Biomarkers, kits and applications thereof for diagnosing abnormal thyroid function

Abstract

The present invention provides a biomarker, a kit and its application for diagnosing abnormal thyroid function. The present invention obtains complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate for diagnosing hyperthyroidism through differential screening, integrated feature selection algorithm (EFS), ROC analysis and other bioinformatics analysis methods, and apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, L-threonine for diagnosing hypothyroidism. Based on the biomarkers of the present invention, corresponding kits and diagnostic equipment can be constructed for accurately diagnosing abnormal thyroid function.

Description

Technical Field

[0001] The present invention belongs to the field of biological detection technology, and specifically relates to a biomarker, a kit and applications thereof for diagnosing patients with abnormal thyroid function. Background Art

[0002] Thyroid hormones are crucial for human growth and development, metabolism, and the activities of several organs. Thyroid disease is a global health issue that severely impacts normal human life. Thyroid disease is generally categorized as thyroid dysfunction and thyroid nodules. Thyroid dysfunction is a common condition, but it carries potentially serious health consequences. Hyperthyroidism and hypothyroidism are typically primary thyroid diseases, generally caused by pathological processes within the thyroid gland, but can also be caused by peripheral factors.

[0003] Hyperthyroidism is characterized by increased thyroid hormone synthesis and secretion. In iodine-sufficient regions, the prevalence of hyperthyroidism is 0.2% to 1.3%. Studies report an incidence of approximately 100 to 200 cases per 100,000 population per year, with a prevalence of 2.7% in women and 0.23% in men. Hypothyroidism, a common form of thyroid hormone deficiency, is easily diagnosed and treated, but untreated, severe cases can be fatal. Definitions of hypothyroidism are primarily biochemical, given the wide variability in clinical presentation and its specificity compared to general deficiency conditions. Overt or clinical primary hypothyroidism is defined as a thyroid-stimulating hormone concentration above the reference range and free thyroxine below the reference range. In iodine-sufficient regions, in the absence of age-specific thyroid-stimulating hormone reference ranges, an aging population may lead to a higher prevalence of hypothyroidism, with the incidence in women being approximately 10 times that of men.

[0004] Currently, the diagnosis of hyperthyroidism begins with measurement of serum thyroid-stimulating hormone (TSH) levels, primarily because TSH has the highest sensitivity and specificity for diagnosing thyroid disease. If TSH levels are low, further measurement of serum free T4 or T3 levels is necessary to differentiate between subclinical and overt hyperthyroidism. However, treatment for hyperthyroidism varies significantly worldwide, with options generally including antithyroid drugs (ATDs), radioactive iodine ablation, and surgery. Furthermore, the reference range for hyperthyroidism testing is influenced by numerous factors, including whether the region is iodine-sufficient, as well as age, gender, and a history of other medical conditions, which can interfere with clinical diagnosis. Currently, the diagnosis of hypothyroidism is primarily based on its definition. For example, primary hypothyroidism is defined as a TSH concentration above the reference range and free thyroxine below the reference range. This definition also varies depending on the type of monitoring and the study population. TSH levels fluctuate significantly during the day, with higher concentrations at night. In severe cases, TSH secretion is irregular and exhibits seasonal variations. Despite the high prevalence, ease of diagnosis, and low cost of treatment for hypothyroidism, there is no consensus on thyroid-stimulating hormone screening for specific subgroups of the general population. Currently, the preferred treatment for hypothyroidism is levothyroxine monotherapy, and the dosage varies depending on the hypothyroid population.

[0005] How to find biomarkers that are easy to detect and less susceptible to interference to prepare kits and diagnostic devices for predicting and diagnosing abnormal thyroid function is a technical problem that urgently needs to be solved. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides a biomarker, a kit and applications thereof for diagnosing abnormal thyroid function.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a biomarker for diagnosing abnormal thyroid function, wherein the biomarker is a hyperthyroidism marker and / or a hypothyroidism marker present in human plasma;

[0009] The hyperthyroidism marker is one or more combinations of complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate;

[0010] The hypothyroidism marker is one or more combinations of apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine.

[0011] As a preferred embodiment of the first aspect, the hyperthyroidism marker is a combination of six markers including complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate.

[0012] As a preferred embodiment of the first aspect, the hypothyroidism marker is a combination of six markers including apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine.

[0013] In a second aspect, the present invention provides a use of a reagent for detecting a biomarker as described in any one of the schemes in the first aspect in preparing a diagnostic kit or detection device for abnormal thyroid function.

[0014] In a third aspect, the present invention provides a kit for diagnosing abnormal thyroid function, comprising a reagent for detecting the biomarker as described in any one of the schemes in the first aspect.

[0015] As a preference in the third aspect above, the kit is preferably an ELISA kit.

[0016] In a fourth aspect, the present invention provides a use of a biomarker as described in any scheme of the first aspect in the diagnosis of abnormal thyroid function for non-disease diagnosis or treatment purposes.

[0017] In a fifth aspect, the present invention provides a diagnostic device for diagnosing abnormal thyroid function, comprising:

[0018] a data acquisition device for acquiring test data of a diagnostic subject, wherein the test data is the level of each biomarker as described in any one of the schemes of the first aspect, obtained from human plasma of the diagnostic subject, wherein if the marker is a protein, the protein expression level is used as the level value; if the marker is a metabolite, the metabolite content in the plasma is used as the level value;

[0019] The data processing equipment is used to calculate the index value of each marker based on the test data of the diagnosis object, wherein the index value of each marker is the ratio between the level value of the marker in the human plasma of the diagnosis object and the level value in the plasma of a normal human without abnormal thyroid function, and then determine whether the calculated index value of each marker is within the risk range of the corresponding marker. If the index value of one or more markers among all the markers is within the risk range of hyperthyroidism or hypothyroidism, a corresponding diagnostic result prompt of abnormal thyroid function is given.

[0020] As a preference for the fifth aspect, the risk range of each marker may adopt one or more of the following preferred ranges: preferably, the risk range of the complement C4-A indicating hyperthyroidism is an index value less than 0.95; preferably, the risk range of the C3 / C5 convertase indicating hyperthyroidism is an index value greater than 1.04; preferably, the risk range of the glutathione peroxidase 3 indicating hyperthyroidism is an index value less than 0.98; preferably, the risk range of the L-arginine indicating hyperthyroidism is an index value greater than 1.04; preferably, the risk range of the L-proline indicating hyperthyroidism is an index value greater than 1.01; preferably, the risk range of the L-glutamate indicating thyroid function is less than 1.02. The risk range of hyperthyroidism is an index value greater than 1.02; preferably, the risk range of hypothyroidism corresponding to the apolipoprotein L1 is an index value greater than 1.25; preferably, the risk range of hypothyroidism corresponding to the α-trypsin inhibitor heavy chain H4 is an index value greater than 1.31; preferably, the risk range of hypothyroidism corresponding to the kininogen-1 is an index value greater than 1.35; preferably, the risk range of hypothyroidism corresponding to the cortisone is an index value greater than 1.05; preferably, the risk range of hypothyroidism corresponding to the cortisol is an index value greater than 1.06; preferably, the risk range of hypothyroidism corresponding to the L-threonine is an index value greater than 1.07.

[0021] As a preferred embodiment of the fifth aspect, in the data processing device, a corresponding diagnosis result of abnormal thyroid function is given only when the index values of all markers in the hyperthyroidism markers are within their respective risk ranges or when the index values of all markers in the hypothyroidism markers are within their respective risk ranges.

[0022] As a preference of the fifth aspect above, the data acquisition device is an input device for inputting data or a communication device for reading data from an external data storage device through an interface.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention provides a novel molecular marker that can be used to identify abnormal thyroid function, and can be used to construct a detection kit and diagnostic equipment for early detection, diagnosis and prediction of abnormal thyroid function.

[0025] The biomarkers for diagnosing hyperthyroidism provided by the present invention include any combination of complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate. The risk of hyperthyroidism is predicted by detecting the content of complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate in the blood and combining the ratio, which is helpful for diagnosing the presence of hyperthyroidism. The biomarkers for diagnosing hypothyroidism include any combination of apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine. The risk of hypothyroidism is predicted by detecting the content of apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine in the blood and combining the ratio, which is helpful for diagnosing the presence of hypothyroidism. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 PCA analysis of proteomic and metabolomic results.

[0027] Figure 2 These are the ROC analysis results of six biomarkers of hyperthyroidism.

[0028] Figure 3 The results of ROC analysis of six biomarkers of hypothyroidism.

[0029] Figure 4 This is the ROC of the combined model of multiple hyperthyroidism markers.

[0030] Figure 5 ROC of the combined model of multiple markers of hypothyroidism.

[0031] Figure 6 Box plot results of analysis and validation of six biomarkers of hyperthyroidism (the three groups from left to right in each figure are THE, THO, and N).

[0032] Figure 7 Box plot results of analysis and validation of six biomarkers of hypothyroidism (from left to right: THE, THO, N). DETAILED DESCRIPTION

[0033] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. The technical features in the various embodiments of the present invention can be combined accordingly without conflicting with each other.

[0034] Hyperthyroidism and hypothyroidism are two typical thyroid dysfunctions. In the present invention, corresponding biomarkers are provided for hyperthyroidism and hypothyroidism, respectively, which are called hyperthyroidism markers and hypothyroidism markers, so as to facilitate the diagnosis of thyroid dysfunction based on these markers.

[0035] Among them, hyperthyroidism markers are one or more combinations of complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline, and L-glutamate. Of these six markers, the first three, complement C4-A, C3 / C5 convertase, and glutathione peroxidase 3, are proteins, while the last three, L-arginine, L-proline, and L-glutamate, are metabolites.

[0036] In addition, markers for hypothyroidism are one or more combinations of apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, and L-threonine. Of these six markers, the first three—apolipoprotein L1, α-trypsin inhibitor heavy chain H4, and kininogen-1—are proteins, while the last three—cortisone, cortisol, and L-threonine—are metabolites.

[0037] It should be noted that complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, apolipoprotein L1, α-trypsin inhibitor heavy chain H4, and kininogen-1 in the present invention are all known proteins in the human body, and their specific sequences are all known. Their protein IDs in the public protein database Uniprot are shown in Table 1. Specifically:

[0038] The English name of complement C4-A is Complement C4-A, the accession number in the protein database uniprot is P0C0L4, and the sequence is shown in SEQ ID No: 1.

