Application of metabolic markers in the preparation of products for monitoring psoriasis and their products

Abstract

Disclosed is an application of a metabolic marker in the preparation of a product for monitoring psoriasis and a product, which can be used for the early diagnosis of psoriasis, has high sensitivity, is fast and convenient, and has accurate and reliable results, can provide a basis for clinical decision-making, and at the same time provide a certain basis for subsequent basic research and clinical research, and has potential application and research value. The application of this metabolic marker in the preparation of a product for monitoring psoriasis, the metabolic marker includes one or more of suberic acid, L-α-glycerophosphorylcholine, 4-hydroxybenzaldehyde, 6-methylhept-5-en-2-one, and canavanine succinic acid; compared with healthy subjects, the levels of suberic acid, L-α-glycerophosphorylcholine, and 4-hydroxybenzaldehyde in biological samples of psoriasis patients are significantly increased, and the levels of 6-methylhept-5-en-2-one and canavanine succinic acid are significantly decreased.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical testing, and in particular to the use of a metabolic marker in the preparation of a product for monitoring psoriasis, and a product capable of effectively reducing the content of a metabolic marker composition, which is used for the auxiliary treatment of psoriasis. Background Art

[0002] Psoriasis is an immune-mediated chronic, recurrent, inflammatory, systemic disease induced by the combined effects of genetics and the environment. Clinical manifestations are scaly erythema or plaques, which are localized or widely distributed. Psoriasis can be combined with systemic diseases, which seriously affect the patient's quality of life. Psoriasis can occur at any age, and about 2 / 3 of patients develop the disease before the age of 40. The clinical symptoms of psoriasis vary, and the diagnosis is often based on clinical features and dermoscopy. Histological examination is the gold standard for its diagnosis. However, histological examination is an invasive examination, which may be accompanied by complications such as infection or scarring, and can only provide information on a specific area. At present, there is no specific plasma marker for laboratory examination for diagnosis. Therefore, early diagnosis is difficult. Misdiagnosis and missed diagnosis are inevitable, causing patients to miss the best treatment opportunities and leading to delayed disease treatment.

[0003] Metabolomics is a powerful method to study the physiological and pathological state of an organism and the biochemical effects of an organism on exogenous substances. It detects changes in the metabolic products of an organism under the stimulation of various pathogenic factors inside and outside the body, and uses bioinformatics technology to reveal specific metabolic biomarkers that are closely related to the occurrence and development of the disease. Thus, early diagnosis and recurrence diagnosis of the disease can be achieved based on the changes in metabolic biomarkers. Using metabolomics technology, the search for metabolic biomarkers of psoriasis based on clinical biological samples such as serum, tissue, and urine has become a research hotspot in the early diagnosis and clinical classification of the disease. Summary of the invention

[0004] In order to overcome the defects of the prior art, the technical problem to be solved by the present invention is to provide an application of a metabolic marker in the preparation of a product for monitoring psoriasis, which can be used for the early diagnosis of psoriasis, has high sensitivity, is fast and convenient, and the results are accurate and reliable. It can provide a basis for clinical decision-making, and at the same time provide a certain foundation for subsequent basic research and clinical research, and has potential application and research value.

[0005] The technical solution of the present invention is: use of such a metabolite marker in the preparation of a product for monitoring psoriasis, wherein the metabolite marker comprises one or more of suberic acid, L-α-glycerophosphorylcholine, 4-hydroxybenzaldehyde, 6-methylhept-5-en-2-one, and canavanine succinic acid; relative to healthy subjects, the levels of suberic acid, L-α-glycerophosphorylcholine, and 4-hydroxybenzaldehyde in biological samples of psoriasis patients are significantly increased, with a P value of less than 0.05 and a Log2 FC of greater than 1.5, and the levels of 6-methylhept-5-en-2-one and canavanine succinic acid are significantly decreased, with a P value of less than 0.05 and a Log2 FC of less than -2.0.

[0006] The metabolic markers of the present invention can be used for the early diagnosis of psoriasis with high sensitivity, rapidity and convenience, accurate and reliable results, and can provide a basis for clinical decision-making. At the same time, they can provide a certain foundation for subsequent basic research and clinical research, and have potential application and research value.

[0007] Also provided is a preparation of a metabolite marker in the preparation of a product for monitoring psoriasis, wherein the preparation is a composite preparation for reducing the content of the metabolite marker in plasma, and the product is a food, a probiotic preparation or a pharmaceutical preparation. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 Shown is the basic flow chart of the psoriasis metabolomics study of the present invention.

