Metabolite combination for evaluating risk of biliary atresia in neonates and use thereof

Abstract

Disclosed in the present invention are a metabolite combination for evaluating the risk of biliary atresia in neonates and a use thereof. The metabolite combination comprises one or more of the following: hyocholic acid, pyroglutamic acid, α-aminobutyric acid, 3-methyl-2-oxovaleric acid and monoconjugated bilirubin, and the metabolite combination cannot only contain one metabolite of monoconjugated bilirubin. The metabolite combination has relatively high correlation with biliary atresia, and has high accuracy, sensitivity and specificity for evaluation of the risk of biliary atresia in neonates.

Description

Metabolite combination for evaluating risk of biliary atresia in newborns and application thereof

[0001] This application claims priority to Chinese patent application 2024106425865 with a filing date of 2024 / 5 / 23. This application incorporates the entirety of the aforementioned Chinese patent application. TECHNICAL FIELD

[0002] The present application relates to the field of biological medical technology, in particular to a metabolite combination for evaluating risk of biliary atresia in newborns and application thereof. BACKGROUND

[0003] Biliary atresia (BA), a progressive, idiopathic extrahepatic biliary system disease occurring in the neonatal period, is a destructive inflammatory fibrotic obstruction of the neonatal bile duct, affecting the intrahepatic and extrahepatic bile ducts of different lengths, and is the main cause of obstructive jaundice in newborns and the main cause of pediatric liver transplantation.

[0004] Kasai radical operation (hepatojejunostomy) is the preferred treatment for biliary atresia. The operation time has a great influence on the efficacy of Kasai operation. Studies have found that Kasai operation within 30 or 45 days after birth can significantly increase the postoperative jaundice disappearance rate and five-year autologous liver survival rate, and significantly reduce the demand for liver transplantation. Unfortunately, biliary atresia cannot be diagnosed in time at present, and the general operation time is after 2 months after birth.

[0005] The current screening and diagnostic serological markers for biliary atresia include: ①serum total bilirubin and direct bilirubin; as the first screening marker. Neonatal serum total bilirubin > 2.0 mg / dL (42-51 μmol / L), or direct bilirubin > 1.0 mg / dL (17 μmol / L) need to be screened for biliary atresia, but the specificity for diagnosing biliary atresia is poor; ②GGT: large sample survey showed that in different age groups, the GGT content of biliary atresia group was significantly higher than that of other cholestasis disease groups [Chen X, et al. The value of γ-GT combined with age in the diagnosis of biliary atresia. Journal of Pediatric Gastroenterology and Nutrition, 2016, 63(3): 370-373]. Liu et al [Liu et al. The value of γ-GT in the early diagnosis of biliary atresia. Chinese Medical Journal, 1998, 61(12): 716-720] reported that when GGT > 300 U / L, the accuracy of diagnosing biliary atresia was 60%-85%. GGT is the most commonly used screening marker for biliary atresia, but the accuracy is limited due to the large difference between different patients in clinical cases; ③Other markers: serum cholic acid, prothrombin concentration, platelet determination have many influencing factors. In imaging examination, abnormal gallbladder (gallbladder shrinkage, poor contraction) and hepatic portal fibrous mass are the characteristic manifestations of liver in children with biliary atresia [Tan et al. Diagnosis of biliary atresia using hepatic portal fibrous mass and gallbladder length. Pediatric Radiology, 2000, 30(2): 69-73], but the hepatic portal fibrous mass does not necessarily appear in every patient, and the observation results of ultrasound examination are different due to different doctors, machines, etc. Therefore, the sensitivity and specificity of diagnosing biliary atresia reported in the literature are different. Recently, a Meta analysis reported that the specificity of gallbladder atresia and hepatic portal fibrous mass can reach 99%, but the corresponding sensitivity is 28% and 80% [Liu et al. The value of γ-GT in the early diagnosis of biliary atresia. Chinese Medical Journal, 1998, 61(12): 716-720]. Other examinations can provide some clues for the diagnosis of biliary atresia, but are limited to different degrees. For example, duodenal fluid detection is difficult to operate; radioactive isotope examination can aggravate the obstructive jaundice of the patient to different degrees [El-Guindi et al. Design and validation of a diagnostic scoring system for biliary atresia. Journal of Pediatric Gastroenterology and Nutrition, 2014, 61(1): 116-123]; for infants under 3 months of age, the diameter of the bile duct is small and the fluid in the bile duct is small, so the high false positive rate of magnetic resonance cholangiopancreatography examination in diagnosing biliary atresia is inevitable. In addition, the pathological features of biliary atresia are small bile duct proliferation, bile thrombosis, capillary bile duct and hepatocyte cholestasis, and fibrosis around the hepatic portal or lobule. The early liver lobule structure can still be seen. Therefore, when applied in the differentiation of biliary atresia and other neonatal cholestasis, the low accuracy or complex process of the detection leads to the delay of the diagnosis and treatment of biliary atresia.At the early stage of the disease, the clinical manifestations, biochemical indicators, imaging and histological features of BA overlap with other cholestatic diseases, and the differential diagnosis process is tortuous and complex, which can easily lead to delayed diagnosis. Therefore, the exploration of simple and specific diagnostic methods has never stopped.