[0039] C3 / C5 convertase is a convertase that can function as both a C3 convertase and a C5 convertase. Its English name is C3 / C5 convertase, its accession number in the protein database Uniprot is B4E1Z4, and its sequence is shown in SEQ ID No: 2.

[0040] The English name of glutathione peroxidase 3 is Glutathione peroxidase 3, the accession number in the protein database uniprot is P22352, and the sequence is as follows:

[0041] MARLLQASCLLSLLLAGFVSQSRGQEKSKMDCHGGISGTIYEYGALTIDGEEYIPFKQYAGKYVLFVNVASYUGLTGQYIELNALQEELAPFGLVILGFPCNQFGKQEPGENS EILPTLKYVRPGGGFVPNFQLFEKGDVNGEKEQKFYTFLKNSCPPTSELLGTSDRLFWEPMKVHDIRWNFEKFLVGPDGIPIMRWHHRTTVSNVKMDILSYMRRQAALGVKRK.

[0042] The English name of apolipoprotein L1 is Apolipoprotein L1, the accession number in the protein database uniprot is O14791, and the sequence is shown in SEQ ID No: 3.

[0043] The English name of α-trypsin inhibitor heavy chain H4 is Inter-alpha-trypsin inhibitor heavy chain H4, the accession number in the protein database uniprot is Q14624, and the sequence is shown in SEQ ID No: 4.

[0044] The English name of kininogen-1 is Kininogen-1, the accession number in the protein database uniprot is P01042, and the sequence is shown in SEQ ID No: 5.

[0045] Table 1 Protein IDs and Chinese and English names

[0046]

[0047] It should be noted that among the above-mentioned hyperthyroidism markers, any one of the six markers can be used alone as a basis for diagnosing hyperthyroidism. However, since a single marker may be misdiagnosed, it is preferred to use a combination of multiple markers from the six markers as biomarkers to diagnose hyperthyroidism. In a preferred embodiment, the hyperthyroidism markers used to diagnose hyperthyroidism are a combination of six markers: complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline, and L-glutamate.

[0048] It should also be noted that any one of the six hypothyroidism markers mentioned above can be used alone as a basis for diagnosing hypothyroidism. However, since a single marker may lead to misdiagnosis, it is preferred to use a combination of multiple of the six markers as biomarkers to diagnose hypothyroidism. In a preferred embodiment, the hypothyroidism markers used to diagnose hypothyroidism are a combination of six markers: apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, and L-threonine.

[0049] In another embodiment of the present invention, there is provided a use of a reagent for detecting the above-mentioned biomarker (a single marker or a combination of multiple markers) in preparing a diagnostic kit or detection device for abnormal thyroid function.

[0050] It should be noted that since the above-mentioned biomarkers may be a single marker or a combination of multiple markers, the corresponding diagnostic kit or detection device may also be a diagnostic kit or detection device for a single marker, or a combination of diagnostic kits or detection devices for multiple markers.

[0051] It should be noted that the reagents contained in the specific kit of the present invention can be set according to the detection method of each marker. These 12 markers are all known compounds, and corresponding detection methods already exist in the prior art. Therefore, the reagents for detecting the above-mentioned biomarkers (single marker or a combination of multiple markers) can be selected with reference to the prior art, and the corresponding diagnostic kit or detection device can be constructed according to the prior art.

[0052] Similarly, in another embodiment of the present invention, a kit for diagnosing thyroid dysfunction is provided, comprising reagents for detecting the above-mentioned biomarkers (a single marker or a combination of multiple markers). Taking into account detection efficiency and convenience, the kit is preferably an ELISA kit.

[0053] It should be noted that, generally speaking, the same diagnostic subject may only suffer from one of hyperthyroidism and hypothyroidism at a given time. Therefore, the above-mentioned diagnostic kit or detection device in the present invention can be used to detect only six markers of one of hyperthyroidism and hypothyroidism.

[0054] In another embodiment of the present invention, a use of the aforementioned biomarker (a single marker or a combination of multiple markers) in the diagnosis of thyroid dysfunction for non-disease diagnosis or treatment purposes is provided. The non-disease diagnosis or treatment of thyroid dysfunction can be for scientific research, non-medical commercial testing, or other purposes.

[0055] In another embodiment of the present invention, a diagnostic device for diagnosing abnormal thyroid function is provided, comprising:

[0056] A data acquisition device for acquiring test data of a diagnostic subject, wherein the test data is the level value of each of the above-mentioned biomarkers (a single marker or a combination of multiple markers) detected in the human plasma of the diagnostic subject, wherein if the marker is a protein, the protein expression level is used as the level value; if the marker is a metabolite, the metabolite content in the plasma is used as the level value;

[0057] The data processing equipment is used to calculate the index value of each marker based on the test data of the diagnosis object, wherein the index value of each marker is the ratio between the level value of the marker in the human plasma of the diagnosis object and the level value in the plasma of a normal human without abnormal thyroid function, and then determine whether the calculated index value of each marker is within the risk range of the corresponding marker. If the index value of one or more markers among all the markers is within the risk range of hyperthyroidism or hypothyroidism, a corresponding diagnostic result prompt of abnormal thyroid function is given.

[0058] It should be noted that the index value of the marker in the present invention is that since markers are divided into two categories: proteins and metabolites, if the marker is a protein, the expression level of the protein needs to be used as its level value, and the corresponding index value is the abundance value ratio AR. If the marker is a metabolite, the content of the metabolite needs to be used as its level value, and the corresponding index value is the density value ratio IR.

[0059] It should be noted that the risk range for each marker in the present invention needs to be obtained through statistical analysis of the marker index values of different populations in a large amount of experimental data, so that the risk range can distinguish between people with abnormal thyroid function and normal people without abnormal thyroid function. In the present invention, through statistical analysis of a large amount of experimental data, the risk ranges of each of the 12 markers can be obtained as follows:

[0060] The risk range of the complement C4-A indicating hyperthyroidism is an index value less than 0.95; the risk range of the C3 / C5 convertase indicating hyperthyroidism is an index value greater than 1.04; the risk range of the glutathione peroxidase 3 indicating hyperthyroidism is an index value less than 0.98; the risk range of the L-arginine indicating hyperthyroidism is an index value greater than 1.04; the risk range of the L-proline indicating hyperthyroidism is an index value greater than 1.01; the risk range of the L-glutamate indicating hyperthyroidism is an index value greater than 1.0 2; the risk range of hypothyroidism corresponding to the apolipoprotein L1 is an index value greater than 1.25; the risk range of hypothyroidism corresponding to the α-trypsin inhibitor heavy chain H4 is an index value greater than 1.31; the risk range of hypothyroidism corresponding to the kininogen-1 is an index value greater than 1.35; the risk range of hypothyroidism corresponding to the cortisone is an index value greater than 1.05; the risk range of hypothyroidism corresponding to the cortisol is an index value greater than 1.06; the risk range of hypothyroidism corresponding to the L-threonine is an index value greater than 1.07.

[0061] Of course, the risk ranges of the 12 markers are merely recommended ranges in the present invention, and those skilled in the art may select some of them for use according to actual circumstances, or use them after further optimization and adjustment.

[0062] In addition, when providing diagnostic results for thyroid dysfunction, it is necessary to distinguish between hyperthyroidism and hypothyroidism. Furthermore, since both thyroid abnormalities can have up to six markers, it is not necessary to include all of them in actual use; one or more of the six can be selected. However, for either hyperthyroidism or hypothyroidism, if multiple markers are included in the six markers for risk range determination, theoretically, any marker within its risk range can be considered to be at risk for thyroid dysfunction. However, in actual application, in order to reduce the false positive rate, the risk of thyroid dysfunction should only be indicated if the index values of multiple markers among all included markers are within the risk range for hyperthyroidism or hypothyroidism.

[0063] As a preferred embodiment of the present invention, the data processing device may also be configured to only present a corresponding thyroid dysfunction diagnosis result when the index values of all markers in the hyperthyroidism marker set are within their respective risk ranges, or when the index values of all markers in the hypothyroidism marker set are within their respective risk ranges. In other words, if any of the markers included in the risk range assessment is outside its corresponding risk range, a thyroid dysfunction diagnosis result may not be presented.

[0064] Of course, in other embodiments, corresponding proportional risk levels can also be set according to the number of markers within the risk range. Even if there are markers that are not within the risk range, different risk levels can be given accordingly to facilitate the assessment of their risk levels and provide a reference for clinical practice. For example, for hyperthyroidism markers, there are a total of 6 markers included in the risk range judgment, so a total of 6 risk levels are set. If N of the markers are within their risk range, then the Nth risk level of hyperthyroidism is indicated. The larger N is, the greater the risk of hyperthyroidism. Similarly, for hypothyroidism markers, there are a total of 6 markers included in the risk range judgment, so a total of 6 risk levels are set. If N of the markers are within their risk range, then the Nth risk level of hypothyroidism is indicated. The larger N is, the greater the risk of hypothyroidism.

[0065] It should be noted that the data acquisition device is an input device for inputting data or a communication device for reading data from an external data storage device via an interface. When an input device is used, data detected by the external device can be input into the diagnostic device, thereby providing a diagnostic result. When a communication device is used, the corresponding external data storage device can be a data storage device on a device that automatically measures the aforementioned biomarkers. The diagnostic device of the present invention can be integrated into the automated biomarker measurement device to directly output the diagnostic result after the measurement is completed, thus achieving an integrated detection and diagnosis function.

[0066] The present invention further illustrates the selection principle, process and effect of the above-mentioned biomarkers through a specific example below, so that those skilled in the art can understand the essence of the present invention.

[0067] Example 1

[0068] Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art. The reagents used in the present invention are all of analytical grade or higher specifications. The chromatographic column used is model: ACQUITY UPLC BEHC18, manufacturer: Waters; the liquid chromatograph is model: UltiMate 3000 UHPLC, manufacturer: Thermo.

[0069] Plasma samples were collected from 40 participants. These 40 participants included 15 patients with hyperthyroidism, 10 patients with hypothyroidism, and 15 healthy controls. All participants were female. Plasma samples were collected from a peripheral vein in all participants after an overnight fast. EDTA blood samples were centrifuged for 10 minutes within 4 hours of collection, and the separated supernatant was extracted and stored at -80°C until further analysis.

[0070] The reagents used in the present invention include formic acid, methanol, ammonium formate, acetonitrile, dithiothreitol (DTT), and iodoacetamide (IAM).

