WD neonatal dried blood spot metabolism marker, detection reagent, screening method and application

Abstract

The invention provides a metabolic marker used for WD neonatal screening, and the metabolic marker is selected from one or any combination of the following components: 5-(3-Chlorophenyl)-5-methylimidazolidin-2, 4-dione, Panaxynyl, 2, 2, 6, 6-Tetrametyl-4-methylidinyl) 2-methylidinyl. The invention also provides a preparation method of the metabolic marker used for the WD neonatal screening, and the metabolic marker used for the WD neonatal screening is characterized in that the metabolic marker used for the WD neonatal screening is selected from one or any combination of the following components. The invention also provides a detection reagent and a screening method. The marker of the WD newborn is represented through metabonomics characteristics for the first time, and the obtained metabolic marker has high value for early screening and timely intervention of WD. The extraction and mass spectrometric detection process of the DBS sample can be carried out at high throughput, and the problems that a traditional index experiment is complex in operation and difficult to detect are solved.

Description

Technical Field

[0001] This invention relates to the field of biochemistry, and in particular to a metabolic marker, detection reagent, screening method and application of dried blood spot in neonatal WD. Background Technology

[0002] Wilson's disease (WD), also known as hepatolenticular degeneration, is a copper metabolism disorder caused by mutations in the ATP7B gene, leading to weakened or absent function of the copper transporter P-ATPase B (P-ATP7B). It is inherited in an autosomal recessive manner. Abnormal P-ATP7B function prevents the synthesis of ceruloplasmin (Cp) from copper and obstructs its excretion via capillary bile ducts, resulting in copper accumulation in the liver and causing liver damage. When copper overflows and deposits in other organs, it can cause neurological disorders, corneal KF rings, proteinuria, osteoarthritis, and other symptoms, ultimately leading to multiple organ dysfunction. Based on different clinical manifestations, WD can be classified into hepatic, cerebral, mixed, and other types. Infants and children often present with the hepatic type; if acute liver failure occurs suddenly and is complicated by hemolytic anemia, the mortality rate without treatment is as high as 90%. Neurological symptoms often appear after liver damage, mainly including dystonia, tremor, bradykinesia, and abnormal mental and behavioral patterns; in severe cases, paranoia, schizophrenia, or even depression may occur. Multiple neurological symptoms often occur simultaneously, varying in severity, and are irreversible. In summary, WD is a progressive and fatal disease affecting multiple organs, imposing a tremendous physiological burden on patients.

[0003] Domestic newborn genetic screening data show that the genetic prevalence of this disease is 1 / 7,194 and 1 / 4,206, far higher than the previously known 1 / 30,000. WD can occur at any age, but is most common between 4 and 40 years old; the youngest reported patient is only 8 months old. Fortunately, WD is one of the few treatable inherited metabolic diseases. The treatment principle is early, individualized, and lifelong treatment. Without treatment, it can lead to disability and death, with a mortality rate of 5% to 6.1%. The most common cause of death in WD patients is late diagnosis. Among the various types of WD, cerebral WD is more severe, often with irreversible neurological damage already present at the time of diagnosis. In contrast, if detected early and treated promptly, the prognosis is better. Therefore, early detection of WD has significant clinical importance.

[0004] Currently, the diagnosis of WD mainly relies on clinical phenotype, laboratory tests (ceruloplasmin, 24-hour urinary copper, etc.), and ATP7B gene testing. Some experts suggest that 3 years of age is the optimal age for WD screening via Cp testing. However, collecting blood or urine samples from 3-year-old children is more difficult than collecting samples from newborns during hospitalization, making widespread screening challenging and prone to missed cases. Including WD in newborn disease screening programs might be a better solution, but reports indicate that Cp testing in the neonatal period can produce false negatives; Cp levels are only reduced in some WD patients, resulting in a low detection rate when used as a single indicator, and normal results do not rule out WD. Furthermore, other copper metabolism indicators such as 24-hour urinary copper, serum copper, non-ceruloplasmin-bound copper, ion-exchangeable copper, and liver copper only show abnormalities after copper accumulation reaches a certain level, making them unsuitable for newborn screening. In recent years, newborn multi-disease genomic screening based on next-generation sequencing (NGS) technology, which includes the ATP7B gene, has achieved good results both domestically and internationally, demonstrating the potential application value of NGS in newborn disease screening. However, considering various factors such as public awareness, family income, testing costs, and the difficulty of operation and interpretation, widespread adoption of genetic screening remains extremely challenging. Therefore, identifying biomarkers that can be effectively used for newborn WD screening is the technical problem this invention aims to solve.

