Fang Zhihao, Liu Changxu, Cheng Yue, Ji Yanchao, Liu Chang
Department of General Surgery, Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Cardiovascular Surgery, Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Life Sci. 2025 Feb 1;362:123377. doi: 10.1016/j.lfs.2025.123377. Epub 2025 Jan 8.
This study aims to identify key biomarkers associated with ferroptosis and lipid metabolism and investigate their roles in the progression of metabolic dysfunction-associated fatty liver disease (MAFLD). It further explores interactions between these biomarkers and the immune-infiltration environment, shedding light on how ferroptosis and lipid metabolism influence immune dynamics in MAFLD.
Single-cell RNA sequencing data from liver samples were analyzed to evaluate expression variations related to ferroptosis and lipid metabolism in MAFLD patients. Gene scores were assessed to explore their impact on the immune microenvironment, particularly hepatocyte-macrophage communication. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Bulk-RNA-Seq data to identify gene clusters associated with ferroptosis and lipid metabolism. The analyses were integrated into a risk assessment system and predictive model, with validation conducted through in vivo experiments.
Integration of single-cell and WGCNA data identified 11 key genes linked to ferroptosis and lipid metabolism (e.g., IER5L, SOCS2, KLF9), significantly influencing the liver's immune microenvironment. The risk assessment system and predictive model achieved an AUC of 0.92 and revealed distinct immune and biological characteristics in MAFLD patients across risk levels. The expression patterns and biological roles of these genes were confirmed in in vivo studies.
This study establishes a strong link between ferroptosis- and lipid metabolism-related gene expression and MAFLD's complexity. It provides novel insights into disease mechanisms, supporting personalized prognosis and targeted therapeutic strategies for MAFLD patients.
本研究旨在识别与铁死亡和脂质代谢相关的关键生物标志物，并研究它们在代谢功能障碍相关脂肪性肝病（MAFLD）进展中的作用。它进一步探索这些生物标志物与免疫浸润环境之间的相互作用，以阐明铁死亡和脂质代谢如何影响MAFLD中的免疫动态。
分析肝脏样本的单细胞RNA测序数据，以评估MAFLD患者中与铁死亡和脂质代谢相关的表达变化。评估基因评分以探索它们对免疫微环境的影响，特别是肝细胞与巨噬细胞之间的通讯。将加权基因共表达网络分析（WGCNA）应用于批量RNA测序数据，以识别与铁死亡和脂质代谢相关的基因簇。这些分析被整合到一个风险评估系统和预测模型中，并通过体内实验进行验证。
整合单细胞和WGCNA数据确定了11个与铁死亡和脂质代谢相关的关键基因（如IER5L、SOCS2、KLF9），显著影响肝脏的免疫微环境。风险评估系统和预测模型的AUC为0.92，并揭示了不同风险水平的MAFLD患者的独特免疫和生物学特征。这些基因的表达模式和生物学作用在体内研究中得到了证实。
本研究在铁死亡和脂质代谢相关基因表达与MAFLD的复杂性之间建立了紧密联系。它为疾病机制提供了新的见解，支持了MAFLD患者的个性化预后和靶向治疗策略。
