Integrated Machine Learning and Multi-Omics Analysis Identifies Mitophagy-Related Core Genes and Mechanisms in...

Area of Science:

• * Molecular biology and bioinformatics
• * Immunology and disease pathology
• * Genomics and transcriptomics

Background:

• * Non-alcoholic fatty liver disease (NAFLD) is a growing global health concern with complex underlying mechanisms.
• * Mitophagy, the selective degradation of damaged mitochondria, plays a critical role in cellular homeostasis and disease pathogenesis.
• * Understanding the core genes regulating mitophagy in NAFLD is essential for developing effective diagnostic and therapeutic strategies.

Purpose of the Study:

• * To systematically identify mitophagy-related core genes in NAFLD.
• * To elucidate the molecular regulatory network and functional mechanisms of these genes.
• * To investigate their role in the NAFLD immune microenvironment for potential therapeutic targeting.

Main Methods:

• * Integration of multiple NAFLD transcriptomic and single-cell RNA sequencing datasets.
• * Application of bioinformatics, Weighted Gene Co-expression Network Analysis (WGCNA), and machine learning for core gene screening.
• * In-depth analysis of functional mechanisms, immune microenvironment, and intercellular communication using SHAP, PPI networks, GSEA, and in vitro validation.

Main Results:

• * Identification of five key genes (IGF1, MYH11, HYOU1, SPATA18, SCD) with high NAFLD discrimination capability (AUC=0.974).
• * These genes are significantly enriched in endoplasmic reticulum stress, mitophagy, and lipid metabolism pathways.
• * Demonstrated crucial roles in modulating the NAFLD immune microenvironment, including M2 macrophage polarization and T cell infiltration, linking mitochondrial dysfunction to inflammation.

Conclusions:

• * Systematic delineation of the regulatory network of mitophagy-related core genes in NAFLD.
• * Novel insights into the interplay between mitophagy, core genes, and the inflammatory immune microenvironment in NAFLD.
• * Provides data support for developing early diagnostic biomarkers and precise therapeutic strategies for NAFLD.