Application of metabolic marker in preparation of product for diagnosing abdominal aortic aneurysm

Abstract

The invention belongs to the technical field of biological medicine, and particularly relates to application of a metabolic marker in preparation of a product for diagnosing abdominal aortic aneurysm. The metabolic marker comprises one or more than two of 5-delta-hydroxybutyl hydantoin, I-alpha-amino acid, PGF2 alpha, D-pyroglutamic acid, nicotine glucuronide, cysteine glutathione disulfide or Trp-P-1. Experiments prove that the metabolic marker has the advantages that the metabolic marker can be applied to the field of biomarkers, and the metabolic marker can be applied to the field of biomarkers; the seven metabolites are independently or jointly used as metabolic markers for diagnosing the abdominal aortic aneurysm and have good specificity and sensitivity.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and specifically relates to the application of metabolic markers in the preparation of products for diagnosing abdominal aortic aneurysms. Background Art

[0002] Metabolomics is an emerging research field downstream of genomics, proteomics and transcriptomics. The metabolome is a quantitative collection of low molecular weight compounds (such as metabolic substrates and products, lipids, small peptides, vitamins and other protein cofactors) produced by metabolism. There are more than 40,000 metabolites in the human body, and their concentrations can provide a snapshot of an individual's current health status.

[0003] The metabolite, 5-δ-hydroxybutyl hydantoin, plays an important role as an intermediate in the synthesis of the essential amino acid lysine. The literature (Patel RN. Enzymatic synthesis of chiral intermediates for Omapatrilat, an antihypertensive drug. Biomol Eng. 2001 Jun; 17(6): 167-82.) discloses that in the enzymatic synthesis of the chiral intermediate of the antihypertensive drug Omapatrilat, the reductive amination reaction of bovine liver glutamate dehydrogenase was used to demonstrate the synthesis and enzymatic conversion of 2-keto-6-hydroxyhexanoic acid 3 to L-6-hydroxynorleucine 2. In order to avoid the lengthy chemical synthesis of keto acid 3, a method was developed in which racemic 6-hydroxydemethylleucine (obtained from the hydrolysis of 5-δ-hydroxybutyl hydantoin) was treated with D-amino acid oxidase derived from pig kidney or variant deltoid muscle, and then reductive amination was performed to increase the yield of the intermediate.

[0004] Metabolite, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butanoic acid (2-Amino-4-[(2-hydroxy-1-oxopropyl)amino]butanoic acid) belongs to the class of organic compounds of I-α-amino acids. In a study by Li et al. (Li T, Liang M, Luo J, Peng X. Metabolites of Clostridium leptum fermenting flaxseedpolysaccharide alleviate obesity in rats. Int J Biol Macromol. 2024Apr;264(Pt1):129907.), it was pointed out that the fermentation broth of flaxseed polysaccharide fermented by Clostridium in vitro was analyzed and found to contain a variety of metabolites, including 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butanoic acid. After intervening obese mice with fermentation broth rich in a variety of metabolites, the weight, abdominal fat ratio and total fat ratio of mice were significantly reduced, and lipid metabolism was improved, proving that the fermentation broth of flaxseed polysaccharide fermented by Clostridium has a significant anti-obesity effect.

[0005] Metabolite, 19(R)-hydroxy-prostaglandin F2α (19(R)-hydroxy PGF2 Alpha) is also known as PGF 2α , a type of prostaglandin, studies have shown that PGF 2α PGF can play a variety of roles in bone metabolism by regulating multiple signaling pathways. 2α It can stimulate the Na-dependent inorganic phosphate transport system in osteocytes by activating PKC, upregulating interleukin (IL)-6 synthesis, increasing vascular endothelial growth factor (VEGF), PGF 2α The molecular mechanism regulating bone metabolism may be a new approach to develop novel targeted therapies for treating bone diseases (see reference: Agas D, Marchetti L, Hurley MM, Sabbieti MG. Prostaglandin F2α: a bone remodeling mediator. J Cell Physiol. 2013 Jan; 228(1): 25-9).

[0006] Metabolites, D-pyroglutamic acid ((R)-(+)-2-Pyrrolidone-5-carboxylic acid) exist in a free form in various body fluids or tissues in the body, and participate in the formation of the amino acid terminal of neuropeptides such as neurotensin and thyrotropin-releasing hormone. Pyroglutamic acid can be converted into each other with glutamate in the body and antagonize glutamate receptors. The literature (Huang Yu, Gu Caiyun, Wu Hanzhong, et al. Metabolomics study of ischemic stroke based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry [J]. Journal of Chemistry in Universities, 2017, 38(10): 1742-1750.) disclosed that pyroglutamic acid, as a cyclized derivative of L-glutamic acid, has a decreasing trend in the plasma of stroke patients, which is related to abnormal glutamine metabolism and can be used as a metabolic marker for the diagnosis and treatment of clinical stroke.

