five

Blood metabolic panels for identifying significant fibrosis and inflammation in patients with MASLD

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://www.omicsdi.org/dataset/metabolights_dataset/MTBLS13268
下载链接
链接失效反馈
官方服务:
资源简介:
Metabolic dysfunction-associated steatotic liver disease (MASLD) remains a prevalent condition with limited diagnostic and therapeutic options. This study aims to identify metabolic signatures of disease progression and develop non-invasive diagnostic models through three independent cohorts (including two cohorts confirmed by biopsy and one cohort confirmed by ultrasound) involving 293 participants for detecting significant fibrosis (≥F2) and mild to severe inflammatory activity (≥I2) using multiple machine learning. Fibrosis Panel shows AUROCs of 0.928 (95%CI 0.835-0.978), 0.829 (0.732-0.902), and 0.806 (0.724-0.872) in Discovery Cohort, Validation Cohort 1 and Validation Cohort 2, respectively, outperforming the FIB-4, APRI, NFS, LSM and MACK-3. Inflammation Panel achieves AUROCs of 0.894 (0.791-0.957) and 0.776 (0.673-0.859) in Discovery Cohort and Validation Cohort 1, respectively. Key metabolites guanidinoacetic acid (GAA) and sebacic acid (SA) demonstrate therapeutic efficacy in mice. These validated panels provide accurate stratification of MASLD severity, and GAA/SA offer therapeutic potential, advancing both diagnosis and treatment strategies.
创建时间:
2025-11-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作