阅读说明：本技术 一组用于心力衰竭诊断的肠道微生物代谢标志物及其应用 (Intestinal microbial metabolism markers for heart failure diagnosis and application thereof ) 是由 詹红 铃木亨 霍志远 朱凤 于 2020-06-30 设计创作，主要内容包括：本发明提供了一组用于心力衰竭诊断的肠道微生物代谢标志物及其应用。具体地,本发明提供了一种生物标志物集合,所述的集合包括乙酰左旋肉碱或乙酰左旋肉碱与选自下组的一种或多种生物标志物的组合：γ-丁基甜菜碱、左旋肉碱、氧化三甲胺,本发明的生物标志物可用于评估待测对象的心力衰竭诊断、预后评估,以及对心力衰竭相关疾病的风险预测。本发明还提供了包含所述生物标志物集合的试剂盒以及所述试剂盒在心力衰竭诊断中的应用。(The invention provides a group of intestinal microbial metabolism markers for heart failure diagnosis and application thereof. In particular, the present invention provides a set of biomarkers comprising acetyl-l-carnitine or a combination of acetyl-l-carnitine with one or more biomarkers selected from the group consisting of: gamma-butyl betaine, L-carnitine and trimethylamine oxide, the biomarker of the invention can be used for evaluating the diagnosis and prognosis of heart failure of a subject to be tested, and predicting the risk of heart failure-related diseases. The invention also provides a kit comprising the biomarker set and application of the kit in heart failure diagnosis.)

1. A set of biomarkers, wherein said set comprises acetyl-l-carnitine or a combination of acetyl-l-carnitine with one or more biomarkers selected from the group consisting of: gamma-butyl betaine, L-carnitine and trimethylamine oxide.

2. The biomarker panel of claim 1, further comprising a biomarker selected from the group consisting of: choline chloride, crotonobetaine, betaine, trimethyllysine, or a combination thereof.

3. The biomarker panel of claim 1, wherein an increase in the level (e.g., amount) of each biomarker in the biomarker panel, as compared to a reference value, indicates that the subject has heart failure.

4. A combination of reagents for the diagnosis of heart failure, wherein the combination of reagents comprises reagents for detecting each biomarker in the panel of claim 1.

5. A kit comprising the collection of claim 1 and/or the combination of reagents of claim 4.

6. Use of a set of biomarkers for the preparation of a kit for (a) diagnosing heart failure; (b) performing prognostic assessment of heart failure; and/or (c) risk prediction of heart failure related diseases, wherein the set of biomarkers comprises one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide.

7. The use of claim 6, wherein the biomarker comprises acetyl-L-carnitine or a combination of acetyl-L-carnitine with one or more biomarkers selected from the group consisting of: gamma-butyl betaine, L-carnitine and trimethylamine oxide.

8. The use according to claim 6, wherein an increase in the level (e.g. amount) of each biomarker in the set of biomarkers, when compared to a reference value, is indicative of heart failure in the subject.

9. A method of (a) diagnosing heart failure; (b) performing prognostic assessment of heart failure; and/or (c) a method for risk prediction of heart failure related diseases, comprising the steps of:

(1) providing a sample derived from a subject, and measuring the level (e.g., amount) of each biomarker in a collection comprising one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide;

(2) comparing the level (e.g., amount) measured in step (1) with a reference data set or a reference value (e.g., a reference value for a healthy control);

preferably, the reference data set comprises the levels (e.g. amounts) of the individual biomarkers in the set as derived from heart failure patients and healthy controls.

10. A method for establishing a diagnosis, a prognosis and a prediction of risk of a heart failure-related disease, said method comprising: identifying a differentially expressed substance in the blood sample between the patient and a healthy control,

wherein the differentially expressed material comprises biomarkers in one or more biomarker panels, wherein the biomarker panels comprise one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide.

Technical Field

The invention relates to the field of biomedicine, in particular to a group of intestinal microbial metabolic markers for heart failure diagnosis and application thereof.

Background

Cardiovascular diseases are the leading cause of death of urban and rural residents in China at present, and are higher than tumors and other diseases. The newly released data of 'Chinese cardiovascular disease report 2018' show that: the morbidity and mortality of cardiovascular diseases in China are still in a continuous rising stage, 2.9 million patients with cardiovascular diseases are calculated, wherein 1300 million stroke, 1100 million coronary heart disease, 500 million pulmonary heart disease, 45 million heart failure, 250 million rheumatic heart disease and 2.7 million hypertension exist in the whole country, the cardiovascular diseases are main killers of human health, the cardiovascular disease prevention and treatment work in China has primary effect but still faces serious challenges, the burden of the cardiovascular diseases is gradually increased, the cardiovascular disease prevention and treatment is a major public health problem, and the prevention and treatment of the cardiovascular diseases are not slow enough. How to early prevent and treat cardiovascular diseases, find effective targets of drug action, open up new therapeutic approaches, and become a hot spot of attention.