[0071] 1. For protein markers, add SDS-free L3 to 100 μL of blood sample to make up the volume to 1 mL; then perform reductive alkylation reaction. The specific steps are as follows: protein extraction, protein enrichment, enrichment quality control, proteolysis

[0072] The dried peptide samples were reconstituted with mobile phase A (2% ACN, 0.1% FA), centrifuged at 20,000 g for 10 min, and the supernatant was injected and separated using a Thermo UltiMate 3000 UHPLC. The sample was first enriched and desalted on a trap column, then connected in series to a self-assembled C18 column (150 μm inner diameter, 1.8 μm column particle size, approximately 35 cm column length). Separation was performed at a flow rate of 500 nL / min using the following effective gradient: 0-5 min, 5% mobile phase B (98% acetonitrile, 0.1% formic acid); 5-120 min, linear increase in mobile phase B from 5% to 25%; 120-160 min, mobile phase B from 25% to 35%; 160-170 min, mobile phase B from 35% to 80%; 170-175 min, 80% mobile phase B; 175-180 min, 5% mobile phase B. The nanoliquid separation column was directly connected to a mass spectrometer and detected according to the following parameters:

[0073] 1. DDA library construction and detection

[0074] The peptides separated by liquid phase were ionized by nano ESI source and then entered into tandem mass spectrometer Q-Exactive HFX (Thermo Fisher Scientific, San Jose, CA) for DDA (Data Dependent Acquisition) mode detection.

[0075] 2.DIA mass spectrometry detection

[0076] The peptides separated by liquid phase were ionized by nano ESI source and then entered into tandem mass spectrometer Q Exactive HFX (Thermo Fisher Scientific, San Jose, CA) for DIA (Data Independent Acquisition) mode detection.

[0077] 2. For metabolite markers, the first step is metabolite extraction: After slowly thawing the sample at 4°C, take 100μL and place it in a 96-well plate. Add 300μL of extraction solution (methanol:acetonitrile = 2:1, v:v, pre-cooled at -20°C) + 10μL of internal standard 1 + 10μL of internal standard 2, vortex mix for 1 minute, let it stand at -20°C for 2 hours, and centrifuge at 4°C, 4000rcf for 20 minutes. After centrifugation, take 300μL of supernatant, place it in a freeze vacuum concentrator to dry, add 150μL of reconstitution solution (methanol: water = 1:1, v:v) for reconstitution, and vortex for 1 minute, 4°C, 4000r·min. -1 Centrifuge for 30 minutes and transfer the supernatant to a vial. 10 μL of the supernatant from each sample was mixed to form a QC sample for evaluating the repeatability and stability of the LC-MS analysis.

[0078] This was followed by LC-MS / MS analysis. In this experiment, Waters 2D UPLC (Waters, USA) was connected to a QExactive high-resolution mass spectrometer (Thermo Fisher Scientific, USA) to separate and detect metabolites.

[0079] 3. Bioinformatics Analysis to Find Biomarkers

[0080] Biomarkers are primarily identified through bioinformatics analysis methods such as differential screening, integrated feature selection (EFS), and receiver operating characteristic (ROC) analysis. The primary criteria for differential screening are fold change >= 1.2 and P value < 0.05. EFS rank and t-tests are then performed on differentially expressed proteins and metabolites. The results are then integrated to identify potential biomarkers, which are then analyzed using ROC analysis to determine the final biomarker.

[0081] like Figure 1Figure 2 shows the PCA results for the proteome (top) and metabolome (bottom) of this example. N represents the healthy control group, THE represents the hyperthyroidism group, and THO represents the hypothyroidism group. The PCA analysis chart reflects the overall distribution of samples in each group, from which 12 markers were screened, including 6 markers for hyperthyroidism and 6 markers for hypothyroidism. The six markers for hyperthyroidism are complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate, among which complement C4-A, C3 / C5 convertase and glutathione peroxidase 3 are proteins, and L-arginine, L-proline and L-glutamate are metabolites; while the six markers for hypothyroidism are apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine, among which apolipoprotein L1, α-trypsin inhibitor heavy chain H4 and kininogen-1 are proteins, and cortisone, cortisol and L-threonine are metabolites.

[0082] like Figure 2 As shown in FIG, the ROC curve analysis of the six hyperthyroidism markers obtained by bioinformatics analysis in this embodiment, that is, the receiver operating characteristic curve analysis, is shown in FIG. Figure 3 As shown, this is the ROC curve analysis of six markers of hypothyroidism obtained by bioinformatics analysis in this embodiment. In the ROC curve, the AUC value is the area covered by the ROC curve. The larger the value, the higher the accuracy of the model prediction. It can be seen that the 12 markers screened out in this embodiment all have a high accuracy rate for diagnosing abnormal thyroid function. Any one of the complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate markers can be used to diagnose whether hyperthyroidism exists, and any one of the markers of apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine can be used to diagnose whether hypothyroidism exists.

[0083] Fourth, LASSO and logistic regression were used to combine metabolites and proteins into a multi-omics model to detect abnormal thyroid function.

[0084] First, the LASSO regression algorithm was used to select the minimum feature set to classify the three sample groups. Fast missing value imputation was achieved by chained random forests in each individual dataset using the “NAguide” R package. After fast imputation by chained random forests on each dataset, they were individually scaled to Z-score and connected to a regularized (L1 norm) machine learning method. Subsequently, conventional machine learning was performed using the “caret” and “glmnet” R packages to train, test, and evaluate the LASSO logistic classification model. Using the LASSO parameterization (alpha = 1), the model was adjusted on a search grid of lambda values: 0.001 to 0.3, with a step size of 0.01. The model was optimized for the highest area under the ROC curve (AUC). For multi-class comparisons, the model was calculated as the average AUC for all applicable comparisons of one class against all other classes. In this example, feature importance and overall LASSO proteomics-metabolomics signature were obtained by using “varImp()” in the caret and keeping the importance of all features non-zero. At the same time, logistic regression analysis was performed using the Sklearn package in Python v3 to generate the optimal prediction model, and LOOCV (leave-one-out cross validation) was used to improve the robustness of the model.

[0085] For the hyperthyroidism group, the six candidate protein biomarkers and six candidate metabolic biomarkers of hyperthyroidism obtained previously were combined, and the Sklearn package in Python was used to build a logistic regression model. The LOOCV algorithm was used to enhance the robustness of the model, and ROC curve analysis and evaluation were performed. Figure 4 The results of the receiver operating characteristic (ROC) analysis of a six-marker combination model for hyperthyroidism were presented, with an AUC value of 0.991. Compared with the aforementioned single protein markers or single metabolite markers, the combined protein and metabolite biomarker demonstrated superior predictive accuracy.

[0086] For the hypothyroidism group, the six candidate protein biomarkers and six candidate metabolic biomarkers of hypothyroidism obtained previously were combined, and the Sklearn package in Python was used to construct a logistic regression model. The LOOCV algorithm was used to enhance the robustness of the model, and ROC curve analysis and evaluation were performed. Figure 5 The ROC results of a combined model of six hypothyroidism markers were presented, showing an AUC value of 0.993. Compared with the aforementioned single protein markers or single metabolite markers, the combined protein and metabolite biomarker had better predictive accuracy.

[0087] 5. Verification Experiment

[0088] To verify the effectiveness of the six markers described above in diagnosing thyroid dysfunction, validation experiments were designed. The Signalway Antibody ELISA kits were used for Human Complement C4-A, C3 / C5 convertase, Glutathionperoxidase 3, L-Arginine, L-Proline, and L-Glutamic acid. The specific procedures for performing validation experiments using the ELISA kits for each marker are as follows:

[0089] 1. Reagent preparation:

[0090] Washing buffer: The dilution ratio of the buffer to water is 1:25, and 30 mL of buffer is mixed with 720 mL of water to make the washing buffer.

[0091] Standards: Add 2 mL of standard diluent to reconstitute, then dilute the standard into 6 portions (50.0, 25.0, 12.5, 6.25, 3.12, 1.56, 0.78 ng / mL) by half-dilution method, plus a blank control.

[0092] Detection reagents: Dilute detection reagents A and B with diluents A and B at a ratio of 1:100, respectively.

[0093] 2. Specific experimental process:

[0094] 2.1) Take 40 μL of plasma from each sample and 40 μL of each standard, repeat once, place all into a 96-well plate, cover with sealing film, and incubate at 37°C for 2 hours.

[0095] 2.3) Remove the liquid from each well, add 100 μL of detection reagent A to each well, cover with sealing film and incubate at 37°C for 1 hour.

[0096] 2.3) Remove the liquid in each well and wash each well three times with washing buffer, each time with 300 μL of washing buffer per well.

[0097] 2.4) Add 100 μL of detection reagent B to each well, cover with sealing film, and incubate at 37°C for 1 hour.

[0098] 2.5) Remove the liquid in the wells and wash five times with wash buffer.

[0099] 2.6) Add 90 μL of substrate to each well, cover with sealing film, and incubate at 37°C for 10-20 minutes.

[0100] 2.7) Add 50 μL of stop solution to each well. Notice that the color in each well changes significantly.

[0101] 2.8) Set the wavelength to 450 nm and measure the OD value of each well using a microplate reader. Calculate the marker level based on the OD value.

[0102] Figure 6 The analysis and validation results of hyperthyroidism markers are presented. THE represents the hyperthyroidism group, THO represents the hypothyroidism group, and N represents the normal control group. Because these markers are hyperthyroidism markers, their expression in the hyperthyroidism group is different from that in the hypothyroidism group and the normal control group. Figure 6 The corresponding complement markers C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline, and L-glutamate are shown in the figure. Taking complement C4-A as an example, its expression in the hyperthyroidism group was significantly lower than that in the hypothyroidism group and the normal group. Combined with its ROC result (greater than 0.7), it is considered a potential biomarker for hyperthyroidism. Boxplots of other markers also show that their expression in the hyperthyroidism group is different from that in the other two groups, and the ROC results are all good. This demonstrates that any one of the complement markers C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline, and L-glutamate can be used to diagnose the presence of hyperthyroidism.

[0103] Figure 7 The analysis and validation results of hypothyroidism markers are presented. THE represents the hyperthyroidism group, THO represents the hypothyroidism group, and N represents the normal control group. Because these markers are hypothyroidism markers, their expression in the hypothyroidism group is different from that in the hyperthyroidism group and the normal control group. Figure 7 The corresponding markers for apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, and L-threonine are shown in the figure. Taking apolipoprotein L1 as an example, its expression in the hypothyroidism group was significantly higher than in the hyperthyroidism group and the normal group. Combined with the receiver operating characteristic (ROC) results, this suggests that it could serve as a potential biomarker for hypothyroidism. Boxplots of other markers also show that their expression in the hypothyroidism group is different from that in the other two groups, and the ROC results all perform well. This demonstrates that any one of the following markers—apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, and L-threonine—can be used to diagnose hypothyroidism.

