Method for detecting circulating bmp10 (bone morphogenetic protein 10)

Abstract

The present invention relates to a method for assessing atrial fibrillation in a subject, said method comprising the steps of determining the amount of BMP10 in a sample from said subject, and comparing said amount of BMP10 to a reference amount, whereby atrial fibrillation is assessed. Furthermore, the present invention relates to a method for diagnosing heart failure based on the determination of BMP10 in a sample from a subject. In addition, the present invention relates to a method for predicting the risk of a subject to be hospitalized due to heart failure based on the determination of BMP10-type peptides in a sample from a subject. The present invention further relates to antibodies binding to one or more BMP10-type peptides, such as NT-proBMP10.

Description

[0001] This invention relates to a method for assessing atrial fibrillation in a subject, the method comprising the steps of: determining the amount of one or more BMP10-type peptides in a sample from the subject, and comparing the amount of the one or more BMP10-type peptides with a reference, thereby assessing atrial fibrillation. Furthermore, this invention relates to a method for diagnosing heart failure based on the determination of one or more BMP10-type peptides in a sample from a subject. Additionally, this invention relates to a method for predicting the risk of hospitalization for heart failure in a subject based on the determination of one or more BMP10-type peptides in a sample from a subject. The invention further relates to antibodies that bind to one or more BMP10-type peptides such as NT-proBMP10. Background Technology

[0002] Atrial fibrillation (AF) is the most common type of heart rhythm disorder and one of the most prevalent conditions among the elderly. AF is characterized by irregular heartbeats that typically begin with brief, abnormal beats that can increase in intensity over time and may become permanent. An estimated 2.7 to 6.1 million Americans have AF, and approximately 33 million people worldwide have the condition (Chugh SS et al., Circulation 2014; 129:837-47).

[0003] The diagnosis of arrhythmias such as atrial fibrillation typically involves determining the cause of the arrhythmia and classifying it. Guidelines for classifying atrial fibrillation according to the American College of Cardiology (ACC), the American Heart Association (AHA), and the European Society of Cardiology (ESC) are primarily based on simplicity and clinical relevance. Category 1 is called “First-Detected AF.” People in this category are initially diagnosed with AF and may or may not have had previously undetected episodes. If the first-detected episode stops spontaneously within a week, but another episode subsequently occurs, the category changes to “Paroxysmal AF.” Although episodes in this category can last up to 7 days, in most cases of paroxysmal AF, the episode will stop within 24 hours. If the episode lasts for more than a week, it is classified as “Persistent AF.” If the episode cannot be stopped—that is, cannot be stopped by electrical or pharmacological cardioversion—and persists for more than a year, the classification changes to “Permanent AF.” Because atrial fibrillation is a significant risk factor for stroke and systemic embolism, early diagnosis of atrial fibrillation is crucial (Hart et al., Ann Intern Med 2007; 146(12):857-67; Go AS et al., JAMA 2001; 285(18):2370-5). Stroke is the second leading cause of disability-adjusted life years in high-income countries and the second leading cause of death globally, after ischemic heart disease. Anticoagulation therapy appears to be the most appropriate treatment to reduce stroke risk.

[0004] We very much hope that biomarkers for assessing atrial fibrillation will be allowed.

[0005] Latini R. et al. (J Intern Med. 2011 Feb; 269(2): 160-71) measured various circulating biomarkers (hsTnT, NT-proBNP, MR-proANP, MR-proADM, copeptin, and CT-pro-endothelin-1) in patients with atrial fibrillation.

[0006] Bone morphogenetic protein 10 (BMP10) is a ligand of the TGF-β (transforming growth factor-β) protein superfamily. Ligands of this family bind to various TGF-β receptors, leading to the recruitment and activation of transcription factors that regulate gene expression. BMP10 binds to activin receptor-like kinase 1 (ALK1) and has been shown to be a functional activator of this kinase in endothelial cells (David et al., Blood. 2007, 109(5):1953-61).

[0007] Bone morphogenetic proteins circulate in the blood in various forms (uncut, processed, or compounded). Kienast et al., J. Biol. Chem. (2016) 293(28) 10963–10974 examined circulating variants of BMP9 and found that mature BMP9 accounts for only 0.5% of total BMP9 in human plasma compared to other BMP9 variants.

[0008] Human preproBMP10 contains a short signal peptide (amino acids 1 to 21), which is enzymatically cleaved to release proBMP10, an inactive precursor protein (amino acids 22 to 424 of human preproBMP10). proBMP10 is cleaved by a protease to produce a 108-aa non-glycosylated C-terminal peptide (~14 kDa; BMP10, amino acids 317 to 424) and a ~50 kDa N-terminal pre-segment (amino acids 22 to 424, Susan-Resiga et al., J Biol Chem. 2011 Jul 1; 286(26):22785-94). The N-terminal pre-segments of mature BMP10 and BMP-10 remain structurally similar, forming homodimers or heterodimers of BMP10, or combining with other BMP family proteins (Yadin et al., CYTOGFR 2016, 27(2016)13–34). Dimerization occurs through the formation of Cys-Cys bridges or strong adhesion between the C-terminal peptides of the two binding partners. This results in an architecture consisting of two subunits.

[0009] US 8,287,868 discloses an isolated monoclonal antibody that binds to a mature humanized or fully human antibody peptide BMP10 and competes with the BMP10 precursor for binding to mature BMP10. Other antibodies against BMP10 or its precursors are disclosed in US 5,932,216.

[0010] It has been shown that BMP10 plays a role in cardiovascular development, including cardiomyocyte proliferation and heart size regulation, ductus arteriosus closure, angiogenesis, and ventricular trabeculae formation.

[0011] Soluble BMP10, which is involved in the regulation of tissue repair, has been identified as a diagnostic and therapeutic target for cardiovascular disease and tissue fibrosis (see, for example, US2013209490), and the involvement of BMP10 in vascular fibrosis and cardiac fibrosis has been described.

[0012] US 2012 / 0213782 discloses that BMP10 precursor peptide can be used to treat heart disease.

[0013] The general role of BMP10 is in the developmental regulation of vascular remodeling (Ricard et al., Blood. 2012 Jun 21; 119(25):6162–6171). Furthermore, BMP10 is a cardiac development factor (Huang et al., J Clin Invest. 2012; 122(10):3678–3691) and induces cardiomyocyte proliferation during myocardial infarction (Sun et al., J Cell Biochem. 2014; 115(11):1868–1876). It has also been described as originating from endothelial cells (Jiang et al., JBC 2016, 291(6):2954–2966).

[0014] Transcriptomic analysis showed that BMP10 mRNA was strongly expressed in the right atrium and right atrial appendage of the heart in healthy individuals. Compared with the left atrial appendage, it was mainly expressed on the right side (Kahr et al., Plos ONE, 2010, 6(10):e26389).

[0015] During the ESC (European Society of Cardiology) meeting held in Paris from August 29 to September 2, 2019, Larissa Fabritz gave a presentation on biomarkers of atrial fibrillation. One of the biomarkers mentioned was BMP (FP number: 2365).

[0016] International patent application PCT / EP2019 / 072042 discloses circulating BMP10 (bone morphogenetic protein 10) for assessing atrial fibrillation.

[0017] Reliable methods are needed to assess atrial fibrillation, including its diagnosis, risk stratification (such as stroke) in patients with atrial fibrillation, assessment of its severity, and evaluation of treatment for patients with atrial fibrillation. Furthermore, reliable assessment of heart failure is also required.

[0018] Tillet et al. (J. Biol. Chem. (2018) 293(28) 10963–10974) found that heterodimers of BMP9 and BMP10 are responsible for most of the biological BMP activity found in plasma. However, Tillet et al. found low levels of BMP10 in plasma, indicating the presence of a masking protein in plasma.

[0019] The technical problem of this invention can be viewed as providing a method to satisfy the above-mentioned needs. This technical problem is solved by the claims and the embodiments characterized below.

[0020] Advantageously, in the context of this invention, it has been found that determining the amount of one or more BMP10-type peptides in samples from subjects allows for improved assessment of atrial fibrillation and heart failure. Therefore, it can, for example, diagnose whether a subject has atrial fibrillation or heart failure, whether they are at risk of stroke associated with atrial fibrillation, or whether they are at risk of recurrent Afib after a treatment intervention.

[0021] Furthermore, the study described in this article showed that the amount of one or more BMP10-type peptides was associated with the presence of white matter lesions (WML) in patients. Since the degree of WML can be caused by clinically resting stroke (Wang Y, Liu G, Hong D, Chen F, Ji X, Cao G. White matter injury in ischemic stroke. Prog Neurobiol. 2016; 141:45–60), BMP10-type peptides can be used to assess the degree of white matter lesions and whether a subject has experienced one or more resting strokes in the past, i.e., clinically resting strokes. Because WML is associated with a predictive risk of dementia, one or more BMP10-type peptides may also be used to predict dementia, such as vascular dementia and / or Alzheimer's disease.

[0022] Advantageously, the study described herein found that detecting BMP10-type peptides in blood, serum, or plasma samples is optimal when using antibodies targeting amino acid regions 22 to 316 of human preproBMP10 (i.e., the N-terminal pre-segment of BMP10) compared to using antibodies targeting the mature BMP10 hormone itself. Therefore, using an assay that binds to amino acid regions 22 to 316 of human preproBMP10, rather than binding to mature BMP10, allows for improved assessment of atrial fibrillation and heart failure. Furthermore, the inventors have identified subregions within amino acid regions 22 to 316 of human preproBMP10 that are particularly suitable target regions for assays. In this case, antibodies that allow for improved detection of BMP10-type peptides were identified. These antibodies are capable of binding to NT-proBMP10 and any BMP10-type peptide containing NT-proBMP10 fragments such as preproBMP10 and proBMP10. Summary of the Invention

[0023] This invention relates to a method for assessing atrial fibrillation in a subject, the method comprising the following steps:

[0024] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0025] b) Atrial fibrillation is assessed by comparing the amount of one or more BMP10-type peptides with a reference amount of one or more BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with a reference amount of at least one other biomarker.

[0026] The present invention further relates to a method for assisting in the assessment of atrial fibrillation, the method comprising the following steps:

[0027] a) Provide at least one sample from the subject.

[0028] b) In at least one sample provided in step a), determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides), and optionally, determine the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP3 (fatty acid binding protein 3), and

[0029] c) Provide physicians with information about the amount of one or more identified BMP10-type peptides and optionally about the amount of at least one other identified biomarker to aid in the assessment of atrial fibrillation.

[0030] Furthermore, the present invention envisions a method for assisting in the assessment of atrial fibrillation, the method comprising:

[0031] a) Provides the assay of one or more BMP10-type peptides and optionally at least one additional assay of other biomarkers selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 and FABP3 (fatty acid-binding protein 3), and

[0032] b) Provide instructions on the use of the results of the measurements obtained or available through the aforementioned assays in the assessment of atrial fibrillation.

[0033] Furthermore, the present invention relates to a method for assessing the degree of white matter lesions in a subject, the method comprising:

[0034] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0035] b) Assess the degree of white matter lesions in the subject based on the quantity determined in step a).

[0036] Furthermore, the present invention relates to a method for assessing whether a subject has experienced one or more resting strokes, the method comprising:

[0037] a) Determine the amount of one or more BMP10-type peptides in samples from subjects.

[0038] b) Compare the quantities determined in step a) with the reference, and

[0039] c) Assess whether the subject has experienced one or more resting strokes.

[0040] Furthermore, the present invention relates to a method for predicting dementia, such as vascular dementia and / or Alzheimer's disease, in a subject, the method comprising:

[0041] a) Determine the amount of one or more BMP10-type peptides in samples from subjects.

[0042] b) Compare the quantities determined in step a) with the reference, and

[0043] c) Predict the risk of the subject developing dementia.

[0044] The present invention also considers a method for predicting the risk of AFib recurrence after a therapeutic intervention (such as pulmonary vein isolation (PVI) or ablation therapy in atrial fibrillation) in samples collected prior to a therapeutic intervention, comprising:

[0045] a) Provides the assay of one or more BMP10-type peptides and optionally at least one additional assay of other biomarkers selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 and FABP3 (fatty acid-binding protein 3), and

[0046] b) Provide a description of the use of test results obtained or available through one or more of the aforementioned assays in assessing the risk of recurrence of atrial fibrillation.

[0047] This invention also covers a computer-implemented method for assessing atrial fibrillation, the method comprising:

[0048] a) Receiving at the processing unit a value for the amount of one or more BMP10-type peptides, and optionally receiving at least one additional value for the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP3 (fatty acid-binding protein 3), wherein the amount of the one or more BMP10-type peptides and optionally the amount of at least one other biomarker have been determined in a sample from the subject.

[0049] b) The processing unit compares one or more values ​​received in step (a) with one or more reference values, and

[0050] c) Assess atrial fibrillation based on the comparison step b).

[0051] The present invention further relates to a method for diagnosing heart failure, the method comprising the following steps:

[0052] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0053] (b) Diagnose heart failure by comparing the amount of one or more BMP10-type peptides with a reference amount of BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with a reference amount of at least one other biomarker.

[0054] The present invention also relates to a method for predicting the risk of hospitalization for heart failure in a subject, the method comprising the following steps:

[0055] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 and FABP3 (fatty acid binding protein 3) in at least one sample from a subject.

[0056] (b) Comparing the amount of one or more BMP10-type peptides to a reference amount, and optionally comparing the amount of at least one other biomarker to a reference amount of said at least one other biomarker, and

[0057] (c) Predict the risk of hospitalization for heart failure in subjects.

[0058] In a preferred embodiment of the method of the present invention, determining the amount of one or more BMP10-type peptides includes contacting the sample with at least one reagent that binds (i.e., is capable of binding) the N-terminal pre-domain of BMP10 (NT-proBMP10, sometimes also referred to as the N-terminal pre-domain of BMP10). Therefore, it should not bind mature BMP10. Thus, the reagent binds to amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1 (i.e., is capable of binding). For example, the sample is contacted with at least one reagent that binds to amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO:1.

[0059] The present invention also relates to a method for determining the amount of one or more BMP10-type peptides, comprising the step of contacting a sample containing one or more BMP10-type peptides with at least one reagent that binds to the N-terminal pre-segment of BMP10, thus being located within amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1, thereby allowing the formation of a complex of the BMP10-type peptide and at least one reagent, and determining the amount of the formed complex.

[0060] In some embodiments, sandwich immunologic assay is used to determine the amount of one or more BMP10-type peptides.

[0061] The present invention further relates to a kit comprising at least one reagent that specifically binds to one or more BMP10-type peptides, such as a reagent that binds to amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1, and at least one other reagent selected from the group consisting of: a reagent that specifically binds to natriuretic peptides, a reagent that specifically binds to ESM-1, a reagent that specifically binds to Ang2, and a reagent that specifically binds to FABP3.

[0062] In addition, the present invention relates to the following in vitro uses:

[0063] i) one or more BMP10-type peptides and optionally at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 and FABP3 (fatty acid binding protein 3), and / or

[0064] ii) at least one reagent that specifically binds to one or more BMP10-type peptides, and optionally at least one additional reagent selected from the group consisting of: reagents that specifically bind to natriuretic peptides, reagents that specifically bind to ESM-1, reagents that specifically bind to Ang2, and reagents that specifically bind to FABP3.

[0065] It can be used to assess atrial fibrillation, predict the risk of stroke, diagnose heart failure, or predict the risk of hospitalization for heart failure.

[0066] In a preferred embodiment of the above-described uses, at least one reagent that specifically binds to one or more BMP10-type peptides is a reagent that binds to NT-proBMP10, i.e., a reagent that binds to amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1. The amino acid sequence of NT-proBMP10 is shown in SEQ ID NO:6.

[0067] The present invention further provides reagents, such as antibodies or antigen-binding fragments thereof, that bind to amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1 (i.e., are capable of binding). In some embodiments, the antibody is a monoclonal antibody.

[0068] In some embodiments, the reagent is an epitope (SLFGDVFSEQD, SEQ ID NO 2) contained in amino acid regions 37 to 47 of the polypeptide shown in SEQ ID NO:1.

[0069] In some embodiments, the reagent is an epitope (LESKGDNEGERNMLV, SEQ ID NO:3) contained in amino acid regions 171 to 185 of SEQ ID NO:1, such as an epitope (SKGDNEGER, SEQ ID NO:4) contained in amino acid regions 173 to 181 of SEQ ID NO:1.

[0070] In some embodiments, the reagent is a reagent that binds to an epitope (SSGPGEEAL, SEQ ID NO:5) contained in amino acid regions 291 to 299 of SEQ ID NO:1.

[0071] The present invention also relates to an antibody (such as a monoclonal antibody) or a fragment thereof that binds one or more BMP10-type peptides.

[0072] In one embodiment, the antibody or a fragment thereof comprises a heavy chain variable domain and / or a light chain variable domain, wherein the heavy chain variable domain is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to the heavy chain variable domain comprising the sequence shown in SEQ ID NO: 7, 8, 9, 10, 11, 12, 13, 14, or 15 (see Table A), and the light chain variable domain is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to the light chain variable domain comprising the sequence shown in SEQ ID NO: 16, 17, 18, 19, 20, 21, 22, 23, or 24 (see Table B) in ascending priority order.

[0073] Alternatively or concurrently, the antibody or fragment thereof of the present invention comprises

[0074] (a) A light chain variable structural domain, which includes:

[0075] (a1) The light chain CDR1 shown in Table D (and therefore the light chain CDR1 sequence selected from SEQ ID NO:34-42),

[0076] (a2) The light chain CDR2 shown in Table D (and therefore the light chain CDR2 sequences selected from SEQ ID NO:52-60), and

[0077] (a3) The light chain CDR3 shown in Table D (and therefore the light chain CDR3 sequence selected from SEQ ID NO:70-78),

[0078] as well as

[0079] (b) Heavy-chain variable structural domains, which include:

[0080] (b1) The heavy chain CDR1 shown in Table C (and therefore the heavy chain CDR1 sequence selected from SEQ ID NO:25-33),

[0081] (b2) The heavy chain CDR2 shown in Table C (and therefore the heavy chain CDR2 sequences selected from SEQ ID NO:43-51), and

[0082] (b3) The heavy chain CDR3 shown in Table C (and therefore the heavy chain CDR3 sequence selected from SEQ ID NO:61-69).

[0083] Detailed Implementation Methods / Definitions

[0084] This invention relates to a method for assessing atrial fibrillation in a subject, the method comprising the following steps:

[0085] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein type 10-peptides) in at least one sample from a subject, and

[0086] b) The amount of BMP10-type peptide was compared with the reference amount of BMP10-type peptide to assess atrial fibrillation.

[0087] The BMP10-type peptide is preferably selected from the group consisting of: BMP10, the N-terminal pre-terminal region of BMP10 (N-terminal proBMP10), proBMP10, and preproBMP10. More preferably, the BMP10-type peptide is selected from the group consisting of: the N-terminal pre-terminal region of BMP10 (N-terminal proBMP10), proBMP10, and preproBMP10. Even more preferably, the BMP10-type peptide is proBMP10 and / or N-terminal proBMP10. Most preferably, the BMP10-type peptide is NT-proBMP10.

[0088] According to the present invention, the amount of one or more BMP10-type peptides should be determined. As described elsewhere herein, it is preferred to use at least one reagent that binds to NT-proBMP10 or a specific subregion thereof for determination. Therefore, the amount (i.e., combination) of all BMP10-type peptides (such as proBMP10, preproBMP10, and NT-proBMP10) containing the NT-proBMP10 peptide sequence can be determined. Therefore, the statement "determining the amount of one or more BMP10-type peptides" preferably refers to determining the combined amount (i.e., the sum of amounts) of polypeptides having an amino acid sequence containing the NT-proBMP10 amino acid sequence, particularly determining the combined amount (i.e., the sum of amounts) of proBMP10, preproBMP10, and NT-proBMP10. Since preproBMP10 is not present in many samples in principle, this statement may also refer to determining the sum of NT-proBMP10 and proBMP10. Therefore, the amount of NT-proBMP10 and / or BMP10 is determined.

[0089] In one embodiment of the method of the present invention, the method further includes determining, in step a), the amount of at least one other biomarker selected from the group consisting of natriuretic peptide, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP-3 (fatty acid binding protein 3) in a sample from a subject, and comparing the amount of at least one other biomarker with a reference amount in step b).

[0090] Therefore, the present invention relates to a method for assessing atrial fibrillation in a subject, the method comprising the following steps:

[0091] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0092] b) Atrial fibrillation is assessed by comparing the amount of one or more BMP10-type peptides with a reference amount of BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with a reference amount of said at least one other biomarker.

[0093] The assessment of atrial fibrillation (AF) should be based on the results of comparison step b).

[0094] Therefore, the present invention preferably includes the following steps:

[0095] a) Determine the amount of one or more BMP10-type peptides and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid binding protein 3) in at least one sample from a subject.

[0096] b) Compare the amount of one or more BMP10-type peptides to a reference amount of one or more BMP10-type peptides, and optionally compare the amount of at least one other biomarker to a reference amount of said at least one other biomarker, and

[0097] c) Assess atrial fibrillation based on the results of comparison step b).

[0098] The method according to the invention comprises a method essentially consisting of the steps described above or a method including other steps. Furthermore, the method of the invention is preferably an ex vivo method, more preferably an in vitro method. It may also include steps other than those explicitly mentioned above. For example, other steps may involve determining other biomarkers and / or sample pretreatment or evaluating the results obtained by the method. The method can be performed manually or with automation assistance. Preferably, steps (a), (b), and / or (c) can be wholly or partially automated, for example, by means of suitable robots and sensory devices for the determination in step (a) or the calculation in step (b) performed by a computer.

[0099] According to the present invention, atrial fibrillation should be assessed. As used herein, the term "assessment of atrial fibrillation" preferably refers to the diagnosis of atrial fibrillation, the diagnosis of a recent onset of AF, the differentiation between paroxysmal and persistent atrial fibrillation, the prediction of the risk of adverse events associated with atrial fibrillation (such as stroke and / or recurrence of atrial fibrillation, such as recurrence of AF after intervention), the identification of subjects to be subjected to electrocardiography (ECG), or the assessment of treatment for atrial fibrillation.

[0100] As those skilled in the art will understand, the assessments of this invention are not generally intended to be correct for 100% of the subjects tested. This term preferably requires the ability to correctly assess the statistically significant portion of the subjects (such as the diagnosis, differentiation, prediction, identification, or assessment of treatments described herein). Whether a portion is statistically significant can be determined by those skilled in the art using various well-known statistical assessment tools (e.g., determining confidence intervals, p-value determination, Student's t-test, Mann-Whitney test, etc.) without further effort. See Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983 for details. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98%, or at least 99%. Preferred p-values ​​are 0.4, 0.1, 0.05, 0.01, 0.005, or 0.0001.

[0101] According to the present invention, the phrase "assessment of atrial fibrillation" is understood as an aid to the assessment of atrial fibrillation, and therefore as an aid to the diagnosis of atrial fibrillation, to differentiating between paroxysmal and persistent atrial fibrillation, to predicting the risk of adverse events associated with atrial fibrillation, to identifying subjects who should undergo electrocardiography (ECG), or as an aid to assessing the treatment of atrial fibrillation. In principle, the final diagnosis will be made by a physician.

[0102] In a preferred embodiment of the invention, the assessment of atrial fibrillation is a diagnosis of atrial fibrillation. Therefore, it is used to diagnose whether a subject has atrial fibrillation.

[0103] Therefore, the present invention envisions a method for diagnosing atrial fibrillation in a subject, the method comprising the following steps:

[0104] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0105] b) Atrial fibrillation can be diagnosed by comparing the amount of one or more BMP10-type peptides with a reference amount.

[0106] In one embodiment, the aforementioned method includes the following steps:

[0107] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10 peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid binding protein 3) in at least one sample from a subject, and

[0108] (b) Atrial fibrillation is diagnosed by comparing the amount of one or more BMP10-type peptides with a reference amount of one or more BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with a reference amount of said at least one other biomarker.

[0109] Preferably, the subject of the method for diagnosing atrial fibrillation is a subject suspected of having atrial fibrillation. However, it is also envisioned that the subject has previously been diagnosed with AF, and the previous diagnosis is confirmed by implementing the method of the present invention.

[0110] In another preferred embodiment of the invention, the assessment of atrial fibrillation involves distinguishing between paroxysmal and persistent atrial fibrillation. Therefore, it is determined whether the subject has paroxysmal or persistent atrial fibrillation.

[0111] Therefore, the present invention envisions a method for distinguishing between paroxysmal atrial fibrillation and persistent atrial fibrillation in a subject, the method comprising the following steps:

[0112] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0113] b) Compare the amount of one or more BMP10-type peptides to a reference amount to differentiate between paroxysmal atrial fibrillation and persistent atrial fibrillation.

[0114] In one embodiment, the aforementioned method includes the following steps:

[0115] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10 peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0116] b) Compare the amount of one or more BMP10-type peptides to a reference amount of one or more BMP10-type peptides, and optionally compare the amount of at least one other biomarker to a reference amount of said at least one other biomarker, thereby distinguishing between paroxysmal atrial fibrillation and persistent atrial fibrillation.

[0117] In another preferred embodiment of the invention, the assessment of atrial fibrillation is a prediction of the risk of adverse events (such as stroke) associated with atrial fibrillation. Therefore, the risk of the subject having and / or not having said adverse events is predicted.

[0118] Therefore, the present invention envisions a method for predicting the risk of adverse events associated with atrial fibrillation in subjects, the method comprising the following steps:

[0119] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0120] b) Compare the amount of one or more BMP10-type peptides to a reference level to predict the risk of adverse events associated with atrial fibrillation.

[0121] In one embodiment, the aforementioned method includes the following steps:

[0122] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10 peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0123] b) Compare the amount of one or more BMP10-type peptides to a reference amount of one or more BMP10-type peptides, and optionally compare the amount of at least one other biomarker to a reference amount of said at least one other biomarker, thereby predicting the risk of adverse events associated with atrial fibrillation.

[0124] Imagine that various adverse events can be predicted. The preferred adverse event to predict is stroke.

[0125] Therefore, the present invention specifically envisions a method for predicting the risk of stroke in a subject, the method comprising the following steps:

[0126] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0127] b) Compare the amount of one or more BMP10-type peptides to a reference amount to predict the risk of stroke.

[0128] The aforementioned method may further include step c) predicting stroke based on the comparison results of step b). Therefore, steps a), b), and c) are preferably as follows:

[0129] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0130] b) Compare the amounts of one or more BMP10-type peptides to reference amounts, and

[0131] c) Predict stroke based on the comparison results of step b).

[0132] In another preferred embodiment of the invention, the assessment of atrial fibrillation is the assessment of the treatment of atrial fibrillation.

[0133] Therefore, the present invention envisions a method for assessing the treatment of atrial fibrillation in a subject, the method comprising the following steps:

[0134] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0135] b) The treatment of atrial fibrillation is assessed by comparing the amount of one or more BMP10-type peptides with a reference amount.

[0136] In one embodiment, the aforementioned method includes the following steps:

[0137] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptide, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0138] b) Therapies for atrial fibrillation are evaluated by comparing the amount of one or more BMP10-type peptides with reference amounts of one or more BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with reference amounts of said at least one other biomarker.

[0139] Preferably, the subjects associated with the aforementioned distinction, prediction, and assessment of atrial fibrillation treatment are those who have atrial fibrillation, particularly those who are known to have atrial fibrillation (and therefore have a known history of atrial fibrillation). However, for the aforementioned prediction method, it is also assumed that the subjects do not have a known history of atrial fibrillation.

[0140] In another preferred embodiment of the invention, the assessment of atrial fibrillation involves identifying subjects who should undergo an electrocardiogram (ECG) examination. Therefore, it involves identifying whether or not a subject should undergo an ECG examination.

[0141] The method may include the following steps:

[0142] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptide, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0143] b) The amount of one or more BMP10-type peptides is compared with a reference amount of one or more BMP10-type peptides, and optionally the amount of at least one other biomarker is compared with a reference amount of said at least one other biomarker, thereby identifying subjects who should undergo electrocardiography.

[0144] Preferably, the subjects relevant to the above-described method for identifying subjects who should undergo electrocardiogram (ECG) testing are subjects without a known history of atrial fibrillation. The expression "without a known history of atrial fibrillation" is defined elsewhere in this document.

