Clinical study of intelligent tongue diagnosis and oral microbiome for classifying TCM syndromes in MASLD
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: This study aimed to analyze the tongue image features and oral microbial markers in different TCM syndromes related to metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: This study involved 34 healthy volunteers and 66 MASLD patients [36 with Dampness-Heat (DH) and 30 with Qi-Deficiency (QD) syndrome]. Oral microbiome analysis was conducted through 16S rRNA sequencing. Tongue image feature extraction used the Uncertainty Augmented Context Attention Network (UACANet), while syndrome classification was performed using five different machine learning methods based on tongue features and oral microbiota. RESULTS: Significant differences in tongue color, coating, and oral microbiota were noted between DH band QD syndromes in MASLD patients. DH patients exhibited a red-crimson tongue color with a greasy coating and enriched Streptococcus and Rothia on the tongue. In contrast, QD patients displayed a pale tongue with higher abundances of Neisseria, Fusobacterium, Porphyromonas and Haemophilus. Combining tongue image characteristics with oral microbiota differentiated DH and QD syndromes with an AUC of 0.939 and an accuracy of 85%. CONCLUSION: This study suggests that tongue characteristics are related to microbial metabolism, and different MASLD syndromes possess distinct biomarkers, supporting syndrome classification.
Source: Chinese Medicine
Authors: Jialin Deng, Shixuan Dai, Shi Liu, Liping Tu, Ji Cui, Xiaojuan Hu, Xipeng Qiu, Hao Lu, Tao Jiang, Jiatuo Xu
Language: English
Subfield: Complementary and alternative medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
Funders: Innovative Research Group Project of the National Natural Science Foundation of China, Shanghai Municipal Health Commission, National Natural Science Foundation of China, China Postdoctoral Science Foundation, State Administration of Traditional Chinese Medicine of the People's Republic of China, Intelligence Community Postdoctoral Research Fellowship Program
OpenAlex ID: W4410869653