Heart failure is the terminal stage of all cardiovascular diseases and is called a heart disease "malignancy". With the aging of the Chinese population, the morbidity and mortality of heart failure are in a remarkably rising trend, and the health of people is seriously influenced. The diagnosis of heart failure requires comprehensive analysis from several aspects of medical history, symptoms, physical examination and auxiliary examination, and biomarkers are widely used in diagnosis, clinical evaluation, prognosis evaluation and the like of heart failure.

Currently, the detection of biomarkers for cardiovascular and cerebrovascular diseases is mainly focused on macromolecules, such as troponin, CK-MB, myoglobin and cardiac fatty acid binding protein, which are markers of myocardial injury; markers of risk factors for coronary artery disease, such as TC, LDL-C, HDL-C, Lpa, TG, CRP, LP-PLA2, and the like; a thromboembolic biomarker D-dimer; b-type natriuretic peptide (BNP) or N-terminal pro-B-type natriuretic peptide (NT-proBNP) as biomarkers for diagnosis, evaluation of therapeutic effect, and prognosis of heart failure. At present, biochemical methods, immunological methods and the like are mostly adopted aiming at macromolecular detection methods, and the specificity and the accuracy of the methods are lower, so that the higher clinical requirements cannot be completely met. Some biomarkers, such as NT-proBNP and BNP, may have certain effects on the results due to the influence of demographic characteristics, sample storage conditions (the markers are active and easy to decompose), and drugs.

Metabolomics, which reflects the direct relationship of genes, proteins and metabolic activities themselves by measuring the change in the concentration of cellular, tissue and body metabolites, is another new branch of omics research that has emerged following genomics, transcriptomics, proteomics. Since metabonomics changes are the final reflection of the body on the effects of genes, diseases, environments, drugs and the like, and endogenous metabolites of the metabonomics are the key or end-point reactions of a series of life events of the body, metabonomics can help people to better understand various complex interactions and the essence thereof in the body and can be used for diagnosing human diseases. The high performance liquid chromatography-mass spectrometry (LC-MS/MS) is one of the most widely applied technical platforms in metabonomics research, and has the characteristics of high sensitivity, high flux, wide linear range and the like.

The human intestinal flora is a complex community and the intestinal microbiota plays an important role in immunity and defense, digestion and metabolism, inflammation and cell proliferation. The main nutrients choline, betaine and carnitine from red meat, eggs, dairy products and saltwater fish are involved in biological activities such as energy metabolism in human bodies. After ingestion, fermentation of these nutrients by gut microbes results in the release of Trimethylamine (TMA), which is converted to trimethylamine oxide (TMAO) by the host liver enzymes, flavin-containing monooxygenase 3(FMO 3). There is increasing evidence that: TMAO, one of small molecules in intestinal microorganism metabolism, participates in cholesterol metabolism, promotes platelet high aggregation, increases thrombus formation, and promotes vascular inflammatory reaction to cause arterial plaque formation. However, there are no metabolic markers currently available that are relevant for the diagnosis of cardiovascular diseases, in particular heart failure.

Therefore, there is an urgent need in the art to find more intestinal microbial metabolic markers on the "intestinal mandrel" associated with the diagnosis of cardiovascular diseases (particularly heart failure) by using LC-MS/MS detection platform and detecting one or more intestinal microbial metabolic markers with higher stability, specificity, sensitivity and accuracy by using larger molecules.

Disclosure of Invention

The invention aims to provide a method for detecting one or more intestinal microbial metabolic markers on an intestinal mandrel, which is related to cardiovascular disease (particularly heart failure) diagnosis, by using an LC-MS/MS detection platform more frequently and detecting one or more intestinal microbial metabolic markers on the intestinal mandrel with higher stability, specificity, sensitivity and accuracy by using larger molecules.

In a first aspect of the invention, there is provided a set of biomarkers comprising acetyl-l-carnitine or a combination of acetyl-l-carnitine with one or more biomarkers selected from the group consisting of: gamma-butyl betaine, L-carnitine and trimethylamine oxide.

In another preferred example, the biomarker panel is used for (a) diagnosing heart failure; (b) performing prognostic assessment of heart failure; and/or (c) risk prediction of heart failure related diseases, or for the preparation of a kit or reagent for diagnosing heart failure using (a); (b) performing prognostic assessment of heart failure; and/or (c) risk prediction of heart failure related diseases.

In another preferred embodiment, the biomarker panel further comprises a biomarker selected from the group consisting of: choline chloride, crotonobetaine, betaine, trimethyllysine, or a combination thereof.

In another preferred embodiment, the heart failure-related disease is selected from the group consisting of: hypertension, coronary heart disease, cardiomyopathy, diabetes, obesity, metabolic syndrome, or a combination thereof.

In another preferred embodiment, the biomarker or set of biomarkers is derived from a blood, plasma, or serum sample.

In another preferred embodiment, an increased level (e.g., amount) of each biomarker in the set of biomarkers, as compared to a reference value, is indicative of heart failure in the subject.

In another preferred embodiment, the individual biomarkers are identified by mass spectrometry, preferably by a combination of chromatographic and mass spectrometry, such as liquid chromatography-mass spectrometry (LC-MS).

