Wang Luyu, Wang Hongtao, Wu Jian, Ji Changyi, Wang Ying, Gu Mengmeng, Li Miaomiao, Yang Hongwei
Anhui Province Key Laboratory of Immunology in Chronic Diseases, Research Center of Laboratory, School of Laboratory, Bengbu Medical University, Bengbu, China.
Department of Clinical Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China.
Front Cell Infect Microbiol. 2025 Jul 23;15:1635638. doi: 10.3389/fcimb.2025.1635638. eCollection 2025.
The global epidemic of Metabolic dysfunction-associated fatty liver disease (MAFLD) urgently demands breakthroughs in precision medicine strategies. Its pathogenesis centers on the cascade dysregulation of the gut microbiota-metabolite-liver axis: microbial dysbiosis drives hepatic lipid accumulation and fibrosis by suppressing short-chain fatty acid synthesis, activating the TLR4/NF-κB inflammatory pathway, and disrupting bile acid signaling. Metabolomics further reveals characteristic disturbances including free fatty acid accumulation, aberrantly elevated branched-chain amino acids (independently predictive of hepatic steatosis), and mitochondrial dysfunction, providing a molecular basis for disease stratification. The field of precision diagnosis is undergoing transformative innovation-multi-omics integration combined with AI-driven analysis of liver enzymes and metabolic biomarkers enables non-invasive, ultra-high-accuracy staging of fibrosis. Therapeutic strategies are shifting towards personalization: microbial interventions require matching to patient-specific microbial ecology, drug selection necessitates efficacy and safety prediction, and synthetically engineered "artificial microbial ecosystems" represent a cutting-edge direction. Future efforts must establish a "multi-omics profiling-AI-powered dynamic modeling-clinical validation" closed-loop framework to precisely halt MAFLD progression to cirrhosis and hepatocellular carcinoma by deciphering patient-specific mechanisms.
代谢功能障碍相关脂肪性肝病(MAFLD)的全球流行迫切需要精准医学策略取得突破。其发病机制以肠道微生物群-代谢物-肝脏轴的级联失调为中心:微生物失调通过抑制短链脂肪酸合成、激活TLR4/NF-κB炎症通路和破坏胆汁酸信号传导来驱动肝脏脂质积累和纤维化。代谢组学进一步揭示了包括游离脂肪酸积累、支链氨基酸异常升高(独立预测肝脂肪变性)和线粒体功能障碍在内的特征性紊乱,为疾病分层提供了分子基础。精准诊断领域正在经历变革性创新——多组学整合结合人工智能驱动的肝酶和代谢生物标志物分析能够实现纤维化的非侵入性、超高精度分期。治疗策略正朝着个性化方向转变:微生物干预需要与患者特定的微生物生态相匹配,药物选择需要对疗效和安全性进行预测,合成工程化的“人工微生物生态系统”代表了一个前沿方向。未来的努力必须建立一个“多组学剖析-人工智能驱动的动态建模-临床验证”闭环框架,通过解读患者特定机制来精准阻止MAFLD进展为肝硬化和肝细胞癌。