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Development and experimental validation of an energy metabolism-related gene signature for diagnosing of osteoporosis

  • 0Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China.
Scientific Reports +

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April 8, 2024

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April 8, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

This study identifies key energy metabolism genes linked to osteoporosis development and creates a diagnostic signature. These findings offer new insights into osteoporosis pathogenesis and potential therapeutic targets.

Area Of Science

  • Genomics and Molecular Biology
  • Metabolic Research
  • Bone Biology

Background

  • Osteoporosis pathogenesis involves excessive bone resorption and altered energy metabolism.
  • The specific roles of energy metabolism-related genes in osteoporosis remain largely unexplored.
  • Understanding these genes is crucial for developing diagnostic and therapeutic strategies.

Purpose Of The Study

  • To identify differentially expressed energy metabolism genes (DE-EMGs) associated with osteoporosis.
  • To develop a diagnostic signature for osteoporosis based on DE-EMGs.
  • To investigate the relationship between DE-EMGs, immune cells, and molecular pathways in osteoporosis.

Main Methods

  • Utilized gene expression datasets (GSE56814, GSE62402, GSE7158) from NCBI Gene Expression Omnibus.
  • Screened for DE-EMGs by intersecting differentially expressed genes between high and low body mineral density (BMD) groups with energy metabolism genes.
  • Constructed a diagnostic model using selected DE-EMGs, validated with RT-qPCR, ROC curves, and nomogram analysis.

Main Results

  • Identified 72 DE-EMGs, leading to a five-gene diagnostic model (B4GALT4, ADH4, ACAD11, B4GALT2, PPP1R3C).
  • The diagnostic model demonstrated significant predictive ability (AUC 0.784 in training, 0.790 for B4GALT2 in validation).
  • Nomogram model showed strong prognostic prediction (C-index = 0.9201).
  • Found significant differences in five immune cell types between high- and low-BMD groups.
  • Constructed a network involving DE-EMGs, microRNA (hsa-miR-23b-3p), long non-coding RNA (DANCR), drugs, and metabolic pathways.

Conclusions

  • DE-EMGs play a significant role in osteoporosis development.
  • The developed diagnostic signature shows promise for osteoporosis diagnosis.
  • The DANCR/hsa-miR-23b-3p/B4GALT4 axis may offer novel molecular insights into osteoporosis.
  • Immune cell infiltration and metabolic pathways are implicated in osteoporosis pathogenesis.

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