Combined analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics reveals the expression patterns of lipid metabolism and ferroptosis in the immune microenvironment of metabolic-associated fatty liver disease

被引:0
|
作者
Fang, Zhihao [1 ]
Liu, Changxu [1 ]
Cheng, Yue [2 ]
Ji, Yanchao [1 ]
Liu, Chang [1 ]
机构
[1] Harbin Med Univ, Affiliated Hosp 4, Dept Gen Surg, Harbin, Peoples R China
[2] Harbin Med Univ, Affiliated Hosp 4, Cardiovasc Surg, Harbin, Peoples R China
关键词
MAFLD; Ferroptosis; Machine learning; Programmed cell death; SOCS-BOX; GENE; VARIANTS; PACKAGE; CANCER;
D O I
10.1016/j.lfs.2025.123377
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Aims: 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. Main methods: 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. Key findings: 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. Significance: 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.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Analyses of single-cell and bulk RNA sequencing combined with machine learning reveal the expression patterns of disrupted mitophagy in schizophrenia
    Yang, Wei
    Lian, Kun
    Ye, Jing
    Cheng, Yuqi
    Xu, Xiufeng
    FRONTIERS IN PSYCHIATRY, 2024, 15
  • [32] Combined Single-Cell, Bulk RNA Sequencing and Proteomics Analysis Reveals New Candidate Targets Involved in Myocardial Fibrogenesis
    Kocherova, Ievgeniia
    Pachera, Elena
    Nurzynska, Daria
    Di Meglio, Franca
    Distler, Oliver
    Blyszczuk, Przemyslaw
    Kania, Gabriela
    ARTHRITIS & RHEUMATOLOGY, 2022, 74 : 3225 - 3227
  • [33] Deciphering the role of sphingolipid metabolism in the immune microenvironment and prognosis of esophageal cancer via single-cell sequencing and bulk data analysis
    He, Rongzhang
    Tang, Jing
    Lai, Haotian
    Zhang, Tianchi
    Du, Linjuan
    Wei, Siqi
    Zhao, Ping
    Tang, Guobin
    Liu, Jie
    Luo, Xiufang
    DISCOVER ONCOLOGY, 2024, 15 (01)
  • [34] Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer's disease
    Lai, Yongxing
    Lin, Han
    Chen, Manli
    Lin, Xin
    Wu, Lijuan
    Zhao, Yinan
    Lin, Fan
    Lin, Chunjin
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [35] Integrating Metabolic RNA Labeling-Based Time-Resolved Single-Cell RNA Sequencing with Spatial Transcriptomics for Spatiotemporal Transcriptomic Analysis
    Chen, Xiaoyong
    Lin, Shichao
    You, Honghai
    Chen, Jinyuan
    Wu, Qiaoyi
    Yin, Kun
    Lin, Fanghe
    Zhang, Yingkun
    Song, Jia
    Ding, Chenyu
    Kang, Dezhi
    Yang, Chaoyong
    SMALL METHODS, 2024,
  • [36] Metabolic and senescence characteristics associated with the immune microenvironment in non-small cell lung cancer: insights from single-cell RNA sequencing
    Liao, Hongliang
    Wan, Zihao
    Liang, Yaqin
    Kang, Lin
    Wan, Renping
    AGING-US, 2023, 15 (20): : 11571 - 11587
  • [37] Integrated analysis of bulk and single-cell RNA sequencing reveals the impact of nicotinamide and tryptophan metabolism on glioma prognosis and immunotherapy sensitivity
    Wang, Sen
    Gao, Shen
    Lin, Shaochong
    Fang, Xiaofeng
    Zhang, Haopeng
    Qiu, Man
    Zheng, Kai
    Ji, Yupeng
    Xiao, Baijun
    Zhang, Xiangtong
    BMC NEUROLOGY, 2024, 24 (01)
  • [38] An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy
    Li, Mengling
    Zhou, Baosen
    Zheng, Chang
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2023, 11
  • [39] Integrative analysis of bulk and single-cell RNA-seq reveals the molecular characterization of the immune microenvironment and oxidative stress signature in melanoma
    Li, Yaling
    Jiang, Bin
    Chen, Bancheng
    Zou, Yanfen
    Wang, Yan
    Liu, Qian
    Song, Bing
    Yu, Bo
    HELIYON, 2024, 10 (06)
  • [40] Integrating Single-cell and Bulk RNA Sequencing Reveals Stemness Phenotype Associated with Clinical Outcomes and Potential Immune Evasion Mechanisms in Hepatocellular Carcinoma
    Zhu, Xiaojing
    Zhang, Jiaxing
    Zhang, Zixin
    Yuan, Hongyan
    Xie, Aimin
    Zhang, Nan
    Wang, Minwei
    Jiang, Minghui
    Xiao, Yanqi
    Wang, Hao
    Wang, Xing
    Xu, Yan
    CURRENT BIOINFORMATICS, 2024, 19 (04) : 408 - 423