Serological biomarkers for diagnosing chronic obstructive pulmonary disease

Abstract

The invention relates to the technical field of biomedicine, in particular to a serological biomarker for diagnosing chronic obstructive pulmonary disease. The marker is selected from the group consisting of myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatetraenoic acid, nervonic acid, wood tar acid, arginine and glutamine. The combined marker has relatively high sensitivity and specificity, can provide reliable diagnosis information in an early stage or an atypical stage of symptoms, and overcomes the limitations of dependence on lung function detection, insufficient sensitivity, complex operation and the like of the existing diagnosis means; therefore, a convenient and accurate detection tool capable of being popularized is provided for early screening, risk prediction and clinical diagnosis of the chronic obstructive pulmonary disease.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to serum biomarkers for the diagnosis of chronic obstructive pulmonary disease. Background Technology

[0002] Chronic obstructive pulmonary disease (COPD) is a heterogeneous lung disease characterized by irreversible airflow limitation and corresponding respiratory symptoms. It is characterized by high morbidity, high disability rate, and high mortality rate, seriously endangering human health. Due to the insidious nature of early COPD symptoms and limited diagnostic methods, approximately half of all COPD patients are not diagnosed in a timely manner, leading to disease progression to the middle and late stages before discovery and missing the optimal intervention window. COPD prevention and control in my country still faces challenges such as low diagnosis rates and insufficient screening at the grassroots level. Currently, COPD diagnosis mainly relies on pulmonary function tests, combined with clinical symptoms (such as chronic cough and dyspnea) and risk factor assessment. Various diagnostic techniques have limitations, including high operational difficulty, insufficient sensitivity, high cost, and insufficient specificity. Therefore, finding a highly sensitive diagnostic method capable of early screening for COPD is urgently needed.

[0003] Abnormalities in amino acid and free fatty acid metabolism are closely related to the pathogenesis and progression of COPD, and have become a hot topic in metabolomics research in recent years. Multiple studies have shown that serum free fatty acid levels in patients with varying degrees of COPD are correlated with lung function. Furthermore, serum glycine, histidine, and threonine levels in COPD patients are consistently lower than in non-COPD smokers. However, their clinical application is limited due to the lack of detailed metabolomic profiling of amino acids and free fatty acids. Although many studies have indicated that dysregulation of amino acid and free fatty acid metabolism may play a crucial role in the development of COPD, the underlying mechanisms remain unclear. Moreover, circulating free fatty acid and amino acid levels have not been quantitatively assessed in large-scale cohorts, and effective predictive models for COPD have not yet been developed. Summary of the Invention

[0004] This invention covers the following technical solutions: One aspect of the present invention relates to the use of a quantitative detection agent for a biomarker in the preparation of a kit for diagnosing chronic obstructive pulmonary disease; The markers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine.

[0005] Another aspect of the invention relates to a system for diagnosing chronic obstructive pulmonary disease, the system comprising: Sample information processing module, diagnostic module, and information output module; The sample information module is used to receive information from the test subject. The test subject information includes at least the biomarker concentration information from the test subject sample. The biomarkers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine. The diagnostic module receives information input from the sample information processing module, determines the risk of chronic obstructive pulmonary disease, and outputs the determination result to the information output module.

[0006] Another aspect of the present invention relates to a computer-readable storage medium for storing computer instructions, programs, code sets, or instruction sets, which, when run on a computer, cause the computer to perform the functions corresponding to the sample information processing module, the diagnostic module, and the information output module described above in the system.

[0007] Another aspect of the present invention relates to an electronic device comprising: One or more processors; and a computer-readable storage medium for storing computer instructions, programs, code sets, or instruction sets that, when run on a computer, cause the one or more processors to perform the functions corresponding to the sample information processing module, the diagnostic module, and the information output module in the system described above.

[0008] This invention provides a novel combination of serum biomarkers for diagnosing chronic obstructive pulmonary disease (COPD), enabling effective differentiation between COPD patients and healthy individuals. This combination of biomarkers exhibits high sensitivity and specificity, providing reliable diagnostic information in early stages or when symptoms are atypical. It overcomes the limitations of existing diagnostic methods, such as reliance on pulmonary function tests, insufficient sensitivity, and complex procedures, thus providing a convenient, accurate, and widely applicable detection tool for early screening, risk prediction, and clinical diagnosis of COPD. Attached Figure Description

[0009] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0010] Figure 1Serum amino acid and free fatty acid levels in COPD patients; (A) Volcano plot showing differentially expressed metabolites between COPD and control groups; (B) List of upregulated and downregulated metabolites in COPD and control groups, respectively.