[0006] Due to the lack of effective diagnostic markers, children often need to undergo a long and complex diagnostic process to be diagnosed, which delays the best surgery time. Chinese patent document CN101221129B discloses a sulfated bile acid enzyme fluorescence capillary analysis method and enzyme fluorescence quantitative kit, which is suitable for rapid screening and diagnosis of hepatobiliary diseases, especially for early detection of neonatal jaundice and congenital biliary atresia. Chinese patent document CN113533596A discloses early screening markers of neonatal biliary atresia, glutamic acid, taurine, taurocholic acid, indoleacetic acid, alpha-ketoisovaleric acid, ketoleucine, 2-hydroxyglutaric acid and glycocholic acid, which are suitable for rapid screening and diagnosis of hepatobiliary diseases, especially for early detection of neonatal jaundice and congenital biliary atresia. The patent shows that the AUC of the 8-index combined model reaches 0.945, the sensitivity is 91%, and the specificity is 90.5%. For screening products, the specificity is low, which can easily produce a large number of false positives, and it is difficult to use in clinical practice. SUMMARY

[0007] In order to solve the technical problem of lack of high specificity, high efficiency and stable screening of metabolites of neonatal biliary atresia in the prior art, the present application provides a metabolite for evaluating the risk of neonatal biliary atresia and its application.

[0008] The "risk" refers to whether the neonate has "biliary atresia"; the output of the risk evaluation by the method of the present application is a qualitative statement of "yes" or "no" compared with a pre-set standard value (i.e. cutoff value, optimal evaluation threshold).

[0009] The present application finds that the combination of 4 metabolites (hyocholic acid, pyroglutamic acid, alpha-aminobutyric acid and 3-methyl-2-oxovaleric acid) in dry blood spots combined with single bilirubin can be used for birth screening and early diagnosis of biliary atresia, so as to diagnose and operate early and maximize the prognosis.

[0010] The present application provides a metabolite combination for screening biliary atresia, its use in preparing a biliary atresia screening product, a kit and a computer system, which has the advantages of high sensitivity, high specificity and / or high detection throughput in biliary atresia birth screening.

[0011] In order to achieve the above-mentioned application purposes, the present application specifically provides the following technical solutions:

[0012] The present application discloses a metabolite combination for evaluating the risk of neonatal biliary atresia, the metabolite combination comprising one or more of the following: hyodeoxycholic acid, pyroglutamic acid, alpha-aminobutyric acid, 3-methyl-2-oxovaleric acid and monoconjugated bilirubin, and the metabolite combination containing only monoconjugated bilirubin as one metabolite.

[0013] In some embodiments, the metabolite combination consists of hyodeoxycholic acid, pyroglutamic acid, alpha-aminobutyric acid, 3-methyl-2-oxovaleric acid and monoconjugated bilirubin.

[0014] In some embodiments, the metabolite combination is from a biological sample of a neonate, the biological sample being whole blood, plasma, serum and dried blood spot.

[0015] In some preferred embodiments, the biological sample is a dried blood spot.

[0016] The present application discloses a reagent for detecting the metabolite combination as described in the first aspect of the present application, the reagent being used for detecting the concentration of the metabolite combination; the concentration being obtained by quantitatively detecting the metabolite combination in a biological sample of a neonate after processing the biological sample by liquid chromatography-mass spectrometry (LC-MS / MS) method.

[0017] In some embodiments, the reagent is a high-performance liquid chromatography reagent for detecting the concentration of the metabolite combination; the processing of the biological sample of a neonate is extracting the metabolites in the biological sample as a detection sample using a sample extraction solution, the detection sample being an organic solvent dispersion system of the biological sample, the biological sample being whole blood, plasma, serum or dried blood spot.

[0018] In some embodiments, the organic solvent of the organic solvent dispersion system is methanol, ethanol, propanol, propylene glycol or acetonitrile; the biological sample is a dried blood spot.

[0019] In some specific embodiments, the liquid chromatography is high-performance liquid chromatography (HPLC), ultra-high-performance liquid chromatography (UPLC) or nanoliter liquid chromatography (Nano-LC), and the tandem mass spectrometry is quadrupole mass spectrometry (Quadrupole, Q), time-of-flight mass spectrometry (Time of Flight, TOF), ion trap mass spectrometry (Ion Trap) or high-resolution orbitrap mass spectrometry (Orbitrap).

[0020] In some embodiments, the separation condition of the liquid chromatography comprises: mobile phase A is an aqueous solution containing an additive selected from any one or a combination of ammonium formate, ammonium acetate, formic acid and acetic acid; mobile phase B is selected from one or a combination of isopropanol, methanol, acetonitrile, ethanol and propylene glycol; the chromatographic column is selected from a T3, C8 or C18 silica gel packing column, the column temperature is set to 25-45°C, and the flow rate is 0.2-0.6 ml / min; the detection condition of the mass spectrometry comprises: data acquisition is performed in a triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode, characteristic ion pair information of metabolites is selected, standard samples are used for information confirmation and detection method establishment, and internal standard samples are used for quantitative correction to obtain accurate concentration values and related ratio values of each metabolite in the biological sample. As an exemplary embodiment, the separation condition of the liquid chromatography can comprise: injection of 5 μl, mobile phase A is 5 mmol of formic acid aqueous solution, mobile phase B is 10% isopropanol + 10% methanol + 80% acetonitrile, the chromatographic column is a 100 mm HSS T3 column, the column temperature is set to 40°C, the flow rate is 0.3 mL / min, 0-1.0 min maintains 4% B, 1.0-3.0 min linearly changes from 4% B to 50% B, 3.0-6.0 min linearly changes from 50% B to 80% B, 6.0-6.5 min linearly changes from 80% B to 100% B, 6.5-8.0 min maintains 100% B, and 8.0-9.0 min linearly changes from 100% B to 4% B.

