Age prediction reagent and method and application thereof

Abstract

The invention belongs to the technical field of gene engineering, and particularly relates to a reagent for predicting age and a method and application thereof. The invention provides a reagent for predicting age. A detection target of the reagent comprises a salivary miRNA composition; the saliva miRNA composition is prepared from miR-142-3p, miR-27a-5p and miR-486-3p, and the miR-27a-5p and the miR-486- Age prediction can be realized by utilizing the miRNA composition disclosed by the invention, and the error is within 8.1 years old. Meanwhile, the invention also provides a method for predicting age, according to the method, based on fluorescent quantitative PCR data of three miRNAs (miR-142-3p, miR-27a-5p and miR-486-3p) of a saliva and / or saliva spot sample, the predicted age is analyzed by adopting a kNN model, and the method has the characteristic of high detection sensitivity, and is low in detection efficiency and lower in cost compared with a traditional method.

Description

Technical Field

[0001] The invention belongs to the technical field of genetic engineering, and specifically relates to a reagent for predicting age and a method and application thereof. Background Art

[0002] In the field of forensic medicine, traditional individual identification and analysis methods mainly rely on DNA fingerprinting technology, but these methods may have limitations when facing some complex samples or trace samples. For example, in some mixed saliva samples or saliva spots affected by environmental factors, DNA extraction and analysis may face many challenges, resulting in inaccurate results or failure to obtain effective information.

[0003] miRNA is a type of endogenous non-coding small RNA with a length of about 20 to 24 nucleotides. They regulate gene expression at the post-transcriptional level by complementary pairing with target mRNA and participate in various physiological and pathological processes of organisms. Studies have found that miRNA in saliva is relatively stable and can resist a certain degree of external environmental changes, such as temperature and humidity. Compared with DNA, miRNA is easier to preserve and detect in some cases. At the same time, there are differences in the expression profile of salivary miRNA in different individuals, and this difference may be related to factors such as the individual's physiological state and genetic background. For example, in certain disease states, the expression level of salivary miRNA will change significantly, which provides the possibility of disease-related forensic analysis through salivary miRNA. Especially at the crime scene, the saliva attached to items such as cigarette butts and cups left by criminals or the dry spots (saliva spots) formed by them provide a rich source of samples for miRNA-based analysis. However, at present, there is not enough in-depth research on the specific application scenarios of salivary miRNA in forensic medicine, and its role in key forensic issues such as individual age inference and individual source identification has not been fully explored. Therefore, there is an urgent need to provide an analytical system for predicting age using salivary miRNA. Summary of the invention

[0004] The purpose of the present invention is to provide a reagent for predicting age and a method and application thereof. By using the reagent of the present invention to detect a saliva miRNA composition, age prediction can be achieved with a small error.

[0005] The invention provides a reagent for predicting age, wherein the detection target of the reagent comprises a saliva miRNA composition; the saliva miRNA composition comprises miR-142-3p, miR-27a-5p and miR-486-3p.

[0006] As a preferred embodiment, the reagent includes a primer set for amplifying the salivary miRNA composition.

[0007] The present invention also provides a primer set for predicting age, wherein the detection target of the primer set includes a salivary miRNA composition; the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p; and the primer set includes a nucleotide sequence such as a sequence shown in SEQ ID NO.1~6.

[0008] The present invention also provides the use of the reagent or primer set described in the above scheme in predicting age.