[0104] When actually used to diagnose thyroid dysfunction, the plasma sample of the diagnosed subject can be tested for complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate to identify hyperthyroidism, or the plasma sample can be tested for apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol, L-threonine to identify hypothyroidism. Figure 6 and Figure 7 Based on the statistical analysis of the average level of each marker in each group of samples, the judgment criteria for each of the 12 markers for diagnosis can be obtained, as follows:

[0105] The expression levels of complement C4A vary in different groups. The expression in hyperthyroidism patients is significantly lower than that in hypothyroidism and normal groups. The expression level of complement C4A in the plasma of the diagnosed subjects is recorded as Abundance, and the expression level of complement C4A in the plasma of normal people is recorded as N. AR = Abundance / N. Based on the abundance value ratio AR, if AR < 0.95, it is diagnosed as hyperthyroidism.

[0106] The expression levels of C3 / C5 convertase vary in different groups. Its expression in hyperthyroidism patients is significantly higher than that in hypothyroidism and normal groups. The expression level of C3 / C5 convertase in the plasma of the diagnosed subjects is recorded as Abundance, and the expression level of C3 / C5 convertase in the plasma of normal subjects is recorded as N. AR = Abundance / N. Based on the abundance value ratio AR, if AR>1.04, it is diagnosed as hyperthyroidism.

[0107] The expression levels of glutathione peroxidase 3 were different in different groups. The expression in hyperthyroidism patients was significantly higher than that in hypothyroidism and normal groups. The expression level of glutathione peroxidase 3 in the plasma of the diagnosed subjects was recorded as Abundance, and the expression level of glutathione peroxidase 3 in the plasma of normal subjects was recorded as N. AR = Abundance / N. According to the abundance value ratio AR, if AR < 0.98, it was diagnosed as hyperthyroidism.

[0108] The expression levels of L-arginine are different in different groups. The expression in hyperthyroidism patients is significantly higher than that in hypothyroidism and normal groups. The L-arginine content in the plasma of the diagnosed subjects is recorded as Intensity, and the L-arginine content in the plasma of normal people is recorded as N. IR = Intensity / N. According to the density value ratio IR, if IR>1.04, it is diagnosed as hyperthyroidism.

[0109] The expression level of L-proline is different in different groups. The expression in hyperthyroidism patients is significantly higher than that in hypothyroidism and normal groups. The L-proline content in the plasma of the diagnosed subjects is recorded as Intensity, and the L-proline content in the plasma of normal people is recorded as N. IR = Intensity / N. According to the density value ratio IR, if IR>1.01, it is diagnosed as hyperthyroidism.

[0110] The expression levels of L-glutamic acid are different in different groups. The expression in hyperthyroidism patients is significantly higher than that in hypothyroidism and normal groups. The L-glutamic acid content in the plasma of the diagnosed subjects is recorded as Intensity, and the L-glutamic acid content in the plasma of normal people is recorded as N. IR = Intensity / N. According to the density value ratio IR, if IR>1.02, it is diagnosed as hyperthyroidism.

[0111] The expression levels of apolipoprotein L1 vary in different groups. The expression in patients with hypothyroidism is significantly higher than that in hyperthyroidism and normal groups. The expression level of apolipoprotein L1 in the plasma of the diagnosed subjects is recorded as Abundance, and the expression level of apolipoprotein L1 in the plasma of normal people is recorded as N. AR = Abundance / N. Based on the abundance value ratio AR, if AR>1.25, it is diagnosed as hypothyroidism.

[0112] The expression levels of α-trypsin inhibitor heavy chain H4 varied among different groups. The expression in hypothyroid patients was significantly higher than that in hyperthyroid and normal subjects. The expression level of α-trypsin inhibitor heavy chain H4 in the plasma of the diagnosed subjects was recorded as Abundance, and the expression level of α-trypsin inhibitor heavy chain H4 in the plasma of normal subjects was recorded as N. AR = Abundance / N. Based on the abundance ratio AR, if AR>1.31, hypothyroidism was diagnosed.

[0113] The expression levels of kininogen-1 vary in different groups. Its expression in hypothyroid patients is significantly higher than that in hyperthyroid and normal groups. The expression level of kininogen-1 in the plasma of the diagnosed subjects is recorded as Abundance, and the expression level of kininogen-1 in the plasma of normal subjects is recorded as N. AR = Abundance / N. Based on the abundance value ratio AR, if AR>1.35, it is diagnosed as hypothyroidism.

[0114] The expression level of cortisone in different groups is different. The expression in hypothyroid patients is significantly higher than that in hyperthyroid and normal groups. The cortisone content in the plasma of the diagnosed subjects is recorded as Intensity, and the cortisone content in the plasma of normal people is recorded as N. IR = Intensity / N. According to the density value ratio IR, if IR>1.05, it is determined to be hypothyroidism.

[0115] The expression level of cortisol in different groups is different. The expression in hypothyroid patients is significantly higher than that in hyperthyroid and normal groups. The cortisol content in the plasma of the diagnosed subjects is recorded as Intensity, and the cortisol content in the plasma of normal people is recorded as N. IR = Intensity / N. According to the density value ratio IR, if IR>1.06, it is determined to be hypothyroidism.

[0116] The expression levels of L-threonine vary in different groups. The expression in hypothyroid patients is significantly higher than that in hyperthyroid and normal groups. The L-threonine content in the plasma of the diagnosed subjects is recorded as Intensity, and the L-threonine content in the plasma of normal people is recorded as N. IR = Intensity / N. Based on the density value ratio IR, if IR>1.07, it is diagnosed as hypothyroidism.

[0117] While the six hyperthyroidism and hypothyroidism markers described above can each be used individually to diagnose thyroid dysfunction, as previously mentioned, combining these markers is more effective and offers higher accuracy. For each of the six hyperthyroidism or hypothyroidism markers, when combining multiple markers for diagnosis, the aforementioned AR or IR values are used to determine whether the condition is within the risk range. If all markers for each thyroid abnormality are within the risk range, a risk warning can be issued for that thyroid abnormality. Alternatively, as previously mentioned, a risk level can be assigned based on the proportion of markers within the risk range among all markers.

