Use of a reagent for diagnosing a neurocognitive disorder in the manufacture of a product for diagnosing or aiding in the diagnosis of a neurocognitive disorder

Abstract

The application discloses application of a reagent for diagnosing a neurocognitive disorder in preparation of a product for diagnosing or assisting in diagnosing the neurocognitive disorder, and relates to the technical field of biological medicine. The application finds that there is a difference in intestinal microbial metabolites between a neurocognitive disorder patient and a healthy control, and further screens out the difference intestinal microbial metabolites as a diagnostic marker of the neurocognitive disorder, which can be used for assisting in differential diagnosis of a mild neurocognitive disorder patient. The application has important significance for early diagnosis, early intervention, and in-depth understanding of the pathological mechanism of the neurocognitive disorder. The application takes feces as a sample, has the advantages of easy-to-obtain, convenient collection, large quantity of samples, low price compared with neural images, and short detection cycle compared with blood, cerebrospinal fluid and other samples, and can be used for differential diagnosis by detecting the intestinal microbial metabolite marker. A corresponding diagnostic or auxiliary diagnostic product is developed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biological medicine, in particular to an application of a reagent for diagnosing neurocognitive disorders in preparation of a product for diagnosing or assisting diagnosis of neurocognitive disorders. BACKGROUND

[0002] Cognitive impairment refers to impairment of cognitive function of different degrees caused by various reasons, including impairment of multiple cognitive domains such as learning, memory, calculation, time and space orientation, executive ability, language understanding and expression application. It mainly occurs in neurodegenerative diseases such as Alzheimer's disease (AD) or secondary to cerebrovascular diseases such as vascular dementia. The American Psychiatric Association in the latest Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition collectively refers to these diseases that affect cognitive function as neurocognitive disorders (NCDs). Mild neurocognitive disorders are characterized by a decrease in cognitive function with increasing age, and literature reports that the incidence of mild neurocognitive disorders in the elderly population in China is between 4.94-19.1%, and 60.5% of the population will develop irreversible dementia within 5 years. Therefore, it is of great significance to find a simple, easy and systematic diagnosis element with high sensitivity for early NCDs to timely discover and effectively intervene.

[0003] Gut microbiota can directly or indirectly affect the central nervous system through the gut-brain axis and influence the physiological functions of the nervous system, endocrine system and immune system through the gut-brain axis. When the intestinal flora homeostasis changes, it may stimulate the release of inflammatory mediators such as cytokines and chemokines by intestinal immune cells, or some specific antibodies, and then circulate to the brain to affect the normal function of the central nervous system. In addition, in terms of intestinal flora products and metabolites, the chemical signal molecules such as gamma-aminobutyric acid produced by lactobacillus and bifidobacterium, serotonin synthesized by enterobacter, enterococcus, streptococcus and candida, acetylcholine produced by lactobacillus, dopamine produced by enterobacter and bacillus, and norepinephrine produced by enterobacter, bacillus and yeast, or short-chain fatty acids produced during glycolysis of carbohydrates, can all pass through the intestinal mucosa to directly affect the vagus nerve in the intestine or indirectly circulate to the central nervous system through the blood, and act on the G protein-coupled receptor on the nerve cell membrane to serve as a neurotransmitter of the central nervous system to affect the physiological function of the brain. Among them, short-chain fatty acids also have the functions of regulating the blood-brain barrier, affecting neural development and neurodegenerative diseases, and affecting the proliferation, differentiation and maturation of microglia cells related to AD. In addition to blood circulation, these metabolites can also interact with the brain through the vagus nerve. The vagus nerve is part of the parasympathetic nervous system, composed of 80% sensory afferent fibers and 20% motor efferent fibers, connecting the solitary nucleus of the medulla oblongata and various visceral organs. In the intestinal system part, the vagus nerve is distributed in the muscle layer and mucosa of the intestine, and its endings extend into the villus tip, close to but not through the intestinal epithelial cell layer. The products metabolized by the intestinal flora can pass through the intestinal epithelial cell layer, stimulate the vagus nerve and transmit impulses to the central nervous system to affect the physiological activity of the brain. Gut microbiota can directly or indirectly affect the central nervous system through the gut-brain axis and influence the physiological functions of the nervous system, endocrine system and immune system through the gut-brain axis.

