Introduction: Lupus nephritis (LN) is one of the most prevalent severe organ manifestations of systemic lupus erythematosus (SLE), impacting 70% of SLE patients. MicroRNAs (miRNAs), are small non-coding RNA molecules which influence the expression of approximately one-third of human genes after the process of transcription. Dysregulation of miRNAs was documented in numerous disorders, including SLE and LN. Cytokines are the orchestrators of the immune response in autoimmune diseases. Our study aims to explore the variation in the levels of circulating miRNAs and proinflammatory cytokines as potential diagnostic biomarkers among LN and SLE patients without LN in comparison to controls.Methods: The study involved 20 LN patients, 20 SLE patients without LN, and 10 healthy controls. Serum levels of IL-12 and IL-21 in addition to miR-124, miR-146a, miR-199a, and miR-21 were assessed using the enzyme-linked immunosorbent assay (ELISA) for cytokines and quantitative real-time PCR for miRNAs.Results: A significant downregulation in miR-124 (p<0.001) and a significant overexpression of miR-146a (p=0.005) were found in SLE patients without LN in comparison to controls. In comparison to SLE patients without LN and the control group, miR-199a, miR-21, and miR-146a were significantly upregulated in LN patients (p=<0.001) with high diagnostic values of these miRNAs in discriminating LN from SLE patients without LN according to Receiver operating curve (ROC) analysis. Logistic regression analysis revealed that only miR-199a is an independent predictor of LN (OR 1.69; 95% CI: 1.1-2.6). The expression of miR-124 was reduced in LN patients in comparison to the control but increased in LN patients in comparison to SLE patients without LN. However, there was no statistically significant difference in either scenario. In comparison to both SLE patients without LN and controls, LN patients exhibited the highest serum levels of IL-12 and IL-21, with no statistically significant difference. Regression analysis revealed that only miR-146a was associated with creatinine levels and SLEDAI score (p= 0.009 and 0.03, respectively), while miR-124 was associated with hemoglobin level (p=0.03).Conclusion: MiR-199a is an independent predictor for LN and might be used as a diagnostic biomarker for this disease. MiR-146a might play an important role in LN pathophysiology.

Pseudomonas aeruginosa (P. aeruginosa) is a multidrug-resistant opportunistic pathogen that causes both acute and chronic infections and is known for its ability to form biofilms. In the current study, we applied a hypothesis-generating framework primarily based on integrating four different datasets and applying batch correction. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed in parallel with differential expression analysis using limma. Therefore, we aimed to identify potential biofilm-associated gene candidates. Significant candidate genes were subjected to functional analysis and gene ontology, followed by the construction of a protein–protein interaction network using STRING. The Pseudomonas Genome Database was used to highlight the candidate genes. A total of 271, 687, 533, and 277 significantly up-regulated differentially expressed genes (DEGs), as well as 306, 985, 472, and 312 significantly down-regulated DEGs, resulted from the exploratory analysis. Through WGCNA/limma integration, 223 common significantly up-regulated/positively correlated gene candidates were identified. Functional analysis results showed significant enrichment in virulence-related pathways, such as biofilm formation (PA0083, PA0084, hcp1, hcpC, pilH, pilI, pilJ, vfr, pqsA, pqsB, pqsC, pqsE, PA1657, and PA1658). In addition, other virulence-related pathways, such as quorum sensing, phenazine biosynthesis, the bacterial secretion system, and secondary metabolite biosynthesis, were enriched. In conclusion, our hypothesis-generating integrative analysis identifies candidate genes and potential pathways associated with biofilm formation, virulence, and other processes in P. aeruginosa. In light of this, we point out that all candidate genes presented in this study remain hypothesis-generating. Further validation is recommended, including large-scale in silico analyses and in vitro experimental studies.