CN115372628B - Metabolic marker related to transthyretin amyloidosis and application thereof - Google Patents

Abstract

The invention discloses a metabolic marker related to transthyretin amyloidosis and application thereof, wherein the metabolic marker comprises 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

Metabolic markers associated with transthyretin amyloidosis and their application

technical field

The invention belongs to the field of biomedicine, and specifically relates to metabolic markers related to transthyretin amyloidosis and applications thereof.

Background technique

Transthyretin amyloidosis (ATTR) is a disease caused by the misfolding of transthyretin (TTR) leading to its abnormal deposition in tissues. Transthyretin (TTR) is a plasma transport protein, which is mainly synthesized by the liver, combines with thyroxine and retinol in tetramer form and transports. Abnormal depolymerization of TTR protein is the core mechanism of the disease, and multiple risk factors such as TTR gene mutation site, age, gender, and family history are closely related to the above pathological mechanism. According to the presence or absence of TTR gene mutation, ATTR is divided into mutant type (ATTRm) and wild-type (wild-type TTR, ATTRwt). ATTRm is an autosomal dominant genetic disease. More than 120 pathogenic TTR gene mutation sites have been found so far. The incidence of ATTRm is only 0.87/100,000. As of 2016, the number of patients worldwide is only 38,468. Rare diseases have been included in the first batch of rare disease catalogs in my country. ATTR disease has the characteristics of low incidence, progressive aggravation, diverse clinical manifestations, difficult clinical diagnosis and differential diagnosis, and extremely poor prognosis, with a 5-year survival rate of less than 50%.

Metabolomics is an emerging discipline, as the most downstream of systems biology, it is an important part of systems biology after genomics, transcriptomics and proteomics. The overall research mode of metabolomics can help to understand more comprehensively the changes of metabolites in the process of disease occurrence and development, so it is widely used in the diagnosis, treatment and efficacy evaluation of diseases. As an extension of genomics and proteomics, metabolomics can explain what has actually happened better than the former two, reflecting the comprehensive effects of genes, environment, pathogenic factors, nutrition, drugs and many other factors on the body. The overall response is the end product of gene expression, and the information provided by the analysis results is more comprehensive than that of genomics and proteomics. Through a series of data collection methods, the fingerprints containing all metabolite information are obtained, and the information is extracted by chemometrics to find useful information, and the final and overall information is given through the analysis of the above small molecule metabolites. result.

Therefore, the study of metabolomics of transthyretin amyloidosis is of great significance for revealing the pathogenesis, diagnosis, treatment and efficacy evaluation of the disease.

Contents of the invention

In order to make up for the deficiencies in the prior art, the present invention provides metabolites related to transthyretin amyloidosis. By detecting the level of metabolites, it is judged whether the patient suffers from transthyretin amyloidosis, so as to provide transthyretin Early diagnosis of protein amyloidosis provides a new means.

To achieve the above object, the present invention adopts the following technical solutions:

The first aspect of the present invention provides the application of the reagent for detecting the metabolic marker in the sample in the preparation of the product for diagnosing transthyretin amyloidosis, and the metabolic marker comprises Lysopc 20:4, LysoPE16:0 or Prostaglandin B2 one or several.

Further, the reagent includes detection of Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 content in samples by targeted or non-targeted nuclear magnetic resonance, chromatography, spectrometry, mass spectrometry, liquid mass spectrometry reagent.

Further, the product also includes reagents for processing samples.

Further, the sample is selected from blood.

The second aspect of the present invention provides a product for diagnosing transthyretin amyloidosis, said product comprising reagents for detecting Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 in a sample.

Further, the reagents include reagents for detecting the content of metabolic markers in samples by targeted or non-targeted nuclear magnetic resonance, chromatography, spectroscopy, mass spectrometry, and liquid mass spectrometry.

Further, the products include kits and chips.

The third aspect of the present invention provides the application of Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 in constructing a calculation model for diagnosing transthyretin amyloidosis.

A fourth aspect of the present invention provides a system, the system comprising:

1) A tool for determining the characteristic values of Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 in a sample;

2) A tool for comparing eigenvalues of metabolic values in samples;

3) Data storage medium.

The fifth aspect of the present invention provides the application of Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 in the preparation of a pharmaceutical composition for treating transthyretin amyloidosis.

Advantages and beneficial effects of the present invention:

The present invention discovers for the first time the metabolic markers related to transthyretin amyloidosis, and by detecting the content of metabolic markers, it can be judged whether the subject suffers from transthyretin amyloidosis, so as to realize transthyretin amyloidosis Early diagnosis of degeneration, so as to intervene in the early stage of the disease and improve the quality of life of patients.