[0021] In some embodiments, the mass spectrometry is selected from quadrupole mass spectrometry, time-of-flight mass spectrometry, ion hydrazine mass spectrometry and high-resolution orbit hydrazine mass spectrometry; the condition and setting of the mass spectrometry are qualitative and quantitative detection modes of mass spectrometry, which comprise: selecting an electrospray ion source (ESI), selecting an ion scanning mode according to the response of the detected target compound; data acquisition is performed in a triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode, characteristic ion pair information of metabolites is selected, standard samples are used for information confirmation and detection method establishment, and internal standard samples are used for quantitative correction to obtain accurate concentration values and related ratio values of each metabolite in the biological sample.

[0022] The third aspect of the present application discloses a kit comprising the metabolite combination according to the first aspect of the present application and / or the reagent according to the second aspect of the present application.

[0023] In some embodiments, the kit further comprises a reagent for extracting metabolites.

[0024] In some embodiments, the reagent for extracting metabolites is a mixture of an organic solvent and water.

[0025] In some embodiments, the organic solvent is selected from one or more of isopropanol, methanol and acetonitrile.

[0026] In some embodiments, the kit comprises an isotopic internal standard. By isotopic internal standard is meant a stable isotope-labeled metabolite, such as deuterium substitution.

[0027] The fourth aspect of the present application discloses the use of the metabolite combination according to the first aspect of the present application, the reagent according to the second aspect of the present application or the kit according to the third aspect of the present application in the preparation of a product for evaluating whether a newborn has biliary atresia;

[0028] The use is the use of porcine cholic acid and / or a reagent for detecting porcine cholic acid in the preparation of a kit for evaluating whether a newborn has biliary atresia; and / or,

[0029] The use is the use of pyroglutamic acid and / or a reagent for detecting pyroglutamic acid in the preparation of a kit for evaluating whether a newborn has biliary atresia; and / or,

[0030] The use is the use of alpha-aminobutyric acid and / or a reagent for detecting alpha-aminobutyric acid in the preparation of a kit for evaluating whether a newborn has biliary atresia; and / or,

[0031] The use is the use of 3-methyl-2-oxovaleric acid and / or a reagent for detecting 3-methyl-2-oxovaleric acid in the preparation of a kit for evaluating whether a newborn has biliary atresia.

[0032] The fifth aspect of the present application provides a computer-aided method for evaluating the risk of biliary atresia in a newborn, the method comprising the following steps:

[0033] Step 1: receiving or inputting the concentration information of the metabolite combination in the biological sample of the newborn, wherein the metabolite combination is the metabolite combination according to the first aspect of the present application;

[0034] Step 2: inputting the concentration of the metabolite combination received or inputted in step 1 into formula 1, and outputting the evaluation result of whether the newborn has biliary atresia from the biological sample;

[0035] The formula 1 is: P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9; wherein C1 is the concentration value of pyroglutamic acid in the biological sample expressed in the concentration unit of μM, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample expressed in the concentration unit of μM, C3 is the concentration value of alpha-aminobutyric acid in the biological sample expressed in the concentration unit of μM, C4 is the concentration value of porcine cholic acid in the biological sample expressed in the concentration unit of μM, and C5 is the concentration value of monobound bilirubin in the biological sample expressed in the concentration unit of μM;

[0036] The judgment standard of the evaluation result is that when P is greater than or equal to an optimal evaluation threshold value, the output evaluation result is that the newborn has biliary atresia; and when P is less than the optimal evaluation threshold value, the output evaluation result is that the newborn does not have biliary atresia; the optimal evaluation threshold value is a cutoff value, and the optimal evaluation threshold value is preferably 0.

[0037] The "risk" refers to whether the newborn has "biliary atresia".

[0038] The sixth aspect of the present application discloses a system for evaluating the risk of biliary atresia in a newborn, wherein the system comprises:

[0039] (1) An information acquisition module for receiving or inputting the concentration information of a metabolite combination in a newborn biological sample, wherein the metabolite combination is the metabolite combination according to the first aspect of the present application.

[0040] (2) A biliary atresia disease risk evaluation module for evaluating whether the newborn has biliary atresia according to the concentration of the metabolite combination; the evaluation is realized by inputting the concentration of the metabolite combination received or inputted by the information acquisition module into formula 1 to output the evaluation result of whether the newborn from which the biological sample is derived has biliary atresia;

[0041] The formula 1 is P=C1*0.448+C2*0.834+C3*0.7-C4*879+C5*69.6-84.9; wherein C1 is the concentration value of pyroglutamic acid in the biological sample, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, C3 is the concentration value of alpha-aminobutyric acid in the biological sample, C4 is the concentration value of hyocholic acid in the biological sample, and C5 is the concentration value of monobound bilirubin in the biological sample, wherein the concentration unit of each metabolite is μM;

[0042] The judgment standard of the evaluation result is that when P is greater than or equal to an optimal evaluation threshold value, the output evaluation result is that the newborn has biliary atresia; and when P is less than the optimal evaluation threshold value, the output evaluation result is that the newborn does not have biliary atresia; the optimal evaluation threshold value is a cutoff value, and the optimal evaluation threshold value is preferably 0.

