Generalized pustular psoriasis diagnostic marker based on metabonomics and application thereof

Abstract

The invention discloses a generalized pustular psoriasis diagnosis marker based on metabonomics and application of the generalized pustular psoriasis diagnosis marker. The diagnostic marker is prepared from one or more of the following 35 compounds: pyruvic acid, alpha-ketoisovaleric acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, methane thiophosphoric acid, proline, uracil, tranexamic acid, 4-aminobutyric acid, threonine, scopoletin, dodecanol, N-methyl-L-leucine, L-cysteine-glycine and L-kynurenine. The feed additive is prepared from the following raw materials: 3-hydroxybenzoic acid, allantoin, delta-tocopherol, xylofuranose, glucose-1-phosphoric acid, pyrophosphate, taurine, L-asparagine, phthalic acid, 4-(dimethylamino) azobenzene, 5-tert-butyl-1h-indole-2, 3-dione, quinic acid, glucose, histidine, lysine, palmitic acid, 7-methylguanine, oleic acid and whale acid. The marker can be used for accurately distinguishing patients with generalized pustular psoriasis from healthy people.

Description

[0001] This application is a divisional application of application No. 2020109716968, filed on September 16, 2020. TECHNICAL FIELD

[0002] The present application belongs to the field of clinical examination and diagnosis, and relates to a generalized pustular psoriasis diagnosis marker based on metabolomics and application thereof. BACKGROUND

[0003] Generalized pustular psoriasis (GPP) is the most severe type of psoriasis, and is characterized by the occurrence of sterile pustules of millet size on the erythematous base, often accompanied by high fever, white blood cell elevation and hypoproteinemia, and even life-threatening. Pustular psoriasis can also involve the eye, liver, lung, gastrointestinal tract, cardiovascular system, kidney and bone, in addition to skin lesions. Due to the unclear pathogenesis of GPP, the diagnosis and treatment are difficult. Although the biological agents for psoriasis have made rapid progress in recent years and have good effects in the treatment of pustular psoriasis, on the one hand, the biological agents are expensive and cannot be widely promoted at present, and on the other hand, the current treatment methods have not achieved satisfactory results in the treatment and control of GPP systemic symptoms. Therefore, prevention, early diagnosis and early treatment are a major and arduous medical task in clinical practice.

[0004] We expect one or a group of biomarkers to be used for more accurate etiological diagnosis of generalized pustular psoriasis. As a quantitative indicator, biomarkers play an important role in the auxiliary quantitative diagnosis of acute exacerbation of generalized pustular psoriasis, the assessment of severity, and the judgment of the etiology and prognosis of acute exacerbation, which is a hot field of research on generalized pustular psoriasis.

[0005] In view of the heterogeneity of generalized pustular psoriasis, a single biomarker is difficult to accurately reflect, and the establishment and development of metabolomics provides an effective means to solve this problem. Metabolomics mainly detects the changes of small molecule metabolites (MWK <1000) to obtain the dynamic changes of metabolic products in vivo over time and the pathophysiological process, including sugars, lipids, amino acids, vitamins, etc. As the final product of cellular physiological activity, metabolites can truly and sensitively reflect the functional state of cells. Metabolomics changes the traditional idea of single marker detection, and uses a group of metabolites as "pattern markers" to diagnose diseases, which has unique advantages. Although metabolomics started late, it has shown strong advantages compared with traditional diagnostic methods and research means. The acute exacerbation of generalized pustular psoriasis inevitably causes characteristic changes in endogenous small molecule metabolites during occurrence and development, and metabolomics with advanced separation, analysis and calculation methods has the ability and advantage of distinguishing characteristic metabolites under different pathophysiological conditions from the whole, and the study of characteristic metabolites of generalized pustular psoriasis by metabolomics can explore the pathogenesis of this complex clinical syndrome from the whole. SUMMARY

[0006] In order to overcome the shortcomings of the prior art and solve the problem that there is no reliable biomarker for generalized pustular psoriasis, the present application finds specific differential metabolites of generalized pustular psoriasis, i.e. diagnostic molecules of generalized pustular psoriasis, by metabolomics analysis of patient serum by high performance liquid chromatography-mass spectrometry. The present application provides a diagnostic marker suitable for the diagnosis of generalized pustular psoriasis, and the application of the diagnostic marker in the diagnosis of generalized pustular psoriasis.