[0009] The present invention also provides a method for predicting age, comprising the following steps: Extract the total miRNA from the saliva sample to be tested, and reverse transcribe to obtain cDNA; Using U6 as an internal reference, the obtained cDNA was amplified by fluorescence quantitative PCR using the primer set described in the above scheme to obtain the Ct values ​​of miR-142-3p, miR-27a-5p, miR-486-3p and U6, respectively, and recorded as Ct miR-142-3p , Ct miR-27a-5p , Ct miR-486-3p and Ct U6 ; According to formula 1, △Ct is calculated 样本 ; △Ct 样本 =Ct miRNA -Ct U6 Formula 1; the Ct miRNA Ct miR-142-3p , Ct miR-27a-5p or Ct miR-486-3p ; When the Ct miRNA Ct miR-142-3p When the △Ct of miR-142-3p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-27a-5p When the △Ct of miR-27a-5p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-486-3p When the △Ct of miR-486-3p in the sample was obtained 样本 ; The saliva samples of 20-year-old individuals were used as the control group samples, and the △Ct of the control group samples was calculated according to formula 1. 样本 , denoted as △Ct 对照 ; The relative gene expression levels of miR-142-3p, miR-27a-5p, and miR-486-3p were calculated according to formula 2; Relative gene expression = 2 -（△Ct样本-△Ct对照） Formula 2; The kNN model was used to analyze the data based on the relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p to obtain the predicted age.

[0010] As a preferred embodiment, the saliva sample includes saliva and / or saliva spots.

[0011] As a preferred embodiment, the extraction of miRNA from the saliva sample also includes pre-treatment of the saliva sample; the pre-treatment includes: adding 4 μL RNA carrier, 200 μL lysis solution and 20 μL digestion solution to the saliva sample, and oscillating and mixing.

[0012] As a preferred solution, the data analysis using the kNN model includes: inputting the calculated relative gene expression levels of miR-142-3p, miR-27a-5p and miR-486-3p into the kNN model database, setting parameters for data fitting using kNN, and obtaining the predicted age; the parameters are the number of neighbors: 5, metric: Euclidean metric, and weight: uniform.

[0013] As a preferred solution, the kNN model is constructed based on Orange software and the relative gene expression levels of miR-142-3p, miR-27a-5p and miR-486-3p in the training set and the actual age.

[0014] The present invention also provides a system for predicting age, comprising: (1) an input module, wherein the input module is used to input the relative expression levels of miR-142-3p, miR-27a-5p and miR-486-3p genes in a saliva sample; (2) a processing module, the processing module is used to input the relative expression of the gene into a prediction model for data analysis, so as to obtain a predicted age; the prediction model includes a kNN model; (3) An output module, wherein the output module is used to output the predicted age.

[0015] Beneficial effects: The present invention provides a reagent for predicting age, wherein the detection target of the reagent includes a salivary miRNA composition, wherein the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p. The miRNA composition of the present invention can be used to predict age, with an error within 8.1 years. At the same time, the present invention also provides a method for predicting age, wherein the method develops a miRNA extraction and fluorescence quantitative PCR method for saliva and / or salivary plaque samples, obtains PCR analysis data, and then uses a kNN model to analyze the predicted age based on the PCR data of three miRNAs (miR-142-3p, miR-27a-5p and miR-486-3p). The method has the characteristics of high detection sensitivity, low detection efficiency, and lower cost than traditional methods. DETAILED DESCRIPTION

[0016] The present invention provides a reagent for predicting age, wherein the detection target of the reagent includes a salivary miRNA composition; the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p. The miR-142-3p, miR-27a-5p and miR-486-3p in the saliva of the present invention can be used as age markers, and age prediction can be performed by analyzing the relative expression of miRNA genes in trace salivary spots. As an embodiment, the reagent includes a primer set for amplifying the salivary miRNA composition.

[0017] The present invention also provides a primer set for predicting age, wherein the detection target of the primer set includes a salivary miRNA composition; the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p; the primer set includes a nucleotide sequence such as a sequence shown in SEQ ID NO.1~6. In the present invention, a nucleotide sequence such as a sequence shown in SEQ ID NO.1~2 is used to amplify miR-142-3p; a nucleotide sequence such as a sequence shown in SEQ ID NO.3~4 is used to amplify miR-27a-5p; a nucleotide sequence such as a sequence shown in SEQ ID NO.5~6 is used to amplify miR-486-3p. As an embodiment, the primer set also includes a primer for amplifying an internal reference gene. In a specific embodiment of the present invention, the internal reference gene includes U6; the nucleotide sequence of the primer for amplifying U6 is shown in SEQ ID NO.7~8.