[0011] Figure 2 A machine learning-based diagnostic model for COPD; (A) Potential biomarkers selected by a random forest model based on 25 differentially expressed metabolites and LASSO regression analysis; (B) ROC curves of 12 metabolite combinations in the training and test sets. Detailed Implementation

[0012] Reference will now be made to detailed embodiments of the present invention, one or more of which are described below. Each example is provided for explanation and not for limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made to the invention without departing from its scope or spirit. For example, features described or illustrated as part of one embodiment may be used in another embodiment to produce further embodiments.

[0013] Unless otherwise stated, all terms used to disclose this invention (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Further guidance is provided below for a better understanding of the teachings of this invention. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0014] In this invention, unless otherwise stated, the scientific and technical terms used herein have the meanings commonly understood by those skilled in the art. Furthermore, the protein and nucleic acid chemistry, molecular biology, cell and tissue culture, immunology-related terms and laboratory procedures used herein are all widely used terms and routine procedures in their respective fields. To better understand this invention, definitions and explanations of relevant terms are provided below.

[0015] The terms "and / or," "or / and," and "and / or" as used herein include any one of two or more of the related listed items, as well as any and all combinations of the related listed items. These arbitrary and all combinations include any two related listed items, any more related listed items, or a combination of all related listed items. It should be noted that when at least three items are connected using at least two conjunctions selected from "and / or," "or / and," and "and / or," it should be understood that in this invention, the technical solution undoubtedly includes solutions connected by "logical AND," and also undoubtedly includes solutions connected by "logical OR." For example, "A and / or B" includes three parallel solutions: A, B, and A+B. For example, the technical solution of "A, and / or, B, and / or, C, and / or, D" includes any one of A, B, C, and D (that is, a technical solution that is connected by "logical OR"), as well as any and all combinations of A, B, C, and D, that is, combinations of any two or three of A, B, C, and D, and also combinations of all four of A, B, C, and D (that is, a technical solution that is connected by "logical AND").

[0016] The terms “containing,” “comprising,” and “including” as used in this invention are synonyms and are inclusive or open-ended, not excluding additional, uncited members, elements, or method steps.

[0017] In this invention, the numerical range represented by endpoints includes all numerical values ​​and fractions contained within that range, as well as the endpoints mentioned.

[0018] As used in this invention, the term "about" or "approximately" means within 20%, preferably within 10%, and more preferably within 5%, of a given value or range. It also includes specific numbers, such as about 20 including 20.

[0019] Furthermore, in describing representative embodiments of the invention, this specification may present the methods and / or processes of the invention as a specific sequence of steps. However, the method or process should not be limited to the specific order of the steps described herein, to the extent that the method or process does not depend on the specific order of the steps presented herein. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps presented in the specification should not be construed as a limitation of the claims. Additionally, the claims relating to the methods and / or processes of the invention should not be limited to the execution of their steps in the order they are written, and those skilled in the art will readily recognize that the sequence can be changed while still remaining within the spirit and scope of the invention.

[0020] This invention relates to concentration values, which include fluctuations within a certain range. For example, fluctuations are allowed within a corresponding precision range. For instance, 2% can fluctuate within ±0.1%. For larger values ​​or values ​​that do not require overly precise control, even greater fluctuations are permitted. For example, 100 mM can fluctuate within ranges of ±1%, ±2%, ±5%, etc. Regarding molecular weight, fluctuations of ±10% are allowed.

[0021] As used in this invention, unless otherwise stated, the singular forms of the articles “a,” “an,” and “the” include plural referents.

[0022] In this invention, the terms "multiple" or "various" are used unless otherwise specified, referring to a quantity of 2 or more.

[0023] In this invention, the technical features described in an open-ended manner include both closed-ended technical solutions composed of the listed features and open-ended technical solutions that include the listed features.

