Intestinal flora marker related to mental health state and application thereof

Abstract

The invention discloses an intestinal flora marker related to a mental health state. The intestinal flora marker at least comprises one of Ackerman bacteria, bifidobacterium longum or lactobacillus helveticus. The invention further discloses application of the intestinal flora marker in preparation of products for predicting or diagnosing psychological sub-health, application of the intestinal flora marker in preparation of drugs for treating or improving psychological sub-health and application of the intestinal flora marker in preparation of health food for improving psychological sub-health. When the three kinds of bacteria are used as predictive factors of the psychological sub-health, the accuracy is high, the predictive mode is noninvasive, and a new way is provided for early discovery, early diagnosis and early treatment of the psychological sub-health.

Description

Technical Field

[0001] The present invention relates to an intestinal flora marker related to mental health status and its application in preparing products for predicting and diagnosing mental illness, preparing drugs for treating mental illness and preparing health products for improving mental illness, belonging to the field of medical evaluation and detection technology. Background Art

[0002] Mental health problems are one of the main factors leading to the global burden of disease. Mental health problems often precede the occurrence of organic diseases and are early signals or triggers of physiological diseases. Therefore, mental health problems have a wide range of social impacts and far-reaching health significance, which can provide a basis for early identification and intervention, reduce personal suffering as early as possible, reduce social burdens, and provide guarantees for economic development and social stability. The WHO's Mental Health Action Plan 2013-2020 points out that psychological health (PH) is a good state of an individual in terms of emotions, thinking and behavior, and can effectively cope with stress in life, maintain good social adaptability, and have positive self-cognition and emotional experience. Psychological sub-health (PSH) is a state between health and disease. Individuals may feel physical or psychological discomfort, but have not yet reached the diagnostic criteria for the disease. Psychological sub-health is often closely related to anxiety and depression, and psychological sub-health may be a precursor to these two emotional disorders. In the state of psychological sub-health, individuals may experience persistent worry and tension, leading to increased anxiety levels; long-term psychological sub-health may trigger depression.

[0003] At present, the identification methods of mental health and mental sub-health are mainly subjective evaluation through mental health scales and interviews, and objective evaluation through physiological indicators and behavioral observations. However, traditional methods are highly subjective, and the results of questionnaires, interviews and self-reports are easily affected by the subjective state of the person being evaluated (for example, when they are irritable, they may be unwilling to fill out the scale completely, or randomly select options), and there may be deliberate concealment or cognitive bias; secondly, there is a lack of early warning. Traditional methods are usually applied when the mental state has obviously fluctuated, and it is impossible to capture the early signals of sub-health in advance; at the same time, long-term and dynamic monitoring is difficult. The mental state has the characteristics of dynamic changes. It is difficult to achieve high-frequency monitoring by relying on regular questionnaires or interviews. Physiological indicators such as heart rate and cortisol levels usually need to be repeatedly measured, and they are highly volatile and difficult to reflect the continuous mental state; in addition, traditional methods cannot directly associate with biological mechanisms, and do not directly reveal the biological basis behind mental health problems, which limits the precision of intervention measures. Therefore, it is necessary to find a new method with strong objectivity, high sensitivity, and convenient long-term dynamic monitoring and biological mechanism association to identify mental health and sub-health.

[0004] In recent years, the study of the "gut-brain" axis has revealed the close relationship between intestinal microbiota and mental health, providing a new way to distinguish between mental health and sub-health status. In the detection method using microbiota as a marker, the composition and metabolites of the microbiota can be detected through biological samples such as feces to avoid subjective bias, but it does not determine which intestinal microbiota markers have a direct correspondence with mental health status. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide an intestinal flora marker, which is related to the mental health state, directly associated with the biological mechanism, can objectively and sensitively reflect the mental health state, and is convenient for long-term dynamic monitoring.