[0043] In some embodiments, the system further comprises one or more of the following modules:

[0044] (3) A sample pretreatment module for precipitating proteins to extract target metabolites in a detection sample; the detection sample is an organic solvent dispersion system of a biological sample, and the organic solvent of the organic solvent dispersion system is methanol, ethanol, propanol, propylene glycol or acetonitrile.

[0045] (4) a sample detection module for detecting the concentration level of the metabolite combination in the sample.

[0046] In some embodiments, the sample detection module is configured to perform at least a liquid chromatography tandem mass spectrometry (LC-MS / MS) operation for detecting the metabolites; the liquid chromatography is high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), or nano liquid chromatography (Nano-LC), and the tandem mass spectrometry is quadrupole mass spectrometry (Quadrupole, Q), time of flight mass spectrometry (Time of Flight, TOF), ion trap mass spectrometry (Ion Trap), or high resolution orbitrap mass spectrometry (Orbitrap); the separation condition of the liquid chromatography includes: mobile phase A is 5 mmol ammonium formate-formic acid aqueous solution, mobile phase B is 10% isopropyl alcohol+10% methanol+80% acetonitrile, the chromatographic column is a 100 mm HSS T3 column, the column temperature is set to 40℃, the flow rate is 0.3 ml / min, 0-1.0 min maintains 4% B, 1.0-3.0 min linearly changes from 4% B to 50% B, 3.0-6.0 min linearly changes from 50% B to 80% B, 6.0-6.5 min linearly changes from 80% B to 100% B, 6.5-8.0 min maintains 100% B, and 8.0-9.0 min linearly changes from 100% B to 4% B; the detection condition of the mass spectrometry includes: data acquisition is performed in a triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode, the characteristic ion pair information of the metabolites is selected, the information is confirmed and the detection method is established by using a standard product, and the accurate concentration value and the related ratio value of each metabolite in the biological sample are obtained by using an internal standard product for quantitative correction.

[0047] In some embodiments, the sample pretreatment module is configured to perform at least an operation of precipitating proteins and extracting metabolites; the operation includes extracting the biological sample with isopropyl alcohol:methanol (v / v) = 1:1-1:5, and taking the supernatant after centrifugation for detection.

[0048] The seventh aspect of the present application discloses a computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to realize the function of the system according to the sixth aspect of the present application, or realize the steps of the method according to the fifth aspect of the present application.

[0049] The eighth aspect of the present application discloses an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to realize the function of the system according to the sixth aspect of the present application, or realize the steps of the method according to the fifth aspect of the present application.

[0050] The present application has the beneficial technical effects that:

[0051] The metabolite combination provided by the present application can be used to accurately evaluate the risk of neonatal biliary atresia, and can realize early screening of neonatal biliary atresia in clinic. In clinical use, by quantitatively determining the content of the metabolite combination in the blood sample of a newborn, a newborn with a high risk of biliary atresia can be quickly screened. The evaluation model established based on the five important biliary atresia differential metabolites disclosed in the present application has the advantages of high sensitivity and specificity and good accuracy when evaluating the risk of neonatal biliary atresia. BRIEF DESCRIPTION OF DRAWINGS

[0052] Fig. 1 is a representative ion chromatogram of the metabolite in blood by liquid chromatography mass spectrometry.

[0053] Fig. 2 is a calibration curve of monoconjugated bilirubin.

[0054] Fig. 3 is a calibration curve of hyocholic acid.

[0055] Fig. 4 is a calibration curve of pyroglutamic acid.

[0056] Fig. 5 is a calibration curve of alpha-aminobutyric acid.

[0057] Fig. 6 is a calibration curve of 3-methyl-2-oxovaleric acid.

[0058] Fig. 7 is a ROC curve of the training set of the evaluation model.

[0059] Fig. 8 is a ROC curve of the validation set of the evaluation model.

[0060] Fig. 9 is a ROC curve of the training set of monoconjugated bilirubin.

[0061] Fig. 10 is a ROC curve of the validation set of monoconjugated bilirubin.

[0062] Fig. 11 is a ROC curve of the training set of alpha-aminobutyric acid.

[0063] Fig. 12 is a ROC curve of the validation set of alpha-aminobutyric acid.

[0064] Fig. 13 is a ROC curve of the training set of pyroglutamic acid.

[0065] Fig. 14 is a ROC curve of the validation set of pyroglutamic acid.

[0066] Fig. 15 is a ROC curve of the training set of 3-methyl-2-oxovaleric acid.

[0067] Fig. 16 is a ROC curve of the validation set of 3-methyl-2-oxovaleric acid.

[0068] Fig. 17 is a ROC curve of the training set of hyocholic acid.

[0069] Figure 18 is a ROC curve of the validation set of porcine cholic acid. DETAILED DESCRIPTION

[0070] The embodiments of the present application will be described in detail below with examples, but those skilled in the art will understand that the following examples are only for illustration of the present application and should not be regarded as limiting the scope of the present application. If the specific conditions are not specified in the examples, the conventional conditions or the conditions recommended by the manufacturer are used. If the manufacturer of the reagent or instrument is not specified, it is a conventional product that can be obtained by purchase.

[0071] Example 1 Collection of dried blood spot samples

[0072] According to the "Technical Specifications for Newborn Disease Screening (2019 Edition)", strictly in accordance with the blood collection technology procedure for newborn disease detection, dried blood spots were collected from heel blood, and the filter paper used was the internationally recognized standard No. 903 filter paper.