Description of drawings

Fig. 1 is Lysopc 20:4 box diagram and ROC diagnostic diagram, wherein, 1A is a box diagram, 1B is a ROC diagnostic diagram;

Figure 2 is a LysoPE 16:0 box diagram and ROC diagnostic diagram, in which 2A is a box diagram and 2B is a ROC diagnostic diagram;

Figure 3 is the box plot of Prostaglandin B2 and the ROC diagnostic plot, in which 3A is the box plot and 3B is the ROC diagnostic plot.

Detailed ways

Definitions of some terms used in this specification are provided below. Unless defined otherwise, all technical and scientific terms used herein generally have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

The invention provides the application of reagents for detecting metabolic markers in samples in the preparation of products for diagnosing transthyretin amyloidosis. The metabolic markers include one or more of Lysopc 20:4, LysoPE 16:0 or ProstaglandinB2. kind.

In the present invention, "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 metabolic substances or metabolites. "Metabolite 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 amount or ratio of two or more metabolites.

In the present invention, "metabolite" means any substance produced by metabolism or necessary for or participating in a specific metabolic process. The term does not include large macromolecules, such as large proteins (e.g., proteins with molecular weights exceeding 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000); large nucleic acids (e.g., molecular weights exceeding 2,000, 3,000, 4,000 , 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000 nucleic acids); or large polysaccharides (such as polysaccharides with molecular weights greater than 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000). The term metabolites includes signaling molecules and intermediates in chemical reactions that convert energy derived from food into usable forms, including but not limited to: sugars, fatty acids, amino acids, nucleosides, antioxidants, vitamins , cofactors, lipids, intermediates and other small molecules formed in cellular processes.

In the present invention, the level or content of metabolites may be one or more of the following: absolute or relative amounts or concentrations of metabolites; presence or absence of metabolites; range of amounts or concentrations of metabolites; minimal and/or maximum amount or concentration; average amount or concentration of metabolites; and/or median amount or concentration of metabolites. As an alternative embodiment, the level for combinations of metabolites may also be a ratio of absolute or relative amounts or concentrations of two or more metabolites relative to each other. Positive and negative reference levels of appropriate metabolites for a particular disease state, its phenotype or deficiency can be determined by measuring the levels of the desired metabolite in one or more appropriate patients, and such reference levels can be modified such that appropriate for a particular patient population (e.g., reference levels can be age-matched so that metabolite levels in samples from patients of a certain age can be correlated with specific disease states, their phenotypes, or lack of reference levels for comparison). As another alternative, the reference level can be adapted to a particular technique that can be used to detect metabolite levels in biological samples (e.g. LC-MS, GC-MS, etc.), Where metabolite levels can vary based on the particular technique used.

In the present invention, the term "diagnosing" refers to distinguishing or determining a disease, syndrome or condition, or to distinguishing or determining a person suffering from a particular disease, syndrome or condition. In an embodiment of the invention, transthyretin amyloidosis in a subject is diagnosed based on analyzing metabolic markers in a sample.

In embodiments of the invention, the diagnosis can be made before clinical signs of disease progression appear. In one embodiment, the invention provides a method of diagnosing transthyretin amyloidosis in a subject in a patient, wherein a sample is collected from the patient and the level of one or more metabolites in the sample is detected. Based on the levels of the detected metabolites, it is determined whether the patient has transthyretin amyloidosis. In an embodiment of the invention, the detected metabolites include Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2. The present invention can be detected by methods well known in the art, including but not limited to simple comparison methods such as manual comparison methods, statistical analysis methods such as t-test, Welch's T-test, Wilcoxon's rank sum test, and random forest algorithm.

Further, the reagents include reagents for detecting the content of metabolic markers in samples by targeted or non-targeted nuclear magnetic resonance, chromatography, spectroscopy, mass spectrometry, and liquid mass spectrometry.

In an embodiment of the present invention, the content of metabolic markers in the sample is detected by chromatography. Chromatography includes GC, CE, LC, HPLC and UHPLC; Spectroscopy includes UV/Vis, IR, NIR and NMR; where, 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 present invention, the content of metabolic markers 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 masses of the resulting ions. Since molecules ionize in a known manner, the molecular weight of the molecule can be determined precisely from the mass of the ions.

Tandem mass spectrometry involves first obtaining a mass spectrum of the ion of interest, followed by fragmentation of the ion and obtaining mass spectra of the fragments. Tandem mass spectrometry thus provides molecular weight information and fragmentation spectra, which can be used together with molecular weight information to identify the exact sequence of a peptide or protein or small molecule (below 1500 Daltons).