[0006] The applicant found that changes in the intestinal flora can reflect fluctuations in mental state, and changes in specific flora may appear before the occurrence and development of mental health, which is helpful for early identification and timely intervention; regular collection of fecal samples can facilitate high-frequency dynamic monitoring of individual mental states; microbial markers can not only assist in diagnosis, but also reveal the biological mechanisms of changes in mental state by analyzing their metabolites and related pathways.

[0007] Therefore, in order to solve the above technical problems, the present invention discloses an intestinal flora marker associated with mental health status, and the intestinal flora marker includes at least one of Akkermansia, Bifidobacterium longum or Lactobacillus helveticus.

[0008] Furthermore, the intestinal flora marker includes any two of Akkermansia, Bifidobacterium longum or Lactobacillus helveticus.

[0009] Furthermore, the intestinal flora markers include Akkermansia, Bifidobacterium longum and Lactobacillus helveticus.

[0010] Furthermore, the mental health state is divided into mental health and mental sub-health, the mental sub-health includes one or both of anxiety and depression, and the mental health does not include anxiety or depression.

[0011] The present invention also discloses an application of the aforementioned intestinal flora marker associated with mental health status in the preparation of a product for predicting or diagnosing mental sub-health.

[0012] Furthermore, the product is a reagent containing a primer sequence of the intestinal flora marker or a kit containing the reagent, and the primer sequence meets the requirements of a PCR experiment.

[0013] Furthermore, the reagent predicts or diagnoses the mental health state by measuring the abundance of the intestinal flora marker.

[0014] Furthermore, the abundance RQ value is calculated by detecting the Ct value of the intestinal flora marker by real-time fluorescence quantitative PCR, RQ=2 -ΔΔCt , ΔΔCt 样本 =ΔCt Mean 样本 -ΔCt Mean 样本1 , ΔCt Mean 样本 =CtMean 样本 -Ct Mean 内参 , the Ct Mean 样本 is the average Ct value of a single intestinal flora marker in a single sample. 内参 is the average Ct value of all intestinal flora in a single sample, the ΔCt Mean 样本1 ΔCtMean of a single sample 样本 Subtract the ΔCt mean of all samples 样本 The average value of .

[0015] The present invention also discloses the use of the aforementioned intestinal flora marker associated with mental health status in the preparation of a drug for treating or improving mental sub-health.

[0016] The present invention also discloses an application of the intestinal flora marker related to the mental health state as mentioned above in the preparation of health-care food for improving mental sub-health.

[0017] The applicant discovered in the long-term medical research that Akkermansia, Bifidobacterium longum and Lactobacillus helveticus are associated with mental health status. Therefore, the association between these three intestinal flora and mental health status was verified as follows:

[0018] 1. Questionnaire Collection

[0019] (1) Through on-site recruitment, publicity and questionnaire survey, several volunteers were randomly selected to conduct a comprehensive questionnaire survey on general conditions and psychological scales, including the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS). Those who received at least one questionnaire were qualified and officially served as subjects.

[0020] 2. Stool Sample Collection

[0021] (2) Use a sterile sampling tube to collect fresh feces from subjects who have been evaluated in step (1) and are recruited as samples for future use; or temporarily stored in a dry ice box; or placed in a dry ice box and transported to the laboratory and frozen in a refrigerator. The specific operation method is determined based on when the genomic DNA extraction is performed on the collected fresh feces. The refrigerator temperature for storage can be -20℃, -40℃, -80℃, etc., depending on the storage time required.

[0022] 3. Extraction of DNA from intestinal flora

[0023] (3) According to the experimental requirements, take an appropriate amount of the fecal sample collected in step (2), usually 100-200 mg.

[0024] (4) Extracting the intestinal flora DNA from the stool sample obtained in step (3) to obtain an intestinal flora DNA sample. The intestinal flora DNA sample can be extracted by a centrifugal column purification method or other methods.

[0025] (5) Determine the concentration of nucleic acid, A260 / A280 and other information in the gut flora DNA sample extracted in step (4). The gut flora DNA sample contains trace amounts of impurities such as RNA and protein, or there is DNA breakage, so its quality needs to be judged based on the measurement information. If the quality is unqualified, the gut flora DNA sample is discarded. The measurement instrument can be a spectrophotometer or the like.