[0073] The dried blood spot samples collected in the present application include a training set: 20 dried blood spot samples of children with biliary atresia, 88 dried blood spot samples of healthy newborns; a validation set: 8 dried blood spot samples of children with biliary atresia, 216 dried blood spot samples of healthy newborns. The design and implementation of the present study were approved and supervised by the Medical Ethics Committee, and written informed consent was obtained from all patients.

[0074] Example 2 Targeted metabolomics screening of potential related metabolites of biliary atresia

[0075] An ultra-high performance liquid chromatography-triple quadrupole tandem mass spectrometry system (UPLC-TQS) from Waters Technology was used to quantitatively detect 300 metabolites including amino acids, organic acids, fatty acids, reducing sugars, bile acids, carnitines, phenyl or benzyl derivatives, indoles, etc. in the training set of dried blood spots.

[0076] The pretreatment method of the dried blood spot sample used was as follows: punch the dried blood spot sample with a puncher and transfer it to a clean 96-well plate, 3 dried blood spots per well; add 25 μL of deionized water to each well, cover with an aluminum film, and shake for 20 minutes; after shaking, carefully remove the aluminum film, add 120 μL of methanol (containing isotope internal standard deuterium) to each well, cover with a new aluminum film, and shake for 20 minutes; then centrifuge at 4000g for 20 minutes; carefully remove the aluminum film and transfer 60 μL of supernatant from each well to a new 96-well plate, add 20 μL of 3-nitrophenylhydrazine solution and 1-ethyl-(3-dimethylaminopropyl) carbonyldiimidazole solution in turn, and derivatize for 1 hour; dilute each well with 300 μL of 50% methanol aqueous solution, shake and centrifuge, and then detect on the instrument.

[0077] The liquid phase and mass spectrometry detection conditions used are: injection volume 5 μl; mobile phase A is 0.1% formic acid aqueous solution, mobile phase B is 30% isopropanol + 70% acetonitrile; the chromatographic column is 100 mm BEH C18 column (ACQUITY UPLC BEH C18 analytical column (2.1 x 100 mm), 1.7 μm, Waters); the column temperature is set to 40°C; the flow rate is 0.4 ml / min; 0-1.0 min maintain 5% B, 1.0-5.0 min from 5% B linearly change to 30% B, 5.0-9.0 min from 30% B linearly change to 50% B, 9.0-11.0 min from 50% B linearly change to 78% B, 11.0-13.5 min from 78% B linearly change to 95% B, 13.5-14.0 min from 95% B linearly change to 100% B, 14.0-16.0 min maintain 100% B, 16.0-18.0 min from 100% B linearly change to 5% B; the mass spectrometry detection parameters use multiple reaction monitoring (MRM) mode for data acquisition.

[0078] Through statistical analysis of the detected metabolite data, 5 differential metabolites are obtained as shown in Table 1.

[0079] Table 1 5 differential metabolites related to biliary atresia screened

[0080] Example 3 Preparation of calibration curve and internal calibration and quality control

[0081] The standard metabolite to be tested is dissolved in methanol or deionized water as a solvent to form a 10 mg / mL stock solution. Then further diluted with desalted serum solution (prepared in the laboratory, mixed human serum sample is adsorbed by activated carbon, centrifuged and filtered to obtain desalted serum) to form a mixed calibration working solution, then the mixed calibration working solution prepared by desalted serum is added dropwise to the filter paper to form a dry serum spot, which is used as the standard curve for dry blood spot sample detection.

[0082] Exemplarily, pyroglutamic acid can be added in the mixed calibration sample working solution, and the concentration points are 500 μM, 200 μM, 80 μM, 32 μM, 12.8 μM and 5.12 μM respectively; α-aminobutyric acid and 3-methyl-2-oxovaleric acid can also be added in the mixed calibration sample working solution, and the concentration points are 50 μM, 20 μM, 8 μM, 3.2 μM, 1.28 μM and 0.512 μM respectively; monoconjugated bilirubin can also be added in the mixed calibration sample working solution, and the concentration points are 20 μM, 8 μM, 3.2 μM, 1.28 μM, 0.512 μM and 0.2 μM respectively; porcine cholic acid can also be added in the mixed calibration sample working solution, and the concentrations are 1 μM, 0.4 μM, 0.16 μM, 0.064 μM, 0.0256 μM and 0.01 μM respectively. It should be noted that this embodiment only exemplarily describes the metabolites in the mixed calibration sample working solution, and is not exhaustive.

[0083] The internal calibration samples glutamic acid-13C5 (ZTR-G596961, Shanghai Zhenjun), aminobutyric acid-D2 (IR-20089, ISOREAG), bilirubin (B850-0.2G, Frontier Scientific, Inc.), cholic acid-D4 (13098-50MG, IsoSciences) were respectively dissolved into 0.1 mM stock solution, and then diluted with deionized water into 1.0 μM mixed internal standard working solution.