[0024] In this invention, terms such as "preferred," "better," "more suitable," and "ideal" merely describe implementation methods or embodiments with better effects and should be understood not to limit the scope of protection of this invention. In this invention, terms such as "optionally," "optionally," and "optional" mean that something is optional, that is, selected from either "with" or "without" a parallel solution. If multiple "optional" statements appear in a technical solution, unless otherwise specified and without contradiction or mutual constraint, each "optional" statement is independent.

[0025] In this invention, "diagnosis" refers to the identification or assessment of whether an individual suffers from a specific disease, pathological state, or abnormal physiological state, or is at risk of disease, in a disease progression stage, or in a treatment response period, through the detection, measurement, or analysis of one or more biomarkers, physiological parameters, clinical symptoms, behavioral indicators, or imaging results. Diagnosis includes both preliminary judgment of the disease and classification, staging, risk prediction, recurrence risk assessment, and treatment response evaluation. Diagnosis can be an auxiliary diagnostic tool.

[0026] In this invention, "chronic obstructive pulmonary disease" refers to a heterogeneous group of lung diseases characterized by persistent, progressive airflow limitation, usually accompanied by chronic airway inflammation. Its pathophysiological basis includes small airway lesions (such as chronic bronchitis) and / or lung parenchymal destruction (such as emphysema), and the airflow limitation is not completely reversible. Chronic obstructive pulmonary disease includes, but is not limited to, chronic bronchitis-type COPD, emphysematous COPD, mixed COPD, and acute exacerbation COPD.

[0027] All references to this invention are incorporated herein by reference as if each document were individually incorporated herein by reference. Unless they conflict with the inventive purpose and / or technical solution of this invention, the referenced documents are incorporated herein by reference in their entirety and for all purposes. When references are made in this invention, the definitions of relevant technical features, terms, nouns, phrases, etc., are also incorporated herein by reference. Examples and preferred embodiments of the referenced technical features may also be incorporated herein by reference, but only to the extent that they enable the implementation of this invention. It should be understood that when the cited content conflicts with the description in this invention, this invention shall prevail or modifications shall be made adaptively according to the description in this invention.

[0028] This invention relates to the use of a quantitative detection reagent for biomarkers in the preparation of a kit for diagnosing chronic obstructive pulmonary disease; The markers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine.

[0029] This invention establishes a metabolic profile of chronic obstructive pulmonary disease (COPD) in a large Chinese cohort, performs targeted metabolomics analysis on serum free fatty acid and amino acid levels in COPD patients and age- and sex-matched healthy controls, and then applies multivariate statistical analysis and machine learning algorithms to identify key metabolites that may have informational value for the clinical diagnosis of COPD, thus providing a foundation for the diagnosis of COPD.

[0030] In some embodiments, the marker is selected from at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or all of the following: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine and glutamine.

[0031] In some embodiments, the quantitative detection reagent is used to perform one or more of the following methods: Liquid chromatography-tandem mass spectrometry, ultra-high performance liquid chromatography-tandem mass spectrometry, liquid chromatography-high resolution mass spectrometry, nuclear magnetic resonance spectroscopy.

[0032] In some embodiments, the test samples for the kit are selected from: blood, serum, plasma, cell or tissue extracts, cerebrospinal fluid, and urine.

[0033] The term "cell or tissue lysate" as used herein is also interchangeable with "lysate," "lysed sample," and "cell or tissue extract," referring to a sample and / or biological sample material containing lysed cells or tissue, i.e., in which the structural integrity of the cells or tissue has been disrupted. To release the contents of a cell or tissue sample, the material is typically treated with enzymes and / or chemical reagents to dissolve, degrade, or disrupt the cell walls and cell membranes of such tissues or cells. Skilled technicians are very familiar with the appropriate methods used to obtain lysates. This process is encompassed by the term "lysis."

[0034] In some embodiments, the kit further comprises at least one of the following: reagents for extracting biomarkers from samples, standards, and internal standards. Examples of reagents for extracting biomarkers include organic solvents (such as methanol, acetonitrile, etc.), acid / buffer solutions (formic acid, acetic acid, ammonia, etc.), water, etc. Standards may include at least one of myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignosulfonic acid, arginine, and glutamine. Exemplary internal standards include at least one of [2H3]-L,-carnitine-d3 hydrochloride, 4-fluoro-L-2-phenylglycine, L-phenylalanine, [2H5]-hippuric acid, [2H5]-kynuronic acid, and [2H5]-phenoxyacetic acid. These standards / internal standards may be packaged individually or as a mixture.