In another preferred embodiment, said collection is used for assessing a diagnosis of a subject suffering from heart failure.

A second aspect of the invention provides a combination of reagents for use in the diagnosis of heart failure, the combination of reagents comprising reagents for detecting each biomarker in a panel according to the first aspect of the invention.

In another preferred embodiment, the reagents comprise substances for mass spectrometry detection of the individual biomarkers of the collection according to the first aspect of the invention.

According to a third aspect of the invention there is provided a kit comprising a collection according to the first aspect of the invention and/or a combination of reagents according to the second aspect of the invention.

In another preferred embodiment, each biomarker in the collection according to the first aspect of the invention is used as a standard.

In another preferred embodiment, the kit further comprises an instruction describing a reference data set of levels of the respective biomarkers in the collection according to the first aspect of the invention from heart failure patients and/or healthy controls.

In a fourth aspect, the present invention provides the use of a biomarker panel for the preparation of a kit for (a) diagnosing heart failure; (b) performing prognostic assessment of heart failure; and/or (c) risk prediction of heart failure related diseases, wherein the set of biomarkers comprises one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide.

In another preferred embodiment, the biomarker comprises acetyl-l-carnitine or a combination of acetyl-l-carnitine with one or more biomarkers selected from the group consisting of: gamma-butyl betaine, L-carnitine and trimethylamine oxide.

In another preferred embodiment, the diagnosis comprises the steps of:

(1) providing a sample from the subject, and measuring the level (e.g., amount) of each biomarker in the collection in the sample;

(2) comparing the amount measured in step (1) with a reference data set or a reference value (e.g. of a healthy control);

preferably, the reference data set comprises the levels (e.g. amounts) of the individual biomarkers in the set as derived from heart failure patients and healthy controls.

In another preferred embodiment, the sample is selected from the group consisting of: blood, plasma, and serum.

In another preferred embodiment, the level (e.g. content) measured in step (1) is compared to a reference data set or reference value.

In another preferred embodiment, an increase in the level (e.g., amount) of each biomarker in the set of biomarkers, when compared to a reference value, is indicative of heart failure in the subject.

In another preferred embodiment, the level (e.g. amount) of each biomarker is detected by mass spectrometry, preferably by a combination of chromatographic and mass spectrometry, such as liquid chromatography-mass spectrometry (LC-MS).

In another preferred embodiment, before step (1), the method further comprises a step of processing the sample.

A fifth aspect of the present invention provides a method of (a) diagnosing heart failure; (b) performing prognostic assessment of heart failure; and/or (c) a method for risk prediction of heart failure related diseases comprising the steps of:

(1) providing a sample derived from a subject, and measuring the level (e.g., amount) of each biomarker in a collection comprising one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide;

(2) comparing the level (e.g., amount) measured in step (1) with a reference data set or a reference value (e.g., a reference value for a healthy control);

preferably, the reference data set comprises the levels (e.g. amounts) of the individual biomarkers in the set as derived from heart failure patients and healthy controls.

In a sixth aspect, the present invention provides a method for establishing a heart failure diagnosis, a prognosis evaluation and a heart failure-related disease risk prediction, the method comprising: identifying a differentially expressed substance in the blood sample between the patient and a healthy control,

wherein the differentially expressed material comprises biomarkers in one or more biomarker panels, wherein the biomarker panels comprise one or more biomarkers selected from the group consisting of: acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide.

It is to be understood that within the scope of the present invention, the above-described features of the present invention and those specifically described below (e.g., in the examples) may be combined with each other to form new or preferred embodiments. Not to be reiterated herein, but to the extent of space.

Drawings

FIG. 1 is a standard regression curve of the standard solution of acetyl L-carnitine obtained in example 1, wherein the compound name is acetyl L-carnitine, m/z:204.00>85.10, the standard curve formula is f (x) ═ 0.562436 x +0.00401288, the correlation coefficient (R) ═ 0.9975895, and the degree of fitting (R ^2) ═ 0.9951848.

FIG. 2 is a standard regression curve of the betaine standard solution obtained in example 1, wherein the compound name is betaine, m/z is 118.10>85.10, the standard curve formula is f (x) 0.430087 x +0.212109, the correlation coefficient (R) is 0.9967028, and the degree of fitting (R2) is 0.9934164.

FIG. 3 is a standard regression curve of the choline chloride standard solution obtained in example 1, wherein the name of the compound is choline chloride, m/z is 104.15>85.10, the formula of the standard curve is f (x) 0.392948 x +0.0579829, the correlation coefficient (R) is 0.9951687, and the degree of fitting (R2) is 0.9903608.

FIG. 4 is a standard regression curve of the crotonobetaine standard solution obtained in example 1, wherein the compound name is crotonobetaine, m/z:144.00>85.10, the standard curve formula is f (x) ═ 0.515572 x +0.00749575, the correlation coefficient (R) ═ 0.9963506, and the degree of fit (R ^2) ═ 0.9927145.

