Application of gut microbiota and metabolites and prediction system of high altitude heart disease

Abstract

The application discloses application of intestinal flora and metabolites and a prediction system for high-altitude heart disease, relates to the cross technical field of microorganisms and computer science. Blood, serum or fecal metabolites are selected from at least one of L-aspartic acid, betaine and ketoglutaric acid. The intestinal flora is selected from at least one of Streptococcus rubneri and Veillonella rogosae. The application mines the characteristics of intestinal flora and related metabolites of people susceptible to high-altitude heart disease after moving to the plateau through multi-omics sequencing and in-vivo and in-vitro experiment verification, reveals the important prediction role of key intestinal flora and related metabolites in high-altitude heart disease, and provides a new train of thought for prevention and treatment of the disease.

Description

TECHNICAL FIELD

[0001] The present application relates to the cross technical field of microorganisms and computer science, in particular, to the application of intestinal flora and metabolites and a prediction system for high altitude heart disease. BACKGROUND

[0002] High altitude heart disease is a chronic mountain sickness characterized by pulmonary hypertension and right heart hypertrophy, which is usually the result of maladaptation and dysfunction of the cardiovascular system at high altitude. In addition to pulmonary hypertension, the myocardium is also susceptible to hypobaric hypoxia, the main environmental stress at high altitude that all high altitude people inevitably encounter, which also promotes the development of altitude-related cardiac hypertrophy and even congestive heart failure. Mechanistically, a complex cellular response is initiated to coordinate the hypoxic adaptation of the heart when subjected to environmental hypoxia, mainly through the hypoxia-inducible factor signal. Similarly, the induced hypoxia-inducible factor signal in the intestine has been shown to be involved in the intestinal symbiotic balance and the production of microbial metabolites, both of which are important for protecting myocardial cells from hypoxic and / or ischemic injury.

[0003] However, recent observations and rodent studies have shown that once the intestinal microbiota changes and enters a state of dysbiosis, accompanied by significant changes in certain microbial metabolites, it can lead to myocardial injury and myocardial perfusion deficiency, making it prone to ischemic heart disease and hypobaric hypoxia-induced cardiac hypertrophy.

[0004] Currently, there is no human study describing the microbiome and metabolome characteristics of high altitude heart disease in high altitude migrants, especially in the early stages before clinical onset. Research focusing on the prevention and treatment of high altitude heart disease by affecting the abundance and structure of intestinal flora is limited to rodent level and cannot be applied to high altitude migrants.

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

[0006] The purpose of the present application is to provide an application of intestinal flora and metabolites and a prediction system for high altitude heart disease to solve the above technical problems.

[0007] The present application is implemented as follows:

[0008] In a first aspect, the present application provides an application of a reagent for detecting blood, serum or fecal metabolite levels in the preparation of a product for predicting and / or diagnosing high altitude heart disease, the blood, serum or fecal metabolite being selected from at least one of L-aspartate, betaine and ketoglutarate.

[0009] The application mines the characteristics of intestinal flora and related metabolites of people susceptible to high-altitude heart disease after migrating to the plateau through multi-omics sequencing and in-vivo and in-vitro experimental verification, reveals the important predictive role of key intestinal flora and related metabolites in high-altitude heart disease, and provides a new idea for the prevention and treatment of the disease.

[0010] The in-vivo and in-vitro experimental results show that there are differences in the occurrence of heart abnormalities in people migrating to the plateau, the abundance of intestinal flora Streptococcus rubneri and Veillonella rogosae in people with high-altitude heart abnormalities is reduced, and the concentration of alpha-ketoglutarate (alpha-KG), betaine and L-aspartate (L-Asp) in blood, serum or fecal metabolites in people with high-altitude heart abnormalities is reduced. Further research confirms that the abundance of intestinal flora Streptococcus rubneri and Veillonella rogosae in people with high-altitude heart abnormalities is significantly positively correlated with the concentration of alpha-ketoglutarate (alpha-KG), betaine and L-aspartate (L-Asp). The ROC analysis results show that the two kinds of differential intestinal flora and the three kinds of differential metabolites have good predictive ability for high-altitude heart disease, and the predictive ability can be further improved by combining the two kinds of differential intestinal flora and the three kinds of differential metabolites.

[0011] Therefore, detecting the level of differential metabolites in blood, serum or feces can better predict and / or diagnose high-altitude heart disease.

[0012] In an alternative embodiment, the skilled person can predict high-altitude heart disease by detecting the level of L-aspartate in a blood, serum or fecal sample.