[0118] The embodiment described above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Persons skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent substitution or equivalent transformation falls within the scope of protection of the present invention. Sequence Listing <110> Institute of Basic Medicine and Oncology, Chinese Academy of Sciences (under preparation) <120> Biomarkers, kits and applications thereof for diagnosing abnormal thyroid function <160> 5 <170> SIPOSequenceListing 1.0 <210> 1 <211> 1744 <212> PRT <213> Homo sapiens <400> 1 Met Arg Leu Leu Trp Gly Leu Ile Trp Ala Ser Ser Phe Phe Thr Leu 1 5 10 15 Ser Leu Gln Lys Pro Arg Leu Leu Leu Phe Ser Pro Ser Val Val His 20 25 30 Leu Gly Val Pro Leu Ser Val Gly Val Gln Leu Gln Asp Val Pro Arg 35 40 45 Gly Gln Val Val Lys Gly Ser Val Phe Leu Arg Asn Pro Ser Arg Asn 50 55 60 Asn Val Pro Cys Ser Pro Lys Val Asp Phe Thr Leu Ser Ser Glu Arg 65 70 75 80 Asp Phe Ala Leu Leu Ser Leu Gln Val Pro Leu Lys Asp Ala Lys Ser 85 90 95 Cys Gly Leu His Gln Leu Leu Arg Gly Pro Glu Val Gln Leu Val Ala 100 105 110 His Ser Pro Trp Leu Lys Asp Ser Leu Ser Arg Thr Thr Asn Ile Gln 115 120 125 Gly Ile Asn Leu Leu Phe Ser Ser Arg Arg Gly His Leu Phe Leu Gln 130 135 140 Thr Asp Gln Pro Ile Tyr Asn Pro Gly Gln Arg Val Arg Tyr Arg Val 145 150 155 160 Phe Ala Leu Asp Gln Lys Met Arg Pro Ser Thr Asp Thr Ile Thr Val 165 170 175 Met Val Glu Asn Ser His Gly Leu Arg Val Arg Lys Lys Glu Val Tyr 180 185 190 Met Pro Ser Ser Ile Phe Gln Asp Asp Phe Val Ile Pro Asp Ile Ser 195 200 205 Glu Pro Gly Thr Trp Lys Ile Ser Ala Arg Phe Ser Asp Gly Leu Glu 210 215 220 Ser Asn Ser Ser Thr Gln Phe Glu Val Lys Lys Tyr Val Leu Pro Asn 225 230 235 240 Phe Glu Val Lys Ile Thr Pro Gly Lys Pro Tyr Ile Leu Thr Val Pro 245 250 255 Gly His Leu Asp Glu Met Gln Leu Asp Ile Gln Ala Arg Tyr Ile Tyr 260 265 270 Gly Lys Pro Val Gln Gly Val Ala Tyr Val Arg Phe Gly Leu Leu Asp 275 280 285 Glu Asp Gly Lys Lys Thr Phe Phe Arg Gly Leu Glu Ser Gln Thr Lys 290 295 300 Leu Val Asn Gly Gln Ser His Ile Ser Leu Ser Lys Ala Glu Phe Gln 305 310 315 320 Asp Ala Leu Glu Lys Leu Asn Met Gly Ile Thr Asp Leu Gln Gly Leu 325 330 335 Arg Leu Tyr Val Ala Ala Ala Ile Ile Glu Ser Pro Gly Gly Glu Met 340 345 350 Glu Glu Ala Glu Leu Thr Ser Trp Tyr Phe Val Ser Ser Pro Phe Ser 355 360 365 Leu Asp Leu Ser Lys Thr Lys Arg His Leu Val Pro Gly Ala Pro Phe 370 375 380 Leu Leu Gln Ala Leu Val Arg Glu Met Ser Gly Ser Pro Ala Ser Gly 385 390 395 400 Ile Pro Val Lys Val Ser Ala Thr Val Ser Ser Pro Gly Ser Val Pro 405 410 415 Glu Val Gln Asp Ile Gln Gln Asn Thr Asp Gly Ser Gly Gln Val Ser 420 425 430 Ile Pro Ile Ile Ile Pro Gln Thr Ile Ser Glu Leu Gln Leu Ser Val 435 440 445 Ser Ala Gly Ser Pro His Pro Ala Ile Ala Arg Leu Thr Val Ala Ala 450 455 460 Pro Pro Ser Gly Gly Pro Gly Phe Leu Ser Ile Glu Arg Pro Asp Ser 465 470 475 480 Arg Pro Pro Arg Val Gly Asp Thr Leu Asn Leu Asn Leu Arg Ala Val 485 490 495 Gly Ser Gly Ala Thr Phe Ser His Tyr Tyr Tyr Met Ile Leu Ser Arg 500 505 510 Gly Gln Ile Val Phe Met Asn Arg Glu Pro Lys Arg Thr Leu Thr Ser 515 520 525 Val Ser Val Phe Val Asp His His Leu Ala Pro Ser Phe Tyr Phe Val 530 535 540 Ala Phe Tyr Tyr His Gly Asp His Pro Val Ala Asn Ser Leu Arg Val 545 550 555 560 Asp Val Gln Ala Gly Ala Cys Glu Gly Lys Leu Glu Leu Ser Val Asp 565 570 575 Gly Ala Lys Gln Tyr Arg Asn Gly Glu Ser Val Lys Leu His Leu Glu 580 585 590 Thr Asp Ser Leu Ala Leu Val Ala Leu Gly Ala Leu Asp Thr Ala Leu 595 600 605 Tyr Ala Ala Gly Ser Lys Ser His Lys Pro Leu Asn Met Gly Lys Val 610 615 620 Phe Glu Ala Met Asn Ser Tyr Asp Leu Gly Cys Gly Pro Gly Gly Gly 625 630 635 640 Asp Ser Ala Leu Gln Val Phe Gln Ala Ala Gly Leu Ala Phe Ser Asp 645 650 655 Gly Asp Gln Trp Thr Leu Ser Arg Lys Arg Leu Ser Cys Pro Lys Glu 660 665 670 Lys Thr Thr Arg Lys Lys Arg Asn Val Asn Phe Gln Lys Ala Ile Asn 675 680 685 Glu Lys Leu Gly Gln Tyr Ala Ser Pro Thr Ala Lys Arg Cys Cys Gln 690 695 700 Asp Gly Val Thr Arg Leu Pro Met Met Arg Ser Cys Glu Gln Arg Ala 705 710 715 720 Ala Arg Val Gln Gln Pro Asp Cys Arg Glu Pro Phe Leu Ser Cys Cys 725 730 735 Gln Phe Ala Glu Ser Leu Arg Lys Lys Ser Arg Asp Lys Gly Gln Ala 740 745 750 Gly Leu Gln Arg Ala Leu Glu Ile Leu Gln Glu Glu Asp Leu Ile Asp 755 760 765 Glu Asp Asp Ile Pro Val Arg Ser Phe Phe Pro Glu Asn Trp Leu Trp 770 775 780 Arg Val Glu Thr Val Asp Arg Phe Gln Ile Leu Thr Leu Trp Leu Pro 785 790 795 800 Asp Ser Leu Thr Thr Trp Glu Ile His Gly Leu Ser Leu Ser Lys Thr 805 810 815 Lys Gly Leu Cys Val Ala Thr Pro Val Gln Leu Arg Val Phe Arg Glu 820 825 830 Phe His Leu His Leu Arg Leu Pro Met Ser Val Arg Arg Phe Glu Gln 835 840 845 Leu Glu Leu Arg Pro Val Leu Tyr Asn Tyr Leu Asp Lys Asn Leu Thr 850 855 860 Val Ser Val His Val Ser Pro Val Glu Gly Leu Cys Leu Ala Gly Gly 865 870 875 880 Gly Gly Leu Ala Gln Gln Val Leu Val Pro Ala Gly Ser Ala Arg Pro 885 890 895 Val Ala Phe Ser Val Val Pro Thr Ala Ala Ala Ala Val Ser Leu Lys 900 905 910 Val Val Ala Arg Gly Ser Phe Glu Phe Pro Val Gly Asp Ala Val Ser 915 920 925 Lys Val Leu Gln Ile Glu Lys Glu Gly Ala Ile His Arg Glu Glu Leu 930 935 940 Val Tyr Glu Leu Asn Pro Leu Asp His Arg Gly Arg Thr Leu Glu Ile 945 950 955 960 Pro Gly Asn Ser Asp Pro Asn Met Ile Pro Asp Gly Asp Phe Asn Ser 965 970 975 Tyr Val Arg Val Thr Ala Ser Asp Pro Leu Asp Thr Leu Gly Ser Glu 980 985 990 Gly Ala Leu Ser Pro Gly Gly Val Ala Ser Leu Leu Arg Leu Pro Arg 995 1000 1005 Gly Cys Gly Glu Gln Thr Met Ile Tyr Leu Ala Pro Thr Leu Ala Ala 1010 1015 1020 Ser Arg Tyr Leu Asp Lys Thr Glu Gln Trp Ser Thr Leu Pro Pro Glu 1025 1030 1035 1040 Thr Lys Asp His Ala Val Asp Leu Ile Gln Lys Gly Tyr Met Arg Ile 1045 1050 1055 Gln Gln Phe Arg Lys Ala Asp Gly Ser Tyr Ala Ala Trp Leu Ser Arg 1060 1065 1070 Asp Ser Ser Thr Trp Leu Thr Ala Phe Val Leu Lys Val Leu Ser Leu 1075 1080 1085 Ala Gln Glu Gln Val Gly Gly Ser Pro Glu Lys Leu Gln Glu Thr Ser 1090 1095 1100 Asn Trp Leu Leu Ser Gln Gln Gln Ala Asp Gly Ser Phe Gln Asp Pro 1105 1110 1115 1120 Cys Pro Val Leu Asp Arg Ser Met Gln Gly Gly Leu Val Gly Asn Asp 1125 1130 1135 Glu Thr Val Ala Leu Thr Ala Phe Val Thr Ile Ala Leu His His Gly 1140 1145 1150 Leu Ala Val Phe Gln Asp Glu Gly Ala Glu Pro Leu Lys Gln Arg Val 1155 1160 1165 Glu Ala Ser Ile Ser Lys Ala Asn Ser Phe Leu Gly Glu Lys Ala Ser 1170 1175 1180 Ala Gly Leu Leu Gly Ala His Ala Ala Ala Ile Thr Ala Tyr Ala Leu 1185 1190 1195 1200 Thr Leu Thr Lys Ala Pro Val Asp Leu Leu Gly Val Ala His Asn Asn 1205 1210 1215 Leu Met Ala Met Ala Gln Glu Thr Gly Asp Asn Leu Tyr Trp Gly Ser 1220 1225 1230 Val Thr Gly Ser Gln Ser Asn Ala Val Ser Pro Thr Pro Ala Pro Arg 1235 1240 1245 Asn Pro Ser Asp Pro Met Pro Gln Ala Pro Ala Leu Trp Ile Glu Thr 1250 1255 1260 Thr Ala Tyr Ala Leu Leu His Leu Leu Leu His Glu Gly Lys Ala Glu 1265 1270 1275 1280 Met Ala Asp Gln Ala Ser Ala Trp Leu Thr Arg Gln Gly Ser Phe Gln 1285 1290 1295 Gly Gly Phe Arg Ser Thr Gln Asp Thr Val Ile Ala Leu Asp Ala Leu 1300 1305 1310 Ser Ala Tyr Trp Ile Ala Ser His Thr Thr Glu Glu Arg Gly Leu Asn 1315 1320 1325 Val Thr Leu Ser Ser Thr Gly Arg Asn Gly Phe Lys Ser His Ala Leu 1330 1335 1340 Gln Leu Asn Asn Arg Gln Ile Arg Gly Leu Glu Glu Glu Leu Gln Phe 1345 1350 1355 1360 Ser Leu Gly Ser Lys Ile Asn Val Lys Val Gly Gly Asn Ser Lys Gly 1365 1370 1375 Thr Leu Lys Val Leu Arg Thr Tyr Asn Val Leu Asp Met Lys Asn Thr 1380 1385 1390 Thr Cys Gln Asp Leu Gln Ile Glu Val Thr Val Lys Gly His Val Glu 1395 1400 1405 Tyr Thr Met Glu Ala Asn Glu Asp Tyr Glu Asp Tyr Glu Tyr Asp Glu 1410 1415 1420 Leu Pro Ala Lys Asp Asp Pro Asp Ala Pro Leu Gln Pro Val Thr Pro 1425 1430 1435 1440 Leu Gln Leu Phe Glu Gly Arg Arg Asn Arg Arg Arg Arg Glu Ala Pro 1445 1450 1455 Lys Val Val Glu Glu Gln Glu Ser Arg Val His Tyr Thr Val Cys Ile 1460 1465 1470 Trp Arg Asn Gly Lys Val Gly Leu Ser Gly Met Ala Ile Ala Asp Val 1475 1480 1485 Thr Leu Leu Ser Gly Phe His Ala Leu Arg Ala Asp Leu Glu Lys Leu 1490 1495 1500 Thr Ser Leu Ser Asp Arg Tyr Val Ser His Phe Glu Thr Glu Gly Pro 1505 1510 1515 1520 His Val Leu Leu Tyr Phe Asp Ser Val Pro Thr Ser Arg Glu Cys Val 1525 1530 1535 Gly Phe Glu Ala Val Gln Glu Val Pro Val Gly Leu Val Gln Pro Ala 1540 1545 1550 Ser Ala Thr Leu Tyr Asp Tyr Tyr Asn Pro Glu Arg Arg Cys Ser Val 1555 1560 1565 Phe Tyr Gly Ala Pro Ser Lys Ser Arg Leu Leu Ala Thr Leu Cys Ser 1570 1575 1580 Ala Glu