[0004] At present, there is no relevant report on the relationship between intestinal microbial metabolites and patients with neurocognitive disorders, and the role of intestinal microbial metabolites in the development of neurocognitive disorders is not clear. It is of great significance to explore the mechanism of intestinal microbial metabolites in the development of neurocognitive disorders and find intestinal microbial metabolite markers that can be used for early diagnosis of neurocognitive disorders.

[0005] In view of this, the present application is proposed. SUMMARY

[0006] The prior art diagnoses the neurocognitive disorder as follows: (1) the imaging signs of the neurocognitive disorder do not have high sensitivity and specificity, and multiple imaging methods are difficult to popularize due to high price and poor practicability; (2) the results of the biochemical method are inconsistent, and cannot be correctly identified. The purpose of the present application is to provide a neurocognitive disorder marker from the perspective of intestinal microbial metabolites, and to provide a reference for the auxiliary diagnosis and efficacy monitoring of the neurocognitive disorder.

[0007] The present application is implemented as follows:

[0008] In a first aspect, the present application provides a use of a reagent for diagnosing or assisting in diagnosing a neurocognitive disorder in the preparation of a neurocognitive disorder diagnosis or auxiliary diagnosis product, the reagent being used for detecting the level of a marker in a fecal sample, the marker being an intestinal microbial metabolite.

[0009] The present application finds that there are differences in intestinal microbial metabolites between neurocognitive disorder patients and healthy controls by detecting intestinal microbial metabolites, and screens out the differential intestinal microbial metabolites as diagnostic markers of neurocognitive disorder, which can be used for the auxiliary differential diagnosis of mild neurocognitive disorder patients, and is of great significance for early diagnosis, early intervention, and in-depth understanding of the pathological mechanism of neurocognitive disorder. The present application provides an easy-to-operate and economical auxiliary examination method for the diagnosis of neurocognitive disorder.

[0010] The present application uses feces as the sample, which is easy to obtain, convenient to collect, large in quantity, low in price compared with neural images, and short in detection cycle, and the differential diagnosis can be performed by detecting the intestinal microbial metabolite marker, which is suitable for large-scale clinical diagnosis of neurocognitive disorder in the Chinese population.

[0011] In a preferred embodiment of the application, the intestinal microbial metabolite includes at least one of dehydrocholic acid, ɑ-farnesene and rhamnetin.

[0012] The intestinal microbial metabolite provided by the present application has the technical advantages of simple operation, low price, short detection time, high sensitivity and strong specificity in assisting in the diagnosis of neurocognitive disorder. The metabolite can more accurately judge and evaluate the neurocognitive disorder.

[0013] In an alternative embodiment, the intestinal microbial metabolite includes dehydrocholic acid, ɑ-farnesene and rhamnetin.

[0014] The AUC values of the three intestinal microbial metabolites are all higher than 0.7, and the specificity and sensitivity are high, and the application in predicting mild neurocognitive disorders has high accuracy.

[0015] In a preferred embodiment of the application, the neurocognitive disorder is mild neurocognitive disorder.

[0016] The reagent is selected from an intestinal microbial metabolite extraction reagent and / or an intestinal microbial metabolite reaction reagent.

[0017] In an alternative embodiment, the cognitive disorder detection product is selected from a kit, a chip, a magnetic bead or a microwell plate.

[0018] In a preferred embodiment of the application, the application comprises:

[0019] The fecal sample to be tested is loaded into LC-MS for analysis of intestinal microbial metabolites, the intestinal microbial metabolites are compared, the LDA effect value of the intestinal microbial metabolites is calculated by linear discriminant analysis, and the receiver operating characteristic (ROC) curve of the neurocognitive disorder patient group and the healthy control group is drawn.