FIG. 5 is a standard regression curve of the gamma-butylbetaine standard solution obtained in example 1, wherein the compound name is gamma-butylbetaine, m/z is 146.00>87.05, the standard curve formula is f (x) 0.392311 x +0.00581357, the correlation coefficient (R) is 0.9979180, and the degree of fitting (R2) is 0.9958404.

FIG. 6 is a standard regression curve of L-carnitine standard solution obtained in example 1, wherein the compound name is L-carnitine, m/z:162.10 is greater than 60.10, the standard curve formula is f (x) 0.290605 x +0.109496, the correlation coefficient (R) is 0.9987178, and the degree of fitting (R2) is 0.9974372.

FIG. 7 is a standard regression curve of trimethyllysine standard solution obtained in example 1, wherein the compound name is trimethyllysine, m/z:189.20>84.10, the standard curve formula is f (x) ═ 0.449088 x-0.00433157, the correlation coefficient (R) ═ 0.9992299, and the degree of fit (R ^2) ═ 0.9984604.

FIG. 8 is a standard regression curve of the trimethylamine oxide standard solution obtained in example 1, wherein the compound name is trimethylamine oxide, m/z:76.15>58.15, the standard curve formula is f (x) ═ 0.305433 x +0.0665364, the correlation coefficient (R) ═ 0.9981962, and the degree of fit (R ^2) ═ 0.9963956.

FIG. 9 is a diagram of a Receiver Operating Curve (ROC) model for index joint inspection using the ROC method.

Detailed Description

The present inventors have extensively and intensively studied and, for the first time, unexpectedly found a novel biomarker for heart failure. Specifically, the invention discovers a biomarker set, wherein the biomarker set comprises one or more biomarkers of heart failure, can be used for evaluating the diagnosis, prognosis evaluation and related disease risk prediction of the heart failure of a subject to be tested, and has the advantages of high sensitivity and high specificity and important application value. On this basis, the inventors have completed the present invention.

Term(s) for

The terms used herein have meanings commonly understood by those of ordinary skill in the relevant art. However, for a better understanding of the present invention, some definitions and related terms are explained as follows:

as used herein, the terms "comprises," "comprising," "includes," "including," and "including" are used interchangeably and include not only closed-form definitions, but also semi-closed and open-form definitions. In other words, the term includes "consisting of … …", "consisting essentially of … …".

As used herein, the term "liquid-mass spectrometry" is short for high performance liquid-mass spectrometry, i.e., "liquid-mass spectrometry" is used interchangeably with "high performance liquid-mass spectrometry".

Acetyl L-carnitine, L-carnitine and trimethylamine oxide are used as examples for description.

As used herein, the term "acetyl-l-carnitine" is abbreviated ALC, i.e. "acetyl-l-carnitine" is used interchangeably with "ALC".

As used herein, the term "l-carnitine" is abbreviated carnitine, i.e., "l-carnitine" is used interchangeably with carnitine.

As used herein, the term "trimethylamine oxide" is abbreviated TMAO, i.e., "trimethylamine oxide" and "TMAO" are used interchangeably.

As used herein, the term "ultra performance liquid chromatography" is abbreviated UPLC, i.e., "ultra performance liquid chromatography" is used interchangeably with "UPLC".

As used herein, "mass spectrometry" (MS) refers to analytical techniques for identifying compounds by their mass MS techniques generally include (1) ionizing a compound to form a charged compound; and (2) detecting the molecular weight of the charged compound and calculating the mass to charge ratio (m/z) the compound can be ionized and detected by any suitable means "mass spectrometers" generally include ionizers and ion detectors.

The term "about" as used herein in reference to a quantitative measurement means that the indicated value is plus or minus 10%.

According to the present invention, the term "biomarker panel" refers to one biomarker, or a combination of two or more biomarkers.

According to the invention, the content of the biomarker substance is indicated by a mass spectrometry signal area normalization value.

According to the present invention, the reference set refers to a training set.

According to the present invention, the training set and the validation set have the same meaning, as is known from the prior art. In one embodiment of the invention, the training set refers to a set of biomarker levels in heart failure patients and healthy control biological samples. In one embodiment of the invention, a validation set refers to a data set used to test the performance of a training set. In one embodiment of the invention, the amount of biomarker may be represented as an absolute value or a relative value according to the method of determination. For example, when mass spectrometry is used to determine the level (e.g., amount) of a biomarker, the intensity or area of the peak may represent the level of the biomarker, which is the level of a relative value; when PCR is used to determine the level of a biomarker, the copy number of the gene or the copy number of a gene fragment may represent the level of the biomarker.

In one embodiment of the invention, the reference value refers to a reference value or normal value of a healthy control. It is clear to those skilled in the art that in case of a sufficient number of samples, a range of normal values (absolute values) for each biomarker can be obtained by means of testing and calculation methods. Therefore, when the levels of biomarkers are detected by methods other than mass spectrometry, the absolute values of the levels of these biomarkers can be directly compared with normal values, thereby evaluating the diagnosis of suffering from heart failure or the early diagnosis of heart failure. Statistical methods may also be used in the present invention.