[0013] In an alternative embodiment, the skilled person can predict high-altitude heart disease by detecting the level of betaine in a blood, serum or fecal sample.

[0014] In an alternative embodiment, the skilled person can predict high-altitude heart disease by detecting the level of betaine and ketoglutarate in a blood, serum or fecal sample. In an alternative embodiment, the skilled person can predict high-altitude heart disease by detecting the level of L-aspartate, betaine and ketoglutarate in a blood, serum or fecal sample.

[0015] In a preferred embodiment of the application, the product is a reagent, a kit, a chip, a magnetic bead or a microwell plate.

[0016] In a preferred embodiment of the application, the reagent for detecting the level of blood, serum or fecal metabolites is selected from at least one of the following: ultra-high performance liquid chromatography triple quadrupole tandem mass spectrometry reagent, high performance liquid chromatography reagent, acid-base titration reagent, magnetic microparticle chemiluminescence reagent, thin layer scanning quantitative reagent, perchloric acid non-aqueous titration reagent, spectrophotometric reagent, gas chromatography reagent, ion chromatography reagent and electrochemical chiral sensor reagent. In addition, other reagents capable of detecting the levels of L-aspartate, betaine and ketoglutarate can also be used, including but not limited to chromatography, spectroscopy and electrochemistry.

[0017] In a second aspect, the application also provides a prediction system for high altitude heart disease, comprising: a detection module and a comparison module;

[0018] The detection module is used to analyze the content of metabolites in a separated blood, serum or fecal sample by an analyzer or a kit, to obtain the content of metabolites in the sample; the metabolites are selected from at least one of L-aspartate, betaine and ketoglutarate;

[0019] The comparison module is used to compare the obtained content of metabolites in the sample with a set value.

[0020] The analyzer includes but is not limited to: ultra-high performance liquid chromatography triple quadrupole tandem mass spectrometer, high performance liquid chromatograph, spectrophotometer, gas chromatograph, thin layer scanner, ion chromatograph and electrochemical chiral sensor.

[0021] The kit includes but is not limited to magnetic microparticle chemiluminescence reagent kit and electrochemical chiral reagent kit.

[0022] In an alternative embodiment, the set value is the content of metabolites of the same sample type of normal healthy people.

[0023] If the content of metabolites (at least one of the three different metabolites mentioned above) of the sample to be tested is lower than that of the same sample type of normal healthy people, it is predicted that the sample has a higher risk of high altitude heart disease.

[0024] In a third aspect, the application also provides a use of a reagent for detecting the abundance of intestinal flora in the preparation of a product for predicting and / or diagnosing high altitude heart disease, the intestinal flora being selected from at least one of Streptococcus lubrigensis and Amanita.

[0025] The abundance of Streptococcus lubrigensis and Amanita in the population with high altitude heart abnormalities is significantly lower than that of the two bacteria in the normal healthy population. It is proved by ROC curve that the abundance of Streptococcus lubrigensis and Amanita in the intestinal flora has good prediction ability for high altitude heart abnormalities.

[0026] In a preferred embodiment of the application, the product is a reagent, a kit, a chip, a magnetic bead or a microplate.

[0027] In a preferred embodiment of the application, the reagent for detecting the abundance of intestinal flora is at least one selected from the group consisting of a metagenomic sequencing reagent, a 16S rRNA amplicon sequencing reagent, a droplet digital PCR detection reagent, a qPCR quantitative detection reagent, a polymerase chain reaction reagent, a reverse transcription-polymerase chain reaction reagent, a nested PCR reagent and a nucleic acid hybridization reagent.

[0028] In a preferred embodiment of the application, the reagent for detecting the abundance of intestinal flora is a primer and / or a probe for detecting intestinal flora. The primer includes, but is not limited to, a primer for detecting 16S rRNA of Streptococcus rubneri and Veillonella rogosae. In other embodiments, the reagent includes, but is not limited to, a primer for detecting internal transcribed spacer (ITS).

[0029] In a fourth aspect, the application further provides a system for predicting high altitude heart disease, comprising: a detection module and a comparison module;

[0030] The detection module is used for sequencing and / or quantifying the nucleic acid sample of the isolated intestinal flora to obtain the content of intestinal flora in the sample; the intestinal flora is at least one selected from the group consisting of Streptococcus rubneri and Veillonella rogosae;

[0031] The comparison module is used for comparing the obtained content of intestinal flora in the sample with a set value;

[0032] In an alternative embodiment, the set value is the content of intestinal flora of the same sample type of a normal healthy mammal. If the content of intestinal flora in the sample to be tested is lower than that of the same sample type of a normal healthy mammal, it is predicted that the sample to be tested has a higher risk of high altitude heart disease.

