Identifying shared hub genes in LIRI and MASLD through bioinformatics analysis and machine learning.

Journal: Scientific reports
Published Date: May 27, 2025

Abstract

Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are more susceptible to liver ischemia-reperfusion injury (LIRI), complicating liver surgery outcomes. This study aimed to uncover shared hub genes and mechanisms linking LIRI and MASLD to enhance donor liver utilization and improve prognosis. Using liver transplantation and MASLD datasets from the Gene Expression Omnibus, we applied Linear Models for Microarray Data and weighted gene co-expression analysis to identify differentially expressed genes and key module genes. Further analysis involved Gene Ontology, KEGG, and machine learning to pinpoint common hub genes and pathways. We identified 5,920 differentially expressed genes in liver datasets and 8,978 across LIRI and MASLD datasets. 71 shared hub genes were associated with pathways like MAPK signaling. Key genes, ADRB2 and CCL2, exhibited correlated mRNA expression in both datasets and human liver tissues. Hypoxia-reoxygenation in MASLD models elevated CCL2 levels and reduced ADRB2 expression. These genes showed strong diagnostic potential (AUC, 0.97). CCL2 knockdown reduced, while ADRB2 knockdown increased, MASLD cells' H/R injury sensitivity. Immune infiltration analysis revealed increased immune cell activity, particularly correlations between M0/M2 macrophages and NK cells/mast cells. ADRB2 and CCL2 were identified as crucial biomarkers, potentially explaining MASLD patients' heightened vulnerability to LIRI during liver transplantation.

Authors

  • Yongzhi Zhou
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Bing Yin
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Zhongyu Li
    Institute of Pathogenic Biology, School of Nursing, Hengyang Medical College, Hunan Provincial Key Laboratory for Special Pathogens Prevention and Control, University of South China, Hengyang 421001, China.
  • Zhanzhi Meng
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Shounan Lu
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Baolin Qian
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Xinglong Li
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Yongliang Hua
    Department of Minimally Invasive Hepatic Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
  • Hongjun Yu
    State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
  • Yao Fu
    Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Urban Pollutant Conversion, Anhui Province Key Laboratory of Biomass Clean Energy, Center for Excellence in Molecular Synthesis of CAS, Institute of Energy, Hefei Comprehensive National Science Center, University of Science and Technology of China, Hefei 230026, China.
  • Yong Ma
    Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.

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