According to the present invention, the term "biomarker", also referred to as "biological marker", refers to a measurable indicator of the biological state of an individual. Such biomarkers can be any substance in an individual as long as they are related to a particular biological state (e.g., disease) of the subject, e.g., nucleic acid markers (e.g., DNA), protein markers, cytokine markers, chemokine markers, carbohydrate markers, antigen markers, antibody markers, species markers (species/genus markers) and functional markers (KO/OG markers), and the like. Biomarkers are measured and evaluated, often to examine normal biological processes, pathogenic processes, or therapeutic intervention pharmacological responses, and are useful in many scientific fields.

According to the present invention, the term "individual" refers to an animal, in particular a mammal, such as a primate, preferably a human.

According to the present invention, the term "plasma" refers to the liquid component of whole blood. Depending on the separation method used, the plasma may be completely free of cellular components and may also contain varying amounts of platelets and/or small amounts of other cellular components.

According to the present invention, terms such as "a," "an," and "the" do not refer only to a singular entity, but also include the general class that may be used to describe a particular embodiment.

It should be noted that the explanation of the terms provided herein is only for the purpose of better understanding the present invention by those skilled in the art, and is not intended to limit the present invention.

Detection method

According to the present invention, Mass Spectrometry (MS) can be divided into ion trap mass spectrometry, quadrupole mass spectrometry, orbitrap mass spectrometry and time-of-flight mass spectrometry with deviations of 0.2amu, 0.4amu, 3ppm and 5ppm, respectively. In the present invention, MS data is obtained using tandem quadrupole mass spectrometry.

Reagent kit

In the present invention, the kit of the invention comprises the collection of the first aspect of the invention and/or the combination of reagents of the second aspect of the invention.

In another preferred embodiment, each biomarker in the collection according to the first aspect of the invention is used as a standard.

In another preferred embodiment, the kit further comprises an instruction which describes a reference data set for the levels (e.g. amounts) of the individual biomarkers of the panel according to the first aspect of the invention from heart failure patients and/or healthy controls.

ROC-AUC

The ROC-AUC is a method for evaluating model accuracy, and is a coordinate graph formed by a Receiver operating characteristic curve (Receiver operating characteristic curve), a False positive probability (False positive rate) as a horizontal axis and a True positive probability (True positive rate) as a vertical axis, and is a comprehensive index reflecting continuous variables of sensitivity and specificity. AUC is the Area under the ROC curve (Area under the curve). The ROC-AUC value is between 1.0 and 0.5, the closer to 1, the better the diagnosis effect is, the lower the accuracy is at 0.5-0.7, the certain accuracy is at 0.7-0.9, and the higher the accuracy is at AUC above 0.9. When AUC is 0.5, the diagnostic method is completely ineffective and is not valuable. AUC <0.5 does not correspond to the real case and occurs rarely in practice.

The main advantages of the invention include:

(a) the invention discloses intestinal microbial metabolism markers on an intestinal mandrel for diagnosing heart failure for the first time, wherein the intestinal microbial metabolism markers comprise one or more of acetyl L-carnitine, gamma-butyl betaine, L-carnitine and TMAO. Wherein, the acetyl L-carnitine is firstly applied to the heart failure diagnosis. Proved by verification, AUC of acetyl L-carnitine, gamma-butyl betaine, L-carnitine and TMAO in intestinal tract microbial metabolism markers on the intestinal mandrel provided by the invention is above 0.8 when used for diagnosing and distinguishing heart failure patients from healthy people (in a ROC curve evaluation method, the closer the AUC of an area value under a ROC curve is to 1 when the AUC is greater than 0.5, the diagnostic effect is shown, the lower the accuracy is when the AUC is between 0.5 and 0.7, the certain accuracy is when the AUC is between 0.7 and 0.9, and the higher the accuracy is when the AUC is above 0.9). The effect of distinguishing heart failure patients from healthy people in the diagnosis of the acetyl-L-carnitine is the best, when any index of the acetyl-L-carnitine and the gamma-butyl betaine, the acetyl-L-carnitine and the L-carnitine, and the acetyl-L-carnitine and the trimethylamine oxide is jointly applied pairwise, the AUC is closer to 1 than that of a single index, and the diagnosis effect is better; when three indexes of acetyl L-carnitine, gamma-butyl betaine and L-carnitine are jointly applied, the AUC is closer to 1 than that of the single index and the two indexes which are jointly applied, and the diagnosis and differentiation effect is the best.

(b) The detection method disclosed by the invention is simple to operate, short in analysis time (joint inspection only needs 5 minutes), accurate in detection result and high in result reproduction rate (CV is less than 10%).

(c) The kit provided by the invention can be used for diagnosing heart failure, improves the convenience of diagnosis and promotes the standardization of a diagnosis method.

The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. The experimental procedures, in which specific conditions are not noted in the following examples, are generally carried out under conventional conditions or conditions recommended by the manufacturers. Unless otherwise indicated, percentages and parts are by weight.

Unless otherwise specified, reagents and materials used in examples of the present invention are commercially available products.

