A higher frequency of peripheral blood activated B cells in patients with non-traumatic osteonecrosis of the femoral head

Flavonoids and flavonoid-based nanoparticles for the treatment of arthritis

Arthritis is an autoimmune disorder that predominantly causes inflammation and impacts peripheral joints. Even though immunosuppressive and NSAIDs or non-steroidal anti-inflammatory medicines are implemented for the management of this disorder, sbut they carry some severe side effects along with them. Therefore, society requires treatment with fewer side effects and powerful anti-arthritic properties, such as flavonoids. These are the most prevalent phenolic compounds found in nature that have potent antioxidant, and immunomodulatory activity and there are several bioactive flavonoids that carry potent anti-inflammatory properties. Nevertheless, only a handful has reached their clinical use. Still, in both clinical and preclinical models of arthritis, flavonoids found in the diet have been shown to reduce swelling in joints and arthritis symptoms. There are only a few scientific studies regarding their mechanisms of action in arthritis. However, the arthritic potential of dietary flavonoids is insufficient because of their limited solubility, absorption, and fast metabolism. Nanocarriers may enhance the bioavailability of flavonoids. This review examines the therapeutic effects of the most prevalent and abundant flavonoid groups on arthritis. Specifically, the modes of action of the most important flavonoids on the chemical messengers in the body that contribute to the signalling of joint inflammation-related indicators of arthritis are discussed in more detail.

Risk factors and prediction model for osteonecrosis of the femoral head in female systemic lupus erythematosus

Background

Osteonecrosis of the femoral head (ONFH) is a severe complication of systemic lupus erythematosus (SLE) and occurs more frequently in SLE patients than in other autoimmune diseases, which can influence patients' life quality. The objective of this research was to analyze risk factors for the occurrence of ONFH in female SLE patients, construct and validate a risk nomogram model.

Methods

Clinical records of SLE patients who fulfilled the 1997 American College of Rheumatology SLE classification criteria were retrospectively analyzed. The Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis were used to summarize the independent risk factors of ONFH in female SLE patients, which were used to develop a nomogram. The predictive performance of the nomogram was assessed using the receiver characteristic (ROC) curve, calibration curves and decision curve analysis (DCA).

Results

793 female SLE patients were ultimately included in this study, of which 87 patients (10.9%) developed ONFH. Ten independent risk factors including disease duration, respiratory involvement, menstrual abnormalities, Sjögren's syndrome, osteoporosis, anti-RNP, mycophenolate mofetil, cyclophosphamide, biologics, and the largest daily glucocorticoid (GC) were identified to construct the nomogram. The area under the ROC curve of the nomogram model was 0.826 (95% CI: 0.780-0.872) and its calibration for forecasting the occurrence of ONFH was good (χ2 = 5.589, P = 0.693). DCA showed that the use of nomogram prediction model had certain application in clinical practice when the threshold was 0.05 to 0.95. In subgroup analysis, we found that the risk of ONFH was significantly increased in age at SLE onset of ≤ 50 years old, largest daily GC dose of ≥50 mg and the therapy of GC combined with immunosuppressant patients with menstrual abnormalities.

Conclusion

Menstrual abnormalities were the first time reported for the risk factors of ONFH in female SLE patients, which remind that clinicians should pay more attention on female SLE patients with menstrual abnormalities and take early interventions to prevent or slow the progression of ONFH. Besides, the nomogram prediction model could provide an insightful and applicable tool for physicians to predict the risk of ONFH.

Exploring the genetic association between immune cells and susceptibility to osteonecrosis using large-scale population data

Objectives

Research shows a close association between aberrant immune reactions in osteonecrotic tissues and immune cell infiltration. However, due to limitations in sample size and dataset comprehensiveness, the causal relationship between them is not fully established. This study aims to determine whether there is a causal relationship using a larger and more diverse dataset.