[0007] Metabolites, nicotine glucuronide is a product of nicotine metabolism. Patent CN105891357A points out that nicotine ingested into the body will quickly pass through the blood-brain barrier into the brain tissue, and the body's metabolism of nicotine is mostly completed in the liver. In fact, nicotine can be converted into more than 20 metabolites in the body. Nicotine glucuronide, as one of the metabolites, can trace and detect the metabolic changes of nicotine in animals, and can also be used as a biomarker to measure the degree of human smoke exposure and distinguish smokers from non-smokers.

[0008] The metabolite, cysteine ​​glutathione disulfide, is a molecule formed under glutathione oxidative stress that forms mixed disulfides with protein thiol groups, leading to reversible S-glutathionylation, which is an important post-translational modification responsible for transducing oxidant signals. S, Albanes D. Serum metabolomic profile of hair dye use. Sci Rep. 2023 Mar 7; 13 (1): 3776.) showed that some substances in hair dyes may be related to human metabolism and cancer risk. By comparing the serum metabolites of hair dye users and non-users, it was found that 11 compounds were significantly different between the two groups, among which cysteine ​​glutathione disulfide was significantly correlated with hair dyes, indicating that it can be used as a diagnostic marker for diseases caused by hair dyes.

[0009] The metabolite, tryptophan P1 (Trp-P-1), also known as 3-amino-1,4-dimethyl-5H-pyridyl[4,3-b]indole, belongs to the class of organic compounds called gamma carbolines. Studies have shown that Trp-P-1 is a dietary carcinogen, and its exocyclic amino group is metabolically activated by cytochrome P450 (CYP) 1A and 1B subfamilies to hydroxyamino derivatives. Literature (Bunsyo Shiotani, Hitoshi Ashida, 3-Amino-1,4-dimethyl-5H-pyrido[4,3-b]indole(Trp-P-1) triggers apoptosis by DNA double-strand breaks caused by inhibition of topoisomerase I, Carcinogenesis, Volume 25, Issue 7, July 2004, Pages 1149–1155) In studying the types of DNA damage involved in Trp-P-1-induced apoptosis, high concentrations of Trp-P-1 were used to treat rat liver cells, leading to apoptotic events such as loss of cell activity and nuclear condensation. The results showed that Trp-P-1-induced apoptosis was triggered by DNA DSB through inhibition of topoisomerase I.

[0010] However, there are few reports on the use of metabolomics to analyze abdominal aortic aneurysm, especially the above-mentioned specific metabolites. Summary of the invention

[0011] To make up for the gaps in the prior art, the present invention provides a group of metabolic markers and uses them to diagnose abdominal aortic aneurysm. Specifically, the metabolic markers of abdominal aortic aneurysm are screened out through a discovery cohort, and their diagnostic efficacy is further verified through a validation cohort. The results show that the metabolic markers provided by the present invention have high specificity and sensitivity. The specificity and sensitivity of diagnosis are further improved by combining the use of 7 metabolic markers, and the AUC value can reach 1. The specific scheme is as follows:

[0012] In a first aspect of the present invention, a metabolic marker is provided for use in preparing a product for diagnosing abdominal aortic aneurysm, wherein the metabolic marker comprises 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0013] Preferably, the metabolic markers are 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide and Trp-P-1.

[0014] Preferably, the I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

[0015] In a specific embodiment of the present invention, the metabolic markers are 5-δ-hydroxybutylhydantoin, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0016] In a specific embodiment of the present invention, the metabolic markers are 5-δ-hydroxybutylhydantoin, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid, PGF 2α , D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide and Trp-P-1.

[0017] The PubChem CID of the 5-δ-hydroxybutyl hydantoin is 95514.

[0018] The PubChem CID of the 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butanoic acid is 131751168.

[0019] The PGF 2α , namely 19(R)-hydroxy-prostaglandin F2α (19(R)-hydroxy PGF2 Alpha), whose PubChemCID is 6443315.

[0020] The PubChem CID of the D-pyroglutamic acid ((R)-(+)-2-Pyrrolidone-5-carboxylic acid) is 439685.

[0021] The PubChem CID of the nicotine glucuronide is 3035848.

[0022] The PubChem CID of the cysteine ​​glutathione disulfide is 53477713.

[0023] The PubChem CID of Trp-P-1 (tryptophan P1) is 5284474.

[0024] The metabolic markers are metabolic markers in blood, plasma, serum, saliva, urine, tears, amniotic fluid, cerebrospinal fluid, lymph or feces.

[0025] Preferably, the metabolite marker is a metabolite marker in plasma.

[0026] The products include test kits, test strips, chips or devices.

[0027] The products include reagents for detecting metabolic markers.

[0028] The reagent detects the presence or concentration level (abundance) of a metabolic marker.

[0029] Preferably, the reagents for detecting metabolic markers include reagents used by one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis.

[0030] Preferably, the product also includes reagents for sample processing and / or standards for blood metabolites.

[0031] The diagnosis of abdominal aortic aneurysm includes detecting metabolic markers by one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis.