Example 1 detection method and specific Experimental procedures

1. Origin of specimen

After patient consent, plasma samples were collected from 30 patients with heart failure (left ventricular ejection fraction < 35%, BNP >400ng/L, functional identifications of the New York Heart Association as II to IV), 30 healthy persons matched age, gender and time of blood collection for patients with heart failure, all in the early morning fasting state.

2. Main apparatus and equipment:

shimadzu LC-MS 8050; labsolutions instruments software.

3. Reagents and materials:

acetyl L-carnitine, betaine, choline chloride, crotonobetaine hydrochloride, gamma-butyl betaine, L-carnitine, trimethyl lysine and trimethylamine oxide standard substances; acetyl L-carnitine-D3, gamma-butyl betaine-D9, betaine-D11, choline chloride-D9, L-carnitine-D9, trimethylamine oxide-D9, methanol, acetonitrile, ethanol, formic acid, ammonia water and carbon adsorbed human plasma are all commercially available reagents.

4. Liquid chromatography and mass spectrometry conditions:

chromatographic conditions are as follows:

a chromatographic column: ACQUITY UPLC BEH HILIC (C)1.7μM，2.1×100mm)；

Protecting the pre-column: ACQUITY UPLC BEH HILIC VanGuard pre-column(1.7μM，2.1×5mm)；

Mobile phase A: an aqueous solution of 0.1% (v/v) formic acid (A) + 0.025% (v/v) aqueous ammonia (B); mobile phase B: 0.1% (v/v) formic acid (A) in acetonitrile; based on the total volume of the mobile phase B; flow rate 0.6 mL/min: column temperature 45 ℃: sample chamber temperature: 8 ℃; the sample volume is 1 mu L; needle washing liquid: 50% methanol water.

Mobile phase gradient method:

mass spectrum conditions:

detecting in positive ion MRM mode by using an electrospray ionization source (ESI);

the flow rate of the atomizing gas is 3L/min, and the flow rate of the heating gas is 10L/min; the flow rate of the drying gas is 10L/min; interface temperature: 300 ℃; DL temperature: 300 ℃; temperature of the heating block: 400 ℃;

5. the experimental process comprises the following steps:

5-1 solution preparation

5-1-1 preparation of mixed standard curve solution:

accurately weighing appropriate amount of acetyl L-carnitine, betaine, choline chloride, crotonobetaine hydrochloride, gamma-butyl betaine, L-carnitine, trimethyl lysine and trimethylamine oxide standard substances, dissolving with 50% methanol aqueous solution, and respectively preparing into standard substance stock solutions with concentration of 5 mmol/L. Then, the standard substance stock solution with the concentration of 5mmol/L is sequentially diluted into the following standard curve working solution by 50 percent methanol aqueous solution.

Mixing standard solutions, wherein the concentrations of standard curves of the four substances, namely acetyl L-carnitine, crotonobetaine, gamma-butyl betaine and trimethyllysine are 0.05, 0.25, 1, 2.5, 5, 10 and 25 mu mol/L; the concentrations of the standard curves of the four substances of the betaine, the choline chloride, the L-carnitine and the trimethylamine oxide are 0.1, 0.5, 2, 5, 10, 20 and 50 mu mol/L; the preparation matrix of the mixed standard solution is 50% methanol aqueous solution.

5-1-2 preparation of mixed internal standard solution:

accurately weighing proper amounts of acetyl L-carnitine-D3, gamma-butyl betaine-D9, betaine-D11, choline chloride-D9, L-carnitine-D9 and trimethylamine oxide-D9, dissolving with methanol to obtain a 1mmol/L mixed internal standard storage solution, and diluting with methanol to obtain a 10 mu mol/L mixed internal standard working solution.

5-1-3 extraction solvent

The components of the extraction solvent are acetonitrile and acetic acid, and the volume ratio of the acetic acid is 2.0%.

5-2, preparation of a quality control product I and a quality control product II:

and (3) taking a proper amount of Seralab carbon to adsorb blank human plasma, adding a small amount of solution with the highest concentration point of the mixed standard substance, and respectively preparing a quality control I and a quality control II.

5-3, pretreatment and sample injection analysis of a plasma sample:

respectively adding 25 mu L of mixed standard substance working solution and 25 mu L of to-be-detected plasma sample into different wells of a 96-well plate, sequentially adding 20 mu L of mixed internal standard into each well, adding 400 mu L of acetic acid acetonitrile solution (the concentration of acetic acid is 2%), performing vortex for 1min, centrifuging at 4000rpm for 5min, taking 120 mu L of supernatant, respectively injecting 1 mu L of supernatant into a liquid chromatograph-mass spectrometer, and determining and analyzing the content (unit is mu M) of each metabolite of the intestinal flora metabolites in the to-be-detected plasma sample. Wherein the standard regression curves of the above compounds are shown in FIGS. 1 to 8.

As shown in FIGS. 1-8, the standard regression curve of the above compounds is very linear, R2 > 0.99, and meets the performance requirements.