[0145] In another preferred embodiment of the invention, the assessment of atrial fibrillation is an assessment of the efficacy of the subject's anticoagulation therapy. Therefore, the efficacy of the treatment is assessed.

[0146] In another preferred embodiment of the invention, the assessment of atrial fibrillation is a prediction of the subject's risk of stroke. Therefore, it predicts whether the subject referred to herein is at risk of stroke.

[0147] In another preferred embodiment of the invention, the assessment of atrial fibrillation involves determining whether the subject is suitable for administration of at least one anticoagulant or for an increase in the dose of at least one anticoagulant. Therefore, the assessment determines whether the subject is suitable for the administration and / or the dose increase.

[0148] In another preferred embodiment of the invention, the assessment of atrial fibrillation is the monitoring of anticoagulation therapy. Therefore, it is an assessment of whether the subject is responding to the treatment.

[0149] The term "atrial fibrillation" (abbreviated as "AF" or "AFib") is well known in the art. As used herein, the term preferably refers to a supraventricular rapid arrhythmia characterized by uncoordinated activation of the atria and consequent deterioration of atrial mechanical function. In particular, the term refers to an abnormal heart rhythm characterized by rapid and irregular beating. It involves the two upper chambers of the heart. In a normal heart rhythm, impulses generated by the sinoatrial node propagate through the heart and cause myocardial contraction and blood pumping. In atrial fibrillation, the regular electrical impulses of the sinoatrial node are replaced by disorganized, rapid electrical impulses that result in an irregular heartbeat. Symptoms of atrial fibrillation include palpitations, syncope, shortness of breath, or chest pain. However, most episodes are asymptomatic. On an electrocardiogram, atrial fibrillation is characterized by the replacement of consistent P waves with rapid oscillations or thrills that vary in amplitude, shape, and timing, which are associated with irregular, frequent, rapid ventricular responses when atrioventricular conduction is intact.

[0150] The American College of Cardiology (ACC), the American Heart Association (AHA), and the European Society of Cardiology (ESC) have proposed the following classification system (see Fuster V. et al., Circulation 2006; 114(7):e257–354, the entire contents of which are incorporated herein by reference, see, for example, the document). Figure 3 ): First detection of AF, intermittent AF, persistent AF and permanent AF.

[0151] All individuals with atrial fibrillation (AF) initially fall into the category referred to as newly detected AF. However, the subject may or may not have previously undetected episodes. If AF persists for more than a year, particularly if sinus rhythm recovery does not occur (or only occurs with medical intervention), the subject has permanent AF. If AF persists for more than 7 days, the subject has persistent AF. The subject may require pharmacological or electrical intervention to terminate the atrial fibrillation. Preferably, persistent AF occurs during an episode, but the arrhythmia does not spontaneously (i.e., without medical intervention) return to sinus rhythm. Paroxysmal atrial fibrillation preferably refers to intermittent atrial fibrillation episodes lasting up to 7 days. In most cases of paroxysmal AF, episodes last less than 24 hours. Atrial fibrillation episodes terminate spontaneously, i.e., without medical intervention. Therefore, while episodes of paroxysmal atrial fibrillation preferably terminate spontaneously, persistent atrial fibrillation preferably does not terminate spontaneously. Preferably, persistent atrial fibrillation requires termination by electrical or pharmacological cardioversion, or by other procedures such as ablation (Fuster V. et al., Circulation 2006; 114(7):e257–354). Both persistent and paroxysmal atrial fibrillation (AF) can recur; therefore, paroxysmal and persistent AF are distinguished by ECG recordings: AF is considered recurrent when the patient has experienced two or more episodes. AF, especially recurrent AF, is designated as paroxysmal if the arrhythmia terminates spontaneously. AF is designated as persistent if it lasts longer than 7 days.

[0152] In a preferred embodiment of the invention, the term "paroxysmal atrial fibrillation" is defined as a spontaneously terminated AF episode lasting less than 24 hours. In an alternative embodiment, a spontaneously terminated episode lasts up to 7 days.

[0153] The term "subject" as used herein is preferably a mammal. Mammals include, but are not limited to, domesticated animals (e.g., cattle, sheep, cats, dogs, and horses), primates (e.g., human and non-human primates, such as monkeys), rabbits, and rodents (e.g., mice and rats). Preferably, the subject is a human subject.

[0154] Preferably, the test subject is of any age; more preferably, the test subject is 50 years of age or older; even more preferably, 60 years of age or older; and most preferably, 65 years of age or older. Further, it is envisioned that the test subject is 70 years of age or older.

[0155] Furthermore, the subjects are assumed to be 75 years of age or older. Similarly, the subjects may be between 50 and 90 years old.

[0156] In a preferred embodiment of the method for assessing atrial fibrillation, the subject should have atrial fibrillation. Therefore, the subject should have a known history of atrial fibrillation. Thus, prior to obtaining the test sample, the subject should have experienced an atrial fibrillation episode, and at least one of the previous atrial fibrillation episodes should have been diagnosed, for example, by ECG. For instance, it is conceivable that the assessment of atrial fibrillation is to differentiate between paroxysmal and persistent atrial fibrillation, or if the assessment is to predict the risk of adverse events associated with atrial fibrillation, or if the assessment is to evaluate the treatment of atrial fibrillation, then the subject has atrial fibrillation.

[0157] In another preferred embodiment of the method for assessing atrial fibrillation, for example, if the assessment of atrial fibrillation is to diagnose atrial fibrillation or to identify subjects who should undergo an electrocardiogram (ECG) examination, then the subject to be tested is suspected of having atrial fibrillation.

[0158] Preferably, the subject suspected of having atrial fibrillation is one who has exhibited at least one symptom of atrial fibrillation prior to the implementation of the methods used to assess atrial fibrillation. These symptoms are typically transient, may appear within seconds, and may disappear quickly. Symptoms of atrial fibrillation include dizziness, fainting, shortness of breath, and especially palpitations. Preferably, the subject has exhibited at least one symptom of atrial fibrillation within six months prior to obtaining the sample.

[0159] Alternatively or otherwise, subjects suspected of having atrial fibrillation should be 70 years of age or older.

[0160] Preferably, subjects suspected of having atrial fibrillation should have no known history of atrial fibrillation.

[0161] According to the present invention, subjects without a known history of atrial fibrillation are preferably subjects who have not been previously diagnosed with atrial fibrillation, i.e., before implementing the method of the present invention (especially before obtaining samples from the subject). However, the subject may have already had or may not have had previously undiagnosed episodes of atrial fibrillation.

[0162] Preferably, the term "atrial fibrillation" refers to all types of atrial fibrillation. Therefore, the term preferably covers paroxysmal atrial fibrillation, persistent atrial fibrillation, or permanent atrial fibrillation.

[0163] However, in one embodiment of the invention, the subject of the test did not have permanent atrial fibrillation. In this embodiment, the term "atrial fibrillation" refers only to paroxysmal and persistent atrial fibrillation.

[0164] However, in another embodiment of the invention, the subject does not suffer from paroxysmal and permanent atrial fibrillation. In this embodiment, the term "atrial fibrillation" refers only to persistent atrial fibrillation.

[0165] When the sample is obtained, the subject may or may not have experienced an atrial fibrillation episode. Therefore, in a preferred embodiment for assessing atrial fibrillation (such as in the diagnosis of atrial fibrillation), the subject has not experienced an atrial fibrillation episode when the sample is obtained. In this embodiment, the subject should have a normal sinus rhythm (and therefore should be in sinus rhythm) when the sample is obtained. Thus, atrial fibrillation can be diagnosed using biomarkers even when there is (temporarily) no atrial fibrillation on the ECG. According to the method of the invention, an elevation of the biomarker described herein should be retained after an atrial fibrillation episode, thereby providing a diagnosis for the subject with atrial fibrillation (“memory effect”). Preferably, AF is diagnosed within approximately three days, approximately one week, approximately one month, approximately three months, or approximately six months after implementing the method of the invention (or more precisely, after obtaining the sample). In a preferred embodiment, it is feasible to diagnose atrial fibrillation within approximately six months after an episode. Therefore, the assessment of atrial fibrillation as mentioned herein, particularly the diagnosis, risk prediction, or differentiation related to the assessment of atrial fibrillation as mentioned herein, is preferably performed approximately three days after the last episode of atrial fibrillation, more preferably approximately one month after, even more preferably approximately three months after, and most preferably approximately six months after. Therefore, it is envisioned that the test sample is preferably obtained approximately three days after the last episode of atrial fibrillation, more preferably approximately one month after, even more preferably approximately three months after, and most preferably approximately six months after. Therefore, the diagnosis of atrial fibrillation preferably also includes the diagnosis of atrial fibrillation episodes, which preferably occurred within approximately three days, more preferably within approximately one week, even more preferably within approximately three months after, and most preferably within approximately six months before obtaining the sample. Therefore, the present invention allows for the diagnosis of recent episodes of AF, such as episodes that occurred within approximately three days, or more preferably within approximately one week, before implementing the method of the present invention (or more precisely, before obtaining the test sample). Furthermore, a recent episode of AF may have occurred approximately two weeks before implementing the method of the present invention.

[0166] Therefore, this invention allows for the aiding diagnosis of a recent episode of atrial fibrillation in a subject with sinus rhythm, including determining the amount of one or more BMP10-peptides (and optionally, at least one other biomarker as described elsewhere herein) and comparing the thus determined amount (or quantity) with a reference amount (or quantity), thereby aiding in the diagnosis of a recent episode of AF. In one embodiment, the subject should be suspected of having recently experienced an episode of AF, for example, the subject could be a subject who has recently exhibited symptoms of AF (such as within three days, one week, or two weeks prior to implementing the method of this invention). Symptoms of atrial fibrillation include palpitations, syncope, shortness of breath, or chest pain.

[0167] However, it is also envisioned that when samples are obtained (e.g., regarding predictions of stroke), subjects experience episodes of atrial fibrillation.

[0168] The term "sample" refers to a body fluid sample, an isolated cell sample, or a sample from a tissue or organ. Body fluid samples can be obtained using well-known techniques and include samples of blood, plasma, serum, urine, lymph, sputum, ascites, or any other bodily secretions or derivatives thereof. Tissue or organ samples can be obtained from any tissue or organ, for example, through a biopsy. Isolated cells can be obtained from body fluids, tissues, or organs using separation techniques such as centrifugation or cell sorting. For example, cell, tissue, or organ samples can be obtained from those cells, tissues, or organs that express or produce biomarkers. Samples can be frozen, fresh, fixed (e.g., formalin fixation), centrifuged, and / or embedded (e.g., paraffin embedding), etc. Cell samples can, of course, be subjected to a variety of well-known post-collection preparation and storage techniques (e.g., nucleic acid and / or protein extraction, fixation, storage, freezing, ultrafiltration, concentration, evaporation, centrifugation, etc.) before assessing the amount of one or more biomarkers in a sample.

[0169] In a preferred embodiment of the invention, the sample is a blood (i.e., whole blood), serum, or plasma sample. Serum is the liquid fraction of whole blood obtained after clotting. To obtain serum, blood clots are removed by centrifugation and the supernatant is collected. Plasma is the cell-free fluid fraction of blood. To obtain a plasma sample, whole blood is collected in anticoagulant-treated tubes (e.g., citrate-treated or EDTA-treated tubes). Cells are removed from the sample by centrifugation, and the supernatant (i.e., the plasma sample) is obtained.

[0170] As mentioned above, the subject may be in sinus rhythm or may have an AF rhythm episode when the sample is obtained.

[0171] BMP10-type peptides are well known in the art. Preferred BMP10-type peptides are disclosed, for example, by Susan-Resiga et al. (J Biol Chem. 2011 Jul 1; 286(26):22785-94), which is incorporated herein by reference in its entirety (see, for example, Susan-Resiga et al.). Figure 3 A, or US2012 / 0213782).

[0172] In one embodiment, the BMP10-type peptide is unprocessed preproBMP10 (see SEQ ID NO:1 below). In another embodiment, the BMP10-type peptide is the propeptide proBMP10. This marker includes an N-terminal pre-terminal region and BMP10. In yet another embodiment, the BMP10-type peptide is the N-terminal pre-terminal region of BMP10 (N-terminal proBMP10, or NT-proBMP10).

[0173] In one embodiment, the BMP10-type peptide is part of a homodimer or heterodimer complex.

[0174] Human preproBMP10 (i.e., unprocessed preproBMP10) is 424 amino acids in length. The amino acid sequence of human preproBMP10 is shown, for example, in SEQ ID NO:1 or US2012 / 0213782. Figure 3 The above is incorporated herein by reference in its entirety. Furthermore, the amino acid sequence of preproBMP10 can be determined using Uniprot (see sequence under accession number O95393-1).

[0175] Furthermore, the amino acid sequence of human preproBMP10 is shown below in this article (SEQ ID NO:1):

[0176]

[0177] Human preproBMP10 comprises a short signal peptide (amino acids 1 to 21), which is enzymatically cleaved to release proBMP10 (in the above sequence, the signal peptide is represented in italics). Therefore, human proBMP10 comprises amino acids 22 to 424 of human preproBMP10 (i.e., the polypeptide having the sequence shown in SEQ ID NO 1). Human proBMP10 is further cleaved into BMP10 and the N-terminal pre-terminal region of the active form (non-glycosylated) BMP10. The N-terminal pre-terminal region of BMP10 comprises amino acids 22 to 316 of the polypeptide having the sequence shown in SEQ ID NO 1 (i.e., human preproBMP10). The sequence of NT-proBMP10 is represented in the above sequence as follows: underline Wire Therefore, NT-proBMP10 has the following sequence (SEQ ID: 6):

[0178] SPIMNLEQSPLEEDMSLFGDVFSEQDGVDFNTLLQSMKDEFLKTLNLSDIPTQDSAKVDPPEYMLELYN KFATDRTMSMPSANIIRSFKNEDLFSQPVSFNGLRKYPLLFNVSIPHHEEVIMAELRLYTLVQRDRMIYDGVDRKITI FEVLESKGDNEGERNMLVLVSGEIYGTNSEWETFDVTDAIRRWQKSGSSTHQLEVHIESKHDEAEDASSGRLEIDTS AQNKHNPLLIVFSDDQSSDKERKEELNEMISHEQLPELDNGLDSFSSGPGEEALLQMRSNIIYDSTARIRR

[0179] BMP10 contains amino acids 317 to 424 of a polypeptide having the sequence shown in SEQ ID NO 1 (in bold in the above sequence).

[0180] Preferred BMP10-type peptides are proBMP10 and N-terminal proBMP10. After proBMP10 cleavage, BMP10 and N-terminal proBMP10 remain structurally close, forming homodimers or heterodimers of BMP10, or combining with other BMP family proteins (Yadin et al., CYTOGFR 2016, 27(2016) 13–34). Dimerization occurs through the formation of Cys-Cys bridges or strong adhesion between the C-terminal peptides of the two binding partners. Thus, an architecture consisting of two subunits is formed.

[0181] Preferably, the amount of BMP10-type peptide is determined by using at least one reagent that specifically binds to the BMP10-type peptide (such as one or more antibodies (or antigen-binding fragments thereof) that specifically bind to the BMP10-type peptide).

[0182] As described above, the basic research of this invention has found that BMP10-type peptides are better detected when antibodies targeting amino acid regions 22 to 316 of human preproBMP10 are used, compared to antibodies targeting the mature BMP10 hormone itself.

[0183] Therefore, it is particularly considered to determine the amount of one or more BMP10-type peptides by using at least one reagent that binds to the N-terminal pre-segment of BMP10 and thus to amino acid regions 22 to 316 of SEQ ID NO:1 (i.e., that binds to amino acid regions 22 to 316 of a polypeptide having the amino acid sequence shown in SEQ ID NO:1). Thus, the reagent should bind to epitopes contained in that region, such as those described elsewhere herein or shown in the table of Example 12.

[0184] SEQ ID NO:1 is the sequence of human preproBMP10. This sequence is used as a reference sequence herein. It is stated herein that the reagent should bind to certain regions within a polypeptide having the sequence shown in SEQ ID NO:1, for example, amino acid regions 37 to 299 or regions 171 to 185 of SEQ ID NO:5. This means that the reagent will bind to regions in the BMP10 type corresponding to these regions. For example, proBMP10 and NT-proBMP10 lack the first 21 amino acids of human preproBMP10. Therefore, the reagent binds to amino acid regions 16 to 278 and regions 150 to 164 of NT-proBMP10 or proBMP10.

[0185] A subregion from amino acid 22 to 316 of SEQ ID NO:1 was identified as particularly suitable for detecting BMP10-type peptides.

[0186] In a preferred embodiment, at least one reagent (such as an antibody or a fragment thereof) that binds to the BMP10-type peptide binds to amino acid regions 37 to 299 of SEQ ID NO:1, that is, the at least one reagent binds to an epitope contained in the region of SEQ ID NO:1 starting at amino acid 37 and ending at amino acid 299.

[0187] In another preferred embodiment, at least one reagent binds to amino acid regions 110 to 200 of SEQ ID NO:1, that is, the at least one reagent binds to an epitope contained in that region.

[0188] In another preferred embodiment, the at least one reagent binds to amino acid regions 37 to 195 of SEQ ID NO:1, such as amino acid regions 37 to 185, i.e., the at least one reagent binds to an epitope contained in that region.

[0189] In another preferred embodiment, the at least one reagent binds to amino acid regions 160 to 299 of SEQ ID NO:1, such as amino acid regions 171 to 299, i.e., the at least one reagent binds to an epitope contained in that region.

[0190] In another preferred embodiment, the at least one reagent is bound to amino acid regions 160 to 195 of SEQ ID NO:1, such as amino acid regions 171 to 185.

[0191] In a further preferred embodiment, the at least one reagent binds to an epitope (SLFGDVFSEQD, SEQ ID NO: 2) contained in amino acid regions 37 to 47 of SEQ ID NO: 1. In one embodiment, the epitope of the reagent is substantially composed of SLFGDVFSEQD (SEQ ID NO: 2).

[0192] In a further preferred embodiment, the at least one reagent binds to an epitope (LESKGDNEGERNMLV, SEQ ID NO:3) contained in amino acid regions 171 to 185 of SEQ ID NO:1. For example, the at least one reagent binds to an epitope (SKGDNEGER, SEQ ID NO:4) contained in amino acid regions 173 to 181 of SEQ ID NO:1. In one embodiment, the epitope of the reagent is substantially composed of SKGDNEGER (SEQ ID NO:4).

[0193] In a further preferred embodiment, the at least one reagent binds to an epitope (SSGPGEEAL, SEQ ID NO:5) contained in amino acid regions 291 to 299 of SEQ ID NO:1. In one embodiment, the epitope of the reagent is substantially composed of SSGPGEEAL (SEQ ID NO:5).

[0194] In a preferred embodiment, one or more antibodies or antigen-binding fragments thereof that specifically bind to the N-terminal prosial region of BMP10 can be used. Since such antibodies (or fragments) will also bind to proBMP10 and preproBMP10, the sum of the amounts of the N-terminal prosial region of BMP10, proBMP10, and preproBMP10 can be determined in step a) of the method of the present invention. Therefore, the expression "determine the amount of the N-terminal prosial region of BMP10" should also mean "determine the sum of the amounts of the N-terminal prosial region of BMP10, proBMP10, and preproBMP10". Since preproBMP10 is substantially absent in many samples, this expression can also mean "determine the sum of the amounts of the N-terminal prosial region of BMP10 and preproBMP10".

[0195] For example, one or more antibodies that specifically bind to BMP10 can be used. Since such antibodies (or fragments) will also bind to proBMP10 and preproBMP10, the sum of the amounts of BMP10, proBMP10, and preproBMP10 is determined in step a) of the method of the present invention. Therefore, the statement "determine the amount of BMP10" should also mean "determine the sum of the amounts of BMP10, proBMP10, and preproBMP10".

[0196] Furthermore, it is envisioned that the sum of the amounts of all four BMP10-type peptides (i.e., BMP10, the N-terminal pre-terminal region of BMP10, proBMP10, and preproBMP10) as described above be determined.

[0197] Therefore, the amount of the following BMP10-type peptides can be determined according to the present invention:

[0198] • Amount of BMP10

[0199] • Quantity of BMP10 N terminal pre-terminal segment

[0200] ·Amount of proBMP10

[0201] • Amount of preproBMP10

[0202] The sum of BMP10, proBMP10, and preproBMP10 levels

[0203] • The sum of the N-terminal pre-terminal segment of BMP10, proBMP10, and preproBMP10, or

[0204] • The sum of BMP10, the N-terminal pre-terminal segment of BMP10, proBMP10, and preproBMP10.

[0205] Specifically, the amount of the following BMP10-type peptides can be determined according to the present invention:

[0206] • Quantity of BMP10 N terminal pre-terminal segment

[0207] ·Amount of proBMP10

[0208] • Amount of preproBMP10

[0209] • The sum of the N-terminal pre-terminal segment of BMP10, proBMP10, and preproBMP10, or

[0210] • The sum of the N-terminal pre-segment of BMP10 and the amounts of proBMP10 and preproBMP10.

[0211] The term "natriuretic peptide" includes atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) peptides. Therefore, the natriuretic peptides according to the present invention comprise ANP and BNP peptides and their variants (see, for example, Boynow RO. et al., Circulation 1996; 93:1946-1950).

[0212] ANP-type peptides include pre-proANP, proANP, NT-proANP, and ANP.

[0213] BNP-type peptides include pre-proBNP, proBNP, NT-proBNP, and BNP.

[0214] The precursor peptide (134 amino acids in the case of pre-proBNP) contains a short signal peptide, which is cleaved by an enzyme to release the leader peptide (108 amino acids in the case of proBNP). The leader peptide is further cleaved into the N-terminal leader peptide (NT-pro peptide, 76 amino acids in the case of NT-proBNP) and the active hormone (32 amino acids in the case of BNP and 28 amino acids in the case of ANP).

[0215] Preferred natriuretic peptides according to the present invention are NT-proANP, ANP, NT-proBNP, and BNP. ANP and BNP are active hormones and have shorter half-lives than their respective inactive counterparts NT-proANP and NT-proBNP. BNP is metabolized in the blood, while NT-proBNP circulates in the blood as an intact molecule and is therefore cleared by the kidneys.

[0216] The most preferred natriuretic peptides according to the present invention are NT-proBNP and BNP, particularly NT-proBNP. As briefly discussed above, the human NT-proBNP referred to in the present invention is a polypeptide that preferably contains 76 amino acids corresponding to the N-terminal portion of the human NT-proBNP molecule. The structures of human BNP and NT-proBNP have been described in detail in the prior art, for example, WO 02 / 089657, WO 02 / 083913 and Boynow RO. et al., New Insights into the Cardiac Natriuretic Peptides. Circulation 1996;93:1946-1950. Preferably, the human NT-proBNP used herein is the human NT-proBNP disclosed in EP 0 648 228 B1.

[0217] As used herein, the term “FABP-3” refers to fatty acid-binding protein 3. FABP-3 is also known as cardiac fatty acid-binding protein or heart-type fatty acid-binding protein (H-FABP for short). Preferably, the term also includes variants of FABP-3. As used herein, FABP-3 preferably refers to human FABP-3. The polypeptide encoding the human FABP-3 polypeptide and the DNA sequence of the protein sequence of human FABP-3 are well known in the art and were first described by Peeters et al. (Biochem. J. 276(Pt 1), 203-207(1991)). In addition, the sequence of human H-FABP can preferably be found in Genbank entries U57623.1 (cDNA sequence) and AAB02555.1 (protein sequence). The primary physiological function of FABP is thought to be the transport of free fatty acids, see, for example, Storch et al., Biochem. Biophys. Acta. 1486(2000), 28-44. Other names for FABP-3 and H-FABP are: FABP-11 (fatty acid binding protein 11), M-FABP (muscle fatty acid binding protein), MDGI (mammary gland-derived growth inhibitor), and O-FABP.

[0218] The biomarker endothelial cell-specific molecule 1 (abbreviated as ESM-1) is well known in the art. Biomarkers are also commonly referred to as endocans. ESM-1 is a secreted protein primarily expressed in endothelial cells of human lung and kidney tissues. Public domain data indicate expression in the thyroid, lung, and kidney, but also in heart tissue; see, for example, the entry for ESM-1 in the Protein Atlas database (Uhlén M. et al., Science 2015; 347(6220):1260419). Expression of this gene is regulated by cytokines. ESM-1 is a proteoglycan composed of a 20 kDa mature polypeptide and a 30 kDa O-linked glycan chain (Bechard D et al., J Biol Chem 2001; 276(51):48341-48349). In a preferred embodiment of the invention, the amount of human ESM-1 polypeptide is determined in a sample from a subject. The sequence of the human ESM-1 polypeptide is well known in the art (see, for example, Lassale P. et al., J. Biol. Chem. 1996; 271:20458-20464) and can be evaluated, for example, by the Uniprot database, see entry Q9NQ30 (ESM1_HUMAN). Two isoforms of ESM-1 are generated by alternative splicing: isoform 1 (with the Uniprot identifier Q9NQ30-1) and isoform 2 (with the Uniprot identifier Q9NQ30-2). Isoform 1 is 184 amino acids in length. In isoform 2, amino acids 101 to 150 of isoform 1 are missing. Amino acids 1 to 19 form the signal peptide (which may be cleaved).

[0219] In a preferred embodiment, the amount of isoform 1 of the ESM-1 peptide, i.e., isoform 1 having the sequence shown in UniProt accession number Q9NQ30-1, is determined.

[0220] In another preferred embodiment, the amount of isoform 2 of the ESM-1 peptide, i.e., isoform 2 having the sequence shown in UniProt accession number Q9NQ30-2, is determined.

[0221] In another preferred embodiment, the amounts of isoform 1 and isoform 2 of the ESM-1 peptide, i.e., the total amount of ESM-1, are determined.

[0222] For example, the amount of ESM-1 can be determined using monoclonal antibodies (such as mouse antibodies) targeting amino acids 85 to 184 of the ESM-1 peptide and / or goat polyclonal antibodies.

[0223] The biomarker angiopoietin-2 (abbreviated as "Ang-2", often also referred to as ANGPT2) is well known in the art. It is a naturally occurring antagonist of both Ang-1 and TIE2 (see, for example, Maisonpierre et al., Science 277 (1997) 55-60). In the absence of ANG-1, this protein induces tyrosine phosphorylation of TEK / TIE2. In the absence of angiogenesis-inducing factors such as VEGF, ANG2-mediated loosening of the cell matrix contact induces endothelial cell apoptosis and the enlarged vascularization that follows. Through its interaction with VEGF, it promotes endothelial cell migration and proliferation, thus acting as a permissive angiogenesis signal. The sequence of human angiopoietin is well known in the art. Uniprot lists three isoforms of angiopoietin-2: isoform 1 (Uniprot identifier: O15123-1), isoform 2 (identifier: O15123-2), and isoform 3 (O15123-3). In a preferred embodiment, the total amount of angiopoietin-2 is determined. The total amount is preferably the sum of the amounts of compound and free angiopoietin-2.

[0224] Determination of the amount of biomarkers

[0225] The term “determine” as used herein refers to the quantification of a biomarker (such as one or more BMP10-type peptides or natriuretic peptides), for example, by measuring the level of the biomarker in a sample using appropriate detection methods described elsewhere herein. The terms “measure” and “determine” are used interchangeably herein.

[0226] In one embodiment, determining the amount of a biomarker includes: contacting a sample with a reagent that specifically binds to the biomarker (such as the antibody of the present invention), thereby forming a complex between the reagent and the biomarker; detecting the amount of the formed complex; and thereby measuring the amount of the biomarker. This determination may further include steps such as contacting the sample with a second reagent.

[0227] Biomarkers (such as one or more BMP10-type peptides) mentioned herein can be detected using methods generally known in the art. Detection methods typically include methods for quantifying the amount of the biomarker in a sample (quantitative methods). Those skilled in the art generally know which of the following methods are suitable for the qualitative and / or quantitative detection of biomarkers. Commercially available Western and immunoassays, such as ELISA, RIA, fluorescence- and luminescent immunoassays, and proximity extension assays, can be used to conveniently determine, for example, proteins in a sample. Other suitable methods for detecting biomarkers include measuring the physical or chemical properties specific to the peptide or polypeptide, such as its precise molecular weight or NMR spectrum. These methods include, for example, biosensors, optical devices coupled to immunoassays, biochips, and analytical devices (such as mass spectrometers, NMR analyzers, or chromatographic devices). Further, methods include microplate-based ELISA methods, fully automated or robotic immunoassays (e.g., in Elecsys). TM Available on analyzers), CBA (e.g., in Roche-Hitachi) TM Enzyme cobalt binding assays and latex agglutination assays available on the analyzer (e.g., at Roche-Hitachi) are also available. TM (Available on the analyzer).