[0018] The present invention also provides the use of the reagent or primer set described in the above scheme in predicting age.

[0019] The present invention also provides a method for predicting age, comprising the following steps: Extract the total miRNA from the saliva sample to be tested, and reverse transcribe to obtain cDNA; Using U6 as an internal reference, the obtained cDNA was amplified by fluorescence quantitative PCR using the primer set described in the above scheme to obtain the Ct values ​​of miR-142-3p, miR-27a-5p, miR-486-3p and U6, respectively, and recorded as Ct miR-142-3p , Ct miR-27a-5p , Ct miR-486-3p and Ct U6 ; According to formula 1, △Ct is calculated 样本 ; △Ct 样本 =Ct miRNA -Ct U6 Formula 1; the Ct miRNA Ct miR-142-3p , Ct miR-27a-5p or Ct miR-486-3p ; When the Ct miRNA Ct miR-142-3p When the △Ct of miR-142-3p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-27a-5p When the △Ct of miR-27a-5p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-486-3p When the △Ct of miR-486-3p in the sample was obtained 样本 ; The saliva samples of 20-year-old individuals were used as the control group samples, and the △Ct of the control group samples was calculated according to formula 1. 样本 , denoted as △Ct 对照 ; The relative gene expression levels of miR-142-3p, miR-27a-5p, and miR-486-3p were calculated according to formula 2; Relative gene expression = 2 -（△Ct样本-△Ct对照） Formula 2; The kNN model was used to analyze the data based on the relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p to obtain the predicted age.

[0020] The present invention extracts total miRNA from a saliva sample to be tested. As an embodiment, the saliva sample includes saliva and / or salivary plaques. As an embodiment, the extraction of miRNA from the saliva sample also includes pre-treatment of the saliva sample; the pre-treatment includes: adding 4 µL RNA carrier, 200 µL lysis solution and 20 µL digestion solution to the saliva sample, and oscillating to mix. As another embodiment, the oscillation temperature is 56°C, and the oscillation time is 10 minutes. The sample of the present invention includes saliva and salivary plaques formed after the saliva is dried, which can expand the application scenarios.

[0021] The present invention reversely transcribes the extracted total miRNA to obtain cDNA. As an embodiment, the reverse transcription reaction system, in 20 µL, includes the following components: 10 µL 2×miRNA fluorescence quantitative reaction buffer (2×miRNA RTReaction Buffer), 2 µL miRNA fluorescence quantitative enzyme mixture (miRNA RT Enzyme Mix), 2 µL total RNA template, 6 µL ribonuclease-free double distilled water; the reverse transcription program is: 42°C 60 min; 93°C 30 min.

[0022] After obtaining cDNA, using U6 as an internal reference, the primer set described in the above scheme is used to perform fluorescent quantitative PCR amplification on the obtained cDNA. As an embodiment, the reaction system of the fluorescent quantitative PCR amplification is 20 μL, including the following components: 10 μL 2×miRcute enhanced miRNA premix (2×miRcute Plus miRNA PreMix (SYBR&ROX)), 0.4 μL forward primer, 0.4 μL reverse primer, 2 μL cDNA template solution and 7.2 μL double distilled water. As another embodiment, the reaction conditions of the fluorescent quantitative PCR amplification are: 95°C 15 min; 94°C 20 s, 64°C 30 s, 72°C 34 s, 5 cycles; 94°C 20 s, 60°C 34 s, 45 cycles. In a specific embodiment of the present invention, the nucleotide sequence of the internal reference U6 amplification primer is shown in SEQ ID NO.7~8.