[0032] Preferably, the chromatography includes one or more of gas chromatography, liquid chromatography, capillary electrophoresis, high performance liquid chromatography or ultra high performance liquid chromatography.

[0033] Preferably, the spectroscopy includes one or more of ultraviolet-visible spectroscopy, infrared spectroscopy, near-infrared spectroscopy, nuclear magnetic resonance spectroscopy, ion mobility spectroscopy or Raman spectroscopy.

[0034] Preferably, the mass spectrometry includes one or more of electron spray ionization mass spectrometry, quadrupole mass spectrometer, ion trap mass spectrometer, matrix-assisted activation desorption / ionization time-of-flight mass spectrometer, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry, MALDI quadrupole-time-of-flight mass spectrometry, electrospray ionization (ESI)-TOF mass spectrometry, ESI ion trap mass spectrometry, ESI triple quadrupole mass spectrometry or Fourier transform ion cyclotron resonance.

[0035] Preferably, the chemical analysis method comprises electrochemical analysis method and / or radiochemical analysis method.

[0036] In a specific embodiment of the present invention, the diagnosis of abdominal aortic aneurysm includes detecting metabolic markers by high performance liquid chromatography.

[0037] The product includes analyzing the concentration level data of metabolic markers using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosting decision tree, xgboost (eXtremeGradient Boosting), lightweight gradient boosting machine, gradient boosting machine, LASSO (Least AbsoluteShrinkage and Selection Operator) or convolutional neural network.

[0038] In a specific embodiment of the present invention, the product includes analyzing the concentration level data of the metabolite markers using the k-nearest neighbor algorithm and the orthogonal partial least squares discriminant analysis method.

[0039] In a specific embodiment of the present invention, the product includes analyzing the concentration level data of metabolic markers using one or more of orthogonal partial least squares discriminant analysis, support vector machine or random forest.

[0040] The abdominal aortic aneurysm (AAA) is a persistent dilatation of the abdominal aorta that exceeds 1.5 times the normal diameter and is located in the abdominal aorta. CT is preferably used as a method for diagnosing abdominal aortic aneurysm.

[0041] A second aspect of the present invention provides a diagnostic model for abdominal aortic aneurysm, the diagnostic model comprising:

[0042] S1: a data receiving unit, wherein the data includes the concentration level of the metabolic marker in the sample;

[0043] S2: a data analysis unit, wherein the data analysis unit includes analyzing the data in S1 using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosted decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO or convolutional neural network;

[0044] The metabolic markers described in S1 include 5-δ-hydroxybutylhydantoin, I-α-amino acids, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0045] Preferably, the I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

[0046] Preferably, the sample is selected from blood, plasma, serum, saliva, urine, tears, amniotic fluid, cerebrospinal fluid, lymph or feces.

[0047] In a specific embodiment of the present invention, the data analysis unit includes using a k-nearest neighbor algorithm and an orthogonal partial least squares discriminant analysis method to analyze the data in S1.

[0048] In a specific embodiment of the present invention, the data analysis unit includes analyzing the data in S1 using one or more of orthogonal partial least squares discriminant analysis, support vector machine or random forest.

[0049] The third aspect of the present invention provides a method for constructing the diagnostic model described in the second aspect.

[0050] In a specific embodiment of the present invention, the construction method comprises:

[0051] 1) Collect blood or plasma from subjects and detect the concentration of metabolic markers;

[0052] 2) Conduct clinical diagnosis on the subjects and divide them into abdominal aortic aneurysm patient group and healthy control group;

[0053] 3) Constructing a diagnosis model based on the detection results of step 1) and the diagnosis results of step 2).

[0054] Preferably, the clinical diagnosis method includes CT (Computed Tomography) examination, digital subtraction angiography, color Doppler ultrasound, magnetic resonance imaging, magnetic resonance angiography or histopathological examination.

[0055] The CT examination includes plain CT, enhanced CT and CT angiography (CTA).

[0056] In a specific embodiment of the present invention, the construction method comprises:

[0057] i) Collect plasma samples from patients with abdominal aortic aneurysm and healthy controls;

[0058] ii): Detect the concentration level of metabolites in the sample and screen out metabolic markers;

[0059] iii): Metabolic marker concentration level data were analyzed using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosted decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO or convolutional neural network.

[0060] The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0061] Preferably, the metabolic markers are 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide and Trp-P-1.

[0062] Preferably, the I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

[0063] A fourth aspect of the present invention provides a use of the diagnostic model described in the second aspect in the preparation of a product for diagnosing abdominal aortic aneurysm.

[0064] In a fifth aspect of the present invention, a kit for diagnosing abdominal aortic aneurysm is provided, wherein the kit comprises a reagent, a test strip or a chip for detecting a metabolic marker, wherein the metabolic marker comprises 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0065] Preferably, the metabolic markers are 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide and Trp-P-1.