[0020] In a second aspect, the application also provides a system for diagnosing or assisting in diagnosing neurocognitive disorders, comprising an intestinal microbial metabolite analysis module and a comparison module;

[0021] The intestinal microbial metabolite analysis module is based on LC-MS for analysis of intestinal microbial metabolites of the fecal sample to be tested;

[0022] The comparison module compares the intestinal microbial metabolites, calculates the LDA effect value of the intestinal microbial metabolites by linear discriminant analysis, and draws the receiver operating characteristic (ROC) curve of the neurocognitive disorder patient group and the healthy control group.

[0023] LC-MS is high performance liquid chromatography-mass spectrometry.

[0024] In a preferred embodiment of the application, the intestinal microbial metabolites include at least one of dehydrocholic acid, a-farnesene and rhamnetin.

[0025] In an alternative embodiment, the intestinal microbial metabolites include dehydrocholic acid, a-farnesene and rhamnetin.

[0026] In a preferred embodiment of the application, the neurocognitive disorder is mild neurocognitive disorder.

[0027] In a third aspect, the present application further provides a model for diagnosing or assisting in diagnosing neurocognitive disorders, comprising:

[0028] COV(X) = X*LDA(X)

[0029] COV(Y) = Y*LDA(Y)

[0030] COV(Z) = Z*LDA(Z)

[0031] COV(Cut-off Value): decision value; X: cholic acid peak area, LDA(X): cholic acid LDA value; Y: a-farnesene peak area, LDA(Y): a-farnesene LDA value; Z: rhamnin peak area, LDA(Z): rhamnin LDA value.

[0032] In a fourth aspect, the present application further provides a screening method for intestinal microbial metabolites, comprising the following steps:

[0033] Based on high performance liquid chromatography-mass spectrometry, intestinal microbial metabolites in fecal samples of neurocognitive disorder patients and healthy controls are extracted respectively;

[0034] The intestinal microbial metabolites are compared, and the LDA effect value of the intestinal microbial metabolites is calculated by linear discriminant analysis to screen for differential intestinal microbial metabolites of neurocognitive disorder patients and healthy controls.

[0035] In a preferred embodiment of the application, the method further comprises: performing receiver operating characteristic curve analysis on the differential intestinal microbial metabolites to determine intestinal microbial metabolites that can be used as diagnostic markers for neurocognitive disorders.

[0036] The present application has the following beneficial effects:

[0037] The present application finds that there are differences in intestinal microbial metabolites between neurocognitive disorder patients and healthy controls by detecting intestinal microbial metabolites, and further screens differential intestinal microbial metabolites as diagnostic markers for neurocognitive disorders, which can be used for the auxiliary differential diagnosis of mild neurocognitive disorder patients. The present application is of great significance for early diagnosis, early intervention, and in-depth understanding of the pathological mechanism of neurocognitive disorders. The present application also provides an easy-to-operate and economical auxiliary examination method for the diagnosis of neurocognitive disorders, and corresponding diagnostic or auxiliary diagnostic products can be developed accordingly.

[0038] In addition, the present application takes stool as a sample, has the advantages of easy-to-obtain sample, convenient collection, large sample quantity, low price compared with neural image, and short detection cycle, and can be used for differential diagnosis by detecting intestinal microbial metabolite markers, and is suitable for large-scale clinical diagnosis of neurocognitive disorders in Chinese population. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0040] Figure 1 The figure is a LEfse result diagram of intestinal microbial metabolites of neurocognitive disorder patients and healthy control group of the present application. OUT 801 is dehydrocholic acid, OUT 1343 is ɑ-farnesene, and OUT 2527 is Rhamnetin.

[0041] Figure 2 The figure is a ROC curve diagram of dehydrocholic acid, ɑ-farnesene and Rhamnetin, three intestinal microbial metabolites, in the diagnosis of neurocognitive disorders.

