Carious caries biomarker of saliva metabolite and diagnostic kit of caries biomarker

Abstract

The invention provides a marker for predicting caries occurrence based on saliva metabolites, which is characterized by comprising 4-acetaminobutyric acid, adipic acid, pantetheine and palmitoyl ethanolamide, and the marker is used for preparing a kit for detecting the caries occurrence risk of a subject. The invention provides four markers in saliva metabolites, and early warning of future caries can be realized in a non-invasive and low-cost manner; according to the basis of detection numerical values of the markers, the morbidity state of the constant dentition caries can be reflected, so that accurate prevention and control of the caries can be realized, and finally the purposes of reducing the morbidity of the caries, helping disease pathological typing and researching drug action targets, accurate medication and pathogenesis can be achieved.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, in particular to a dental caries biomarker group of saliva metabolites and a diagnostic kit thereof. Background Art

[0002] Dental caries (tooth decay) are bacterial infections that cause the chronic, progressive destruction of tooth hard tissue. Caries are a common oral disease in all age groups. In its early stages, caries manifests only as demineralization of hard tissue, resulting in a chalky discoloration of the tooth surface. Over time, repeated demineralization leads to the formation of cavities. In the early stages of caries, patients often experience no discomfort. However, once cavities develop, food often becomes impacted, causing bad breath. When the cavities reach the pulp cavity, patients may experience varying degrees of pain and discomfort that can impact their quality of life. Without timely and effective treatment, caries can lead to tooth loss, periapical periodontitis, mandibular osteomyelitis, and even the entry of caries-causing bacteria into the bloodstream, resulting in bacteremia and infective endocarditis, among other life-threatening consequences.

[0003] Although dental caries is a bacterial infection and a common oral disease, some individuals are not susceptible to dental caries. One reason for this is the variation in the antimicrobial components and expression levels in saliva. It is known that saliva molecules such as lysozyme, lactoferrin, and secretory immunoglobulin A can effectively inhibit the growth of oral bacteria and play a crucial protective role against the development of dental caries.

[0004] Metabolites are the end products of cellular metabolism. Numerous studies on systemic diseases have shown that metabolite levels can effectively reflect disease severity. Saliva is an ideal biofluid that is non-invasive and easier to obtain and store than other tissue and blood samples.

[0005] Dental caries is a predictable disease. Previous studies have established several dental caries risk prediction models based on relative abundance data of oral microbes at the genus level. However, due to factors such as horizontal gene transfer and functional redundancy, studies based on the microbial species level struggle to accurately link species composition with microbial community function. Furthermore, dental caries prediction models based on high-throughput sequencing are complex to construct and difficult to translate into clinical applications that require high operability, convenience, speed, and low cost.

[0006] The use of fewer markers can reflect the onset of dental caries and provide a basis for early warning of dental caries, thereby helping doctors to study the pathological typing of the disease, precise medication, and drug target research on the pathogenesis, which has important demonstration significance. Summary of the Invention

[0007] The present invention aims to overcome the deficiencies in the prior art and provides a dental caries biomarker combination of salivary metabolites and its application.

[0008] This application provides the following technical solutions: A marker for predicting the occurrence of dental caries based on saliva metabolites, characterized in that it includes 4-acetylaminobutyric acid, adipic acid, pantetheine, and palmitoylethanolamide, and is used in the preparation of a kit for detecting the risk of dental caries in a subject.

[0009] On the basis of the above technical solutions, the following further technical solutions can be provided: The subject has permanent dentition.

[0010] The sample used for detection in the kit is selected from saliva.

[0011] The saliva is non-stimulated saliva.

[0012] The kit detects the marker for predicting the occurrence of dental caries according to any one of claims 1 to 4 by using a metagenomic sequencing method.

[0013] Advantages of the invention: The present invention provides four markers of saliva metabolites that can provide non-invasive and inexpensive early warning of future dental caries. Based on the detection values of the above markers, the onset of dental caries in the permanent dentition can be reflected, thereby achieving precise prevention and control of dental caries, ultimately reducing the incidence of dental caries, and assisting in the pathological classification of the disease, as well as research on drug targets, precise medication, and pathogenesis. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a comprehensive comparative analysis of the metabolomics of the caries population (DC) and the caries-free population (CF); Figure 2 This is the analysis diagram of the differential metabolites between the caries-affected population (DC) and the caries-free population (CF); Figure 3 is the expression distribution of the four markers in the caries population (DC) and caries-free population (CF) groups; Figure 4 This is the receiver operating characteristic (ROC) curve of four markers: 4-Acetamidobutanoic Acid, Adipic Acid, Pantetheine, and Palmitoylethanolamide (PEA). DETAILED DESCRIPTION

[0015] Figure 1-4As shown, a marker for predicting the occurrence of dental caries based on saliva metabolites is characterized in that it includes 4-acetylaminobutyric acid, adipic acid, pantetheine, and palmitoylethanolamide, and is used in the preparation of a kit for detecting the risk of dental caries in a subject.

[0016] Methods: Saliva metabolites were detected in 100 dental caries patients (DC) and 100 dental-free controls (CF). The distribution profiles and differential expression of metabolites between the two groups were evaluated using bioinformatics methods, and effective metabolite markers that could distinguish the two groups were screened.

[0017] 1) Population Selection: Two hundred university students who lived and studied at the same university were enrolled in this study. To control for the influence of confounding factors on dental caries, participants completed a questionnaire collecting information on gender, parental education level, and oral health behaviors (including fluoride toothpaste use, frequency of brushing, flossing, and sugar intake). All oral examinations were performed by trained dentists (Kappa value > 0.8).