[0009] Figure 2 Shown is the detection result of high-resolution mass spectrometry of the sample in Example 1 of the present invention.

[0010] in, Figure 2 A is the total ion current of positive ion full scan obtained by high-resolution mass spectrometry of the sample; Figure 2 B is the total ion current of the full scan of negative ions obtained by high-resolution mass spectrometry detection of the sample.

[0011] Figure 3 Shown is a metabolomics software library search flow chart.

[0012] Figure 4 The multivariate statistical model diagram of the plasma sample in the first and second embodiments of the present invention is shown. Figure 4 A is the PCA model score graph of the discovery set, Figure 4 B is the score graph of the discovery set OPLS-DA model.

[0013] Among them, the left circle represents the healthy control group, and the right circle represents the psoriasis patients. The results show that HC (healthy control) and psoriasis patients can be well distinguished; Figure 4 C is the PCA model score graph of the validation set. Figure 4D is the validation set OPLS-DA model score diagram. The left circle represents the healthy control group, and the right circle represents the psoriasis patients. The results show that HC (healthy control) and psoriasis patients can be well distinguished.

[0014] Figure 5 Shown is the area under the ROC curve of the markers between healthy controls and psoriasis patients in the discovery set in Example 3 of the present invention.

[0015] Figure 6 Shown is the area under the ROC curve of markers between healthy controls and psoriasis patients in the validation set in Example 3 of the present invention. DETAILED DESCRIPTION

[0016] The use of this metabolite marker in the preparation of a product for monitoring psoriasis, wherein the metabolite marker includes one or more of suberic acid, L-α-glycerophosphorylcholine, 4-hydroxybenzaldehyde, 6-methylhept-5-en-2-one, and canavanine succinic acid; compared with healthy subjects, the levels of suberic acid, L-α-glycerophosphorylcholine, and 4-hydroxybenzaldehyde in biological samples of psoriasis patients are significantly increased, with P values ​​less than 0.05 and Log2 FC greater than 1.5, and the levels of 6-methylhept-5-en-2-one and canavanine succinic acid are significantly decreased, with P values ​​less than 0.05 and Log2 FC less than -2.0.

[0017] The metabolic markers of the present invention can be used for the early diagnosis of psoriasis with high sensitivity, rapidity and convenience, accurate and reliable results, and can provide a basis for clinical decision-making. At the same time, they can provide a certain foundation for subsequent basic research and clinical research, and have potential application and research value.

[0018] Preferably, the biological sample is plasma.

[0019] Preferably, the level of metabolite markers in the biological sample is detected by one or more of the following methods: chromatography, spectroscopy, mass spectrometry, chemical analysis, immunology.

[0020] Preferably, the chromatography includes high performance liquid chromatography, thin layer chromatography, and gas chromatography; the spectroscopy includes nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy, and near infrared spectroscopy; and the chemical analysis includes electrochemical analysis and radiochemical analysis.

[0021] Preferably, the mobile phase in the chromatography method is: mobile phase A is an aqueous solution containing 0.1% formic acid and 2.5 mmol / L ammonium formate, and mobile phase D is acetonitrile; the gradient elution program for sample determination is: 0-1.0 min, 95% A; 1.0-5.0 min, 95%-40% A; 5.0-8.0 min, 40%-0% A; 8.0-11.0 min, 0% A; 11.0-14.0 min, 0%-40% A; 14.0-15.0 min, 40%-95% A; 15.0-18.0 min, 95% A, analysis time is 0 to 18 min, 5 μL is injected each time, the flow rate is 0.25 mL / min, the chromatographic column is: ACQUITY BEH C18 1.7 μm, 2.1×50 mm, and the chromatographic column temperature is 30°C.

[0022] Preferably, the mass spectrometry is a high-resolution mass spectrometry, which first uses a chromatographic column for gradient elution, and then collects data in an electrospray ion source ESI positive and negative ion Full scan-ddMS2 mode.

[0023] Preferably, in the mass spectrometry, spray voltage: 3000 V; evaporation temperature: 350° C.; capillary temperature: 350° C.; S-lens RF: 50; resolution of primary full scan: 70000, scanning range: 70-1050 m / z; secondary data-dependent scan: resolution: 17500, AGC target: 1e5, MaximunTT: 50 ms, NCE: 20, 40, 60.