[0066] Preferably, the I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

[0067] In a specific embodiment of the present invention, the kit contains 5-δ-hydroxybutylhydantoin, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid, PGF 2α, D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide and Trp-P-1 reagents, test strips or chips.

[0068] The test strip or chip contains molecules that bind to metabolic markers.

[0069] A sixth aspect of the present invention provides a method for diagnosing abdominal aortic aneurysm, wherein the method comprises detecting metabolic markers in a sample from a subject.

[0070] The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0071] The detecting of the metabolite markers in the subject's sample includes detecting the presence or concentration level of the metabolite markers.

[0072] The method includes comparing the concentration level of the detected metabolic marker with a threshold value, wherein the threshold value is obtained in a previous experiment, that is, the threshold value is determined by experiments and data analysis based on the difference in metabolic markers between abdominal aortic aneurysm patients and healthy people.

[0073] If the metabolic markers described in this application are different or significantly different from the threshold (the difference is statistically significant, such as p<0.05, p<0.01, p<0.001, p<0.0001), it is determined to be a disease. For example:

[0074] A) 5-δ-hydroxybutylhydantoin is below a threshold or significantly below a threshold indicating the occurrence of an abdominal aortic aneurysm; and / or,

[0075] B) I-α-amino acid is below the threshold or significantly below the threshold indicating the occurrence of abdominal aortic aneurysm; and / or,

[0076] C)PGF 2α A value below the threshold or significantly below the threshold indicates the occurrence of an abdominal aortic aneurysm; and / or,

[0077] D) D-pyroglutamate is below a threshold or significantly below a threshold indicating the occurrence of an abdominal aortic aneurysm; and / or,

[0078] E) nicotine glucuronide is below a threshold or significantly below a threshold indicating the occurrence of an abdominal aortic aneurysm; and / or,

[0079] F) cysteine ​​glutathione disulfide is below a threshold or significantly below a threshold indicating the occurrence of abdominal aortic aneurysm; and / or,

[0080] G) Trp-P-1 above the threshold or significantly above the threshold indicates the occurrence of abdominal aortic aneurysm.

[0081] The method includes diagnosing abdominal aortic aneurysm by fold change.

[0082] The change fold is the concentration (expression abundance) of the metabolite marker in patients / the concentration (expression abundance) in healthy people.

[0083] The change multiple greater than 1 indicates that the expression of the metabolite marker is increased in patients with abdominal aortic aneurysm, and the change multiple less than 1 indicates that the expression of the metabolite marker is decreased in patients with abdominal aortic aneurysm.

[0084] Preferably, the change multiple is greater than 1.2, and further preferably, the change multiple is greater than 1.5, for example, greater than 1.21, 1.3, 1.4, 1.5, 1.51, 2, 3, 4, 5, 10, 15, 20, 21, 22, 23, 24, 25, 25.2, 25.4, 25.491, 25.5, 26, 30, 35, 40, 50, 60, 80, etc.

[0085] Preferably, the change factor is less than 0.8, and further preferably, the change factor is less than 0.67, for example, less than 0.00001, 0.0001, 0.001, 0.01, 0.02, 0.05, 0.055, 0.06, 0.1, 0.15, 0.17, 0.19, 0.191, 0.2, 0.22, 0.227, 0.25, 0.254, 0.3, 0.352, 0.398, 0.4, 0.5, 0.6, 0.66, 0.67, 0.7, 0.79, 0.799, etc.

[0086] The change factor of the 5-δ-hydroxybutylhydantoin is less than 0.8, preferably less than 0.67, and more preferably 0.055.

[0087] The change factor of the I-α-amino acid is less than 0.8, preferably less than 0.67, and more preferably 0.191.

[0088] The PGF 2α The change factor is less than 0.8, preferably less than 0.67, and more preferably 0.254.

[0089] The change factor of D-pyroglutamic acid is less than 0.8, preferably less than 0.67, and more preferably 0.398.

[0090] The change factor of nicotine glucuronide is less than 0.8, preferably less than 0.67, and more preferably 0.227.

[0091] The change factor of cysteine ​​glutathione disulfide is less than 0.8, preferably less than 0.67, and more preferably 0.352.

[0092] The change factor of Trp-P-1 is greater than 1.2, preferably greater than 1.5, and more preferably 25.491.

[0093] The diagnosing of abdominal aortic aneurysm includes using a cut-off value to assess the risk of abdominal aortic aneurysm.

[0094] The cutoff value of 5-δ-hydroxybutylhydantoin is ≤800, preferably ≤600, for example ≤800, 750, 700, 650, 600, 550, 530, 510, 509, 508.5, 508.4871, 508, 500, 450, 400, etc.

[0095] The cutoff value of the I-α-amino acid is ≤1800, preferably ≤1500, for example ≤1800, 1700, 1600, 1500, 1480, 1475, 1473, 1471, 1470.5, 1470.3784, 1470, 1400, 1200, 1000, 800, etc.