[0026] 4. Real-time fluorescence quantitative PCR detection

[0027] (6) Primer design: Search the gene ID of the target gene (i.e., the intestinal flora markers Akkermansia, Bifidobacterium longum and Lactobacillus helveticus of the present invention) in the database of the National Center for Biotechnology Information (NCBI) of the United States, import the searched gene ID into the Primer Bank to obtain the primer sequence of the target gene, the length of the primer sequence is 15-30 base pairs, and the GC content is 40%-60%, and then import the obtained primer sequence into the Basic Local Alignment Search Tool (BLAST) of NCBI to check the specificity of the primer corresponding to the primer sequence. The primer sequence of the target gene used is shown in Table 1:

[0028] Table 1 Primer sequences for real-time fluorescence quantitative PCR detection of intestinal flora markers

[0029]

[0030] (7) Sample dilution: When the concentration of the intestinal flora DNA sample obtained in step (4) is too high, it is diluted with double distilled water (ddH2O) to obtain a concentration suitable for amplification.

[0031] (8) Primer dilution: Dissolve the primers confirmed in step (6) in ddH2O and dilute to a working concentration of 10-12.5 μM.

[0032] (9) Add the sample to the real-time fluorescence quantitative PCR amplification tube: first add the quantitative qPCR Mix (PCR amplification solution), upstream primer F, downstream primer R, and double distilled H2O to obtain a primer mixture system, then add the quantitative intestinal flora DNA sample obtained in step (4) or the intestinal flora DNA sample diluted in step (7), apply a film, centrifuge slightly to mix, and place on ice away from light.

[0033] (10) PCR reaction: Place the amplification tube after adding the sample in step (9) into a real-time fluorescence quantitative PCR amplification instrument and select the SYBR GREEN fluorescence detection mode.

[0034] 5. Statistical Analysis

[0035] (11) Determine the reaction product using the melting curve (Melting curve is a curve based on the degree of degradation of the double helix structure of DNA as the temperature increases) obtained by the PCR reaction in step (10), and observe the peak graph. If it is a single peak, it means that the primer sequence is acceptable, indicating good amplification specificity and good product purity; the amplification curves obtained by repeated wells of the same sample are basically overlapping, indicating that the sample reproducibility is acceptable.

[0036] (12) Calculate the RQ value: RQ = 2 -ΔΔCt , ΔΔCt 样本 =ΔCt Mean 样本 -ΔCt Mean 样本1 , ΔCt Mean 样本 =Ct Mean 样本 -Ct Mean 内参 In real-time PCR, Ct Mean refers to the average value of the cycle threshold value, and the subject is the sample. 样本 is the average Ct value of a single intestinal flora marker in a single subject. 内参 is the average Ct value of all intestinal flora in a single subject, the ΔCt Mean 样本1 ΔCt Mean of a single subject 样本Subtract the ΔCt mean of all subjects 样本 The average value of .

[0037] (13) All variables were described using mean ± standard error or median (range). Based on the results of normality test and variance homogeneity test, one-way analysis of variance (ANOVA) or Kruskal-Wallis test was used for multiple group comparisons of variables. Pearson correlation analysis or Spearman rank correlation was used for bivariate correlation analysis. If P < 0.05, the difference between the groups was statistically significant.