[0024] Preferably, the biological sample is pretreated before detection as follows: 450 μL of a precipitant containing an internal standard is added to 50 μL of plasma, the internal standard is dissolved in methanol and acetonitrile mixed in equal proportions, vortexed for 30 seconds, centrifuged at 12000 rpm for 10 minutes, and the supernatant is aspirated to obtain a test solution for quantitative analysis.

[0025] Also provided is a preparation of a metabolite marker in the preparation of a product for monitoring psoriasis, wherein the preparation is a composite preparation for reducing the content of the metabolite marker in plasma, and the product is a food, a probiotic preparation or a pharmaceutical preparation.

[0026] Preferably, the levels of metabolic markers in plasma before and after intervention with candidate foods, probiotic preparations or pharmaceutical preparations are detected, and screening is performed based on whether the composition reduces the levels.

[0027] The embodiments of the present invention are described in detail below.

[0028] Example 1

[0029] Discovery set: Screening of metabolic markers between plasma of psoriasis patients and healthy subjects:

[0030] 1. Source of samples:

[0031] After approval by the Ethics Committee of the China-Japan Friendship Hospital, plasma samples from 20 HCs (healthy controls) and 17 psoriasis patients were collected as the discovery set. All participants were from the China-Japan Friendship Hospital, all patients were Han Chinese, aged over 18 years, and were diagnosed with psoriasis by dermatologists referring to the Chinese Psoriasis Diagnosis and Treatment Guidelines. The diagnostic criteria were plaque psoriasis with BSA ≥ 5%; plaque psoriasis with BSA ≥ 3% with or without arthritis psoriasis.

[0032] The age and gender of HC were matched with those of psoriasis patients to exclude metabolic differences caused by gender and age. Blood was collected in the early morning on an empty stomach. All samples were stored at -80°C until use.

[0033] (II) Main reagents:

[0034] LC / MS grade acetonitrile was purchased from Merck, HPLC grade methanol was purchased from Merck, and formic acid was purchased from CNW. Other reagents were commercially available and of analytical grade. Deionized water was prepared using the Milli-Q ultrapure water system from Millipore.

[0035] (III) High-resolution mass spectrometry screening of differential metabolites in plasma:

[0036] 3.1 Sample preparation:

[0037] Sample pretreatment: 50 μL of plasma (healthy control group and psoriasis group) was drawn, 450 μL of precipitant containing internal standard (methanol:acetonitrile=1:1) was added, vortexed for 60 s, centrifuged at 12000 rpm for 10 min, and 100 μL was drawn for metabolomics analysis.

[0038] 3.2 Chromatographic / mass spectrometry conditions:

[0039] High-resolution mass spectrometer QE-Orbitrap was used for detection. Chromatographic mobile phase: Mobile phase A was an aqueous solution containing 0.1% formic acid and 2.5 mmol / L ammonium formate, and mobile phase D was acetonitrile. Gradient elution program for sample determination: 0-1.0 min, 95% A; 1.0-5.0 min, 95%-40% A; 5.0-8.0 min, 40%-0% A; 8.0-11.0 min, 0% A; 11.0-14.0 min, 0%-40% A; 14.0-15.0 min, 40%-95% A; 15.0-18.0 min, 95% A, analysis time 0-18 min, 5 μL each injection, flow rate 0.25 mL / min, chromatographic column: ACQUITY BEH C18 1.7 μm, 2.1×50 mm, column temperature 30°C, and the temperature of the autosampler was maintained at 4°C. Data were collected in positive and negative ion modes of electrospray ion source (ESI), spray voltage: 3000V; evaporation temperature: 350℃; capillary temperature: 350℃; S-lens RF: 50; resolution of full scan: 70000, scanning range: 70-1050m / z. Secondary data dependent scan (Full MS / dd-MS2): resolution: 17500; AGC target: 1e5; MaximunTT: 50ms; NCE: 20, 40, 60.

[0040] High-resolution mass spectrometry results Figure 2 shown.

[0041] 3.3 Metabolic pathway analysis:

[0042] MetaboAnalyst5.0 was used to analyze the differences in endogenous metabolites in the plasma of the healthy control group and the psoriasis group, and the endogenous metabolites with VIP values ​​greater than 1 and P values ​​less than 0.05 were found. Then, the Pathway Analysis in the MetaboAnalyst5.0 website was used to analyze the differential metabolic pathways in plasma, and the metabolic pathways with Impact values ​​greater than 0.1 were selected as the main differential metabolic pathways in plasma.