[0228] For the detection of the biomarker proteins described herein, various immunoassay techniques of this assay form can be used, see, for example, US Patent Nos. 4016043, 4424279, and 4018653. These techniques include non-competitive single-site and two-site or “sandwich” assays, as well as conventional competitive binding assays. These assays also include direct binding of labeled antibodies to target biomarkers.

[0229] Electrochemiluminescence (ECL) tagging is a well-known method. This approach utilizes the ability of a specific metal complex to achieve an excited state via oxidation, from which the complex decays to its ground state, emitting ECL. For a review, see Richter, MM, Chem. Rev. 2004; 104:3003-3036.

[0230] In one embodiment, the antibody (or its antigen-binding fragment) used to measure the amount of the biomarker is ruthenium- or iridium-conjugated. Therefore, the antibody (or its antigen-binding fragment) should contain a ruthenium tag. In one embodiment, the ruthenium tag is a bipyridine ruthenium-(II) complex. Alternatively, the antibody (or its antigen-binding fragment) should contain an iridium tag. In one embodiment, the iridium tag is a complex as disclosed in WO2012 / 107419.

[0231] In one embodiment of a sandwich assay for identifying one or more BMP10-type peptides, the assay comprises a biotinylated first monoclonal antibody (or a fragment thereof) that specifically binds to one or more BMP10-type peptides and a ruthenium-modified second monoclonal antibody (or a fragment thereof). The two antibodies form a sandwich immunoassay complex with one or more BMP10-type peptides in the sample.

[0232] Measuring the amount of a peptide (such as a BMP10-type peptide or a natriuretic peptide) may preferably include the following steps: (a) contacting the peptide with a reagent that specifically binds the peptide, (b) (optionally) removing unbound reagent, and (c) measuring the amount of bound reagent, i.e., the amount of the reagent complex formed in step (a). According to a preferred embodiment, the contact, removal, and measurement steps may be performed by an analyzer unit. According to some embodiments, the steps may be performed by a single analyzer unit of the system or by more than one analyzer unit operatively communicating with each other. For example, according to a particular embodiment, the system disclosed herein may include a first analyzer unit for performing the contact and removal steps; and a second analyzer unit operatively connected to the first analyzer unit via a transmission unit (e.g., a robotic arm), the second analyzer unit performing the measurement steps.

[0233] A reagent that specifically binds to a biomarker (also referred to herein as a “binding reagent”) can be covalently or nonvalently coupled to a tag, thereby allowing the detection and measurement of the bound reagent. Tagging can be performed by direct or indirect methods. Direct tagging involves directly (covalently or nonvalently) coupling a tag to a binding reagent. Indirect tagging involves the binding (covalently or nonvalently) of a secondary binding reagent to a primary binding reagent. The secondary binding reagent should specifically bind to the primary binding reagent. The secondary binding reagent may be coupled to a suitable tag and / or a target (receptor) of a tertiary binding reagent that binds to the secondary binding reagent. Suitable secondary and higher-order binding reagents may include antibodies, secondary antibodies, and the well-known streptavidin-biotin system (Vector Laboratories, Inc.). The binding reagent or substrate may also be “tagged” with one or more tags known in the art. Such tags may be targets of higher-order binding reagents. Suitable tags include biotin, digitalisin, His tag, glutathione S-transferase, FLAG, GFP, myc tag, influenza A virus hemagglutinin (HA), maltose-binding protein, etc. In the case of peptides or polypeptides, the tag is preferably located at the N-terminus and / or C-terminus. Suitable tags are any tags detectable by a suitable detection method. Typical tags include gold particles, latex beads, acridinium esters, luminol, ruthenium complexes, iridium complexes, enzyme activity tags, radioactive tags, magnetic tags (“e.g., magnetic beads,” including paramagnetic and superparamagnetic tags), and fluorescent tags. Enzyme activity tags include, for example, horseradish peroxidase, alkaline phosphatase, β-galactosidase, luciferase, and their derivatives. Suitable substrates for detection include diaminobenzidine (DAB), 3,3'-5,5'-tetramethylbenzidine, NBT-BCIP (4-nitroblue tetrazolium chloride and 5-bromo-4-chloro-3-indolyl phosphate, available as a ready-made stock solution from Roche Diagnostics), and CDP-Star. TM (Amersham Bio-sciences), ECF TM(Amersham Biosciences). Suitable enzyme-substrate combinations can produce colored reaction products, fluorescence, or chemiluminescence, which can be determined according to methods known in the art (e.g., using photographic film or a suitable imaging system). The standards given above are similarly applicable for the measurement of enzyme reactions. Typical fluorescent labels include fluorescent proteins (such as GFP and its derivatives), Cy3, Cy5, Texas Red, fluorescein, and Alexa dyes (e.g., Alexa 568). Further fluorescent tags are available from Molecular Probes (Oregon). Quantum dots are also considered as fluorescent tags. Radioactive tags can be detected by any known and suitable method, such as photographic film or a phosphorescent imaging system.

[0234] The amount of peptide can also preferably be determined as follows: (a) contacting a solid support containing a binding agent for the peptide as described elsewhere herein with a sample containing the peptide or polypeptide, and (b) measuring the amount of peptide or polypeptide bound to the support. Materials used to manufacture the support are well known in the art and include, in particular, commercial column materials, polystyrene beads, latex beads, magnetic beads, colloidal metal particles, glass and / or silicon wafers and surfaces, nitrocellulose tapes, membranes, sheets, durable cells, pores and walls of reaction discs, plastic tubing, etc.

[0235] In another aspect, the sample is removed from the complex formed between the binding agent and at least one marker before the amount of the formed complex is measured. Thus, in one aspect, the binding agent may be immobilized on a solid support. In another aspect, the sample can be removed from the complex formed on the solid support by applying a washing solution.

[0236] Sandwich assays are among the most useful and commonly used assays, encompassing many variations of the sandwich assay technique. Simply put, in a typical assay, an unlabeled (capture) binding agent is immobilized, or can be immobilized, on a solid substrate, and the sample to be tested is brought into contact with the capture binding agent. After an appropriate incubation period, sufficient to allow the formation of the binding agent-biomarker complex, a second (detection) binding agent labeled with a reporter molecule capable of producing a detectable signal is added, followed by incubation sufficient to allow for the formation of another complex of the binding agent-biomarker-labeled binding agent. Any unreacted material can be washed away, and the presence of the biomarker is determined by observing the signal produced by the reporter molecule bound to the detection binding agent. The results can be qualitatively determined by simply observing the visible signal, or quantitatively determined by comparison with a control sample containing a known amount of the biomarker.

[0237] The incubation steps for typical sandwich assays can be varied as needed and as appropriate. Such variations include, for example, simultaneous incubation, where two or more binding reagents and biomarkers are co-incubated. For instance, the sample to be analyzed and the labeled binding reagent are added simultaneously to a fixed capture binding reagent. Alternatively, the sample to be analyzed and the labeled binding reagent may be incubated first, followed by the addition of an antibody bound to or capable of binding to a solid phase.

[0238] The complex formed between a specific binding agent and a biomarker should be proportional to the amount of the biomarker present in the sample. It should be understood that the specificity and / or sensitivity of the binding agent to be applied defines the proportion of at least one biomarker contained in the sample that can be specifically bound. Further details on how measurements can be performed can be found elsewhere in this document. The amount of the complex formed should be converted into the amount of the biomarker, thus reflecting the actual amount present in the sample.

[0239] The terms “binding reagent,” “specific binding reagent,” “analyte-specific binding reagent,” “detector,” and “reagent that specifically binds to a biomarker” are used interchangeably herein. Preferably, it refers to a reagent containing a binding portion that specifically binds to the corresponding biomarker. Examples of “binding reagent,” “detector,” and “reagent” are nucleic acid probes, nucleic acid primers, DNA molecules, RNA molecules, aptamers, antibodies, antibody fragments, peptides, peptide nucleic acids (PNAs), or compounds. Preferred reagents are antibodies that specifically bind to the biomarker to be measured. The term “antibody” is used herein in the broadest sense and includes various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments, provided they exhibit the desired antigen-binding activity (i.e., their antigen-binding fragments). Preferably, the antibody is a polyclonal antibody (or its antigen-binding fragment). More preferably, the antibody is a monoclonal antibody (or an antigen-binding fragment thereof). Thus, as described elsewhere herein, it is contemplated to use two monoclonal antibodies (in sandwich immunoassays) that bind at different sites on one or more BMP10-type peptides. Therefore, at least one antibody is used to determine the amount of BMP10-type peptide.

[0240] In one embodiment, at least one antibody is a mouse monoclonal antibody. In another embodiment, at least one antibody is a rabbit monoclonal antibody. In yet another embodiment, the antibody is a goat polyclonal antibody. In still another embodiment, the antibody is a sheep polyclonal antibody.

[0241] In some embodiments, at least one antibody or fragment thereof that specifically binds to the BMP10-type peptide is at least one antibody or fragment thereof described in the next section (titled “Antibodies of the Invention”).

[0242] As used herein, the term "amount" includes the absolute amount, relative amount, or concentration of the biomarker mentioned herein (such as one or more BMP10-type peptides or natriuretic peptides), and any value or parameter associated with or derived therefrom. Such values ​​or parameters include intensity signal values ​​from all specific physical or chemical properties obtained by direct measurement of the peptide, such as intensity values ​​in mass spectrometry or NMR spectra. Furthermore, all values ​​or parameters obtained by indirect measurement specified elsewhere in this specification are included, for example, the amount of response determined from a bioreading system in response to an intensity signal obtained from a peptide or a specifically bound ligand. It should be understood that values ​​associated with the above-described amounts or parameters can also be obtained through all standard mathematical operations.

[0243] As used herein, the term "comparison" refers to comparing the amount of a biomarker (such as one or more BMP10-type peptides and natriuretic peptides, such as NT-proBNP or BNP) in a sample from a subject with a reference amount of the biomarker specified elsewhere in this specification. It should be understood that, as used herein, comparison generally refers to a comparison of corresponding parameters or values, such as comparing an absolute amount with an absolute reference amount, or a concentration with a reference concentration, or comparing an intensity signal obtained from a biomarker in a sample with an intensity signal of the same type obtained from a first sample. Comparisons can be performed manually or computer-assisted. Therefore, comparisons can be made by a computing device. For example, the value of a measured or detected amount of a biomarker in a sample from a subject can be compared with a reference amount, and such comparisons can be performed automatically by a computer program that executes a comparison algorithm. The computer program performing the assessment will provide the desired evaluation in an appropriate output format. For computer-assisted comparisons, the value of the measured amount can be compared with a value corresponding to an appropriate reference stored in a database by the computer program. The computer program can further evaluate the results of the comparison, i.e., automatically provide the desired evaluation in an appropriate output format. For computer-aided comparisons, the value of the measured quantity can be compared with a value corresponding to an appropriate reference stored in a database by a computer program. The computer program can further evaluate the results of the comparison, i.e., automatically provide the required assessment in an appropriate output format.

[0244] According to the invention, the amounts of one or more BMP10-type peptides and optionally at least one other biomarker (such as natriuretic peptides) are compared with reference values. The reference is preferably a reference amount. The term "reference amount" is well understood by those skilled in the art. It should be understood that the reference amount should allow for the atrial fibrillation assessment described herein. For example, with respect to methods for diagnosing atrial fibrillation, the reference amount preferably refers to a amount that allows for the allocation of subjects to (i) a group of subjects with atrial fibrillation or (ii) a group of subjects without atrial fibrillation. An appropriate reference amount can be determined from the first sample to be analyzed together with the test sample (i.e., simultaneously or subsequently).

[0245] It should be understood that the amount of one or more BMP10-type peptides is compared to a reference amount of one or more BMP10-type peptides, while the amount of at least one other biomarker (such as a natriuretic peptide) is compared to a reference amount of said at least one other biomarker (such as a natriuretic peptide). If the amounts of two or more markers are determined, it is also conceivable to calculate a composite score based on the amounts of two or more markers (such as the amounts of one or more BMP10-type peptides and the amounts of natriuretic peptides). In subsequent steps, the score is compared to a reference score.

[0246] In principle, reference values ​​for the subject cohorts specified above can be calculated based on the mean or average of a given biomarker by applying standard statistical methods. In particular, the accuracy of a test (such as a method designed to diagnose the occurrence or absence of an event) is best described by its receiver operating characteristic (ROC) (see, in particular, Zweig MH. et al., Clin. Chem. 1993; 39:561-577). An ROC curve is a curve showing all sensitivity versus specificity pairs produced by continuously varying the decision threshold across the entire observed data range. The clinical performance of a diagnostic method depends on its accuracy, i.e., its ability to correctly assign subjects to a given prognosis or diagnosis. The ROC curve shows the overlap between the two distributions by plotting the sensitivity versus 1-specificity across the entire range of thresholds applicable to the distinction. The y-axis represents sensitivity, or the true positive score, which is defined as the ratio of the number of true positive test results to the product of the number of true positive test results and the number of false negative test results. It is calculated only from the affected subgroup. The x-axis represents the false positive score, or 1-specificity, which is defined as the ratio of the number of false positive results to the product of the number of true negative results and the number of false positive results. This is a specificity index and is calculated entirely from the unaffected subgroups. Because the true positive score and the false positive score are calculated completely separately, the ROC curve is independent of the prevalence of events in the cohort by using test results from two different subgroups. Each point on the ROC curve represents a sensitivity / 1-specificity pair corresponding to a specific decision threshold. Tests with perfect discrimination (no overlap between the two outcome distributions) have an ROC curve that crosses the top left corner, where the true positive score is 1.0 or 100% (perfect sensitivity) and the false positive score is 0 (perfect specificity). Tests with no discrimination (identical outcome distributions in both groups) have a theoretical curve that runs diagonally from the bottom left to the top right corner at a 45° angle. Most curves fall between these two extremes. If the ROC curve falls completely below the 45° diagonal, it can be easily corrected by reversing the criteria for "positive" from "greater than" to "less than" or vice versa. Qualitatively, the closer the curve is to the upper left corner, the higher the overall accuracy of the test. Based on the desired confidence interval, a threshold can be derived from the ROC curve, allowing for diagnosis of a given event with an appropriate balance of sensitivity and specificity. Therefore, preferably, by establishing the ROC of the aforementioned cohorts and thereby deriving the threshold amount, a reference for the method of the present invention can be generated, i.e., a threshold that allows for the assessment of atrial fibrillation. The ROC curve allows for the determination of an appropriate threshold based on the required sensitivity and specificity of the diagnostic method. It should be understood that optimal sensitivity is, for example, required to exclude subjects with atrial fibrillation (i.e., exclusion), while optimal specificity is envisioned for subjects assessed as having atrial fibrillation (i.e., confirmation).In one embodiment, the method of the present invention allows for the prediction of a subject's risk of adverse events associated with atrial fibrillation, such as the occurrence or recurrence of atrial fibrillation and / or stroke.

[0247] In a preferred embodiment, the term "reference value" herein refers to a predetermined value. This predetermined value should allow for the assessment of atrial fibrillation, thereby diagnosing atrial fibrillation, differentiating between paroxysmal and persistent atrial fibrillation, predicting the risk of adverse events associated with atrial fibrillation, identifying subjects who should undergo electrocardiography (ECG), or assessing treatment for atrial fibrillation. It should be understood that the reference value may vary based on the type of assessment. For example, the reference value for one or more BMP10-type peptides used to differentiate AF will generally be higher than the reference value used to diagnose AF. However, those skilled in the art will take this into account.

[0248] As stated above, the term "assessment of atrial fibrillation" preferably refers to the diagnosis of atrial fibrillation, the distinction between paroxysmal and persistent atrial fibrillation, the prediction of the risk of adverse events associated with atrial fibrillation, the identification of subjects who should undergo electrocardiography (ECG), or the assessment of atrial fibrillation treatment. These embodiments of the methods of the present invention will be described in more detail below. The above definitions apply accordingly.

[0249] Methods for diagnosing atrial fibrillation

[0250] As used herein, the term "diagnosis" refers to assessing whether a subject, according to the method of the invention, has atrial fibrillation (AF). In a preferred embodiment, the subject is diagnosed with paroxysmal AF. In an alternative embodiment, the subject is diagnosed as not having AF.

[0251] According to the present invention, all types of atrial fibrillation can be diagnosed. Therefore, atrial fibrillation can be paroxysmal AF, persistent AF, or permanent AF. Preferably, and particularly in subjects who do not have permanent AF, paroxysmal or persistent atrial fibrillation is diagnosed.

[0252] The actual diagnosis of whether a subject has atrial fibrillation (AF) may include other steps, such as confirmatory diagnosis (e.g., ECG confirmation via Holter-ECG). Therefore, this invention allows for the assessment of the likelihood of a patient having atrial fibrillation. Subjects with levels of one or more BMP10-type peptides higher than reference levels are likely to have atrial fibrillation, while subjects with levels of one or more BMP10-type peptides lower than reference levels are less likely to have atrial fibrillation. Therefore, in the context of this invention, the term "diagnosis" also covers assisting physicians in assessing whether a subject has atrial fibrillation.

[0253] Preferably, an increase in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in the sample from the test subject compared to a reference level (or multiple reference levels) indicates that the subject has atrial fibrillation, and / or a decrease in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in the sample from the subject compared to a reference level (or multiple reference levels) indicates that the subject does not have atrial fibrillation.

[0254] In a preferred embodiment, the reference amount, namely a reference amount of one or more BMP10-type peptides, and, if determined, a reference amount of at least one other biomarker, should allow for differentiation between subjects with atrial fibrillation and those without atrial fibrillation. Preferably, the reference amount is a predetermined value.

[0255] In one embodiment, the method of the present invention allows for the diagnosis of atrial fibrillation in a subject. Preferably, the subject has AF if the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3, and / or natriuretic peptides) is above a reference level. In one embodiment, the subject has AF if the amount of one or more BMP10-type peptides is above a specific percentile (e.g., the 99th percentile) upper reference limit (URL) of the reference level.

[0256] In one embodiment of a method for diagnosing atrial fibrillation, the method further includes the step of recommending and / or initiating atrial fibrillation treatment based on the diagnostic result. Preferably, treatment is recommended or initiated if the subject is diagnosed with AF. Preferred therapies for atrial fibrillation are disclosed elsewhere herein (such as anticoagulation therapy).

[0257] Methods for differentiating between paroxysmal atrial fibrillation and persistent atrial fibrillation

[0258] As used herein, the term "differentiation" refers to distinguishing between paroxysmal atrial fibrillation and persistent atrial fibrillation in a subject. The term, as used herein, preferably includes the differential diagnosis of paroxysmal and persistent atrial fibrillation in a subject. Therefore, the method of the present invention allows for the assessment of whether a subject with atrial fibrillation has paroxysmal or persistent atrial fibrillation. The actual differentiation may include other steps, such as confirmation of the differentiation. Therefore, in the context of the present invention, the term "differentiation" also encompasses assisting physicians in differentiating between paroxysmal and persistent atrial fibrillation.

[0259] Preferably, an increase in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3, and / or natriuretic peptides) in a sample from a subject compared to a reference level (or multiple reference levels) indicates that the subject has persistent atrial fibrillation, and / or a decrease in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3, and / or natriuretic peptides) in a sample from a subject compared to a reference level (or multiple reference levels) indicates that the subject has paroxysmal atrial fibrillation. In both AF types (paroxysmal and persistent), the amount of BMP10-type peptides is increased compared to the reference level for non-AF subjects.

[0260] In a preferred embodiment, the reference value should allow differentiation between subjects with paroxysmal atrial fibrillation and subjects with persistent atrial fibrillation. Preferably, the reference value is a predetermined value.

[0261] In one embodiment of the above method for distinguishing between paroxysmal atrial fibrillation and persistent atrial fibrillation, the subject did not have permanent atrial fibrillation.

[0262] Methods for predicting the risk of adverse events associated with atrial fibrillation

[0263] The method of the present invention also envisions a method for predicting the risk of adverse events.

[0264] In one embodiment, the adverse event risk described herein can be a prediction of any adverse event associated with atrial fibrillation. Preferably, the adverse event is selected from recurrence of atrial fibrillation (e.g., recurrence of atrial fibrillation after cardioversion) and stroke. Therefore, the risk of a subject (a patient with atrial fibrillation) experiencing adverse events (such as stroke or recurrence of atrial fibrillation) in the future should be predicted.

[0265] Furthermore, it is hypothesized that the adverse events associated with atrial fibrillation are the occurrence of atrial fibrillation in subjects with no known history of atrial fibrillation.

[0266] In a particularly preferred embodiment, the risk of stroke is predicted.

[0267] Therefore, the present invention relates to a method for predicting the risk of stroke in a subject, the method comprising the following steps:

[0268] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0269] b) Compare the amount of one or more BMP10-type peptides to a reference amount to predict the risk of stroke.

[0270] Specifically, the present invention relates to a method for predicting the risk of stroke in a subject, the method comprising the following steps:

[0271] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0272] (b) The amount of one or more BMP10-type peptides is compared with a reference amount of BMP10-type peptides, and optionally the amount of at least one other biomarker is compared with a reference amount of said at least one other biomarker, thereby predicting the risk of stroke.

[0273] Furthermore, it is envisioned to predict the risk of atrial fibrillation recurrence in subjects after cardioversion, such as the risk of atrial fibrillation recurrence after pulmonary vein isolation or ablation therapy. Therefore, biomarkers as described herein are used as predictors of atrial fibrillation recurrence after therapeutic interventions such as pulmonary vein isolation and ablation therapy. The success rate of such procedures depends on the ablation strategy and patient characteristics, with reported success rates of 50% to 60% for persistent AF (J Am HeartAssoc. 2013; 2:e004549). In this embodiment, it is envisioned that subjects should be analyzed prior to the therapeutic intervention, i.e., the subjects to be tested have an AF episode at the time of testing, i.e., when the sample is obtained. According to this embodiment, the amount of one or more biomarkers should be determined in the obtained sample before the (planned) intervention, preferably one month prior to the planned intervention, more preferably one week prior to the (planned) intervention, and most preferably one day prior to the (planned) intervention. Therefore, biomarkers can be used to predict the risk of AF recurrence prior to treatment. According to the method of the present invention, an elevation of biomarkers as referred to herein should facilitate the stratification of subjects with high-risk and low-risk recurrent AFib after therapeutic intervention. Based on the detected or predicted risk, some patients with low success rates can be treated differently from those with high success rates, depending on blood biomarkers measured preoperatively as predictors of AF recurrence after PVI or ablation.

[0274] Preferably, as used herein, the term "predicted risk" refers to assessing the probability that a subject will suffer from an adverse event as referred to herein (e.g., a stroke). Typically, this predicts whether a subject has a risk of suffering the adverse event (and therefore an increased risk) or no risk of suffering the adverse event (and therefore a decreased risk). Thus, the method of the present invention allows for the differentiation between subjects at risk of suffering the adverse event and subjects at risk of not suffering the adverse event. Further, it is envisioned that the method of the present invention allows for the differentiation between subjects with reduced, average, or increased risk.

[0275] As described above, the risk (and probability) of experiencing the adverse event within a certain time window should be predicted. In a preferred embodiment of the invention, the prediction window is a period of approximately three months, approximately six months, or particularly approximately one year. Therefore, short-term risk is predicted.

[0276] In another preferred embodiment, the prediction window is a period of approximately five years (e.g., for predicting stroke). Alternatively, the prediction window may be a period of approximately six years (e.g., for predicting stroke). Or, the prediction window may be approximately 10 years. Furthermore, a prediction window of 1 to 3 years is envisioned. Therefore, the risk of developing stroke within 1 to 3 years can be predicted. Furthermore, a prediction window of 1 to 10 years is envisioned. Therefore, the risk of developing stroke within 1 to 10 years can be predicted.

[0277] Preferably, the prediction window is calculated from the completion of the method of the present invention. More preferably, the prediction window is calculated from the time point when the sample to be tested is obtained. As those skilled in the art will understand, risk prediction is generally not intended to be correct for 100% of the subjects being tested. However, this term requires the ability to predict the statistically significant portion of the subjects in an appropriate and correct manner. Whether a portion is statistically significant can be determined by those skilled in the art using various well-known statistical evaluation tools (e.g., determining confidence intervals, p-value determination, Student's t-test, Mann-Whitney test, etc.) without further effort. See Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983 for details. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98%, or at least 99%. P-values ​​are preferably 0.1, 0.05, 0.01, 0.005, or 0.0001.

[0278] In a preferred embodiment, the expression "predicting the risk of having the adverse event" means that the subjects to be analyzed by the method according to the invention are assigned to a group of subjects at risk of having the adverse event, or to a group of subjects at no risk of having the adverse event (such as stroke). Thus, it is possible to predict whether a subject has the risk of having the adverse event. As used herein, "subjects at risk of having the adverse event" preferably have an increased risk of having the adverse event (preferably within a prediction window). Preferably, the risk is increased compared to the average risk in the subject cohort. As used herein, "subjects at no risk of having the adverse event" preferably have a decreased risk of having the adverse event (preferably within a prediction window). Preferably, the risk is decreased compared to the average risk in the subject cohort. Preferably, within a prediction window of about one year, subjects at risk of having the adverse event preferably have at least a 20% or more preferably at least a 30% risk of having the adverse event (such as recurrence or occurrence of atrial fibrillation). Preferably, within a one-year prediction window, subjects who do not have a risk of having the adverse event have a risk of having the adverse event of less than 12%, more preferably less than 10%.

[0279] Regarding the prediction of stroke, preferably within a prediction window of about five years, or particularly about six years, subjects at risk of the aforementioned adverse event have a risk of at least 10%, or more preferably at least 13%, of the aforementioned adverse event. Preferably, within a prediction window of about five years, or particularly about six years, subjects not at risk of the aforementioned adverse event have a risk of less than 10%, more preferably less than 8%, or most preferably less than 5%. The risk may be higher if the subject is not receiving anticoagulation therapy. This will be taken into account by those skilled in the art.

[0280] Preferably, the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in the sample from the subject increases compared to a reference level (or multiple reference levels) to indicate that the subject has a risk of having adverse events related to atrial fibrillation, and / or the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in the sample from the subject decreases compared to a reference level (or multiple reference levels) to indicate that the subject does not have a risk of having adverse events related to atrial fibrillation.

[0281] In a preferred embodiment, a reference value (or multiple reference values) should allow for the distinction between subjects at risk of experiencing adverse events as described herein and subjects not at risk of experiencing said adverse events. Preferably, the reference value is a predetermined value.

[0282] The adverse event to be predicted is preferably stroke. The term "stroke" is well known in the art. As used herein, the term preferably refers to ischemic stroke, and more particularly to cerebral ischemic stroke. The stroke predicted by the method of the present invention should be due to a reduction in blood flow to the brain or a portion thereof, resulting in insufficient oxygen supply to brain cells. In particular, stroke causes irreversible tissue damage due to brain cell death. Symptoms of stroke are well known in the art. For example, stroke symptoms include sudden numbness or weakness in the face, arm, or leg, especially on one side of the body; sudden confusion; difficulty speaking or understanding; sudden loss of vision in one or both eyes; and sudden difficulty walking, dizziness, loss of balance or coordination. Ischemic stroke may be caused by atherosclerotic thrombosis or aortic embolism, by coagulation disorders or non-neoplastic vascular diseases, or by myocardial ischemia leading to a reduction in total blood flow. Ischemic stroke is preferably selected from the group consisting of free artery atherosclerotic thrombotic stroke, cardiac embolic stroke, and lacunar stroke. Preferably, the stroke to be predicted is acute ischemic stroke, especially cardiac embolic stroke. Atrial fibrillation can cause cardiac embolic stroke (also commonly referred to as embolic or thromboembolic stroke).

[0283] Preferably, the stroke should be associated with atrial fibrillation. More preferably, the stroke should be caused by atrial fibrillation. However, it is also conceivable that the subject has no history of atrial fibrillation.

