Aim: Steroid-induced osteonecrosis of the femoral head (SONFH) is a severe complication following glucocorticoid therapy. This study aimed to identify the differential mRNA expression and investigate the molecular mechanisms of SONFH. Materials & methods: RNA sequencing was performed in eight SONFH patients, five non-SONFH patients and five healthy individuals. Results: A total of 1555, 3997 and 5276 differentially expressed mRNAs existed between the following combinations: SONFH versus non-SONFH, SONFH versus healthy subjects and non-SONFH versus healthy subjects. Increased ISM1 expression might contribute to a high risk of SONFH through antiangiogenesis. Decreased FOLR3 expression might affect the metabolism of homocysteine, leading to avascular necrosis of the femoral head. KCNJ2, which plays a pivotal role in regulating bone development, was also deregulated. Conclusion: ISM1, FOLR3 and KCNJ2 might be related to the occurrence of SONFH.

Osteonecrosis of the femoral head (ONFH), also known as vascular necrosis of the femoral head, is combined with lipid metabolism disorders in most patients. This study aims to explore the lipid metabolism profiles in different subtypes of ONFH.

The subjects were divided into an alcohol-induced osteonecrosis of the femoral head (AONFH) group, a steroid-induced osteonecrosis of the femoral head (SONFH) group, and a normal control (NC) group (n=16, 29, and 32, respectively). Ultra-performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS) was used to detect the lipidomics analysis in the peripheral blood samples of subjects and identify the underlying biomarkers. The samples were preprocessed, the partial least squares discriminant analysis (PLS-DA) was adopted, and the variable importance for the projection (VIP) values were calculated to measure the expression pattern of each lipid metabolite and observe the influence and explanatory power of the expression pattern of each lipid metabolite on the classification and discrimination between the different groups. The lipid metabolites with fold change (FC)>2, P<0.05 and VIP>1 in the different groups were screened as differential lipids. Among them, the differential lipids co-existing in the AONFH group and the SONFH group were regarded as common differential lipids for ONFH, and the differential lipids that exist separately were regarded as specific differential lipids in the AONFH group or the SONFH group. Binary logistic regression was used to evaluate the diagnostic value of differential lipid metabolites on the basis of the receiver operator characteristic (ROC) curve analysis. Based on the disease stage information, the correlation between the differential lipids and the disease stage was analyzed in the AONFH group and the SONFH group.

In this study, 1 358 lipid metabolites were detected in each plasma sample. Compared with the NC group, there were significant difference in the expression patterns of lipid metabolism profiles in the AONFH group and the SONFH group. A total of 62 and 64 differential lipid metabolites were screened in the AONFH and SONFH patients (FC>2, P<0.05, VIP>1) respectively, and these differential lipids were mainly up-regulated in the disease samples. Nine differential lipid metabolites were further identified, which were shared by the AONFH group and the SONFH group; the area under the curve (AUC) in 6 kinds of lipid components was greater than 0.7, including 1-myristoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine, hypoxanthin, serotonin, PE (19:0/22:5), PE (19:0/22:5), and cholest-5-en-3-yl beta-D-glucopyranosiduronic acid. Fifty-three specific differential lipid metabolites were identified in the AONFH group, and 55 specific differential lipid metabolites were identified in the SONFH group. The AUC in 6 kinds of lipid components was greater than 0.9, including 1D-myo-Inositol 1,2-cyclic phosphate, L-pyroglutamic acid, DL-carnitine, 8-amino-7-oxononanoic acid, Clobetasol, and presqualene diphosphate. In the AONFH group, there were 9 differential lipid metabolites related to the disease stages, including LPG 18:1, serotonin, PC (22:4e/23:0), PC (19:2/18:5), hypoxanthin, PE (18:1/20:3), LPE 18:1, 1-stearoyl-2-arachidonoyl-sn-glycerol, and PE (16:0/18:1); with AONFH disease progresses from I/II stages to III/IV stages, the relative content of these 9 differential lipid metabolites was increased. In the SONFH group, 8 differential lipid metabolites were found to be related to the stage of the disease, including TM6076000, 4-(1,1-dimethylpropyl)phenol, D-617, asarone, phenylac-gln-OH, creatine, leu-pro, and 8-amino-7-oxononanoic acid; and with the SONFH progressed from stage I/II to stage III/IV, the content of these 8 differential lipid metabolites were gradually increased.

This study analyzes the characteristics of the plasma lipid metabolism profile in the AONFH and SONFH patients, and which identifies the differential lipid metabolites related to disease diagnosis and evaluation. These results provide evidence for exploring lipid metabolism alterations and the mining of novel lipid biomarkers for the ONFH.

The imbalance of osteogenic/adipogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) is closely related to steroid-induced avascular necrosis of the femoral head (SANFH). We aimed to investigate the epigenetic mechanism of intramedullary fat accumulation and continuous osteonecrosis after glucocorticoid (GC) withdrawal in SANFH.

