生物
免疫系统
发病机制
基因表达谱
基因
疾病
免疫学
基因表达
计算生物学
生物信息学
遗传学
病理
医学
作者
Yan Huang,Jingyu Qian,Zheng‐yun Luan,Junling Han,Limin Tang
出处
期刊:Biology
[Multidisciplinary Digital Publishing Institute]
日期:2025-05-08
卷期号:14 (5): 518-518
被引量:1
标识
DOI:10.3390/biology14050518
摘要
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD), a chronic inflammatory disorder characterized by alcohol-independent hepatic lipid accumulation, remains poorly understood in terms of PANoptosis involvement. METHODS: We integrated high-throughput sequencing data with bioinformatics to profile differentially expressed genes (DEGs) and immune infiltration patterns in MASLD, identifying PANoptosis-associated DEGs (PANoDEGs). Machine learning algorithms prioritized key PANoDEGs, while ROC curves assessed their diagnostic efficacy. Cellular, animal, and clinical validations confirmed target expression. RESULTS: Three PANoDEGs (SNHG16, Caspase-6, and Dynamin-1-like protein) exhibited strong MASLD associations and diagnostic significance. Immune profiling revealed elevated M1 macrophages, naïve B cells, and activated natural killer cells in MASLD tissues versus controls. Further experiments verified the expression of the key PANoDEGs. CONCLUSIONS: This study provides new insights for further studies on the pathogenesis and treatment strategies of PANoptosis in MASLD.
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