[0033] In a fifth aspect, the application further provides a use of a reagent for detecting the level of blood, serum or fecal metabolite and a reagent for detecting the abundance of intestinal flora in the preparation of a product for predicting and / or diagnosing high altitude heart disease, the blood, serum or fecal metabolite is at least one selected from the group consisting of L-aspartate, betaine and ketoglutarate; the intestinal flora is at least one selected from the group consisting of Streptococcus rubneri and Veillonella rogosae.

[0034] Studies have shown that the three differential metabolites and two differential intestinal flora have good predictive ability for high altitude heart disease, and the ROC analysis results show that the AUC reaches 0.7857.

[0035] In an alternative embodiment, the product is a reagent, a kit, a chip, a magnetic bead or a microplate.

[0036] In an alternative embodiment, the reagent for detecting the abundance of intestinal flora is selected from at least one of the following: a metagenomic sequencing reagent, a 16S rRNA amplicon sequencing reagent, a microdroplet digital PCR detection reagent, a qPCR quantitative detection reagent, a polymerase chain reaction reagent, a reverse transcription-polymerase chain reaction reagent, a nested PCR reagent, or a nucleic acid hybridization reagent;

[0037] In an alternative embodiment, the reagent for detecting the level of blood, serum or fecal metabolites is selected from at least one of the following: an ultra-high performance liquid chromatography triple quadrupole tandem mass spectrometry detection reagent, a high performance liquid chromatography detection reagent, an acid-base titration reagent, a magnetic microparticle chemiluminescence detection reagent, a thin-layer scanning quantitative reagent, a perchloric acid non-aqueous titration reagent, a spectrophotometric detection reagent, a gas chromatography reagent, an ion chromatography reagent, and an electrochemical chiral sensor detection reagent.

[0038] In a sixth aspect, the present application also provides a prediction system for high altitude heart disease, comprising: a detection module and a comparison module;

[0039] The detection module has the following functions:

[0040] (1) sequencing and / or quantifying the isolated intestinal nucleic acid sample to obtain the content of intestinal flora in the sample; the intestinal flora is selected from at least one of Streptococcus rubneri and Veillonella rogosae;

[0041] (2) analyzing the content of metabolites in the isolated blood, serum or fecal sample using an analyzer to obtain the content of metabolites in the sample; the metabolites are selected from at least one of L-aspartic acid, betaine and ketoglutaric acid;

[0042] The comparison module has the following functions:

[0043] (1) for comparing the obtained content of metabolites in the sample with a set value;

[0044] (2) for comparing the obtained content of intestinal flora in the sample with a set value.

[0045] The present application has the following beneficial effects:

[0046] The present application, through multi-omics sequencing and in vivo and in vitro experimental verification, has mined the characteristics of intestinal flora and related metabolites of people susceptible to high altitude heart disease after moving to high altitude, and has revealed the important prediction role of key intestinal flora and related metabolites in high altitude heart disease, providing a new idea for the prevention and treatment of the disease.

[0047] The present application shows that there are differences in the occurrence of heart abnormalities in plateau immigrants through in-vivo and in-vitro experimental results, the abundance of intestinal flora Streptococcus rubneri and Veillonella rogosae in the plateau heart abnormal population is reduced, and the concentration of alpha-ketoglutarate (alpha-KG), betaine and L-aspartate (L-Asp) in the blood, serum or fecal metabolites of the plateau heart abnormal population is reduced.

[0048] The study confirms that the abundance of intestinal flora Streptococcus rubneri and Veillonella rogosae in the plateau heart abnormal population is significantly positively correlated with the concentration of alpha-ketoglutarate (alpha-KG), betaine and L-aspartate (L-Asp). The ROC analysis results show that the two kinds of different intestinal flora and three kinds of different metabolites have good prediction ability for plateau heart disease, especially when the two kinds of different intestinal flora and three kinds of different metabolites are combined, which can further improve the prediction ability. Therefore, by detecting the levels of different metabolites in blood, serum or feces and detecting the levels of intestinal flora, the plateau heart disease can be better predicted and / or diagnosed. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. 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.