Val Cys Gln Cys Ala Glu Gly Lys Cys Pro Arg Gln Arg Arg 1585 1590 1595 1600 Ala Leu Glu Arg Gly Leu Gln Asp Glu Asp Gly Tyr Arg Met Lys Phe 1605 1610 1615 Ala Cys Tyr Tyr Pro Arg Val Glu Tyr Gly Phe Gln Val Lys Val Leu 1620 1625 1630 Arg Glu Asp Ser Arg Ala Ala Phe Arg Leu Phe Glu Thr Lys Ile Thr 1635 1640 1645 Gln Val Leu His Phe Thr Lys Asp Val Lys Ala Ala Ala Asn Gln Met 1650 1655 1660 Arg Asn Phe Leu Val Arg Ala Ser Cys Arg Leu Arg Leu Glu Pro Gly 1665 1670 1675 1680 Lys Glu Tyr Leu Ile Met Gly Leu Asp Gly Ala Thr Tyr Asp Leu Glu 1685 1690 1695 Gly His Pro Gln Tyr Leu Leu Asp Ser Asn Ser Trp Ile Glu Glu Met 1700 1705 1710 Pro Ser Glu Arg Leu Cys Arg Ser Thr Arg Gln Arg Ala Ala Cys Ala 1715 1720 1725 Gln Leu Asn Asp Phe Leu Gln Glu Tyr Gly Thr Gln Gly Cys Gln Val 1730 1735 1740 <210> 2 <211> 1266 <212> PRT <213> Homo sapiens <400> 2 Met Gly Pro Leu Met Val Leu Phe Cys Leu Leu Phe Leu Tyr Pro Gly 1 5 10 15 Leu Ala Asp Ser Ala Pro Ser Cys Pro Gln Asn Val Asn Ile Ser Gly 20 25 30 Gly Thr Phe Thr Leu Ser His Gly Trp Ala Pro Gly Ser Leu Leu Thr 35 40 45 Tyr Ser Cys Pro Gln Gly Leu Tyr Pro Ser Pro Ala Ser Arg Leu Cys 50 55 60 Lys Ser Ser Gly Gln Trp Gln Thr Pro Gly Ala Thr Arg Ser Leu Ser 65 70 75 80 Lys Ala Val Cys Lys Pro Gly His Cys Pro Asn Pro Gly Ile Ser Leu 85 90 95 Gly Ala Val Arg Thr Gly Phe Arg Phe Gly His Gly Asp Lys Val Arg 100 105 110 Tyr Arg Cys Ser Ser Asn Leu Val Leu Thr Gly Ser Ser Glu Arg Glu 115 120 125 Cys Gln Gly Asn Gly Val Trp Ser Gly Thr Glu Pro Ile Cys Arg Gln 130 135 140 Pro Tyr Ser Tyr Asp Phe Pro Glu Asp Val Ala Pro Ala Leu Gly Thr 145 150 155 160 Ser Phe Ser His Met Leu Gly Ala Thr Asn Pro Thr Gln Lys Thr Lys 165 170 175 Asp His Glu Asn Gly Thr Gly Thr Asn Thr Tyr Ala Ala Leu Asn Ser 180 185 190 Val Tyr Leu Met Met Asn Asn Gln Met Arg Leu Leu Gly Met Glu Thr 195 200 205 Met Ala Trp Gln Glu Ile Arg His Ala Ile Ile Leu Leu Thr Asp Gly 210 215 220 Lys Ser Asn Met Gly Gly Ser Pro Lys Thr Ala Val Asp His Ile Arg 225 230 235 240 Glu Ile Leu Asn Ile Asn Gln Lys Arg Asn Asp Tyr Leu Asp Ile Tyr 245 250 255 Ala Ile Gly Val Gly Lys Leu Asp Val Asp Trp Arg Glu Leu Asn Glu 260 265 270 Leu Gly Ser Lys Lys Asp Gly Glu Arg His Ala Phe Ile Leu Gln Asp 275 280 285 Thr Lys Ala Leu His Gln Val Phe Glu His Met Leu Asp Val Ser Lys 290 295 300 Leu Thr Asp Thr Ile Cys Gly Val Gly Asn Met Ser Ala Asn Ala Ser 305 310 315 320 Asp Gln Glu Arg Thr Pro Trp His Val Thr Ile Lys Pro Lys Ser Gln 325 330 335 Glu Thr Cys Arg Gly Ala Leu Ile Ser Asp Gln Trp Val Leu Thr Ala 340 345 350 Ala His Cys Phe Arg Asp Gly Asn Asp His Ser Leu Trp Arg Val Asn 355 360 365 Val Gly Asp Pro Lys Ser Gln Trp Gly Lys Glu Phe Leu Ile Glu Lys 370 375 380 Ala Val Ile Ser Pro Gly Phe Asp Val Phe Ala Lys Lys Asn Gln Gly 385 390 395 400 Ile Leu Glu Phe Tyr Gly Asp Asp Ile Ala Leu Leu Lys Leu Ala Gln 405 410 415 Lys Val Lys Met Ser Thr His Ala Arg Pro Ile Cys Leu Pro Cys Thr 420 425 430 Met Glu Ala Asn Leu Ala Leu Arg Arg Pro Gln Gly Ser Thr Cys Arg 435 440 445 Asp His Glu Asn Glu Leu Leu Asn Lys Gln Ser Val Pro Ala His Phe 450 455 460 Val Ala Leu Asn Gly Ser Lys Leu Asn Ile Asn Leu Lys Met Gly Val 465 470 475 480 Glu Trp Thr Ser Cys Ala Glu Val Val Ser Gln Glu Lys Thr Met Phe 485 490 495 Pro Asn Leu Thr Asp Val Arg Glu Val Val Thr Asp Gln Phe Leu Cys 500 505 510 Ser Gly Thr Gln Glu Asp Glu Ser Pro Cys Lys Gly Val Thr Thr Thr 515 520 525 Pro Trp Ser Leu Ala Arg Pro Gln Gly Ser Cys Ser Leu Glu Gly Val 530 535 540 Glu Ile Lys Gly Gly Ser Phe Arg Leu Leu Gln Glu Gly Gln Ala Leu 545 550 555 560 Glu Tyr Val Cys Pro Ser Gly Phe Tyr Pro Tyr Pro Val Gln Thr Arg 565 570 575 Thr Cys Arg Ser Thr Gly Ser Trp Ser Thr Leu Lys Thr Gln Asp Gln 580 585 590 Lys Thr Val Arg Lys Ala Glu Cys Arg Ala Ile His Cys Pro Arg Pro 595 600 605 His Asp Phe Glu Asn Gly Glu Tyr Trp Pro Arg Ser Pro Tyr Tyr Asn 610 615 620 Val Ser Asp Glu Ile Ser Phe His Cys Tyr Asp Gly Tyr Thr Leu Arg 625 630 635 640 Gly Ser Ala Asn Arg Thr Cys Gln Val Asn Gly Arg Trp Ser Gly Gln 645 650 655 Thr Ala Ile Cys Asp Asn Gly Ala Gly Tyr Cys Ser Asn Pro Gly Ile 660 665 670 Pro Ile Gly Thr Arg Lys Val Gly Ser Gln Tyr Arg Leu Glu Asp Ser 675 680 685 Val Thr Tyr His Cys Ser Arg Gly Leu Thr Leu Arg Gly Ser Gln Arg 690 695 700 Arg Thr Cys Gln Glu Gly Gly Ser Trp Ser Gly Thr Glu Pro Ser Cys 705 710 715 720 Gln Asp Ser Phe Met Tyr Asp Thr Pro Gln Glu Val Ala Glu Ala Phe 725 730 735 Leu Ser Ser Leu Thr Glu Thr Ile Glu Gly Val Asp Ala Glu Asp Gly 740 745 750 His Gly Pro Gly Glu Gln Gln Lys Arg Lys Ile Val Leu Asp Pro Ser 755 760 765 Gly Ser Met Asn Ile Tyr Leu Val Leu Asp Gly Ser Asp Ser Ile Gly 770 775 780 Ala Ser Asn Phe Thr Gly Ala Lys Lys Cys Leu Val Asn Leu Ile Glu 785 790 795 800 Lys Val Ala Ser Tyr Gly Val Lys Pro Arg Tyr Gly Leu Val Thr Tyr 805 810 815 Ala Thr Tyr Pro Lys Ile Trp Val Lys Val Ser Glu Ala Asp Ser Ser 820 825 830 Asn Ala Asp Trp Val Thr Lys Gln Leu Asn Glu Ile Asn Tyr Glu Asp 835 840 845 His Lys Leu Lys Ser Gly Thr Asn Thr Lys Lys Ala Leu Gln Ala Val 850 855 860 Tyr Ser Met Met Ser Trp Pro Asp Asp Val Pro Pro Glu Gly Trp Asn 865 870 875 880 Arg Thr Arg His Val Ile Ile Leu Met Thr Asp Gly Leu His Asn Met 885 890 895 Gly Gly Asp Pro Ile Thr Val Ile Asp Glu Ile Arg Asp Leu Leu Tyr 900 905 910 Ile Gly Lys Asp Arg Lys Asn Pro Arg Glu Asp Tyr Leu Asp Val Tyr 915 920 925 Val Phe Gly Val Gly Pro Leu Val Asn Gln Val Asn Ile Asn Ala Leu 930 935 940 Ala Ser Lys Lys Asp Asn Glu Gln His Val Phe Lys Val Lys Asp Met 945 950 955 960 Glu Asn Leu Glu Asp Val Phe Tyr Gln Met Ile Asp Glu Ser Gln Ser 965 970 975 Leu Ser Leu Cys Gly Met Val Trp Glu His Arg Lys Gly Thr Asp Tyr 980 985 990 His Lys Gln Pro Trp Gln Ala Lys Ile Ser Val Ile Arg Pro Ser Lys 995 1000 1005 Gly His Glu Ser Cys Met Gly Ala Val Val Ser Glu Tyr Phe Val Leu 1010 1015 1020 Thr Ala Ala His Cys Phe Thr Val Asp Asp Lys Glu His Ser Ile Lys 1025 1030 1035 1040 Val Ser Val Gly Gly Glu Lys Arg Asp Leu Glu Ile Glu Val Val Leu 1045 1050 1055 Phe His Pro Asn Tyr Asn Ile Asn Gly Lys Lys Glu Ala Gly Ile Pro 1060 1065 1070 Glu Phe Tyr Asp Tyr Asp Val Ala Leu Ile Lys Leu Lys Asn Lys Leu 1075 1080 1085 Lys Tyr Gly Gln Thr Ile Arg Pro Ile Cys Leu Pro Cys Thr Glu Gly 1090 1095 1100 Thr Thr Arg Ala Leu Arg Leu Pro Pro Thr Thr Thr Cys Gln Gln Gln 1105 1110 1115 1120 Lys Glu Glu Leu Leu Pro Ala Gln Asp Ile Lys Ala Leu Phe Val Ser 1125 1130 1135 Glu Glu Glu Lys Lys Leu Thr Arg Lys Glu Val Tyr Ile Lys Asn Gly 1140 1145 1150 Asp Lys Lys Gly Ser Cys Glu Arg Asp Ala Gln Tyr Ala Pro Gly Tyr 1155 1160 1165 Asp Lys Val Lys Asp Ile Ser Glu Val Val Thr Pro Arg Phe Leu Cys 1170 1175 1180 Thr Gly Gly Val Ser Pro Tyr Ala Asp Pro Asn Thr Cys Arg Gly Asp 1185 1190 1195 1200 Ser Gly Gly Pro Leu Ile Val His Lys Arg Ser Arg Phe Ile Gln Val 1205 1210 1215 Gly Val Ile Ser Trp Gly Val Val Asp Val Cys Lys Asn Gln Lys Arg 1220 1225 1230 Gln Lys Gln Val Pro Ala His Ala Arg Asp Phe His Ile Asn Leu Phe 1235 1240 1245 Gln Val Leu Pro Trp Leu Lys Glu Lys Leu Gln Asp Glu Asp Leu Gly 1250 1255 1260 Phe Leu 1265 <210> 3 <211> 398 <212> PRT <213> Homo sapiens <400> 3 Met Glu Gly Ala Ala Leu Leu Arg Val Ser Val Leu Cys Ile Trp Met 1 5 10 15 Ser Ala Leu Phe Leu Gly Val Gly Val Arg Ala Glu Glu Ala Gly Ala 20 25 30 Arg Val Gln Gln Asn Val Pro Ser Gly Thr Asp Thr Gly Asp Pro Gln 35 40 45 Ser Lys Pro Leu Gly Asp Trp Ala Ala Gly Thr Met Asp Pro Glu Ser 50 55 60 Ser Ile Phe Ile Glu Asp Ala Ile Lys Tyr Phe Lys Glu Lys Val Ser 65 70 75 80 Thr Gln Asn Leu Leu Leu Leu Leu Thr Asp Asn Glu Ala Trp Asn Gly 85 90 95 Phe Val Ala Ala Ala Glu Leu Pro Arg Asn Glu Ala Asp Glu Leu Arg 100 105 110 Lys Ala Leu Asp Asn Leu Ala Arg Gln Met Ile Met Lys Asp Lys Asn 115 120 125 Trp His Asp Lys Gly Gln Gln Tyr Arg Asn Trp Phe Leu Lys Glu Phe 130 135 140 Pro Arg Leu Lys Ser Glu Leu Glu Asp Asn Ile Arg Arg Leu Arg Ala 145 150 155 160 Leu Ala Asp Gly Val Gln Lys Val His Lys Gly Thr Thr Ile Ala Asn 165 170 175 Val Val Ser Gly Ser Leu Ser Ile Ser Ser Gly Ile Leu Thr Leu Val 180 185 190 Gly Met Gly Leu Ala Pro Phe Thr Glu Gly Gly Ser Leu Val Leu Leu 195 200 205 Glu Pro Gly Met Glu Leu Gly Ile Thr Ala Ala Leu Thr Gly Ile Thr 210 215 220 Ser Ser Thr Met Asp Tyr Gly Lys Lys Trp Trp Thr Gln Ala Gln Ala 225 230 235 240 His Asp Leu Val Ile Lys Ser Leu Asp Lys Leu Lys Glu Val Arg Glu 245 250 255 Phe Leu Gly Glu Asn Ile Ser Asn Phe Leu