[0005] Metabolomics based on liquid chromatography can detect fragment components of macromolecular compounds in biological samples such as human serum, thereby qualitatively and quantitatively identifying tens of thousands of metabolites. By revealing metabolic networks, it can uncover the potential biochemical activities of cells, tissues, and organs, reflecting actual metabolite changes in individuals. Even subtle abnormalities in the body's metabolic levels can be sensitively detected. Metabolomics can provide a preliminary description of the metabolic profile of diseases and identify specific differentially expressed metabolites between patients and healthy individuals as biochemical biomarkers for diseases, aiding in the early discovery of biomarkers, disease diagnosis, progression, and treatment. Therefore, we intend to utilize metabolomics technology to discover specific biomarkers for newborn WD screening. Summary of the Invention

[0006] The purpose of this invention is to provide screening and application of metabolic markers for dried blood spots in newborns with WD, thus providing a new approach for early clinical screening of WD.

[0007] One aspect of the present invention provides the application of metabolic biomarkers in the preparation of WD newborn screening products.

[0008] Another aspect of the invention provides metabolic biomarkers for newborn screening for WD, said metabolic biomarkers being selected from one or any combination of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, Panaxynol, 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate.

[0009] This invention also provides a method for screening metabolic markers for newborn screening in WD, comprising the following steps: Sample pretreatment: used for the extraction of metabolites from dried blood spot samples; Sample metabolomics testing: for the detection of metabolites; Data quality control: Used for quality control of metabolomics data, determining the limit of quantitation and the coefficient of variation within and between batches for each metabolite; Differential metabolite screening and analysis: Metabolites with concentration differences between the WD neonatal group and the healthy neonatal group and metabolites associated with the risk of disease occurrence were screened using a two-independent-samples t-test, orthogonal partial least squares discriminant analysis, and false discovery rate correction method. The predictive efficacy of the predictive model was evaluated using the area under the receiver operating characteristic curve to screen for WD neonatal dried blood spot metabolites. The metabolites are one of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, Panaxynol, 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate or any combination thereof.

[0010] The present invention also provides reagents for detecting metabolic markers in newborn screening for WD.

[0011] The detection reagent of this invention includes a metabolite extraction reagent, a chromatographic separation reagent, and a cleaning reagent. The extraction reagent is a 1:1 mixture of methanol and acetonitrile. The liquid chromatography phase A for chromatographic separation contains 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and the phase B contains acetonitrile. The cleaning reagent consists of acetic acid and isopropanol.

[0012] Furthermore, the detection reagent includes an internal standard mixture, wherein the internal standard is an introduced isotope-labeled metabolite.

[0013] Furthermore, the WD screening product of the test reagent is used in conjunction with the testing device to detect metabolic markers.

[0014] Furthermore, the detection device includes a liquid chromatography-tandem mass spectrometer, and the detection reagents are used to detect the content of each metabolite in the metabolic markers by liquid chromatography-tandem mass spectrometry.

[0015] Furthermore, the test sample for the test reagent is dried blood spots on the soles of newborn feet.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention is the first to characterize biomarkers for neonatal WD using metabolomics features. The obtained metabolic biomarkers are of high value for early screening and timely intervention of WD.

[0017] The metabolic biomarkers screened by this invention have good biological stability and representativeness, and their biological activity can be maintained even after long-term storage, thus ensuring the reliability of the detection results.

[0018] This invention has good sensitivity: the combined marker AUC > 0.95.

[0019] This invention is newborn-friendly: it requires only a heel prick blood DBS sample and is compatible with existing newborn screening systems (coverage >99%).

[0020] This invention enables high-throughput extraction and mass spectrometry detection of DBS samples, solving the problems of complex experimental operations and difficult detection of traditional indicators.

[0021] This invention has a cost advantage: the cost of mass spectrometry detection is only 1 / 10 to 1 / 5 of that of gene sequencing.

[0022] This invention has the function of family early warning: a positive result can be linked to the screening of siblings of the child with WD, providing family members with WD with the opportunity for early detection and early intervention. Attached Figure Description

[0023] Figure 1 This diagram illustrates the significant differences in metabolites between newborns with WD and normal newborns.

[0024] Figure 2 This diagram illustrates the 12 metabolites that were most significantly upregulated in the neonatal WD group.

[0025] Where A is 2-Hydroxy-6-methoxybenzoic acid / 3,4-Dihydroxyphenylaceticacid / Homogentisic acid, B is 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, C is N-Dodecanoyl-N-methylglycine, D is Panaxynol, E is 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate, F is Homoarecoline, G is Pivagabine, H is 2-(Dipentylamino)-2-(hydroxymethyl)-1,3-propanediol, I is Tetradecyl sulfate (sodium), J is Enol-3,5,5-Trimethyl-1,2-cyclohexanedione. Positive=9, Negative=137.

[0026] Figure 3 This is a schematic diagram of ROC curve analysis for candidate metabolic biomarkers of WD.