[0284] Preferably, stroke is associated with atrial fibrillation if there is a temporal relationship between the onset of stroke and atrial fibrillation. More preferably, stroke is associated with atrial fibrillation if it is caused by atrial fibrillation. Most preferably, stroke is associated with atrial fibrillation if it can be caused by atrial fibrillation. For example, atrial fibrillation can cause cardiogenic stroke (commonly referred to as embolic or thromboembolic stroke). Preferably, stroke associated with atrial fibrillation can be prevented by oral anticoagulation. Also preferably, stroke is considered associated with atrial fibrillation if the subject has atrial fibrillation and / or a known history of atrial fibrillation. Similarly, in one embodiment, stroke is considered associated with atrial fibrillation if the subject is suspected of having atrial fibrillation.

[0285] The term "stroke" preferably does not include hemorrhagic stroke.

[0286] In a preferred embodiment of the aforementioned method for predicting adverse events (such as stroke), the subject has atrial fibrillation. More preferably, the subject has a known history of atrial fibrillation. According to the method for predicting adverse events, the subject preferably has permanent atrial fibrillation, more preferably has persistent atrial fibrillation, and most preferably has paroxysmal atrial fibrillation.

[0287] In one embodiment of the method for predicting adverse events, the subject with atrial fibrillation experiences an atrial fibrillation episode when the sample is received. In another embodiment of the method for predicting adverse events, the subject with atrial fibrillation does not experience an atrial fibrillation episode when the sample is received (and therefore should have a normal sinus rhythm). Furthermore, the subject whose risk is being predicted may be receiving anticoagulation therapy.

[0288] In another embodiment of the method for predicting adverse events, the subject has no known history of atrial fibrillation. Specifically, it is assumed that the subject does not have atrial fibrillation.

[0289] The method according to the invention can assist in personalized medicine. In a preferred embodiment, the method for predicting a subject's stroke risk further includes, if the subject has been determined to have a stroke risk, i) recommending anticoagulation therapy, or ii) recommending intensified anticoagulation therapy. In a preferred embodiment, the method for predicting a subject's stroke risk further includes, if the subject has been determined to have a stroke risk (by the method of the invention), i) initiating anticoagulation therapy, or ii) intensifying anticoagulation therapy.

[0290] If the test subject is receiving anticoagulation therapy, and if it has been determined that the subject is not at risk of stroke (by the method of the present invention), the dose of anticoagulation therapy can be reduced. Therefore, a dose reduction can be recommended. By reducing the dose, the risk of side effects (such as bleeding) can be reduced.

[0291] As used herein, the term "recommendation" refers to a proposal to establish a therapy that can be applied to the subject. However, it should be understood that this term does not include the application of an actual therapy. The recommended therapy depends on the outcome provided by the method of this invention.

[0292] In particular, the following provisions apply:

[0293] If the subject is not receiving anticoagulation therapy, it is recommended to start anticoagulation therapy if the subject has been identified as having a stroke risk. Therefore, anticoagulation therapy should be initiated.

[0294] If the subject is already receiving anticoagulation therapy, then if the subject has been identified as having a stroke risk, it is recommended to intensify the anticoagulation therapy. Therefore, anticoagulation therapy should be intensified.

[0295] In a preferred embodiment, anticoagulation therapy is enhanced by increasing the dose of the anticoagulant (i.e., the dose of the currently applied coagulant).

[0296] In a particularly preferred embodiment, anticoagulation therapy is enhanced by replacing the currently administered anticoagulation with a more effective one. Therefore, changing the anticoagulation agent is recommended.

[0297] As described, compared with the vitamin K antagonist warfarin, the oral anticoagulant apixaban achieves better prevention in high-risk patients, as described by Hijazi et al., The Lancet 2016 387, 2302-2311. Figure 4 As shown in the figure.

[0298] Therefore, it is assumed that the subject is receiving treatment with a vitamin K antagonist (such as warfarin or dicumarol). If the subject is determined to have a risk of stroke (by the method of this invention), it is recommended to use an oral anticoagulant (particularly dabigatran, rivaroxaban, or apixaban) instead of the vitamin K antagonist. Therefore, treatment with the vitamin K antagonist is discontinued, and treatment with an oral anticoagulant is initiated.

[0299] Methods for identifying subjects who should undergo an electrocardiogram (ECG) examination

[0300] According to this embodiment of the method of the present invention, it should be assessed whether the subject to be tested using biomarkers should undergo an electrocardiogram (ECG) examination, i.e., an ECG assessment. This assessment should be performed for diagnostic purposes, i.e., to detect the presence of atrial fibrillation (AF) in the subject.

[0301] As used herein, the term "identifying subject" preferably refers to information or data generated using the amount of one or more BMP10-type peptides (and optionally at least one other biomarker) in a sample involving the subject to identify the subject who should undergo an ECG. Identified subjects have an increased likelihood of having atrial fibrillation (AF). An ECG assessment is performed for confirmation.

[0302] An electrocardiogram (ECG) is the process of recording the electrical activity of the heart using a suitable ECG device. An ECG device records electrical signals generated by the heart that travel throughout the body to the skin. Recording of these electrical signals is achieved by bringing the skin of the test subject into contact with electrodes contained in the ECG device. The process of acquiring the recording is non-invasive and risk-free. ECGs are performed to diagnose atrial fibrillation, i.e., to assess the presence of atrial fibrillation in the test subject. In embodiments of the method of the present invention, the ECG device is a single-lead device (such as a single-lead handheld ECG device). In another preferred embodiment, the ECG device is a 12-lead ECG device, such as a Holter monitor.

[0303] Preferably, an increase in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in a sample from a test subject compared to a reference level (or multiple reference levels) indicates that the subject should receive an ECG, and / or a decrease in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in a sample from a subject compared to a reference level (or multiple reference levels) indicates that the subject should not receive an ECG.

[0304] In a preferred embodiment, the reference value should allow for the distinction between subjects who should undergo ECG and those who should not. Preferably, the reference value is a predetermined value.

[0305] In one embodiment of the above method, the method includes identifying subjects who should undergo electrocardiography, particularly when the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in a sample from a test subject increases compared to a reference amount (or multiple reference amounts), and the identified subject undergoes electrocardiography.

[0306] Methods for assessing atrial fibrillation treatment

[0307] As used herein, the term "assessment of atrial fibrillation treatment" preferably refers to the assessment of treatment aimed at treating atrial fibrillation. Specifically, the efficacy of the treatment should be assessed.

[0308] The treatment to be evaluated can be any treatment method intended to treat atrial fibrillation. Preferably, the treatment is selected from the group consisting of: administration of at least one anticoagulant, rhythm control, heart rate control, cardioversion, and ablation. Such treatments are well known in the art and are described, for example, in Fuster V et al., Circulation 2011; 123:e269-e367, the entire contents of which are incorporated herein by reference.

[0309] In one embodiment, the treatment is the administration of at least one anticoagulant, i.e., anticoagulation therapy. Anticoagulation therapy is preferably a treatment designed to reduce the risk of anticoagulation in the subject. Administration of at least one anticoagulant should be intended to reduce or prevent blood clotting and associated stroke. In a preferred embodiment, at least one anticoagulant is selected from the group consisting of: heparin, coumarin derivatives (i.e., vitamin K antagonists) (especially warfarin or dicumarol), oral anticoagulants (especially dabigatran, rivaroxaban, or apixaban), tissue factor pathway inhibitors (TFPIs), antithrombin III, factor Ixa inhibitors, factor Xa inhibitors, factor Va and VIIIa inhibitors, and thrombin inhibitors (anti-IIa type). Therefore, it is envisioned that the subject takes at least one of the above-mentioned drugs.

[0310] In a preferred embodiment, the anticoagulant is a vitamin K antagonist, such as warfarin or dicumarol. Vitamin K antagonists, such as warfarin or dicumarol, are less expensive, but their treatment is inconvenient, cumbersome, and often unreliable, with treatment durations fluctuating within the therapeutic range, thus requiring better patient compliance. NOACs (new oral anticoagulants) include direct factor Xa inhibitors (apixaban, rivaroxaban, darexaban, edoxaban), direct thrombin inhibitors (dabigatran), and PAR-1 antagonists (vorapaxar, atopaxar).

[0311] In another preferred embodiment, the anticoagulant and oral anticoagulant, particularly apixaban, rivaroxaban, daressaban, edoxaban, dabigatran, vorapazan, or atropazan.

[0312] Therefore, the test subject can be on oral anticoagulant or vitamin K antagonist therapy at the time of testing (i.e., when the sample is received).

[0313] In a preferred embodiment, assessing atrial fibrillation treatment involves monitoring the treatment. In this embodiment, the reference amount is preferably the amount of BMP10-type peptide or multiple BMP10-type peptides in an earlier obtained sample (i.e., a sample obtained before the test sample in step a).

[0314] Optionally, in addition to the amount of one or more BMP10-type peptides, the amount of at least one other biomarker described herein is also determined.

[0315] Therefore, the present invention relates to a method for monitoring atrial fibrillation treatment in a subject, preferably a subject suffering from atrial fibrillation, wherein the method includes the following steps:

[0316] (a) In a first sample from a subject, determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides), and optionally, determine the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP-3 (fatty acid binding protein 3).

[0317] (b) In a second sample from a subject, determine the amount of one or more BMP10-type peptides and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP-3 (fatty acid-binding protein 3), wherein the second sample was obtained after the first sample was obtained.

[0318] (c) The amount of one or more BMP10-type peptides in the first sample is compared with the amount of one or more BMP10-type peptides in the second sample, and optionally the amount of the at least one other biomarker in the first sample is compared with the amount of the at least one other biomarker in the second sample, thereby monitoring anticoagulation therapy.

[0319] As used herein, the term "monitoring" preferably refers to assessing the effectiveness of treatments as mentioned elsewhere herein. Therefore, monitoring the efficacy of treatments (such as anticoagulation therapy) is crucial.

[0320] The aforementioned method may include monitoring other steps of treatment based on the results of the comparison step performed in step c). As those skilled in the art will understand, risk prediction is generally not intended to be accurate for 100% of the subjects being tested. However, this term requires the ability to predict the statistically significant portion of the subjects in an appropriate and accurate manner. Therefore, actual monitoring may include other steps such as confirmation.

[0321] Preferably, by implementing the method of the present invention, it is possible to assess whether the subject responds to the treatment. If the subject's condition improves between obtaining the first sample and the second sample, the subject responds to the treatment. Preferably, if the subject's condition deteriorates between obtaining the first sample and the second sample, the subject does not respond to the treatment.

[0322] Preferably, the first sample is obtained before the start of the treatment. More preferably, the sample is obtained within one week, and particularly two weeks, before the start of the treatment. However, it is also considered that the first sample may be obtained after the start of the treatment (but before the second sample is obtained). In this case, the ongoing treatment is monitored.

[0323] Therefore, the second sample should be obtained after the first sample. It should be understood that the second sample should be obtained after the start of the treatment.

[0324] Furthermore, it is particularly anticipated that the second sample be obtained after a reasonable period of time following the acquisition of the first sample. It should be understood that the amount of the biomarker mentioned herein will not change immediately (e.g., within 1 minute or 1 hour). Therefore, in this abbreviation, "reasonable" refers to the interval between obtaining the first and second samples that allows for adjustment of the biomarker. Thus, preferably, the second sample is obtained at least one month after the first sample, at least three months after the first sample, or particularly at least six months after the first sample.

[0325] Preferably, the amount of biomarkers (i.e., one or more BMP10-type peptides and optional natriuretic peptides) in the second sample is reduced compared to the amount of biomarkers in the first sample, and more preferably significantly reduced, and most preferably statistically significantly reduced, indicating that the subject has responded to the treatment. Therefore, the treatment is effective. Also preferably, compared to the amount of biomarkers in the first sample, the amount of biomarkers in the second sample does not show a change or increase in the concentration of one or more BMP10-type peptides, more preferably significantly increased, and most preferably statistically significantly increased, indicating that the subject has not responded to the treatment. Therefore, the treatment is ineffective.

[0326] The terms "significant" and "statistically significant" are known to those skilled in the art. Therefore, those skilled in the art can determine whether an increase or decrease is significant or statistically significant using various well-known statistical assessment tools without further effort. For example, a significant increase or decrease is an increase or decrease of at least 10%, and particularly at least 20%.

[0327] If treatment reduces the risk of recurrent atrial fibrillation in a subject, the subject is considered to have responded to treatment. If treatment does not reduce the risk of recurrent atrial fibrillation in a subject, the subject is considered to have not responded to treatment.

[0328] In one embodiment, if the subject does not respond to treatment, the treatment intensity is increased. Conversely, it is envisioned that if the subject responds to treatment, the treatment intensity is decreased. For example, the treatment intensity could be increased by increasing the dosage of the administered drug. Conversely, the treatment intensity could be decreased by decreasing the dosage of the administered drug. Therefore, it is possible to avoid harmful adverse side effects, such as bleeding.

[0329] In another preferred embodiment, the assessment of atrial fibrillation treatment serves as guidance for atrial fibrillation treatment. As used herein, the term "guidance" preferably refers to adjusting the intensity of treatment based on the determination of biomarkers, specifically BMP10-type peptides, during treatment, such as increasing or decreasing the dosage of oral anticoagulants.

[0330] In another preferred embodiment, the assessment of atrial fibrillation treatment is a stratification of atrial fibrillation treatment. Therefore, subjects eligible for a particular atrial fibrillation treatment should be identified. As used herein, the term "stratification" preferably refers to selecting appropriate treatment based on a given or specific risk, the identified molecular pathway, and / or the expected efficacy of a particular drug or procedure. Patients with few or no symptoms related to the arrhythmia, based on detected or predicted risk, will be eligible for ventricular rate control, cardioversion, or ablation; otherwise, they will only receive antithrombotic therapy. Treatment can be differentiated between patients with low success rates and those with high success rates based on detected or predicted risk, depending on preoperative blood biomarkers that serve as predictors of PVI or AF recurrence after ablation.

[0331] The definitions and explanations given above, with necessary modifications to the details, are applicable to the methods of the present invention described below (unless otherwise stated). For example, the terms "subject," "sample," and "determination" have been defined above. Furthermore, determination preferably includes contacting the sample with at least one reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO:1.

[0332] Interestingly, the basic research of this invention shows that BMP10-type peptides can be used to estimate the risk, presence, and / or severity of cerebrovascular injury as a cause of dementia and cognitive impairment in patients such as those with atrial fibrillation. Specifically, studies have shown that the biomarker is associated with the presence of white matter lesions (WML) in patients. Higher levels of the biomarker are associated with a greater degree of white matter lesions (and vice versa). Therefore, it can serve as a marker for assessing the degree of white matter lesions.

[0333] Furthermore, the present invention relates to a method for assessing the degree of white matter lesions in a subject, the method comprising:

[0334] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0335] b) Assess the degree of white matter lesions in the subject based on the quantity determined in step a).

[0336] The term “white matter lesion” is well known in the field. White matter refers to regions of the central nervous system (CNS) that are primarily composed of myelinated axons. White matter lesions (also known as “white matter disease”) are typically detected on brain MRI in older individuals as white matter hyperintensity (WMH) or “leukoaraiosis.” The presence and extent of WMH have been described as imaging biomarkers for cerebrovascular disease and as important predictors of lifelong risk of stroke, cognitive impairment, and functional impairment (Chutinet A, Rost NS. White matter disease as a biomarker for long-term cerebrovascular disease and dementia. Curr Treat Options Cardiovasc Med. 2014; 16(3):292. doi:10.1007 / s11936-013-0292-z). The determination of RET allows for the assessment of the extent of WML, i.e., the burden of WML. Thus, biomarkers allow for the quantification of WML in subjects, i.e., they are markers of functional brain tissue volume loss.

[0337] The severity of white matter lesions can be represented by the Fazekas score (Fazekas, JB Chawluk, A Alavi, HIHurtig, and RA Zimmerman, American Journal of Roentgenology 1987 149:2,351-356). The Fazekas score ranges from 0 to 3, with 0 indicating no white matter lesions, 1 indicating mild white matter lesions, 2 indicating moderate white matter lesions, and 3 indicating severe white matter lesions.

[0338] WML severity can be caused by clinical resting stroke. Therefore, the biomarker RET can be further used to help assess whether a subject has experienced one or more resting strokes in the past, i.e., before obtaining the sample.

[0339] Resting stroke, also known as resting cerebrovascular accident, is known in the art and described, for example, by Conen et al. (Conen et al., J Am Coll Cardiol 2019; 73:989–99), the entire disclosure of which is incorporated herein by reference. Resting stroke is a clinically resting stroke in a patient without a clinical history of stroke or transient ischemic attack (TIA). Therefore, subjects to be tested should have no known history of stroke and / or TIA.

[0340] Furthermore, the present invention relates to a method for assessing whether a subject has experienced one or more resting strokes, the method comprising:

[0341] a) Determine the amount of one or more BMP10-type peptides in samples from subjects.

[0342] b) Compare the quantities determined in step a) with the reference, and

[0343] c) Assess whether the subject has experienced one or more resting strokes.

[0344] The following are preferably used as diagnostic algorithms: a biomarker level greater than the reference indicates a subject who has experienced one or more resting strokes, and / or a level less than the reference indicates a subject who has not experienced a resting stroke.

[0345] Therefore, the present invention relates to a method for predicting dementia, such as vascular dementia and / or Alzheimer's disease, in a subject, the method comprising:

[0346] a) Determine the amount of one or more BMP10-type peptides in samples from subjects.

[0347] b) Compare the quantities determined in step a) with the reference, and

[0348] c) Predict the risk of the subject developing dementia.

[0349] Preferably, as used herein, the term "predicting dementia" refers to assessing the probability that a subject will develop dementia. Typically, it predicts whether a subject is at risk of developing dementia (and therefore at increased risk) or not at risk of developing dementia (and therefore at decreased risk).

[0350] In one embodiment, the prediction window is a period of 1 to 3 years. Therefore, the risk of developing dementia within 1 to 3 years is predicted. In a preferred embodiment, the prediction window is a period of 1 to 10 years. Therefore, the risk of a subject developing dementia within 1 to 10 years can be predicted. Preferably, the prediction window is calculated from the completion of the method of the present invention. More preferably, the prediction window is calculated from the time point when the sample to be tested was obtained.

[0351] As used herein, the term "dementia" preferably refers to a condition characterized by a loss of cognitive and intellectual function, usually progressive, but without perceptual or consciousness impairment caused by various diseases, but most commonly associated with structural brain disorders. The most common type of dementia is Alzheimer's disease, accounting for 50% to 70% of cases. Other common types include vascular dementia (25%), Lewy body dementia, and frontotemporal dementia. The term "dementia" includes, but is not limited to, HIV-related dementia, Alzheimer's disease, early-onset dementia, senile dementia, catatonic dementia, Lewy body dementia (diffuse Lewy body disease), multiple infarct dementia (vascular dementia), paralytic dementia, post-traumatic dementia, early-onset dementia, and vascular dementia.

[0352] In one embodiment, the term dementia refers to vascular dementia, Alzheimer's disease, Lewy body dementia, and / or frontotemporal dementia. Therefore, the risk of developing vascular dementia, Alzheimer's disease, Lewy body dementia, and / or frontotemporal dementia is predicted.

[0353] In one embodiment, the risk of developing "Alzheimer's disease" is predicted. The term "Alzheimer's disease" is well known in the art. Alzheimer's disease is a chronic neurodegenerative disease that typically begins slowly and gradually worsens over time. As the disease progresses, symptoms may include language problems, disorientation, mood swings, loss of motivation, inability to care for oneself, and behavioral problems.

[0354] In one embodiment, the risk of developing "vascular dementia" is predicted. The term "vascular dementia" preferably refers to the progressive loss of memory and other cognitive functions caused by damage or disease to blood vessels in the brain. Therefore, the term should refer to dementia symptoms caused by problems with blood circulation in the brain. It may occur after a stroke or accumulate over time.

[0355] Regarding the prediction of dementia risk, the diagnostic algorithm is preferably as follows: preferably, a level greater than a reference biomarker indicates a subject at risk of dementia, and / or a level less than a reference biomarker indicates a subject at no risk of dementia.

[0356] The definitions and explanations given above, with necessary modifications to the details, are applicable to the methods of the present invention described below (unless otherwise stated). For example, the terms "subject," "sample," and "determination" have been defined above. Furthermore, determination preferably includes contacting the sample with at least one reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO:1.

[0357] The present invention further relates to a method for assisting in the assessment of atrial fibrillation, the method comprising the following steps:

[0358] a) Provide at least one sample from the subject.

[0359] b) In at least one sample provided in step a), determine the amount of one or more BMP10-type peptides, and optionally, determine the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP-3 (fatty acid-binding protein 3), and

[0360] c) Provide physicians with information about the amount of one or more identified BMP10-type peptides and optionally about the amount of at least one other identified biomarker to aid in the assessment of atrial fibrillation.

[0361] The physician should be the attending physician, i.e., the physician who requests the determination of biomarkers. The methods described above should assist the attending physician in assessing atrial fibrillation. Therefore, this method does not include the diagnosis, prediction, monitoring, differentiation, and differential diagnosis mentioned in the methods for assessing atrial fibrillation described above.

[0362] Step a) of the above sample acquisition method does not include extracting the sample from the subject. Preferably, the sample is obtained by receiving a sample from the subject. Therefore, the sample can be delivered.

[0363] In one embodiment, the method is an auxiliary method for stroke prediction, the method comprising the following steps:

[0364] a) Provide at least one sample from the subjects, as mentioned in this article, in conjunction with methods for assessing atrial fibrillation, particularly methods for predicting atrial fibrillation.

[0365] b) Determine the amount of one or more BMP10-type peptides and the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP-3 (fatty acid-binding protein 3), and

[0366] c) Provide physicians with information about the amount of one or more identified BMP10-type peptides and optionally about the amount of at least one other identified biomarker to aid in the prediction of stroke.

[0367] The present invention further relates to a method comprising:

[0368] a) Provides the assay of one or more BMP10-type peptides and optionally at least one additional assay of other biomarkers selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP-3 (fatty acid-binding protein 3), and

[0369] b) Provide a description of the use of the measurement results obtained or available through the measurement in the assessment of the atrial fibrillation.

[0370] The purpose of the aforementioned method is preferably to assist in the assessment of atrial fibrillation.

[0371] The description should include a protocol for implementing the method for assessing atrial fibrillation as described above. Furthermore, the description should include at least one reference value for one or more BMP10-type peptides, and optionally at least one reference value for a dilinacin peptide.

[0372] "Assay" preferably refers to a kit suitable for determining the amount of a biomarker. The term "kit" is explained below. For example, the kit should contain at least one assay for one or more BMP10-type peptides and at least one additional reagent optionally selected from the group consisting of: a reagent specifically binding to natriuretic peptides, a reagent specifically binding to ESM-1, a reagent specifically binding to Ang2, and a reagent specifically binding to FABP-3. Thus, one to four assays may be present. Assays for one to four biomarkers may be provided in a single kit or in separate kits.

[0373] The test result obtained or available through the test is the value of the amount of one or more biomarkers.

[0374] In one embodiment, step b) includes providing instructions on using test results obtained or available through the one or more tests in the prediction of stroke (as described elsewhere herein).

[0375] The present invention further relates to a computer-implemented method for assessing atrial fibrillation, the method comprising:

[0376] a) Receiving at the processing unit a value for the amount of one or more BMP10-type peptides, and optionally receiving at least one additional value for the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2, and FABP-3 (fatty acid-binding protein 3), wherein the amount of the one or more BMP10-type peptides and optionally the amount of at least one other biomarker have been determined in a sample from the subject.

[0377] b) The processing unit compares one or more values ​​received in step (a) with one or more reference values, and

[0378] c) Assess atrial fibrillation based on the comparison step b).

[0379] The above method is a computer-implemented method. Preferably, all steps of the computer-implemented method are executed by one or more processing units of a computer (or computer network). Therefore, the evaluation in step (c) is performed by the processing unit. Preferably, the evaluation is based on the result of step (b).

[0380] As described elsewhere in this document, one or more values ​​received in step (a) should be derived from determining the amount of biomarker from the subject. Preferably, this value is a value representing the concentration of the biomarker. This value will typically be received by the processing unit by uploading or sending the value to the processing unit. Alternatively, the processing unit may receive the value by inputting it via a user interface.

[0381] In embodiments of the foregoing method, one or more reference values ​​proposed in step (b) are established from memory. Preferably, the reference values ​​are established from memory.

[0382] In an embodiment of the computer-implemented method of the present invention described above, the result of the evaluation performed in step c) is provided via a display configured to present the result.

[0383] In an embodiment of the computer-implemented method of the present invention described above, the method may include a further step of transmitting information regarding the assessment performed in step c) to the subject's electronic medical record.

[0384] Methods for diagnosing heart failure

[0385] Furthermore, studies in this invention have shown that determining the amount of one or more BMP10-type peptides in samples from subjects allows for the diagnosis of heart failure. Therefore, this invention also contemplates a method for diagnosing heart failure based on the amount of one or more BMP10-type peptides (and optionally further based on natriuretic peptides, ESM-1, Ang2, and / or FABP3).

[0386] The definitions given above in relation to the assessment of atrial fibrillation, with necessary modifications to the details, apply to the following (unless otherwise stated).

[0387] Therefore, the present invention further relates to a method for diagnosing heart failure in a subject, the method comprising the following steps:

[0388] a) Determine the amount of one or more BMP10-type peptides in samples from subjects, and

[0389] b) Diagnose heart failure by comparing the amount of one or more BMP10-type peptides with a reference amount.

[0390] Methods for diagnosing heart failure may further include determining the amount of at least one other biomarker selected from the group consisting of natriuretic peptide, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP-3 (fatty acid binding protein 3), and comparing it with an appropriate reference amount.

[0391] Therefore, methods for diagnosing heart failure may include the following steps:

[0392] a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from a subject, and

[0393] b) Diagnose heart failure by comparing the amount of one or more BMP10-type peptides with a reference amount of one or more BMP10-type peptides, and optionally by comparing the amount of at least one other biomarker with a reference amount of said at least one other biomarker.

[0394] As used herein, the term "diagnosis" refers to assessing whether a subject, as described by the method according to the invention, suffers from heart failure. The actual diagnosis of whether a subject suffers from heart failure may include other steps such as confirming the diagnosis. Therefore, the diagnosis of heart failure is understood as an aid to the diagnosis of heart failure. Thus, in the context of this invention, the term "diagnosis" also encompasses assisting a physician in assessing whether a subject suffers from heart failure.

[0395] The term "heart failure" (abbreviated as "HF") is well known to those skilled in the art. As used herein, the term preferably refers to impaired cardiac systolic and / or diastolic function known to those skilled in the art, accompanied by obvious signs of heart failure. Preferably, heart failure referred to herein is also chronic heart failure. Heart failure according to the invention includes obvious and / or late-stage heart failure. In obvious heart failure, the subject exhibits heart failure symptoms known to those skilled in the art.

[0396] In one embodiment of the invention, the term "heart failure" refers to heart failure with a reduced left ventricular ejection fraction (HFrEF). In another embodiment of the invention, the term "heart failure" refers to heart failure with a preserved left ventricular ejection fraction (HFpEF).

[0397] Heart failure (HF) can be classified into different degrees of severity. According to the NYHA (New York Heart Association) classification, patients with heart failure are categorized into NYHA I, NYHA II, NYHA III, and NYHA IV. In NYHA class I, structural and functional changes have occurred in the pericardium, myocardium, coronary circulation, or heart valves. Full recovery is not possible, and treatment is required. NYHA class I patients do not have obvious cardiovascular symptoms, but there is objective evidence of functional impairment. NYHA class II patients have mild limitations in physical activity. NYHA class III patients exhibit significant limitations in physical activity. NYHA class IV patients are unable to perform any physical activity without discomfort. They exhibit symptoms of heart failure at rest.

[0398] This functional classification is supplemented by the latest classifications from the American College of Cardiology and the American Heart Association (see J. Am. Coll. Cardiol. 2001; 38; 2101-2113, updated in 2005, see J. Am. Coll. Cardiol. 2005; 46; e1-e82). Four stages, A, B, C, and D, are defined. Stages A and B are not HF, but are considered helpful in identifying patients early before the development of “true” HF. It is best to define patients in stages A and B as those with risk factors for developing HF. For example, patients with coronary artery disease, hypertension, or diabetes who have not yet shown left ventricular (LV) dysfunction, hypertrophy, or malformation of the ventricle would be considered stage A, while asymptomatic patients who show LV hypertrophy and / or LV dysfunction would be designated stage B. Stage C indicates patients with current or past symptoms of HF associated with underlying structural heart disease (most patients have HF), while stage D indicates patients with truly refractory HF.

