Tongue Fur and Metabolites in Diabetes Mellitus

This study is a prospective cross-sectional study. The investigators enroll participants form the department of endocrinology and of metabolism, China Medical University Hospital. In total, 400 participants , composed of 100 of type 2 diabetes , 100 of pre-DM and 200 healthy participants. The investigators apply tongue diagnosis system, pulse wave analysis, body constitution questionnaires, and nailfold capillaroscopy to assess the differences of TCM diagnosis. After collecting the tongue coating and analyzing the metabolite signals with a flying mass spectrometer, The investigators collect the data to establish metabolite pattern and biomarkers. This study aims to identify the clinical symptoms of DM with TCM diagnostic tools and investigate the pattern difference and treatment for DM. Furtherly, the investigators add mass spectrometer to analyze the metabolites of tongue coating, the investigators propose to establish a metabolite pattern and biomarker to identify important biological indicators of DM.

The data were acquired by UNIFI software (Waters) and processed by UNIFI and Progenesis QI software. Omics analysis methods, such as principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and orthogonal partial least squares-discriminate analysis (OPLS-DA), were employed to identify the biochemical patterns in tongue coating samples and suggest variables that can be used as biomarkers for diabetes and pre-diabetes.

The primary outcome is the differentiation of tongue features extracted by ATDS. There are nine primary features for TCM clinical tongue diagnosis, namely, tongue shape, tongue color, fur thickness, fur color, saliva, tongue fissure, ecchymosis, teeth mark, and red dot. Features identified are further sub-divided according to the areas located, i.e., heart-lung area, left liver-gall, right liver-gall, spleen-stomach, and kidney.

The study researched tongue coating metabolic markers in patients with diabetes to determine any relationship between tongue diagnosis and metabolic processes. Chromatographic analysis and comparison between the diabetes group and normal controls. PCA and PLS-DA analysis of metabolic profiles of tongue coating samples from the chronic gastritis group and normal controls. To improve the accuracy of the PLS discriminated model, OPLS-DA was used to analysis the results by removing some redundant information, such as envir- onmental factors, gender, and diet. Tongue metabolic fingerprint differences between the chronic gastritis group and normal controls were compared using OPLS-DA.

Inclusion Criteria: Clinical diagnosis of type 2 DM Clinical diagnosis of pre-DM Participants in the control group had a normal fasting glucose level Exclusion Criteria: comorbidity of inadequate heart, liver, kidney, or other serious diseases. pregnancy or lactation. history of mental illness.