[0084] According to the concentration range of each labeled composition in the sample, two quality control samples with high relative concentration (monoconjugated bilirubin concentration of about 3.0 μM, porcine cholic acid concentration of about 1.0 μM, pyroglutamic acid concentration of about 80 μM, α-aminobutyric acid concentration of about 10 μM, 3-methyl-2-oxovaleric acid concentration of about 10 μM) and low relative concentration (monoconjugated bilirubin concentration of about 1.0 μM, porcine cholic acid concentration of about 0.4 μM, pyroglutamic acid concentration of about 30 μM, α-aminobutyric acid concentration of about 4 μM, 3-methyl-2-oxovaleric acid concentration of about 4 μM) were prepared.

[0085] Example 4 Pretreatment of dried blood spot samples and extraction of diagnostic labeled composition

[0086] The above 108 dry blood spot samples and standard curve of dry serum spot were punched with a puncher on the dry blood spot sample or standard curve sample, and the punched blood spot was moved to a clean 96-well V-bottom plate, and one blood spot was added to each well. A multichannel pipettor was used to add 25 μL of internal standard solution to each well, and a 96-well aluminum film was covered. The plate was shaken at 10°C and 650 rpm for 20 minutes (note that the dry blood spot should be completely immersed in deionized water). After shaking, the aluminum film was carefully removed, and a multichannel syringe was used to add 110 μL of sample extraction solution (methanol:acetonitrile = 1:1) to each well of the V-bottom plate. A new 96-well aluminum film was covered, and the plate was shaken at 10°C and 650 rpm for 20 minutes. The plate was centrifuged at 10°C and 4000g for 20 minutes. After centrifugation, the aluminum film was carefully removed to avoid spilling the liquid in the V-bottom plate. 80 μL of supernatant was carefully transferred from each well of the V-bottom plate to a new V-bottom plate. A 96-well adhesive film was covered on the V-bottom plate (do not use an aluminum film to avoid clogging the sample needle). The plate was ready for mass spectrometry detection.

[0087] Example 5 High-performance liquid chromatography-mass spectrometry detection of diagnostic marker composition

[0088] The main liquid chromatography separation conditions and parameters are as follows: injection volume 5 μl, mobile phase A 5 mmol ammonium formate-formic acid aqueous solution, mobile phase B 10% isopropanol + 10% methanol + 80% acetonitrile, chromatographic column HSS T3 column (ACQUITY UPLC HSS T3, 100 mm x 2.1 mm, 1.8 μm, Waters) 100 mm, column temperature set to 40°C, flow rate 0.3 ml / min, 0-1.0 min maintain 4% B, 1.0-3.0 min linearly change from 4% B to 50% B, 3.0-6.0 min linearly change from 50% B to 80% B, 6.0-6.5 min linearly change from 80% B to 100% B, 6.5-8.0 min maintain 100% B, 8.0-9.0 min linearly change from 100% B to 4% B.

[0089] The main mass spectrometry detection parameters are as follows: data acquisition is performed in multiple reaction monitoring (MRM) mode using a triple quadrupole mass spectrometer. The representative ion chromatogram of the metabolite in blood according to the present application is shown in Figure 1.

[0090] Example 6 Establishment of metabolite evaluation model

[0091] A calibration standard curve for each metabolite is established, for example as shown in Figures 2-6, where the vertical axis represents the concentration of the corresponding detected substance (μM), and the horizontal axis represents the peak area of the mass spectrometry signal. The calibration standard curve obtained in this example can be used to query the concentration of the corresponding detected substance in the neonatal serum sample.

[0092] The binary logistic regression analysis was performed using SPSS (V19), the grouping information was selected as the dependent variable, and the concentration information of the single conjugated bilirubin, pyroglutamic acid, 3-methyl-2-oxovaleric acid, alpha-aminobutyric acid and hyocholic acid was selected as the covariate, and the evaluation model was established, and the evaluation model contained 5 metabolites (single conjugated bilirubin, pyroglutamic acid, 3-methyl-2-oxovaleric acid, alpha-aminobutyric acid and hyocholic acid, respectively). Then the clinical diagnostic performance curve (ROC curve, as shown in Figure 7) was used to evaluate the metabolites in the birth spot sample of the children with biliary atresia. The evaluation model established by the logistic regression model:

[0093] P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9;

[0094] Wherein, the C1 is the concentration value of pyroglutamic acid in the biological sample, the C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, the C3 is the concentration value of alpha-aminobutyric acid in the biological sample, the C4 is the concentration value of hyocholic acid in the biological sample, and the C5 is the concentration value of single conjugated bilirubin in the biological sample.

[0095] The area under the ROC curve of the newborn according to the evaluation model is AUC = 1.0, the sensitivity is 100%, the specificity is 100%, and the accuracy is 100%, which is higher than the AUC, sensitivity and specificity of single conjugated bilirubin (see Figures 9 and 10, the AUC of the ROC curve of the validation set is 0.994, the sensitivity is 96.6%, and the specificity is 95%), pyroglutamic acid (see Figures 13 and 14, the AUC of the ROC curve of the validation set is 0.869, the sensitivity is 75%, and the specificity is 90%), 3-methyl-2-oxovaleric acid (see Figures 15 and 16, the AUC of the ROC curve of the validation set is 0.797, the sensitivity is 69.3%, and the specificity is 80%), alpha-aminobutyric acid (see Figures 11 and 12, the AUC of the ROC curve of the validation set is 0.719, the sensitivity is 75%, and the specificity is 60%), and hyocholic acid (see Figures 17 and 18, the AUC of the ROC curve of the validation set is 0.712, the sensitivity is 61.4%, and the specificity is 80%) as the biliary atresia marker, indicating that the combination of single conjugated bilirubin, alpha-aminobutyric acid, pyroglutamic acid, 3-methyl-2-oxovaleric acid and hyocholic acid as biliary atresia metabolites has the advantages of high sensitivity and specificity and good accuracy in diagnosing biliary atresia disease.