[0399] As used herein, the term "heart failure" preferably includes stages A, B, C, and D of the ACC / AHA classification described above. Furthermore, the term includes NYHA I, NYHA II, NYHA III, and NYHA IV. Therefore, subjects may or may not exhibit typical symptoms of heart failure.

[0400] In a preferred embodiment, the term "heart failure" refers to stage A of heart failure according to the ACC / AHA classification described above, or particularly stage B of heart failure. Identifying these early stages, especially stage A, is advantageous because treatment can begin before irreversible damage occurs.

[0401] Subjects to be tested according to the diagnostic methods for heart failure are preferably not diagnosed with atrial fibrillation. However, it is also assumed that a subject may have atrial fibrillation. The term "atrial fibrillation" is defined in conjunction with the methods used to assess heart failure.

[0402] Preferably, the subject to be tested in conjunction with a method for diagnosing heart failure is suspected of having heart failure.

[0403] The term "reference value" has been defined in conjunction with the methods for assessing atrial fibrillation. The reference value used in methods for diagnosing heart failure can, in principle, be determined as described above.

[0404] Preferably, an increase in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in a sample from the subject compared to a reference level indicates that the subject has heart failure, and / or a decrease in the amount of one or more BMP10-type peptides (and optionally at least one other biomarker such as ESM-1, Ang-2, FABP-3 and / or natriuretic peptides) in a sample from the subject compared to a reference level indicates that the subject does not have heart failure.

[0405] In one embodiment of a method for diagnosing heart failure, the method further includes the step of recommending and / or initiating heart failure treatment based on the diagnostic result. Preferably, treatment is recommended or initiated if the subject is diagnosed with heart failure. Preferably, heart failure treatment comprises administering at least one drug selected from the group consisting of: angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers, beta-blockers, and aldosterone antagonists. Examples of angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers, beta-blockers, and aldosterone antagonists will be described in the next section.

[0406] Methods for predicting the risk of hospitalization in subjects

[0407] Some subjects are known to develop heart failure more quickly, thus increasing their risk of hospitalization due to heart failure. Identifying these subjects as early as possible is important because it will allow for treatments to prevent or delay the progression of heart failure.

[0408] Advantageously, in the basic research of this invention, it was found that the amount of one or more BMP10-type peptides in the subject samples allows for the identification of subjects at risk of hospitalization for heart failure. For example, subjects in the fourth quartile of the analyzed cohort (Example 4) with BMP10 levels had approximately a fourfold increased risk of hospitalization for heart failure over a three-year period compared to subjects in the first quartile.

[0409] Therefore, the present invention also relates to a method for predicting the risk of hospitalization for heart failure in a subject, the method comprising the following steps:

[0410] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from said subject, and

[0411] (b) Compare the amount of one or more BMP10-type peptides to a reference amount of one or more BMP10-type peptides, and optionally compare the amount of at least one other biomarker to a reference amount of said at least one other biomarker.

[0412] The definitions and explanations regarding the assessment methods for atrial fibrillation and the diagnostic methods for heart failure are preferably applicable to methods for predicting the risk of hospitalization for heart failure in subjects.

[0413] The above method may further include step (c) predicting the risk of hospitalization for heart failure in the subject. Therefore, steps (a), (b), and (c) are preferably as follows:

[0414] (a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) and, optionally, the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1 (endothelial cell-specific molecule), Ang2 (angiopoietin 2), and FABP3 (fatty acid-binding protein 3) in at least one sample from said subject, and

[0415] (b) Compare the amount of BMP10-type peptide to a reference amount, and optionally compare the amount of at least one other biomarker to a reference amount of said at least one other biomarker, and

[0416] (c) Predict the risk of hospitalization for heart failure in subjects.

[0417] Preferably, the prediction is based on the comparison result of step (b).

[0418] The term "hospitalization" is easily understood by those skilled in the art and preferably refers to the admission of a subject to a hospital, particularly in the context of hospitalized patients. Hospitalization should be due to heart failure. Therefore, heart failure should be the cause of hospitalization. Preferably, hospitalization is due to acute or chronic heart failure. Therefore, heart failure includes both acute and chronic heart failure. More preferably, hospitalization is due to acute heart failure. Thus, the risk of hospitalization for heart failure is predicted for the subject.

[0419] The term "heart failure" has been defined above. This definition applies accordingly. In some embodiments, hospitalization is due to heart failure classified as stage C or D according to the ACC / AHA classification. The ACC / AHA classification is well known in the art and is described, for example, in Hunt et al. (Journal of the American College of Cardiology, Vol. 46, No. 6, September 20, 2005, pp. e1-e82, ACC / AHA Practice Guide), the entire contents of which are incorporated herein by reference.

[0420] According to the method described above, the risk of hospitalization due to heart failure in a subject should be predicted. Therefore, subjects at risk of hospitalization due to heart failure or those not at risk of hospitalization due to heart failure can be identified. Therefore, according to the method described above, the term "predicted risk" as used herein preferably refers to assessing the probability of hospitalization due to heart failure. In some embodiments, the method described above allows for the differentiation between subjects at risk of hospitalization due to heart failure and subjects not at risk of hospitalization due to heart failure.

[0421] According to the present invention, the term "predicted risk" is understood as assisting in the prediction of the risk of hospitalization due to heart failure. In principle, the final prediction will be made by a physician and may include further diagnostic results.

[0422] As those skilled in the art will understand, risk prediction is generally not intended to be correct for 100% of the subjects. Preferably, the term refers to the ability to predict the statistically significant portion of the subjects in an appropriate and correct manner. Whether a portion is statistically significant can be determined by those skilled in the art using various well-known statistical assessment tools (e.g., determining confidence intervals, p-value determination, Student's t-test, Mann-Whitney test, etc.) without further effort. See Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983 for details. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98%, or at least 99%. Preferred p-values ​​are 0.1, 0.05, 0.01, 0.005, or 0.0001.

[0423] Preferably, the risk / probability within a certain time window is predicted. In some embodiments, the prediction window is calculated from the completion of the method of the present invention. In particular, the prediction window is calculated from the time point when the sample to be tested is obtained.

[0424] In a preferred embodiment of the invention, the prediction window is preferably an interval of at least 1 year, at least 2 years, at least 3 years, at least 4 years, at least 5 years, or at least 10 years, or any intermittent time range. In another preferred embodiment of the invention, the prediction window is preferably a period of up to 5 years, more preferably up to 4 years, or most preferably up to 3 years. Thus, risks are predicted for a maximum of three, four, or five years. Furthermore, a prediction window of 1 to 5 years is envisioned. Alternatively, the prediction window can be a period of 1 to 3 years.

[0425] In a preferred embodiment, the risk of hospitalization for heart failure within three years is predicted.

[0426] Preferably, subjects analyzed by the method described above are assigned to either a group of subjects at risk of hospitalization due to heart failure or a group of subjects without risk of hospitalization due to heart failure. Among the at-risk subjects, preferably, those with an increased risk of hospitalization due to heart failure (particularly within the prediction window). Preferably, this risk is increased compared to the risk in the subject cohort (i.e., a group of subjects). Among the subjects without risk, preferably, those with a decreased risk of hospitalization due to heart failure (particularly within the prediction window). Preferably, this risk is decreased compared to the average risk in the subject cohort (i.e., a group of subjects). Therefore, the method of the present invention allows for the differentiation between increased and decreased risks. Preferably, within a 3-year prediction window, the risk of hospitalization due to heart failure for at-risk subjects is preferably 12% or greater, more preferably 15% or greater, or most preferably 20% or greater. Preferably, within a 3-year prediction window, the risk of hospitalization due to heart failure for subjects without risk is preferably less than 10%, more preferably less than 8%, or most preferably less than 7%.

[0427] The term "reference value" has been defined elsewhere in this document. That definition applies accordingly. The reference value used in the methods described above should allow for the prediction of the risk of hospitalization due to heart failure. In some embodiments, the reference value should allow for the differentiation between subjects at risk of hospitalization due to heart failure and subjects not at risk of hospitalization due to heart failure. In some embodiments, the reference value is a predetermined value.

[0428] Preferably, the amount of one or more BMP10-type peptides in the sample from the subject is increased compared to a reference level, indicating that the subject is at risk of hospitalization for heart failure. More preferably, the amount of one or more BMP10-type peptides in the sample from the subject is decreased compared to a reference level, indicating that the subject is not at risk of hospitalization for heart failure.

[0429] If more than one biomarker is identified, the following applies:

[0430] Preferably, the amounts of one or more BMP10-type peptides and at least one other biomarker (or more) in the sample from the subject are increased compared to their respective reference levels, indicating that the subject is at risk of hospitalization for heart failure. More preferably, the amounts of one or more BMP10-type peptides and at least one other biomarker (or more) in the sample from the subject are decreased compared to their respective reference levels, indicating that the subject is not at risk of hospitalization for heart failure.

[0431] The term "sample" has been defined elsewhere in this document. That definition applies accordingly. In some embodiments, a sample is a blood, serum, or plasma sample.

[0432] The term "subject" has been defined elsewhere herein. That definition applies accordingly. In some embodiments, the subject is a human subject. Preferably, the subject is 50 years of age or older, more preferably 60 years of age or older, and most preferably 65 years of age or older. Further, it is envisioned that the subject is 70 years of age or older. Additionally, it is envisioned that the subject is 75 years of age or older. Similarly, the subject may be between 50 and 90 years of age.

[0433] In one embodiment, the subject being tested has a history of heart failure. In another embodiment, the subject being tested does not have a history of heart failure.

[0434] The method according to the invention can assist in personalized medicine. In a preferred embodiment, the above-described method for predicting the risk of hospitalization for heart failure in a subject further includes the step of recommending and / or initiating at least one suitable treatment if the subject is predicted to be at risk of hospitalization for heart failure. Therefore, the invention also relates to a treatment method.

[0435] Preferably, the term "treatment" used in the context of methods for predicting the risk of hospitalization for heart failure in subjects includes lifestyle changes, dietary protocols, physical interventions, and pharmacological treatment, i.e., treatment with one or more drugs. Preferably, the treatment aims to reduce the risk of hospitalization for heart failure. In one embodiment, the treatment is the administration of one or more drugs. Preferably, the drug is selected from the group consisting of angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), aldosterone antagonists, and beta-blockers.

[0436] In some embodiments, the drug is a beta-blocker, such as propranolol, metoprolol, bisoprolol, carvedilol, buxinolol, and nebivolol. In some embodiments, the drug is an ACE inhibitor, such as enalapril, captopril, ramipril, and quindopril. In some embodiments, the drug is an angiotensin II receptor blocker, such as losartan, valsartan, irbesartan, candesartan, telmisartan, and eprosartan. In some embodiments, the drug is an aldosterone antagonist, such as eplerenone, spironolactone, canrenone, mexrenone, and prorenone.

[0437] Lifestyle changes include quitting smoking, moderate alcohol consumption, increasing physical activity, losing weight, sodium (salt) restriction, weight management and healthy eating, and daily fish oil and salt restriction.

[0438] Furthermore, the present invention relates to uses of the following (particularly in vitro uses, such as in samples from subjects):

[0439] i) one of a variety of BMP10-type peptides and optionally at least one other biomarker selected from the group consisting of natriuretic peptide, ESM-1 (endothelial cell-specific molecule), Ang2 and FABP-3 (fatty acid binding protein 3), and / or

[0440] ii) at least one reagent that specifically binds to one or more BMP10-type peptides, and optionally at least one additional reagent selected from the group consisting of: reagents that specifically bind to natriuretic peptides, reagents that specifically bind to ESM-1, reagents that specifically bind to Ang2, and reagents that specifically bind to FABP-3.

[0441] Used to a) assess atrial fibrillation, b) predict the risk of stroke in subjects, and / or c) diagnose heart failure.

[0442] Terms mentioned in connection with the foregoing uses, such as “sample,” “subject,” “detector,” “specific binding,” “atrial fibrillation,” and “assessment of atrial fibrillation,” have been defined in conjunction with the methods used to assess atrial fibrillation. Definitions and interpretations apply accordingly.

[0443] This invention further relates to BMP10-type peptides and / or at least one reagent that specifically binds to BMP10-type peptides for predicting dementia in subjects. in vitro use.

[0444] This invention further relates to a BMP10-type peptide and / or at least one reagent that specifically binds to the BMP10-type peptide for assessing the degree of white matter lesions in subjects. in vitro use.

[0445] This invention further relates to a BMP10-type peptide and / or at least one reagent that specifically binds to the BMP10-type peptide for assessing whether a subject has experienced one or more resting strokes. in vitro use.

[0446] The present invention further relates to the use of BMP10-type peptide and / or at least one reagent that specifically binds to BMP10-type peptide for predicting the risk of hospitalization for heart failure in a subject (particularly for in vitro use, e.g., in a sample from a subject).

[0447] Preferably, the above-described use is for in vitro applications. Furthermore, the detection reagent is preferably an antibody, such as a monoclonal antibody (or its antigen-binding fragment).

[0448] The present invention also relates to a kit. In one embodiment, the kit of the present invention comprises at least one reagent that specifically binds to one or more BMP10-type peptides and at least one additional reagent selected from the group consisting of: a reagent that specifically binds to natriuretic peptides, a reagent that specifically binds to ESM-1, a reagent that specifically binds to Ang2, and a reagent that specifically binds to FABP-3.

[0449] Preferably, the kit is adapted to perform the methods of the present invention, namely, methods for assessing atrial fibrillation, diagnosing heart failure, or predicting the risk of a subject being hospitalized due to heart failure. Alternatively, the kit includes instructions for performing the methods.

[0450] In some embodiments, at least one agent that specifically binds to a BMP10-type peptide is at least one antibody or fragment thereof described in the next section (titled “Antibodies of the Invention”).

[0451] As used herein, the term "kit" refers to a collection of the aforementioned components, preferably provided separately or in a single container. The container also includes instructions for carrying out the methods of the invention. These instructions may be in the form of a manual or may be provided by computer program code capable of performing the calculations and comparisons mentioned in the methods of the invention and, when implemented on a computer or data processing device, accordingly establishing an assessment or diagnosis. The computer program code may be provided on a data storage medium or device such as an optical storage medium (e.g., an optical disc) or directly on a computer or data processing device. Furthermore, the kit may preferably contain a standard amount of a BMP10-type peptide for calibration purposes. In a preferred embodiment, the kit further contains a standard amount of at least one other biomarker described herein (such as natriuretic peptide or ESM-1) for calibration purposes.

[0452] In one embodiment, the kit is used for in vitro assessment of atrial fibrillation. In an alternative embodiment, the kit is used for in vitro diagnosis of heart failure. In an alternative embodiment, the kit is used for in vitro prediction of the risk of hospitalization due to heart failure.

[0453] In the methods and uses of the invention described above and in the claims, the antibodies (fragments thereof) described in the next section may be used.

[0454] The definitions and explanations provided above, after necessary modifications to the details, apply to the following text.

[0455] The antibody of this invention:

[0456] The present invention also relates to an antibody (such as a monoclonal antibody) or a fragment thereof that binds one or more BMP10-type peptides. In particular, it should bind NT-proBMP10.

[0457] The antibody (or a fragment thereof) should be able to bind to at least one amino acid region of a polypeptide having the sequence shown in SEQ ID NO:1 disclosed in the previous section.

[0458] Therefore, the antibody (or fragment thereof) of the present invention should be able to bind NT-proBMP10, that is, it should be able to bind amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1. Since the region is contained in preproBMP10 and proBMP10, the antibody (or fragment thereof) should be able to bind preproBMP10, proBMP10, and NT-proBMP10. However, the antibody (or fragment) should not bind BMP10, i.e., mature BMP10.

[0459] In a preferred embodiment, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, should be able to bind to amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO:1, i.e., it should be able to bind to an epitope contained in the region of the polypeptide shown in SEQ ID NO:1 that begins at amino acid 37 and ends at amino acid 299.

[0460] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to amino acid regions 110 to 200 of the polypeptide shown in SEQ ID NO:1, i.e., the at least one reagent binds to an epitope contained in that region.

[0461] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to amino acid regions 37 to 195, such as amino acid regions 37 to 185, of the polypeptide shown in SEQ ID NO:1, i.e., the at least one reagent binds to an epitope contained in that region.

[0462] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to amino acid regions 160 to 299 of SEQ ID NO:1, such as amino acid regions 171 to 299, i.e., the at least one reagent binds to an epitope contained in that region.

[0463] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to amino acid regions 160 to 195, such as amino acid regions 171 to 185, of SEQ ID NO:1.

[0464] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to the epitope (SLFGDVFSEQD, SEQ ID NO 2) contained in amino acid regions 37 to 47 of SEQ ID NO:1.

[0465] For example, an antibody or fragment thereof that binds to one or more BMP10-type peptides, such as NT-proBMP10, can bind to the epitope (LESKGDNEGERNMLV, SEQ ID NO:3) contained in amino acid regions 171 to 185 of SEQ ID NO:1. For example, the at least one reagent binds to the epitope (SKGDNEGER, SEQ ID NO:4) contained in amino acid regions 173 to 181 of SEQ ID NO:1.

[0466] For example, an antibody or fragment thereof that binds to one or more BMP10 type peptides, such as NT-proBMP10, can bind to the epitope (SSGPGEEAL, SEQ ID NO:5) contained in amino acid regions 291 to 299 of SEQ ID NO:1.

[0467] In the foundational research of this invention, the inventors have generated a monoclonal antibody against human NT-proBMP10 (in rabbits). A detailed kinetic screening was performed on 280 antibodies. In this screening, antibodies exhibiting favorable kinetic properties were identified, making them particularly suitable for detecting BMP10-type peptides, such as NT-proBMP10 and / or proBMP10. For example, antibodies exhibiting a rapid complex formation rate of the NT-proBMP10-antibody complex were identified. Furthermore, the antibodies exhibited slow dissociation of the complex, resulting in a long half-life. Clones 11A5, 11C10, 13G6, 14C8, 2H8, and 9E7 showed considerably rapid complex formation rates and complex half-lives t / 2diss > 15 minutes. Clone 13G6 showed the slowest dissociation (k d <1.0E-04s -1 This results in a complex half-life t / 2-diss > 115 minutes.

[0468] The identified antibodies are as follows: 11A2, 11A5, 11C10, 13G6, 14C8, 2H8, 3H8, 8G5, and 9E7. The sequences of the antibodies are provided in Tables A through D below.

[0469] For the four antibodies mentioned above, linear epitopes can be detected (see the Examples section and...). Figure 12 Two of the antibodies bind to the same region.

[0470] The epitope of 3H8 contains the sequence shown in SEQ ID NO:2 (SLFGDVFSEQD).

[0471] The epitope of 11A5 contains the sequence shown in SEQ ID NO:3 (LESKGDNEGERNMLV).

[0472] The epitope of 13G6 contains the sequence (SKGDNEGER) shown in SEQ ID NO:4.

[0473] The epitope of 2H8 contains the sequence (SSGPGEEAL) shown in SEQ ID NO:5.

[0474] Antibodies (or fragments thereof) or reagents used to determine the amount of BMP10-type peptides can therefore bind to the aforementioned region.

[0475] Table A summarizes the amino acid sequence of the variable heavy (VH) chain of the antibody of the present invention.

[0476] Table A: Variable Heavy (VH) Chain Domains of the Invention

[0477]

[0478]

[0479] Table B summarizes the amino acid sequence of the antibody variable light chain of the present invention (see below).

[0480] Table B: Variable Light Chain (VL) Chain Domains of the Invention

[0481]

[0482]

[0483] Heavy chain CDR sequences are shown in Table C. Light chain CDR sequences are shown in Table D below. For example, the complementarity-determining regions (CDRs) of antibodies can be identified using the system described by Kabat et al. in Sequences of Proteins of Immunological Interest, 5th edition, U.S. Department of Health and Human Services, PHS, NIH, NIH Publication No. 91-3242, 1991.

[0484]

[0485] The antibody (or fragment thereof) of the present invention should specifically bind to the preproBMP, proBMP10, and NT-proBMP10 peptides. Therefore, the antigen-binding protein should bind to preproBMP, proBMP10, and NT-proBMP10 within amino acid regions 22 to 316 of SEQ ID NO:1, as described in more detail elsewhere herein. It should be understood that it does not bind to mature BMP10. However, it can be used in combination with antigen-binding proteins that bind mature BMP10.

[0486] This invention is not limited to the identified antibodies, namely 11A2, 11A5, 11C10, 13G6, 14C8, 2H8, 3H8, 8G5, and 9E7, but also includes variants that bind to one or more BMP10-type variants, preferably in the same region. For example, variants of 13G6 should bind to the same or substantially the same epitopes as 13G6.

[0487] Preferably, the antibody or fragment thereof of the present invention should comprise a light chain variable domain (or a variant thereof) and a heavy chain variable domain (or a variant thereof) of antibody 11A2, 11A5, 11C10, 13G6, 14C8, 2H8, 3H8, 8G5, or 9E7. For example, it may comprise a light chain variable domain (or a variant thereof) and a heavy chain variable domain (or a variant thereof) of 13G6, or, for example, it may comprise a light chain variable domain (or a variant thereof) and a heavy chain variable domain (or a variant thereof) of antibody 11C10.

[0488] In a preferred embodiment, the antibody or antigen-binding fragment of the present invention comprises a heavy chain variable domain (or a variant thereof) selected from VH1, VH2, VH3, VH4, VH5, VH6, VH7, VH8, and VH9 as shown in Table A and / or a light chain variable domain (or a variant thereof) selected from VL1, VL2, VL3, VL4, VL5, VL6, VL7, VL8, and VL9 as shown in Table B. Each heavy chain variable domain shown in Table A may be combined with each light chain variable domain shown in Table B. In a preferred embodiment, the heavy chain variable domains in Table A are combined with the corresponding light chain variable domains in Table B, for example, VH1 with VL1, VH2 with VL2, VH3 with VL3, etc.

[0489] In some embodiments, the polypeptide variants mentioned in the present invention should have an amino acid sequence that differs due to at least one amino acid substitution, deletion, and / or addition, wherein the amino acid sequence of the variant is still preferably at least 80%, 85%, 90%, 95%, 98%, or 99% identical to the amino sequence of the polypeptide.

[0490] In some embodiments, the antibody variant (or fragment antibody) comprises a heavy chain variable domain and / or a light chain variable domain, wherein the heavy chain variable domain is at least 80%, 85%, 90%, 95%, 98%, or 99% identical to the heavy chain variable domain comprising the sequence shown in SEQ ID NO: 7, 8, 9, 10, 11, 12, 13, 14, or 15 (see Table A), and the light chain variable domain is at least 80%, 85%, 90%, 95%, 98%, or 99% identical in ascending order of priority to the light chain variable domain comprising the sequence shown in SEQ ID NO: 16, 17, 18, 19, 20, 21, 22, 23, or 24 (see Table B).

[0491] Alternatively or additionally, variants of the antibody or fragments thereof may comprise the antibody or fragments thereof of the present invention, which comprise six CDRs of the parent antibody, wherein the six CDRs differ by no more than a total of three, two, or particularly one amino acid addition, substitution, and / or deletion from their respective parent CDRs (see Tables C and D).

[0492] Therefore, in some embodiments, the antibody or fragment thereof of the present invention may comprise a heavy chain variable domain (at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to the heavy chain variable domain comprising the sequences shown in SEQ ID NO: 7, 8, 9, 10, 11, 12, 13, 14, or 15 (see Table A)) and / or a light chain variable domain (at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to the light chain variable domain comprising the sequences shown in SEQ ID NO: 16, 17, 18, 19, 20, 21, 22, 23, or 24 in ascending order of priority (see Table B)). Each heavy chain variable domain shown may be combined with each light chain variable domain. However, it is preferred to combine the corresponding sequences (e.g., SEQ ID NO: 7 with SEQ ID NO: 16).

[0493] The "percentage (%) amino acid sequence identity" relative to a reference polypeptide sequence is defined as the percentage of amino acid residues in the candidate sequence that are identical to those in the reference polypeptide sequence after aligning the candidate sequence with the reference sequence and introducing gaps (if necessary) to achieve the maximum percentage of sequence identity. Preferably, standard parameters are applied to determine the degree of sequence identity between the two sequences. Preferably, the degree of identity is determined by comparing two best-aligned sequences in a comparison window, wherein the amino acid sequence fragments in the comparison window may contain additions or deletions (e.g., gaps or protrusions) to achieve optimal alignment compared to the reference sequence (excluding additions or deletions). The percentage is calculated by determining the number of positions where identical amino acid residues are present in both sequences to obtain the number of matching positions, dividing the number of matching positions by the total number of positions in the comparison window, and multiplying the result by 100 to obtain the percentage of sequence identity. The optimal sequence alignment for comparison can be performed using the Smith and Waterman homology alignment algorithm (Add. APL. Math. 2:482 (1981)), the Needleman and Wunsch homology alignment algorithm (J. Mol. Biol. 48:443 (1970)), the Pearson and Lipman search similarity method (Proc. Natl. Acad. Sci. (USA) 85:2444 (1988)), through the computerized execution of these algorithms (e.g., GAP, BESTFIT, BLAST, PASTA, and TFASTA in the Wisconsin Genetics Package, Genetics Computer Group (GCG), 575 Science Dr., Madison, WI), or by visual inspection. Given that two sequences have been identified for comparison, GAP and BESTFIT are preferred to determine their optimal alignment, thus establishing their similarity. The default values ​​for gap weight (5.00) and gap weight length (0.30) are preferably used. In one embodiment, the percentage equality between the two amino acid sequences was determined using the Needleman and Wunsch algorithm (Needleman 1970, J.Mol.Biol.(48):444-453), which has been incorporated into the needle program in the EMBOSS software package (EMBOSS: European Molecular Biology Open Software Suite, Rice, P., Longden, I. and Bleasby, A., Trends in Genetics 16(6), 276-277, 2000), the BLOSUM62 scoring matrix, and a gap opening penalty of 10 and a gap widening penalty of 0.5.Preferred, non-limiting examples of parameters used for aligning two amino acid sequences using the needle program are the default parameters, which include the EBLOSUM62 scoring matrix, a gap opening penalty of 10, and a gap widening penalty of 0.5.

[0494] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:7 and a light chain variable domain having the sequence shown in SEQ ID NO:16.

[0495] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:8 and a light chain variable domain having the sequence shown in SEQ ID NO:17.

[0496] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:9 and a light chain variable domain having the sequence shown in SEQ ID NO:18.

[0497] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:10 and a light chain variable domain having the sequence shown in SEQ ID NO:19.

[0498] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:11 and a light chain variable domain having the sequence shown in SEQ ID NO:20.

[0499] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:12 and a light chain variable domain having the sequence shown in SEQ ID NO:21.

[0500] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:13 and a light chain variable domain having the sequence shown in SEQ ID NO:22.

[0501] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:14 and a light chain variable domain having the sequence shown in SEQ ID NO:23.

[0502] In one aspect, the antibody or fragment thereof of the present invention comprises a heavy chain variable domain having the sequence shown in SEQ ID NO:15 and a light chain variable domain having the sequence shown in SEQ ID NO:24.

[0503] Alternatively or additionally, the antibodies or fragments thereof of the present invention include

[0504] (a) A light chain variable structural domain, which includes:

[0505] (a1) Light chain CDR1, which differs from the light chain CDR1 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0506] (a2) Light chain CDR2, which differs from the light chain CDR2 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0507] (a3) Light chain CDR3, which differs from the light chain CDR3 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0508] (b) Heavy-chain variable structural domains, which include:

[0509] (b1) Heavy chain CDR1, which differs from the heavy chain CDR1 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0510] (b2) Heavy chain CDR2, which differs from the heavy chain CDR2 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion in total, and

[0511] (b3) Heavy chain CDR3, which differs from the heavy chain CDR3 shown in Table C by no more than three, two or more, or in particular one amino acid addition, substitution and / or deletion.