In an embodiment of the present invention, the content of metabolic markers in the sample is detected by liquid chromatography-mass spectrometry. Liquid chromatography-mass spectrometry is also called liquid chromatography-mass spectrometry, which uses liquid chromatography as the separation system and mass spectrometry as the detection system. The sample is separated from the mobile part in the mass spectrometer, and after being ionized, the ion fragments are separated according to the mass number by the mass analyzer of the mass spectrometer, and the mass spectrogram is obtained by the detector.

As a preferred embodiment, the product further includes reagents for processing samples.

In embodiments of the invention, a "sample" includes any substance, biological fluid, tissue or cell obtained or otherwise obtained from an individual. It includes blood (including whole blood, white blood cells, peripheral blood mononuclear cells, buffy coat, plasma, and serum), sputum, tears, mucus, nasal washes, nasal aspirate, breath samples, urine, semen, Saliva, meningeal fluid, amniotic fluid, glandular fluid, lymph fluid, nipple aspirates, bronchial aspirates, synovial fluid, joint aspirates, ascites, cells, cell extracts, and cerebrospinal fluid.

In a particular embodiment of the invention, said sample is blood.

The invention provides a system comprising:

1) A tool for determining the characteristic values of Lysopc 20:4, LysoPE 16:0 and/or Prostaglandin B2 in a sample;

2) A tool for comparing eigenvalues of metabolic values in samples;

3) Data storage medium.

A "system" in the present invention refers to different tools operatively connected to each other. The means may be implemented into a single device or may be physically separate devices operatively connected to each other. The means for comparing characteristic values of metabolites preferably operate on the basis of an algorithm for comparison. The data storage medium preferably comprises a data set or database as described above, wherein each of the stored data sets is indicative of transthyretin amyloidosis or a susceptibility thereof. Thus, the system of the present invention allows identifying whether a data set stored in a data storage medium contains a test data set. The system of the invention can be used as a diagnostic tool for the diagnosis of transthyretin amyloidosis or its susceptibility.

In the present invention, the term "means for determining a characteristic value of a metabolite" preferably relates to a device for determining a metabolite, such as a mass spectrometry device, an NMR device, or a device for performing a chemical or biological determination of a metabolite.

In the present invention, the term "data storage medium" includes data storage medium or cloud disk based on a single physical entity such as 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 such a way as to provide the above-mentioned collection of data, preferably in a suitable manner for querying and searching.

The data storage medium in the present invention stores a data set, and the term "data set" refers to a physically and/or logically assembled data set. Accordingly, a collection of data may be implemented in a single data storage medium or in physically separate data storage media operatively connected to each other. Preferably, the data set is committed to a database. Accordingly, a database as used herein encompasses a collection of data on a suitable storage medium. Furthermore, the database preferably also includes a database management system. The database management system is preferably an Internet-based hierarchical database management system or an object-oriented database management system. Also, the database can 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 structured 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, databases can be searched (ie query searches) for similar or identical data sets indicative of transthyretin amyloidosis or a predisposition thereof. Therefore, if the same or a similar data set can be identified in the data set, the trial data set will be related to transthyretin amyloidosis or its susceptibility. As a result, the information obtained from the data set can be used to diagnose transthyretin amyloidosis or a predisposition thereof based on the experimental data set obtained from the subject. More preferably, the data set comprises the characteristic values of all metabolites contained in any one of the groups described above.

Below in conjunction with specific embodiment further elaborates this invention. It should be understood that the specific embodiments described herein are presented by way of example and not as limitations of the invention. The principal characteristics of this invention can be employed in various embodiments without departing from the scope of the invention.

Example Screening and detection of metabolites related to transthyretin amyloidosis

1. Queue recruitment crowd

Twenty-two healthy volunteers and 13 patients diagnosed with hereditary transthyretin amyloidosis (ATTRm) at Peking Union Medical College Hospital were recruited. Diagnosis is confirmed by clinical symptoms, family history, echocardiography, biopsy, and genetic screening. All amyloid patients with elevated light chain levels in blood/urine/bone biopsy or no confirmed TTR mutation were excluded. Other exclusion criteria include: 1) receiving antibiotic treatment _{for ≥} 3 days within 3 months before enrollment; 2) currently suffering from organic digestive system diseases, or having undergone gastrointestinal surgery within 1 year; 3) combined with hyperthyroidism and diabetic ketoacidosis Poisoning, adrenal insufficiency, pregnancy, severe anemia, severe renal insufficiency (eGFR _≤ 15ml/min/1.73m ² ), poisoning or drug side effects; 4) confirmed systemic autoimmune disease (such as systemic lupus erythematosus) or malignant tumors.