[0043] (IV) Data processing and statistical analysis:

[0044] The process of establishing a metabolic marker database is as follows: Figure 3As shown. The identification of endogenous metabolites used high-resolution mass spectrometry mzCloud to obtain the 5-decimal accurate mass of each endogenous metabolite, and identified them by the molecular formula of each endogenous metabolite. Then, Compound Discover software was used to automatically search the self-built library and the online public database to annotate the metabolite name. Subsequently, the metabolite matrix was analyzed using the MetaboAnalyst5.0 website, and the PCA and OPLS-DA model diagrams were drawn to find the differences in metabolic patterns and obvious classification trends between healthy people and psoriasis patients. Finally, the metabolic markers with differences were selected according to the standards of VIP>1 and P<0.05.

[0045] (V) Results:

[0046] MetaboAnalyst5.0 website was used to calculate PCA and OPLS-DA. PCA( Figure 4 A) Results show the differences between the plasma of the healthy control group and the plasma of the psoriasis group, OPLS-DA ( Figure 4 B) The results showed that the plasma metabolites of the healthy control group and the psoriasis group could be completely separated. At the same time, endogenous substances with VIP>1, P value less than 0.05, and Log2 FC (difference multiple) greater than 1.5 or less than -2.0 were selected as the main differential metabolites. Table 1 shows the change rate of differential metabolites in plasma obtained using the OPLS-DA model. The results in Table 1 show that there are a total of 83 differential metabolites in plasma. Compared with the healthy control group, the proportion of 45 endogenous substances in the psoriasis group mainly increased, and the other 38 mainly showed a downward trend. The results show that the occurrence of psoriasis affects the metabolic secretion of endogenous substances in plasma, causing a significant change in its content. The main components that changed are amino acids, organic acids, carnitine, and lipid substances.

[0047] Table 1

[0048]

[0049]

[0050]

[0051] Example 2

[0052] Validation set: Validation of metabolic markers between plasma of psoriasis patients and healthy subjects

[0053] 1. Sample collection:

[0054] Plasma samples from 19 HC (healthy controls) and 14 psoriasis patients were collected as validation sets. All participants were from the China-Japan Friendship Hospital. The age and gender of HC were matched with those of psoriasis patients to exclude metabolic differences caused by gender and age. Blood was collected in the early morning on an empty stomach. Fasting plasma samples were collected from the subjects and stored in a -80°C refrigerator for future use.

[0055] (II) Sample testing and statistical analysis: Same as “(III) and (IV)” in Example 1

[0056] (III) Result analysis:

[0057] MetaboAnalyst5.0 website was used to calculate PCA and OPLS-DA. PCA( Figure 4 C) Results show the difference between the plasma of the healthy control group and the plasma of the psoriasis group, OPLS-DA ( Figure 4 D) The results showed that the plasma metabolites of the healthy control group and the psoriasis group could be completely separated. At the same time, endogenous substances with VIP>1, P value less than 0.05, and Log2 FC (difference fold) greater than 1.5 or less than -2.0 were selected as the main differential metabolic pathways for further analysis of plasma. There were 42 differential metabolic markers in the plasma of the discovery set and validation set (19 HC and 14 psoriasis patients) as shown in Table 2. Compared with the healthy control group, the proportion of 25 endogenous substances in the psoriasis group was mainly increased, and the other 17 mainly showed a downward trend. The results further showed that the occurrence of psoriasis affected the metabolic secretion of plasma endogenous substances, causing a significant change in its content.

[0058] Table 2

[0059]

[0060]

[0061] Based on the 42 common serum differential metabolites screened in the previous step, after reviewing the published literature, five plasma metabolic markers including suberic acid, L-α-glycerophosphorylcholine, 4-hydroxybenzaldehyde, 6-methylhept-5-en-2-one and canavanine(yl)succinate were discovered for the first time in the early diagnosis of psoriasis, which is of great significance for the diagnosis and treatment of psoriasis.

[0062] Study on the differences in metabolic pathways of endogenous substances in plasma:

[0063] Table 3 shows the metabolic pathways of plasma analyzed by MetaboAnalyst5.0. The results in Table 3 show that there are significantly different metabolic pathways with Impact values ​​greater than 0.1 between the healthy control group and the psoriasis group. There are mainly 5 different metabolic pathways, showing that the main affected pathways include phenylalanine, tyrosine and tryptophan synthesis, and arginine biosynthesis. The analysis results show that the occurrence of psoriasis affects the metabolism and synthesis of amino acids, thereby leading to changes in the content of endogenous substances in plasma.

