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Identification of Key Osteoporosis Genes Through Comparative Analysis of Men's and Women's Osteoblast Transcriptomes

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Abstract

Osteoporosis disproportionately affects older women, yet gender differences in human osteoblasts remain unexplored. Identifying mechanisms and biomarkers of osteoporosis will enable the development of preventative and therapeutic approaches. Transcriptome data of 187 osteoblast samples from men and women were compared. Differentially expressed genes (DEGs) were identified, and weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed modules. Enrichment analysis was performed to annotate DEGs. Preservation analysis determined whether modules and pathways were similar between genders. Blood methylation, transcriptome data, mouse phenotype data, and drug treatment data were utilized to identify key osteoporosis genes. We identified 1460 DEGs enriched in immune response, neurogenesis, and GWAS osteoporosis-related genes. WGCNA uncovered 8 modules associated with immune response, development, collagen metabolism, mitochondrion, and amino acid synthesis. Preservation analysis indicated modules and pathways were generally similar between genders. Incorporating GWAS and mouse phenotype data revealed 9 key genes, including GMDS, SMOC2, SASH1, MMP2, AHCYL1, ARRDC2, IGHMBP2, ATP6V1A, and CTSK. These genes were differentially methylated in patient blood and differentiated high and low bone mineral density patients in pre- and postmenopausal women. Denosumab treatment in postmenopausal women down-regulated 6 key genes, up-regulated T cell proportions, and down-regulated fibroblast proportion. qRT-PCR was used to confirm the genes in postmenopausal women. We identified 9 key osteoporosis genes by comparing the transcriptome of osteoblasts in women and men. Our findings' clinical implications were confirmed by multi-omics data and qRT-PCR, and our study provides novel biomarkers and therapeutic targets for osteoporosis diagnosis and treatment.

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Data Availability

The data analyzed in the study is available through the NCBI GEO database at https://www.ncbi.nlm.nih.gov/geo/.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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  1. Dongfeng Chen and Ying Li contributed equally to this work.

Authors and Affiliations

  1. Department of Bone and Joint Sports Medicine, Longyan First Hospital Affiliated to Fujian Medical University, Longyan, 364000, Fujian, People’s Republic of China

    Dongfeng Chen, Ying Li, Qiang Wang & Peng Zhan

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Dongfeng Chen, Ying Li, and Qiang Wang. The first draft of the manuscript was written by Dongfeng Chen, Ying Li, and Peng Zhan and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Peng Zhan.

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Dongfeng Chen, Ying Li, Qiang Wang, and Peng Zhan declare that they have no conflict of interest.

Ethics Approval

This study was approved by the Ethics Committee of Clinical Research of Longyan First Hospital Affiliated to Fujian Medical University. The trials were conducted in compliance with the International Code of Medical Ethics of the World Medical Association, and all participants provided written informed consent.

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The study was performed according to the Declaration of Helsinki and was approved by the Ethics Committee of Clinical Research of Longyan First Hospital. This article does not contain any studies with animals.

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Chen, D., Li, Y., Wang, Q. et al. Identification of Key Osteoporosis Genes Through Comparative Analysis of Men's and Women's Osteoblast Transcriptomes. Calcif Tissue Int 113, 618–629 (2023). https://doi.org/10.1007/s00223-023-01147-3

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