CN115372628A - Metabolic marker related to transthyretin amyloidosis and application thereof - Google Patents
Metabolic marker related to transthyretin amyloidosis and application thereof Download PDFInfo
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Abstract
The invention discloses transthyretin amyloidosis-associated metabolic markers and application thereof, wherein the metabolic markers comprise Lysopc20, lysoPE 16. The invention discovers for the first time that the metabolic marker shows significant difference between a transthyretin amyloidosis patient and a healthy population, and has a higher AUC value, which prompts that the metabolic marker has higher diagnostic value in the transthyretin amyloidosis.
Description
Technical Field
The invention belongs to the field of biomedicine, and particularly relates to a transthyretin amyloidosis-related metabolic marker and application thereof.
Background
Transthyretin Amyloidosis (ATTR) is a disease caused by the abnormal deposition of transthyretin (TTR) in tissues due to its misfolding. Transthyretin (TTR) is a plasma transport protein, which is synthesized primarily by the liver, binds to and transports thyroxine and retinol in a tetrameric form. Abnormal depolymerization of TTR protein is the core mechanism of the disease, and multiple risk factors such as the mutation site, age, sex, family history and the like of TTR gene are closely related to the pathological mechanism. ATTR is classified into a mutant type (ATTRm) and a wild type (wild-type TTR, ATTRwt) according to the presence or absence of a mutation in the TTR gene. ATTRm is an autosomal dominant hereditary disease, more than 120 pathogenic TTR gene mutation sites are found at present, the incidence rate of ATTRm is only 0.87/100,000, only 38468 patients are suffered in the world as far as 2016, and the ATTRm is a rare disease and has been selected from the first rare disease list in China. ATTR disease has the characteristics of low morbidity, progressive exacerbation, various clinical manifestations, great difficulty in clinical diagnosis and differential diagnosis and the like, and has extremely poor prognosis and 5-year survival rate of less than 50%.
Metabolomics is an emerging developing discipline, and is an important component of system biology after genomics, transcriptomics and proteomics as the most downstream of system biology. The mode of research of the whole metabonomics can help to more comprehensively understand the change rule of the metabolic substances in the process of disease occurrence and development, so that the metabonomics is generally applied to the aspects of disease diagnosis, treatment, curative effect evaluation and the like. As the extension of genomics and proteomics, metabonomics can be more specific than the former two, the total reaction of genes, environment, pathogenic factors, nutrition, medicines and other factors after comprehensively acting on organisms is reflected, the final product of gene expression is reflected, and the information provided by the analysis result is more comprehensive than that of genomics and proteomics. The fingerprint containing all metabolite information is obtained through a series of data acquisition means, the information is extracted by using chemometrics, useful information is found out, and a final and integral result is given through the analysis of the small molecule metabolites.
Therefore, the research on the metabonomics of transthyretin amyloidosis is of great significance for the disclosure of pathogenesis and the diagnosis, treatment and efficacy evaluation of diseases.
Disclosure of Invention
In order to make up the defects of the prior art, the invention provides a metabolite related to transthyretin amyloidosis, and whether a patient has the transthyretin amyloidosis is judged by detecting the level of the metabolite, thereby providing a new means for the early diagnosis of the transthyretin amyloidosis.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides the use of a reagent for detecting a metabolic marker in a sample, the metabolic marker comprising one or more of Lysopc20, lysoPE16:0 or Prostaglandin B2, in the preparation of a product for diagnosing transthyretin amyloidosis.
Further, the reagents include reagents for detecting the Lysopc 20.
Further, the product also includes reagents for processing the sample.
Further, the sample is selected from blood.
A second aspect of the invention provides a product for use in the diagnosis of transthyretin amyloidosis, which product comprises a reagent which detects Lysopc20, lysoPE16 and/or Prostaglandin B2 in a sample.
Further, the reagent comprises a reagent for detecting the content of the metabolic marker in the sample by targeted or non-targeted nuclear magnetic resonance method, chromatography, spectrometry, mass spectrometry and liquid chromatography-mass spectrometry.
Further, the product comprises a kit and a chip.
A third aspect of the invention provides the use of Lysopc20, lysoPE 16.