[0007] The present application analyzes 24 cases of generalized pustular psoriasis patients and 12 cases of healthy volunteers plasma samples, and obtains the fingerprint of small molecule metabolites by gas chromatography mass spectrometry (GC-MS). After univariate and multivariate analysis and feature screening of the fingerprint of small molecule metabolites of generalized pustular psoriasis and healthy normal controls, a diagnostic marker suitable for generalized pustular psoriasis is obtained, which has high clinical use and popularization value.

[0008] The specific technical scheme for implementing the present application is: the present application provides a diagnosis marker for generalized pustular psoriasis based on metabolomics, which comprises one or more of the following 35 compounds: tyramine, pyruvic acid, alpha-ketoisovaleric acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, methanephosphonothioic acid, L-proline, uracil, tranexamic acid, 4-aminobutyric acid, L-threonine, scopoletin, dodecanol, N-methyl-l-leucine, L-cysteine-glycine, L-kynurenine, 3-hydroxybenzoic acid, allantoin, delta-tocopherol, xylofuranose, glucose-1-phosphate, pyrophosphate, taurine, L-asparagine, phthalic acid, 4-(dimethylamino)azobenzene, 5-tert-butyl-1h-indole-2,3-dione, quinic acid, glucose, L-histidine, L-lysine, palmitelaidic acid, 7-methylguanine, oleic acid and cis-gondoic acid.

[0009] Among them, preferably, any one or more of the following 5 compounds: threonine (L-threonine), L-cysteine-glycine (L-cysteine-glycine), pyrophosphate, glucose and histidine (L-histidine). Any one of the five compounds is related to the severity of generalized pustular psoriasis.

[0010] The application also provides the use of the diagnostic marker in the preparation of a generalized pustular psoriasis diagnostic preparation.

[0011] Among them, preferably, the generalized pustular psoriasis diagnostic preparation is a preparation for diagnosing serum metabolites of generalized pustular psoriasis.

[0012] Preferably, the diagnostic marker is a plasma metabolic marker.

[0013] Preferably, the diagnostic marker is used as a standard for a gas chromatography-mass spectrometer (GC-MS) combination instrument.

[0014] The application also provides a screening method for the above-mentioned various diagnostic markers suitable for the diagnosis of generalized pustular psoriasis, comprising the following steps:

[0015] (1) Collecting serum samples of patients with generalized pustular psoriasis and healthy volunteers as analysis samples;

[0016] (2) Using GC-MS combination technology to perform non-targeted metabolomics analysis on each analysis sample to obtain the original metabolic fingerprint of each serum sample;

[0017] (3) Preprocessing the obtained serum metabolomics fingerprint data, screening differential metabolites through multivariate statistical analysis, and further screening marker metabolites by analyzing the Pearson correlation between the differential metabolites and the disease severity score;

[0018] (4) Through ROC curve analysis, differential metabolites with an AUC value greater than 0.9 are obtained, i.e. serum metabolic markers suitable for the diagnosis of generalized pustular psoriasis.

[0019] The advantage of the application is that serum metabolomics technology is used to analyze patients with generalized pustular psoriasis and healthy normal controls, and a diagnostic marker suitable for generalized pustular psoriasis is obtained. The marker is good for classifying the metabolomics data of generalized pustular psoriasis and healthy people, and can accurately distinguish between patients with generalized pustular psoriasis and healthy people. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 Figure 3 is a score plot of the OPLS-DA model of serum samples, showing that healthy people (CON) and generalized pustular psoriasis patients (GPP) can be well distinguished;

[0021] Figure 2 Figure 4 is a permutational test method for evaluating the reliability of the OPLS-DA model of serum samples;

[0022] Figure 3 Figure 5 is a ROC curve method for evaluating the diagnostic effect of serum L-threonine, L-cysteine-glycine, pyrophosphate, glucose and L-histidine. The vertical coordinate is the sensitivity, and the horizontal coordinate is the specificity. DETAILED DESCRIPTION

[0023] The application will be further illustrated below with specific implementation examples, which are only used to explain the application and do not mean to limit the protection scope of the application.

[0024] Example 1: Screening and characterization of differential metabolites between healthy people and generalized pustular psoriasis patients

[0025] I. Subjects and methods

[0026] 1. Sample source

[0027] After obtaining the consent of the patients, serum samples of 12 healthy volunteers and 24 generalized pustular psoriasis patients were collected, and the healthy volunteers and the patients were from Shanghai Skin Disease Hospital, and the age, gender and body mass index of the healthy volunteers were matched with those of the patients, so as to exclude the metabolic differences caused by dietary habits, gender, age and body mass index. The blood collection time was in the morning on an empty stomach. All samples were stored at -80℃ for use.

