Inflammasome activators induce fibronectin expression and release in macrophages

Bioinformatics and Machine Learning Methods to Identify FN1 as a Novel Biomarker of Aortic Valve Calcification

Aim

The purpose of this study was to identify potential diagnostic markers for aortic valve calcification (AVC) and to investigate the function of immune cell infiltration in this disease.

Methods

The AVC data sets were obtained from the Gene Expression Omnibus. The identification of differentially expressed genes (DEGs) and the performance of functional correlation analysis were carried out using the R software. To explore hub genes related to AVC, a protein–protein interaction network was created. Diagnostic markers for AVC were then screened and verified using the least absolute shrinkage and selection operator, logistic regression, support vector machine-recursive feature elimination algorithms, and hub genes. The infiltration of immune cells into AVC tissues was evaluated using CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. Finally, the Connectivity Map database was used to forecast the candidate small molecule drugs that might be used as prospective medications to treat AVC.

Results

A total of 337 DEGs were screened. The DEGs that were discovered were mostly related with atherosclerosis and arteriosclerotic cardiovascular disease, according to the analyses. Gene sets involved in the chemokine signaling pathway and cytokine–cytokine receptor interaction were differently active in AVC compared with control. As the diagnostic marker for AVC, fibronectin 1 (FN1) (area the curve = 0.958) was discovered. Immune cell infiltration analysis revealed that the AVC process may be mediated by naïve B cells, memory B cells, plasma cells, activated natural killer cells, monocytes, and macrophages M0. Additionally, FN1 expression was associated with memory B cells, M0 macrophages, activated mast cells, resting mast cells, monocytes, and activated natural killer cells. AVC may be reversed with the use of yohimbic acid, the most promising small molecule discovered so far.

Conclusion

FN1 can be used as a diagnostic marker for AVC. It has been shown that immune cell infiltration is important in the onset and progression of AVC, which may benefit in the improvement of AVC diagnosis and treatment.

A proteomics approach to further highlight the altered inflammatory condition in Rett syndrome

Rett syndrome (RTT) is a progressive neurodevelopmental disorder caused by mutations in the X-linked MECP2 gene. RTT patients show multisystem disturbances associated with perturbed redox homeostasis and inflammation, which appear as possible key factors in RTT pathogenesis. In this study, using primary dermal fibroblasts from control and RTT subjects, we performed a proteomic analysis that, together with data mining approaches, allowed us to carry out a comprehensive characterization of RTT cellular proteome. Functional and pathway enrichment analyses showed that differentially expressed proteins in RTT were mainly enriched in biological processes related to immune/inflammatory responses. Overall, by using proteomic data mining as supportive approach, our results provide a detailed insight into the molecular pathways involved in RTT immune dysfunction that, causing tissue and organ damage, can increase the vulnerability of affected patients to unknown endogenous factors or infections.

Identification of pathogenic genes and transcription factors in glaucoma

Glaucoma is a group of eye diseases characterized by alterations in the contour of the optic nerve head, with corresponding visual field defects and progressive loss of retinal ganglion cells. The present study aimed to identify the key genes and upstream regulators in glaucoma. To screen the pathogenic genes involved in glaucoma, an integrated analysis was performed by using the microarray datasets in glaucoma derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were additionally examined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A glaucoma‑specific transcriptional regulatory network was constructed to identify crucial transcriptional factors that target the DEGs in glaucoma. From two GEO datasets, 1,935 DEGs (951 upregulated and 984 downregulated genes) between glaucoma and normal controls were identified. GO and KEGG analyses identified that 'eye development' [false discovery rate (FDR)=0.00415533] and 'visual perception' (FDR=0.00713283) were significantly enriched pathways for DEGs. The expression of lipocalin 2 (LCN2), monoamine oxidase A (MAOA), hemoglobin subunit β (HBB), paired box 6 (PAX6), fibronectin (FN1) and cAMP responsive element binding protein 1 (CREB1) were demonstrated to be involved in the pathogenesis of glaucoma. In conclusion, LCN2, MAOA, HBB, PAX6, FN1 and CREB1 may serve roles in glaucoma, regulated by PAX4, solute carrier family 22 member 1, hepatocyte nuclear factor 4 α and ELK1, ETS transcription factor. These data may contribute to the development of novel potential biomarkers, reveal the underlying pathogenesis and additionally identify novel therapeutic targets for glaucoma.