[0512] For example, the antibody or fragment thereof of the present invention includes

[0513] (a) A light chain variable structural domain, which includes:

[0514] (a1) Light chain CDR1, which differs from the light chains CDRL1-4 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0515] (a2) Light chain CDR2, which differs from the light chains CDRL2-4 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0516] (a3) Light chain CDR3, which differs from the light chains CDRL3-4 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0517] (b) Heavy-chain variable structural domains, which include:

[0518] (b1) Heavy chain CDR1, which differs from heavy chain CDRH1-1 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0519] (b2) Heavy chain CDR2, which differs from heavy chain CDRH2-4 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0520] (b3) Heavy chain CDR3, which differs from the heavy chain CDRH3-4 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0521] Preferably, the antibody or fragment thereof of the present invention comprises

[0522] (c) Light chain variable structural domain, which includes:

[0523] (a1) The light chain CDR1 shown in Table D (and therefore the light chain CDR1 sequence selected from SEQ ID NO:34-42),

[0524] (a2) The light chain CDR2 shown in Table D (and therefore the light chain CDR2 sequences selected from SEQ ID NO:52-60), and

[0525] (a3) The light chain CDR3 shown in Table D (and therefore the light chain CDR3 sequence selected from SEQ ID NO:70-78),

[0526] as well as

[0527] (d) Heavy-chain variable structural domains, which include:

[0528] (b1) The heavy chain CDR1 shown in Table C (and therefore the heavy chain CDR1 sequence selected from SEQ ID NO:25-33),

[0529] (b2) The heavy chain CDR2 shown in Table C (and therefore the heavy chain CDR2 sequences selected from SEQ ID NO:43-51), and

[0530] (b3) The heavy chain CDR3 shown in Table C (and therefore the heavy chain CDR3 sequence selected from SEQ ID NO:61-69).

[0531] More preferably, the antibody or its antigen-binding fragment of the present invention comprises six CDRs of 11A2, six CDRs of 11A5, six CDRs of 11C10, six CDRs of 13G6, six CDRs of 14C8, six CDRs of 2H8, six CDRs of 3H8, six CDRs of 8G5, or six CDRs of 9E7 (or six CDRs differing from the six CDRs of the heavy chain by no more than a total of three, two, or particularly one amino acid addition, substitution, and / or deletion).

[0532] In a particularly preferred embodiment, the antibody or antigen-binding fragment of the present invention comprises six CDRs of 13G6. Therefore, the antibody or fragment comprises the heavy chain CDRH1 (NYAMS) of SEQ ID NO:28, the heavy chain CDRH2 (YISASGNTYYASWVKG) of SEQ ID NO:46, the heavy chain CDRH3 (GYSGWISGTWA) of SEQ ID NO:64, the light chain CDRL1 (QSSQSVVNNNRLS) of SEQ ID NO:37, the light chain CDRL2 (RASTLAS) of SEQ ID NO:55, and the light chain CDRL3 (LGDYVSYSEAA) of SEQ ID NO:73.

[0533] In another particularly preferred embodiment, the antibody or antigen-binding fragment of the present invention comprises six CDRs of 11C10. Therefore, the antibody or fragment comprises the heavy chain CDRH1 (RNLMS) of SEQ ID NO:27, the heavy chain CDRH2 (SINFRNITWYASWAKG) of SEQ ID NO:45, the heavy chain CDRH3 (GVYVNSNGYYSL) of SEQ ID NO:63, the light chain CDRL1 (QASQSVSNLLA) of SEQ ID NO:36, the light chain CDRL2 (GASKLES) of SEQ ID NO:54, and the light chain CDRL3 (QTYWGGDGTSYLNP) of SEQ ID NO:72.

[0534] In some embodiments, the antibody or fragment thereof comprises six CDRs of 11A2. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 11A5. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 14C8. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 2H8. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 3H8. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 8G5. In some embodiments, the antibody or fragment of the present invention comprises six CDRs of 9E7.

[0535] It should be understood that the variable structural domain of the light chain should contain the CDR of the light chain, and the variable structural domain of the heavy chain should contain the CDR of the heavy chain.

[0536] Furthermore, it is envisioned that the antibody or fragment thereof of the present invention comprises

[0537] (a) A light chain variable structural domain that is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical in ascending order of preference to light chain variable structural domains comprising the sequences shown in SEQ ID NO: 16, 17, 18, 19, 20, 21, 22, 23, or 24 (see Table B), wherein the light chain variable structural domain comprises

[0538] (a1) Light chain CDR1, which differs from the light chain CDR1 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0539] (a2) Light chain CDR2, which differs from the light chain CDR2 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0540] (a3) Light chain CDR3, which differs from the light chain CDR3 shown in Table D by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0541] (b) and a heavy chain variable structural domain that is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to a heavy chain variable structural domain comprising the sequence shown in SEQ ID NO: 7, 8, 9, 10, 11, 12, 13, 14, or 15 (see Table A), wherein the heavy chain variable structural domain comprises

[0542] (b1) Heavy chain CDR1, which differs from the heavy chain CDR1 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion.

[0543] (b2) Heavy chain CDR2, which differs from the heavy chain CDR2 shown in Table C by no more than three, two, or particularly one amino acid addition, substitution, and / or deletion in total, and

[0544] (b3) Heavy chain CDR3, which differs from the heavy chain CDR3 shown in Table C by no more than three, two or more, or in particular one amino acid addition, substitution and / or deletion.

[0545] In one embodiment, the antibody or fragment thereof of the present invention comprises

[0546] (a) A light chain variable structural domain that is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical in ascending order of preference to light chain variable structural domains comprising the sequences shown in SEQ ID NO: 16, 17, 18, 19, 20, 21, 22, 23, or 24 (see Table B), wherein the light chain variable structural domain comprises

[0547] (a1) The light chain CDR1 shown in Table D,

[0548] (a2) The light chain CDR2 shown in Table D, and

[0549] (a3) The light chain CDR3 shown in Table D

[0550] (b) and a heavy chain variable structural domain that is at least 80%, 85%, 90%, 95%, 98%, 99%, or 100% identical to a heavy chain variable structural domain comprising the sequence shown in SEQ ID NO: 7, 8, 9, 10, 11, 12, 13, 14, or 15 (see Table A), wherein the heavy chain variable structural domain comprises

[0551] (b1) The heavy chain CDR1 shown in Table C,

[0552] (b2) The heavy chain CDR2 shown in Table C, and

[0553] (b3) Heavy chain CDR3 shown in Table C.

[0554] The term "antibody" refers to an immunoglobulin or immunoglobulin-like molecule, including, but not limited to, IgA, IgD, IgE, IgG, and IgM, combinations thereof, and similar molecules produced during immune responses in any vertebrate, such as mammals like goats, rabbits, and mice, as well as in non-mammalian species, such as shark immunoglobulins. In some embodiments, the antibody may be a rabbit antibody. The term "antibody" includes the complete immunoglobulin and an "antibody fragment" or "antigen-binding fragment" that specifically binds to a target molecule. In a preferred embodiment, the antibody is an IgG antibody.

[0555] Specifically, the term "antibody" refers to a polypeptide ligand containing at least a light chain and a heavy chain immunoglobulin variable region that specifically recognizes and binds to an epitope of an antigen. An antibody consists of a heavy chain and a light chain, each of which has a variable region, referred to as a variable heavy chain (VH) region and a variable light chain (VL) region. The VH and VL regions together are responsible for binding the antigen recognized by the antibody. Typically, the antibodies of this invention have a heavy (H) chain and a light (L) chain interconnected by disulfide bonds. As used herein, the term "light chain" includes a full-length light chain and fragments thereof having a sufficient variable region sequence to confer binding specificity. A full-length light chain includes a variable region domain (VL) and a constant region domain (CL). The variable region domain of the light chain is located at the amino terminus of the polypeptide. The term "heavy chain" includes a full-length heavy chain and fragments thereof having a sufficient variable region sequence to confer binding specificity. A full-length heavy chain includes a variable region domain (VH) and a constant region domain (CL). H and three constant region structural domains C H 1. C H 2 and C H 3, V H The domain is located at the amino terminus of the polypeptide, C H The domain is at the carboxyl terminus, where C H 3. The part closest to the carboxyl terminus of the polypeptide.

[0556] Five main heavy chain classes (or isotypes) determine the functional activity of antibody molecules: IgM, IgD, IgG, IgA, and IgE. Both heavy and light chains contain constant and variable regions (also called "domains"). Together, the variable regions of the heavy and light chains specifically bind to antigens. The variable regions of both the light and heavy chains contain "framework" regions, also known as "complementarity-determining regions" or "CDRs," which are interrupted by three hypervariable regions. CDRs are primarily responsible for binding to antigenic epitopes. The CDRs of each chain are typically called CDR1, CDR2, and CDR3, numbered sequentially starting from the N-terminus, and are usually identified by the chain in which a particular CDR is located. Therefore, VH CDR3 is located in the variable domain of the heavy chain from which the antibody found it, while VL CDR1 is CDR1 from the variable domain of the light chain from which the antibody found it.

[0557] The antibodies or fragments thereof of the present invention may be single-chain antibodies, IgD antibodies, IgE antibodies, IgM antibodies, IgG antibodies, or fragments thereof. For example, the antibody may be an IgG antibody, such as an IgG1 antibody, an IgG2 antibody, an IgG3 antibody, or an IgG4 antibody. In one embodiment, the antibody or fragment thereof has been recombined.

[0558] This invention also covers fragments of the monoclonal antibodies of the present invention. These fragments should be immunofunctional fragments, i.e., antigen-binding fragments. Therefore, the fragments of the monoclonal antibodies of the present invention should be capable of binding one or more BMP10-type peptides. Thus, as used herein, the term "immunofunctional fragment" of an antibody refers to a portion of an antibody lacking at least some amino acids present in the full-length chain but capable of specifically binding one or more BMP10-type peptides. Immunoglobulin fragments with immunofunctionality include Fab, Fab', F(ab')2, and Fv fragments. How to generate antigen-binding fragments is well known in the art. For example, fragments can be generated by enzymatic cleavage of the antibodies of the present invention. Furthermore, fragments can be generated by synthetic or recombinant techniques. Fab fragments are preferably generated by papain digestion of the antibody, Fab' fragments by pepsin digestion and partial reduction, and F(ab')2 fragments by pepsin digestion. Fv fragments are preferably generated by molecular biology techniques.

[0559] In one embodiment, the antibody fragment of the present invention is an F(ab`)2 fragment. In another embodiment, the antibody fragment of the present invention is an F(ab`)2 fragment. In yet another embodiment, the antibody fragment of the present invention is a Fab fragment. In still another embodiment, the antibody fragment of the present invention is an Fv fragment.

[0560] Antibody fragments can also be biantibodies. A biantibody is a small antibody fragment with two antigen-binding sites. Biantibodies preferably contain a heavy chain variable domain linked to a light chain variable domain in the same polypeptide chain.

[0561] The antibodies of the present invention are preferably monoclonal antibodies. As used herein, the term "monoclonal antibody" refers to an antibody produced by a single B lymphocyte or by a cell transfected with the light and heavy chain genes of the antibody.

[0562] In the embodiments, the antibodies of the present invention are isolated antibodies. Therefore, the antibodies should be purified antibodies. Antibody purification can be achieved using methods well known in the art.

[0563] The monoclonal antibody or fragment thereof of the present invention (and the reagents referred to in the preceding section) should be able to bind to one or more BMP10-type peptides (such as NT-proBMP10). The terms “bind,” “specifically bind,” “capable of binding,” and “capable of specifically binding” are preferably used interchangeably herein. The term “specifically bind” or “specifically bind” means that the binding pair molecules exhibit a binding reaction to each other under conditions where they do not significantly bind to other molecules. When referring to a protein or peptide as a biomarker, the term “specifically bind” or “specifically bind” preferably refers to the binding reagent at a concentration of at least 10 7 M -1 Affinity (“binding constant” K)a The binding reaction between a target molecule and its corresponding biomarker. The term "specific binding" or "specifically binding" preferably refers to a binding affinity of at least 10 for the target molecule. 8 M -1 Or even more preferably at least 10 9 M -1 Affinity. The term "specific" or "specifically" is used to indicate that other molecules present in the sample do not significantly bind to the binding reagent specific to the target molecule. However, as explained above, the reagent referred to herein should not only be able to bind NT-proBMP10, but also preproBMP10 and proBMP10.

[0564] K D It is the dissociation constant, which can be determined by methods such as surface plasmon resonance (SPR). GE-Healthcare Uppsala, Sweden). Preferably, the antibody (or its antigen-binding fragment) binds to one or more BMP10-type peptides, in some embodiments, having one or more BMP10-type peptides (particularly human NT-proBMP10) in the nanomolar or sub-nanomolar range at 37°C. D value.

[0565] Another way to describe the kinetic binding properties of an antibody to its antigen is to decompose the dissociation equilibrium constant into its kinetic rate contribution, since there exists an association rate k. a constant and dissociation rate constant k d Association rate k a The constant characterizes the rate of antibody / antigen complex formation and is time- and concentration-dependent. In some embodiments, the antibody of the present invention (or its antigen-binding fragment) bound to one or more BMP10-type peptides (particularly human NT-proBMP10) as referred to herein has a kinematic constant greater than 1.0E+05M-1s-1 at 37°C. a Value (for its antigen).

[0566] Dissociation rate constant (k d The dissociation rate constant represents the rate of dissociation of the antibody from its antigen. Therefore, the dissociation rate constant indicates the probability that the complex will disintegrate per unit time. The lower the dissociation rate constant, the stronger the binding between the antibody and its antigen. In some embodiments, the antibody of the present invention (or its antigen-binding fragment) bound to one or more BMP10-type peptides (particularly human NT-proBMP10) as referred to herein has a kinematic constant of less than 1.1E-03s-1 at 37°C. d value.

[0567] In some embodiments, K D value, kd value and k a The value is determined as described in the Examples section.

[0568] The term "epitope" refers to a protein determinant that can specifically bind to an antibody. Therefore, the term preferably refers to the portion of a polypeptide, as referred to herein, that can be specifically bound by the antibody (or fragment thereof) of the present invention. Epitopes typically consist of a large group of chemically active surfaces of molecules such as amino acids, and generally possess specific three-dimensional structural features and specific charge characteristics. The difference between conformational and non-conformational epitopes is that, in the presence of denaturing solvents, binding to the former, but not the latter, is lost.

[0569] The antibodies or antigen-binding fragments thereof of the present invention can be used in methods relating to determining the amount of BMP10-type peptides as referred to herein. For example, the antibodies or fragments thereof allow for the determination of the amount of BMP10-type peptides in a sample used in diagnostic methods.

[0570] Therefore, the present invention relates to a method for determining the amount of one or more BMP10-type peptides using the antibodies or fragments of the present invention. Preferred methods for determining the amount of biomarkers, such as sandwich assays, are described in the section entitled “Determination of the Amount of Biomarkers”.

[0571] For example, a method for determining the amount of one or more BMP10-type peptides may include the step of contacting a sample containing one or more BMP10-type peptides with at least one reagent bound to amino acid regions 22 to 316 of the polypeptide shown in SEQ ID NO:1, thereby allowing the formation of a complex of the BMP10-type peptide and at least one reagent, and determining the amount of the formed complex.

[0572] Furthermore, the antibody or fragment thereof may contain a tag, i.e., it may be covalently or non-covalently coupled to a tag that allows the detection and measurement of the binding reagent. Preferred tags are disclosed above. For example, the tag may be a biotinylated tag, a radioactive tag, a fluorescent tag, a chemiluminescent tag, an electrochemiluminescent tag, a gold tag, or a magnetic tag as described in more detail above.

[0573] In one embodiment, the antibody or a fragment thereof (such as the (ab')2 fragment) is biotinylated. In another embodiment, the antibody or a fragment thereof is ruthenium-modified (as described above).

[0574] The present invention further relates to the in vitro use of the antibodies or fragments thereof of the present invention for determining one or more BMP10-type peptides in a sample.

[0575] This invention also relates to a kit comprising at least one monoclonal antibody or a fragment thereof of the present invention. The term kit has been defined above.

[0576] Furthermore, antibody pairs that allow for improved detection of BMP10-type peptides in sandwich assays were identified (Example 13). Specifically, biotinylated and ruthenium-treated clones 2H8, 3H8, 8G5, 9E7, 11A5, 11C10, 14C8, and 13G6 were tested in multiple sandwiches to identify sandwich partners. The combination of clones 13G6 and 11C10 showed high-level performance regardless of orientation. Similar observations were made for the combination of 3H8 and 9E7. Other combinations achieved good ratios. Although only in one orientation, other combinations also achieved good ratios.

[0577] Therefore, the present invention relates to a kit comprising a first antibody or antigen-binding fragment thereof binding to one or more BMP10-type peptides and a second antibody or antigen-binding fragment thereof binding to one or more BMP10-type peptides. Preferably, the first antibody and the second antibody bind to different epitopes. The first antibody is selected from 2H8, 3H8, 8G5, 9E7, 11A5, 11C10, 14C8, 13G6 (or variants thereof), and the second antibody is selected from 2H8, 3H8, 8G5, 9E7, 11A5, 11C10, 14C8, 13G6 (or variants thereof).

[0578] Both antibodies or fragments thereof can be labeled. For example, the first antibody or fragment thereof can be ruthenium-modified, and the second antibody or fragment thereof can be biotinylated (or vice versa).

[0579] In some embodiments, the first antibody is 2H8. In some embodiments, the first antibody is 3H8. In some embodiments, the first antibody is 8G5. In some embodiments, the first antibody is 9E7. In some embodiments, the first antibody is 11A5. In some embodiments, the first antibody is 11C10. In some embodiments, the first antibody is 14C8. In some embodiments, the first antibody is 13G6.

[0580] Preferred antibody combinations are disclosed in Tables 13 and 14 of Example 14.

[0581] For example, the first antibody could be 11C10, and the second antibody could be 13G6 (and vice versa).

[0582] For example, the first antibody could be 3H8, and the second antibody could be 9E7 (or vice versa).

[0583] In one embodiment, the kit comprises a biotinylated first monoclonal antibody or a fragment thereof that specifically binds to one or more BMP10-type peptides, wherein the first antibody is 11C10 (or a variant thereof), and a ruthenium-modified second monoclonal antibody or a fragment thereof, wherein the second antibody is 13G6 (or a variant thereof).

[0584] In one embodiment, the kit comprises a biotinylated first monoclonal antibody or a fragment thereof that specifically binds to one or more BMP10-type peptides, wherein the first antibody is 13G6 (or a variant thereof), and a ruthenium-modified second monoclonal antibody or a fragment thereof, wherein the second antibody is 11C10 (or a variant thereof).

[0585] This invention also relates to host cells that produce the antibodies of the invention or antigen-binding fragments thereof. In a preferred embodiment, the host cell that produces the antibodies of the invention is a hybridoma cell. Furthermore, the host cell can be any type of cell system that can be engineered to produce antibodies according to the invention. For example, the host cell can be an animal cell, particularly a mammalian cell, such as HEK cells. In one embodiment, HEK293 (human embryonic kidney cells), such as the HEK293-F cells used in the examples section, or CHO (Chinese hamster ovary) cells, are used as the host cell. In another embodiment, the host cell is a non-human animal or mammalian cell.

[0586] The host cell preferably contains at least one polynucleotide encoding the antibody of the present invention or a fragment thereof. For example, the host cell contains at least one polynucleotide encoding the light chain of the antibody of the present invention and at least one polynucleotide encoding the heavy chain of the antibody of the present invention. The polynucleotide should be operatively linked to a suitable promoter.

[0587] The attached image shows:

[0588] Figure 1 Measurement of BMP10 ELISA in three patient groups (paroxysmal atrial fibrillation, persistent atrial fibrillation, and sinus rhythm).

[0589] Figure 2 ROC curve of BMP10 in paroxysmal Afib; AUC = 0.68

[0590] Figure 3 ROC curve of BMP10 in persistent Afib; AUC = 0.90 (Exploratory Afib group: patients with a history of atrial fibrillation, including 14 paroxysmal Afib, 16 persistent Afib and 30 controls)

[0591] Figure 4 BMP10 [unit: ng / ml] to differentiate between patients with and without heart failure.

[0592] Figure 5 BMP10 as a differentiator for heart failure; ROC curve of BMP10; AUC = 0.76

[0593] Figure 6Kaplan-Meier curves, using BMP-10 quartiles, indicate the risk of hospitalization for heart failure in patients with a prior history of heart failure.

[0594] Figure 7 Kaplan-Meier curves, using BMP-10 quartiles, indicate the risk of hospitalization for heart failure in patients without a prior history of heart failure.

[0595] Figure 8 The Kaplan-Meier curve shows the risk of stroke using the BMP-10 dichotomy (median).

[0596] Figure 9 Kaplan-Meier curves, using BMP-10 quartiles, indicate the risk of AFib recurrence in patients undergoing pulmonary vein isolation (BEAT-PVI).

[0597] Figure 10 Kinetic characteristics of the binding of propeptide BMP10 to selected 8 mAbs at 37 °C obtained by SPR. The image shows a superposition of sensor plots as the concentration of propeptide BMP10 increases, ranging from c = 3.7 to 300 nM.

[0598] A) 2H8 B) 3H8 C) 8G5

[0599] D)9E7 E)11A5 F)11C10

[0600] G)14C8 H)13G6

[0601] Figure 11 Normalized dissociation phase overlay diagram of 8 mAb-binding propeptide BMP10 at 37℃

[0602] Figure 12 Epitopes of the four monoclonal antibodies of this invention

[0603] Figure 13 Detection of NT-proBMP10 and detection of mature BMP10

[0604] Figure 14 Measurement of circulating BMP-10 in EDTA plasma samples from the SWISS AF study, Fazekas score <2 (no) and Fazekas score ≥2 (yes): detection of WML / prediction of resting stroke risk: assessment of circulating BMP-10 levels.

[0605] Example

[0606] The present invention is illustrated by the following examples only. In any case, these examples should not be interpreted in a way that limits the scope of the invention.

[0607] Example 1: Plotting test - Patients diagnosed with atrial fibrillation compared to those diagnosed based on different cyclic NT-proBMP10 levels.

[0608] The mapping study was conducted on patients undergoing open-heart surgery. Samples were obtained prior to anesthesia and surgery. Patients were electrophysiologically characterized using high-density epicardial mapping (HDM), a multi-electrode array. The trial included 14 patients with paroxysmal atrial fibrillation, 10 patients with persistent atrial fibrillation, and 28 control patients, matched as best possible (age, sex, comorbidities). NT-proBMP10 was identified in serum samples from the mapping study. Elevated NT-proBMP10 levels were observed in patients with atrial fibrillation compared to controls. NT-proBMP10 levels were elevated in patients with paroxysmal atrial fibrillation compared to matched controls, and in patients with persistent atrial fibrillation compared to controls.

[0609] Furthermore, the biomarker ESM-1 was identified in samples from the plotting cohort. Interestingly, the results showed that the combined identification of NT-proBMP10 and ESM-1 allowed for an AUC increase to 0.92 to differentiate between persistent AF and SR (sinus rhythm).

[0610] Furthermore, the biomarker FABP-3 was identified in samples from the plotting cohort. Interestingly, the results showed that the combined identification of NT-proBMP10 and FABP-3 allowed for an AUC increase to 0.73, distinguishing paroxysmal AF from SR (sinus rhythm).

[0611] Example 2: Heart Failure Group

[0612] The heart failure group included 60 patients with chronic heart failure. Patients diagnosed with heart failure were defined as having typical signs and symptoms, and objective evidence of structural or functional abnormalities of the heart at rest, according to ESC guidelines. Patients aged 18 to 80 years with ischemic or dilated cardiomyopathy or severe valvular disease and able to provide consent were included in the study. Patients who had experienced acute myocardial infarction, pulmonary embolism, or stroke within the past 6 months, and who further had severe pulmonary hypertension and end-stage renal disease, were excluded. Patients primarily had NYHA stage II-IV heart failure.

[0613] The healthy control cohort included 33 participants. Health status was verified by assessing ECG and echocardiographic results. Participants with any abnormalities were excluded.

[0614] Elevated NT-proBMP10 levels were observed in serum samples from patients with heart failure compared to controls.

[0615] Example 3: Biomarker Measurement

[0616] NT-proBMP10 was measured in a research-grade ECLIA assay for bone morphogenetic protein 10 (BMP10); the ECLIA assay was performed by Roche Diagnostics, Germany.

[0617] To detect NT-proBMP10 in human serum and plasma samples, antibody sandwiches specifically binding to the N-terminal prodomain of BMP10 were used. These antibodies also bind to both proBMP10 and preproBMP10. Therefore, the sum of the amounts of the N-terminal prodomain, proBMP10, and preproBMP10 was determined. Based on structural predictions from findings of other BMP-type proteins, such as BMP9, indicating that BMP10 and proBMP10 remain in a complex, the detection of the N-terminal prodomain also reflects the amount of BMP10 bound to the prodomain. Furthermore, homodimeric forms of BMP10, as well as heterodimeric structures, such as those in combination with BMP9 or other BMP-type proteins, can be detected.

[0618] Example 4: SWISS AF Study - Risk Prediction for Hospitalization Due to Heart Failure

[0619] Data from the SWISS-AF study included 2,387 patients, 617 of whom had a history of heart failure (HF). BMP-10 was measured in these patients to assess its ability to predict the risk of hospitalization due to heart failure.

[0620] Because hospitalization for heart failure can occur in both patients with a history of heart failure and those without, the ability to predict future heart failure hospitalizations was independently assessed in both groups. During the follow-up period, a total of 233 patients were hospitalized for HF. Of these 233 hospitalizations, 125 occurred in patients with a prior history of HF.

[0621] Prediction of HF hospitalization in patients with a known history of HF

[0622] Table 1 shows the results of the Cox proportional hazards model, including patients with a known history of heart failure (HF). The dependent variable is the time until hospitalization for HF, and the independent variable is the log-2 transformed NT-proBMP10 value.

[0623] As evidenced by the hazard ratio and low p-value, NT-proBMP10 significantly predicts the risk of HF hospitalization in patients with a known history of HF. Since the NT-proBMP10 value underwent a log-2 transformation before being input into the model, the hazard ratio can be interpreted as a 3.43% increase in patient risk if the NT-proBMP10 value doubles.

[0624] Risk ratio 95% confidence interval p-value 3.43 2.23–5.27 <0.001

[0625] Table 1: Summary of Cox proportional hazards model using NT-proBMP10 (log-2 transformation) to predict the risk of HF hospitalization in patients with a known history of HF.

[0626] Figure 6 The Kaplan-Meier curves are shown, illustrating the risk of hospitalization for heart disease (HF) using the NT-proBMP10 quartiles. It can be seen that the risk increases with increasing NT-proBMP10 values, and patients with NT-proBMP10 levels in the highest quartile were observed to have the highest risk.

[0627] Prediction of HF hospitalization in patients with no known history of HF

[0628] Table 2 shows the results of the Cox proportional hazards model, including patients without a known history of HF. The dependent variable is the time until hospitalization for HF, and the independent variable is the log-2 transformed NT-proBMP10 value.

[0629] As evidenced by the hazard ratio and low p-value, NT-proBMP10 significantly predicted the risk of HF hospitalization in patients without a known history of HF. Since the NT-proBMP10 value underwent a log-2 transformation before being input into the model, the hazard ratio can be interpreted as a 3.43% increase in patient risk if the NT-proBMP10 value doubles.

[0630] Risk ratio 95% confidence interval p-value 4.24 2.52-7.15 <0.001

[0631] Table 2: Summary of Cox proportional hazards model using NT-proBMP10 (log-2 transformation) to predict the risk of HF hospitalization in patients with no known history of HF.

[0632] Figure 7 The Kaplan-Meier curves are shown, illustrating the risk of hospitalization for heart disease (HF) through the NT-proBMP10 quartiles. It can be seen that the risk increases with increasing NT-proBMP10 values, and patients with NT-proBMP10 levels in the two highest quartiles have the highest risk.

[0633] Example 5: SWISS AF Study - Stroke Risk Prediction

[0634] In a prospective, multicenter registry of patients with documented atrial fibrillation, the ability of circulatory NT-proBMP10 to predict stroke risk was demonstrated (see Case 3) (Conen D., Swiss Med Wkly. 2017 Jul 10; 147: w14467).

[0635] NT-proBMP10 results were available in 65 patients who experienced events and 2269 patients who did not.

[0636] To quantify the univariate prognostic value of NT-proBMP10, a proportional risk model with stroke outcomes was used.