[0028] 2. Main reagents

[0029] Acetonitrile, methanol and formic acid (chromatographic grade) were purchased from Sigma-Aldrich Company; analytical pure chloroform, pyridine and anhydrous sodium sulfate were purchased from China Pharmaceutical Group Corporation; L-2-chlorophenylalanine, methoxyamine, N-methyl-N-(trimethylsilyl) trifluoroacetamide (containing 1% trimethylchlorosilane), heptadecanoic acid and leucine- enkephalin were purchased from Sigma-Aldrich Company; deionized water was prepared by a MIlli-Q ultrapure water system of Millipore Company.

[0030] 3. Characterization of serum differential metabolites

[0031] 3.1. GC-MS screening characterization

[0032] 3.1.1. Sample preparation

[0033] Sample processing: Take 100 μL serum in a 1.5 mL centrifuge tube, add 10 μL L-2- chlorophenylalanine (0.3 mg / mL, dissolved in water) and 10 μL heptadecanoic acid (1 mg / mL, dissolved in methanol) as internal standard, vortex for 10 seconds to mix; then add 300 μL methanol / chloroform mixture (volume ratio 3:1), vortex for 30 seconds to mix, incubate the sample at -20°C for 10 minutes, then centrifuge at 12000 g for 10 minutes (4°C); take 300 μL supernatant in a glass sampling bottle, dry it with a nitrogen blower at room temperature, add 80 μL methoxyamine (15 mg / mL, dissolved in pyridine), incubate at 30°C for 90 minutes, then add 80 μL N-methyl-N-(trimethylsilyl) trifluoroacetamide (containing 1% trimethylchlorosilane by volume), incubate at 70°C for 60 minutes to obtain the sample.

[0034] 3.1.2. Detection characterization

[0035] GC-MS conditions: Chromatographic separation uses ultra-high performance gas chromatography, mass spectrometric analysis uses quadrupole-time-of-flight mass spectrometry. The chromatographic column is a DB-5ms capillary column (30 m x 250 μm i.d., 0.25 μm); the carrier gas is high-purity helium, the flow rate is 1.0 mL / min; the injection volume is 1 μL; the programmed temperature is 80°C constant temperature for 2 minutes, 80°C-180°C (10°C / min), 180°C-240°C (5°C / min), 240°C-290°C (25°C / min), 290°C constant temperature for 9 minutes; no split, injection temperature 260°C; interface temperature 270°C; ion source temperature 200°C; electronic energy 70 eV; full scan mode is used, the scan mass range is m / z 30-600 daltons, the spectrum acquisition rate is 20 spectra / s.

[0036] 4. Data processing and analysis

[0037] The serum metabolites detected by GC-MS non-targeted detection were annotated by JiaLib™ metabolic database, and then the detection data were subjected to multivariate and univariate analysis. First, the data were imported into SIMCA software (version 14.0.1, Umetrics) for orthogonal partial least squares-discriminant analysis (OPLS-DA), and the signals unrelated to model classification were filtered to obtain the OPLS-DA model. The quality of the model was tested by cross-validation method, and the R2Y and Q2 (Y explainable variables and model predictable variables) obtained after cross-validation were used to evaluate the effectiveness of the model. The closer R2Y and Q2 to 1, the better the quality of the model, and Q2 greater than 0.5 indicates a better model. The R2 and Q2 obtained by permutation test of the OPLS-DA model were used to further evaluate the model, and Q2 less than 0 indicates a better model. The variable projection importance index (VIP) of the first principal component of the OPLS-DA model was calculated, and then the metabolic data were subjected to univariate analysis by using online analysis software MetaboAnalys (http: / / www.metaboanalyst.ca / ). The difference fold of metabolites between generalized pustular psoriasis patients and healthy volunteers was calculated, and the false discovery rate (FDR) was obtained by Student t test to screen metabolites with FDR value less than 0.05. The metabolites with VIP>1.5 and FDR<0.05 were screened by combining multivariate and univariate analysis results, and were defined as generalized pustular psoriasis candidate metabolic markers.

