Complex causal association between genetically predicted 731 immunocyte phenotype and osteonecrosis: A bidirectional Two-sample mendelian randomization analysis.

PURPOSE: Previous studies have explored the role of immune cells on osteonecrosis. This Mendelian randomization (MR) study further assessed 731 immunocyte phenotypes on osteonecrosis whether a causal relationship exists and provides some evidence of causality. METHODS: The 731 immunocyte phenotypes and osteonecrosis data used in this study were obtained from their respective genome-wide association studies (GWAS). We used inverse variable weighting (IVW) as the primary analysis method. In addition, we simultaneously employed multiple analytical methods, including MR-Egger, weighted mode, simple mode, and weighted median, to strengthen the final results. Finally, sensitivity analyses were conducted to verify the stability and feasibility of the data. RESULTS: The results of the IVW method of MR analysis showed that 8 immunocyte phenotypes were positively associated with osteonecrosis (P<0.05, OR > 1); 18 immunocyte phenotypes were negatively associated with osteonecrosis (P<0.05, OR<1), none of which were heterogeneous or horizontally pleiotropic (P > 0.05) or reverse causality. In addition to this, in reverse MR, osteonecrosis was positively associated with 10 additional immunocyte phenotypes (P<0.05, OR > 1) and negatively associated with 14 immunocyte phenotypes (P<0.05, OR<1). And none of them had heterogeneity and horizontal pleiotropy (P > 0.05) or reverse causality. CONCLUSIONS: We demonstrated a complex causal relationship between multiple immune phenotypes and osteonecrosis through a comprehensive two-way two-sample MR analysis, highlighting the complex pattern of interactions between the immune system and osteonecrosis.

No evidence of genetic causality between diabetes and osteonecrosis: a bidirectional two-sample Mendelian randomization analysis.

OBJECTIVE: This study aimed to examine whether diabetes mellitus is causally associated with osteonecrosis. METHOD: Using publicly accessible genome-wide association study statistics, a bidirectional two-sample Mendelian randomization analysis was carried out. In order to determine whether diabetes has a causal effect on osteonecrosis and whether osteonecrosis has a causal effect on diabetes, we extracted six date on diabetes in Europeans from IEU OpenGWAS and GWAS Catalogue and osteonecrosis in Europeans from FinnGen. We then evaluated the data using inverse variance weighting, MR-Egger regression, weighted median, weighted mode, and simple mode. The results' stability and dependability were then evaluated using sensitivity analysis and heterogeneity analysis. Finally, meta-analysis is used to further confirm if there is a relationship between diabetes and osteonecrosis. RESULTS: When diabetes was used as an exposure factor, MR-Egger regression showed that directional fold product was unlikely to bias the results. Cochran's Q test showed only minor heterogeneity in a few data sets. Multidirectional tests Egger-intercept, MR-PRESSO and funnel plots for most data did not show multidirectional and asymmetry at the gene level. Most of the IVW results showed no causal relationship between diabetes mellitus and osteonecrosis. The results of meta-analysis of IVW methods further confirmed the absence of a causal relationship. Inverse MR analysis also showed no causal relationship between osteonecrosis and diabetes. CONCLUSION: Results of bidirectional MR analysis show no evidence of causal relationship between diabetes and osteonecrosis.

Knowledge mapping of programmed cell death in osteonecrosis of femoral head: a bibliometric analysis (2000-2022).

BACKGROUND: Osteonecrosis of the femoral head (ONFH) is a common, refractory and disabling disease of orthopedic department, which is one of the common causes of hip pain and dysfunction. Recent studies have shown that much progress has been made in the research of programmed cell death (PCD) in ONFH. However, there is no bibliometric analysis in this research field. This study aims to provide a comprehensive overview of the knowledge structure and research hot spots of PCD in ONFH through bibliometrics. METHOD: The literature search related to ONFH and PCD was conducted on the Web of Science Core Collection (WoSCC) database from 2002 to 2021. The VOSviewers, "bibliometrix" R package and CiteSpace were used to conduct this bibliometric analysis. RESULTS: In total, 346 articles from 27 countries led by China and USA and Japan were included. The number of publications related to PCD in ONFH is increasing year by year. Shanghai Jiao Tong University, Xi An Jiao Tong University, Wuhan University and Huazhong University of Science and Technology are the main research institutions. Molecular Medicine Reports is the most popular journal in the field of PCD in ONFH, and Clinical Orthopaedics and Related Research is the most cocited journal. These publications come from 1882 authors among which Peng Hao, Sun Wei, Zhang Chang-Qing, Zhang Jian and Wang Kun-zheng had published the most papers and Ronald S Weinstein was cocited most often. Apoptosis, osteonecrosis, osteonecrosis of the femoral head, glucocorticoid and femoral head appeared are the main topics the field of PCD in ONFH. Autophagy was most likely to be the current research hot spot for PCD in ONFH. CONCLUSION: This is the first bibliometric study that comprehensively summarizes the research trends and developments of PCD in ONFH. This information identified recent research frontiers and hot directions, which will provide a reference for scholars studying PCD in ONFH.

Pyroptosis -related potential diagnostic biomarkers in steroid-induced osteonecrosis of the femoral head.

PURPOSE: Steroid-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. METHODS: There 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. RESULTS: A 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. CONCLUSIONS: There 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.