A fourth aspect of the invention provides a system comprising:
1) Means for determining the characteristic values of Lysopc20, lysoPE16 and/or Prostaglandin B2 in a sample;
2) Means for comparing the characteristic value of the metabolic value in the sample;
3) A data storage medium.
A fifth aspect of the invention provides the use of Lysopc20, lysoPE 16.
The invention has the advantages and beneficial effects that:
the invention discovers the metabolic marker related to the transthyretin amyloidosis for the first time, and can judge whether a subject has the transthyretin amyloidosis or not by detecting the content of the metabolic marker so as to realize the early diagnosis of the transthyretin amyloidosis, thereby carrying out intervention treatment at the early stage of the disease and improving the life quality of the patient.
Drawings
FIG. 1 is a Lysopc 20;
FIG. 2 is a LysoPE16 box plot of 0 and a ROC diagnostic plot, wherein 2A is a box plot and 2B is a ROC diagnostic plot;
FIG. 3 is a Prostagladin B2 box diagram and a ROC diagnostic diagram, wherein 3A is a box diagram and 3B is a ROC diagnostic diagram.
Detailed Description
The following provides definitions of some terms used in this specification. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides application of a reagent for detecting a metabolic marker in a sample in preparing a product for diagnosing transthyretin amyloidosis, wherein the metabolic marker comprises one or more of Lysopc 20.
In the present invention, a "metabolic marker" or "metabolite marker" is defined as a compound suitable as an indicator of the presence and status of transthyretin amyloidosis, which is a metabolite or metabolic compound occurring during metabolic processes in the body of a mammal. "metabolic marker" or "metabolite marker" is generally used synonymously in the context of the present invention and generally refers to the amount of one metabolite or the content or ratio of two or more metabolites.
In the present invention, "metabolite" means any substance produced by metabolism or necessary for or involved in a specific metabolic process. The term does not include large, bulky molecules, such as large proteins (e.g., proteins with molecular weights in excess of 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000); large nucleic acids (e.g., nucleic acids having a molecular weight of greater than 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000); or large polysaccharides (e.g., polysaccharides having a molecular weight of greater than 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000). The term metabolite includes signal transduction molecules and intermediates in chemical reactions that convert food-derived energy into a useful form, including, but not limited to: sugars, fatty acids, amino acids, nucleosides, antioxidants, vitamins, cofactors, lipids, intermediates formed in cellular processes (cellular processes), and other small molecules.
In the present invention, the level or amount of the metabolite may be one or more of the following: absolute or relative amounts or concentrations of metabolites; the presence or absence of a metabolite; the amount or range of concentrations of the metabolite; a minimum and/or maximum amount or concentration of a metabolite; the average amount or concentration of the metabolite; and/or the median number or concentration of metabolites. As an alternative embodiment, the level for a combination of metabolites may also be a ratio of absolute or relative amounts or concentrations of two or more metabolites that are related to each other. The positive and negative reference levels for the appropriate metabolites for a particular disease state, its phenotype or deficiency may be determined by detecting the levels of the desired metabolites in one or more appropriate patients, and such reference levels may be adapted to suit a particular patient population (e.g., the reference levels may be age-matched so that a comparison may be made between the levels of metabolites in a patient sample obtained from a certain age and the reference levels for a particular disease state, its phenotype or deficiency in a certain age group). As another alternative, the reference level may be modified to suit a particular technique that may be used to detect metabolite levels (e.g., LC-MS, GC-MS, etc.) in a biological sample, where metabolite levels may vary based on the particular technique used.
In the present invention, the term "diagnosis" refers to the differentiation or determination of a disease, syndrome or condition, or to the differentiation or determination of a person having a particular disease, syndrome or condition. In embodiments of the invention, transthyretin amyloidosis is diagnosed in a subject based on analyzing metabolic markers in a sample.
In embodiments of the invention, the diagnosis may be made prior to the occurrence of clinical signs of disease progression. In one embodiment, the invention provides a method of diagnosing a subject as having transthyretin amyloidosis in a patient, wherein a sample is collected from the patient and the level of one or more metabolites in the sample is detected. Determining whether the patient has transthyretin amyloidosis based on the level of the detected metabolite. In an embodiment of the invention, the metabolites detected include Lysopc20, lysoPE 16. The present invention can be tested using methods well known in the art, including, but not limited to, simple comparisons such as manual comparisons, statistical analyses such as t-tests, welch's T-test, wilcoxon's rank-sum test, random forest algorithms.