[0042] Figure 3 The figure is a peak area comparison diagram of dehydrocholic acid, ɑ-farnesene and Rhamnetin, three intestinal microbial metabolites, in the diagnosis of neurocognitive disorders. DETAILED DESCRIPTION

[0043] Reference will now be made in detail to the embodiments of the present application, one or more examples of which are set forth below. Each example is provided as an explanation and not a limitation on the present application. Indeed, it will be apparent to one of ordinary skill in the art that numerous modifications and variations of the present application are possible in light of the above teachings. For example, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment.

[0044] Unless otherwise specified, the practice of this invention will employ conventional techniques of cell biology, molecular biology (including recombinant technologies), microbiology, biochemistry, and immunology, which are within the capabilities of those skilled in the art. This technique is well explained in the literature, such as *Molecular Cloning: A Laboratory Manual*, 2nd edition (Sambrook et al., 1989); *Oligonucleotide Synthesis* (edited by M.J. Gait, 1984); *Animal Cell Culture* (edited by R.R. Freshney, 1987); *Methods in Enzymology* (Academic Press, Inc.); *Handbook of Experimental Immunology* (edited by D.M. Weir and C.C. Blackwell); *Gene Transfer Vectors for Mammalian Cells* (edited by J.M. Miller and M.P. Calos, 1987); *Current Protocols in Molecular Biology* (edited by F.M. Mausubel et al., 1987); and *PCR: The Polymerase Chain Reaction*. The references cited in the references are: "Reaction" (Mullis et al., ed., 1994); and "Current Protocols in Immunology" (JEColigan et al., ed., 1991), each of which is explicitly incorporated herein by reference.

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0046] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0047] The following experiment aims to identify gut microbial metabolites as diagnostic markers for neurocognitive impairment, which can be used in the differential diagnosis of mild neurocognitive impairment. This experiment was approved by the Ethics Committee of the University of Macau. All participants voluntarily participated and were verbally informed of the purpose of the experiment and signed informed consent forms.

[0048] Study Participants: The study included 11 patients with mild neurocognitive impairment and 8 healthy controls with normal cognition, collected from various elderly integrated service centers in the Macao SAR. Detailed sociodemographic information, including gender and age, was recorded for each participant. Exclusion Criteria: Individuals with comorbid respiratory diseases (bronchial asthma, COPD), benign or malignant tumors, mental disorders, or severe organ failure; those unable to communicate verbally or in writing and unable to complete the questionnaire even with assistance; and those taking antibiotics, antibacterial drugs, or immunosuppressants. Participants in each group were matched for age, gender, and education level.

[0049] Sample collection: Each group of subjects provided their first morning stool sample, which was frozen and stored at -80°C for analysis of gut microbial metabolites.

[0050] Example 1

[0051] Screening gut microbial metabolites as diagnostic biomarkers for neurocognitive impairment can be used for the differential diagnosis of neurocognitive impairment. The specific steps are as follows:

[0052] (1) Metabolite extraction: Take 100 mg of fecal sample ground with liquid nitrogen, place it in an EP tube, and add 500 μL of 80% methanol aqueous solution.

[0053] (2) Vortex oscillation, let stand in ice bath for 5 min, centrifuge at 15000g and 4℃ for 20 min.

[0054] (3) Take a certain amount of supernatant and dilute it with mass spectrometry grade water until the methanol content is 53%.

[0055] (4) Centrifuge at 15000g and 4℃ for 20min, collect the supernatant, and analyze it by LC-MS.

[0056] (5) QC sample: Take an equal volume of sample from each experimental sample and mix it to obtain the QC sample; Blank sample: 53% methanol aqueous solution replaces the experimental sample, and the pretreatment process is the same as that of the experimental sample.

[0057] Chromatographic conditions: Column: Hypesil Gold column (C18), column temperature: 40℃, flow rate: 0.2 mL / min. Positive mode: Mobile phase A: 0.1% formic acid, mobile phase B: methanol; Negative mode: Mobile phase A: 5 mM ammonium acetate (pH 9.0), mobile phase B: methanol.