[0096] The optimal evaluation threshold (cutoff value) is 0 obtained by the ROC curve analysis of the neonatal working characteristic curve. The metabolite concentration value of each sample is detected, and the metabolite concentration value is input into the evaluation model to calculate the P value of each sample. According to the size of the P value, the risk of the neonate suffering from biliary atresia is evaluated. The "risk" refers to whether the neonate has "biliary atresia". The output of the evaluation of the risk of the neonate suffering from biliary atresia by the method of the present application is a qualitative expression of "yes" or "no" or the like compared with the pre-set threshold value. When the P value is greater than or equal to the optimal evaluation threshold, the evaluation result is "the neonate has biliary atresia"; when the P value is less than the optimal evaluation threshold, the evaluation result is "the neonate does not have biliary atresia".

[0097] ROC curve of the verification set of Example 7

[0098] This example adds 8 newly collected biliary atresia and 216 healthy neonatal dried blood spot samples as a verification set. The area under the ROC curve of the verification set obtained according to the evaluation model is AUC = 1.00; the sensitivity is 100%, the specificity is 100%, and the accuracy is 100% (Figure 8).

[0099] Establishment of a computer system for evaluating the disease of neonatal biliary atresia in Example 8

[0100] This example establishes a computer system for evaluating the risk of neonatal biliary atresia, which includes an information acquisition module, a biliary atresia disease risk evaluation module, a sample detection module, and a sample pretreatment module.

[0101] The information acquisition module is at least used to perform the following operations: acquiring metabolite combination detection information in the neonatal sample, and the metabolite combination is selected from the aforementioned metabolite combination.

[0102] The biliary atresia disease risk evaluation module is at least used to perform the following operations: according to the metabolite group level acquired by the information acquisition module, evaluating whether the neonate has biliary atresia or has the risk of suffering from biliary atresia disease; specifically including inputting the level of the metabolite group acquired by the information acquisition module into the evaluation model, and evaluating whether the neonate has biliary atresia disease or has the risk of suffering from biliary atresia disease according to the evaluation model; the evaluation model is as follows:

[0103] P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9;

[0104] Wherein, C1 is the concentration value of pyroglutamic acid in the biological sample, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, C3 is the concentration value of alpha-aminobutyric acid in the biological sample, C4 is the concentration value of hyocholic acid in the biological sample, and C5 is the concentration value of monomeric bilirubin in the biological sample.

[0105] When the P value is greater than or equal to the optimal evaluation threshold value, the evaluation result is that the newborn has biliary atresia; when the P value is less than the optimal evaluation threshold value, the evaluation result is that the newborn does not have biliary atresia.

[0106] The sample detection module is at least used for detecting the levels of the metabolites in the sample, and specifically includes:

[0107] The sample detection module is at least used for detecting the levels of the metabolites in the sample, and specifically includes: The liquid chromatography is high performance liquid chromatography (HPLC), ultra performance liquid chromatography (UPLC), or nanoscale liquid chromatography (Nano-LC), and the tandem mass spectrometry is quadrupole mass spectrometry (Quadrupole, Q), time of flight mass spectrometry (Time of Flight, TOF), ion trap mass spectrometry (Ion Trap), or high-resolution orbitrap mass spectrometry (Orbitrap); the separation conditions of the liquid chromatography include: mobile phase A is 5 mmol ammonium formate-formic acid aqueous solution, mobile phase B is 10% isopropyl alcohol+10% methanol+80% acetonitrile, the chromatographic column is a 100 mm HSS T3 column, the column temperature is set to 40°C, the flow rate is 0.3 ml / min, 0-1.0 min maintains 4% B, 1.0-3.0 min linearly changes from 4% B to 50% B, 3.0-6.0 min linearly changes from 50% B to 80% B, 6.0-6.5 min linearly changes from 80% B to 100% B, 6.5-8.0 min maintains 100% B, and 8.0-9.0 min linearly changes from 100% B to 4% B; the detection conditions of the mass spectrometry include: data acquisition is performed in a triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode, the characteristic ion pair information of the metabolites is selected, the information is confirmed and the detection method is established by using a standard product, and the accurate concentration values and related proportion values of the metabolites in the biological sample are obtained by using an internal standard product for quantitative correction.

[0108] The sample pretreatment module is at least used for performing protein precipitation and metabolite extraction operations; the operations include extracting the newborn sample with isopropyl alcohol:methanol (v / v) = 1:1-1:5, and taking the supernatant after centrifugation for detection.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some or all of the technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A combination of metabolites for assessing the risk of biliary atresia in a neonate, characterized in that, The metabolite combination comprises one or more of the following: hyocholic acid, pyroglutamic acid, alpha-aminobutyric acid, 3-methyl-2-oxovaleric acid, and monoconjugated bilirubin, and the metabolite combination contains only monoconjugated bilirubin as one metabolite.

2. The combination of metabolites according to claim 1, wherein The metabolite combination is from a biological sample of a neonate, and the biological sample is whole blood, plasma, serum, or a dried blood spot; and / or, the metabolite combination consists of hyocholic acid, pyroglutamic acid, alpha-aminobutyric acid, 3-methyl-2-oxovaleric acid, and monoconjugated bilirubin.