[0035] In this invention, the term "subject" or "examinee" should be understood as a mammal receiving or awaiting any form of medical care, diagnosis, treatment, monitoring, rehabilitation, or palliative care. In a preferred embodiment, the subject of the kit is a primate, more preferably a human; and even more preferably a Chinese person.

[0036] The present invention also relates to a system for diagnosing chronic obstructive pulmonary disease, the system comprising: Sample information processing module, diagnostic module, and information output module; The sample information module is used to receive information from the test subject. The test subject information includes at least the biomarker concentration information from the test subject sample. The biomarkers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine. The diagnostic module receives information input from the sample information processing module, determines the risk of chronic obstructive pulmonary disease, and outputs the determination result to the information output module.

[0037] In some implementations, the subject information may also include one or more of the following: the subject's photograph, age, gender, height, weight, dietary habits, medication history, mood, time from symptom onset to medical visit, family history of genetic diseases, smoking frequency, and type and frequency of exercise.

[0038] In some implementations, the subject information may also include other chronic obstructive pulmonary disease (COPD) diagnostic information inputs, such as the ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) after bronchodilator administration, the percentage of FEV1 to predicted value to classify disease severity, chest imaging (such as CT showing emphysema or airway wall thickening), arterial blood gas analysis (hypoxemia or hypercapnia), 6-minute walk test, and BODE index.

[0039] The present invention also relates to a computer-readable storage medium for storing computer instructions, programs, code sets or instruction sets, which, when run on a computer, cause the computer to perform the functions corresponding to the sample information processing module, the diagnostic module and the information output module in the system described above.

[0040] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0041] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0042] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, etc., or any suitable combination of the above media.

[0043] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and Swift, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including local area networks (LANs) or wide area networks (WANs), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0044] The present invention also relates to an electronic device, comprising: One or more processors; and a computer-readable storage medium for storing computer instructions, programs, code sets, or instruction sets that, when run on a computer, cause the one or more processors to perform the functions corresponding to the sample information processing module, the diagnostic module, and the information output module in the system described above.

[0045] In some embodiments, the electronic device may also include a transceiver. The processor and the transceiver are connected, such as via a bus. It should be noted that in practical applications, the transceiver is not limited to one unit, and the structure of the electronic device does not constitute a limitation on the embodiments of this application.

[0046] The processor can be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0047] A bus can include a pathway for transmitting information between the aforementioned components. The bus can be a PCI bus or an EISA bus, etc. Buses can be categorized as address buses, data buses, control buses, etc.

[0048] The embodiments of the present invention will be described in detail below with reference to examples. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. For experimental methods in the following embodiments where specific conditions are not specified, please refer to the guidelines given in this invention, or follow experimental manuals or conventional conditions in the art, or other experimental methods known in the art, or follow the conditions recommended by the manufacturer.

[0049] In the specific embodiments described below, the measurement parameters involving raw material components may have slight deviations within the weighing accuracy range unless otherwise specified. Temperature and time parameters are subject to acceptable deviations due to instrument testing accuracy or operational precision.

[0050] Example 1: Detection of serum amino acid and free fatty acid levels based on targeted metabolomics technology 1. Research Subjects The China Pulmonary Health (CPH) study included 810 patients with chronic obstructive pulmonary disease (COPD) and 241 age- and sex-matched healthy controls. COPD was diagnosed based on a forced expiratory volume in one second (FEV1 / FVC) ratio <0.70. Healthy controls were adults with no history of respiratory or cardiac disease and an FEV1 / FVC ratio ≥0.70 as measured by pulmonary function testing. The main exclusion criteria included: 1) a diagnosis of primary asthma; 2) significant abdominal pain, bloating, diarrhea, or respiratory infection within the past 4 weeks; and 3) a history of gastrointestinal disease, unstable or life-threatening arrhythmias, interstitial lung disease, bronchiectasis, or lung cancer. We used a questionnaire to obtain each participant's demographic characteristics, including age, personal medical history, biomass exposure (e.g., timber, straw, corn stalks), birth information, self-reported respiratory symptoms, and smoking status. All participants signed informed consent forms, and the research protocol was approved by the Ethics Committee of China-Japan Friendship Hospital.

