CRSwNP Metabolic Reprogramming Hub Genes and Diagnostic Model

A 2026 bioinformatics study by Li Zhao integrates multiple transcriptome datasets to analyze Chronic Rhinosinusitis with Nasal Polyps (CRSwNP). The research identifies 21 differentially expressed genes related to metabolic reprogramming and uses machine learning to select 8 hub genes for a diagnostic model. The findings were validated via qRT-PCR on independent tissue samples.

Use Cases

• Building diagnostic models for CRSwNP based on the 8 identified hub genes (ERBB4, FBP1, HMGCS2, LYZ, NDRG2, PIP, PYCR1, SLC43A1).
• Investigating the relationship between metabolic reprogramming and immune cell subsets in CRSwNP using single-cell RNA sequencing data.
• Assessing causal risk factors for CRSwNP via Mendelian randomization analysis on genes like FBP1, LYZ, and NDRG2.

Strengths

• The diagnostic model built from the 8 hub genes achieved a high reported AUC of 0.979.
• Analysis integrates multiple data types: bulk RNA-seq, single-cell RNA-seq, and Mendelian randomization.
• Key findings were validated with independent experimental samples using qRT-PCR.

Limitations

• The dataset is a 148.6 KB PDF, suggesting it contains summary results rather than raw or processed data tables.
• Row and column counts are unknown, limiting assessment of data scale and granularity.
• The description provides no column-level documentation, requiring inference of data structure from the paper.

Provenance

Source

GEO database (Gene Expression Omnibus).

Collection Method

Bioinformatics analysis integrating multiple CRSwNP datasets, employing WGCNA and machine learning algorithms.

Freshness

Last updated 2026-05-25 04:33:22.