Further, the reagent comprises a reagent for detecting the content of the metabolic marker in the sample by targeted or non-targeted nuclear magnetic resonance method, chromatography, spectroscopy, mass spectrometry and liquid chromatography-mass spectrometry.
In an embodiment of the invention, the metabolic marker content in the sample is determined by chromatography. Chromatograms include GC, CE, LC, HPLC and UHPLC; spectra include UV/Vis, IR, NIR and NMR; wherein, GC = gas chromatography, CE = capillary electrophoresis, LC = liquid chromatography, HPLC = high liquid chromatography, UHPLC = ultra high performance liquid chromatography, UV-Vis = ultraviolet visible, IR = infrared, NIR = near-infrared, NMR = nuclear magnetic resonance.
In an embodiment of the invention, the amount of the metabolic marker in the sample is detected by mass spectrometry. Mass spectrometry includes, for example, tandem mass spectrometry, matrix Assisted Laser Desorption Ionization (MALDI) time of flight (TOF) mass spectrometry, MALDI-TOF-TOF mass spectrometry, MALDI quadrupole-time of flight (Q-TOF) mass spectrometry, electrospray ionization (ESI) -TOF mass spectrometry, ESI-Q-TOF, ESI-TOF-TOF, ESI-ion trap mass spectrometry, ESI triple quadrupole mass spectrometry, ESI Fourier Transform Mass Spectrometry (FTMS), MALDI-FTMS, MALDI-ion trap-TOF, and ESI-ion trap TOF. At its most basic level, mass spectrometry involves ionizing molecules and subsequently measuring the mass of the resulting ions. Since the molecules are ionized in a known manner, the molecular weight of the molecules can be accurately determined from the mass of the ions.
Tandem mass spectrometry involves first obtaining a mass spectrum of an ion of interest, then fragmenting the ion and obtaining a mass spectrum of the fragment. Tandem mass spectrometry thus provides molecular weight information and fragmentation spectra that can be used together with the molecular weight information to identify the exact sequence of a peptide or protein or small molecule (below 1500 daltons).
In an embodiment of the invention, the amount of the metabolic marker in the sample is measured by LC-MS. The LC-MS technology is also called as LC-MS technology, and uses LC as separation system and MS as detection system. The sample is separated in the mass spectrum part and the flow part, ionized, and then separated according to the mass number of ion fragments by a mass analyzer of the mass spectrum, and a mass spectrogram is obtained by a detector.
As a preferred embodiment, the product further comprises reagents for processing the sample.
In embodiments of the invention, a "sample" includes any substance, biological fluid, tissue, or cell obtained or otherwise taken from an individual. It includes blood (including whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma and serum), sputum, tears, mucus, nasal wash, nasal aspirate, breath-like, urine, semen, saliva, meningeal fluid, amniotic fluid, glandular fluid, lymph fluid, nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, ascites, cells, cell extracts and cerebrospinal fluid.
In a particular embodiment of the invention, the sample is blood.
The present invention provides a system, comprising:
1) Means for determining the Lysopc20, lysoPE16 and/or Prostaglandin B2 signature in a sample;
2) Means for comparing the characteristic value of the metabolic value in the sample;
3) A data storage medium.
The "system" in the present invention relates to different tools operatively connected to each other. The tools may be embodied in a single device or may be physically separate devices operatively connected to each other. The means for comparing metabolite feature values preferably operate based on an algorithm for comparison. The data storage medium preferably comprises a data set or database as described above, wherein each set of stored data sets is indicative of transthyretin amyloidosis or a susceptibility thereof. The system of the present invention thus allows to identify whether a data set stored in a data storage medium contains a test data set. The system of the invention is useful as a diagnostic tool for diagnosing transthyretin amyloidosis or a susceptibility thereof.
In the present invention, the term "means for determining characteristic values of metabolites" preferably relates to devices for determining metabolites, such as mass spectrometry devices, NMR devices, or devices for performing chemical or biological assays of metabolites.