[0096] The PGF 2α The cutoff value is ≤500, preferably ≤300, for example ≤500, 450, 400, 350, 300, 250, 230, 220, 218, 216, 215.8, 215.6347, 215, 210, 200, 180, 160, 140, etc.

[0097] The cutoff value of D-pyroglutamic acid is ≤6000, preferably ≤5800, for example ≤6000, 5900, 5800, 5700, 5600, 5590, 5560, 5550, 5540, 5535, 5530.901, 5530, 5500, 5200, 5000, etc.

[0098] The cutoff value of nicotine glucuronide is ≤800, preferably ≤500, for example ≤800, 750, 700, 650, 600, 550, 500, 450, 430, 410, 409, 408.3321, 408, 405, 400, 350, 300, etc.

[0099] The cutoff value of cysteine ​​glutathione disulfide is ≤4000, preferably ≤3800, for example ≤4000, 3900, 3800, 3700, 3600, 3500, 3490, 3480, 3475, 3470.707, 3470, 3450, 3400, etc.

[0100] The cutoff value of Trp-P-1 is >300, preferably >400, for example >301, 310, 350, 400, 420, 440, 460, 480, 484, 486, 486.8928, 488, 490, 500, 550, 600, 650, 700, etc.

[0101] Preferably, the detection method can be selected from chromatography, spectroscopy, mass spectrometry or chemical analysis.

[0102] The method comprises analyzing the metabolic marker concentration level data using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosting decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO or convolutional neural network.

[0103] Preferably, the method comprises using the diagnostic model described in the second aspect or the kit described in the fifth aspect to diagnose abdominal aortic aneurysm.

[0104] A seventh aspect of the present invention provides a system for diagnosing abdominal aortic aneurysm, the system comprising a device, unit or module for determining whether a subject suffers from abdominal aortic aneurysm based on the concentration of a metabolic marker.

[0105] Preferably, the diagnostic system comprises:

[0106] A data detection device, unit or module for detecting the concentration level of a metabolic marker in a sample;

[0107] a data input device, unit or module for inputting concentration level data of metabolic markers;

[0108] a data analysis device, unit or module for calculating the risk of abdominal aortic aneurysm based on the concentration level data of the metabolic marker;

[0109] A data output device, unit or module is used to output the analysis result of whether an individual suffers from abdominal aortic aneurysm.

[0110] The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0111] Implementation of the diagnostic system may include manually and / or automatically performing or completing selected tasks.

[0112] The diagnostic system may perform tasks via software and / or hardware.

[0113] The present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0114] An eighth aspect of the present invention provides a device, wherein the device comprises the diagnostic system described in the seventh aspect.

[0115] The ninth aspect of the present invention provides a reagent for detecting metabolic markers or the use of the diagnostic system described in the seventh aspect in the preparation of a product for diagnosing abdominal aortic aneurysm.

[0116] The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

[0117] Preferably, the metabolic markers are 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide and Trp-P-1.

[0118] Preferably, the I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

[0119] The reagent detects the presence or concentration level (abundance) of a metabolic marker.

[0120] Preferably, the reagents for detecting metabolic markers include reagents used by one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis.

[0121] The term "diagnosis" as used herein refers to finding out whether a patient has had a disease or condition in the past, at the time of diagnosis, or in the future, or to finding out the progression of a disease or its possible future progression.

[0122] The "subject" may be a human or non-human animal, including "patients", "suspected patients" and "healthy individuals", etc. This term does not indicate a specific age or gender, and covers adult or newborn subjects and fetuses. The non-human animal may be a wild animal, a zoo animal, an economic animal, a pet, an experimental animal, etc. Preferably, the non-human animal includes but is not limited to pigs, cattle, sheep, horses, donkeys, foxes, raccoon dogs, minks, camels, dogs, cats, rabbits, mice (e.g., rats, mice, guinea pigs, hamsters, gerbils, chinchillas, squirrels) or monkeys, etc.

[0123] The "healthy controls" refer to subjects or a group of subjects diagnosed by doctors as not having abdominal aortic aneurysm based on qualitative or quantitative test results. The method includes the clinical diagnosis method of the present invention.

[0124] The "cut-off value" is the boundary value used to determine the positive and negative results of a test, that is, to determine the normal value of a certain indicator to distinguish between normal and abnormal. The most commonly used method for determining the cut-off value is the receiver operating characteristic curve (ROC curve). For example, in risk assessment, the cut-off value is used to determine the range of high risk.

[0125] Beneficial effects of the present invention:

[0126] (1) The present invention uses metabolomics to analyze the metabolic markers of abdominal aortic aneurysm. The metabolomics is downstream of the transcriptome and proteome. Any changes from the normal state will be amplified, and the values ​​are easier to handle, the detection is more sensitive, and the test results are more scientific.

[0127] (2) Based on the discovery cohort, the present invention screened out 85 metabolites with significant differences between patients with abdominal aortic aneurysm and healthy people, and combined MetaboAnalyst and MedCalc software to perform metabolite ROC analysis, and screened out 7 metabolites with better diagnostic effects as metabolic markers for diagnosing abdominal aortic aneurysm, namely 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide, and Trp-P-1.

