Abstract

Non-alcoholic fatty liver disease (NAFLD) and myocardial infarction (MI) are two major health burdens with significant prevalence and mortality. This study aimed to explore the co-expressed genes to understand the relationship between NAFLD and MI and identify potential crucial biomarkers of NAFLD-related MI using bioinformatics and machine learning. Functional enrichment analysis was conducted, a co-protein-protein interaction (PPI) network diagram was constructed, and support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) techniques were employed to identify one differentially expressed gene (DEG), Thrombospondin 1 (THBS1). THBS1 demonstrated strong performance in distinguishing NAFLD patients (AUC = 0.981) and MI patients (AUC = 0.900). Immuno-infiltration analysis revealed significantly lower CD8+ T cells and higher neutrophil levels in patients with NAFLD and MI. CD8+ T cells and neutrophils were effective in distinguishing NAFLD/MI from healthy controls. Correlation analysis showed that THBS1 was positively correlated with CCR (chemokine receptor), MHC class (major histocompatibility complex class), neutrophils, parainflammation, and Tfh (follicular helper T cells), and negatively correlated with CD8+ T cells, cytolytic activity, and TIL (tumor-infiltrating lymphocytes) in NAFLD and MI patients. THBS1 emerged as a novel biomarker for diagnosing NAFLD/MI in comparison to healthy controls. The results indicate that CD8+ T cells and neutrophils could serve as inflammatory immune features for differentiating patients with NAFLD/MI from healthy individuals.

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