[0050] Figure 1 The figure is the analysis result of the differences in the expression profile of myocardial enzymes, the composition of intestinal flora and the concentration of metabolites between the plain control group and the plateau immigrants;

[0051] Figure 2 The figure is the relationship between the composition and performance of intestinal flora and the susceptibility of high-altitude heart abnormalities;

[0052] Figure 3 The figure is the experimental result of the characteristics of serum and fecal metabolome related to individuals with heart abnormalities;

[0053] Figure 4 The figure is the experimental result of the influence of intestinal flora on the host serum and fecal metabolites of plateau immigrants with heart abnormalities;

[0054] Figure 5 The figure is the comparison result of the abundance of 10 kinds of microorganisms in the verification cohort. DETAILED DESCRIPTION

[0055] Reference will now be made in detail to embodiments of the application, one or more examples of which are described hereinbelow. Each example is provided by way of explanation of the application and is not meant as a restriction of the application. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope or spirit of the application. For instance, features illustrated or described as part of one embodiment, can be used with another embodiment to yield a still further embodiment.

[0056] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below. If specific conditions are not indicated in the embodiments, the conventional conditions or the conditions suggested by the manufacturers are adopted. If the manufacturers of the reagents or instruments are not indicated, the conventional products that can be purchased in the market are adopted.

[0057] The features and performances of the present application are further described in detail below in combination with the embodiments.

[0058] In order to solve the problem that the current classification method based on intestinal flora and serum metabolites cannot effectively prevent and treat susceptible people, the present application provides a prediction model method for dividing susceptible people of high-altitude heart disease based on intestinal flora and serum metabolites.

[0059] Multi-omic analysis was performed on 230 graduates from the same university (163 migrated to the Tibetan Plateau and 67 lived in the Chengdu plain as controls), and 206 differential metabolites (82 from serum and 124 from feces) and 369 differential species were found between the migrants and the controls. Among them, 27 differential microorganisms and 4 differential metabolites were related to impaired heart health in migrants. In addition, in the population with abnormal heart health, the abundance of Streptococcus rubneri and Veillonella rogosae was related to the levels of L-Aspartic acid, betaine and Ketoglutaric acid in serum. The abundance of these species and metabolites was verified in an independent cohort, and the combination of the two had good discriminant effect on the abnormal heart health of the migrants (AUC = 0.7857).

[0060] Example 1

[0061] This example provides the population screening criteria, sampling method, and macro-genome sequencing and analysis of fecal samples.

[0062] 1. Population description and sample collection

[0063] Two different groups were recruited in this study: the plain group included 105 adult males from Chengdu plain in Sichuan province; the high-altitude group included 641 adult males from Tibet who lived at an altitude of 3500-4500 meters. All participants filled in a comprehensive basic information questionnaire, which included detailed information such as age, education level, altitude of the place of residence, length of residence in Tibet (only for plateau immigrants), body mass index, smoking and drinking history, antibiotic use history, and previous medical history. These information were collected to facilitate subsequent population screening.

[0064] To ensure that the discovered heart problems and changes in gut microbiota are mainly affected by environmental factors, precise inclusion and exclusion criteria were implemented in this study. Inclusion criteria included selecting participants aged 20-30 years old, without a history of heart disease or family genetic history. Exclusion criteria included taking antibiotics, undergoing weight loss surgery or intestinal resection (except appendectomy) within the past 3 months, having inflammatory bowel disease or autoimmune disease, being affected by infectious diseases (such as hepatitis B or C or human immunodeficiency virus), having a history of organ transplantation or undergoing immunosuppressive therapy, drug or alcohol abuse.

[0065] To ensure consistency in the source of the population, plateau immigrants were required to live in a geographical area roughly the same as the plain population before migrating to the plateau. According to the above criteria, 67 people were selected into the plain group and 163 people were selected into the high-altitude group, all of whom graduated from Chengdu Medical College. These two groups of patients underwent detailed examination at the Army 954 Hospital, including electrocardiogram, echocardiogram, and frequency domain cardiogram. Based on the results of electrocardiogram, echocardiogram, and frequency domain cardiogram, individuals in the plateau group were divided into two subgroups according to age, altitude, time of migration to the plateau, and body mass index, including a normal heart health group (n=42) and an abnormal heart health group (n=35). The purpose was to explore the characteristics of gut microbiota groups and metabolic groups related to the heart health of immigrants.

[0066] To further verify the discovered features, the researchers recruited 20 volunteers with myocardial ischemia to form an abnormal group (Abnormal), and selected 21 volunteers to form a normal group (Normal) by matching age, altitude, time of migration to the plateau, and body mass index.