[0027] Where A is 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, B is Panaxynol, C is 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate, D is 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione+Panaxynol+2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate. Positive=9, Negative=137. Detailed Implementation

[0028] The technical solution of the present invention will be described in detail below: I. Sample collection and data processing The inventors collected dried blood spot samples from 9 newborns with WD and 137 healthy newborns from Nanjing Maternal and Child Health Hospital. Positive newborns were confirmed through ATP7B gene testing and family verification. Dried blood spot samples were collected 48–72 hours after birth, air-dried naturally, and stored at 4°C after collection. All newborn dried blood spot samples had complete information, including serial number, date of birth, date of blood collection, sex, gestational age, and birth weight. There were no significant differences in sex, gestational age, birth weight, or delivery method between the two groups. We intend to use a combination of genomics and metabolomics to identify novel biochemical biomarkers for newborn screening of WD.

[0029] II. FH Marker Detection Procedure for DBS Samples 1. Reagents and Instruments (1) Reagents Methanol (CNW Technologies) Acetonitrile (CNW Technologies) Ammonium acetate (SIGMA-ALDRICH) Ammonia hydroxide CNW Technologies Ultrapure water (ddH2O) - Watsons Acetic acid (SIGMA-ALDRICH) Isopropanol (2-Propanol) CNW Technologies (2) Instruments PerkinElmer Fully Automatic Hole Punch Ultra-high performance liquid chromatography (UHPC) Thermo Fisher Scientific High-resolution mass spectrometer Thermo Fisher Scientific Centrifuges by Thermo Fisher Scientific The scale Sartorius Ultrasonic Instruments Shenzhen Redbon Electronics Co., Ltd. Homogenizer Shanghai Jingxin Technology Co., Ltd. Refrigeration Dryer Sihuan Furui Instrument Technology Development Co., Ltd. 2. Testing Procedures (1) Sample preparation Place the newborn's DBS (3.2 mm in diameter) into a 1.5 mL ep tube; Add 200 μL of water to the sample, sonicate in an ice-water bath for 30 min, and then add 480 μL of extraction buffer (MTBE:MeOH=5:1). Vortex mix for 30 seconds, then sonicate in an ice-water bath for 10 minutes; The sample was left to stand at -40 ℃ for 1 h.

[0030] Centrifuge the sample at 4 ℃, 3000 rpm (centrifugal force 900 (×g), radius 8.6 cm) for 15 min; Take 300 μL of the supernatant and dry it under low temperature and vacuum. Add 100 μL of extraction buffer (DCM:MeOH = 1:1, v / v) to the dried sample. The extraction buffer contains an isotope-labeled internal standard for reconstitution. Vortex mix for 30 seconds, then sonicate in an ice-water bath for 10 minutes. Centrifuge the sample at 4 ℃, 12000 rpm (centrifugal force 16200 (×g), radius 8.6 cm) for 15 min; Take 75 μL of the supernatant into a sample vial for instrumental analysis; Take 20 μL of supernatant from each sample and mix them together to form a QC sample for instrument testing.

[0031] (2) LC-MS / MS analysis Chromatographic conditions: The Orbitrap Exploris 120 mass spectrometer can perform primary and secondary mass spectrometry data acquisition under the control of software (Xcalibur, version 4.4, Thermo). Detailed parameters are as follows: Sheath gas flow rate: 30 Arb, Aux gas flow rate: 10 Arb, Capillary temperature: 320 ℃ (positive) or 320 ℃ (negative), Full ms resolution: 60000, MS / MS resolution: 15000. Chromatographic conditions: Chromatograph: Vanquish (Thermo Fisher Scientific) Ultra-High Performance Liquid Chromatograph Column: Phenomenex Kinetex C18 (2.1 mm × 100 mm, 2.6 μm) Mobile phase: A (40% water + 60% acetonitrile, containing 10 mmol / L ammonium formate), B (10% acetonitrile + 90% isopropanol solution, with 50 mL of 10 mmol / L ammonium formate aqueous solution added per 1000 mL) Injection volume: 2 μL Mass spectrometry conditions: Mass spectrometer: Orbitrap Exploris 120 mass spectrometer Control software: Xcalibur, version 4.4, Thermo Detailed parameters: Sheath gas flow rate: 30 Arb, Aux gas flow rate: 10 Arb, Capillary temperature: 320 ℃ (positive) or 320 ℃ (negative), Full msresolution: 60000, MS / MS resolution: 15000, Collision energy: 15 / 30 / 45 in NCEmode, Spray Voltage: 3.8 kV (positive) or -3.4 kV (negative) (3) Results processing The raw data was converted into mzXML format using ProteoWizard software, and then metabolite identification was performed using a collaboratively developed R package. The database used was BiotreeDB (V3.0), and then visualization analysis was performed using a self-developed R package.