[0051] 2. Serum targeted metabolomics analysis based on liquid chromatography-tandem mass spectrometry All serum samples were centrifuged and stored at -80°C. During the study, serum samples were retrieved, pretreated, and then subjected to targeted metabolomics analysis using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS / MS) to obtain raw metabolic fingerprints containing chromatographic and mass spectrometric information. The specific procedures are as follows: 2.1 Detection of amino acid metabolites Serum samples were thawed in an ice-water bath, vortexed for 30 seconds, and then 50 μL of sample was mixed with 200 μL of extraction buffer (pre-chilled at -40°C 1:1 acetonitrile-methanol solution containing an isotopically labeled internal standard mixture), vortexed again for 30 seconds, sonicated in an ice-water bath for 15 minutes, and then incubated at -40°C for 1 hour. Finally, the sample was centrifuged at 12000×g for 15 minutes at 4°C, and 100 μL of the supernatant was used for ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS / MS). Metabolite separation was performed using an Agilent 1290 Infinity II series UHPLC-MS / MS system equipped with an ACQUITY BEHAmide column. Mobile phase A was 1% formic acid aqueous solution, mobile phase B was 1% formic acid acetonitrile solution, column temperature was set to 35°C, autosampler temperature was set to 4°C, and injection volume was 1 mL. Amino acid metabolites were detected using an Agilent mass spectrometer equipped with an AJS electrospray ionization interface.

[0052] 2.2 Detection of fatty acid metabolites Serum samples were collected in 2 mL EP tubes and extracted with 430 μL of extraction buffer (isopropanol:n-hexane = 2:3) and 20 μL of internal standard mixture. The extraction mixture was sonicated in an ice-water bath for 10 min, then centrifuged at 12000×g for 15 min at 4°C. 400 μL of the supernatant was dried under a nitrogen stream and resuspended in 200 μL methanol and 100 μL dimethylamine. After incubation for 15 min, the sample was dried under a nitrogen stream, dissolved in 160 μL of n-hexane, and centrifuged at 12000×g for 5 min. The supernatant was used for gas chromatography-mass spectrometry (GC-MS). GC-MS was performed using an Agilent 7890B GC system coupled to an Agilent 5977B mass spectrometer with a DB-Fast FAME capillary column. 1 μL of analyte was injected in split mode. Helium was used as the carrier gas, the purge flow rate at the inlet was 3 mL / min, and the gas flow rate through the column was maintained at 46 psi in constant pressure mode.

[0053] 2.3 Identification of differentially expressed amino acids and free fatty acids The Mann-Whitney test was performed using R software to compare the amino acid and free fatty acid levels between patients with chronic obstructive pulmonary disease and healthy controls. Differential metabolites were defined using a p-value <0.05 as the screening criterion and visualized using a volcano plot.

[0054] 3. Experimental Results 3.1 Clinical baseline information of the subjects This study included 1051 male participants (810 COPD patients and 241 healthy controls). The average age of COPD patients was higher than that of healthy participants, while the average body mass index (BMI) of the COPD group was significantly lower than that of the control group. Furthermore, the pre- and post-diastolic pulmonary function indicators of COPD patients were worse than those of the healthy control group. Detailed clinical information and demographic characteristics of the participants are shown in Table 1.

[0055] Table 1. Clinical characteristics of the study population

[0056] PM: particulate matter; VC: vital capacity; N / A: not applicable;GOLD: The Global Initiative for Chronic Obstructive Lung Disease. P valuescomparing groups were determined by Student's t-test or Mann-Whitney test for continuous data and the chi-squared test for categorical variables. 3.2 Differential Metabolite Content and Differential Analysis Compared with healthy controls, patients with chronic obstructive pulmonary disease (COPD) showed differential upregulation of 18 metabolites, including 7 amino acids (glutamine, glycine, asparagine, threonine, arginine, phenylalanine, and aspartic acid) and 11 free fatty acids (eicosapentaenoic acid, palmitoleic acid, docosahexaenoic acid, nervonic acid, myristic acid, linolenic acid, oleic acid, docosapentaenoic acid, arachidonic acid, docosahexaenoic acid, and eicosaenoic acid); and differential downregulation of 7 metabolites, including 2 amino acids (glutamate and serine) and 5 free fatty acids (arachidic acid, lignotaric acid, linoleic acid, stearic acid, and behenic acid). Figure 1 ).