[0067] Both groups of volunteers used vacuumized blood collection tubes (Becton Dickinson Medical Devices (Shanghai) Co., Ltd.) to collect blood samples. The samples were left to stand for 30 minutes, and then centrifuged at a speed of 5000 rpm / min for 15 minutes at a temperature of 4°C. 0.5 milliliters of serum was extracted from each sample for biochemical testing, including creatine kinase isozyme (CKMB), hydroxybutyrate dehydrogenase (HBDH), lactate dehydrogenase (LDH), and cardiac troponin I (CTNI) parameters. These tests used Roche c311 biochemical analyzers (Shenzhen Roche Biotechnology Co., Ltd.). The remaining samples were stored in an environment at minus 80 degrees Celsius for subsequent serum metabolomics analysis. Participants' fecal samples were collected by fecal sampling tubes (Shenzhen Maideke Biomedical Technology Co., Ltd.), and after sampling, they were also stored at a temperature of minus 80°C. These samples were used for metagenomic and metabolomics analysis.

[0068] 2. Metagenomic sequencing and analysis

[0069] According to the manufacturer's protocol, microbial DNA was extracted from fecal samples using the Fecal DNA Kit. Subsequently, metagenomic shotgun sequencing libraries were constructed and sequenced at Shanghai Ling'en Biotechnology Co., Ltd.

[0070] Alpha diversity was evaluated using Shannon and Simpson indices. Bray-Curtis distance and Euclidean distance were used to evaluate the changes in species abundance between the two groups.

[0071] Similarity analysis (ANOSIM) was used to determine the significance index (P), with a critical value of P < 0.05 indicating significant differences in species abundance between groups. At the kingdom level, Wilcoxon rank-sum tests were used to demonstrate differences in Archaea, Bacteria, Eukarya, and Virus abundance between the two groups. The top ten phyla were obtained by calculating the relative abundance of species in the two groups at the phylum level. Linear discriminant analysis effect size (Lefse) was used to determine differences in microbial feature abundance. Using STAMP 2.1.3, differential species were screened using partial least squares discriminant analysis (pls-da) with a variable importance in projection (VIP) score > 1 and a P < 0.05 Stamp analysis.

[0072] In addition, ten-fold cross-validation was performed using random forest classification to evaluate the importance of species in grouping. The significance of importance scores was determined by 1,000 permutation analyses. Based on the differences in abundance between the two groups, the screened species were divided into a heart normal enrichment group and a heart abnormal enrichment group. Receiver operating characteristic curve (ROC) analysis was used to evaluate the predictive effect on disease. Wilcoxon rank-sum tests were used to detect differences between groups. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

[0073] Results of the experiment of the plain group and the high altitude group are referenced Figure 1 Figure 1 A is a workflow diagram revealing the metabolic and microbiota features associated with high altitude cardiac abnormalities; B is a difference result diagram of myocardial enzyme (CKMB, CTNI, LDH and HBDH) expression levels of the ordinary control group (i.e. the plain group PL) and the high altitude group, C and D are principal component analysis (PCA) based on serum metabolome (C) and fecal metabolome (D) showing the classification between the plain group (PL) and the high altitude group (HA). E and F are respectively the volcano plot of serum metabolites (E) and fecal metabolites (F) of the PL group and the HA group. The metabolites showing significant changes (P<0.05) are represented in blue (log2(fold change)<0) and in red (log2(fold change)>0). G is a gut microbiota system diagram. Each circle represents a taxonomic rank. The points enriched in the PL group and the HA group (P<0.05 and |LDA score|>2) are represented in blue and red respectively. H is a histogram showing specific gut microbiota with significant differences. Blue and red bar charts represent the gut microbiota enriched in the PL group and the HA group respectively.

[0074] Figure 2 ​The relationship between gut microbiota composition and manifestation and high altitude cardiac abnormal susceptibility is shown. 35 volunteers with myocardial ischemia in the volunteers who migrated to high altitude form an abnormal group (HH-A) and 42 volunteers with healthy hearts form a normal group (HH-N). A is a gut microbiota system at the kingdom level based on metagenomic sequencing, of which 86.38% is bacteria and 6.89% is viruses. B is the gut microbiota composition of the normal group (HH-N) and the abnormal group (HH-A) at the door level. C is the screening of species with different abundance related to high altitude cardiac abnormal susceptibility. P<0.05 by Wilcoxon rank sum test; species with VIP score>1 by PLS-DA test are screened out. Green and yellow nodes are HH-N enriched species and HH-A enriched species, respectively. D is the importance of the screened species in the HH-N and HH-A groups predicted by random forest (RF). The greater the mean square error (MSE) value, the more important the species is as a driving factor for predicting high altitude immigrant cardiac health damage. Significance is evaluated by 1000 random arrangements, as follows: *, p<0.05; **, p<0.01; ***, p<0.001. Green is the HH-N enriched species; yellow is the HH-A enriched species. E is the classification effect (classified according to the enriched species of each group) of the HH-N group and the HH-A group. The green line and the yellow line represent the HH-N enriched species and the HH-A enriched species, respectively. The area under the curve (AUC) is used to evaluate the performance of each classification. F is the KEGG pathway enriched by the gut microbiota of different abundance in the HH-N group and the HH-A group. Blue line, P<0.05; red line, P<0.01.

