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Integrated Machine Learning and Multi-Omics Analysis Identifies Mitophagy-Related Core Genes and Mechanisms in Non-Alcoholic Fatty Liver Disease
Using Machine Learning and Multi-Omics to Find Key Genes and Processes in Mitochondrial Recycling Linked to Non-Alcoholic Fatty Liver Disease
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Abstract
Five key genes—IGF1, MYH11, HYOU1, SPATA18, and SCD—showed excellent disease discrimination in Non-alcoholic fatty liver disease (NAFLD) with a training set of 0.974.
- These genes are significantly enriched in processes related to endoplasmic reticulum stress, , and lipid metabolism.
- In the immune microenvironment of NAFLD, they are associated with increased macrophage M2 polarization and T cell infiltration.
- Expression heterogeneity of these genes was observed across hepatocytes, macrophages, and T cells.
- The study highlights a connection between mitochondrial dysfunction and inflammatory responses in NAFLD.
- Experimental validation indicated altered core gene expression and mitophagy levels in NAFLD cell models.
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Key numbers
0.974
Performance
Maximum achieved across multiple validation cohorts.
5
Core Genes Identified
Five core genes linked to and immune responses in NAFLD.