ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Diabetes: Molecular Mechanisms
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1588718
LC-MS-based conventional metabolomics combined with machine learning models to identify metabolic markers for the diagnosis of type I diabetes
Provisionally accepted
- 1Hangzhou City University, Hangzhou, China
- 2Lianshui County People’s Hospital, Huai’an, China
- 3the Affiliated Chuzhou Hospital of Traditional Chinese Medicine of Jiangsu College of Nursing, Huai'an, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: Changes in certain metabolites are linked to an increased risk of type I diabetes (T1D), making metabolite analysis a valuable tool for T1D diagnosis and treatment. This study aimed to identify a metabolic signature linked with T1D.Methods: Untargeted metabolomic profiling was performed using liquid chromatography–mass spectrometry (LC-MS) on peripheral blood samples from T1D patients (n = 45) and healthy controls (n = 40). Data preprocessing and quality control were conducted using MetaboAnalyst 4.0. Differential metabolites (DMs) were identified via Wilcoxon rank-sum test (P < 0.05), and key diagnostic markers were selected using least absolute shrinkage and selection operator (LASSO) regression. A streptozotocin (STZ)-induced diabetic rat model was used for in vivo validation.Results: A total of 157 annotated metabolites were detected (58 in ESI− and 99 in ESI+ mode). Twenty-six DMs were identified, including 25 upregulated and 1 downregulated in the T1D group, mainly involving Acylcarnitines and xanthine metabolites. LASSO regression selected Hydroxyhexadecanoyl carnitine, Propionylcarnitine, and Valerylcarnitine as candidate markers. In the rat model, Hydroxyhexadecanoyl carnitine and Valerylcarnitine demonstrated strong diagnostic performance, with AUCs of 0.9383 (95% CI: 0.8786–0.9980) and 0.8395 (95% CI: 0.7451–0.9338), respectively (P < 0.01).Conclusion: Hydroxyhexadecanoyl carnitine and Valerylcarnitine are closely linked to altered lipid oxidation in T1D and show strong potential as diagnostic biomarkers. These findings provide new insights into the metabolic basis of T1D and offer promising targets for early detection.
Keywords: type 1 diabetes, Metabolomics, LC-MS, metabolic markers, LASSO
Received: 06 Mar 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Tuerxunyiming, Zhao, Hu, Zhu and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Shiting Zhu, Lianshui County People’s Hospital, Huai’an, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.