5-4 results

As shown in table 1 below, according to the sensitivity and specificity data automatically derived by the ROC curve method, when the specificity of all the markers is fixed to 96.7% (i.e., when only one of the healthy human samples is positive), the AUC areas and the threshold values obtained from the ROC curve are shown in table 1. Greater than the threshold is defined as + and less than the threshold is defined as-.

AUC and threshold value of each index in Table 1

Example 2 construction of ROC curves comparing the above intestinal flora metabolites singly or in combination for the diagnostic discrimination between patients with heart failure and healthy populations

The test subject working curve (ROC) method is adopted for verification, and the capacity of the test subject in diagnosing the heart failure is judged according to the expression levels of acetyl L-carnitine, betaine, choline chloride, crotonobetaine hydrochloride, gamma-butyl betaine, L-carnitine, trimethyl lysine and trimethylamine oxide in 30 samples of the heart failure and 30 samples of plasma samples of healthy people. From the sensitivity and specificity data automatically derived by the ROC curve method, the sensitivity, AUC and threshold values obtained from the ROC curve are shown in table 2 when the specificity of all the markers is fixed at 96.7% (i.e. when only one of the healthy human samples is positive).

TABLE 2 ability of Single differential metabolite diagnosis to differentiate between Heart failure patients and healthy population

Single differential metabolite	Specificity of	Sensitivity of the probe	AUC	Threshold value
					Acetyl L-carnitine	96.7％	86.7％	0.98	9.23uM
Gamma-butylbetaine	96.7％	53.3％	0.884	1.32uM
					L-carnitine	96.7％	60％	0.842	104uM
Oxetamine	96.7％	80％	0.902	4.3uM
					Choline chloride	96.7％	26.7％	0.617	14.6uM
Crotonobetaine	96.7％	10％	0.546	8.7uM
					Betaine	96.7％	20％	0.512	101uM
Trimethyllysine	96.7％	13％	0.272	2.1uM

As can be seen from Table 2, acetyl L-carnitine, gamma-butylbetaine, L-carnitine and TMAO in the metabolites of intestinal flora on the "intestinal mandrel" have strong ability to differentiate patients with heart failure from healthy people, and AUC is above 0.8. Choline chloride, crotonobetaine, betaine and trimethyllysine are weak in the ability of diagnosing and distinguishing heart failure patients and healthy people individually, and AUC is below 0.7 (in a ROC curve evaluation method, the area value AUC under the ROC curve is more than 0.5 and is closer to 1, which shows that the diagnosis effect is better, AUC has lower accuracy between 0.5 and 0.7, AUC has certain accuracy between 0.7 and 0.9, and AUC has higher accuracy above 0.9).

The acetyl L-carnitine is firstly applied to diagnosis and differentiation of heart failure patients and healthy people, the capacity of diagnosis and differentiation of the heart failure patients and the healthy people is strongest in the four difference indexes, the AUC is 0.98, the sensitivity is 86.7%, and the specificity is 96.7%. TMAO is used as index of cardiovascular disease risk prediction and maturity, and the ability of diagnosing and distinguishing heart failure patients from healthy people is secondly, AUC is 0.902, sensitivity is 80%, and specificity is 96.7%. The diagnosis of gamma-butyl betaine and L-carnitine distinguishes heart failure patients from healthy people, the AUC is 0.884 and 0.842 respectively, the sensitivity is 53.3 percent and 60 percent respectively, and the specificity is 96.7 percent.

In addition, it was further verified whether acetyl-l-carnitine jointly detected with the three indices of γ -butylbetaine, l-carnitine, and trimethylamine oxide, and the results are shown in tables 3 and 4.

TABLE 3 ability of two differential metabolite joint diagnosis to differentiate between patients with heart failure and healthy population

TABLE 4 ability of three differential metabolite combination diagnostics to differentiate patients with heart failure from healthy populations

Three differential metabolite combinations	Specificity of	Sensitivity of the probe	AUC
				Acetyl L-carnitine, gamma-butylbetaine and L-carnitine	96.7％	96.7％	0.991

As shown in Table 3, when acetyl L-carnitine and gamma-butyl betaine are used in combination, the capacity of diagnosing and distinguishing heart failure patients from healthy people can be obviously improved, the AUC is 0.99, and the diagnosis and distinguishing effect is good; when the specificity is 96.7%, the sensitivity is respectively improved from 86.7% and 53.3% in the single detection to 93.3% in the joint detection. When the acetyl L-carnitine and the L-carnitine are jointly applied, the capacity of diagnosing and distinguishing heart failure patients and healthy people can be obviously improved, the AUC is 0.99, and the diagnosis and distinguishing effect is good; when the specificity is 96.7%, the sensitivity is respectively improved from 86.7% and 60% in the single detection to 93.3% in the joint detection. When acetyl L-carnitine and trimethylamine oxide are jointly applied, the capacity of diagnosing and distinguishing heart failure patients from healthy people can be obviously improved, and the AUC is 0.99; the sensitivity is respectively improved from 86.7 percent and 80 percent in single detection to 96.7 percent in joint detection, and the specificity is reduced from 96.7 percent to 93.3 percent.