[0023] After the fluorescence quantitative PCR amplification, the Ct values ​​of miR-142-3p, miR-27a-5p, miR-486-3p and U6 were obtained and recorded as Ct miR-142-3p , Ct miR-27a-5p , Ct miR-486-3p and Ct U6 ; Calculate △Ct according to formula 1 样本 ; △Ct样本 =Ct miRNA -Ct U6 Formula 1; the Ct miRNA Including Ct miR-142-3p , Ct miR-27a-5p or Ct miR-486-3p ; When the Ct miRNA Ct miR-142-3p When the △Ct of miR-142-3p in the sample was obtained 样本 , denoted as △Ct 样本-miR-142-3p ; When the Ct miRNA Ct miR-27a-5p When the △Ct of miR-27a-5p in the sample was obtained 样本 , denoted as △Ct 样本-miR-27a-5p ; When the Ct miRNA Ct miR-486-3p When the △Ct of miR-486-3p in the sample was obtained 样本 , denoted as △Ct 样本-miR-486-3p ; In a specific embodiment of the present invention, the ΔCt 样本-miR-142-3p =Ct miR-142-3p -Ct U6 ; the ΔCt 样本-miR-27a-5p =Ct miR-27a-5p -Ct U6 ; the ΔCt 样本-miR-486-3p =Ct miR-486-3p -Ct U6 .

[0024] The present invention uses saliva samples of 20-year-old individuals as control group samples, and calculates the △Ct of the control group samples according to formula 1: 样本 , denoted as △Ct 对照 In a specific embodiment of the present invention, the ΔCt values ​​of miR-142-3p, miR-27a-5p and miR-486-3p in the control group samples are 对照 , respectively denoted as △Ct 对照-miR-142-3p , ΔCt control -miR-27a-5p and ΔCt 对照-miR-486-3p The present invention randomly selects individuals aged 20 years old, and can establish a relatively standard miRNA (miR-142-3p, miR-27a-5p and miR-486-3p) expression baseline, accurately reflecting the change pattern of miRNA in the sample to be tested, thereby improving the accuracy of age prediction.

[0025] The relative gene expression levels of miR-142-3p, miR-27a-5p, and miR-486-3p were calculated according to formula 2; Relative gene expression = 2 -（△Ct样本-△Ct对照） Formula 2; Based on the relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p, the kNN model is used to perform data analysis to obtain the predicted age. As an embodiment, the kNN model is constructed based on Orange software and the relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p in the training set and the actual age. In a specific embodiment of the present invention, the training set is 45 male saliva spot samples with determined ages; after the model is constructed by the present invention, the age parameter is adjusted by cross-validation with the retention method, and verified by the validation data set. As an embodiment, the data analysis using the kNN model includes: inputting the calculated relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p into the kNN model database, setting the parameters for data fitting using kNN, and obtaining the predicted age; the parameters are the number of neighbors: 5, the metric: Euclidean metric, and the weight: uniform.

[0026] The present invention also provides a system for predicting age, comprising: (1) an input module, wherein the input module is used to input the relative expression levels of miR-142-3p, miR-27a-5p and miR-486-3p genes in a saliva sample; (2) a processing module, the processing module is used to input the relative expression of the gene into a prediction model for data analysis, so as to obtain a predicted age; the prediction model includes a kNN model; (3) An output module, wherein the output module is used to output the predicted age.

[0027] In order to further illustrate the present invention, a reagent for predicting age and its method and application provided by the present invention are described in detail below in conjunction with embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0028] Example 1 (1) Saliva stain sample collection: Saliva (stain) samples from 20-year-old male individuals were collected and recorded as control group samples.

[0029] (2) Extraction of salivary plaque RNA: Use the BIOG RNA extraction kit to extract RNA from saliva (plaque) samples (the saliva plaque sample is made by smearing 300 µL of saliva on a blood card, the smearing area is about 1 cm², and it needs to be cut into pieces before extraction).