Methods

We conducted a comprehensive Mendelian Randomization (MR) analysis to investigate the causal relationship between immune cell characteristics and osteonecrosis. Utilizing publicly available genetic data, we explored the causal relationships between 731 immune cell features and 604 cases from the FinnGen Finnish database, as well as 257 cases from the UK Biobank database with osteonecrosis data. The inverse-variance weighted (IVW) method was used for the primary analysis, and we employed sensitivity analyses to assess the robustness of the main results. In addition, considering data from the two databases used in this study, a meta-analysis was conducted on the significant immune cells associated with osteonecrosis (FDR <0.05).

Results

our findings suggested that specific immune cell signatures, such as CD20- % lymphocytes, CD62L-monocytes, and CD33br HLA DR+ CD14-cells were associated with increased odds of osteonecrosis. In contrast, EM CD4+ activated cells and DP (CD4+ CD8+) T cells were associated with decreased odds. Notably, osteonecrosis was associated with a potential decrease in CD45 on immature MDSC cell content.

Conclusion

From a genetic perspective, we demonstrated a close association between immune cells and osteonecrosis. These findings significantly enhance our understanding of the interplay between immune cell infiltration and the risk of osteonecrosis, contributing to the potential design of therapeutic strategies from an immunological standpoint.

Emerging factors affecting peri-implant bone metabolism

Implant dentistry has evolved to the point that standard implant osseointegration is predictable. This is attributed in part to the advancements in material sciences that have led toward improvements in implant surface technology and characteristics. Nonetheless, there remain several cases where implant therapy fails (specifically at early time points), most commonly attributed to factors affecting bone metabolism. Among these patients, smokers are known to have impaired bone metabolism and thus be subject to higher risks of early implant failure and/or late complications related to the stability of the peri-implant bone and mucosal tissues. Notably, however, emerging data have unveiled other critical factors affecting osseointegration, namely, those related to the metabolism of bone tissues. The aim of this review is to shed light on the effects of implant-related factors, like implant surface or titanium particle release; surgical-related factors, like osseodensification or implanted biomaterials; various drugs, like selective serotonin reuptake inhibitors, proton pump inhibitors, anti-hypertensives, nonsteroidal anti-inflammatory medication, and statins, and host-related factors, like smoking, diet, and metabolic syndrome on bone metabolism, and aseptic peri-implant bone loss. Despite the infectious nature of peri-implant biological complications, these factors must be surveyed for the effective prevention and management of peri-implantitis.

Exploring the potential mechanism of Taohong Siwu decoction in the treatment of avascular necrosis of the femoral head based on network pharmacology and molecular docking

Based on network pharmacology and molecular docking, this study seeks to investigate the mechanism of Taohong Siwu decoction (THSWD) in the treatment of avascular necrosis of the femoral head (AVNFH). The Traditional Chinese Medicine Systems Pharmacology database was used in this investigation to obtain the active ingredients and related targets for each pharmaceutical constituent in THSWD. To find disease-related targets, the terms "avascular necrosis of the femoral head," "necrosis of the femoral head," "steroid-induced necrosis of the femoral head," "osteonecrosis," and "avascular necrosis of the bone" were searched in the databases DisGeNET, GeneCards, Comparative Toxicogenomics Database, and MalaCards. Following the identification of the overlap targets of THSWD and AVNFH, enrichment analysis using gene ontology, Kyoto Encyclopedia of Genes and Genomes, Reactome, and WikiPathways was conducted. The "THSWD-drug-active compound-intersection gene-hub gene-AVNFH" network and protein-protein interaction network were built using Cytoscape 3.9.1 and string, and CytoHubba was used to screen hub genes. The binding activities of hub gene targets and key components were confirmed by molecular docking. 152 prospective therapeutic gene targets were found in the bioinformatics study of ONFH treated with THSWD, including 38 major gene targets and 10 hub gene targets. The enrichment analysis of 38 key therapeutic targets showed that the biological process of gene ontology analysis mainly involved cytokine-mediated signaling pathway, angiogenesis, cellular response to reactive oxygen species, death-inducing signaling complex. The Kyoto Encyclopedia of Genes and Genomes signaling pathway mainly involves TNF signaling pathway, IL-17 signaling pathway, and the Recactome pathway mainly involves Signaling by Interleukins, Apoptosis, and Intrinsic Pathway for Apoptosis. WikiPathways signaling pathway mainly involves TNF-related weak inducer of apoptosis signaling pathway, IL-18 signaling pathway. According to the findings of enrichment analysis, THSWD cured AVNFH by regulating angiogenesis, cellular hypoxia, inflammation, senescence, apoptosis, cytokines, and cellular proliferation through the aforementioned targets and signaling pathways. The primary component of THSWD exhibits a strong binding force with the key protein of AVNFH. This study sheds new light on the biological mechanism of THSWD in treating AVNFH by revealing the multi-component, multi-target, and multi-pathway features and molecular docking mechanism of THSWD.

