ArticleDisease markers2022
Screening of Potential Biomarkers in the Peripheral Serum for Steroid-Induced Osteonecrosis of the Femoral Head Based on WGCNA and Machine Learning Algorithms.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 19 citations in OpenAlex.
- Vascularized bone organoids: current advances and a biomimetic platform for osteonecrosis of the femoral head.Bone research · 2026Review
- Advances in the mechanism for steroid-induced osteonecrosis of the femoral head.Bone research · 2026Review
- Identification of Senescence- and Inflammation-Related Genes and Immune Microenvironment Characterization in Intracranial AneurysmsEndocrine, metabolic & immune disorders drug targets · 2026Article
- Osteoimmune microenvironmental failure in osteonecrosis of the femoral head: a necrosis-inflammation-repair loop and immune-editing-inspired framework for hip preservation.Frontiers in immunology · 2026Review
- HGF knockdown suppresses ovarian cancer malignancy: insights from a transient receptor potential-related gene model.European journal of medical research · 2025Article
- Machine Learning and Weighted Gene Coexpression Network-Based Identification of Biomarkers Predicting Immune Profiling and Drug Resistance in Lung Adenocarcinoma.International journal of genomics · 2025Article
- Pathological mechanisms and related markers of steroid-induced osteonecrosis of the femoral head.Annals of medicine · 2024Review
- Integrated analysis ceRNA network of autophagy-related gene RNF144B in steroid-induced necrosis of the femoral head.Scientific reports · 2024Article
- A Network Pharmacology Approach and Validation Experiments to Investigate the Mechanism of Wen-Dan Decoction in the Treatment of SINFH.Combinatorial chemistry & high throughput screening · 2024Article
- Bioinformatics-Based Analysis of Key Genes in Steroid-Induced Osteonecrosis of the Femoral Head That Are Associated with Copper Metabolism.Biomedicines · 2023Article
- Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms.Frontiers in immunology · 2023Article
- Identifying potential biomarkers for non-obstructive azoospermia using WGCNA and machine learning algorithms.Frontiers in endocrinology · 2023Article
- LTF induces senescence and degeneration in the meniscus via the NF-κB signaling pathway: A study based on integrated bioinformatics analysis and experimental validation.Frontiers in molecular biosciences · 2023Article
- Identification of hub genes of Parkinson's disease through bioinformatics analysis.Frontiers in neuroscience · 2022Article
- The role of immune cells in modulating chronic inflammation and osteonecrosis.Frontiers in immunology · 2022Review
- Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma.Frontiers in immunology · 2022Article
- Screening of potential biomarkers in peripheral blood of patients with depression based on weighted gene co-expression network analysis and machine learning algorithms.Frontiers in psychiatry · 2022Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSteroid-induced osteonecrosis of the femoral head (SONFH) has produced a substantial burden of medical and social experience. However, the current diagnosis is still limited. Thus, this study is aimed at identifying potential biomarkers in the peripheral serum of patients with SONFH.
methodsThe expression profile data of SONFH (number: GSE123568) was acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in SONFH were identified and used for weighted gene coexpression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the biological functions. The protein-protein interaction (PPI) network and machine learning algorithms were employed to screen for potential biomarkers. Gene set enrichment analysis (GSEA), transcription factor (TF) enrichment analysis, and competing endogenous RNA (ceRNA) network were used to determine the biological functions and regulatory mechanisms of the potential biomarkers.
resultsA total of 562 DEGs, including 318 upregulated and 244 downregulated genes, were identified between SONFH and control samples, and 94 target genes were screened based on WGCNA. Moreover, biological function analysis suggested that target genes were mainly involved in erythrocyte differentiation, homeostasis and development, and myeloid cell homeostasis and development. Furthermore, GYPA, TMCC2, and BPGM were identified as potential biomarkers in the peripheral serum of patients with SONFH based on machine learning algorithms and showed good diagnostic values. GSEA revealed that GYPA, TMCC2, and BPGM were mainly involved in immune-related biological processes (BPs) and signaling pathways. Finally, we found that GYPA might be regulated by hsa-miR-3137 and that BPGM might be regulated by hsa-miR-340-3p.
conclusionGYPA, TMCC2, and BPGM are potential biomarkers in the peripheral serum of patients with SONFH and might affect SONFH by regulating erythrocytes and immunity.
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