[0030] A. Prepare anhydrous ethanol, 1.5 mL RNase-free centrifuge tubes, and 2.0 mL RNase-free centrifuge tubes by yourself.

[0031] B. Take out the washing solution and add anhydrous ethanol according to the corresponding steps: a) Washing solution A: Mix at a ratio of 7:3 (washing solution: anhydrous ethanol). b) Washing solution B: Mix at a ratio of 3:7 (washing solution: anhydrous ethanol). c) If precipitation occurs after preparation, dissolve the precipitation at 37°C and shake well.

[0032] C. Saliva pretreatment method: Take 300 µL of saliva sample into a centrifuge tube, add 4 µL of RNA Carrier and mix evenly, add 200 µL of lysis buffer and 20 µL of digestion buffer, shake and mix evenly, and place in a 56°C water bath for 10 min; Saliva spot pretreatment method: Take a 1cm² saliva spot sample into a centrifuge tube, add 4 µL RNA Carrier and mix evenly, add 200 µL lysis buffer and 20 µL digestion buffer, shake and mix, and place in a 56℃ water bath for 10 min.

[0033] D. Add 1 mL of anhydrous ethanol and gently invert to mix. A translucent suspension may appear, but it will not affect subsequent experiments.

[0034] E. Place the adsorption column into the collection tube, transfer 760 µL of the sample solution into the adsorption column, let it stand for 2 min, centrifuge at 12000 rpm at 4°C for 1 min, and discard the waste liquid in the collection tube. Repeat this step twice until all the prepared sample solution is transferred.

[0035] F. Place the adsorption column back into the collection tube, add 500 µL of washing solution A to the adsorption column, centrifuge at 12,000 rpm, 4°C for 1 min, and discard the waste liquid.

[0036] G. Place the adsorption column back into the collection tube, add 500 µL of washing solution B into the adsorption column, let it stand for 2 min, centrifuge at 12,000 rpm, 4°C for 1 min, and discard the waste liquid.

[0037] H. Place the adsorption column back into the collection tube and centrifuge at 12,000 rpm and 4°C for 2 min to remove the remaining washing solution.

[0038] I. Take out the adsorption column, put it into a new 1.5 mL centrifuge tube, add 30 µL of elution buffer, let it stand for 3 min, centrifuge at 12000 rpm, 4°C for 2 min, and save the RNA solution.

[0039] (3) Reverse transcription A. Preparation of reverse transcription system Thaw 2× miRNA RT Reaction Buffer and mix well. Place miRNA RT Enzyme Mix on ice for later use. Add the following reagents to a pre-cooled RNase Free reaction tube on ice to a total volume of 20 μL (the final RNA input amount is 50 ng).

[0040] Table 1 Reverse transcription system configuration

[0041] B. Use a pipette to gently mix the prepared reaction solution, and perform the reverse transcription reaction of miRNA according to the procedure in Table 2.

[0042] Table 2 Amplification conditions

[0043] (4) Fluorescence quantitative PCR reaction: Detection of three age-related miRNAs (miR-142-3p, miR-27a-5p and miR-486-3p U6).

[0044] The PCR system was prepared as shown in Table 3. The cDNA obtained after reverse transcription was diluted 100 times. 2 μL of the diluted cDNA (5 ng / μL) was used as the template for real-time PCR assay. The miRcute miRNA qPCR Detection Kit (Tiangen, China) and 7500RT-PCR Detection System (Applied Biosystems, USA) were used to perform the experiment and calculate the Ct value of each reaction.

[0045] Table 3 PCR reaction system

[0046] The primer sequences and reaction procedures of the PCR are shown in Tables 4 and 5.

