Biology of the Tongue Coating and Its Value in Disease Diagnosis

Distinctive Lipid Characteristics of Colorectal Cancer Revealed through Non-targeted Lipidomics Analysis of Tongue Coating

The metabolites and microbiota in tongue coating display distinct characteristics in certain digestive disorders, yet their relationship with colorectal cancer (CRC) remains unexplored. Here, we employed liquid chromatography coupled with tandem mass spectrometry to analyze the lipid composition of tongue coating using a nontargeted approach in 30 individuals with colorectal adenomas (CRA), 32 with CRC, and 30 healthy controls (HC). We identified 21 tongue coating lipids that effectively distinguished CRC from HC (AUC = 0.89), and 9 lipids that differentiated CRC from CRA (AUC = 0.9). Furthermore, we observed significant alterations in the tongue coating lipid composition in the CRC group compared to HC/CRA groups. As the adenoma-cancer sequence progressed, there was an increase in long-chain unsaturated triglycerides (TG) levels and a decrease in phosphatidylethanolamine plasmalogen (PE-P) levels. Furthermore, we noted a positive correlation between N-acyl ornithine (NAOrn), sphingomyelin (SM), and ceramide phosphoethanolamine (PE-Cer), potentially produced by members of the Bacteroidetes phylum. The levels of inflammatory lipid metabolite 12-HETE showed a decreasing trend with colorectal tumor progression, indicating the potential involvement of tongue coating microbiota and tumor immune regulation in early CRC development. Our findings highlight the potential utility of tongue coating lipid analysis as a noninvasive tool for CRC diagnosis.

Metabolomic profiling of serum and tongue coating of pregnant women with intrahepatic cholestasis in pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is associated with an increased risk of cesarean section and adverse fetal outcomes. Currently, ICP diagnosis depends largely on serum levels of bile acids and lacks sensitivity and specificity for accurate diagnosis. Tongue diagnosis is an important diagnostic tool in traditional Chinese medicine (TCM) and is used in our clinic as complementary treatment and personalized medicine for ICP. However, the molecular basis of the manifestation of greasy white tongue coatings in ICP remains unknown. In this study, we performed untargeted metabolomic profiling of the serum, tongue coating, and saliva of 66 pregnant women, including 22 with ICP. The metabolomic profiles of the serum and tongue coatings showed marked differences between the two clinical groups. Forty-six differentially abundant metabolites were identified, and their relative concentrations correlated with total bile acid levels. These differential metabolites included bile acids, lipids, microbiota- and diet-related metabolites, and exposomes. Conventional biochemical markers, including serum aminotransferases and bilirubin, were not significantly increased in the ICP group, whereas the total cholesterol and triglyceride levels were significantly increased as early as the first trimester. Our data provide insights into the pathophysiology of ICP and implicate the gut-liver axis and environmental exposure. Tongue coating has the potential to be a non-invasive diagnostic approach. Further studies are required to validate the clinical utility of these findings.

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study

BACKGROUND

Our previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer.

METHODS

We employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins.

RESULTS

We measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort.

CONCLUSIONS

We characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer. Video Abstract.

Study on the Characteristics of Traditional Chinese Medicine Syndromes in Patients with Erosive Gastritis Based on Metabolomics

According to traditional Chinese medicine theory, tongue coatings reflect changes in the body. The goal of this study was to identify a metabolite or a set of metabolites capable of classifying characteristics of traditional Chinese medicine syndromes in erosive gastritis. In this study, we collected tongue coatings of patients with erosive gastritis with damp-heat syndrome (DHS), liver depression and qi stagnation syndrome (LDQSS), and healthy volunteers. Then, we analyzed the differences in metabolic characteristics between the two groups based on metabolomics. We identified 14 potential biomarkers related to the DHS group, and six metabolic pathways were enriched. The differential pathways included pyrimidine metabolism, pantothenate and CoA biosynthesis, citrate cycle (TCA cycle), pyruvate metabolism, glycolysis/gluconeogenesis, and purine metabolism. Similarly, in the LDQSS group, we identified 25 potential biomarkers and 18 metabolic pathways were enriched. The top five pathways were the TCA cycle, sphingolipid metabolism, fatty acid biosynthesis, pantothenate and CoA biosynthesis, and the pentose phosphate pathway. In conclusion, the DHS group and the LDQSS group have different characteristics.

Machine learning aided non-invasive diagnosis of coronary heart disease based on tongue features fusion

BACKGROUND

Coronary heart disease (CHD) is the first cause of death globally. Hypertension is considered to be the most important independent risk factor for CHD. Early and accurate diagnosis of CHD in patients with hypertension can plays a significant role in reducing the risk and harm of hypertension combined with CHD.