[0128] (3) To verify the effectiveness of metabolite markers in the diagnosis of abdominal aortic aneurysm, non-targeted metabolomics analysis was performed on the 7 metabolite markers screened in the validation cohort. The diagnostic performance of the metabolite markers was analyzed using the ROC curve. The results showed that the AUCs of the 7 metabolite markers were all greater than 0.88, and all had good specificity and sensitivity.

[0129] (4) The present invention further uses a combination of seven metabolites as a marker for diagnosing abdominal aortic aneurysm, and analyzes the combination using MetaboAnalyst. The results show that the combination has a good diagnostic effect, with an AUC of 1. BRIEF DESCRIPTION OF THE DRAWINGS

[0130] Figure 1 :CT angiography results in patients with abdominal aortic aneurysm.

[0131] Figure 2 : Abundance of 5-δ-hydroxybutylhydantoin in abdominal aortic aneurysms and healthy subjects, **** represents p<0.0001.

[0132] Figure 3 : Abundance of 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid in patients with abdominal aortic aneurysm and healthy subjects, **** represents p<0.0001.

[0133] Figure 4 :PGF 2α Abundance plots in abdominal aortic aneurysm patients and healthy subjects, **** represents p < 0.0001.

[0134] Figure 5 : Abundance of D-pyroglutamate in patients with abdominal aortic aneurysm and healthy subjects, **** represents p<0.0001.

[0135] Figure 6 : Abundance of nicotine glucuronide in patients with abdominal aortic aneurysm and healthy subjects, **** represents p<0.0001.

[0136] Figure 7 : Abundance of cysteine ​​glutathione disulfide in patients with abdominal aortic aneurysm and healthy subjects, **** represents p < 0.0001.

[0137] Figure 8 : Abundance diagram of Trp-P-1 in patients with abdominal aortic aneurysm and healthy subjects, *** represents p<0.001, and the actual P value is 0.0004.

[0138] Fig. 9 : ROC curve of 5-δ-hydroxybutylhydantoin in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0139] Fig.10 : ROC curve of 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0140] Fig.11 :PGF 2α ROC curve in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0141] Fig.12 : ROC curve of D-pyroglutamate in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0142] Fig.13 : ROC curve of nicotine glucuronide in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0143] Fig.14 : ROC curve of cysteine ​​glutathione disulfide in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0144] Fig.15 : ROC curve of Trp-P-1 in the diagnosis of abdominal aortic aneurysm, where standard represents the cut-off value.

[0145] Fig.16 :5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α ROC curve of the combination of , D-pyroglutamate, nicotine glucuronide, cysteine ​​glutathione disulfide and Trp-P-1 in the diagnosis of abdominal aortic aneurysm, where CI represents confidence interval. DETAILED DESCRIPTION

[0146] The present invention is further described below in conjunction with the embodiments. The following description is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change it into an equivalent embodiment with equivalent changes. Any simple modification or equivalent change made to the following embodiments based on the technical essence of the present invention without departing from the content of the present invention falls within the protection scope of the present invention.

[0147] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0148] The reagents, materials, etc. used in the following examples, unless otherwise specified, can be obtained from commercial sources. The subjects, instruments or equipment involved in the examples are as follows:

[0149] 1. Diagnosis of subjects: All subjects underwent a preoperative abdominal aortic CT examination to determine whether they had abdominal aortic aneurysm. That is, CT examination was performed on patients with abdominal aortic aneurysm ( Figure 1 ), the results showed that the diameter of the abdominal aorta in patients with abdominal aortic aneurysm was 1.5 times greater than that of the normal aorta.

[0150] 2. Collection and analysis of plasma from subjects: Obtain plasma samples from patients with abdominal aortic aneurysm and compare the metabolite expression with that of control plasma, where the control is healthy subjects without abdominal aortic aneurysm.

[0151] The specific materials, reagents, and collection methods for plasma collection and analysis of metabolite expression are as follows:

[0152] (1) Instruments:

[0153] LTQ Orbitrap velos mass spectrometer was purchased from Thermo Fisher Scientific; ultra-high performance liquid chromatography ACQUITY H-class LC system was purchased from Waters.

[0154] (2) Reagents:

[0155] Chromatographic grade acetonitrile and methanol were produced by Waters; ammonium acetate was purchased from Sigma; and ammonia was purchased from Fisher Chemical.

[0156] (3) Sample collection process: Plasma samples from abdominal aortic aneurysm patients and controls were collected using EDTA-anticoagulated blood collection tubes, centrifuged at 2000 g for 10 min at 4°C, and the supernatant was aspirated and stored in a -80°C refrigerator.

[0157] Example 1: Screening for metabolic markers of abdominal aortic aneurysm

[0158] 1. The discovery cohort included 30 patients with confirmed abdominal aortic aneurysm (n=30, 25 males and 5 females, with an average age of 67.8 years) and 30 healthy controls without abdominal aortic aneurysm (n=30, 24 males and 6 females, with an average age of 66.2 years).