[0038] The present invention has discovered for the first time that Akkermansia, Bifidobacterium longum and Lactobacillus helveticus are significantly reduced in people with psychological subhealth, especially those suffering from anxiety, depression, or anxiety and depression at the same time. Therefore, the present invention uses intestinal flora markers to identify the psychological health and psychological subhealth of the population, which can be applied to the preparation of screening, prediction and diagnosis products for patients with mental illness, and to the preparation of health foods for alleviating symptoms related to mental illness. The method is non-invasive, highly objective, highly sensitive, and convenient for long-term dynamic monitoring and biological mechanism association. By integrating key flora into a prediction model, it is used to identify psychological health and subhealth status, providing a basis for early intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a result diagram of the relative quantification (i.e., the corresponding abundance RQ value) of intestinal flora markers in the fecal samples of each subject in cohort A detected by real-time fluorescence quantitative PCR in Example 1;

[0040] Figure 2 This is the ROC curve diagram of anxiety and intestinal flora of cohort A in Example 1;

[0041] Figure 3 This is the ROC curve diagram of depression and intestinal flora in cohort A in Example 1;

[0042] Figure 4 The ROC curve diagram of the psychological sub-health status and intestinal flora of cohort A in Example 1;

[0043] Figure 5 This is a graph showing the relative quantitative results of intestinal flora in the fecal samples of each subject in Cohort B of Example 2;

[0044] Figure 6 This is a ROC curve diagram of the psychological sub-health status and intestinal flora of cohort B in Example 2;

[0045] Note: Data are expressed as mean ± standard error, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. p values ​​were calculated by paired sample t-test, Pearson test or one-way analysis of variance (One-way ANOVA). Area Under Curve (AUC): area under the ROC curve; Confidence intervals (CI): confidence intervals. DETAILED DESCRIPTION

[0046] The present invention is further explained below in conjunction with the examples. The examples are merely illustrative of the present disclosure and do not define the scope of the present disclosure. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

[0047] Example 1

[0048] The following steps are used to determine the bacterial flora marker method for identifying mental health and mental sub-health people:

[0049] 1. Questionnaire Collection

[0050] (1) Through on-site recruitment, publicity and epidemiological survey questionnaires, 23 volunteers were randomly recruited as subjects (designated as cohort A). A comprehensive epidemiological survey of general conditions and psychological scales was first conducted. The mental health scale assessment included the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS). For the SAS and SDS tables, forward scoring questions were scored as 1, 2, 3, and 4, and reverse scoring questions were scored as 4, 3, 2, and 1. The total score was multiplied by 1.25 and the integer was obtained to obtain the standard score. In the Self-Rating Anxiety Scale (SAS), a standard score of 25-49 was normal, 50-59 was mild anxiety, 60-69 was moderate anxiety, and 70-100 was severe anxiety; in the Self-Rating Depression Scale (SDS), a standard score below 50 was normal; 50-60 was mild depression, 61-70 was moderate depression, and 70 or above was severe depression. In cohort A, if the score of either the anxiety self-rating scale or the depression self-rating scale exceeded 50 points, it was considered as psychological sub-health (PSH); if the scores of both questionnaires were normal, it was considered as psychological health (PH).

[0051] The psychological scale score results for each subject in cohort A are shown in Table 2. Two volunteers did not receive both scales and were no longer included in the statistics as subjects.

[0052] Table 2: Psychological scale scores and diagnostic results of cohort A

[0053]

[0054]

[0055] Psychological sub-health, PSH; Psychological health, PH; - SAS and SDS tables were not provided for the subjects.

[0056] 2. Stool Sample Collection

[0057] (2) Collect fresh feces from the 21 subjects in step (1) as samples, put them into sterile sampling tubes, place them in a dry ice box, and quickly transfer them to a -80°C refrigerator for freezing and storage within 30 minutes in preparation for subsequent testing.

[0058] 3. Extraction of intestinal flora genomic DNA

[0059] (3) Take 100 mg of the stool sample from step (2) and place it in a grinding tube.

[0060] (4) The intestinal flora DNA of the fecal sample is extracted by centrifugal column purification to obtain an intestinal flora DNA sample.

[0061] (5) The concentration of the intestinal flora DNA sample was measured by a spectrophotometer, and the concentration range was 128.04±60.54ng / μL. The absorbance of DNA (including trace RNA) at 260nm and the absorbance at 280nm A260 and A280 were also measured, and their ratio was calculated. A260 / A280 was 1.87±0.03. The absorbance of pollutants such as organic solvents, salts, and polysaccharides at 230nm A230 was also measured, and the ratio of A260 to A230 was calculated. As shown in Table 3, it can be seen that the obtained intestinal flora DNA sample meets the quality requirements. The concentration range can be obtained by the mean and standard deviation of the corresponding values ​​of all subject samples in Table 3.

