Correlational analysis between neutrophil granulocyte levels and osteonecrosis of the femoral head

Identification and analysis of mitochondria-related central genes in steroid-induced osteonecrosis of the femoral head, along with drug prediction

Purpose

Steroid-induced osteonecrosis of the femoral head (SONFH) is a refractory orthopedic hip joint disease that primarily affects middle-aged and young individuals. SONFH may be caused by ischemia and hypoxia of the femoral head, where mitochondria play a crucial role in oxidative reactions. Currently, there is limited literature on whether mitochondria are involved in the progression of SONFH. Here, we aim to identify and validate key potential mitochondrial-related genes in SONFH through bioinformatics analysis. This study aims to provide initial evidence that mitochondria play a role in the progression of SONFH and further elucidate the mechanisms of mitochondria in SONFH.

Methods

The GSE123568 mRNA expression profile dataset includes 10 non-SONFH (non-steroid-induced osteonecrosis of the femoral head) samples and 30 SONFH samples. The GSE74089 mRNA expression profile dataset includes 4 healthy samples and 4 samples with ischemic necrosis of the femoral head. Both datasets were downloaded from the Gene Expression Omnibus (GEO) database. The mitochondrial-related genes are derived from MitoCarta3.0, which includes data for all 1136 human genes with high confidence in mitochondrial localization based on integrated proteomics, computational, and microscopy approaches. By intersecting the GSE123568 and GSE74089 datasets with a set of mitochondrial-related genes, we screened for mitochondrial-related genes involved in SONFH. Subsequently, we used the good Samples Genes method in R language to remove outlier genes and samples in the GSE123568 dataset. We further used WGCNA to construct a scale-free co-expression network and selected the hub gene set with the highest connectivity. We then intersected this gene set with the previously identified mitochondrial-related genes to select the genes with the highest correlation. A total of 7 mitochondrial-related genes were selected. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the selected mitochondrial-related genes using R software. Furthermore, we performed protein network analysis on the differentially expressed proteins encoded by the mitochondrial genes using STRING. We used the GSEA software to group the genes within the gene set in the GSE123568 dataset based on their coordinated changes and evaluate their impact on phenotype changes. Subsequently, we grouped the samples based on the 7 selected mitochondrial-related genes using R software and observed the differences in immune cell infiltration between the groups. Finally, we evaluated the prognostic significance of these features in the two datasets, consisting of a total of 48 samples, by integrating disease status and the 7 gene features using the cox method in the survival R package. We performed ROC analysis using the roc function in the pROC package and evaluated the AUC and confidence intervals using the ci function to obtain the final AUC results.

Results

Identification and analysis of 7 intersecting DEGs (differentially expressed genes) were obtained among peripheral blood, cartilage samples, hub genes, and mitochondrial-related genes. These 7 DEGs include FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR, all of which are upregulated genes with no intersection in the downregulated gene set. Subsequently, GO and KEGG pathway enrichment analysis revealed that the upregulated DEGs are primarily involved in processes such as oxidative stress, release of cytochrome C from mitochondria, negative regulation of intrinsic apoptotic signaling pathway, cell apoptosis, mitochondrial metabolism, p53 signaling pathway, and NK cell-mediated cytotoxicity. GSEA also revealed enriched pathways associated with hub genes. Finally, the diagnostic value of these key genes for hormone-related ischemic necrosis of the femoral head (SONFH) was confirmed using ROC curves.

Conclusion

BID, FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR may serve as potential diagnostic mitochondrial-related biomarkers for SONFH. Additionally, they hold research value in investigating the involvement of mitochondria in the pathogenesis of ischemic necrosis of the femoral head.

Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head

Objective

Osteonecrosis of the femoral head (ONFH) is a common orthopedic condition that will prompt joint dysfunction, significantly impacting patients' quality of life. However, the specific pathogenic mechanisms underlying this disease remain elusive. The objective of this study is to examine the differentially expressed messenger RNAs (DE mRNAs) and key genes linked to ONFH, concurrently investigating the immune cell infiltration features in ONFH patients through the application of the CIBERSORT algorithm.

