulators in RA. Using bulk RNA-seq data from peripheral CD14+ monocytes (GSE294225) from 15 healthy controls and 9 patients with active RA (DAS28 > 2.7), we identified 1,410 significantly differentially expressed genes (DEGs) (adjusted P 1). WGCNA revealed an RA-associated module enriched in oxidative stress, mitochondrial dysfunction, and cell death pathways. Overlap analysis of ferroptosis- and cuproptosis-related gene sets distinguished three upregulated hub genes, including FTH1 (ferritin heavy chain 1), SOD2 (superoxide dismutase 2), and CDKN2A (cyclin-dependent kinase inhibitor 2A) as key candidate regulators. These genes showed high module membership, significant differential expression in RA monocytes, and notable associations with immune infiltration patterns, including increased pro-inflammatory monocytes/macrophages and reduced regulatory T cells. Functional enrichment also highlighted oxidative stress response, iron and copper homeostasis, mitochondrial respiration, and cellular senescence. The single-cell analysis further showed that these hub genes are predominantly expressed in the RA synovial macrophages and fibroblasts, two major mediators of joint pathology. Together, these findings indicate that there may be an association between ferroptosis-related pathways and cuproptosis-related pathways in RA and suggest that FTH1, SOD2, and CDKN2A are candidate biomarkers and candidate therapeutic targets.
Diabetes mellitus and chronic inflammation are global health issues, exacerbated by the incomplete control of metabolic-inflammatory pathways and the adverse effects of long-term pharmacotherapy. The development of multifunctional therapeutic nanomaterials via green nanotechnology has recently garnered attention. In this study, we synthesized copper-based nanoparticles (Cu NPs) using Salvia hispanica (chia) seed-derived polysaccharides and characterized their in vitro anti-inflammatory and antidiabetic activities, as well as in vivo antidiabetic effects in an alloxan-induced diabetic mouse model. Successful formation of polysaccharide-based Cu NPs was confirmed using UV-Visible, FTIR, XRD, and SEM analyses. Hemocompatibility assessment showed concentration-dependent hemolysis by Cu NPs (0.92 ± 0.06%, 5.71 ± 0.44%, and 8.42 ± 0.63% at the respective tested concentrations), indicating reduced hemocompatibility at higher concentrations. In the HRBC membrane stabilization assay, Cu NPs exhibited dose-dependent inhibition of hemolysis (45.83 ± 1.7% to 70.59 ± 2.1%), while heat hemolysis was reduced by 72.91 ± 1.5% at 1000 µg/mL. Enzyme inhibition studies showed significant inhibition of α-amylase (58.45 ± 0.7% to 87.20 ± 2.1%) and α-glucosidase (83.87 ± 1.6% at 1000 µg/mL) compared to acarbose. Glucose uptake in yeast cells increased to 59.87 ± 0.3% at 1000 µg/mL. In alloxan-induced diabetic mice, Cu NPs (150 mg/kg) reduced fasting blood glucose from 287 ± 4.2 to 131 ± 7.02 mg/dL over 30 days and improved lipid profiles (e.g., decreased total cholesterol to 85 ± 1.3 mg/dL and increased HDL to 39.8 ± 1.2 mg/dL). Histopathological analyses showed restoration of pancreatic and hepatic architecture. Collectively, chia seed polysaccharide-mediated copper-based nanoparticles exhibited anti-hyperglycemic, anti-inflammatory, and lipid-modulating activities under the investigated experimental conditions, supporting their further evaluation for diabetes-related applications.