Diagnostic value and immune microenvironment regulatory network of metabolic reprogramming in chronic rhinosinusitis with nasal polyps identified by multidimensional transcriptome integration and machine learning - Summary - MDSpire

Diagnostic value and immune microenvironment regulatory network of metabolic reprogramming in chronic rhinosinusitis with nasal polyps identified by multidimensional transcriptome integration and machine learning

  • By

  • Li Zhao

  • Xiang Jiang Meng

  • Xu Liang

  • Guang Mei Yuan

  • Li Shi

  • May 25, 2026

  • 0 min

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Objective:

To systematically analyze the molecular characteristics related to metabolic reprogramming in Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) and their interactions with the immune microenvironment.

Key Findings:
  • Identified 21 DEGs associated with metabolic reprogramming relevant to CRSwNP.
  • Machine learning analysis identified 8 hub genes: ERBB4, FBP1, HMGCS2, LYZ, NDRG2, PIP, PYCR1, and SLC43A1.
  • A prediction model using these biomarkers achieved high diagnostic performance (AUC = 0.979).
  • Single-cell analysis revealed distinct expression patterns of these genes across immune cell subsets.
  • MR analysis indicated that lower expression of FBP1, LYZ, and NDRG2 could be risk factors for CRSwNP.
  • qRT-PCR validated the downregulation of these genes in CRSwNP tissues.
Interpretation:

The study systematically identifies and validates metabolic reprogramming-related genes with diagnostic value in CRSwNP, enhancing understanding of the disease's pathogenesis.

Limitations:
  • The study relies on publicly available datasets, which may have inherent biases.
  • Further validation in larger, diverse cohorts is necessary to confirm findings.
Conclusion:

The findings provide a novel platform for diagnostic and therapeutic strategies focusing on metabolism in CRSwNP.

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