[0062] Table 3: Concentrations and related absorbance values ​​of intestinal flora DNA samples of cohort A subjects

[0063]

[0064] 4. Real-time fluorescence quantitative PCR detection

[0065] (6) Primer design: The gene ID of the target gene (i.e., the intestinal flora markers Akkermansia, Bifidobacterium longum and Lactobacillus helveticus of the present invention) is searched in the database of the National Center for Biotechnology Information (NCBI) of the United States, and the searched gene ID is imported into the Primer Bank to obtain the primer sequence of the target gene. The primer sequence length is 15-30 base pairs and the GC content is 40%-60%. The obtained primer sequence is then imported into the Basic Local Alignment Search Tool (BLAST) of NCBI to check the specificity of the primers corresponding to the primer sequences. If all meet the requirements, the primers are confirmed.

[0066] The obtained primer sequences are shown in Table 1.

[0067] (7) Sample dilution: When the concentration of the intestinal flora DNA sample obtained in step (4) is too high, it is diluted with double distilled water (ddH2O) to obtain a concentration suitable for amplification, which is 27.39±9.04 ng / μL, see Table 3.

[0068] (8) Primer dilution: Dissolve the primers confirmed in step (6) with ddH2O and dilute to a working concentration of 10-12.5 μM. The primers can be purchased directly from the market based on the primer sequences obtained in step (6).

[0069] (9) Add the sample to the real-time fluorescence quantitative PCR amplification tube: first add 12.5 μL of qPCR Mix (PCR amplification solution, conventional amplification solution can be used), 2 μL of upstream primer F, 2 μL of downstream primer R, and 6.5 μL of double distilled water (double distilled H2O, ddH2O) as shown in the table below to obtain 23 μL of primer mixture system, then add 2 μL of the intestinal flora DNA sample obtained in step (4) or the intestinal flora DNA sample diluted in step (7), apply a film, centrifuge slightly to mix, and place on ice away from light. The PCR reaction system of this step is shown in Table 4.

[0070] Table 4: PCR reaction system

[0071] Reagent name volume qPCR Mix 12.5μL Upstream primer F (12.5 μM) 2μL Downstream primer R (12.5 μM) 2μL <![CDATA[Doubly distilled water (doubledistilled H2O, ddH2O)]]> 6.5μL Gut flora DNA samples 2μL Total volume 25μL

[0072] (10) PCR reaction: Place the amplification tube after adding the sample in step (9) into a real-time fluorescence quantitative PCR amplification instrument, select the SYBR GREEN fluorescence detection mode, and the specific amplification reaction conditions are shown in Table 5:

[0073] Table 5: PCR reaction conditions

[0074]

[0075] 5. Statistical Analysis

[0076] (11) Determine the reaction product by the melting curve (Melting curve is a curve based on the degree of degradation of the double helix structure of DNA as the temperature increases) obtained by the PCR reaction in step (10): Observe the peak graph. If it is a single peak, it means that the primer sequence is acceptable, indicating good amplification specificity and good product purity; the amplification curves obtained by repeated wells of the same sample are basically overlapping, indicating that the sample reproducibility is acceptable.

[0077] (12) Calculate the RQ value: RQ = 2 -ΔΔCt , ΔΔCt 样本 =ΔCt Mean 样本 -ΔCt Mean 样本1 , ΔCt Mean 样本 =Ct Mean 样本 -Ct Mean 内参 The Ct Mean 样本 is the average Ct value of a single intestinal flora marker in a single subject. 内参 is the average Ct value of all intestinal flora in a single subject, the ΔCt Mean 样本1 ΔCt Mean of a single subject 样本 Subtract the ΔCt mean of all subjects 样本 See Table 6-8 for details.

