文献类型：期刊文献

英文题名：Alternations of Gut Microbiome and Serum Metabolome With Prolongation of the Course of Type 1 Diabetes Mellitus

作者：Li, Jiayu[1,2];Chen, Xuedi[2];Min, Hang[1,2];Du, Zouxi[1,2];Zhang, Leyuan[2,3];Hua, Wenting[1,2];Tian, Limin[1,4]

第一作者：Li, Jiayu

通信作者：Tian, LM[1];Tian, LM[2]

机构：[1]Lanzhou Univ, Sch Clin Med 1, Lanzhou, Gansu, Peoples R China;[2]Gansu Prov Hosp, Dept Endocrinol, Lanzhou, Gansu, Peoples R China;[3]Gansu Univ Tradit Chinese Med, Clin Med Coll 1, Lanzhou, Gansu, Peoples R China;[4]Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Dept Endocrinol, Chengdu, Sichuan, Peoples R China

第一机构：Lanzhou Univ, Sch Clin Med 1, Lanzhou, Gansu, Peoples R China

通信机构：[1]corresponding author), Lanzhou Univ, Sch Clin Med 1, Lanzhou, Gansu, Peoples R China;[2]corresponding author), Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Dept Endocrinol, Chengdu, Sichuan, Peoples R China.

年份：2025

卷号：41

期号：6

外文期刊名：DIABETES-METABOLISM RESEARCH AND REVIEWS

收录：;Scopus(收录号：2-s2.0-105012735204);WOS:【SCI-EXPANDED(收录号:WOS:001545185900001)】；

基金：This work was supported by the Major Science and Technology Project of Gansu Province (Grant 22ZD6FA033), the Natural Science Foundation of Gansu Province (Grant 23JRRA1318), and the Research Fund project of Gansu Provincial Hospital (Grant 23GSSYB-10). The authors thank the research volunteers for their participation in this study.

语种：英文

外文关键词：biomarkers; diabetic course; gut microbiome; machine learning; metabolome; type 1 diabetes mellitus

摘要：AimsWe aimed to explore the gut microbial and serum metabolic disturbances associated with the course of type 1 diabetes mellitus (T1DM), and identify potential biomarkers for discriminating T1DM from normoglycemia individuals by machine learning.MethodsWe performed 16s ribosomal RNA gene sequencing and untargeted metabolomics in a cohort of 41 patients with T1DM of varying diabetes duration and 39 healthy controls (HCs) to characterise complex interactions between the gut microbiome and serum metabolome during T1DM progression.ResultsWe identified 25 microbial genera that significantly altered in patients with T1DM, eight genera changed as the disease course, and 17 genera changed only in a specific T1DM-course group. Metabolomics analysis revealed that serum glycerophospholipid and amino acids levels were significantly changed in T1DM patients with varying disease course. Notably, we observed significantly higher levels of serum estrone, whereas lower levels of corticosterone and estrone glucuronide as the course of T1DM prolonged; Glycated haemoglobin and fasting blood glucose levels were positively correlated with estrone, and negatively correlated with corticosterone and estrone glucuronide. Furthermore, these notably changes in gut microbiota and serum metabolome were accompanied by functional alterations in sphingolipid, glutathione and taurine and hypotaurine metabolism pathways with T1DM progression. Finally, we successfully selected seven microbial and three metabolic biomarkers to differentiate T1DM from HCs.ConclusionsPerturbed diabetes course-related gut microbiota was highly correlated with the alternation of metabolic patterns in T1DM, and multi-omics coupled with machine learning algorithms can be used to develop diagnostic models based on selected biomarkers.