3. The combination of metabolites according to claim 2, wherein The biological sample is a dried blood spot.

4. A reagent for detecting the metabolite combination according to any one of claims 1 to 3, characterized in that, The reagent is used to detect the concentration of the metabolite combination; the concentration is obtained by quantitatively detecting the metabolite combination in the biological sample of the neonate after processing the biological sample using liquid chromatography-mass spectrometry.

5. The agent of claim 4, wherein The reagent is a high-performance liquid chromatography reagent for detecting the concentration of the metabolite combination; the processing of the biological sample of the neonate is to extract the metabolites in the biological sample using a sample extraction solution as a detection sample, the detection sample is an organic solvent dispersion system of the biological sample, and the biological sample is whole blood, plasma, serum, or a dried blood spot.

6. The agent of claim 5, wherein The organic solvent of the organic solvent dispersion system is methanol, ethanol, propanol, propylene glycol, or acetonitrile; and the biological sample is a dried blood spot.

7. A kit characterized in that, The kit comprises the metabolite combination of any one of claims 1-3 and / or the reagent of any one of claims 4-6.

8. The kit of claim 7, wherein The kit further comprises a reagent for extracting metabolites.

9. The kit of claim 8, wherein The reagent for extracting metabolites is a mixture of an organic solvent and water.

10. The kit of claim 9, wherein The organic solvent is selected from one or more of the following: isopropyl alcohol, methanol, and acetonitrile.

11. The kit of claim 7, wherein The kit comprises an isotopic internal standard.

12. The kit of claim 11, wherein The isotopic internal standard is deuterated.

13. Use of the metabolite combination of any one of claims 1-3, the reagent of any one of claims 4-6, or the kit of any one of claims 7-12 in the manufacture of a product for assessing whether a neonate has biliary atresia.

14. A computer-aided method for assessing the risk of neonatal biliary atresia, characterized in that, The method comprises the following steps: Step 1: receiving or inputting the concentration information of the metabolite combination in the biological sample of the neonate, the metabolite combination being the metabolite combination of any one of claims 1-3; Step 2: inputting the concentration of the metabolite combination received or inputted in step 1 into Formula 1 to output an assessment result of whether the neonate from which the biological sample is derived has biliary atresia; The Formula 1 is: P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9; wherein C1 is the concentration value of pyroglutamic acid in the biological sample, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, C3 is the concentration value of alpha-aminobutyric acid in the biological sample, C4 is the concentration value of hyocholic acid in the biological sample, and C5 is the concentration value of monoconjugated bilirubin in the biological sample, all of which are expressed in the concentration unit of μM; The Formula 1 is: P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9; wherein C1 is the concentration value of pyroglutamic acid in the biological sample, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, C3 is the concentration value of alpha-aminobutyric acid in the biological sample, C4 is the concentration value of hyocholic acid in the biological sample, and C5 is the concentration value of monoconjugated bilirubin in the biological sample, all of which are expressed in the concentration unit of μM; The judgment standard of the evaluation result is: when P≥the optimal evaluation threshold, the output evaluation result is "the newborn has biliary atresia"; when P 15. The method of claim 14, wherein, The optimal evaluation threshold is 0.

16. A system for assessing the risk of biliary atresia in a neonate, the system comprising: The system comprises: (1) an information acquisition module for receiving or inputting the concentration information of the metabolite combination in the newborn biological sample, wherein the metabolite combination is as described in any one of claims 1-3; (2) a biliary atresia disease risk evaluation module for evaluating whether the newborn has biliary atresia according to the concentration of the metabolite combination; the evaluation is realized by inputting the concentration of the metabolite combination received or inputted by the information acquisition module into formula 1 to output the evaluation result of whether the newborn from which the biological sample is derived has biliary atresia; The formula 1 is: P = C1*0.448 + C2*0.834 + C3*0.7 - C4*879 + C5*69.6 - 84.9; wherein C1 is the concentration value of pyroglutamic acid in the biological sample, C2 is the concentration value of 3-methyl-2-oxovaleric acid in the biological sample, C3 is the concentration value of alpha-aminobutyric acid in the biological sample, C4 is the concentration value of hyocholic acid in the biological sample, and C5 is the concentration value of monobound bilirubin in the biological sample, all of which are expressed in the concentration unit of μM; The evaluation standard of the evaluation result is: when P≥the optimal evaluation threshold, the output evaluation result is "the newborn has biliary atresia"; when P 17. The system of claim 16, wherein, The optimal evaluation threshold is 0.

18. The system of claim 17, wherein, The system further comprises one or more of the following modules: (3) a sample pretreatment module for extracting target metabolites in the detection sample after precipitating proteins; the detection sample is an organic solvent dispersion system of the biological sample, and the organic solvent of the organic solvent dispersion system is methanol, ethanol, propanol, propylene glycol or acetonitrile; (4) a sample detection module for detecting the concentration level of the metabolite combination as described in any one of claims 1-3 in the sample.

19. A computer readable storage medium storing a computer program, wherein the computer program comprises instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 18. The computer program, when executed by a processor, can realize the functions of the system as claimed in any one of claims 16-18, or realize the steps of the method as claimed in claim 14 or 15.

20. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor is configured to execute the computer program to realize the functions of the system as claimed in any one of claims 16-18, or realize the steps of the method as claimed in claim 14 or 15.

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