[0047] Table 4 PCR primer sequences

[0048] Table 5 PCR reaction conditions

[0049] (5) PCR result analysis The Ct of each group was obtained by fluorescence quantitative PCR, with U6 as the internal reference, and recorded as Ct miR-142-3p , Ct miR -27a-5p , Ct miR-486-3p and Ct U6; △Ct is obtained by subtracting the Ct of the internal reference from the Ct of the three age-related miRNAs (miR-142-3p, miR-27-5p, miR-486-3p), and the formula is as follows: △Ct 样本 =Ct miRNA -Ct U6 Formula 1; the Ct miRNA Ct miR-142-3p , Ct miR-27a-5p or Ct miR-486-3p ; The △Ct of the control group samples 样本 Denoted as △Ct 对照 ,in, △Ct 对照-miR-142-3p =Ct miR-142-3p -Ct U6 ; △Ct 对照-miR-27a-5p =Ct miR-27a-5p -Ct U6 ; △Ct 对照-miR-486-3p =Ct miR-486-3p -Ct U6 △Ct of three miRNAs in the control group 对照 The values ​​are shown in Table 6.

[0050] Table 6 △Ct of three miRNAs in the control group 对照 value

[0051] Example 2 (1) Determination of relative expression of miRNA in samples 45 male saliva spot samples with a certain age were selected, and their actual ages were counted. The Ct values ​​corresponding to miR-142-3p, miR-27-5p, miR-486-3p and U6 in each sample were calculated using the method of Example 1, and were recorded as Ct miR -142-3p , Ct miR-27a-5p , Ct miR-486-3p and Ct U6 .

[0052] According to Formula 1 in Example 1, the ΔCt values ​​of miR-142-3p, miR-27a-5p and miR-486-3p were calculated. 样本 The relative expression of miR-142-3p, miR-27-5p, and miR-486-3p in each sample was calculated according to Formula 2, where △Ct 对照 The value is calculated for Example 1.

[0053] Relative gene expression = 2 -（△Ct样本-△Ct对照） Formula 2.

[0054] The test results are shown in Table 7.

[0055] Table 7 45 sample data

[0056] (2) Use machine learning techniques to build an age inference model Orange software (orange, Slovenia) was used to establish an age inference model: multiple constants were left out to evaluate the support vector machine (SVM) algorithm, decision tree (Tree) model, random forest algorithm, linear regression algorithm, adaptive boosting (AdaBoost) algorithm, k-nearest neighbor (kNN) algorithm, stochastic gradient descent (SGD) algorithm, and gradient boosting algorithm. The age parameter was adjusted by leave-one-out cross-validation. Then, the training set data (the relative expression data of miR-142-3p, miR-27-5p, and miR-486-3p genes in the 45 samples in step (1) were used as the training set) were used to predict the results of saliva stains. In order to evaluate different statistical models, the mean absolute error (MAE) and root mean square error (RMSE) values ​​were analyzed and compared.

[0057] Finally, it was concluded that the kNN method was the best, with an average age error of 7.273 years.

[0058] (3) Model validation A. Randomly select 20 healthy males aged 22 to 69 years old and collect saliva plaque samples as the validation data set. According to the method in step (1), the relative expression levels of miR-142-3p, miR-27-5p, and miR-486-3p in each sample are determined. The results are shown in Table 8.

[0059] Table 8 20 sample data

[0060] B. Use the validation data set to validate all models in step (2). In order to evaluate different statistical models, the mean absolute error (MAE) and root mean square error (RMSE) values ​​are analyzed and compared. Among them, kNN has the smallest average error age, with an average error value of 8.120.

[0061] Among them, when the kNN model is used as the evaluation model for predicting age in the 20 validation data sets in step (A), the operation is as follows: the relative gene expression levels of miR-142-3p, miR-27-5p, and miR-486-3p of the 20 samples measured in step (A) are input into the above-evaluated kNN model database, and the parameters for data fitting using kNN are set as the number of neighbors: 5, the metric: Euclidean, and the weight: Uniform, and the predicted age can be obtained. The results are shown in Table 9.

[0062] Table 9 Age inference results

[0063] According to the results in Table 9, the sample age predicted by this method is similar to the actual age, with an average error of 8.120.