In the present invention, the term "data storage medium" includes a data storage medium or a cloud based on a single physical entity, such as a CD, CD-ROM, hard disk, optical storage medium or magnetic disk. Furthermore, the term also includes data storage media consisting of physically separate entities operatively connected to each other in a manner that provides the data collection described above, preferably in a suitable manner for query searching.
The data storage medium of the present invention stores data sets, and the term "data set" refers to a physically and/or logically aggregated data set. Thus, the data sets may be embodied in a single data storage medium or in physically separate data storage media that are operatively coupled to each other. Preferably, the data set is implemented into a database. Thus, a database as used herein comprises a collection of data on a suitable storage medium. In addition, the database preferably also contains a database management system. The database management system is preferably an internet-based hierarchical database management system or an object-oriented database management system. Further, the database may be a federated database or an integrated database. More preferably, the database will be implemented as a distributed (federated) System, such as a Client-Server-System. More preferably, the database is constructed to allow a search algorithm to compare the test data set with the data set comprising the data set. In particular, by using such algorithms, the database can be searched (i.e., a query search) for similar or identical data sets indicative of transthyretin amyloidosis or a susceptibility thereof. Thus, if the same or similar data set can be identified in the data set, the test data set will be associated with transthyretin amyloidosis or a susceptibility thereof. As a result, the information obtained from the data set can be used to diagnose transthyretin amyloidosis, or a susceptibility thereof, based on the test data set obtained from the subject. More preferably, the data set comprises characteristic values for all metabolites comprised in any one of the groups as set out above.
The invention is further illustrated below with reference to specific examples. It should be understood that the particular embodiments described herein are presented by way of example and not as limitations of the invention. The principal features of this invention can be employed in various embodiments without departing from the scope of the invention.
Example screening and detection of transthyretin amyloidosis-associated metabolites
1. Crowd recruited in queue
22 healthy volunteers and 13 patients diagnosed with hereditary transthyretin amyloidosis (ATTRm) in Beijing coordination and Hospital were recruited. Diagnosis is validated by clinical symptoms, family history, echocardiography, biopsy, and genetic screening. All amyloid patients with elevated light chain levels or unidentified TTR mutations in blood/urine/bone biopsies were excluded. Other exclusion criteria included: 1) Receiving antibiotic therapy within 3 months before group entry ≥ 3 days; 2) Now suffering from organic digestive system diseases, or having undergone digestive tract surgery within 1 year; 3) With hyperthyroidism, diabetic ketoacidosis, adrenal insufficiency, pregnancy, severe anemia, and severe renal insufficiency (eGFR) ≤ 15ml/min/1.73m 2 ) Poisoning or drug side effects; 4) Systemic autoimmune diseases (such as systemic lupus erythematosus) or malignant tumors are diagnosed.
Healthy control group entry criteria: doctors make inquiries, physical examination and blood tests to identify healthy people.
For participants, peripheral venous blood was drawn the next morning after admission and fresh serum samples were collected and immediately frozen at-80 ℃. All clinical information was collected according to standard procedures.
The study was approved by the ethical committee of the Beijing coordination hospital and was performed according to the principles of the declaration of Helsinki. All subjects provided written informed consent for participation in the study.
2. Blood sample collection and preservation
The subjects collected peripheral venous blood in the early morning on an empty stomach, collected about 5ml samples from 1 tube each using an EDTA-K2 anticoagulation blood tube (plasma tube) and a separation gel procoagulant tube (serum tube), centrifuged within 1 hour after the samples were obtained (plasma tube 500 g.times.10 minutes, serum tube 3500 rpm.times.5 minutes), and the supernatants were dispensed into 1.5ml eppendorf tubes and stored in a refrigerator at-80 ℃.