An SANFH model was established in SD rats, which received an intermittent high GC dose for the first 4 weeks followed by an additional 4 weeks without GC. We explored the synergistic effects and mechanisms of C/EBPα and PPARγ on the differentiation of BMSCs by lentivirus-mediated gene knockdown and overexpression assays. A chromatin immunoprecipitation assay was performed to identify epigenetic modification sites on PPARγ in vivo and in vitro.

In the SANFH model, intramedullary fat was significantly increased, and the transcription factors C/EBPα and PPARγ were upregulated simultaneously in the femoral head. In vitro, C/EBPα promoted adipogenic differentiation of BMSCs by targeting the PPARγ signalling pathway, while overexpression of C/EBPα significantly impaired osteogenic differentiation. Further studies demonstrated that histone H3K27 acetylation of PPARγ played an important role in the epigenetic mechanism underlying SANFH. C/EBPα upregulates the histone H3K27 acetylation level in the PPARγ promoter region by inhibiting HDAC1. Additionally, inhibiting the histone acetylation level of PPARγ effectively prevented adipogenic differentiation, thus slowing the progression of SANFH.

Our results demonstrate the molecular mechanism by which C/EBPα regulates PPARγ expression by acetylating histones and revealed the epigenetic phenomenon in SANFH for the first time.

Atraumatic ONFH is one of the leading cause of hip morbidity in the working-age group. It is a multi-factorial disease whose root cause can be attributed to single-nucleotide polymorphism. Identifying such polymorphisms could pave the way for new modalities of treatment for ONFH.

Two databases were electronically searched for relevant articles. The articles were screened through titles, abstract and full texts to include the relevant studies. A secondary search was done through the reference list of selected articles.

A total of 52 studies were included among the 181 hits. All 181 were case-control studies. Summary of these studies identifies multiple SNPs which can cause ONFH. There were 117 SNPs in all 181 studies, of which 92 were associated with the causation of ONFH and 25 were protective against ONFH.

SNPs play an essential role in causing atraumatic ONFH. Identification of SNP that contribute to causing ONFH may help reduce the disease burden by early identification, diagnosis and treatment, including targeted gene therapy.

To develop and validate a prediction model based on targeted sequencing for glucocorticoid (GC)-associated osteonecrosis of the femoral head (GA-ONFH) in GC-treated adults.

This two-centre retrospective study was conducted between July 2015 and April 2019 at Zhongshan Hospital (training set) and the Sixth People's Hospital (test set) in Shanghai, China. All patients had a history of GC therapy, with a dose exceeding 2000 mg equivalent prednisone within 6 weeks. Patients were divided into two groups according to whether they were diagnosed with GA-ONFH within 2 years after GC initiation. Blood or saliva samples were collected for targeted sequencing of 358 single nucleotide polymorphisms and genetic risk score (GRS) calculating for developing GA-ONFH prediction model. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to evaluate and validate the model.

. The training set comprised 117 patients, while the test set comprised 30 patients for external validation. Logistic regression analysis showed that GRS was significantly associated with GA-ONFH (OR 1.87, 95% CI: 1.48, 2.37). The ROC and DCA curves showed that the multivariate model considering GRS, age at GC initial, sex and underlying diseases had a discrimination with area under the ROC curve (AUC) of 0.98 (95% CI: 0.96, 1.00). This model was further externally validated using the test set with an AUC of 0.91 (95% CI: 0.81, 1.00).

Our prediction model comprising GRS, age, sex and underlying diseases yields valid predictions of GA-ONFH incidence. It may facilitate effective screening and prevention strategies of GA-ONFH.

Septic shock is the major cause of childhood mortality. However, the application of corticosteroids remains controversial. This work aimed to analyze the source of controversy based on existing data and recent randomized controlled trials by meta-analysis and to assess whether it can avoid these factors to guide clinical treatment.

We searched the public databases up to 8 June 2019 and included only randomized controlled trials. The primary outcome was mortality. Sensitivity analysis, subgroup analysis, and dose-response meta-analysis were performed in this work.

We included twelve studies consisting of 701 children in the meta-analysis. For primary outcome, the fixed-effect model showed steroids could significantly reduce the mortality compared to the control (Odds Ratio: 0.67; 95% confidence interval: 0.46-0.98; P = .041). However, the random-effect model showed a negative result (Odds Ratio: 0.69; 95% confidence interval: 0.32-1.51; P = .252). None of the subgroup results rejected the null hypothesis that the overall effect equaled zero. Dose-response effect analysis showed that increased dosage at a low dosage might reduce the mortality, while at a high dosage, increasing the dose might increase the mortality. Moreover, the grading of recommendations assessment, development, and evaluation level of evidence is low for mortality.

Corticosteroid application is not recommended for septic shock children under current medical conditions.