[0064] It can be seen that the combination of miR-142-3p, miR-27-5p, and miR-486-3p in saliva can be used to predict age with a small error. The method of the present invention has high detection efficiency and sensitivity and is less expensive than traditional detection methods.

[0065] Although the above embodiment describes the present invention in detail, it is only a part of the embodiments of the present invention, not all of the embodiments. People can also obtain other embodiments based on this embodiment without creativity, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A reagent for predicting age, characterized in that: The detection target of the reagent includes a salivary miRNA composition; the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p.

2. The reagent according to claim 1, characterized in that The reagents include a primer set for amplifying the salivary miRNA composition.

3. A primer set for predicting age, characterized in that: The detection target of the primer set includes a salivary miRNA composition; the salivary miRNA composition includes miR-142-3p, miR-27a-5p and miR-486-3p; the primer set includes a nucleotide sequence such as a sequence shown in SEQ ID NO.1~6.

4. Use of the reagent according to claim 1 or 2 or the primer set according to claim 3 in predicting age.

5. A method for predicting age, characterized in that: The following steps are involved: Extract the total miRNA from the saliva sample to be tested, and reverse transcribe to obtain cDNA; Using U6 as an internal reference, the obtained cDNA was amplified by fluorescent quantitative PCR using the primer set described in claim 3 to obtain the Ct values ​​of miR-142-3p, miR-27a-5p, miR-486-3p and U6, which were respectively recorded as Ct miR-142-3p , Ct miR-27a-5p , Ct miR -486-3p and Ct U6 ; According to formula 1, △Ct is calculated 样本 ; △Ct 样本 =Ct miRNA -Ct U6 Formula 1; the Ct miRNA Ct miR-142-3p , Ct miR-27a-5p or Ct miR-486-3p ; When the Ct miRNA Ct miR-142-3p When the △Ct of miR-142-3p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-27a-5p When the △Ct of miR-27a-5p in the sample was obtained 样本 ; When the Ct miRNA Ct miR-486-3p When the △Ct of miR-486-3p in the sample was obtained 样本 ; The saliva samples of 20-year-old individuals were used as the control group samples, and the △Ct of the control group samples was calculated according to formula 1. 样本 , denoted as △Ct 对照 ; The relative gene expression levels of miR-142-3p, miR-27a-5p, and miR-486-3p were calculated according to formula 2; Relative gene expression = 2 -（△Ct样本-△Ct对照） Formula 2; The kNN model was used to analyze the data based on the relative gene expression of miR-142-3p, miR-27a-5p and miR-486-3p to obtain the predicted age.

6. The method according to claim 5, characterized in that The saliva sample includes saliva and / or saliva spots.

7. The method according to claim 5 or 6, characterized in that: The method further includes pre-treating the saliva sample before extracting the miRNA from the saliva sample; the pre-treatment includes: adding 4 µL RNA carrier, 200 µL lysis solution and 20 µL digestion solution to the saliva sample, and oscillating and mixing.

8. The method according to claim 5, characterized in that The data analysis using the kNN model includes: inputting the calculated relative gene expression levels of miR-142-3p, miR-27a-5p and miR-486-3p into the kNN model database, setting parameters for data fitting using kNN, and obtaining the predicted age; the parameters are the number of neighbors: 5, the metric: Euclidean metric, and the weight: uniform.

9. The method according to claim 5, characterized in that The kNN model was constructed based on Orange software and the relative gene expression levels of miR-142-3p, miR-27a-5p and miR-486-3p in the training set and the actual age.

10. A system for predicting age, characterized in that: include: (1) an input module, wherein the input module is used to input the relative expression levels of miR-142-3p, miR-27a-5p and miR-486-3p genes in a saliva sample; (2) a processing module, the processing module is used to input the relative expression of the gene into a prediction model for data analysis, so as to obtain a predicted age; the prediction model includes a kNN model; (3) An output module, wherein the output module is used to output the predicted age.

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