Methods

Microarray was applied to scrutinize mRNA expression profiles in both ONFH patients and healthy controls, with data integration sourced from the GEO database. DE mRNAs were screened using the Limma method. The biological functions of DE mRNAs were explored through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) functional analysis, and Gene Set Enrichment Analysis (GSEA). Additionally, support vector machine-recursive feature elimination (SVM-RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to discern diagnostic biomarkers associated with the disease. Receiver operating characteristic (ROC) analysis was utilized to assess the statistical performance of the feature genes. The validation of key genes was performed using qRT-PCR in bone tissues obtained from ONFH patients and healthy controls. Osteogenic differentiation of BMSC was then performed and detected by alkaline phosphatase staining (ALP) and qRT-PCR to verify the correlation between key genes and osteogenic differentiation. Finally, immune cell infiltration analysis was executed to evaluate immune cell dysregulation in ONFH, concurrently exploring the correlation between the infiltration of immune cells and key genes.

Results

After consolidating the datasets, the Limma method revealed 107 DEGs, comprising 76 downregulated and 31 upregulated genes. Enrichment analysis revealed close associations of these DE mRNAs with functions such as cell migration, osteoblast differentiation, cartilage development and extracellular region. Machine learning algorithms further identified APOD, FBXO43 and LRP12 as key genes. ROC curves demonstrated the high diagnostic efficacy of these genes. The results of qRT-PCR showed that the expression levels of key genes were consistent with those of microarray analysis. In addition, the results of in vitro experiments showed that APOD was closely related to osteogenic differentiation of BMSC. Immune infiltration analysis suggested a close correlation between ONFH and imbalances in levels of Neutrophils, Monocytes, Macrophages M2, Dendritic cells activated and Dendritic cells resting.

Conclusion

APOD is closely related to osteogenic differentiation of BMSCs and can be used as a diagnostic marker of ONFH. Immune cell infiltration significantly differs between controls and ONFH patients.

Identification and validation of ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head

OBJECTIVES

Treatment of steroid-induced osteonecrosis of the femoral head (SIONFH) is challenging. Due to the limited understanding of its molecular mechanisms, investigating the potential mechanisms of ferroptosis will shed light on SIONFH and provide directions for treating this disease.

METHODS

The GSE123568 dataset was utilized to apply various bioinformatics methodologies to identify ferroptosis-related hub genes (FRHGs). Subsequently, the importance of these genes and the reliability of the results were confirmed using protein data-independent acquisition (DIA) and cell experiments. Finally, we assessed the correlation between FRHG expression and immune cell infiltration.

RESULTS

Thirty-one hub genes were identified and validated by constructing a protein-protein interaction network and subsequent screening using experimentally determined interactions. These 31 hub genes were enriched in immunity, the AMPK signaling pathway, and the Toll-like receptor signaling pathway. Next, we identified a diagnostic marker comprising two ferroptosis-related genes, NCF2 and SLC2A1. The differential expression of these two genes in healthy and necrotic regions was confirmed by protein DIA analysis. Cell experiments verified the link between FRHGs and ferroptosis and preliminarily explored the potential mechanism of the antioxidant vitexin in promoting osteogenic differentiation in cells. The diagnostic efficiency of these two markers was confirmed by receiver operating characteristic curve (ROC) curves, yielding an area under the curve of 1.0. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated enrichment of FRHGs in the superoxide anion and HIF-1 signaling pathways. A significant correlation was observed between FRHGs and various immune cell populations.

CONCLUSION

NCF2 and SLC2A1 are promising ferroptosis-related diagnostic biomarkers of SIONFH. Concurrently, we embarked on a preliminary investigation to elucidate the potential mechanism underlying the promotion of osteogenic differentiation by the antioxidant vitexin. Moreover, these biomarkers are associated with distinct immune cell populations.

Individual immune cell and cytokine profiles determine platelet-rich plasma composition

OBJECTIVE

Platelet-rich plasma (PRP) therapy is increasingly popular to treat musculoskeletal diseases, including tendinopathies and osteoarthritis (OA). To date, it remains unclear to which extent PRP compositions are determined by the immune cell and cytokine profile of individuals or by the preparation method. To investigate this, we compared leukocyte and cytokine distributions of different PRP products to donor blood samples and assessed the effect of pro-inflammatory cytokines on chondrocytes.