[0078] Table 6: Real-time fluorescence quantitative PCR detection results of total bacteria and Akkermansia in intestinal flora DNA samples of feces of subjects in cohort A

[0079]

[0080]

[0081] Table 7: Real-time fluorescence quantitative PCR detection results of Lactobacillus helveticus in intestinal flora DNA samples of feces of subjects in cohort A

[0082]

[0083] Table 8: Real-time fluorescence quantitative PCR detection results of Bifidobacterium longum in the intestinal flora DNA samples of feces of subjects in cohort A

[0084]

[0085] The abundance (RQ) distribution of Akkermansia, Lactobacillus helveticus and Bifidobacterium longum corresponding to different subjects is shown in Figure 2. Figure 1 shown.

[0086] (13) All variables were described using mean ± standard error or median (range). Based on the results of normality test and variance homogeneity test, one-way analysis of variance (ANOVA) was used. Pearson correlation analysis was performed. If P < 0.05, the difference between the groups was statistically significant.

[0087] According to the diagnosis results of mental illness of each subject in cohort A, ROC analysis was performed in combination with the relative quantitative value (abundance RQ value) of each intestinal bacteria to determine the specific biomarkers for judging the mental health status. SPSS25 software was used to calculate the predictive variable values ​​of single bacteria, double bacteria (Lactobacillus helveticus + Bifidobacterium longum) and triple bacteria (Akkermansia helveticus + Lactobacillus helveticus + Bifidobacterium longum) through binary logistic regression, and the results were imported into GraphPad Prism8.0.1 software to draw the ROC curve. The software first calculated the threshold of the actual measurement value, and then calculated the true positive cases (TP), false positive cases (FP), true negative cases (TN), and false negative cases (FN) corresponding to the threshold. Specificity (true negative rate) = TN / (TN+FP), sensitivity (true positive rate) = TP / (TP+FN), and the ROC curve can be constructed by 1-specificity and sensitivity. The integral of the ROC curve is AUC. In order to calculate the specificity and sensitivity of a certain indicator, we first calculated the Youden coefficient (Youden index = sensitivity + specificity - 1). The specificity and sensitivity corresponding to the maximum value of the Youden coefficient are the specificity and sensitivity of a certain indicator. The ROC curves of the anxiety state and intestinal flora of each subject in cohort A, the ROC curves of the depression state and intestinal flora of each subject in cohort A, and the ROC curves of the psychological sub-health state and intestinal flora of each subject in cohort A are shown in Tables 9, 10, and 11, and are plotted. Figure 2-Figure 4 , Figure 2 The relative amounts of gut microbiota markers can predict or differentiate between psychologically healthy and anxious individuals in cohort A. Figure 3 The relative amounts of gut microbial markers can predict or differentiate between mental health and depression in cohort A. Figure 4 It was shown that the relative amounts of intestinal bacterial markers could predict or distinguish between mentally healthy and mentally subhealthy individuals in cohort A.

[0088] Table 9: ROC curve parameters of anxiety self-rating scale scores and intestinal flora markers in cohort A

[0089]

[0090] Table 10: ROC curve parameters of self-rating depression scale scores and intestinal flora markers in cohort A

[0091]

[0092]

[0093] Table 11: ROC curve parameters of psychological sub-health status (including anxiety and depression) and intestinal flora markers in cohort A

[0094]

[0095] The ROC curves of anxiety state and intestinal flora markers of cohort A showed that the area under the operating characteristic curve (AUC) values ​​were all over 0.5, and the triple combination (Akkermansia + Lactobacillus helveticus + Bifidobacterium longum) had the strongest predictive ability for psychological anxiety in cohort A (AUC = 0.6389, 95% CI: 0.3800 to 0.8978). The ROC curves of depression state and intestinal flora markers of cohort A showed that the area under the operating characteristic curve (AUC) values ​​were all over 0.5, and Akkermansia had the strongest predictive ability for psychological depression in cohort A (AUC = 0.6409, 95% CI: 0.3997 to 0.8821). The ROC curve of the psychological sub-health status and intestinal flora markers of cohort A showed that the area under the operating characteristic curve (AUC) values ​​were all over 0.5, and Akkermansia and double (Lactobacillus helveticus + Bifidobacterium longum) had the strongest predictive ability for the psychological sub-health status of cohort A (AUC = 0.7593, Akkermansia 95% CI: 0.5556 to 0.9629; double 95% CI: 0.5465 to 0.9720).