Identification of key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head based on machine learning

BACKGROUND

This study was aimed to identify key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head (SONFH) based on machine learning algorithm.

METHODS

The SONFH dataset GSE123568 (including 30 SONFH patients and 10 controls) was used in this study. The differentially expressed genes (DEGs) were selected between SONFH and control groups, which were subjected to WGCNA. Ferroptosis-related genes were downloaded from FerrDb V2, which were then compared with DEGs and module genes. Two machine learning algorithms were utilized to identify key ferroptosis-related genes, and the underlying mechanisms were analyzed by GSEA. Correlation analysis between key ferroptosis-related genes and immune cells was analyzed by Spearman method. The drug-gene relationships were predicted in CTD.

RESULTS

Total 2030 DEGs were obtained. WGCNA identified two key modules and obtained 1561 module genes. Finally, 43 intersection genes were identified as disease-related ferroptosis-related genes. After LASSO regression and RFE-SVM algorithms, 4 intersection genes (AKT1S1, BACH1, MGST1 and SETD1B) were considered as key ferroptosis-related gene. The 4 genes were correlated with osteoclast differentiation pathway. Twenty immune cells with significant differences were obtained between the groups, and the 4 key ferroptosis-related genes were correlated with most immune cells. In CTD, 41 drug-gene relationship pairs were finally obtained.

CONCLUSIONS

The 4 key ferroptosis-related genes, AKT1S1, BACH1, MGST1 and SETD1B, were identified to play a critical role in SONFH progression through osteoclast differentiation and immunologic mechanisms. Additionally, all the 4 genes had good disease prediction effect and could act as biomarkers for the diagnosis and treatment of SONFH.

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.

Network-Based Pharmacology and Bioinformatics Study on the Mechanism of Action of Gujiansan in the Treatment of Steroid-Induced Avascular Necrosis of the Femoral Head

Objective

To investigate the main pharmacological basis and mechanism of action of Gujiansan in the treatment of steroid-induced avascular necrosis of the femoral head (SANFH).

Methods

The active constituents and targets of Gujiansan were screened by using TCMSP and other databases, and relevant disease targets were obtained by analyzing the microarray of SANFH in the GEO database. The intersection of the two was taken to obtain the potential targets of Gujiansan for the treatment of SANFH, and key active constituents were screened with the “active constituent-target” network constructed by the Cytoscape software; then, the STRING database was used to construct the protein interaction network to screen the key targets. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of key targets were performed by the DAVID database, and the relationship between the “key active constituent-key target-key signaling pathway” was explored. Finally, the molecular docking between key active constituents and key targets was verified. In addition, qPCR detection technology was used to evaluate the preventive and therapeutic effects of key active constituents of Gujiansan in a rat osteoblast model of SANFH to verify the possible mechanism of the effect of Gujiansan in the treatment of SANFH.

Results

(1) 106 active constituents and 55 targets were obtained for the treatment of SANFH. (2) Quercetin, luteolin, kaempferol, cryptotanshinone, and naringenin were the key active constituents for the treatment of SANFH. (3) IL1B, STAT3, CAT, PTGS2, and MAPK3 were the key targets for the treatment of SANFH. (4) IL1B, STAT3, CAT, PTGS2, MAPK3, and HMOX1 are key targets in the protein interaction network. (5) DAVID enrichment analysis mainly covers the regulation of DNA-binding transcription factor activity, positive regulation of cytokine production, and response to oxidative stress and other biological processes, involving IL-17, AGE-RAGE, C-type lectin receptor, and other signaling pathways. (6) Gujiansan is a multitarget and multisignaling pathway for the treatment of SANFH. (7) Good binding activity exists between key active constituents and key targets.

