Integrative Analysis and Experimental Validation Identify Potential m6A-Related Biomarkers for Osteoporosis

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Authors: Zhenyang Wang, Yongqin Chen, Yuxuan Yang, Biteng Xu, Xiejia Jiao, Lei Qi
Cited by: 1
References: 40

Abstract

Background: This study investigates the role of N6-methyladenosine (m6A) regulators in osteoporosis (OP) and their interplay with the immune microenvironment, aiming to identify potential m6A-related biomarkers for OP risk assessment and treatment. Methods: Transcriptomic data from GEO datasets were analyzed for differential expression of 22 m6A regulators and immune infiltration patterns. Consensus clustering and m6Ascore grouping defined molecular subtypes, while machine learning algorithms identified potential biomarkers, leading to the construction and validation of a nomogram. Experimental validation involved peripheral blood monocytes (PBMCs) transcriptome sequencing and Western blot of bone tissue. Results: FTO, HNRNPC, and METTL4 were upregulated, while CBLL1 and YTHDF2 were downregulated in OP, with two distinct m6A modification patterns and immune phenotypes identified. METTL4, HIRA, MATN4, and YTHDF2 were selected as potential biomarkers, and the nomogram demonstrated favorable predictive performance in training and external datasets. Single-cell RNA sequencing confirmed the cellular distribution of these biomarkers. HIRA heterogeneity in Marrow Mesenchymal Stem Cells (BMSCs) was associated with distinct cell–cell communication patterns. Transcriptome sequencing confirmed HIRA RNA downregulation in OP PBMCs, and Western blot verified decreased HIRA protein in OP bone tissue. Conclusions: This study establishes a potential m6A-related biomarker signature for OP and provides multi-level experimental evidence that HIRA is a consistently downregulated biomarker, linking epigenetic modification to immune dysregulation in osteoporosis.

Fields of Study & Subjects

RNA modifications and cancer Bone Metabolism and Diseases Ubiquitin and proteasome pathways

Publication details

Journal / source
Genes
Publisher
MDPI AG
Volume
17
Issue
4
Pages
458–458
Publication date
14 April 2026
Language
EN