[0064] Table 3

[0065]

[0066] Example 3 Analysis of diagnostic performance of plasma metabolic markers

[0067] 1. Data Statistics

[0068] For the discovery set and validation set, we further determined whether five plasma metabolite markers, including suberic acid, L-alpha-Glycerylphosphorylcholine, 4-hydroxybenzaldehyde, 6-Methylhept-5-en-2-one, and canavaninosuccinate, could be used as early diagnostic biomarkers for psoriasis based on the receiver operating characteristic (ROC) curve. SPSS software was used to set the group as the state variable, and the target plasma metabolite measurement intensity as the test variable. After calculating the ROC curve, SPSS generated an output report containing the ROC curve graph and the area under the curve (AUC) value. In large-scale data analysis, an AUC greater than 0.7 can be considered to have good diagnostic ability.

[0069] (II) Results Analysis

[0070] The ROC curve analysis results of the discovery set and validation set showed that the AUC values ​​of the five metabolites were all greater than 0.8, as shown in Table 4. Figure 5 and Figure 6 , indicating that these five metabolites classified the metabolomic data of psoriasis patients and healthy people very well and could accurately distinguish patients from healthy people.

[0071] Table 4

[0072]

[0073] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. Use of a metabolic marker in the preparation of a product for monitoring psoriasis, characterized in that: The metabolite markers include one or more of suberic acid, 4-hydroxybenzaldehyde, 6-methylhept-5-en-2-one, and canavanine succinate; compared with healthy subjects, the levels of suberic acid and 4-hydroxybenzaldehyde in biological samples of psoriasis patients are significantly increased, with a P value less than 0.05 and a Log2 FC greater than 1.5, and the levels of 6-methylhept-5-en-2-one and canavanine succinate are significantly decreased, with a P value less than 0.05 and a Log2 FC less than -2.0; The biological sample is plasma.

2. Use of the metabolic marker according to claim 1 in the preparation of a product for monitoring psoriasis, characterized in that: The level of metabolic markers in biological samples is detected by one or more of the following methods: chromatography, spectroscopy, mass spectrometry, chemical analysis, and immunoassay.

3. Use of the metabolic marker according to claim 2 in the preparation of a product for monitoring psoriasis, characterized in that: The chromatography includes high performance liquid chromatography, thin layer chromatography, and gas chromatography; the spectroscopy includes nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy, and near infrared spectroscopy; the chemical analysis includes electrochemical analysis and radiochemical analysis.

4. Use of the metabolic marker according to claim 3 in the preparation of a product for monitoring psoriasis, characterized in that: The mobile phases in the HPLC method are: mobile phase A is an aqueous solution containing 0.1% formic acid and 2.5 mmol / L ammonium formate, and mobile phase D is acetonitrile; the gradient elution program for sample determination is: 0-1.0 min, 95% A; 1.0-5.0 min, 95%-40% A; 5.0-8.0min, 40%-0%A; 8.0-11.0 min, 0% A; 11.0-14.0 min, 0%-40% A; 14.0-15.0 min, 40%-95% A; 15.0-18.0 min, 95% A, analysis time 0-18 min, 5 μL injection each time, flow rate 0.25 mL / min, chromatographic column: ACQUITY BEH C18 1.7 μm, 2.1×50 mm, column temperature 30 °C.

5. Use of the metabolic marker according to claim 2 in the preparation of a product for monitoring psoriasis, characterized in that: The mass spectrometry is a high-resolution mass spectrometry method, which first uses a chromatographic column for gradient elution, and then collects data in an electrospray ion source ESI positive and negative ion Full scan-ddMS2 mode.

6. Use of the metabolic marker according to claim 5 in the preparation of a product for monitoring psoriasis, characterized in that: In the mass spectrometry, spray voltage: 3000 V; evaporation temperature: 350° C.; capillary temperature: 350° C.; S-lens RF: 50; resolution of primary full scan: 70000, scanning range: 70-1050 m / z; secondary data-dependent scan: resolution: 17500, AGC target: 1e 5 , Maximun TT: 50ms, NCE: 20, 40, 60.

7. Use of the metabolic marker according to claim 1 in the preparation of a product for monitoring psoriasis, characterized in that: The biological sample was pretreated before detection as follows: 50 μL of plasma was added with 450 μL of precipitant containing internal standard, the internal standard was dissolved by mixing methanol and acetonitrile in equal proportions, vortexed for 30 seconds, centrifuged at 12000 rpm for 10 minutes, and the supernatant was aspirated to obtain the test solution for quantitative analysis.

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