[0057] Meanwhile, we found significant differences in the levels of some metabolites among COPD groups with different severities. The levels of four metabolites (nervonic acid, eicosapentaenoic acid, arachidonic acid, and docosahexaenoic acid) increased with increasing COPD severity. Conversely, the levels of three metabolites (glutamate, lignosulfonate, and linoleic acid) decreased with increasing COPD severity.

[0058] Example 2: Constructing a COPD diagnostic model and screening biomarkers using machine learning algorithms To verify whether the 25 differentially expressed amino acids or fatty acids identified could serve as reliable biomarkers for the diagnosis of COPD, we first constructed a random forest model based on serum metabolite profiles to identify informative metabolite features associated with COPD pathogenesis. Subsequently, we used a LASSO regression model to further screen for differentially expressed metabolites between the COPD group and the control group. After cross-validation using the random forest model and the LASSO algorithm, 12 metabolites with significant diagnostic value for COPD were finally identified, including myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine. Figure 2 (A)

[0059] To evaluate the diagnostic value of these 12 candidate biomarkers, 810 COPD patients and 241 healthy controls were randomly assigned to a training set (70%) and a test set (30%). ROC curve analysis showed that all 12 metabolites demonstrated good diagnostic efficacy in distinguishing COPD patients from healthy controls. The area under the ROC curve (AUC) for the training set was 0.825 (95% CI: 0.791–0.859), and the AUC for the test set was 0.813 (95% CI: 0.757–0.868). Figure 2 (B)

[0060] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims, and the specification and drawings can be used to interpret the content of the claims.

Claims

1. Application of quantitative detection reagents for biomarkers in the preparation of reagent kits for diagnosing chronic obstructive pulmonary disease; The markers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine.

2. The application according to claim 1, wherein the quantitative detection reagent is used to perform one or more of the following methods: Liquid chromatography-tandem mass spectrometry, ultra-high performance liquid chromatography-tandem mass spectrometry, liquid chromatography-high resolution mass spectrometry, nuclear magnetic resonance spectroscopy.

3. The application according to claim 1, wherein the test samples of the kit are selected from: blood, serum, plasma, cell or tissue extracts, cerebrospinal fluid and urine.

4. The application according to claim 1, wherein the kit further comprises at least one of a reagent for extracting biomarkers from a sample, a standard, and an internal standard.

5. The application according to any one of claims 1-4, wherein the subject of the kit is a mammal.

6. The application according to claim 5, wherein the subject of the kit is a primate.

7. The application according to claim 6, wherein the subject of the kit is a human.

8. A system for diagnosing chronic obstructive pulmonary disease, the system comprising: Sample information processing module, diagnostic module, and information output module; The sample information module is used to receive information from the test subject. The test subject information includes at least the biomarker concentration information from the test subject sample. The biomarkers are selected from: myristic acid, oleic acid, stearic acid, eicosapentaenoic acid, arachidic acid, docosahexaenoic acid, docosapentaenoic acid, docosatraenoic acid, nervonic acid, lignotaric acid, arginine, and glutamine. The diagnostic module receives information input from the sample information processing module, determines the risk of chronic obstructive pulmonary disease, and outputs the determination result to the information output module.

9. A computer-readable storage medium for storing computer instructions, programs, code sets, or instruction sets, which, when run on a computer, cause the computer to perform the functions corresponding to the sample information processing module, the diagnostic module, and the information output module in the system of claim 8.

10. An electronic device, comprising: One or more processors; And a computer-readable storage medium for storing computer instructions, programs, code sets or instruction sets, which, when run on a computer, enable the one or more processors to perform the functions corresponding to the sample information processing module, the diagnostic module and the information output module in the system as described in claim 8.

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