Huang Yan, Qian Jingyu, Luan Zhengyun, Han Junling, Tang Limin
Medical College, Yangzhou University, Yangzhou 225000, China.
Taizhou School of Clinical Medicine, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou 225300, China.
Biology (Basel). 2025 May 8;14(5):518. doi: 10.3390/biology14050518.
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.
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.
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.
This study provides new insights for further studies on the pathogenesis and treatment strategies of PANoptosis in MASLD.
代谢功能障碍相关脂肪性肝病（MASLD）是一种以非酒精性肝脂质蓄积为特征的慢性炎症性疾病，目前对其细胞焦亡参与情况的了解仍很有限。
我们将高通量测序数据与生物信息学相结合，以分析MASLD中差异表达基因（DEG）和免疫浸润模式，识别与细胞焦亡相关的DEG（PANoDEG）。机器学习算法对关键的PANoDEG进行优先级排序，同时通过ROC曲线评估其诊断效能。细胞、动物和临床验证确认了靶标表达。
三个PANoDEG（SNHG16、半胱天冬酶-6和动力蛋白样蛋白1）与MASLD有很强的相关性且具有诊断意义。免疫分析显示，与对照组相比，MASLD组织中的M1巨噬细胞、幼稚B细胞和活化自然杀伤细胞增多。进一步实验验证了关键PANoDEG的表达。
本研究为进一步研究细胞焦亡在MASLD发病机制和治疗策略方面提供了新见解。