DESIGN

For each of three PRP preparations (ACP®, Angel™, and nSTRIDE® APS), products were derived using whole blood samples from twelve healthy donors. The cellular composition of PRP products was analyzed by flow cytometry using DURAClone antibody panels (DURAClone IM Phenotyping Basic and DURAClone IM T Cell Subsets). The MESO QuickPlex SQ 120 system was used to assess cytokine profiles (V-PLEX Proinflammatory Panel 1 Human Kit, Meso Scale Discovery). Primary human chondrocyte 2D and 3D in vitro cultures were exposed to recombinant IFN-γ and TNF-α. Proliferation and chondrogenic differentiation were quantitatively assessed.

RESULTS

All three PRP products showed elevated portions of leukocytes compared to baseline levels in donor blood. Furthermore, the pro-inflammatory cytokines IFN-γ and TNF-α were significantly increased in nSTRIDE® APS samples compared to donor blood and other PRP products. The characteristics of all other cytokines and immune cells from the donor blood, including pro-inflammatory T cell subsets, were maintained in all PRP products. Chondrocyte proliferation was impaired by IFN-γ and enhanced by TNF-α treatment. Differentiation and cartilage formation were compromised upon treatment with both cytokines, resulting in altered messenger ribonucleic acid (mRNA) expression of collagen type 1A1 (COL1A1), COL2A1, and aggrecan (ACAN) as well as reduced proteoglycan content.

CONCLUSIONS

Individuals with elevated levels of cells with pro-inflammatory properties maintain these in the final PRP products. The concentration of pro-inflammatory cytokines strongly varies between PRP products. These observations may help to unravel the previously described heterogeneous response to PRP in OA therapy, especially as IFN-γ and TNF-α impacted primary chondrocyte proliferation and their characteristic gene expression profile. Both the individual's immune profile and the concentration method appear to impact the final PRP product.

TRIAL REGISTRATION

This study was prospectively registered in the Deutsches Register Klinischer Studien (DRKS) on 4 November 2021 (registration number DRKS00026175).

The role of immune cells in modulating chronic inflammation and osteonecrosis

Osteonecrosis occurs when, under continuous stimulation by adverse factors such as glucocorticoids or alcohol, the death of local bone and marrow cells leads to abnormal osteoimmune function. This creates a chronic inflammatory microenvironment, which interferes with bone regeneration and repair. In a variety of bone tissue diseases, innate immune cells and adaptive immune cells interact with bone cells, and their effects on bone metabolic homeostasis have attracted more and more attention, thus developing into a new discipline - osteoimmunology. Immune cells are the most important regulator of inflammation, and osteoimmune disorder may be an important cause of osteonecrosis. Elucidating the chronic inflammatory microenvironment regulated by abnormal osteoimmune may help develop potential treatments for osteonecrosis. This review summarizes the inflammatory regulation of bone immunity in osteonecrosis, explains the pathophysiological mechanism of osteonecrosis from the perspective of osteoimmunology, and provides new ideas for the treatment of osteonecrosis.

[Research progress of immune cells regulating the occurrence and development of osteonecrosis of the femoral head]

OBJECTIVE

To summarize the characteristics of the occurrence and development of osteonecrosis of the femoral head (ONFH), and to review the important regulatory role of immune cells in the progression of ONFH.

METHODS

The domestic and foreign literature on the immune regulation of ONFH was reviewed, and the relationship between immune cells and the occurrence and development of ONFH was analyzed.

RESULTS

The ONFH region has a chronic inflammatory reaction and an imbalance between osteoblast and osteoclast, while innate immune cells such as macrophages, neutrophils, dendritic cells, and immune effector cells such as T cells and B cells are closely related to the maintenance of bone homeostasis.

CONCLUSION

Immunotherapy targeting the immune cells in the ONFH region and the key factors and proteins in their regulatory pathways may be a feasible method to delay the occurrence, development, and even reverse the pathology of ONFH.