Inclusion criteria for the healthy control group: Healthy people confirmed by doctor's consultation, physical examination and blood tests.

For participants, peripheral venous blood was drawn the morning after admission and fresh serum samples were collected and immediately frozen at -80°C. All clinical information was collected according to standard procedures.

This study was approved by the Ethics Committee of Peking Union Medical College Hospital and performed in accordance with the principles of the Declaration of Helsinki. All subjects provided written informed consent to participate in the study.

2. Collection and storage of blood samples

Subjects draw peripheral venous blood in the morning on an empty stomach, use EDTA-K2 anticoagulant blood collection tubes (plasma tubes) and separation gel coagulation tubes (serum tubes) to collect a tube of about 5ml samples each, and collect samples within 1 hour Centrifuge (500g x 10 minutes for plasma tubes, 3500 rpm x 5 minutes for serum tubes), take the supernatant and aliquot into 1.5mleppendorf tubes, and store in a -80°C refrigerator.

3. Serum non-targeted metabolomics detection and differential metabolite screening

Serum metabolomics was analyzed by ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS), using Vanquish ultra-high performance liquid chromatography system (ThermoFisher, Germany) and Orbitrap Q ExactiveTM HF mass spectrometer (Thermo Fisher, Germany), at Novogene Co. , Ltd. (Beijing, China) Instruments. First, sample metabolites were extracted, and then LC-MS/MS was used to detect molecular characteristic peaks. During the detection process, QC samples prepared by mixing equal volumes of experimental samples were used for data quality control. Then, use the CompoundDiscoverer 3.1 (CD3.1) software to perform data preprocessing on the original results of the off-machine. First, simply filter through parameters such as retention time and mass-to-charge ratio. For different samples, according to the retention time deviation and mass deviation (Partper million, ppm) Perform peak alignment to make identification more accurate; then perform peak extraction according to the set ppm, signal-to-noise ratio (S/N), adducted ion and other information, and quantify the peak area at the same time. Then compare the high-resolution secondary spectrum database mzCloud and mzVault and the MassList primary database search for metabolite identification. The specific principle is: determine the molecular weight of the metabolite according to the mass-to-charge ratio (m/z) of the parent ion in the primary mass spectrum, predict the molecular formula through information such as ppm and adducted ions, and then match it with the database; The database matches the actual secondary spectrum with the fragment ions, collision energy and other information of each metabolite in the database to realize the secondary identification of metabolites. Features with coefficient of variation (CV) values less than 30% in quality control (QC) samples were filtered for downstream analysis. Metabolites were analyzed using KEGG database (https://www.genome.jp/kegg/pathway.html), HMDB database (https://hmdb.ca/metabolites) and LIPIDMaps database (http://www.lipidmaps.org/ ) to comment. After obtaining the serum metabolite annotation and quantitative table, use SIMCA software (v14.1, Umetrics, Sweden) to conduct multivariate statistical analysis OPLS-DA, calculate the VIP value of each feature, use the Wilcoxon rank sum test to calculate the significance, and finally select VIP Metabolites with _> 1 and P _< 0.05 were differential metabolites.

4. Assess the diagnostic performance of differential metabolites

The R package pROC was used to calculate the receiver operating curve (ROC) of the differential metabolites, and the area under the curve (AUC) and the optimal cut-off value were calculated to obtain multiple diagnostic models. The differential metabolites with the best AUC values were screened out as candidate diagnostic markers.

5. Experimental results

The results showed that the lipid metabolites LysoPC20:4, LysoPE16:0 and prostaglandinB2 were significantly increased in ATTRm patients, and the diagnostic AUCs were 0.993, 0.996 and 0.982, respectively, which had a high diagnostic and predictive value (Figure 1-Figure 3).

The description of the above embodiments is only for understanding the method and core idea of the present invention. It should be pointed out that for those skilled in the art, without departing from the principles of the present invention, some improvements and modifications can be made to the present invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims (5)

1. Use of a reagent for the detection of a metabolic marker in a sample selected from blood in the manufacture of a product for diagnosing transthyretin amyloidosis, wherein the metabolic marker comprises one or more of Lysopc20, lysoPE 16.

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. The use according to claim 1, wherein the product comprises a kit, a chip.

5. Use of a metabolic marker as claimed in claim 1 for the construction of a computational model for the diagnosis of transthyretin amyloidosis.

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