OBJECTIVE

To propose a non-invasive method for early diagnosis of coronary heart disease according to tongue image features with the help of machine learning techniques.

METHODS

We collected standard tongue images and extract features by Diagnosis Analysis System (TDAS) and ResNet-50. On the basis of these tongue features, a common machine learning method is used to customize the non-invasive CHD diagnosis algorithm based on tongue image.

RESULTS

Based on feature fusion, our algorithm has good performance. The results showed that the XGBoost model with fused features had the best performance with accuracy of 0.869, the AUC of 0.957, the AUPR of 0.961, the precision of 0.926, the recall of 0.806, and the F1-score of 0.862.

CONCLUSION

We provide a feasible, convenient, and non-invasive method for the diagnosis and large-scale screening of CHD. Tongue image information is a possible effective marker for the diagnosis of CHD.

A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation

The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods and machine learning applied in tongue image analysis that have been studied in the last 5 years, focusing on tongue image calibration, detection, segmentation, and classification of diseases, syndromes, and symptoms/signs. Introducing technical evolutions or emerging technologies were applied in tongue image analysis; as we have noticed, attention mechanism, multiscale features, and prior knowledge were successfully applied in it, and we emphasized the value of combining deep learning with traditional methods. We also pointed out two major problems concerned with data set construction and the low reliability of performance evaluation that exist in this field based on the basic essence of tongue diagnosis in traditional Chinese medicine. Finally, a perspective on the future of intelligent tongue diagnosis was presented; we believe that the self-supervised method, multimodal information fusion, and the study of tongue pathology will have great research significance.

Relationship between thick or greasy tongue-coating microbiota and tongue diagnosis in patients with primary liver cancer

Tongue diagnosis is a unique aspect of traditional Chinese medicine for diagnosing diseases before determining proper means of treatment, but it also has the disadvantage of relying on the subjective experience of medical practitioners and lack objective basis. The purpose of this article is to elucidate tongue-coating microbiota and metabolic differences in primary liver cancer (PLC) patients with thick or greasy tongue coatings. Tongue-coating samples were analyzed in 60 PLC patients (30 PLC with thick or greasy tongue-coating patients and 30 PLC with tongue-coating neither thick nor greasy) and 25 healthy controls (HC) using 16S rRNA gene sequencing technology. As compared to healthy individuals, tongue coatings of patients with PLC had elevated levels of Firmicutes and Actinobacteria. The abundance of Fusobacteria, SR1_Absconditabacteria_, and Spirochaete were higher in tongue coatings of healthy controls compared to samples in patients with PLC. In addition to site-specific differences, higher abundances of Fusobacteria and Actinobacteria were observed in thick or greasy tongue-coating patients as compared to non-thick and greasy tongue-coating patients. The inferred metagenomic pathways enriched in the PLC tongue-coating patients were mainly those involved in replication, recombination, and repair of protein. We also identify a tongue-coating microbiome signature to discriminate HC and PLC, including 15 variables on genus level. The prediction performance of the signature showed well in the training and validation cohorts. This research illustrates specific clinical features and bacterial structures in PLC patients with different tongue coatings, which facilitates understanding of the traditional tongue diagnosis.

Tongue features of patients with granulomatous lobular mastitis

Traditional Chinese tongue diagnosis plays an irreplaceable role in disease diagnosis. This study aimed to describe the tongue characteristics of patients with granulomatous lobular mastitis (GLM). Forty GLM patients and 40 non-GLM controls were evaluated using the Traditional Chinese Medicine subjective clinical interpretation and a TDA-1 Tongue Diagnostic and Analysis system. The associations between the image features of the tongue body and coating and the profiling of immune-inflammatory parameters were analyzed. GLM patients were prone to a reddish tongue bodies with thick, white, and greasy coatings. Thick and greasy tongue coating features are risk factors for GLM. GLM patients had higher levels of white blood cells (WBC), platelets, C-reactive protein, interleukin-2, and transforming growth factor-β (TGF-β) than non-GLM controls (P < .05). Also, tongue coating contrast and entropy values were significantly correlated with WBC or TGF-β levels in GLM patients (r < -0.310 and P < .05). We demonstrated that the hot evil and phlegm-dampness constitutions are the main characteristics of GLM. This might provide a reference for GLM diagnosis.

Weifuchun alters tongue flora and decreases serum trefoil factor I levels in gastric intestinal metaplasia: A CONSORT-compliant article

OBJECTIVE

To explore the molecular mechanisms of Weifuchun in the treatment of gastric intestinal metaplasia (GIM), we designed a preclinical pilot study to examine potential markers of disease progression based on alterations in the tongue flora.