[0159] 2. Experimental process: First, H 2 O (150 μl) was added to each plasma sample (50 μl) and vortexed for 30 seconds. Then, acetonitrile (400 μl) was added to each sample and vortexed for 1 minute. After standing at -20 ° C for 60 minutes, the sample was centrifuged at 14000 × g for 10 minutes to remove plasma proteins. The supernatant was then dried under vacuum and reconstituted with 100 μl 2% acetonitrile. Plasma metabolites were further separated from small protein molecules using a 10 kDa molecular weight cutoff ultracentrifugal filter (Millipore Amicon Ultra, MA). Quality control (QC) samples were prepared by mixing equal aliquots of all plasma samples. During the entire analytical run, QC samples were injected once every ten samples to evaluate the stability and repeatability of the analytical process.

[0160] Metabolomics analysis was performed using a Waters ACQUITY H-class LC system coupled to a LTQ Orbitrap velos mass spectrometer (ThermoFisher Scientific, MA). Plasma metabolites were separated on a Waters HSS C18 column with an 18-min gradient at a flow rate of 500 μl / min. Mobile phase A was 0.1% formic acid in water and mobile phase B was acetonitrile. The gradient elution program was as follows: 0–1 min, 2% solvent B; 1–3 min, 2%–55% solvent B; 3–8 min, 55%–100% solvent B; 8–13 min, 100% solvent B; 13–13.1 min, 100%–2% solvent B; 13.1–18 min, 2% solvent B. Full MS acquisition was performed by scanning from 100 to 1000 m / z at a resolution of 60 K. The automatic gain control (AGC) target was set to 1 × 10 6 The maximum injection time was 100 ms. For each target with high-energy collisional dissociation (HCD) fragmentation, the collision energy was optimized to 20, 40, and 60.

[0161] 3. Data analysis: Progenesis QI software (Waters) was used to process the raw data files, including peak alignment, peak picking, peak grouping, deconvolution, and normalization by total compounds. The exported feature files were imported into MetaboAnalyst (http: / / www.metaboanalyst.ca) for further analysis. Variables missing in more than 50% of the samples were removed from further statistical analysis, and the missing values ​​were filled by the k-nearest neighbor algorithm (KNN algorithm). Orthogonal partial least squares discriminant analysis (OPLS-DA) was performed using SIMCA14.1 (Umetrics) software. Permutation tests were performed to validate the OPLS-DA model to avoid overfitting. Differentially enriched metabolites were identified according to the following criteria: P value <0.05; fold change >1.5 or <0.67. Differentially enriched metabolites were analyzed using the enrichment and pathway analysis modules in MetaboAnalyst 6.0. Receiver operating characteristic curve (ROC) analysis was performed using the “Biomarker Analysis” module on the MetaAnalyst website and MedCalc software.

[0162] 4. Filter results

[0163] By performing non-targeted metabolite detection on plasma samples of patients with abdominal aortic aneurysm and healthy controls in the discovery cohort, 85 metabolites with differential expression with a change fold greater than 1.5 or less than 0.67 and a p value < 0.05 were screened. MetaboAnalyst (http: / / www.metaboanalyst.ca) and MedCalc software (Statistical Software version 23.0.2 (MedCalc Software Ltd, Ostend, Belgium; https: / / www.medcalc.org; 2024)) were used for metabolite ROC analysis, and 7 metabolites with high AUC values ​​were screened out, 7 potential candidate diagnostic metabolic markers for AAA, and their AUC values ​​are shown in Table 1.

[0164] Table 1: Candidate metabolic biomarkers in patients with abdominal aortic aneurysm

[0165]

[0166]

[0167] Example 2: Validation of plasma metabolic markers in AAA diagnosis

[0168] To further validate the value of the screened metabolite markers in the diagnosis of abdominal aortic aneurysm, non-targeted metabolomics analysis was performed in a new validation cohort.

[0169] The validation cohort included 46 AAA patients (n=46, 40 males and 6 females, with an average age of 70.4 years) and 42 healthy controls (n=42, 36 males and 6 females, with an average age of 67.6 years), and the abundance of the above-mentioned metabolite markers in patients with abdominal aortic aneurysm and healthy controls was detected. Sample collection, processing and experimental procedures were the same as in Example 1.

[0170] The results are as follows Figure 2-8 As shown, 5-δ-hydroxybutylhydantoin, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid, PGF 2α The abundance of , D-pyroglutamic acid, nicotinic acid glucuronide, and cysteine ​​glutathione disulfide in patients with abdominal aortic aneurysm was significantly lower than that in healthy controls, and the abundance of Trp-P-1 in patients with abdominal aortic aneurysm was significantly higher than that in healthy controls. Statistical analysis was performed using GraphPad Prism version 10.3.0 for Windows, GraphPad Software, Boston, Massachusetts USA, www.graphpad.com.

