Dataset Information

ARG2, MAP4K5 and TSTA3 as Diagnostic Markers of Steroid-Induced Osteonecrosis of the Femoral Head and Their Correlation With Immune Infiltration.

ABSTRACT:

Background

The diagnosis for steroid-induced osteonecrosis of the femoral head (SONFH) is hard to achieve at the early stage, which results in patients receiving ineffective treatment options and a poor prognosis for most cases. The present study aimed to find potential diagnostic markers of SONFH and analyze the effect exerted by infiltration of immune cells in this pathology.

Materials and methods

R software was adopted for identifying differentially expressed genes (DEGs) and conducting functional investigation based on the microarray dataset. Then we combined SVM-RFE, WGCNA, LASSO logistic regression, and random forest (RF) algorithms for screening the diagnostic markers of SONFH and further verification by qRT-PCR. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. CIBERSORT was then adopted for assessing the infiltration of immune cells and the relationship of infiltration-related immune cells and diagnostic markers.

Results

We identified 383 DEGs overall. This study found ARG2, MAP4K5, and TSTA3 (AUC = 0.980) to be diagnostic markers of SONFH. The results of qRT-PCR showed a statistically significant difference in all markers. Analysis of infiltration of immune cells indicated that neutrophils, activated dendritic cells and memory B cells were likely to show the relationship with SONFH occurrence and progress. Additionally, all diagnostic markers had different degrees of correlation with T cell follicular helper, neutrophils, memory B cells, and activated dendritic cells.

Conclusion

ARG2, MAP4K5, and TSTA3 are potential diagnostic genes for SONFH, and infiltration of immune cells may critically impact SONFH occurrence and progression.

SUBMITTER: Yu R

PROVIDER: S-EPMC8350574 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeSteroid-induced necrosis of the femoral head (SONFH) is a refractory orthopedic hip disease occurring in young and middle-aged people, with glucocorticoids being the most common cause. Previous experimental studies have shown that cell pyroptosis may be involved in the pathological process of SONFH, but its pathogenesis in SONFH is still unclear. This study aims to screen and validate potential pyroptosis-related genes in SONFH diagnosis by bioinformatics analysis to further elucidate the mechanism of pyroptosis in SONFH.MethodsThere were 33 pyroptosis-related genes obtained from the prior reviews. The mRNA expression was downloaded from GSE123568 dataset in the Gene Expression Omnibus (GEO) database, including 10 non-SONFH (following steroid administration) samples and 30 SONFH samples. The pyroptosis-related differentially expressed genes involved in SONFH were identified with "affy" and "limma" R package by intersecting the GSE123568 dataset with pyroptosis genes. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the pyroptosis-related differentially expressed genes involved in SONFH were conducted by "clusterProfiler" R package and visualized by "GOplot" R package. Then, the correlations between the expression levels of the pyroptosis-related differentially expressed genes involved in SONFH were confirmed with "corrplot" R package. Moreover, the protein-protein interaction (PPI) network was analysed by using GeneMANIA database. Next, The ROC curve of pyroptosis-related differentially expressed genes were analyzed by "pROC" R package.ResultsA total of 10 pyroptosis-related differentially expressed genes were identified between the peripheral blood samples of SONFH patients and non-SONFH patients based on the defined criteria, including 20 upregulated genes and 10 downregulated genes. The GO and KEGG pathway enrichment analyses revealed that these 10 pyroptosis-related differentially expressed genes involved in SONFH were particularly enriched in cysteine-type endopeptidase activity involved in apoptotic process, positive regulation of interleukin-1 beta secretion and NOD-like receptor signaling pathway. Correlation analysis revealed significant correlations among the 10 differentially expressed pyroptosis-related genes involved in SONFH. The PPI results demonstrated that the 10 pyroptosis-related differentially expressed genes interacted with each other. Compared to non-SONFH samples, these pyroptosis-related differentially expressed genes had good predictive diagnostic efficacy (AUC = 1.000, CI = 1.000-1.000) in the SONFH samples, and NLRP1 had the highest diagnostic value (AUC: 0.953) in the SONFH samples.ConclusionsThere were 10 potential pyroptosis-related differentially expressed genes involved in SONFH were identified via bioinformatics analysis, which might serve as potential diagnostic biomarkers because they regulated pyroptosis. These results expand the understanding of SONFH associated with pyroptosis and provide new insights to further explore the mechanism of action and diagnosis of pyroptosis associated in SONFH.

Project description:PurposeSteroid-induced osteonecrosis of the femoral head (SONFH) was a refractory orthopedic hip joint disease in the young and middle-aged people, but the pathogenesis of SONFH remained unclear. We aimed to identify the potential genes and screen potential therapeutic compounds for SONFH.MethodsThe microarray was obtained for blood tissue from the GEO database, and then it identifies differentially expressed genes (DEGs). The DEGs were analyzed to obtain the differences in immune cell infiltration. The gene functional enrichment analysis of SONFH was analyzed. The PPI of DEGs was identified through the STRING database, and the cluster modules and hub genes were ascertained using MCODE and CytoHubba, and the ROC curve of hub genes was analyzed, and the tissues distribution of hub genes was understood by the HPA, Bgee and BioGPS databases. The hub genes and target miRNAs and corresponding upstream lncRNAs were predicted by TargetScan, miRDB and ENCORI database. Subsequently, we used CMap, DGIdb and L1000FWD databases to identify several potential therapeutic molecular compounds for SONFH. Finally, the AutoDockTools Vina, PyMOL and Discovery Studio were employed for molecular docking analyses between compounds and hub genes.ResultsThe microarray dataset GSE123568 was obtained related to SONFH. There were 372 DEGs including 197 upregulated genes and 175 downregulated genes by adjusted P value < 0.01 and |log2FC|> 1. Several significant GSEA enrichment analysis and biological processes and KEGG pathway associated with SONFH were identified, which were significantly related to cytoskeleton organization, nucleobase-containing compound catabolic process, NOD-like receptor signaling pathway, MAPK signaling pathway, FoxO signaling pathway, neutrophil-mediated immunity, neutrophil degranulation and neutrophil activation involved in immune response. Activated T cells CD4 memory, B cells naïve, B cells memory, T cells CD8 and T cells gamma delta might be involved in the occurrence and development of SONFH. Three cluster modules were identified in the PPI network, and eleven hub genes including FPR2, LILRB2, MNDA, CCR1, IRF8, TYROBP, TLR1, HCK, TLR8, TLR2 and CCR2 were identified by Cytohubba, which were differed in bone marrow, adipose tissue and blood, and which had good diagnostic performance in SONFH. We identified IRF8 and 10 target miRNAs that was utilized including Targetsan, miRDB and ENCORI databases and 8 corresponding upstream lncRNAs that was revealed by ENCORI database. IRF8 was detected with consistent expression by qRT-PCR. Based on the CMap, DGIdb and L1000FWD databases, the 11 small molecular compounds that were most strongly therapeutic correlated with SONFH were estradiol, genistein, domperidone, lovastatin, myricetin, fenbufen, rosiglitazone, sirolimus, phenformin, vorinostat and vinblastine. All of 11 small molecules had good binding affinity with the IRF8 in molecular docking.ConclusionThe occurrence of SONFH was associated with a "multi-target" and "multi-pathway" pattern, especially related to immunity, and IRF8 and its noncoding RNA were closely related to the development of SONFH. The CMap, DGIdb and L1000FWD databases could be effectively used in a systematic manner to predict potential drugs for the prevention and treatment of SONFH. However, additional clinical and experimental research is warranted.