METHODS

Total 27 patients with GIM were treated with Weifuchun for 4 weeks and 26 volunteers as controls. Tongue coating bacteria were profiled using 16S rDNA high-throughput sequencing. Serum pepsinogen I and II levels were detected using the latex immunoturbidimetric assay. The levels of serum trefoil factor I was detected by ELISA. Microplate-based quantification was used to detect serum total bile acid (TBA).

RESULTS

After treatment, the relative abundance of 4 dominant tongue coating genera (Granulicatella, Gemella, Lachnoanaerobaculum, and Neisseria) increased significantly wheras Alloprevotella, [Eubacterium] nodatum group, Prevotell, and Ruminococcaceae UCG-014 decreased (P < .05). The results showed that Alloprevotella and 3 rare tongue coating genera (Lautropia, Treponema 2, and Aliihoeflea) might be potential markers or target flora for the treatment of GIM. Kyoto encyclopedia of genes and genomes (KEGG) function prediction analysis showed that Weifuchun may regulate bile secretion and folate biosynthesis in patients with GIM. The level of serum trefoil factor I decreased significantly in response to Weifuchun treatment, which was consistent with the decrease in folate biosynthesis predicted by KEGG.

CONCLUSION

Weifuchun may restore the balance of tongue flora by decreasing the levels of serum trefoil factor I, thereby providing a new way to measuring the underlying effectiveness and potential mechanisms of action of this traditional Chinese medicinal compound in the treatment of GIM.

A Clinical Study on the Relationship Among Insomnia, Tongue Diagnosis, and Oral Microbiome

Currently, there is a lack of adequate methods to assess insomnia objectively. This study addresses the usefulness of tongue features and oral microbial profile as a potential diagnostic biomarker of insomnia. One hundred insomniac patients and 20 healthy control subjects were selected. Their demographic and clinical characteristics, as well as the tongue diagnostic indices and oral microbial profile, were examined. Compared to the control group, insomniac patients showed a higher abnormal low-frequency/high-frequency (LF/HF) ratio. In tongue diagnosis, the indices related to lightness of tongue body and tongue coating were higher in the insomniac group vs. the control group. Furthermore, linear discriminant analysis (LDA) of oral microbial population revealed that the relative abundances of Clostridia, Veillonella, Bacillus and Lachnospiraceae were significantly higher in the insomniac patients than the control group. Additionally, the tongue features of the insomniac group exhibited that the non-coating group had a poor sleep condition compared to the thick-coating group, although the difference was insignificant. On the other hand, the oral microbial communities of the insomniac patients revealed greater alpha and beta diversities in the non-coating group vs. the thick-coating group. The alpha and beta diversities were higher in orotype1 than orotype2. Collectively, this study highlighted that the lightness of tongue body and tongue coating as well as oral microbial profiles of SR1, Actinobacteria, Clostridia and Lachnospiraceae_unclassified could be considered potential biomarkers of insomnia.

A Nonlinear Association between Tongue Fur Thickness and Tumor Marker Abnormality: A Cross-Sectional Study

Background

Many associations between tongue fur and different physiological and biochemical indexes have been revealed. However, the relationship between tongue fur and tumor markers remains unexplored.

Methods

We collected the medical examination reports of 1625 participants. Participants were residents of Chengdu, China, undergoing routine health checkups at the health management center of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine between December 2018 and September 2020. The participants' tongue fur thickness was measured using the DAOSH four-diagnostic instrument. Tumor marker levels, including t-PSA, AFP, CEA, CA125, and CA199, were measured in the clinical laboratory. Curve-fitting and multivariable logistic regression were used to analyze the association between tongue fur thickness and tumor marker abnormality.

Results

Curve-fitting showed that the relationship between tongue fur thickness and abnormal tumor marker rate was nonlinear, similar to a U shape. As the tongue fur thickness value increased, the abnormal tumor marker probability initially decreased and then increased. Logistic regression showed that, in the crude model, compared with the thin tongue fur group, the odds ratios (ORs) and 95% confidence intervals (CIs) of the less or peeling tongue fur group and thick tongue fur group for tumor marker abnormality were 1.79 (1.02–3.17) and 1.70 (1.13–2.54), respectively. After adjusting gender, age, body mass index (BMI), smoking history, drinking history, tongue color, the form of the tongue, and fur color, the ORs and 95% CIs of the less or peeling tongue fur group and thick tongue fur group were 1.93 (1.04–3.57) and 1.82 (1.17–2.81), respectively.

Conclusions

Excessive or very little tongue fur is associated with tumor marker abnormality. Further cross-sectional studies are needed to evaluate the clinical value of tongue fur for cancer diagnosis and screening.