Ser Leu Ala Gly Asn Thr 260 265 270 Tyr Gln Leu Thr Arg Gly Ile Gly Lys Asp Ile Arg Ala Leu Arg Arg 275 280 285 Ala Arg Ala Asn Leu Gln Ser Val Pro His Ala Ser Ala Ser Arg Pro 290 295 300 Arg Val Thr Glu Pro Ile Ser Ala Glu Ser Gly Glu Gln Val Glu Arg 305 310 315 320 Val Asn Glu Pro Ser Ile Leu Glu Met Ser Arg Gly Val Lys Leu Thr 325 330 335 Asp Val Ala Pro Val Ser Phe Phe Leu Val Leu Asp Val Val Tyr Leu 340 345 350 Val Tyr Glu Ser Lys His Leu His Glu Gly Ala Lys Ser Glu Thr Ala 355 360 365 Glu Glu Leu Lys Lys Val Ala Gln Glu Leu Glu Glu Lys Leu Asn Ile 370 375 380 Leu Asn Asn Asn Tyr Lys Ile Leu Gln Ala Asp Gln Glu Leu 385 390 395 <210> 4 <211> 930 <212> PRT <213> Homo sapiens <400> 4 Met Lys Pro Pro Arg Pro Val Arg Thr Cys Ser Lys Val Leu Val Leu 1 5 10 15 Leu Ser Leu Leu Ala Ile His Gln Thr Thr Thr Ala Glu Lys Asn Gly 20 25 30 Ile Asp Ile Tyr Ser Leu Thr Val Asp Ser Arg Val Ser Ser Arg Phe 35 40 45 Ala His Thr Val Val Thr Ser Arg Val Val Asn Arg Ala Asn Thr Val 50 55 60 Gln Glu Ala Thr Phe Gln Met Glu Leu Pro Lys Lys Ala Phe Ile Thr 65 70 75 80 Asn Phe Ser Met Ile Ile Asp Gly Met Thr Tyr Pro Gly Ile Ile Lys 85 90 95 Glu Lys Ala Glu Ala Gln Ala Gln Tyr Ser Ala Ala Val Ala Lys Gly 100 105 110 Lys Ser Ala Gly Leu Val Lys Ala Thr Gly Arg Asn Met Glu Gln Phe 115 120 125 Gln Val Ser Val Ser Val Ala Pro Asn Ala Lys Ile Thr Phe Glu Leu 130 135 140 Val Tyr Glu Glu Leu Leu Lys Arg Arg Leu Gly Val Tyr Glu Leu Leu 145 150 155 160 Leu Lys Val Arg Pro Gln Gln Leu Val Lys His Leu Gln Met Asp Ile 165 170 175 His Ile Phe Glu Pro Gln Gly Ile Ser Phe Leu Glu Thr Glu Ser Thr 180 185 190 Phe Met Thr Asn Gln Leu Val Asp Ala Leu Thr Thr Trp Gln Asn Lys 195 200 205 Thr Lys Ala His Ile Arg Phe Lys Pro Thr Leu Ser Gln Gln Gln Lys 210 215 220 Ser Pro Glu Gln Gln Glu Thr Val Leu Asp Gly Asn Leu Ile Ile Arg 225 230 235 240 Tyr Asp Val Asp Arg Ala Ile Ser Gly Gly Ser Ile Gln Ile Glu Asn 245 250 255 Gly Tyr Phe Val His Tyr Phe Ala Pro Glu Gly Leu Thr Thr Met Pro 260 265 270 Lys Asn Val Val Phe Val Ile Asp Lys Ser Gly Ser Met Ser Gly Arg 275 280 285 Lys Ile Gln Gln Thr Arg Glu Ala Leu Ile Lys Ile Leu Asp Asp Leu 290 295 300 Ser Pro Arg Asp Gln Phe Asn Leu Ile Val Phe Ser Thr Glu Ala Thr 305 310 315 320 Gln Trp Arg Pro Ser Leu Val Pro Ala Ser Ala Glu Asn Val Asn Lys 325 330 335 Ala Arg Ser Phe Ala Ala Gly Ile Gln Ala Leu Gly Gly Thr Asn Ile 340 345 350 Asn Asp Ala Met Leu Met Ala Val Gln Leu Leu Asp Ser Ser Asn Gln 355 360 365 Glu Glu Arg Leu Pro Glu Gly Ser Val Ser Leu Ile Ile Leu Leu Thr 370 375 380 Asp Gly Asp Pro Thr Val Gly Glu Thr Asn Pro Arg Ser Ile Gln Asn 385 390 395 400 Asn Val Arg Glu Ala Val Ser Gly Arg Tyr Ser Leu Phe Cys Leu Gly 405 410 415 Phe Gly Phe Asp Val Ser Tyr Ala Phe Leu Glu Lys Leu Ala Leu Asp 420 425 430 Asn Gly Gly Leu Ala Arg Arg Ile His Glu Asp Ser Asp Ser Ala Leu 435 440 445 Gln Leu Gln Asp Phe Tyr Gln Glu Val Ala Asn Pro Leu Leu Thr Ala 450 455 460 Val Thr Phe Glu Tyr Pro Ser Asn Ala Val Glu Glu Val Thr Gln Asn 465 470 475 480 Asn Phe Arg Leu Leu Phe Lys Gly Ser Glu Met Val Val Ala Gly Lys 485 490 495 Leu Gln Asp Arg Gly Pro Asp Val Leu Thr Ala Thr Val Ser Gly Lys 500 505 510 Leu Pro Thr Gln Asn Ile Thr Phe Gln Thr Glu Ser Ser Val Ala Glu 515 520 525 Gln Glu Ala Glu Phe Gln Ser Pro Lys Tyr Ile Phe His Asn Phe Met 530 535 540 Glu Arg Leu Trp Ala Tyr Leu Thr Ile Gln Gln Leu Leu Glu Gln Thr 545 550 555 560 Val Ser Ala Ser Asp Ala Asp Gln Gln Ala Leu Arg Asn Gln Ala Leu 565 570 575 Asn Leu Ser Leu Ala Tyr Ser Phe Val Thr Pro Leu Thr Ser Met Val 580 585 590 Val Thr Lys Pro Asp Asp Gln Glu Gln Ser Gln Val Ala Glu Lys Pro 595 600 605 Met Glu Gly Glu Ser Arg Asn Arg Asn Val His Ser Gly Ser Thr Phe 610 615 620 Phe Lys Tyr Tyr Leu Gln Gly Ala Lys Ile Pro Lys Pro Glu Ala Ser 625 630 635 640 Phe Ser Pro Arg Arg Gly Trp Asn Arg Gln Ala Gly Ala Ala Gly Ser 645 650 655 Arg Met Asn Phe Arg Pro Gly Val Leu Ser Ser Arg Gln Leu Gly Leu 660 665 670 Pro Gly Pro Pro Asp Val Pro Asp His Ala Ala Tyr His Pro Phe Arg 675 680 685 Arg Leu Ala Ile Leu Pro Ala Ser Ala Pro Pro Ala Thr Ser Asn Pro 690 695 700 Asp Pro Ala Val Ser Arg Val Met Asn Met Lys Ile Glu Glu Thr Thr 705 710 715 720 Met Thr Thr Gln Thr Pro Ala Pro Ile Gln Ala Pro Ser Ala Ile Leu 725 730 735 Pro Leu Pro Gly Gln Ser Val Glu Arg Leu Cys Val Asp Pro Arg His 740 745 750 Arg Gln Gly Pro Val Asn Leu Leu Ser Asp Pro Glu Gln Gly Val Glu 755 760 765 Val Thr Gly Gln Tyr Glu Arg Glu Lys Ala Gly Phe Ser Trp Ile Glu 770 775 780 Val Thr Phe Lys Asn Pro Leu Val Trp Val His Ala Ser Pro Glu His 785 790 795 800 Val Val Val Thr Arg Asn Arg Arg Ser Ser Ala Tyr Lys Trp Lys Glu 805 810 815 Thr Leu Phe Ser Val Met Pro Gly Leu Lys Met Thr Met Asp Lys Thr 820 825 830 Gly Leu Leu Leu Leu Ser Asp Pro Asp Lys Val Thr Ile Gly Leu Leu 835 840 845 Phe Trp Asp Gly Arg Gly Glu Gly Leu Arg Leu Leu Leu Arg Asp Thr 850 855 860 Asp Arg Phe Ser Ser His Val Gly Gly Thr Leu Gly Gln Phe Tyr Gln 865 870 875 880 Glu Val Leu Trp Gly Ser Pro Ala Ala Ser Asp Asp Gly Arg Arg Thr 885 890 895 Leu Arg Val Gln Gly Asn Asp His Ser Ala Thr Arg Glu Arg Arg Leu 900 905 910 Asp Tyr Gln Glu Gly Pro Pro Gly Val Glu Ile Ser Cys Trp Ser Val 915 920 925 Glu Leu 930 <210> 5 <211> 644 <212> PRT <213> Homo sapiens <400> 5 Met Lys Leu Ile Thr Ile Leu Phe Leu Cys Ser Arg Leu Leu Leu Ser 1 5 10 15 Leu Thr Gln Glu Ser Gln Ser Glu Glu Ile Asp Cys Asn Asp Lys Asp 20 25 30 Leu Phe Lys Ala Val Asp Ala Ala Leu Lys Lys Tyr Asn Ser Gln Asn 35 40 45 Gln Ser Asn Asn Gln Phe Val Leu Tyr Arg Ile Thr Glu Ala Thr Lys 50 55 60 Thr Val Gly Ser Asp Thr Phe Tyr Ser Phe Lys Tyr Glu Ile Lys Glu 65 70 75 80 Gly Asp Cys Pro Val Gln Ser Gly Lys Thr Trp Gln Asp Cys Glu Tyr 85 90 95 Lys Asp Ala Ala Lys Ala Ala Thr Gly Glu Cys Thr Ala Thr Val Gly 100 105 110 Lys Arg Ser Ser Thr Lys Phe Ser Val Ala Thr Gln Thr Cys Gln Ile 115 120 125 Thr Pro Ala Glu Gly Pro Val Val Thr Ala Gln Tyr Asp Cys Leu Gly 130 135 140 Cys Val His Pro Ile Ser Thr Gln Ser Pro Asp Leu Glu Pro Ile Leu 145 150 155 160 Arg His Gly Ile Gln Tyr Phe Asn Asn Asn Thr Gln His Ser Ser Leu 165 170 175 Phe Met Leu Asn Glu Val Lys Arg Ala Gln Arg Gln Val Val Ala Gly 180 185 190 Leu Asn Phe Arg Ile Thr Tyr Ser Ile Val Gln Thr Asn Cys Ser Lys 195 200 205 Glu Asn Phe Leu Phe Leu Thr Pro Asp Cys Lys Ser Leu Trp Asn Gly 210 215 220 Asp Thr Gly Glu Cys Thr Asp Asn Ala Tyr Ile Asp Ile Gln Leu Arg 225 230 235 240 Ile Ala Ser Phe Ser Gln Asn Cys Asp Ile Tyr Pro Gly Lys Asp Phe 245 250 255 Val Gln Pro Pro Thr Lys Ile Cys Val Gly Cys Pro Arg Asp Ile Pro 260 265 270 Thr Asn Ser Pro Glu Leu Glu Glu Thr Leu Thr His Thr Ile Thr Lys 275 280 285 Leu Asn Ala Glu Asn Asn Ala Thr Phe Tyr Phe Lys Ile Asp Asn Val 290 295 300 Lys Lys Ala Arg Val Gln Val Val Ala Gly Lys Lys Tyr Phe Ile Asp 305 310 315 320 Phe Val Ala Arg Glu Thr Thr Cys Ser Lys Glu Ser Asn Glu Glu Leu 325 330 335 Thr Glu Ser Cys Glu Thr Lys Lys Leu Gly Gln Ser Leu Asp Cys Asn 340 345 350 Ala Glu Val Tyr Val Val Pro Trp Glu Lys Lys Ile Tyr Pro Thr Val 355 360 365 Asn Cys Gln Pro Leu Gly Met Ile Ser Leu Met Lys Arg Pro Pro Gly 370 375 380 Phe Ser Pro Phe Arg Ser Ser Arg Ile Gly Glu Ile Lys Glu Glu Thr 385 390 395 400 Thr Val Ser Pro Pro His Thr Ser Met Ala Pro Ala Gln Asp Glu Glu 405 410 415 Arg Asp Ser Gly Lys Glu Gln Gly His Thr Arg Arg His Asp Trp Gly 420 425 430 His Glu Lys Gln Arg Lys His Asn Leu Gly His Gly His Lys His Glu 435 440 445 Arg Asp Gln Gly His Gly His Gln Arg Gly His Gly Leu Gly His Gly 450 455 460 His Glu Gln Gln His Gly Leu Gly His Gly His Lys Phe Lys Leu Asp 465 470 475 480 Asp Asp Leu Glu His Gln Gly Gly His Val Leu Asp His Gly His Lys 485 490 495 His Lys His Gly His Gly His Gly Lys His Lys Asn Lys Gly Lys Lys 500 505 510 Asn Gly Lys His Asn Gly Trp Lys Thr Glu His Leu Ala Ser Ser Ser 515 520 525 Glu Asp Ser Thr Thr Pro Ser Ala Gln Thr Gln Glu Lys Thr Glu Gly 530 535 540 Pro Thr Pro Ile Pro Ser Leu Ala Lys Pro Gly Val Thr Val Thr Phe 545 550 555 560 Ser Asp Phe Gln Asp Ser Asp Leu Ile Ala Thr Met Met Pro Pro Ile 565 570 575 Ser Pro Ala Pro Ile Gln Ser Asp Asp Asp Trp Ile Pro Asp Ile Gln 580 585 590 Ile Asp Pro Asn Gly Leu Ser Phe Asn Pro Ile Ser Asp Phe Pro Asp 595 600 605 Thr Thr Ser Pro Lys Cys Pro Gly Arg Pro Trp Lys Ser Val Ser Glu 610 615 620 Ile Asn Pro Thr Thr Gln Met Lys Glu Ser Tyr Tyr Phe Asp Leu Thr 625 630 635 640 Asp Gly Leu Ser