3. Serum non-targeted metabonomics detection and differential metabolite screening
Serum metabonomics were analyzed using ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS) during which a Vanquish ultra-high performance liquid chromatography system (Thermo Fisher, germany) and an Orbitrap Q exact HF mass spectrometer (Thermo Fisher, germany) were used in Novogene co. Firstly, extracting metabolites of a sample, then detecting a molecular characteristic peak by an LC-MS/MS machine, and performing data quality control by using a QC sample prepared by mixing experiment samples in equal volumes in the detection process. Secondly, performing data preprocessing on the off-line original result by using CompundDiscoverer 3.1 (CD 3.1) software, simply screening parameters such as retention time, mass-to-charge ratio and the like, and performing peak alignment on different samples according to retention time deviation and mass deviation (Partper million, ppm) so as to ensure more accurate identification; subsequently, peak extraction is carried out according to information such as set ppm, signal-to-noise ratio (S/N), adduct ions and the like, and meanwhile, the peak area is quantified. And then comparing the high-resolution secondary spectrogram databases mzCloud and mzVault with the MassList for primary database retrieval, and identifying the metabolites. The specific principle is as follows: determining the molecular weight of a metabolite according to the mass-to-charge ratio (m/z) of parent ions in the primary mass spectrum, predicting the molecular formula according to information such as ppm and adduct ions, and matching with a database; and the database containing the secondary spectrogram is matched with information such as fragment ions, collision energy and the like of each metabolite in the database according to the actual secondary spectrogram, so that secondary identification of the metabolite is realized. The features with Coefficient of Variation (CV) values less than 30% in the Quality Control (QC) samples were filtered for downstream analysis. The metabolites used the KEGG database (https:// www. Genome. Jp/KEGG/pathway. Html), the HMDB database (https:// HMDB. Ca/metabolites), and the LIPADMaps database (http:// www).Comments. Org /). Obtaining serum metabolite annotation and quantitative table, performing multivariate statistical analysis on OPLS-DA by using SIMCA software (v 14.1, umetrics, sweden), calculating VIP value of each feature, calculating significance by using Wilcoxon rank sum test, and finally selecting VIP ＞ 1 and P ＜ The metabolite of 0.05 was a differential metabolite.
4. Evaluating diagnostic efficacy of differential metabolites
The multiple diagnostic models were obtained by calculating the Receiver Operating Curve (ROC) for differential metabolites using the R package pROC, calculating the area under the curve (AUC) and the optimal Cut-off value. And screening the differential metabolite with the optimal AUC value as a candidate diagnostic marker.
5. Results of the experiment
As a result, the lipid metabolites LysoPC20:4, lysoPE16.
The above description of the embodiments is only intended to illustrate the method of the invention and its core idea. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications will also fall into the protection scope of the claims of the present invention.
Claims (10)
1. Use of a reagent for detecting a metabolic marker in a sample for the manufacture of a product for diagnosing transthyretin amyloidosis, wherein the metabolic marker comprises one or more of Lysopc 20.
2. The use of claim 1, wherein the reagent comprises a reagent for detecting the amount of a metabolic marker in a sample by targeted or non-targeted nuclear magnetic resonance, chromatography, spectroscopy, mass spectrometry, or LC-MS.
3. The use of claim 1, wherein the product further comprises a reagent for processing the sample.
4. Use according to claim 3, wherein the sample is selected from blood.
5. A product for diagnosing transthyretin amyloidosis, comprising a reagent for detecting a metabolic marker as claimed in claim 1 in a sample.
6. The product of claim 5, wherein the reagents comprise reagents for detecting the amount of metabolic markers in the sample by targeted or non-targeted nuclear magnetic resonance, chromatography, spectroscopy, mass spectrometry, or LC MS.
7. The product of claim 5, wherein the product comprises a kit or chip.
8. Use of a metabolic marker as claimed in claim 1 for the construction of a computational model for the diagnosis of transthyretin amyloidosis.
9. A system, characterized in that the system comprises:
1) Means for determining in a sample a value characteristic of a metabolic marker as defined in claim 1;
2) Means for comparing the characteristic value of the metabolic value in the sample;
3) A data storage medium.
10. Use of a metabolic marker as claimed in claim 1 for the preparation of a pharmaceutical composition for the treatment of transthyretin amyloidosis.
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| A H JAFAR AND A J SINCLAIR: ""Free radicals and vascular disease."" * |
| ISABELL NESSEL ET AL.: ""Lipid profiling of brain tissue and blood after traumatic brain injury A review of human and experimental studies"" * |
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