Tongue cleaning in the elderly and its role in the respiratory and swallowing functions: Benefits and medical perspectives

Oral dysfunction, including oral uncleanness and decline in tongue motor function, tongue pressure and swallowing function, precedes frailty. The tongue's dorsum is a reservoir of oral microbiota, desquamated epithelial mucosa and leukocytes due to the multi-papillate anatomy, and leads to tongue coating. The tongue coating is frequently found in older adults because of hyposalivation, immunity's hypoactivity, diminished motor function and compromised tongue's pressure with age. Anaerobe-driven volatile sulphur compounds in tongue coating are a major cause of intra-oral malodor. Dysbiosis of the tongue-coating microbiome rather than the amount of microorganisms is associated with a risk of aspiration pneumonia. Daily tongue cleaning with a brush or scraper is an easy way to control tongue coating deposits and quality. Using mouth wash or rinse-containing germicides is also a way to control the microbiota of tongue coating. The tongue function is closely related to swallowing. Tongue and suprahyoid muscles are linked with respiratory muscles through the endothoracic fascia. The mechanical stimulation during the cleaning of the tongue may stimulate the respiratory muscles. An intervention trial revealed that tongue cleaning by mucosal brush improves tongue pressure, swallowing and respiratory function in old residents of nursing homes, suggesting a rehabilitative effect of tongue cleaning on the swallowing and respiratory functions, preventing aspiration pneumonia. This narrative review assesses the tongue-cleaning benefits for respiratory and swallowing functions and the possibility of preventing aspiration pneumonia.

Tongue Coating Bacteria as a Potential Stable Biomarker for Gastric Cancer Independent of Lifestyle

BACKGROUND

Gastric cancer (GC) is one of the most common cancers, and the noninvasive diagnostic methods for monitoring GC are still lacking. Growing evidence shows that human microbiota has potential value for identifying digestive diseases.

AIMS

The present study aimed to explore the association of the tongue coating microbiota with the serum metabolic features and inflammatory cytokines in GC patients and seek a potential, noninvasive biomarker for diagnosing GC.

METHODS

The tongue coating microbiota was profiled by 16S rRNA and 18S rRNA genes sequencing technology in the original population with 181 GC patients and 112 healthy controls (HCs). Propensity score matching method was used to eliminate potential confounders including age, gender, and six lifestyle factors and a matching population with 66 GC patients and 66 HCs generated. Serum metabolomics profiling was performed by ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) in the matching population. Random forest model was constructed for the diagnosis of GC.

RESULTS

Linear discriminant analysis effect size (LEfSe) revealed that the differential bacterial taxa between GC patients and HCs in the matching population were similar to that in the original population, while the differential fungal taxa between GC patients and HCs dramatically changed before and after PSM. By random forest analysis, the combination of six bacterial genera (Peptostreptococcus, Peptococcus, Porphyromonas, Megamonas, Rothia, and Fusobacterium) was the optimal predictive model to distinguish GC patients from HCs effectively, with an area under the curve (AUC) value of 0.85. The model was verified with a high predictive potential (AUC = 0.76 to 0.96). In the matching population, eighteen specific HCs-enriched bacterial genera (Porphyromonas, Parvimonas, etc.) had negative correlations with lysophospholipids metabolites, and three of them had also negative correlations with serum IL-17α.

CONCLUSIONS

The alteration of tongue coating microbiota had a possible linkage with the inflammations and metabolome, and the tongue coating bacteria could be a potential noninvasive biomarker for diagnosing GC, which might be independent of lifestyle.

Metabolite Characteristics in Tongue Coating from Damp Phlegm Pattern in Patients with Gastric Precancerous Lesion

Objective

In this study, we analyzed the metabolite profile of the tongue coating of patients having gastric precancerous lesion (GPL) with damp phlegm pattern and proposed a mechanism of pathological transition.

Methods

The changes in tongue-coating metabolites in patients with GPL damp phlegm pattern were analyzed using GC-TOF-MS and UHPLC-QE-MS metabolomics methods.

Results

When compared with 20 patients who did not exhibit a nondamp phlegm pattern, 12 metabolites were highly expressed and 10 metabolites were under expressed in 40 cases of damp phlegm pattern, of which involved 9 metabolic pathways. Compared with 15 healthy people, 134 metabolites were upregulated and 3 metabolites were downregulated in 40 cases exhibiting a damp phlegm pattern, of which involved 17 metabolic pathways. The patients with damp phlegm pattern were compared with nondamp phlegm pattern patients and healthy people, the main differential metabolites were primarily lipids and lipid-like molecules, and the main differential metabolic pathways were related to glycerophospholipid metabolism. In the glycerophospholipid metabolism, the metabolites with changes were phosphatidylethanolamine and lysoPC(18 : 1 (9z)). Among them, phosphatidylethanolamine exists in the synthesis stage of glycerophospholipid metabolism.

Conclusions

Abnormal expression of lipids and lipid-like molecules, as the major metabolic change, was involved in the formation of GPL patients with damp phlegm pattern.