[0058] Chromatographic gradient elution program:

[0059] Time A％ B％ 0 98 2 1.5 98 2 12 0 100 14 0 100 14.1 98 2 17.0 98 2

[0060] Mass spectrometry conditions: Scan range selected as m / z 100-1500; ESI source settings as follows: spray voltage: 3.2 kV; Sheath gas flow rate: 40 alb; Aux gas flow rate: 10 alb; capillary temperature: 320℃. Polarity: positive; negative; MS / MS secondary scans were data-dependent scans.

[0061] Data preprocessing and metabolite identification: The raw data files were imported into CD 3.1 search software for processing. Each metabolite underwent simple screening based on parameters such as retention time and mass-to-charge ratio. Then, a retention time deviation of 0.2 min and a mass deviation of 5 ppm were set to align peaks from different samples for more accurate identification. Subsequently, peak extraction was performed using parameters such as a mass deviation of 5 ppm, a signal intensity deviation of 30%, a signal-to-noise ratio of 3, a minimum signal intensity, and added ions. Peak areas were also quantified. Target ions were then integrated, and molecular formulas were predicted using molecular ion peaks and fragment ions, compared with the mzCloud (https: / / www.mzcloud.org / ), mzVault, and Masslist databases. Background ions were removed using blank samples, and the raw quantitative results were standardized. Finally, the metabolite identification and relative quantitative results were obtained.

[0062] Data statistical analysis:

[0063] The identified metabolites were annotated using the KEGG database (https: / / www.genome.jp / kegg / pathway.html), the HMDB database (https: / / hmdb.ca / metabolites), and the LIPID Maps database (http: / / www.lipidmaps.org / ). Data analysis was performed using SPSS 22.0 and Graph Pad Prism 9.0 software, and plotting was done using R 3.6.0 software. Differences in the types of gut microbial metabolites between samples were assessed using the LDA effect value calculated via LEfSe. A t-test was used to examine the effects of different levels of gut microbial metabolites between the two groups, estimating the magnitude of each metabolite's influence on the difference. A p-value < 0.05 was considered statistically significant.

[0064] The results showed that, compared with healthy individuals, patients with neurocognitive impairment had significantly increased expression of three gut microbial metabolites: dehydrocholic acid, α-farnesene, and rhamnetin (P < 0.05).

[0065] Based on the LEfSe analysis results ( Figure 1 Based on the results of the t-test, it was found that three intestinal microbial metabolites, namely dehydrocholic acid, α-farnesene, and rhamnetin, are the main pathogenic bacteria genera of mild neurocognitive impairment and can be used as biomarkers associated with mild neurocognitive impairment.

[0066] ROC curves of gut microbial metabolites associated with mild neurocognitive impairment are shown below. Figure 2 As shown, the AUC values ​​of three gut microbial metabolites—dehydrocholic acid, α-farnesene, and rhamnetin—are all higher than 0.7, indicating high specificity and sensitivity, and thus high accuracy in predicting mild neurocognitive impairment.

[0067] Experimental Example 1

[0068] Identification of neurocognitive disorders

[0069] The study used three intestinal microbial metabolites: dehydrocholic acid, α-farnesene, and rhamnetin.

[0070] (1) Collect feces from the subjects, extract metabolites after pretreatment, and then detect the peak areas of the three intestinal microbial metabolites by LC-MS.

[0071] (2) Calculate COV(X), COV(Y), and COV(Z) using the model. When the COV(X) value exceeds 7.89*10 6 Or the COV(Y) value exceeds 1.58*10 8 Or the COV(Z) value exceeds 3.93*10 6 This allows the examinee to be diagnosed with mild neurocognitive impairment.

[0072] Models for diagnosing or assisting in the diagnosis of neurocognitive disorders, including:

[0073] COV(X) = X * LDA(X)

[0074] COV(Y) = Y * LDA(Y)

[0075] COV(Z) = Z * LDA(Z)

[0076] COV (Cut-off Value): Determination value; X: Peak area of ​​procholic acid, LDA(X): LDA value of procholic acid; Y: Peak area of ​​α-farnesene, LDA(Y): LDA value of α-farnesene; Z: Peak area of ​​rhamnine, LDA(Z): LDA value of rhamnine.