[0038] II. Results

[0039] 1. Screening of serum differential metabolites

[0040] A total of 123 annotatable metabolites were detected in serum samples by GC-MS. OPLS-DA analysis using SIMCA software obtained an OPLS-DA model (R2Y=0.984, Q2=0.893) Figure 1 ), and the cross-validation method tested the quality of the model to obtain R2Y=0.984, Q2=0.893 Figure 2). Combined with the results of multivariate and univariate analysis, 35 differential metabolites (VIP > 1.5 and FDR < 0.05) were screened in serum samples. See Table 1, these markers are tyramine, pyruvic acid, alpha-ketoisovaleric acid, 2-hydroxybutyric acid, 3-hydroxybutyric acid, methanephosphonothioic acid, L-proline, uracil, tranexamic acid, 4-aminobutyric acid, L-threonine, scopoletin, dodecanol, N-methyl-l-leucine, L-cysteine-glycine, L-kynurenine, 3-hydroxybenzoic acid, allantoin, delta-tocopherol, xylofuranose, glucose-1-phosphate, pyrophosphate, taurine, L-asparagine, phthalic acid, 4-(dimethylamino)azobenzene, 5-tert-butyl-lh-indole-2,3-dione, quinic acid, glucose, L-histidine, L-lysine, palmitelaidic acid, 7-methylguanine, oleic acid, cis-gondoic acid. After checking the published literature, these 35 plasma metabolic markers were first found in the early diagnosis of generalized pustular psoriasis, which has very important significance for the diagnosis and treatment of generalized pustular psoriasis.

[0041] Table 1.

[0042]

[0043]

[0044] 2. Metabolite screening associated with disease severity.

[0045] Based on the 35 serum differential metabolites screened in the previous step, Pearson correlation analysis was performed between the metabolites and the generalized pustular psoriasis disease severity score (JDA score). According to P < 0.05, 5 metabolites associated with disease severity were screened, which were L-threonine, L-cysteine-glycine, pyrophosphate, glucose, and L-histidine (Table 2).

[0046] Table 2.

[0047]

[0048] ROC curve analysis showed that the AUC values of the 5 metabolites were all greater than 0.9, which were L-threonine: AUC = 0.93, 95% CI: 0.85-1.00, P < 0.0001, L-cysteine-glycine: AUC = 0.94, 95% CI: 0.88-1.00, P < 0.0001, pyrophosphate: AUC = 0.98, 95% CI: 0.95-1.00, P < 0.0001, glucose: AUC = 1.00, 95% CI: 1.00-1.00, P < 0.0001, L-histidine: AUC = 0.96, 95% CI: 0.90-1.00, P < 0.0001, see Figure 3 , indicating that the 5 metabolites can well classify the metabolomic data of generalized pustular psoriasis patients and healthy people, and can accurately distinguish patients from healthy people.

[0049] The 35 metabolites can accurately distinguish patients and healthy people, and 5 metabolites are screened from them. The contents of the 5 metabolites are individually associated with the severity of generalized pustular psoriasis, and the ROC curve further determines that the 5 metabolites can be used to predict the disease state individually.

[0050] The diagnostic markers of this invention can effectively distinguish patients with generalized pustular psoriasis from healthy controls, which is beneficial for the clinical diagnosis of generalized pustular psoriasis. They are of great help in improving the clinical diagnosis, treatment and evaluation of generalized pustular psoriasis and have good clinical application and promotion value.

[0051] The above description of the embodiments is only for understanding the method and core ideas of the present invention. It should be noted that, for those skilled in the art, other embodiments based on the patent concept of the present invention will also fall within the protection scope of the claims of the present invention without departing from the principles of the present invention.

Claims

1. The application of a diagnostic marker in the preparation of a diagnostic agent for generalized pustular psoriasis, wherein the diagnostic marker is threonine.

2. The application according to claim 1, characterized in that, The diagnostic markers mentioned are plasma metabolic markers.

3. The application according to claim 1, characterized in that, The diagnostic biomarkers were used as standards for the gas chromatography-mass spectrometry (GC-MS) instrument.

4. The method for screening diagnostic markers for generalized pustular psoriasis as described in claim 1, characterized in that, Includes the following steps: (1) Collect serum samples from patients with generalized pustular psoriasis and healthy volunteers as analytical samples; (2) Non-targeted metabolomics analysis was performed on each sample using GC-MS to obtain the original metabolic fingerprint of each serum sample; (3) Data preprocessing and multivariate statistical analysis were performed on the obtained serum metabolomics fingerprint profiles to screen differential metabolites, and Pearson correlation analysis between differential metabolites and disease severity scores was used to further screen marker metabolites. (4) Differential metabolites with AUC values ​​greater than 0.9 were obtained by ROC curve analysis, which are serum metabolic markers suitable for the diagnosis of generalized pustular psoriasis.

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