[0032] Metabolomics analysis of newborns diagnosed with WD and healthy controls using a newborn genetic screening program that includes the ATP7B gene revealed that, compared with healthy newborns, 89 metabolites were upregulated and 50 metabolites were downregulated in WD newborns (P<0.05, VIP>1). Figure 1The volcano plot shows that newborns with WD have a wide range of differential metabolite changes compared to normal newborns. Among them, 12 metabolites were significantly elevated in WD neonatal DBS, including 2-Hydroxy-6-methoxybenzoic acid / 3,4-Dihydroxyphenylacetic acid / Homogentisic acid (isomers), 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, N-Dodecanoyl-N-methylglycine, Panaxynol, 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate, Homoarecoline, Pivagabine, 2-(Dipentylamino)-2-(hydroxymethyl)-1,3-propanediol, Tetradecyl sulfate (sodium), and Enol-3,5,5-Trimethyl-1,2-cyclohexanedione (P<0.001, FDR<0.05, log2 Fold change>1.5). Figure 2 ROC curves were plotted, revealing three relatively good indicators: 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, Panaxynol, and 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate, with AUC > 0.9 and specificity and sensitivity both greater than 80%. Among these three metabolites, 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione performed best, with an AUC of 0.913, specificity of 83.9%, and sensitivity of 88.9%. To further improve screening efficiency, we also conducted a combined analysis of these three indicators that were significantly elevated in newborns with WD, and the combined indicator had an AUC of 0.964, specificity of 100.0%, and sensitivity of 84.7%. Figure 3 ).

[0033] Therefore, based on the combined application and analysis of our genome and metabolomics, we have invented a biochemical screening kit for newborns with WD based on specific differential metabolite indicators. This kit can detect children with WD by detecting the combined metabolite indicators of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione+Panaxynol+2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate.

[0034] This invention, based on a combination of genomics and metabolomics, yielded three metabolites with significantly different levels in dried blood spots of healthy and disease-prone newborns. These three metabolites exhibit excellent screening performance for disease-prone WD. Specifically, under unadjusted conditions, the AUC of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione was 0.913, the AUC of Panaxynol was 0.910, and the AUC of 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate was 0.908, indicating that these three metabolites are effective biomarkers for screening disease-prone WD. Furthermore, the screening effect remains robust when the three metabolites are used in combination.

Claims

1. An application of a metabolic biomarker, characterized in that: The application of the metabolic biomarkers in the preparation of WD newborn screening products.

2. A metabolic biomarker for newborn screening for WD, characterized in that: The metabolic markers are selected from one or any combination of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, Panaxynol, 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate.

3. The metabolic biomarker for newborn screening for WD according to claim 2, characterized in that... The method for screening metabolic biomarkers includes the following steps: Sample pretreatment: used for the extraction of metabolites from dried blood spot samples; Sample metabolomics testing: for the detection of metabolites; Data quality control: Used for quality control of metabolomics data, determining the limit of quantitation and intra- and inter-batch coefficients of variation for each metabolite; Differential metabolite screening and analysis: Metabolites with concentration differences between the WD neonatal group and the healthy neonatal group and metabolites associated with the risk of disease occurrence were screened using a two-independent-samples t-test, orthogonal partial least squares discriminant analysis, and false discovery rate correction method. The predictive efficacy of the predictive model was evaluated using the area under the receiver operating characteristic curve to screen for WD neonatal dried blood spot metabolites. The metabolites are one of 5-(3-Chlorophenyl)-5-methylimidazolidine-2,4-dione, Panaxynol, 2,2,6,6-Tetramethyl-4-piperidinyl 2-methylacrylate or any combination thereof.

4. A detection reagent, characterized in that, Includes reagents for detecting the metabolic markers for WD newborn screening as described in claim 2.

5. The detection reagent according to claim 4, characterized in that... The reagents include metabolite extraction reagents, chromatographic separation reagents, and cleaning reagents. The extraction reagent is a 1:1 mixture of methanol and acetonitrile. The liquid chromatography phase A for chromatographic separation consists of 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and phase B consists of acetonitrile. The cleaning reagents are acetic acid and isopropanol.

6. The detection reagent according to claim 5, characterized in that... The detection reagent includes an internal standard mixture, wherein the internal standard is an introduced isotope-labeled metabolite.

7. The detection reagent according to claim 5, characterized in that... WD screening products are designed to work with testing devices to detect metabolic markers.

8. The detection reagent according to claim 5, characterized in that... The detection device includes a liquid chromatography-tandem mass spectrometer, and the detection reagents are used to detect the content of each metabolite in the metabolic markers.

9. The detection reagent according to claim 5, characterized in that... The test sample was dried blood spots from the soles of newborns' feet.

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