[0075] Example 2

[0076] This example is directed to the serum / fecal samples of 35 volunteers with myocardial ischemia in the volunteers who migrated to high altitude forming an abnormal group (HH-A) and 42 volunteers with healthy hearts forming a normal group (HH-N) for metabolome sequencing and analysis.

[0077] 1. Serum / fecal metabolome sequencing and analysis

[0078] Serum samples were mixed with 4 volumes of ice-cold acetonitrile, including 0.001 mg / mL of 4-chloro-DL-phenylalanine as an internal standard, and then incubated on ice for 15 min to eliminate proteins. The resulting mixture was then centrifuged at 20000 g for 10 min at 4°C, and the supernatant was collected into a new microcentrifuge tube. Subsequently, after a second round of centrifugation under the same conditions, the sample was transferred to a sample vial, ready for metabolomics analysis. About 60 mg of fecal sample was mixed with 600 μL of 80% ice methanol (including 0.001 mg / mL of 4-chloro-DL-phenylalanine as an internal standard) and zirconium oxide crushing beads. The sample was then crushed by a 60 Hz vibration crusher. Subsequently, the sample was ultrasonicated in an ice bath for 10 min and left to stand at -20°C for 30 min. The supernatant was collected by centrifugation at 4°C 20000 g for 10 min and mixed with three volumes of distilled water. The sample was then ultrasonicated for 3 min to ensure uniform mixing and was placed in an environment at -20°C for 2 h. Subsequently, the supernatant obtained by centrifugation was transferred to a sample vial for metabolomics analysis.

[0079] The metabolome was analyzed using a precision targeted metabolomics approach, which relies on a UPLC-TQ / MS system (Agilent 1290 Infinity UHPLC and Agilent 6495 QQQ, Agilent Technologies, U.S.A.). To separate metabolites, an ACQUITY UPLC HSS T3 column (2.1 x 100 mm, 1.8 μm) (Waters, U.S.A) was used. Raw data were centrally processed using the MetaboAnalyst platform. Important metabolites were filtered by PLS-DA analysis (VIP score greater than 1). A thorough screening was performed to determine the metabolites in feces and serum that met the VIP score criteria. Subsequently, non-parametric tests were performed on these metabolites to determine any significant differences between the normal and abnormal groups. In addition, a receiver operating characteristic curve (ROC) analysis was performed to determine the indicative effect of the screened metabolites on the disease, with a minimum AUC value of 0.5.

[0080] The present application evaluated the correlation between serum and fecal metabolites by examining the relationship between the main components and variables within the same axis, and performed a Procrustes analysis. The relationship between serum metabolites and fecal metabolites was elucidated using a variation multivariate analysis of variance (PERMANOVA), with statistical significance determined by P<0.05, and an adjusted R2>0.02 indicating a significant effect on the differential metabolites. The contribution of differential strain abundance to differential metabolites was elucidated using a variation multivariate analysis of variance (PERMANOVA), with statistical significance determined by P<0.05, and an adjusted R2>0.02 indicating a significant effect on the differential metabolites.

[0081] Results refer to Figure 3 shown, Figure 3 The serum and fecal metabolome profiles were shown to be associated with individuals with cardiac abnormalities. A and B are PLS-DA displays of classification between HH-N and HH-A groups based on serum (A) and fecal (B) metabolome. Each sub-panel shows the explained degree of X and Y axes and the predictive ability of each model. Green and yellow nodes represent HH-N (n=42) and HH-A (n=35) groups, respectively.

[0082] C is the VIP scores of metabolites in serum and feces. The VIP scores of all metabolites are greater than 1. Red bars are serum metabolites; blue bars are fecal metabolites; gray blocks are serum and fecal metabolites.

[0083] D is the abundance difference of four differential metabolites between HH-N and HH-A groups. Wilcoxon rank-sum test was used to detect the significance of differential metabolites in each group. The levels of 3-GUA, Betaine, L-Asp in serum and feces were significantly lower in HH-A group than in HH-N group; the serum a-KG was significantly lower in HH-A group than in HH-N group, while the fecal a-KG was significantly higher in HH-A group than in HH-N group.