[0171] The ROC curve of the above-mentioned metabolic markers in distinguishing abdominal aortic aneurysm patients from healthy controls was drawn (the experimental process and data analysis were the same as in Example 1).

[0172] According to ROC curve analysis, the AUC value of 5-δ-hydroxybutylhydantoin was 0.996, the sensitivity was 93.48%, and the specificity was 100.00% ( Fig. 9 ); the AUC value of 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid was 0.987, the sensitivity was 97.83%, and the specificity was 92.86% ( Fig.10 );PGF 2α The AUC value was 0.993, the sensitivity was 95.65%, and the specificity was 100.00% ( Fig.11 ); the AUC value of D-pyroglutamate was 0.971, the sensitivity was 86.96%, and the specificity was 95.24% ( Fig.12 ); the AUC value of nicotine glucuronide was 0.887, the sensitivity was 93.48%, and the specificity was 80.95% ( Fig.13 ); the AUC value of cysteine ​​glutathione disulfide was 0.905, the sensitivity was 76.09%, and the specificity was 95.24% ( Fig.14 ); the AUC value of Trp-P-1 was 0.921, the sensitivity was 89.13%, and the specificity was 90.48% ( Fig.15 ), the diagnostic performance of each metabolic marker is shown in Table 2.

[0173] Table 2: Diagnostic performance of metabolic markers

[0174]

[0175]

[0176] The “BiomarkerAnalysis” module in MetaboAnalyst (http: / / www.metaboanalyst.ca) was used to analyze 5-δ-hydroxybutylhydantoin, 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid, and PGF 2α The combination of these seven metabolic markers, cysteine ​​glutathione disulfide, D-pyroglutamic acid, nicotinic acid glucuronide, cysteine ​​glutathione disulfide, and Trp-P-1, showed a good diagnostic effect for abdominal aortic aneurysm, with an area under the ROC curve (AUC) value of 1.000 ( Fig.16 ).

Claims

1. Use of a metabolic marker in the preparation of a product for diagnosing abdominal aortic aneurysm, characterized in that: The metabolic markers include I-α-amino acids, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

2. The use according to claim 1, characterized in that: The I-α-amino acid is 2-amino-4-[(2-hydroxy-1-oxopropyl)amino]butyric acid.

3. The use according to claim 1, characterized in that: The metabolic markers are metabolic markers in blood, plasma, serum, saliva, urine, tears, amniotic fluid, cerebrospinal fluid, lymph or feces.

4. The use according to claim 1, characterized in that: The products include test kits, test strips, chips or devices; Preferably, the product includes a reagent for detecting a metabolic marker, and the reagent detects the presence or concentration level of the metabolic marker; Preferably, the product comprises analyzing concentration level data of metabolic markers using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosted decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO or convolutional neural network.

5. The use according to claim 1, characterized in that: The diagnosis of abdominal aortic aneurysm includes detecting metabolic markers by one or more of chromatography, spectroscopy, mass spectrometry or chemical analysis.

6. A diagnostic system for abdominal aortic aneurysm, characterized in that: The diagnostic system includes a device, unit or module for determining whether the subject suffers from abdominal aortic aneurysm based on the concentration of the metabolite marker; The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , one or more of D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1; Preferably, the diagnostic system comprises: A data detection device, unit or module for detecting the concentration level of a metabolic marker in a sample; a data input device, unit or module for inputting concentration level data of metabolic markers; a data analysis device, unit or module for calculating the risk of abdominal aortic aneurysm based on the concentration level data of the metabolic marker; A data output device, unit or module is used to output the analysis result of whether an individual suffers from abdominal aortic aneurysm.

7. A method for constructing a diagnostic model, characterized in that: The construction method comprises: i) Collect plasma samples from patients with abdominal aortic aneurysm and healthy controls; ii): Detect the concentration level of metabolites in the sample and screen out metabolic markers; iii) Analyze the metabolic marker concentration level data using one or more of orthogonal partial least squares discriminant analysis, classification and logistic regression, k-nearest neighbor algorithm, naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosted decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO or convolutional neural network; The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

8. A method for constructing a diagnostic model, characterized in that: The construction method comprises: 1) Collect blood or plasma from subjects and detect the concentration of metabolic markers; 2) Conduct clinical diagnosis on the subjects and divide them into abdominal aortic aneurysm patient group and healthy control group; 3) constructing a diagnostic model based on the detection results of step 1) and the diagnosis results of step 2); The metabolic markers include 5-δ-hydroxybutylhydantoin, I-α-amino acid, PGF 2α , D-pyroglutamic acid, nicotine glucuronide, cysteine ​​glutathione disulfide or Trp-P-1, or two or more thereof.

9. A diagnostic model obtained by the construction method according to claim 7 or 8.

10. Use of the diagnostic system according to claim 6, the construction method according to claim 7 or 8, or the diagnostic model according to claim 9 in preparing a product for diagnosing abdominal aortic aneurysm.

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