[0096] From the above results, it can be seen that the combination of the three bacteria as biomarkers has a good predictive ability for the psychological sub-health state (anxiety and / or depression) of cohort A, and is much higher than that of a single genus or a double genus.

[0097] Example 2

[0098] 1. Questionnaire Collection

[0099] (1) Through on-site recruitment, publicity and questionnaire survey, 24 volunteers were randomly selected as subjects for a comprehensive survey of general conditions and psychological scales, including the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS). A total of 22 SAS and 21 SDS were actually received. The results are shown in Table 12. Among them, three volunteers did not receive either scale and were no longer counted as subjects.

[0100] Table 12: Psychological scale scores and diagnostic results of cohort B

[0101]

[0102] Note: Psychological sub-health, PSH; Psychological health, PH. - means the subjects did not provide the questionnaire results.

[0103] 2. Stool Sample Collection

[0104] Fresh feces of the 24 subjects in step (1) were collected as samples, placed in sterile sampling tubes, placed in dry ice boxes, and quickly transferred to a -80°C refrigerator for freezing within 30 minutes for subsequent testing. The intestinal flora genomic DNA extraction, real-time fluorescence quantitative PCR detection and statistical analysis process are the same as in Example 1 and will not be repeated here.

[0105] The concentrations of the intestinal flora DNA samples and the related absorbance values ​​of this Example 2 are shown in Table 13.

[0106] Table 13: Concentration and related absorbance values ​​of intestinal flora DNA samples of cohort B

[0107]

[0108]

[0109] Among them, the results of real-time fluorescence quantitative PCR detection of total bacteria, Akkermansia, Bifidobacterium longum, and Lactobacillus helveticus in the intestinal flora DNA samples of subjects in cohort B are shown in Tables 14 to 16.

[0110] Table 14: Real-time fluorescence quantitative PCR detection results of total bacteria and Akkermansia in intestinal flora DNA samples of feces of subjects in cohort B

[0111]

[0112] Table 15: Real-time fluorescence quantitative PCR detection results of Lactobacillus helveticus in intestinal flora DNA samples of feces of subjects in cohort B

[0113]

[0114]

[0115] Table 16: Real-time fluorescence quantitative PCR detection results of Bifidobacterium longum in the intestinal flora DNA samples of feces of cohort B subjects

[0116]

[0117]

[0118] The abundance (RQ) distribution of Akkermansia, Lactobacillus helveticus, and Bifidobacterium longum in stool samples of different subjects in cohort B is shown in Figure 2. Figure 5 shown.

[0119] According to the diagnosis results of mental illness in cohort B, ROC analysis was performed in combination with the relative quantitative values ​​of each intestinal bacteria to determine the specific biomarkers for judging the mental health status. SPSS25 software was used to calculate the predictive variable values ​​of single bacteria, double bacteria (Lactobacillus helveticus + Bifidobacterium longum) and triple bacteria (Akkermansia helveticus + Bifidobacterium longum) through binary logistic regression, and the results were imported into GraphPad Prism8.0.1 software to draw the ROC curve. The software first calculated the threshold of the actual measurement value, and then calculated the true positive cases (TP), false positive cases (FP), true negative cases (TN), and false negative cases (FN) corresponding to the threshold. Specificity (true negative rate) = TN / (TN+FP), sensitivity (true positive rate) = TP / (TP+FN), and the ROC curve can be constructed by 1-specificity and sensitivity. The integral of the ROC curve is AUC. In order to calculate the specificity and sensitivity of a certain indicator, we first calculated the Youden coefficient (Youden index = sensitivity + specificity - 1). The specificity and sensitivity corresponding to the maximum value of the Youden coefficient are the specificity and sensitivity of a certain indicator. The ROC curve parameters of the psychological sub-health status and intestinal flora markers of cohort B are shown in Table 17, and the plot is obtained. Figure 6 , showing that the relative amounts of intestinal flora markers can predict or distinguish between mentally healthy and mentally subhealthy individuals in cohort B.