[0084] E is the Procrustes analysis result plot of serum metabolites and fecal metabolites. Serum and fecal metabolites are represented by red and blue circles, respectively. Serum and fecal samples of the same individual are connected by a line.

[0085] F and G are the result plots of predicting cardiac abnormalities in high altitude areas by serum metabolites (F) and fecal metabolites (G) (the predicted population consists of 35 volunteers with myocardial ischemia to form the abnormal group (HH-A) and 42 volunteers with healthy hearts to form the normal group (HH-N)). AUC reflects the predictive ability of metabolites with different abundances for cardiac abnormalities. The higher the AUC value, the stronger the predictive ability of the metabolite. The results show that 3 serum metabolites (F) and 3 fecal metabolites (G) have good prediction results for cardiac abnormalities in high altitude areas.

[0086] H is the AUC curve plot of predicting cardiac abnormalities by serum or fecal metabolite groups. Serum and fecal metabolites are fitted by logistic regression, respectively.

[0087] Figure 4 The results show that the intestinal microbiota affects the host serum and fecal metabolites of cardiac abnormality high altitude immigrants, i.e. the intestinal microbiota is positively correlated with the host serum and fecal metabolites of cardiac abnormality high altitude immigrants.

[0088] Figure 4A in FIG. 6E and FIG. 6F. The co-variance relationship between each serum metabolite and gut microbiome composition or fecal metabolite was assessed by PERMANOVA. The effect size between serum metabolite and gut microbiota or fecal metabolite was indicated by blue shade. *, p < 0.05; **, p < 0.01; ***, p < 0.001. B in FIG. 6E and FIG. 6F. The correlation results between serum and fecal metabolite concentration, HH-N enriched and HH-A enriched species and microbial functions. The red bar in the heatmap indicates positive correlation, and the blue bar indicates negative correlation. The degree of correlation between species and microbial functions is shown by Spearman's rank correlation coefficient, *, p < 0.05; **, p < 0.01; ***, p < 0.001.

[0089] C and D in FIG. 6E and FIG. 6F. Scatter plots showing the correlation between each serum metabolite concentration and Veillonella rogosae (C) or Streptococcus rubneri (D) abundance in HH-N group and HH-A group, respectively. The relationship between each two samples was calculated by Spearman's rank correlation coefficient. The results showed that the concentration of four serum metabolites was positively correlated with Veillonella rogosae or Streptococcus rubneri abundance in the abnormal group of myocardial ischemia (HH-A group).

[0090] Experimental Example 1

[0091] The serum metabolites and gut microbiota described above were used to predict the high altitude heart disease of the test sample, and the accuracy of the prediction was calculated.

[0092] The prediction results of serum metabolites are referred to in FIG. 6E and FIG. 6F. Figure 4

[0093] Figure 4 E in FIG. 6E and FIG. 6F. The experimental results of the differences in the contents of L-Aspartate (L-Asp), Betaine and Ketoglutarate (a-KG) in the validation queue (validation population). Wilcoxon rank sum test was used to detect the significance of the differences between each comparison. The results showed that the contents of serum metabolites L-Aspartate (L-Asp), Betaine and Ketoglutarate (a-KG) in the abnormal heart high altitude immigrants were significantly lower than those in the normal heart high altitude immigrants.

[0094] The ROC curve in F shows the prediction ability of the selected serum metabolites, gut microbiota and the combination of the two features for heart abnormalities in the validation population. Blue curve, serum metabolite; purple curve, gut microbiota; orange curve, combination of the two features. The results show that the prediction ability of serum metabolites and gut microbiota for heart abnormalities is good, and the combination of the two has higher prediction ability, AUC = 0.7857.

[0095] ​Figure 5 To validate the abundance comparison of the 10 microorganisms in the cohort, Veillonella rogosae and Streptococcus rubneri were consistent with the experimental group, and their abundance significantly decreased in the population with heart abnormalities, p<0.05.

[0096] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. Use of a reagent for detecting blood, serum or fecal metabolite levels in the manufacture of a product for predicting and / or diagnosing high altitude heart disease, characterized in that, The blood, serum or fecal metabolites are L-aspartate, betaine and ketoglutarate.

2. Use according to claim 1, characterized in that, The product is a reagent, a kit, a chip, a magnetic bead or a microwell plate.

3. Use according to claim 1, characterized in that, The reagent for detecting the level of blood, serum or fecal metabolites is at least one selected from the group consisting of a super high performance liquid chromatography triple quadrupole tandem mass spectrometry detection reagent, a high performance liquid chromatography detection reagent, an acid-base titration reagent, a magnetic microparticle chemiluminescence detection reagent, a thin layer scanning quantitative reagent, a perchloric acid non-aqueous titration detection reagent, a spectrophotometric detection reagent, a gas chromatography reagent, an ion chromatography reagent and an electrochemical chiral sensor detection reagent.