Conclusion

This study analyzes the potential mechanism of action of Gujiansan in the treatment of SANFH with network pharmacology, which can provide a reference for the further study of its pharmacological basis and targets.

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.

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.

CD4+ T Cell Profile and Activation Response in Sickle Cell Disease Patients with Osteonecrosis

Recent evidence suggests that abnormalities involving CD4⁺T lymphocytes are associated with the pathophysiology of osteonecrosis (ON); however, few studies have addressed the CD4⁺T cells in ON related to sickle cell disease (SCD/ON). In addition, T cells producing multiple cytokines simultaneously are often present in the inflammatory milieu and may be implicated in the immune response observed in SCD/ON. In the present study, we aimed to characterize the functional status of CD4⁺T cells in SCD by simultaneously determining the frequency of IFN-γ ⁺, IL-4⁺, and IL-17⁺ CD4⁺T in cell cultures under exogenous stimuli. Peripheral blood mononuclear cells (PB-MNCs) from 9 steady-state SCD patients, 15 SCD/ON patients, and 19 healthy controls had functional status of CD4⁺T cells analyzed. Bone marrow mononuclear cells (BM-MNCs) from 24 SCD/ON patients (SCD BM) and 18 patients with ON not related to SCD (non-SCD BM) were also analyzed. We found that PB-MNC of SCD patients with or without ON presented significantly reduced TCD4⁺, TCD8⁺, and TCD4⁺ naïve cell frequencies and increased frequency of circulating CD4⁺T cells able to simultaneously produce IFN-γ ⁺/IL4⁺ and IL-17⁺/IL4⁺ compared to healthy controls. Conversely, the polyclonal stimulation of BM-MNC induced an increased frequency of CD4⁺IFN-γ ⁺ and CD4⁺IL-17⁺ in SCD BM compared to non-SCD BM. The increased proportion of CD4⁺ T cells able to produce a broad spectrum of proinflammatory cytokines after a strong stimulus indicates that the immune system in SCD/ON patients presents an expressive pool of partially differentiated cells ready to take on effector function. It is possible that this increased subpopulation may extend to inflammatory sites of target organs and may contribute to the maintenance of inflammation and the pathophysiology of osteonecrosis in sickle cell disease.

TNF-α regulates the early development of avascular necrosis of the femoral head by mediating osteoblast autophagy and apoptosis via the p38 MAPK/NF-κB signaling pathway

Previous studies have shown that the tumor necrosis factor-α (TNF-α) levels in serum and bone tissues formed in avascular necrosis of femoral head (ANFH) patients were higher than those of normal individuals, indicating TNF-α might play a role in the pathogenesis of ANFH. However, the underlying mechanisms remain unclear. Hematoxylin and eosin staining was performed to show the pathological changes of ANFH bone tissues. TNF-α expression in normal and ANFH tissues was examined by quantitative real-time polymerase chain reaction and western blot analyses. Osteoblast autophagy and apoptosis, as well as signaling pathways activation, were measured by their corresponding marker proteins. Osteoblast proliferation, autophagy, and apoptosis were evaluated using cell counting kit-8, transmission electron microscopy, and flow cytometry. The structures of bone tissues of ANFH were obviously damaged. TNF-α expression was significantly upregulated in ANFH bone tissues compared to normal tissues. Autophagy and apoptosis were remarkably promoted, and p38 mitogen-activated protein kinase (MAPK)/nuclear factor-κB (NF-κB) signaling pathways were markedly activated in ANFH. Suppression of the p38 MAPK/NF-κB pathway significantly attenuated the TNF-α-induced autophagy, however, enhanced the TNF-α-induced apoptosis in osteoblasts. Increased TNF-α in ANFH regulated osteoblast autophagy and apoptosis by p38 MAPK/NF-κB signaling pathways, blocking the pathway by inhibitors exacerbated TNF-α-induced apoptosis through impairing autophagy flux.

