Identifying Macrophage-Related Genes in Ulcerative Colitis Using Weighted Coexpression Network Analysis and Machine...

Area of Science:

• Gastroenterology and Immunology
• Molecular Biology
• Computational Biology

Background:

• Ulcerative colitis (UC) is a chronic inflammatory bowel disease with complex immune system involvement.
• Macrophages, particularly M1 and M2 subtypes, play a critical role in UC pathogenesis.
• Understanding immune cell dynamics and molecular markers is crucial for UC diagnosis and treatment.

Purpose of the Study:

• To investigate the role of immune cell infiltrates, especially macrophages, in UC.
• To identify novel molecular markers associated with UC pathogenesis and progression.
• To develop a diagnostic tool for UC based on identified gene signatures.

Main Methods:

• Immune cell infiltration analysis using CIBERSORT algorithm.
• Weighted gene coexpression network analysis (WGCNA) to identify macrophage-related genes (MRGs).
• Consensus clustering, machine learning, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA).

Main Results:

• Elevated immune cell infiltrates and altered M1/M2 macrophage ratios observed in UC patients.
• Identification of 52 MRGs, leading to three distinct UC subtypes.
• ENPP1, SLC6A14, and HMGCS2 identified as key diagnostic markers with validated diagnostic value.
• HMGCS2 expression decreased during UC progression to colorectal cancer.

Conclusions:

• ENPP1, SLC6A14, and HMGCS2 are significantly associated with UC pathogenesis and macrophage activity.
• These genes demonstrate potential as reliable diagnostic biomarkers for UC.
• The findings provide insights into molecular mechanisms underlying UC and its transition to colorectal cancer.