[0637] The univariate prognostic performance of NT-proBMP10 was evaluated using two different combinations of prognostic information provided by NT-proBMP10.

[0638] The first proportional risk model includes NT-proBMP10 binarized at the median (2.2 ng / mL), thus comparing the risk of patients with NT-proBMP10 below or equal to the median with those with NT-proBMP10 above the median.

[0639] The second proportional risk model includes the original NT-proBMP10 level, but is converted to a log2 scale. The log2 conversion is performed to achieve better model calibration.

[0640] To obtain estimates of absolute survival in the two groups based on bipartite baseline NT-proBMP10 measurements (<=2.2 ng / mL vs. >2.2 ng / mL), Kaplan-Meier curves were created.

[0641] To assess whether the prognostic value of NT-proBMP10 was independent of known clinical and demographic risk factors, a weighted proportional Cox model was calculated, which also included the following variables: age and history of stroke / TIA / thromboembolism. These were the only significant clinical risk predictors across the entire cohort (including all control patients).

[0642] To assess the ability of existing risk scores to improve stroke outcomes using NT-proBMP10, the CHADS2, CHA2DS2-VASc, and ABC scores were extended using NT-proBMP10 (log2 transformed). This extension was achieved by creating a component risk model that included NT-proBMP10 and the corresponding risk scores as independent variables.

[0643] Compare the c-index of CHADS2, CHA2DS2-VASc, and ABC scores with the c-index of these extended models.

[0644] result

[0645] Table 1 shows the results of two univariate weighted proportional risk models, which include NT-proBMP10 after binarization or log2 transformation. In the model using log2-transformed NT-proBMP10 as a risk predictor, the association between the risk of experiencing stroke and the baseline value of NT-proBMP10 was not significant, but close to the significance level of 0.05.

[0646] For the model using binarized NT-proBMP10, the p-value is slightly higher. However, it can be argued that this effect may be statistically significant as the number of events increases.

[0647] The binarized NT-proBMP10 hazard ratio implies that the stroke risk in the patient group with baseline NT-proBMP10 > 2.2 ng / mL is 1.5 times higher than that in the patient group with baseline NT-proBMP10 <= 2.2 ng / mL. This can also be seen in the Kaplan-Meier curves showing the two groups. Figure 8 I saw it in the middle.

[0648] Results from a proportional risk model, including NT-proBMP10 as a linear risk predictor after log2 transformation, indicate that the log2 transformed value of NT-proBMP10 is proportional to the risk of experiencing stroke. A hazard ratio of 2.038 can be interpreted as a 2-fold decrease in NT-proBMP10 being associated with a 2.038-fold increase in stroke risk.

[0649] Table 1: Results of the univariate weighted proportional risk model for NT-proBMP10, including binarization and log2 transformation.

[0650]

[0651] Table 2 shows the results of the proportional hazards model including NT-proBMP10 (log2 transformed) combined with clinical and demographic variables. It can be seen that the prognostic value of NT-proBMP10 is reduced to some extent, but this can also be partly explained by the model's low statistical power.

[0652] Table 2: Multivariate proportional hazards model including NT-proBMP10 and related clinical and demographic variables.

[0653]

[0654] Table 3 shows the results of a weighted proportional risk model that combines the CHADS2 score with NT-proBMP10 (log2 transformed). In this model, NT-proBMP10 can add prognostic information to the CHADS2 score, but the p-value is higher than 0.05, which is tolerable for low sample sizes.

[0655] Table 3: Weighted proportional risk model combining CHADS2 score and NT-proBMP10 (log2 transformed)

[0656]

[0657] Table 4 shows the results of a weighted proportional risk model that combines the CHA2DS2-VASc score with NT-proBMP10 (log2 transformed). In this model, NT-proBMP10 can add prognostic information to the CHA2DS2-VASc score, but the p-value is higher than 0.05; however, this is tolerable for low sample sizes.

[0658] Table 4: Weighted proportional risk model combining CHA2DS2-VASc score and NT-proBMP10 (after log2 transformation)

[0659]

[0660] Table 5 shows the results of the weighted proportional hazard model, which combines the ABC score with NT-proBMP10 (log2 transformed). In this model, the estimated hazard ratio is reduced, and NT-proBMP10 may not improve prognostic performance in any way.

[0661] Table 5: Weighted proportional risk model combining ABC score and NT-proBMP10 (log2 transformed)

[0662]

[0663] Table 6 shows the estimated c-index for individual NT-proBMP10, CHADS2 score, CHA2DS2-VASc score, ABC score, and the weighted proportional hazard model (combining CHADS2, CHA2DS2-VASc, ABC scores with NT-proBMP10(log2)) in the case cohort selection. It can be seen that adding NT-proBMP10 increases the c-index of CHADS2, i.e., the CHA2DS2-VASc score, but does not increase the ABC score.

[0664] The differences in the c-index of CHADS2, CHA2DS2-VASc, and ABC scores were 0.019, 0.015, and -0.002, respectively.

[0665] Table 6: NT-proBMP10, CHA2DS2-VASc score, CHA2DS2-VASc score combined with NT-proBMP10 C-index, and CHADS2 and ABC scores and their C-index combined with NT-proBMP10.

[0666] C-index NT-proBMP10 univariate 0.577 <![CDATA[CHADS2]]> 0.629 <![CDATA[CHADS2+NT-proBMP10]]> 0.643 <![CDATA[CHA2DS2-VASc]]> 0.616 <![CDATA[CHA2DS2-VASc+NT-proBMP10]]> 0.627 ABC rating 0.692 ABC rating + NT-proBMP10 0.690

[0667] Example 6: BEAT-AF-PVI study - predicting the risk of recurrent AFIb after pulmonary vein isolation and catheter ablation.

[0668] The ability of NT-proBMP10 to predict the future risk of atrial fibrillation recurrence was evaluated in the BEAT-AF-PVI study. The BEAT-AF-PVI study (Knecht S, International Journal of Cardiology, Vol. 176, 2014, Vol. 3, pp. 645-650) was a prospective cohort study that included patients with atrial fibrillation undergoing pulmonary vein isolation. One of the study endpoints included was the time to first recurrence of atrial fibrillation. Therefore, the ability of circulating NT-proBMP10 to predict the risk of PVI and AFib recurrence after catheter ablation was validated in a prospective, multicenter registry of patients with documented atrial fibrillation (Zeljkovic I., Biochem Med. 2019; 29:020902).

[0669] NT-proBMP10 measurements and information on atrial fibrillation recurrence were available for 719 patients. Atrial fibrillation recurrence was observed in 310 of these 719 patients. NT-proBMP10 was measured using a study-grade ECLIA assay (from Roche Diagnostics, Germany).

[0670] The ability of NT-proBMP10 to predict the risk of recurrent atrial fibrillation was assessed using a Cox (proportional hazard) regression model. Table 1 shows the results of the proportional hazard model. The results indicate that the risk of recurrent atrial fibrillation increases significantly with increasing NT-proBMP10 values. Since NT-proBMP10 is included in the log2-transformed model to improve model calibration, a 2-fold increase in NT-proBMP10 can be interpreted as an increase in hazard ratio of 1.91.

[0671] Table 7: Summary of Cox regression model prediction of recurrent AFIB risk using log2 transformed values ​​of NT-proBMP10.

[0672] Risk ratio 95% CI (Risk Ratio) p-value NT-proBMP10(log2) 1.91 1.24–2.93 0.003

[0673] Alternatively, NT-proBMP10 can also be used in a binarized form (e.g., split by the median of 1.7 ng / mL) for atrial fibrillation risk prediction. Table 8 shows that the risk was 32% higher in patients with NT-proBMP10 levels above the median. This risk difference was again statistically significant.

[0674] Table 8: Summary of Cox regression model prediction of recurrent AFIB risk by observing binarized NT-proBMP10 of median value.

[0675] Risk ratio 95% CI (Risk Ratio) p-value NT-proBMP10 > 1.7 ng / mL 1.32 1.05–2.65 0.018

[0676] Example 7: Assessment of recurrent atrial fibrillation using cyclic NT-proBMP10

[0677] The GISSI AF study included patients with a history of atrial fibrillation (AF) but without significant left ventricular dysfunction or heart failure and exhibiting sinus rhythm (SR). All patients underwent three biochemical NT-proBMP10 assessments and electrocardiograms during a 1-year follow-up period.

[0678] Circulating NT-proBMP10 levels were determined in blood samples from n=281 patients with SR at 6-month visit who underwent blood collection and biomarker testing, and in blood samples from n=33 patients with persistent AF at 6-month visit who underwent blood collection and biomarker testing. An antibody targeting the propeptide BMP10 was used.

[0679] Table 9. Measurement of circulating NT-proBMP10 in GISSI AF patients with SR and persistent AF at 6-month visit.

[0680]

[0681] As shown in Table 9, at the 6-month visit of the GISSI AF study, NT-proBMP10 was observed in patients with persistent AF at the time of sampling compared with patients with SR at the time of blood collection.

[0682] Clearly, a small but very significant incremental change in NT-proBMP10 was detected in patients with AF compared to those with SR. In 33 patients with persistent AF at sampling time, compared to 281 patients with SR at sampling time, the median NT-proBMP10 values ​​were 2.31 [2.04–2.67] and 1.97 [1.75–2.33] ng / mL.

[0683] The sample of n=105 patients was in SR at 6 months of visit, but experienced more than one AF recurrence between randomization and 6 months of visit. All 105 patients spontaneously converted to SR.

[0684] -0-7 days n = 11 patients

[0685] -8-30 days n=17 patients

[0686] ->30 days, n=77 patients

[0687]

[0688] Table 10 Measurement of circulating NT-proBMP10 in GISSI AF patients in SR; case control group of patients who experienced recurrent AF a few days prior to sampling.

[0689] As shown in Table 10, elevated NT-proBMP10 titers were observed for up to 7 days after AF, spontaneously converting to SR. In 11 patients with AF up to 7 days prior to sampling, the median NT-proBMP10 titer was 2.30 [1.65–2.45] ng / mL, compared to 1.90 [1.75–2.25] ng / mL in 77 patients with AF more than 30 days prior to sampling. Surprisingly, the median NT-proBMP10 value observed up to 7 days after AF prior to sampling was very similar to that observed in patients with persistent AF. In 11 patients with SR following AF up to 7 days prior to sampling, the median NT-proBMP10 titer was 2.30 [1.65–2.45] ng / mL. As shown in Table 9, in 33 patients with persistent AF during SR, the median NT-proBMP-10 titer at sampling time was 2.31 [2.04–2.67] ng / mL.

[0690] Data assessment indicated that patients with NT-proBMP10 levels (independent of other biomarkers) higher than the reference value (>2.0 ng / mL in the study) were suspected of having recurrent atrial fibrillation after treatment intervention, such as after cardioversion. Distinguishing between poor and good treatment responses supports decisions about which patients might not benefit from treatment to avoid costly treatment and associated burdens, but which would be detrimental to patient outcomes.

[0691] It was even shown that elevated NT-proBMP10 levels could be detected in patients who developed sinus rhythm up to 7 days after a previous AF episode.

[0692] In summary, paroxysmal atrial fibrillation can be diagnosed in patients who develop sinus rhythm within 7 days by detecting elevated NT-proBMP10 levels alone or in combination with cardiac injury markers (e.g., cTNThs) and / or heart failure markers (NT-ProBNP).

[0693] Example 8: Detection of NT-proBMP10 and Detection of Mature BMP10

[0694] To compare the detection of mature BMP10 and NT-proBMP10, a head-to-head analysis was performed using the Elecsys prototype detection method as described in Example 14 and a BMP-10 ELISA (R&Dsystems DuoSet DY2926-05) for detecting mature BMP-10 homodimers (aa 317-424). Samples measured were from the plotting cohort described in Example 1. Patients diagnosed with atrial fibrillation were compared with a commercial immunoassay from R&Dsystems for detecting mature BMP10 based on different circulating BMP10 levels using the novel method for detecting NT-proBMP10. Serum samples from patients were electrophysiologically characterized using high-density epicardial mapping with a multi-electrode array (plotting study). Figure 13 (or the table below).

[0695] sample Mature BMP10 [pg / ml] diagnosis Patient 1 52.4 sinus rhythm Patient 2 605 sinus rhythm Patient 3 552 sinus rhythm Patient 4 217 Persistent AF Patient 5 2374 sinus rhythm Patient 6 74.5 Paroxysmal AF

[0696] Of the 52 samples, only 6 showed detectable levels of mature BMP10. These reflected 4 patients with sinus rhythm, 1 with paroxysmal atrial fibrillation, and 1 with persistent atrial fibrillation. NT-proBMP10 levels were detectable in all samples as described in Example 1.

[0697] The finding that only 11.5% of samples had detectable levels of mature BMP10 suggests that the physiologically mature form is underrepresented in circulation due to internalization after receptor binding. Therefore, NT-proBMP10 circulates in a more stable form and at higher detectable concentration levels, allowing for clinical decision-making based on circulating NT-proBMP10 levels.

[0698] Example 9: Immunizing rabbits to produce antibodies against BMP-10

[0699] Here, we describe the developed antibody capable of binding to bone morphogenetic protein 10 (NT-proBMP10). To generate this antibody, we immunized 12–16 week old NZW rabbits with rec.NT-proBMP10 (a polypeptide containing the first 312 amino acids of preproBMP10). All rabbits were repeatedly immunized. During the first month, animals were immunized weekly. From the second month onwards, animals were immunized monthly. For the first immunization, we dissolved 500 μg of immunogen in 1 mL of 140 mM NaCl and then emulsified the solution in 1 mL of CFA. For all subsequent immunizations, IFA was used instead of CFA.

[0700] Example 10: Development of antibodies binding to NT-proBMP10

[0701] To develop antibodies that bind to BMP-10, B cell clones as described in Seeber et al. (2014), PLoS One. 2014 Feb 4; 9(2) were used. First, PBMC cell pools were prepared from whole blood of immunized animals by ficoll gradient centrifugation. To enrich antigen-reactive B cells from the PBMC pools, randomly biotinylated NT-proBMP10 was immobilized on streptavidin-coated magnetic beads (Miltenyi). A protein concentration of 1 μg / ml was used for the bead coating. Therefore, the prepared PBMC pools of immunized animals were incubated with the NT-proBMP10-coated beads for 1 hour. MACS columns (Miltenyi) were used to enrich antigen-reactive B cells. B cell sorting and incubation were performed as described in Seeber et al. (2014), PLoS One. 2014 Feb 4; 9(2). To identify NT-proBMP10-responsive clones by ELISA, we immobilized NT-proBMP10 on the surface of 96-well plates at a concentration of 250 ng / ml. After washing, the plates were blocked with 5% BSA to reduce background signal. The plates were washed again, and 30 μl of primary rabbit B cell supernatant was transferred to the 96-well plates and incubated at room temperature for 1 hour. To detect antibodies binding to the screening peptide, HRP-labeled F(ab`)2 goat anti-rabbit Fcγ (Dianova) and ABTS (Roche) were added as substrates. As described in Seeber et al. (2014), PLoS One 2014 Feb 4; 9(2), clones that bound NT-proBMP10 were selected for subsequent molecular cloning.

[0702] Example 11: Kinetic Screening

[0703] Information antigens: Both propeptide BMP10 (R&D-Systems) and the internal construct "312" (pre-propeptide BMP10) represent the front domain of the N-terminal leader peptide of BMP10±19aa. Recombinant human BMP-10, R&D-Systems, catalog number: 2926-BP / CF, lot number: Qual0518031, disulfide-linked homodimer, MW 24.40kDa.

[0704] Kinetic screening

[0705] Kinetic screening was performed at 37°C on a GE Healthcare Biacore 4000 instrument. The Biacore CM5 Series S sensor was installed in the instrument and subjected to hydrodynamic treatment and pretreatment according to the manufacturer's instructions. The system buffer was HBS-EP (10 mM HEPES, 150 mM NaCl, 1 mM EDTA, 0.05% (w / v) P20). A system buffer supplemented with 1 mg / m³ LCMMD (carboxymethyl dextran, Fluka) was used as the sample buffer.

[0706] The rabbit antibody capture system was immobilized on the sensor surface. Following the manufacturer's instructions, the polyclonal goat anti-rabbit IgG Fc capture antibody GARbFcγ (code number 111-005-046; Jackson Immuno Research) was amine-conjugated using EDC / NHS Chemistry.

[0707] 30 μg / mL GARbFcγ in 10 mM sodium acetate buffer (pH 4.5) was pre-concentrated to points 1, 2, 4, and 5 in flow cells 1, 2, 3, and 4, and covalently bound to the CMD surface at a density of approximately 10,000 RU. The free activated carboxyl groups were then saturated with 1 M ethanolamine at pH 8.5.

[0708] Points 1 and 5 were used for interaction measurements, while points 2 and 4 served as references. Each rabbit antibody supernatant suspension was diluted 1:5 in sample buffer and injected at a flow rate of 10 μL / min for 2 minutes. Rabbit antibody capture levels (CL) were monitored in response units (RU).

[0709] Construct “312” at a single concentration of c = 150 nM was injected into rabbit mAbs displaying the anti-propeptide BMP10 at a rate of 30 μL / min. The association and dissociation phases were monitored for 5 min each. After each kinetically determined cycle, the rabbit clones were completely washed off the sensor surface by injecting 10 mM glycine at pH 1.5 at 20 μL / min for 30 sec. Reporting point binding late (BL) and stability late (SL) shortly before the end of propeptide BMP10 injection were extracted from the obtained sensor maps. These were used to characterize antibody / antigen binding stability. Furthermore, the dissociation rate constant k was calculated according to the Langmuir 1:1 model. d [s -1 According to the formula ln(2) / 60*k d Calculate the stability half-life (minutes) of the antigen / antibody complex. Calculate the molar ratio representing the binding stoichiometry using the following formula:

[0710] MW (antibody) / MW (antigen)*BL (antigen) / CL (antibody)

[0711] This method was used to test 280 rabbit antibodies. Eighteen antibodies were identified as having suitable kinetic properties conforming to the Elecsys platform standards.

[0712] Dynamic characterization

[0713] Detailed kinetic studies were performed using a BIAcore 8K instrument from GE Healthcare. Rabbit mAbs <propeptide BMP10> clones 2H8, 3H8, 8G5, 9F7, 11A5, 11C10, 14C8, and 13G6 were identified by kinetic screening and their binding to propeptide BMP10 was characterized in detail at 37 °C.

[0714] Install the Biacore CM5 series S sensor (batch number #10281824 / 10276998) onto the instrument.

[0715] Amine coupling of the captured molecule

[0716] The rabbit antibody capture system was immobilized on the sensor surface. Polyclonal goat anti-rabbit IgG Fc capture antibody GARbFcγ (serial number 111-005-046, batch number #131053; Jackson Immuno Research) was amine-coupled using EDC / NHS chemistry according to the manufacturer's instructions: run buffer: HBS-N buffer (10 mM HEPES, 150 mM NaCl, pH 7.4), activated by the EDC / NHS mixture; the capture antibody was diluted in conjugation buffer NaAc, pH 5.0, c = 30 μg / mL; finally, the remaining activated carboxyl groups were blocked by injection of 1 M ethanolamine at pH 8.5; the Ab density reached 11200–12700 RU.

[0717] Kinetic characterization of the binding of propeptide BMP10 to selected mAbs at 37 °C

[0718] The system and sample buffer were HBS-EP (10 mM HEPES, 150 mM NaCl, 1 mM EDTA, 0.05% (w / v) P20, pH 7.4).

[0719] Flow cell 2 of channels 1, 2, 3, 4, 5, 6, 7, and 8 was used for interaction measurements, while flow cell 1 of each channel served as a reference. Each rabbit antibody was diluted to 3 nM in sample buffer and injected at a flow rate of 5 μL / min for 2 minutes. Rabbit antibody capture level (CL) was monitored in response units (RU).

[0720] A series of increasing concentrations of propeptide BMP10 "BMP10(312)" at c = 3.7–300 nM were injected at a rate of 60 μL / min onto the corresponding surfaces of the displayed anti-propeptide BMP10 rabbit mAbs, with repeated concentrations at c = 33.3 nM. The associative phase was monitored for 3 min; the dissociative phase was monitored for 10 min. After each kinetically determined cycle, the rabbit clone was eluted from the capture system by injection of 10 mM glycine at pH 2.0 for 1 min, followed by two consecutive injections of 10 mM glycine at pH 2.25 for 1 min at a rate of 20 μL / min.

[0721] According to BIAcore from GE Healthcare TM The dissociation rate constant k was evaluated using the Insight SW V 2.0 evaluation software and a Langmuir 1:1 fitting model. d According to the formula ln(2) / 60*k d Calculate the stability half-life (minutes) of the antigen / antibody complex.

[0722] The molar ratio representing the combined stoichiometry is calculated using the following formula:

[0723] MW (antibody) / MW (antigen)*BL (antigen) / CL (antibody)

[0724] Since the propeptide BMP10 is a dimer molecule, the affinity obtained is affinity-loaded, thus representing significant data.

[0725] result

[0726] Kinetic screening

[0727] Two hundred and eighty rabbit antibodies were tested using a kinetic screening method. Eighteen antibodies with suitable kinetic properties were identified and further characterized.

[0728] Detailed dynamic characterization

[0729] Eighteen antibodies were selected from 280 rabbit monoclonal antibodies screened by kinetics.

[0730] Detailed concentration-dependent kinetic studies showed that the interaction with propeptide BMP10 did not conform to the Langmuir 1:1 interaction.

[0731] The propeptide BMP10 is a dimer molecule, and interactions may be affinity-burdened. Kinetic data represent readily apparent data, but can be characterized by visual inspection of sensor plots and quantification of the linear dissociation phase of the antibody. Complex half-lives vary between t / 2diss = 6 and >115 minutes. Binding stoichiometry is between 1.2 and 1.4, representing a 2:1 binding stoichiometry.

[0732] All Abs except 14C8 and 8G5 exhibited suitable kinetic profiles: fairly rapid complex formation rates and complex half-lives t / 2diss > 15 min. The molar ratios of all Abs indicated a 2:1 binding stoichiometry. Clones 8G5 and 14C8 showed slightly slower association and less complex stability than the other clones. Both covered the same epitope region. Clones 2H8 and 3H8 each covered a unique epitope region.

[0733] Cloning 13G6 shows the slowest dissociation (k d <1.0E-04s -1 This results in a complex half-life t / 2-diss > 115 minutes. Clone 11A5 exhibits suitable kinetic characteristics, with a rapid complex formation rate and a complex half-life of 30 minutes. The molar ratio indicates a fully functional antibody with a 2:1 binding stoichiometry.

[0734] The results are summarized in Table 11, and the sensor images are overlaid on the table. Figure 10 In the middle. The normalized antibody dissociation phases of 8 clones are as follows: Figure 11 As shown

[0735] Table 11: Through SPR ( Kinetic constants and affinity data for the binding of propeptide BMP10 to the selected mAb <propeptide BMP10>, measured at 37 °C (8K).

[0736]

[0737] k d Dissociation rate constant [s] -1 ]

[0738] t / 2-diss According to the formula ln(2) / 60*k d Calculated half-life of antigen / antibody complex stability [min]

[0739] R max Maximum analyte response [RU]

[0740] MR molar ratio: R of the analyte bound to each mAb max Example 12: Ratio of experimental to theoretical values: Epitope mapping using peptide microarrays

[0741] Epitope mapping for antibody cloning was performed using a library of fixed peptide fragments (length: 15 amino acids, 14 amino acid overlaps) corresponding to the sequence of human bone morphogenetic protein 10. Peptides were synthesized on modified cellulose disks using an automated synthesizer (Intavis MultiPep RS) and dissolved after synthesis. Solutions of each peptide were then spotted onto coated microscope slides. Synthesis was performed stepwise on amino-modified cellulose disks in 384-well synthesis plates using 9-fluorenylmethoxycarbonyl (Fmoc) chemistry. In each coupling cycle, the corresponding amino acid was activated with a solution of DIC / HOBt in DMF. Between coupling steps, unreacted amino groups were capped with a mixture of acetic anhydride, diisopropylethylamine, and 1-hydroxybenzotriazole. After synthesis, the cellulose disks were transferred to 96-well plates and treated with a mixture of trifluoroacetic acid (TFA), dichloromethane, triisopropylsilane (TIS), and water for side-chain deprotection. After removing the lysis solution, the cellulose-bound peptides were dissolved in a mixture of TFA, TFMSA, TIS, and water, precipitated with diisopropyl ether, and resuspended in DMSO. These peptide solutions were then spotted onto Intavis CelluSpots using an Intavis slide spotting robot. TM On a glass slide.

[0742] For epitope analysis, the prepared slides were washed with ethanol, then with Tris-buffered saline (TBS; 50 mM Tris, 137 mM NaCl, 2.7 mM KCl, pH 8), and then blocked at 37°C for 1 hour with 5 mL of 10x Western Blocking Reagent (Roche Applied Science), TBS containing 2.5 g sucrose, and 0.1% Tween 20. After washing (TBS + 0.1% Tween 20), the slides were incubated at 37°C for 1 hour with antibody cloning solution (1 μg / mL) in TBS + 0.1% Tween 20. After washing, the slides were incubated with anti-rabbit secondary HRP antibody (1:20000 in TBS-T) for detection, and then incubated with DAB substrate. Positive SPOTs were assigned to the corresponding peptide sequences.

[0743] Table 12: Table Positions

[0744]

[0745]

[0746] Example 13: Selecting antibodies for sandwich assays

[0747] Biotinylated and ruthenium-treated clones 2H8, 3H8, 8G5, 9E7, 11A5, 11C10, 14C8, and 13G6 were tested in multiple sandwiches to identify sandwich partners for further development of the Elecsys immunoassay. The relationship between the recognition of recombinant NT-proBMP10 (22-312) in sandwich combinations at 0.01 ng / ml and blank values ​​(Table 13) reflected signal-to-noise ratios of 1.16 and 1.22 for the biotinylated and ruthenium-treated sides, respectively, in the combination of clones 11A2 and 11C2. The combination of 13G6 and 11C10 reflected ratios of 1,22 and 1,23, indicating high-rank performance independent of orientation. Similar observations were made for the combination of 3H8 and 9E7 with ratios of 1,22 and 1,23, but with higher blank values ​​compared to the combination of 11C10 and 13G6. Other combinations described achieved good ratios, but only for one sandwich orientation.

[0748] Table 13: Antibody sandwich characteristics of maximum signal readout on the Elecsys ECLIA measurement unit at a recombinant NT-proBMP10 (22-312) concentration level of 0.01 ng / ml and signal-to-noise ratio of 0.01 ng / ml divided by the blank value (S / N) without recombinant protein incorporation.

[0749]

[0750] The identification of 20 natural samples from healthy donors (Table 14) shows the detection range of NT-proBMP10 in natural serum samples, allowing for the determination of baseline values ​​for clinical sample measurements. These were within comparable ranges for both Ru- and Bi-orientations of 11C10 and 13G6. Similar ranges were also detected for 11C10 and 11A5 in both orientations.

[0751] Table 14: Antibody sandwich characteristics of the signal readouts on the Elecsys ECLIA measurement unit for the concentration levels of the 20 described natural healthy human serum samples, including minimum, maximum, and median values.

[0752]

[0753] Example 14: Biomarker Measurement (Exemplary Method for Detecting NT-proBMP10)

[0754] Using commercial products from Roche Diagnostics (Mannheim, Germany) The reagents were used to measure serum and plasma concentrations of the biomarker NT-proBMP10. A prototype from Roche Diagnostics (Mannheim, Germany) was used. The reagent was used to measure the biomarker NT-proBMP10.