The Role of Immune Regulatory Cells in Nontraumatic Osteonecrosis of the Femoral Head: A Retrospective Clinical Study

The immunologic factors have been implicated in the pathogenesis of osteonecrosis. We aimed to investigate the potential role of immune regulatory cells in the development of osteonecrosis of femoral head (ONFH). Sixty-seven patients diagnosed with ONFH and fifty-eight age-, height-, and weight-matched healthy subjects were included in this retrospective study between September 2015 and September 2018. The flow cytometry was used to test the count, percentage, and ratio of T and B lymphocyte subsets in peripheral blood. The T and B lymphocyte levels were compared among different ARCO stages, CJFH types, and etiology groups. The total lymphocyte count, CD3⁺T cells, Ts cells (CD3⁺CD8⁺), B-1 cell count, and B-1 cells (CD5⁺CD19⁺) were significantly higher in the patients with ONFH than those in the control subjects. The percentage of T lymphocytes in the patients with ARCO IV stage was significantly smaller than that in the ONFH patients with ARCO II and III stages. The percentage of inhibitory T lymphocytes in patients with CJFH type L3 was significantly smaller than that in the patients with types L1 and L2. In terms of the different ONFH etiologies, the total lymphocyte count and Ts cells (CD3⁺CD8⁺) were significantly lower in the ONFH patients induced by excessive alcohol intake than those in the idiopathic ONFH patients. Our results seem to indicate that immune regulatory cells, such as T and B lymphocytes, play an important role in the pathogenesis of ONFH. The development and progression of ONFH may be associated with immune system imbalance.

TGF‑β1 expression in adults with non‑traumatic osteonecrosis of the femoral head

Non-traumatic osteonecrosis of the femoral head (NONFH) is a common clinical osteoarthropathy. The present study aimed to investigate the association between transforming growth factor β1 (TGF‑β1) and NONFH. Femoral head specimens were collected from patients with NONFH. Patients with traumatic osteonecrosis served as the control. Hematoxylin and eosin (H&E) staining was used to visualize the bone tissue architecture. Immunohistochemistry and densitometry were performed to quantify TGF‑β1 expression in tissues. Flow cytometry was used to detect cluster of differentiation (CD)3+, CD4+ and CD8+ cells, and the ratio of CD4+ to CD8+ T cells in the peripheral blood. H&E staining revealed osteonecrosis, disintegration of osteocytes with karyopyknosis and karyorrhexis, loss of osteocyte lacunae, aberrantly arranged circumferential lamellae, as well as dissolution of the lamellae and subtle osteogenesis in the experimental group, as opposed to the control group. Immunohistochemistry revealed that the expression of TGF‑β1 was significantly reduced in the experimental group (P<0.01). Further, the NONFH group had a decrease in the CD3+ and CD4+ cell populations (P<0.05 and P<0.01, respectively), an increase in the CD8+ cell population (P<0.05), as well as a reduction in the ratio of CD4+ to CD8+ cells (P<0.01). The present study indicated that TGF‑β1 expression was reduced in NONFH. This was associated with impaired repairing capacity of the femoral head and dysregulated subsets of T‑lymphocytes and possible immune functions.

Differential proteomic screening and identification for non-traumatic necrotic femoral osseous tissue