Identification of Inflammation-Related Genes and Exploration of Regulatory Mechanisms in Patients with Osteonecrosis of the Femoral Head

Background

Osteonecrosis of the femoral head (ONFH) is a disabling orthopedic disease, which is impacted by infiltration of immune cells. Thus, the aim of the current research was to determine the inflammation-related biomarkers in ONFH.

Methods

GSE123568 dataset with control and steroid-induced osteonecrosis of the femoral head (SONFH) samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were detected by limma R package and weighted gene co-expression network analysis (WGCNA) was used to explore the co-expression genes and modules. We obtained inflammation-related genes (IRGs) from the Molecular Signatures Database (MSigDB). Then, the IRGs associated with SONFH (IRGs-SONFH) were screened out and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and hub genes were identified by the MCODE algorithm. Based on the hub genes, we constructed a lncRNA-miRNA-mRNA network.

Results

We identified 535 DEGs between control and SONFH samples. The WGCNA clearly indicated that the brown module was most significantly associated with SONFH. We identified 25 IRGs-SONFH through WGCNA module genes, DEGs and IRGs. A total of 4 hub genes (CD14, CYBB, NOD2, and TLR1) were identified by Cytoscape. Receiver operating characteristic (ROC) curve analysis determined that the expressions of the four genes could distinguish SONFH from controls as evidenced by the area under the curve (AUC) greater than 0.7. Finally, we constructed a competitive endogenous RNA (ceRNA) network which included 67 lncRNAs, 1 miRNA (hsa-miR-320a), and 1 mRNA (NOD2).

Conclusions

Our study identified 4 hub genes as potential inflammation-related biomarkers of SONFH. Moreover, we proposed a ceRNA network of lncRNAs targeting hsa-miR-320a, hsa-miR-320a, and NOD2 as a potential RNA regulatory pathway that controls disease progression in ONFH.

The Rising Era of “Immunoporosis”: Role of Immune System in the Pathophysiology of Osteoporosis

Discoveries in the last few years have emphasized the existence of an enormous breadth of communication between bone and the immune system in maintaining skeletal homeostasis. Originally, the discovery of various factors was assigned to the immune system viz. interleukin (IL)-6, IL-10, IL-17, tumor necrosis factor (TNF)-α, receptor activator of nuclear factor kappa B ligand (RANKL), nuclear factor of activated T cells (NFATc1), etc., but now these factors have also been shown to have a significant impact on osteoblasts (OBs) and osteoclasts (OCs) biology. These discoveries led to an alteration in the approach for the treatment of several bone pathologies including osteoporosis. Osteoporosis is an inflammatory bone anomaly affecting more than 500 million people globally. In 2018, to highlight the importance of the immune system in the pathophysiology of osteoporosis, our group coined the term “immunoporosis”. In the present review, we exhaustively revisit the characteristics, mechanism of action, and function of both innate and adaptive immune cells with the goal of understanding the potential of immune cells in osteoporosis. We also highlight the Immunoporotic role of gut microbiota (GM) for the treatment and management of osteoporosis. Importantly, we further discuss whether an immune cell-based strategy to treat and manage osteoporosis is feasible and relevant in clinical settings.

Identification of key biomarkers in steroid-induced osteonecrosis of the femoral head and their correlation with immune infiltration by bioinformatics analysis

Objective

This study aimed to identify key diagnostic markers and immune infiltration of (SONFH) by bioinformatics analysis.

Methods

Related SONFH datasets were downloaded from the Gene Expression Omnibus (GEO) database. First, we identified the differentially expressed genes (DEGs) and performed the functional enrichment analysis. Then weighted correlation network analysis (WGCNA) and the MCODE plug-in in Cytoscape were used to identify the diagnostic markers of SONFH. Finally, CIBERSORT was used to analyze the immune infiltration between SONFH and healthy controls, and the correlation between infiltrating immune cells and diagnostic markers was analyzed.

Results

TYROBP, TLR2, P2RY13, TLR8, HCK, MNDA, and NCF2 may be key diagnostic markers of SONFH. Immune cell infiltration analysis revealed that Memory B cells and activated dendritic cells may be related to the SONFH process. Moreover, HCK was negatively correlated with CD8 T cells, and neutrophils were positively correlated with those key diagnostic markers.

