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ORIGINAL RESEARCH article
Front. Cell. Infect. Microbiol.
Sec. Oral Microbes and Host
Volume 14 - 2024 |
doi: 10.3389/fcimb.2024.1477638
This article is part of the Research Topic Impact of oral and gut microbiome on health and diseases View all 3 articles
Application of tongue image characteristics and oral-gut microbiota in predicting pre-diabetes and type 2 diabetes with machine learning
Provisionally accepted
Jialin Deng
1
ShiXuan Dai
1
Shi Liu
1*
Liping Tu
1*
Ji Cui
1*
Xiaojuan Hu
1*
Xipeng Qiu
2*
Tao Jiang
1*
Jiatuo Xu
1*- 1 Shanghai University of Traditional Chinese Medicine, Shanghai, Shanghai Municipality, China
- 2 School of Computer Science and Technology, Fudan University, Shanghai, Shanghai Municipality, China
Background This study aimed to characterize the oral and gut microbiota in prediabetes mellitus (Pre-DM) and type 2 diabetes mellitus (T2DM) patients while exploring the association between tongue manifestations and the oral-gut microbiota axis in diabetes progression. Methods Participants included 30 Pre-DM patients, 37 individuals with T2DM, and 28 healthy controls. Tongue images and oral/fecal samples were analyzed using image processing and 16S rRNA sequencing. Machine learning techniques, including support vector machine (SVM), random forest, gradient boosting, adaptive boosting, and K-nearest neighbors, were applied to integrate tongue image data with microbiota profiles to construct predictive models for Pre-DM and T2DM classification. Results Significant shifts in tongue characteristics were identified during the progression from Pre-DM to T2DM. Elevated Firmicutes levels along the oral-gut axis were associated with white greasy fur, indicative of underlying metabolic changes. An SVM-based predictive model demonstrated an accuracy of 78.9%, with an AUC of 86.9%. Notably, tongue image parameters (TB-a, perALL) and specific microbiota (Escherichia, Porphyromonas-A) emerged as prominent diagnostic markers for Pre-DM and T2DM. Conclusion The integration of tongue diagnosis with microbiome analysis reveals distinct tongue features and microbial markers. This approach significantly improves the diagnostic capability for Pre-DM and T2DM.
Keywords: Tongue diagnosis, Oral-gut microbiome, Prediabetes mellitus, type 2 diabetes mellitus, Diagnostic model
Received: 08 Aug 2024; Accepted: 16 Oct 2024.
Copyright: © 2024 Deng, Dai, Liu, Tu, Cui, Hu, Qiu, Jiang and Xu. 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:
Shi Liu, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
Liping Tu, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
Ji Cui, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
Xiaojuan Hu, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
Xipeng Qiu, School of Computer Science and Technology, Fudan University, Shanghai, 200433, Shanghai Municipality, China
Tao Jiang, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
Jiatuo Xu, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, Shanghai Municipality, China
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