4. A prediction system of high altitude heart disease characterized by, It comprises: a detection module and a comparison module; The detection module is used for analyzing the content of metabolites in the separated blood, serum or fecal sample by using an analyzer or a kit to obtain the content of metabolites in the sample; the metabolites are L-aspartate, betaine and ketoglutarate; The comparison module is used for comparing the obtained content of metabolites in the sample with a set value.

5. The prediction system for high altitude heart disease according to claim 4, characterized in that, The set value is the content of metabolites of the same sample type of a normal healthy person.

6. Use of a reagent for detecting the abundance of gut microbiota in the preparation of a product for predicting and / or diagnosing high altitude heart disease, characterized in that, The gut flora is Streptococcus rubiginosus (S. rubiginosus) Streptococcus rubneri ) and Amanita (Amanita) Veillonella rogosae ).

7. Use according to claim 6, characterized in that, The product is a reagent, a kit, a chip, a magnetic bead or a microwell plate.

8. Use according to claim 6, characterized in that, The reagent for detecting the abundance of intestinal flora is selected from the group consisting of a metagenomic sequencing reagent, a 16S rRNA amplicon sequencing reagent, a droplet digital PCR detection reagent, a qPCR quantitative detection reagent, a polymerase chain reaction reagent, a reverse transcription polymerase chain reaction reagent, a nested PCR reagent, or a reagent for nucleic acid hybridization.

9. A prediction system of high altitude heart disease characterized by, It comprises: a detection module and a comparison module; The detection module is used for sequencing and / or quantifying the nucleic acid sample of the separated intestinal tract to obtain the content of intestinal flora in the sample; the intestinal flora is Streptococcus lutiae ( Streptococcus rubneri ) and Boletus ( Veillonella rogosae ). The comparison module is used for comparing the obtained content of intestinal flora in the sample with a set value.

10. The prediction system for high altitude heart disease according to claim 9, characterized in that, The set value is the content of intestinal flora of the same sample type of a normal healthy mammal.

11. Use of a reagent for detecting blood, serum or fecal metabolite levels and a reagent for detecting intestinal microbiota abundance in the manufacture of a product for predicting and / or diagnosing high altitude heart disease, characterized in that, The blood, serum or fecal metabolites are L-aspartate, betaine and ketoglutarate; the gut microbiota are Streptococcus lubeana Streptococcus rubneri and Boletus Veillonella rogosae .

12. Use according to claim 11, characterized in that, The product is a reagent, a kit, a chip, a magnetic bead or a microwell plate.

13. The use according to claim 11, characterized in that, The reagent for detecting the abundance of intestinal flora is selected from the group consisting of a metagenomic sequencing reagent, a 16S rRNA amplicon sequencing reagent, a droplet digital PCR detection reagent, a qPCR quantitative detection reagent, a polymerase chain reaction reagent, a reverse transcription polymerase chain reaction reagent, a nested PCR reagent, or a reagent for nucleic acid hybridization.

14. The use according to claim 11, characterized in that, The reagent for detecting the level of blood, serum or fecal metabolites is at least one selected from the group consisting of a super high performance liquid chromatography triple quadrupole tandem mass spectrometry detection reagent, a high performance liquid chromatography detection reagent, an acid-base titration reagent, a magnetic microparticle chemiluminescence detection reagent, a thin layer scanning quantitative reagent, a perchloric acid non-aqueous titration detection reagent, a spectrophotometric detection reagent, a gas chromatography reagent, an ion chromatography reagent and an electrochemical chiral sensor detection reagent.

15. A system for predicting high altitude heart disease, characterized by, It comprises: a detection module and a comparison module; The detection module has the following functions: (1) sequencing and / or quantifying nucleic acid samples isolated from the gut to obtain the content of gut microbiota in the sample; the gut microbiota is Streptococcus lutiae (S. lutiae) Streptococcus rubneri ) and Boletus (Boletus) Veillonella rogosae ); (2) analyzing the content of metabolites in the separated blood, serum or fecal sample by using an analyzer or a kit to obtain the content of metabolites in the sample; the metabolites are L-aspartate, betaine and ketoglutarate; The comparison module has the following functions: (1) for comparing the obtained content of metabolites in the sample with a set value; (2) for comparing the obtained content of intestinal flora in the sample with a set value.

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