[0120] Table 17: ROC curve parameters of psychological sub-health status (including anxiety and depression) and intestinal flora of subjects in cohort B

[0121]

[0122]

[0123] The ROC curves of psychological sub-health status and intestinal flora markers in cohort B showed that the area under the operating characteristic curve (AUC) values ​​were all over 0.51, and the triple bacteria (Akkermansia + Lactobacillus helveticus + Bifidobacterium longum) had the strongest predictive ability for psychological sub-health in cohort B (AUC = 0.6667, 95% CI: 0.4370 to 0.8963).

[0124] From the above results, it can be seen that the combined three bacterial species as biomarkers have a much higher predictive ability for psychological sub-health status (anxiety and / or depression) in volunteers of cohort B than two single bacterial genera or double bacterial genera.

[0125] In summary, the present invention discovered for the first time the association between Akkermansia, Lactobacillus helveticus and Bifidobacterium longum and mental health status, which was specifically manifested in that the bacterial abundance in the mental sub-health group was lower than that in the mental health group. When these three bacterial genera were used as predictors of mental sub-health, the accuracy rate was high and the prediction method was non-invasive. The present invention provides a new approach for the early detection, early diagnosis and early treatment of mental sub-health.

[0126] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A marker of intestinal flora associated with mental health status, characterized in that: The intestinal flora marker includes at least one of Akkermansia, Bifidobacterium longum or Lactobacillus helveticus.

2. The intestinal flora marker according to claim 1, characterized in that: The intestinal flora markers include any two of Akkermansia, Bifidobacterium longum or Lactobacillus helveticus.

3. The intestinal flora marker according to claim 1, characterized in that: The intestinal flora markers include Akkermansia, Bifidobacterium longum and Lactobacillus helveticus.

4. The intestinal flora marker according to claim 1, 2 or 3, characterized in that: The mental health state is divided into mental health and mental sub-health. The mental sub-health includes one or both of anxiety and depression, while the mental health does not include anxiety or depression.

5. Use of the intestinal flora marker associated with mental health status as claimed in any one of claims 1 to 4 in the preparation of a product for predicting or diagnosing mental sub-health.

6. The use according to claim 5, characterized in that: The product is a reagent containing the primer sequence of the intestinal flora marker or a kit containing the reagent, and the primer sequence meets the requirements of PCR experiments.

7. The use according to claim 6, characterized in that: The reagent predicts or diagnoses the mental health state by measuring the abundance of the intestinal flora marker.

8. The use according to claim 7, characterized in that: The abundance RQ value is calculated by detecting the Ct value of the intestinal flora marker by real-time fluorescence quantitative PCR, RQ=2 -ΔΔCt , ΔΔCt 样本 =ΔCt Mean 样本 -ΔCtMean 样本1 , ΔCt Mean 样本 =Ct Mean 样本 -Ct Mean 内参 , the Ct Mean 样本 is the average Ct value of a single intestinal flora marker in a single sample. 内参 is the average Ct value of all intestinal flora in a single sample, the ΔCtMean 样本1 ΔCt Mean of a single sample 样本 Subtract the ΔCt mean of all samples 样本 The average value of .

9. Use of the intestinal flora marker associated with mental health status as claimed in any one of claims 1 to 4 in the preparation of a drug for treating or improving mental sub-health.

10. Use of the intestinal flora marker associated with mental health status as claimed in any one of claims 1 to 4 in the preparation of health food for improving mental sub-health.

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