As shown in table 4, when the three indexes of acetyl l-carnitine, γ -butylbetaine and l-carnitine are used in combination, AUC is closer to 1 than any two combinations, AUC is 0.991, and the diagnosis and differentiation effect is better; when the specificity is 96.7%, the sensitivity is respectively improved from 86.7%, 53.3% and 60% in the single detection to 96.7% in the joint detection. Wherein, the index joint inspection ROC curve model graph refers to fig. 9.

Example 3 validation of selected markers in Heart failure samples in myocardial infarction samples

1. Origin of specimen

After patient consent was obtained, plasma samples of 20 patients with myocardial infarction (troponin > 500pg/mL) were collected, and 30 healthy persons were aged and sexed to patients with myocardial infarction, and blood was collected in the early morning on an empty stomach.

2. The experimental method in example 1 is used for pretreatment and LC-MS/MS on-machine detection of plasma of 20 patients with myocardial infarction and 30 healthy people, and an ROC curve is constructed to further verify the sensitivity and specificity of single or index combination screened from heart failure samples in myocardial infarction samples. From the sensitivity and specificity data automatically derived by the ROC curve method, when the specificity of all the joint test indexes in fixed myocardial infarction was identical to that of all the joint test indexes in heart failure (96.7% in all cases), the sensitivity obtained from the ROC curve was as shown in tables 5 and 6.

TABLE 5 validation of single or two combined differential metabolites in heart failure to differentiate patients with myocardial infarction from healthy population

TABLE 6 validation of the combination of three different metabolites in heart failure in differentiating patients with myocardial infarction from healthy people

As shown in Table 5, the sensitivity of the single index of acetyl-L-carnitine screened from the heart failure sample reaches 86.7% in the heart failure sample and only 25% in the myocardial infarction sample under the condition that the specificity is 96.7%, which indicates that the acetyl-L-carnitine can well distinguish the heart failure sample from the healthy sample, and the myocardial infarction sample has no interference with the acetyl-L-carnitine.

Further, when the acetyl L-carnitine screened in the heart failure sample is detected together with any one index of gamma-butyl betaine, L-carnitine and trimethylamine oxide (the specificity is the same), the sensitivity reaches 93.3%, 93.3% and 96.7% in the heart failure sample, and only 25%, 30% and 40% in the myocardial infarction sample. The method shows that when any index of acetyl L-carnitine, gamma-butyl betaine, L-carnitine and trimethylamine oxide is detected together, a heart failure sample and a health sample can be well distinguished and diagnosed, and a myocardial infarction sample has no interference on the combination of the two indexes.

Further, as shown in table 6, when the three indexes of acetyl l-carnitine, γ -butyl betaine and l-carnitine, which are screened from the heart failure sample, are tested together (the specificity is the same), the sensitivity reaches 96.7% in the heart failure sample, and is only 25% in the myocardial infarction sample. The method shows that the heart failure sample and the health sample can be well distinguished and diagnosed when the three indexes of acetyl L-carnitine, gamma-butyl betaine and L-carnitine are detected together, and the myocardial infarction sample has no interference to the combination of the three indexes.

Example 4: preparation of detection kit

A detection kit is prepared based on the metabolic marker provided by the invention, and the kit comprises the following components: quality control product, isotope internal standard extracting solution, extracting solvent, mobile phase additive A and mobile phase additive B. Preferably, the test kit further comprises a control, a 96-well reaction plate, a 96-well filter plate, instructions, and the like. The kit can be used for detecting the content of four intestinal flora metabolites, namely acetyl L-carnitine, gamma-butyl betaine, L-carnitine and TMAO.

Specifically, in the kit, a reference substance and/or a quality control substance contains acetyl L-carnitine, gamma-butyl betaine, L-carnitine and TMAO, an isotope internal standard extracting solution contains acetyl L-carnitine-D3, gamma-butyl betaine-D9, L-carnitine-D9 and TMAO-D9, the concentrations of the acetyl L-carnitine, the gamma-butyl betaine-D9, the L-carnitine-D9 and the TMAO-D9 are 5 mu M, an extracting solvent comprises a component (i) acetonitrile and a component (ii) acetic acid, the volume ratio (v/v) is 2.0%, a mobile phase additive A is formic acid, and a mobile phase additive B is ammonia water. The kit is stored at 2-8 ℃.

Of course, when designing the detection kit, it is not necessary to completely contain the above-mentioned 4 metabolic markers as a standard, and only a few of them may be used in combination. The standard products can be packaged separately or made into mixture package. The kit is designed based on the metabolic marker provided by the invention, and can be used for diagnosing and distinguishing heart failure patients from healthy people.

In conclusion, the present invention effectively overcomes the disadvantages of the prior art and has high industrial utilization value.

All documents referred to herein are incorporated by reference into this application as if each were individually incorporated by reference. Furthermore, it should be understood that various changes and modifications of the present invention can be made by those skilled in the art after reading the above teachings of the present invention, and these equivalents also fall within the scope of the present invention as defined by the appended claims.