[0018] The presence of dental caries was diagnosed using the ICDAS-II criteria. Saliva samples were collected from 100 individuals with an ICDAS score of >4 and 100 individuals without dental caries (ICDAS score = 0). Participants had to meet the following criteria: no genetic or systemic diseases; no dental fluorosis, periodontitis, recurrent oral ulcers, or other oral diseases; no fluoride treatment within the past 6 months; no antibiotics or disinfectants within the past 6 months; and an ICDAS score of >4 for the dental caries group and 0 for the dental caries-free healthy group.

[0019] Saliva sample collection: Non-stimulated saliva samples were collected from 100 dental caries patients (DC) and 100 dental-free controls (CF), and quickly transferred to a -80°C freezer for storage. They were then quickly transported by a dedicated person on dry ice to Wuhan Maiwei Metabolism Company for extraction and detection of saliva metabolites.

[0020] Metabolite extraction and detection: Saliva samples were thawed on ice and vortexed for 10 seconds. Each sample was then mixed with 20% acetonitrile-methanol and centrifuged at 4°C for 10 minutes. The supernatant was collected and allowed to stand at -20°C for half an hour before being centrifuged at 4°C for 3 minutes. The resulting supernatant was then collected and subjected to metabolite detection using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS / MS) (UPLC, ExionLC-AD, HPLC-ESI-MS / MS).

[0021] Quality Control: Quality control samples are prepared by mixing sample extracts and are used to monitor the repeatability of analytical samples under the same processing method. During the instrument analysis process, a quality control sample is inserted into every 10 analytical samples to monitor the repeatability of the analytical process.

[0022] 5) Data Analysis 5.1) Mass spectrometry data were processed using Analyst 1.6.3 software; 5.2) Use the self-built database MWDB (metware database) to perform qualitative analysis of metabolites; 5.3) Calculate the coefficient of variation (CV) values for the metabolites present in these quality control samples and exclude from this analysis those metabolites that exhibit a CV > 0.5 in either positive or negative ion mode; 5.4) Principal component analysis (PCoA) was performed using R 4.2.1 based on the Bray-Curtis distance. p If the p-value was <0.05 and the partial correlation coefficient (PCC) was <-0.2 or >0.2, there was a significant difference in metabolite abundance between the groups. Using a cross-validated random forest model, metabolite abundance information was input into a random forest classifier. The classifier was subjected to five 10-fold cross-validations, and the receiver operating characteristic (ROC) was plotted. The area under the curve (AUC) was calculated as a parameter for evaluating the discriminant model performance. The combination with the best discriminant performance was selected, and the importance index of each metabolite was output in the model. The higher the importance index, the more important the marker is for discriminating between caries and non-caries.

[0023] Experimental results: (1) Metabolomics grouping: 100 individuals with ICDAS > 4 were included in the caries group (DC), while 100 individuals without caries (ICDAS = 0) were included in the caries-free group (CF). We used partial correlation to exclude the influence of clinical phenotype. When using the PCoA model, the samples of the DC and CF groups were clearly separated, confirming the significant metabolomics differences between the two groups ( Figure 1 ).

[0024] Analysis of differential metabolites: We identified a total of 822 metabolites in 200 samples. There were 114 (13.9%, FDR < 0.05) differential metabolites between the two groups ( Figure 2 ). Figure 2 This is an analysis of differential metabolites between the caries-affected group (DC) and the caries-free group (CF). Red dots represent metabolites with high expression in the DC group, blue dots represent metabolites with low expression in the DC group, and brown dots represent metabolites with no difference.

[0025] Analysis of biomarkers: When we set the differential expression condition to pThere were 24 differentially expressed metabolites with a correlation coefficient of <0.05 and a fold change greater than 1.6. Among these 24 metabolites, the correlation coefficients of 15 metabolites were statistically significant ( p <0.05). Among these 15 metabolites, 4 metabolites (4-acetylaminobutyric acid, adipic acid, pantetheine and palmitoylethanolamide, Figure 3 ) were greater than 5, and the AUC values of these metabolites were higher than 0.8 ( Figure 4 ), which indicated that these four metabolites could be used as biomarkers for evaluating the caries status in constant-pressure series.

[0026] Biomarker 1: 4-Acetamidobutanoic Acid (4-acetamidobutanoic acid); Biomarker 2: Adipic Acid (adipic acid); Biomarker 3: Pantetheine (pantetheine); Biomarker 4: Palmitoylethanolamide (PEA) (Palmitoylethanolamide, as a marker, is used in the test kit to better determine the status of constant-pressure dental caries. It can be used in clinical diagnosis to assist clinicians in estimating the risk of constant-pressure dental caries in patients, identifying high-risk groups as early as possible, providing early intervention guidance, and improving the treatment effect of clinical patients.

Claims

1. A marker for predicting the occurrence of dental caries based on salivary metabolites, characterized by: The invention comprises the use of 4-acetylaminobutyric acid, adipic acid, pantetheine and palmitoylethanolamide in preparing a kit for detecting the risk of dental caries of a subject.

2. A marker for predicting the occurrence of dental caries based on saliva metabolites according to claim 1, characterized in that: The subject has permanent dentition.

3. The marker for predicting the occurrence of dental caries based on saliva metabolites according to claim 1, characterized in that: The sample used for detection in the kit is selected from saliva.

4. The method according to claim 5, wherein the marker for predicting the occurrence of dental caries based on saliva metabolites is characterized in that: The saliva is non-stimulated saliva.

5. A kit for predicting the occurrence of dental caries based on saliva metabolites, characterized in that: The kit detects the marker for predicting the occurrence of dental caries according to any one of claims 1 to 4 by using a metagenomic sequencing method.

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