[0077] A schematic diagram comparing the peak areas of three gut microbial metabolites—dehydrocholic acid, α-farnesene, and rhamnetin—in the diagnosis of neurocognitive impairment is shown below. Figure 3 As shown, the results are as follows:

[0078] The peak area of ​​procholic acid multiplied by the average value is 2.49 * 10. 6 LDA(X) = 3.17; the average peak area of ​​α-farnesene (Y) is 5.24 × 10⁻⁶. 7 LDA(Y) = 2.02; the average area Z of the rhamnite peak is 1.51 * 10⁻⁶. 6 LDA(Z) = 2.60.

[0079] When the COV(X) value exceeds 7.89*10 6 Or the COV(Y) value exceeds 1.58*10 8 Or the COV(Z) value exceeds 3.93*10 6 This allows the examinee to be diagnosed with mild neurocognitive impairment.

[0080] Based on this, an individual disease risk assessment kit can be constructed for evaluating the risk of neurocognitive impairment. The kit consists of a gut microbial metabolite extraction reagent and a gut microbial metabolite reaction reagent. It can also be used to construct a detection kit for prognostic monitoring of neurocognitive impairment.

[0081] In summary, the screened intestinal microbial metabolites dehydrocholic acid, α-farnesene, and rhamnetin can serve as diagnostic biomarkers for neurocognitive impairment and can be used for the differential diagnosis of mild neurocognitive impairment. The diagnostic or auxiliary diagnostic techniques provided by this invention have the advantages of simple operation, low cost, short detection time, and high sensitivity and specificity, and have significant clinical value.

[0082] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. The application of reagents for the diagnosis or auxiliary diagnosis of neurocognitive disorders in the preparation of products for the diagnosis or auxiliary diagnosis of neurocognitive disorders, characterized in that, The reagent is used to detect the level of a biomarker in a fecal sample, the biomarker being a gut microbial metabolite; the gut microbial metabolite includes at least one of procholic acid, α-farnesene, and rhamnine.

2. The application according to claim 1, characterized in that, The intestinal microbial metabolites include procholic acid, α-farnesene, and rhamnosine.

3. The application according to claim 1, characterized in that, The neurocognitive impairment described is mild.

4. The application according to any one of claims 1-3, characterized in that, The reagents are selected from intestinal microbial metabolite extraction reagents and / or intestinal microbial metabolite reaction reagents.

5. The application according to claim 4, characterized in that, The diagnostic or auxiliary diagnostic products for neurocognitive disorders are selected from reagent kits, chips, magnetic beads, or microplates.

6. The application according to any one of claims 1-3, characterized in that, The applications include: The fecal samples were loaded for analysis of gut microbial metabolites by LC-MS. The gut microbial metabolites were compared, and the LDA effect value of gut microbial metabolites was calculated by linear discriminant analysis. Receiver operating characteristic curves were plotted for the neurocognitive impairment patient group and the healthy control group.

7. A system for diagnosing or assisting in the diagnosis of neurocognitive disorders, characterized in that, Includes a gut microbial metabolite analysis module and a comparison module; The gut microbial metabolite analysis module analyzes gut microbial metabolites in fecal samples based on LC-MS. The comparison module compares the gut microbial metabolites, calculates the LDA effect value of the gut microbial metabolites using linear discriminant analysis, and plots the receiver operating characteristic curves of the neurocognitive impairment patient group and the healthy control group. The gut microbial metabolites include at least one of procholic acid, α-farnesene, and rhamnine.

8. The system according to claim 7, characterized in that, The intestinal microbial metabolites include procholic acid, α-farnesene, and rhamnosine.

9. The system according to claim 7, characterized in that, The neurocognitive impairment described is mild.

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