Conclusions

TYROBP, TLR2, P2RY13, TLR8, HCK, MNDA, and NCF2 may be used as diagnostic markers of SONFH, and immune-related mechanism of SONFH and the potential immunotherapy are worthy of further study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-04994-7.

Blood biomarkers related to osteonecrosis of femoral head by internal fixation after Garden I femoral neck fracture: a cohort study

BACKGROUND

Internal fixation is currently considered the gold standard in treatment for femoral neck fractures in adults. However, osteonecrosis of the femoral head (ONFH) after internal fixation would occur in quite proportion of patients with femoral neck fracture, even in Garden I femoral neck fracture. The purpose of this study was to determine the association between the blood biomarkers (serum albumin, pre-albumin, total protein and total lymphocyte count) and ONFH following internal fixation of Garden I femoral neck fracture in adults.

METHOD

This is a single center cohort study, in which each patient who sustained a Garden I femoral neck fracture had been treated with internal fixation, and had adequate preoperative blood examinations. The serum albumin was categorized as ≥ 40g/L or < 40g/L. The pre-albumin was categorized as ≥ 22mg/dL or < 22mg/dL. The total protein was categorized as ≥ 65g/L or < 65 g/L. The total lymphocyte count was categorized as ≥1.1× 10⁹ /L or <1.1×10⁹ /L. Multivariate cox proportional hazards analysis was used to assess the association between blood markers and the osteonecrosis of femoral head during the 2-years follow-up period controlling the confounders.

RESULT

A total of 10 cases of ONFH were identified. Multivariate Cox regression analysis revealed that low total lymphocyte count and hypertension state were significant independent risk factors for ONFH after internal fixation for Garden I femoral head fractures.

CONCLUSION

Blood biomarkers were potential predictors for ONFH after internal fixation Garden I femoral neck fractures. We suggest that routine laboratory tests might can be used to assist surgeons to identify patients at great risk of ONFH.

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

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.

Development and validation of a predictive nomogram for postoperative osteonecrosis of the femoral head with cannulated screws fixation

Background

Osteonecrosis of the femoral head (ONFH) remains a major complication of femoral neck fractures. Early interventions require preliminary prediction and detection. In this study, we aimed to evaluate the perioperative variables of postoperative ONFH in femoral neck fracture patients with closed reduction and cannulated screw fixation. We also established and validated an individualized nomogram for the prediction of postoperative ONFH.

Methods

We included 470 patients with ONFH from two hospitals [First Affiliated Hospital of University of Science and Technology of China (n=360) and Southern Branch of the First Affiliated Hospital of the University of Science and Technology of China (n=110)]. We evaluated the prognostic value of multiple perioperative variables using a Cox regression model in the training cohort. We developed a nomogram for the prediction of ONFH using a logistic regression model. We assessed the performance of this nomogram in a validation cohort and evaluated its clinical value.

Results

Of the 470 patients who met the inclusion criteria, 141 (30.0%) developed postoperative ONFH. We found alcohol use [odds ratio (OR), 1.743, 95% confidence interval (CI), 1.042-2.901, P=0.033], cerebrovascular disease (OR, 5.357, 95% CI, 2.318-13.13, P<0.001), interval to surgery (OR, 5.273, 95% CI, 2.724-10.43, P<0.001), Garden classification (OR, 23.17, 95% CI, 6.812-145.3, P<0.001), Garden index (OR, 5.935, 95% CI, 2.670-14.184, P<0.001), interval to partial weight-bearing (OR, 0.053, 95% CI, 0.006-0.296, P=0.002), and six-month Harris hip score (OR, 0.856; 95% CI, 0.792-0.919, P<0.001) were independent predictors of postoperative development of ONFH. Based on these variables, we developed a nomogram that showed good discrimination in both the training [area under the curve (AUC) =0.865] and the validation cohort (AUC =0.877). The favorable performance of this nomogram was also confirmed in the validation cohort.

Conclusions

We developed and validated an easy-to-use nomogram for predicting postoperative ONFH. This nomogram can aid decision-making of intraoperative interventions and postoperative rehabilitation plans for patients, surgeons, and osteo-rehabilitative physicians.