Evidence map›Paper›PMID 39827330›Full record

ArticleMolecular biotechnology2026

Exploration of the Biological Function of Ferroptosis in Bone Nonunion: An Analysis of Bioinformatics Combined Mendelian Randomization.

Jun Yu, Kai Feng, Ming Yang, Kaijie Yang, Yun Jin, Zhanhu Mi

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Article in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jun YuOrthopedic Trauma, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
Kai FengNingxia Medical University, Yinchuan, 750004, China.
Ming YangNingxia Hui Autonomous Region People's Hospital, Yinchuan, 750002, China.
Kaijie YangOrthopedic Trauma, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
Yun JinOrthopedic Trauma, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
Zhanhu MiOrthopedic Trauma, General Hospital of Ningxia Medical University, Yinchuan, 750004, China. mizhanhu2024@163.com.ORCID http://orcid.org/0009-0004-4286-8980

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To deeply investigate the mechanism of ferroptosis-related genes in the process of bone nonunion based on the GEO database. And using Mendelian randomization to explore the causal association of 15 trace elements with the occurrence of bone nonunion. Bone nonunion RNA-seq data were retrieved and downloaded from the GEO database. The differentially expressed genes in bone nonunion were identified using two differential expression analysis methods, "limma" and "WGCNA". Random Forest Tree, Support Vector Machine, and Lasso-cox were used to analyze and screen the genes related to ferroptosis in bone nonunion; A risk model of bone nonunion was constructed based on the screened ferroptosis-related genes; based on this, the pathway mechanism of ferroptosis-related genes involved in the occurrence and development of bone nonunion was further investigated. Mendelian randomization analysis was performed using inverse variance weighting as the main analysis method, and weighted median, Weighted mode, Mr-Egger, and Simple mode were used as complementary methods. Heterogeneity was detected using Cochran's Q test and funnel plot analysis, horizontal pleiotropy was detected using Mr-Egger intercept, and sensitivity analyses were performed using the "leave-one-out" method. PTGS2/PRKCA/MAPK14 all showed excellent diagnostic efficacy for bone nonunion. The risk prediction model based on PTGS2, PRKCA, and MAPK14 showed good predictive efficacy and clinical benefit rate for bone nonunion. Ferroptosis core gene PRKCA may be involved in the VEGF signaling pathway to affect the cell cycle and inhibit fracture healing. MR analysis suggests that Potassium and Vitamin E are protective factors for the development of bone nonunion. Ferroptosis genes PTGS2/PRKCA/MAPK14 are potential diagnostic targets for bone nonunion. The down-regulation of PRKCA expression may inhibit fracture healing through the VEGF signaling pathway during the growth of blood vessels at fracture breaks. The results of MR suggested that Potassium and Vitamin E have a promoting effect on fracture healing.

Indexed as

Computational BiologyFerroptosisFractures, UnunitedMendelian Randomization AnalysisCyclooxygenase 2Gene Expression ProfilingGene Regulatory NetworksHumansCyclooxygenase 2Bone nonunionFerroptosisMachine learningMendelian randomizationTrace elementVEGF signaling pathway

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.