Claims

1. A biomarker for diagnosing abnormal thyroid function, characterized in that: It is a marker of hyperthyroidism and hypothyroidism present in human plasma; The hyperthyroidism marker is a combination of six markers: complement C4-A, C3 / C5 convertase, glutathione peroxidase 3, L-arginine, L-proline and L-glutamate; The hypothyroidism marker is a combination of six markers: apolipoprotein L1, α-trypsin inhibitor heavy chain H4, kininogen-1, cortisone, cortisol and L-threonine.

2. Use of a reagent for detecting the biomarker according to claim 1 in preparing a diagnostic kit or detection device for abnormal thyroid function.

3. A kit for diagnosing abnormal thyroid function, characterized in that: The invention comprises a reagent for detecting the biomarker according to claim 1.

4. The kit for diagnosing abnormal thyroid function according to claim 3, wherein The kit is an ELISA kit.

5. Use of the biomarker according to claim 1 in the diagnosis of thyroid dysfunction for non-disease diagnosis or treatment purposes.

6. A diagnostic device for diagnosing abnormal thyroid function, characterized in that: include: A data acquisition device for acquiring test data of a diagnostic subject, wherein the test data is the level value of each biomarker according to claim 1 detected in the human plasma of the diagnostic subject, wherein if the marker is a protein, the expression amount of the protein is used as the level value; if the marker is a metabolite, the content of the metabolite in the plasma is used as the level value; a data processing device for calculating an index value for each marker based on the test data of the diagnostic subject, wherein the index value for each marker is a ratio between the level of the marker in the plasma of the diagnostic subject and the level of the marker in the plasma of a normal human without abnormal thyroid function, and then determining whether the calculated index value for each marker is within a risk range for the corresponding marker; if the index value of one or more markers among all the markers is within the risk range for hyperthyroidism or hypothyroidism, then providing a corresponding diagnostic result prompt of abnormal thyroid function; The risk range of the complement C4-A indicating hyperthyroidism is an index value less than 0.95; the risk range of the C3 / C5 convertase indicating hyperthyroidism is an index value greater than 1.04; the risk range of the glutathione peroxidase 3 indicating hyperthyroidism is an index value less than 0.98; the risk range of the L-arginine indicating hyperthyroidism is an index value greater than 1.04; the risk range of the L-proline indicating hyperthyroidism is an index value greater than 1.01; the risk range of the L-glutamate indicating hyperthyroidism is an index value greater than 1.0 2; the risk range of hypothyroidism corresponding to the apolipoprotein L1 is an index value greater than 1.25; the risk range of hypothyroidism corresponding to the α-trypsin inhibitor heavy chain H4 is an index value greater than 1.31; the risk range of hypothyroidism corresponding to the kininogen-1 is an index value greater than 1.35; the risk range of hypothyroidism corresponding to the cortisone is an index value greater than 1.05; the risk range of hypothyroidism corresponding to the cortisol is an index value greater than 1.06; the risk range of hypothyroidism corresponding to the L-threonine is an index value greater than 1.

07.

7. The diagnostic device according to claim 6, wherein In the data processing device, a corresponding diagnosis result prompt of abnormal thyroid function is given only when the index values of all markers in the hyperthyroidism markers are within their respective risk ranges or when the index values of all markers in the hypothyroidism markers are within their respective risk ranges.

8. The diagnostic device according to claim 6, wherein The data acquisition device is an input device for inputting data or a communication device for reading data from an external data storage device through an interface.

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