Currently, there is a lack of effective early screening and detection methods for femoral head necrosis. Current research on most orthopedic diseases focuses on proteomics in the preliminary stage. The recent fluorescence differential in gel electrophoresis (DIGE) has advantages such as a high reproducibility, high sensitivity, high throughput, and high dynamic range. It is currently one of the most widely used quantitative proteomic research means. We conducted this study to investigate the pathogenesis of non-traumatic femoral head necrosis using the fluorescence DIGE to screen non-traumatic femoral head necrosis based on proteomics and provide a theoretical basis for screening possible biomarkers and molecular targeted treatment. The DIGE technique was used to separate the protein. An electrophoretogram was established on the basis of scanning and analysis. Identification and a bioinformatics analysis were conducted for the differential protein. The protein with differential expression of over 2-fold was excavated and ionized by means of substrate assisted laser desorption. The flight time was identified with a mass spectrometer (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, MALDI-TOF/TOF). The formation on sequences, structures and functions of these proteins were obtained through database retrieval. Western blot analysis was used to verify the differential protein expression and the reliability of the DIGE result was verified. DIGE was used to successfully separate 1,500±40 protein spots. There were 252 significant differential protein spots. The Ettan™ Spot Picker automatic work station was used to excavate 49 significant differential protein spots with expression difference over 2-fold. The MALDI-TOF/TOF mass spectrometer was used to identify these differential protein spots. Six proteins were identified in total, which include apolipoprotein A1 (APOA1), fibrous protein original chain, fibrous protein original chain, serum albumin, sulfur-oxygen protein peroxiredoxin 2 (PRDX2) and actin. APOA1 and PRDX2 were subject to western blot analysis detection; results were consistent with the DIGE result. Based on an analysis of the biological information, these proteins may be associated with the incidence and progression of femoral head necrosis.

Association of apolipoprotein A5 genetic polymorphisms with steroid-induced osteonecrosis of femoral head in a Chinese Han population

BACKGROUND

Previous studies suggested that apolipoprotein A5 (ApoA5) genetic polymorphisms (SNPs) may result in lipid metabolism disorders. Therefore, genetic polymorphisms in ApoA5 may be associated with the occurrence of osteonecrosis of femoral head (ONFH).

METHODS

We designed a case-control study including 223 patients of osteonecrosis and 201 age- and sex-matched control subjects to analyze the association between ApoA5 polymorphisms and susceptibility of steroid-induced ONFH. We utilized polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method to genotype two SNPs (rs662799 and rs3135506) in ApoA5 gene.

RESULTS

We found both rs662799 and rs3135506 were associated with the risk of ONFH in codominant, dominant, and recessive model, respectively. Haplotype analyses suggested that T-C haplotype was associated with decreased risk of ONFH, whereas the haplotype C-C was significantly associated with an increased risk of ONFH.

CONCLUSION

Our study suggested that ApoA5 genetic polymorphisms were associated with susceptibility to ONFH in Chinese population. However, our results need further investigation with large sample size and various populations.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_229.

Relationship between the Apolipoprotein AI, B gene polymorphism and the risk of non-traumatic osteonecrosis

BACKGROUND

Previous studies suggested that Apolipoprotein AI (ApoAI) and apolipoprotein B (ApoB) gene polymorphisms may result in lipid metabolism disorders. Genetic polymorphisms in these genes may be associated with the occurrence of osteonecrosis.

METHODS

We designed a case-control study including 429 patients of osteonecrosis and 368 age- and sex-matched control subjects. Polymerase chain reaction was used to amplify the DNA fragments in promoter -75 G > A of ApoAI gene and EcoR I, Xba I and 3'-VNTR of ApoB gene in osteonecrosis patients and healthy controls. We utilized polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method to genotype these four single nucleotide polymorphisms (SNPs).

RESULTS

For -75 G > A polymorphism of ApoAI, AA genotype frequency (0.501) was significantly higher in patients with osteonecrosis than that in control (0.462) subjects (P <0.001), GA genotype frequency (0.170) was significantly lower than that in the control (0.310) group (P <0.0001). In osteonecrosis patients, the odds ratio (OR) of A allele was 3.932 (95% CI: 3.0847 ~ 5.0123), which suggested that subjects carrying A allele of promoter region -75 G > A of ApoAI gene had higher susceptibility to osteonecrosis than G allele carriers. The genotype and allele frequency distributions showed no significant difference in EcoR I, Xba Iand 3'-VNTR loci of ApoB gene between the osteonecrosis group and control group.

CONCLUSION

Our study suggested that ApoAI gene -75G > A polymorphism may be associated with susceptibility to osteonecrosis in Chinese population. However, our results need further investigation with large sample size and various populations.