[0755] Using biotinylated rabbit MAB <nt-probmp10>F(ab′)2-Bi and ruthenium-modified MAB <nt-probmp10>-Ru was used to determine NT-proBMP10-:

[0756] use The cobas E601 analyzer has developed an electrochemiluminescence immunoassay (ECLIA) for the specific measurement of NT-proBMP10, particularly in human serum or plasma samples. The Elecsys NT-proBMP10 immunoassay is an ECLIA that operates on a sandwich principle. The assay contains two antibodies: a biotinylated monoclonal antibody F(ab`)2-fragment MAB. <bmp10>(MAB<BMP10_22-312> Bi; capture antibodies, such as 11C10) and ruthenium-containing monoclonal anti-BMP10 antibody MAB <bmp10>(MAB<BMP10_22-312> -Ru; detection antibodies, such as 13G6), form a sandwich immunoassay complex with NT-proBMP10 in the sample. The complex is then bound to solid-phase streptavidin-coated microparticles. These are magnetically trapped to the electrode surface, resulting in chemiluminescence emission when a voltage is applied to the electrode, which is measured by a photomultiplier tube. The results are determined by an instrument-specific calibration curve determined by a series of six calibrators with different concentrations of NT-proBMP10 throughout the measurement range. Assay protocol 2 is used to measure the sample, with pipette volumes of 20 μL sample, 75 μL reagent 1 (R1), 75 μL reagent 2 (R2), and 30 μL magnetic beads. R1 contains MAB in phosphate reaction buffer. <bmp10>F(ab`)2-Bi, reagent 2 (R2) in MAB containing the same reaction buffer <bmp10>-Ru.

[0757] Example 15: Predicting Resting Cerebral Infarction Based on Cyclic BMP-10 Levels (LNCCI and SNCI)

[0758] BMP-10 provides a method for assessing resting stroke, including the following:

[0759] 1. Predicting the risk of resting stroke in patients with atrial fibrillation based on serum / plasma circulating BMP-10 levels (SWISSAF study, Tables 15+16)

[0760] 2. Improving the predictive accuracy of clinical stroke risk scores for resting ischemic stroke based on serum / plasma circulating BMP-10 levels (e.g., CHA2DS2-VASc, CHADS2 score) (SWISS AF study, Table 17)

[0761] The ability of BMP-10 to predict the risk of resting infarction was assessed in the SWISS AF study (Conen D., Forum Med Suisse 2012; 12:860–862; Conen et al. Swiss Med Wkly. 2017; 147). The median age of patients in the SWISS AF cohort was 74 years, with a 20% incidence of prior clinical stroke or TIA, a 34% incidence of vascular disease, and a 17% history of diabetes.

[0762] BMP-10 was measured in the complete SWISS AF study, a pre-commercial assay for bone morphogenetic protein 10 (BMP-10) (high-throughput). Immunological assay; Roche Diagnostics, Mannheim, Germany). To detect BMP-10, a cobas... The ECLIA platform has developed a sandwich immunoassay.

[0763] Because estimates from a simple proportional hazard model for a case-control cohort would be biased (due to the varying proportions of cases versus controls), a weighted proportional hazard model was used. The weights are based on the inverse probability of each patient selected for the case-control cohort. To obtain estimates of absolute survival in both groups based on a dichotomous baseline BMP-10 measure (<= median versus > median), a weighted form of the Kaplan-Meier curve was created.

[0764] To assess the ability of existing risk scores to improve stroke outcomes using BMP-10, the CHADS2, CHA2DS2-VASc, and ABC scores were extended using BMP-10 (log2 transformed). This extension was achieved by creating a risk-sharing model that included BMP-10 and the corresponding risk scores as independent variables.

[0765] The c-indices of CHADS2, CHA2DS2-VASc, and ABC scores were compared with those of these extended models. To calculate the c-indices in the case contemporaneous cohorts, a weighted form of the c-indices proposed in Ganna (2011) was used.

[0766] result

[0767] Table 15: Significantly altered circulating BMP-10 levels in patients with brain injury (SWISS AF study). Brain injury includes LNCCI and SNCI. Values ​​are median (first and third quartiles).

[0768]

[0769] bMRI showed that patients with LNCCI or SNCI were older (75.0 vs. 68.1 years, p<0.0001), had a higher incidence of permanent atrial fibrillation (28.4% vs. 17.8%, p=0.0002), higher systolic blood pressure (136.7 vs. 131.3 mmHg, p<0.0001), and higher CHA2DS2-VASc scores (3.2 vs. 2.1, p<0.0001), but there was no difference in oral anticoagulation rates (90.3% vs. 88.5%, p=0.32). As shown in Table 15, BMP-10 levels were significantly elevated in patients with brain injury.

[0770] As shown in Table 15, the risk of resting stroke in patients with atrial fibrillation can be assessed based on the circulating BMP-10 levels in serum / plasma.

[0771] Table 16: Significant multivariate adjusted hazard ratios (HRs) (95% confidence interval (CI) associated with resting infarction in BMP-10 (with LNCCI and SNCI))

[0772]

[0773] Model 1 was adjusted for age and gender.

[0774] Model 2 also made additional adjustments for systolic blood pressure, history of major bleeding, diabetes, peripheral vascular disease, BMI, smoking status, and use of oral anticoagulants and antiplatelet drugs.

[0775] Logarithmic transformation of biomarkers.

[0776] As shown in Table 16, after multivariate adjustment for age and sex (Model 1) or age, sex, systolic blood pressure, history of major bleeding, diabetes, peripheral vascular disease, BMI, smoking status, use of oral anticoagulants and antiplatelet drugs, BMP-10 was significantly associated with LNCCI.

[0777] Therefore, the risk of resting stroke in patients with atrial fibrillation can be assessed based on the circulating BMP-10 levels in serum / plasma.

[0778] Table 17: BMP-10 significantly improved the CHAD2DS2-VASc score associated with large-area noncortical infarction.

[0779] In addition to the CHADS2-VA2SC score, the predictor variables were log-quantified biomarkers, and the outcome variables were the presence / absence of large noncortical and cortical infarctions.

[0780]

[0781] When we added a single biomarker to the CHA2DS2-VASc score, the AUC (95% CI) improved BMP-10 by 0.699 (0.673–0.724), as shown in Table 17.

[0782] Combining BMP-10 with clinical parameters of the CHA2DS2-VASC score is a good predictor of clinical resting stroke, and is superior to the CHA2DS2-VASC score. Early clinical identification of patients at risk of cognitive decline allows for better diagnostic and preventative measures.

[0783] Example 16: Predicting white matter lesions based on circulating BMP-10 levels

[0784] Data from the SWISS-AF dataset showed that BMP-10 was associated with patients having large noncortical and cortical infarcts (LNCCI).

[0785] The severity of white matter lesions can be represented by the Fazekas score (Fazekas, JB Chawluk, A Alavi, HIHurtig, and RA Zimmerman, American Journal of Roentgenology 1987 149:2,351-356). The Fazekas score ranges from 0 to 3, with 0 indicating no white matter lesions, 1 indicating mild white matter lesions, 2 indicating moderate white matter lesions, and 3 indicating severe white matter lesions.

[0786] To compare the association between BMP-10 and large noncortical and cortical infarctions (LNCCI), patients were divided into two groups: Fazekas score <2 (no) and Fazekas score ≥2 (yes). Figure 14 The results showed that patients with moderate or severe WML had increased BMP-10 levels compared to patients with mild or no WML.

[0787] White matter injury (WML) can be caused by clinical resting stroke (Wang Y, Liu G, Hong D, Chen F, Ji X, Cao G. White matter injury in ischemic stroke. Prog Neurobiol. 2016; 141:45–60. doi:10.1016 / j.pneurobio.2016.04.005). This further demonstrates the usefulness of BMP-10 in predicting clinical stroke risk.

[0788] The ability of the circulating BMP-10 to distinguish between patients with a Fazekas score <2 (no) and a Fazekas score ≥2 (yes) was expressed as an AUC of 0.62. White matter changes in the brain of dementia patients. Changes in advanced age and WML scores have been described as being correlated with the severity of dementia in Alzheimer's disease patients (Kao et al., 2019).

[0789] Age is also an important predictor of clinical stroke. Therefore, data showing a significant increase in circulating BMP-10 levels appear to indicate not only moderate or severe large noncortical and cortical infarcts (LNCCI), but also age-related brain diseases such as vascular dementia. sequence list <110> Universiteit Maastricht F. Hoffmann-La Roche AG Roche Diagnostics GmbH Academy Ziekenhuis Maastricht Roche Diagnostics Operations, Inc. <120> Detection method for circulating BMP10 (bone morphogenetic protein 10) <130> P35929 <160> 78 <170> BiSSAP 1.3.6 <210> 1 <211> 424 <212> PRT <213> Homo sapiens <400> 1 Met Gly Ser Leu Val Leu Thr Leu Cys Ala Leu Phe Cys Leu Ala Ala 1 5 10 15 Tyr Leu Val Ser Gly Ser Pro Ile Met Asn Leu Glu Gln Ser Pro Leu 20 25 30 Glu Glu Asp Met Ser Leu Phe Gly Asp Val Phe Ser Glu Gln Asp Gly 35 40 45 Val Asp Phe Asn Thr Leu Leu Gln Ser Met Lys Asp Glu Phe Leu Lys 50 55 60 Thr Leu Asn Leu Ser Asp Ile Pro Thr Gln Asp Ser Ala Lys Val Asp 65 70 75 80 Pro Pro Glu Tyr Met Leu Glu Leu Tyr Asn Lys Phe Ala Thr Asp Arg 85 90 95 Thr Ser Met Pro Ser Ala Asn Ile Ile Arg Ser Phe Lys Asn Glu Asp 100 105 110 Leu Phe Ser Gln Pro Val Ser Phe Asn Gly Leu Arg Lys Tyr Pro Leu 115 120 125 Leu Phe Asn Val Ser Ile Pro His His Glu Glu Val Ile Met Ala Glu 130 135 140 Leu Arg Leu Tyr Thr Leu Val Gln Arg Asp Arg Met Ile Tyr Asp Gly 145 150 155 160 Val Asp Arg Lys Ile Thr Ile Phe Glu Val Leu Glu Ser Lys Gly Asp 165 170 175 Asn Glu Gly Glu Arg Asn Met Leu Val Leu Val Ser Gly Glu Ile Tyr 180 185 190 Gly Thr Asn Ser Glu Trp Glu Thr Phe Asp Val Thr Asp Ala Ile Arg 195 200 205 Arg Trp Gln Lys Ser Gly Ser Ser Thr His Gln Leu Glu Val His Ile 210 215 220 Glu Ser Lys His Asp Glu Ala Glu Asp Ala Ser Ser Gly Arg Leu Glu 225 230 235 240 Ile Asp Thr Ser Ala Gln Asn Lys His Asn Pro Leu Leu Ile Val Phe 245 250 255 Ser Asp Asp Gln Ser Ser Asp Lys Glu Arg Lys Glu Glu Leu Asn Glu 260 265 270 Met Ile Ser His Glu Gln Leu Pro Glu Leu Asp Asn Leu Gly Leu Asp 275 280 285 Ser Phe Ser Ser Gly Pro Gly Glu Glu Ala Leu Leu Gln Met Arg Ser 290 295 300 Asn Ile Ile Tyr Asp Ser Thr Ala Arg Ile Arg Arg Asn Ala Lys Gly 305 310 315 320 Asn Tyr Cys Lys Arg Thr Pro Leu Tyr Ile Asp Phe Lys Glu Ile Gly 325 330 335 Trp Asp Ser Trp Ile Ile Ala Pro Pro Gly Tyr Glu Ala Tyr Glu Cys 340 345 350 Arg Gly Val Cys Asn Tyr Pro Leu Ala Glu His Leu Thr Pro Thr Lys 355 360 365 His Ala Ile Ile Gln Ala Leu Val His Leu Lys Asn Ser Gln Lys Ala 370 375 380 Ser Lys Ala Cys Cys Val Pro Thr Lys Leu Glu Pro Ile Ser Ile Leu 385 390 395 400 Tyr Leu Asp Lys Gly Val Val Thr Tyr Lys Phe Lys Tyr Glu Gly Met 405 410 415 Ala Val Ser Glu Cys Gly Cys Arg 420 <210> 2 <211> 11 <212> PRT <213> Homo sapiens <400> 2 Ser Leu Phe Gly Asp Val Phe Ser Glu Gln Asp 1 5 10 <210> 3 <211> 15 <212> PRT <213> Homo sapiens <400> 3 Leu Glu Ser Lys Gly Asp Asn Glu Gly Glu Arg Asn Met Leu Val 1 5 10 15 <210> 4 <211> 9 <212> PRT <213> Homo sapiens <400> 4 Ser Lys Gly Asp Asn Glu Gly Glu Arg 1 5 <210> 5 <211> 9 <212> PRT <213> Homo sapiens <400> 5 Ser Ser Gly Pro Gly Glu Glu Ala Leu 1 5 <210> 6 <211> 295 <212> PRT <213> Homo sapiens <400> 6 Ser Pro Ile Met Asn Leu Glu Gln Ser Pro Leu Glu Glu Asp Met Ser 1 5 10 15 Leu Phe Gly Asp Val Phe Ser Glu Gln Asp Gly Val Asp Phe Asn Thr 20 25 30 Leu Leu Gln Ser Met Lys Asp Glu Phe Leu Lys Thr Leu Asn Leu Ser 35 40 45 Asp Ile Pro Thr Gln Asp Ser Ala Lys Val Asp Pro Pro Glu Tyr Met 50 55 60 Leu Glu Leu Tyr Asn Lys Phe Ala Thr Asp Arg Thr Ser Met Pro Ser 65 70 75 80 Ala Asn Ile Ile Arg Ser Phe Lys Asn Glu Asp Leu Phe Ser Gln Pro 85 90 95 Val Ser Phe Asn Gly Leu Arg Lys Tyr Pro Leu Leu Phe Asn Val Ser 100 105 110 Ile Pro His His Glu Glu Val Ile Met Ala Glu Leu Arg Leu Tyr Thr 115 120 125 Leu Val Gln Arg Asp Arg Met Ile Tyr Asp Gly Val Asp Arg Lys Ile 130 135 140 Thr Ile Phe Glu Val Leu Glu Ser Lys Gly Asp Asn Glu Gly Glu Arg 145 150 155 160 Asn Met Leu Val Leu Val Ser Gly Glu Ile Tyr Gly Thr Asn Ser Glu 165 170 175 Trp Glu Thr Phe Asp Val Thr Asp Ala Ile Arg Arg Trp Gln Lys Ser 180 185 190 Gly Ser Ser Thr His Gln Leu Glu Val His Ile Glu Ser Lys His Asp 195 200 205 Glu Ala Glu Asp Ala Ser Ser Gly Arg Leu Glu Ile Asp Thr Ser Ala 210 215 220 Gln Asn Lys His Asn Pro Leu Leu Ile Val Phe Ser Asp Asp Gln Ser 225 230 235 240 Ser Asp Lys Glu Arg Lys Glu Glu Leu Asn Glu Met Ile Ser His Glu 245 250 255 Gln Leu Pro Glu Leu Asp Asn Leu Gly Leu Asp Ser Phe Ser Ser Gly 260 265 270 Pro Gly Glu Glu Ala Leu Leu Gln Met Arg Ser Asn Ile Ile Tyr Asp 275 280 285 Ser Thr Ala Arg Ile Arg Arg 290 295 <210> 7 <211> 117 <212> PRT <213> Synthetic sequence <220> <223> VH-1 <400> 7 Gln Ser Leu Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Val Ser Gly Ile Asp Leu Ser Arg Asn Val 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Glu Gly Leu Glu Trp Ile Gly 35 40 45 Ser Ile Asn Thr Gly Gly Ser Thr Trp Tyr Ala Ser Trp Ala Glu Gly 50 55 60 Arg Leu Thr Ile Ser Lys Ser Ser Thr Thr Val Asp Leu Lys Ile Ser 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Arg Gly Val 85 90 95 Tyr Gly His Ser Asn Gly Tyr Tyr Ser Leu Trp Gly Gln Gly Thr Leu 100 105 110 Val Thr Val Ser Ser 115 <210> 8 <211> 116 <212> PRT <213> Artificial Sequence <220> <223> VH-2 <400> 8 Gln Ser Val Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Ala Ser Gly Phe Ser Leu Ser Ser Tyr Ala 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Gln Phe Ile Gly 35 40 45 Tyr Ile Ser Gly Gly Gly Ser Thr Tyr Tyr Ala Ser Trp Val Lys Gly 50 55 60 Arg Phe Thr Ile Ser Lys Thr Ser Thr Thr Val Asp Leu Lys Leu Thr 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Arg Gly Tyr 85 90 95 Pro Gly Tyr Ile Ser Gly Thr Trp Ala Val Gly Gln Gly Thr Leu Val 100 105 110 Thr Val Ser Ser 115 <210> 9 <211> 117 <212> PRT <213> Artificial Sequence <220> <223> VH-3 <400> 9 Gln Ser Leu Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Ala 1 5 10 15 Leu Thr Val Thr Cys Thr Val Ser Gly Ile Asp Leu Ser Arg Asn Leu 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Glu Gly Leu Glu Trp Ile Gly 35 40 45 Ser Ile Asn Phe Arg Asn Ile Thr Trp Tyr Ala Ser Trp Ala Lys Gly 50 55 60 Arg Phe Thr Ile Ser Lys Thr Ser Thr Thr Val Asp Leu Arg Ile Ser 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Arg Gly Val 85 90 95 Tyr Val Asn Ser Asn Gly Tyr Tyr Ser Leu Trp Gly Gln Gly Thr Pro 100 105 110 Val Thr Val Ser Ser 115 <210> 10 <211> 116 <212> PRT <213> Artificial Sequence <220> <223> VH-4 <400> 10 Gln Ser Leu Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Val Ser Gly Phe Ser Leu Ser Asn Tyr Ala 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Met Gly Leu Glu Tyr Ile Gly 35 40 45 Tyr Ile Ser Ala Ser Gly Asn Thr Tyr Tyr Ala Ser Trp Val Lys Gly 50 55 60 Arg Phe Thr Ile Ser Lys Thr Ser Thr Thr Val Asp Leu Lys Met Thr 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Arg Gly Tyr 85 90 95 Ser Gly Trp Ile Ser Gly Thr Trp Ala Val Gly Gln Gly Thr Leu Val 100 105 110 Thr Val Ser Ser 115 <210> 11 <211> 117 <212> PRT <213> Artificial sequence <220> <223> VH-5 <400> 11 Gln Ser Val Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Ala Ser Gly Ile Asp Leu Ser Arg Tyr Ala 20 25 30 Met Thr Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Glu Trp Ile Gly 35 40 45 Ile Ile Gly Ala Ser Ser Gly Thr Trp Tyr Ala Ser Trp Ala Lys Gly 50 55 60 Arg Phe Thr Ile Ala Lys Thr Ser Thr Thr Val Asp Leu Arg Ile Thr 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Arg Asp Asn 85 90 95 Gly Asp Ser Lys Asp Tyr Ala Phe Asp Pro Trp Gly Pro Gly Thr Leu 100 105 110 Val Thr Val Ser Ser 115 <210> 12 <211> 108 <212> PRT <213> Artificial sequence <220> <223> VH-6 <400> 12 Gln Ser Val Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Ala Ser Ala Phe Ser Leu Ser Arg Tyr Val 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Glu Phe Ile Gly 35 40 45 Phe Ile Asn Ala Ser Gly Ser Thr Ser Tyr Ala Ser Trp Ala Lys Gly 50 55 60 Arg Phe Thr Ile Ser Lys Thr Ser Thr Thr Val Asp Leu Lys Met Thr 65 70 75 80 Ser Leu Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Ala Thr Gly Asn 85 90 95 Leu Trp Gly Pro Gly Thr Leu Val Thr Val Ser Ser 100 105 <210> 13 <211> 112 <212> PRT <213> Artificial Sequence <220> <223> VH-8 <400> 13 Gln Ser Val Glu Glu Ser Gly Gly Arg Leu Val Thr Pro Gly Thr Pro 1 5 10 15 Leu Thr Leu Thr Cys Thr Ala Ser Gly Phe Ser Leu Ser Lys Tyr Asp 20 25 30 Met Ser Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Glu Trp Ile Gly 35 40 45 Ala Ile Gly Gly Arg Gly Val Thr Asp Tyr Thr Thr Trp Ala Lys Gly 50 55 60 Arg Phe Thr Ile Ser Lys Thr Ala Thr Thr Val Asp Leu Lys Met Thr 65 70 75 80 Ser Pro Thr Thr Glu Asp Thr Ala Thr Tyr Phe Cys Val Arg Ala Leu 85 90 95 Ala Gly Asp Thr Leu Trp Gly Pro Gly Thr Leu Val Thr Val Ser Ser 100 105 110 <210> 14 <211> 127 <212> PRT <213> Artificial Sequence <220> <223> VH-8 <400> 14 Gln Ser Leu Glu Glu Ser Gly Gly Asp Leu Val Lys Pro Gly Ala Ser 1 5 10 15 Leu Thr Leu Thr Cys Thr Ala Ser Gly Phe Ser Phe Ser Ser Ser Tyr 20 25 30 Trp Ile Cys Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Glu Trp Ile 35 40 45 Ala Cys Ile Tyr Ala Gly Ser Ser Asp Ile Thr Tyr Tyr Ala Ser Trp 50 55 60 Ala Lys Gly Arg Phe Thr Val Ser Lys Thr Ser Ser Pro Thr Val Thr 65 70 75 80 Leu Gln Met Thr Ser Leu Thr Ala Ala Asp Thr Ala Thr Tyr Phe Cys 85 90 95 Ala Arg Gly Arg Tyr Tyr Val Asp Gly Tyr Ala Asp Tyr Tyr Pro Gly 100 105 110 Asp Phe Asn Leu Trp Gly Pro Gly Thr Leu Val Thr Val Ser Ser 115 120 125 <210> 15 <211> 120 <212> PRT <213> Artificial Sequence <220> <223> VH-9 <400> 15 Gln Ser Leu Glu Glu Ser Gly Gly Gly Leu Val Gln Pro Glu Gly Ser 1 5 10 15 Leu Thr Leu Thr Cys Ile Ala Ser Ala Phe Ser Phe Ser Ser Gly Tyr 20 25 30 Tyr Met Cys Trp Val Arg Gln Ala Pro Gly Lys Gly Leu Glu Trp Ile 35 40 45 Ala Cys Ile Tyr Ala Gly Ser Ser Gly Thr Thr Tyr Tyr Ala Ser Trp 50 55 60 Ala Lys Gly Arg Phe Thr Ile Ser Lys Ala Ser Ser Thr Thr Val Thr 65 70 75 80 Leu Leu Met Thr Ser Leu Thr Ala Ala Asp Thr Ala Thr Tyr Phe Cys 85 90 95 Ala Arg Gly Pro Gly Ala Ser Gly Tyr Arg Leu Gly Leu Trp Gly Pro 100 105 110 Gly Thr Leu Val Thr Val Ser Ser 115 120 <210> 16 <211> 112 <212> PRT <213> artificial sequence <220> <223> VL‑1 <400> 16 Ala Leu Val Met Thr Gln Thr Pro Ala Ser Val Glu Ala Ala Val Gly 1 5 10 15 Gly Thr Val Thr Ile Asn Cys Gln Ala Ser Gln Ser Ile Ser Asn Leu 20 25 30 Leu Ala Trp Tyr Gln Gln Lys Pro Gly Gln Pro Pro Lys Val Leu Ile 35 40 45 Tyr Ala Ala Ser Pro Leu Ala Ser Gly Val Ser Pro Arg Phe Lys Gly 50 55 60 Ser Gly Ser Gly Thr His Phe Thr Leu Thr Val Ser Asp Leu Glu Cys 65 70 75 80 Ala Asp Ala Ala Thr Tyr Tyr Cys Gln Ser Tyr Trp Gly Gly Ser Gly 85 90 95 Glu Arg Tyr Leu Asn Thr Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 110 <210> 17 <211> 110 <212> PRT <213> Artificial Sequence <220> <223> VL-2 <400> 17 Ala Val Leu Thr Gln Thr Pro Ser Pro Val Ser Ala Ala Val Gly Gly 1 5 10 15 Thr Val Ser Ile Ser Cys Gln Ser Ser Gln Ser Val Val Asn Asn Asn 20 25 30 Arg Cys Ser Trp Phe Gln Gln Lys Pro Gly Gln Pro Pro Lys Gln Leu 35 40 45 Ile Tyr Ser Ala Ser Thr Leu Ala Ser Gly Val Pro Ser Arg Phe Lys 50 55 60 Gly Ser Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Ser Asp Val Gln 65 70 75 80 Cys Asp Asp Ala Ala Thr Tyr Tyr Cys Leu Gly Asp Tyr Val Ser Tyr 85 90 95 Gly Asp Ser Ala Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 110 <210> 18 <211> 112 <212> PRT <213> Synthetic sequence <220> <223> VL-3 <400> 18 Asp Ile Val Met Thr Gln Thr Pro Ala Ser Val Glu Ala Ala Val Gly 1 5 10 15 Gly Thr Val Thr Ile Asn Cys Gln Ala Ser Gln Ser Val Ser Asn Leu 20 25 30 Leu Ala Trp Tyr Gln Gln Lys Pro Gly Gln Pro Pro Lys Leu Leu Ile 35 40 45 Tyr Gly Ala Ser Lys Leu Glu Ser Gly Val Pro Ser Arg Phe Lys Gly 50 55 60 Ser Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Asn Asp Leu Glu Cys 65 70 75 80 Asp Asp Ala Ala Thr Tyr Tyr Cys Gln Thr Tyr Trp Gly Gly Asp Gly 85 90 95 Thr Ser Tyr Leu Asn Pro Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 110 <210> 19 <211> 110 <212> PRT <213> artificial sequence <220> <223> VL‑4 <400> 19 Ala Val Leu Thr Gln Thr Pro Ser Pro Val Ser Ala Ala Val Gly Gly 1 5 10 15 Thr Val Asn Ile Gly Cys Gln Ser Ser Gln Ser Val Val Asn Asn Asn 20 25 30 Arg Leu Ser Trp Phe Gln Gln Arg Pro Gly Gln Pro Pro Lys Gln Leu 35 40 45 Ile Tyr Arg Ala Ser Thr Leu Ala Ser Gly Val Pro Ser Arg Phe Lys 50 55 60 Gly Ser Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Ser Asp Val Gln 65 70 75 80 Cys Asp Asp Ala Ala Thr Tyr Tyr Cys Leu Gly Asp Tyr Val Ser Tyr 85 90 95 Ser Glu Ala Ala Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 110 <210> 20 <211> 109 <212> PRT <213> artificial sequence <220> <223> VL‑5 <400> 20 Ile Asp Met Thr Gln Thr Pro Ser Pro Val Ser Ala Ala Val Gly Asp 1 5 10 15 Thr Val Thr Ile Asn Cys Gln Ala Ser Glu Asn Ile Tyr Ser Phe Leu 20 25 30 Ala Trp Tyr Gln Gln Lys Pro Gly His Ser Pro Asn Leu Leu Ile Tyr 35 40 45 Phe Ala Ser Lys Leu Val Ser Gly Val Pro Ser Arg Phe Lys Gly Ser 50 55 60 Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Ser Asp Val Gln Cys Asp 65 70 75 80 Asp Ala Ala Thr Tyr Tyr Cys Gln Gln Thr Tyr Thr Tyr Ser Asn Gly 85 90 95 Asp Asn Pro Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 <210> 21 <211> 111 <212> PRT <213> Synthetic sequence <220> <223> VL-6 <400> 21 Asp Ile Val Met Thr Gln Thr Pro Ser Ser Val Ser Gly Pro Val Gly 1 5 10 15 Gly Thr Val Thr Ile Asn Cys Gln Ala Ser Gln Asn Ile Tyr Ser Asn 20 25 30 Leu Ala Trp Tyr Gln Gln Lys Pro Gly Gln Pro Pro Lys Leu Leu Ile 35 40 45 Tyr Tyr Ala Ser Thr Leu Val Ser Gly Val Pro Ser Arg Phe Lys Gly 50 55 60 Ser Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Ser Asp Leu Glu Cys 65 70 75 80 Ala Asn Ala Ala Thr Tyr Tyr Cys Gln Ser Lys Asp Gly Pro Thr Ser 85 90 95 Ser Thr Tyr Gly Ala Phe Gly Gly Gly Thr Glu Val Val Val Arg 100 105 110 <210> 22 <211> 113 <212> PRT <213> artificial sequence <220> <223> VL‑7 <400> 22 Ala Gln Val Leu Thr Gln Thr Ala Ser Pro Val Ser Ala Ala Val Gly 1 5 10 15 Ser Thr Val Thr Ile Asn Cys Gln Ala Ser Gln Asn Ile Tyr Lys Tyr 20 25 30 Asn Asn Leu Ala Trp Tyr Gln Gln Lys Pro Gly Gln Pro Pro Lys Arg 35 40 45 Leu Ile Tyr Glu Ala Ser Lys Leu Ala Ser Gly Val Pro Ser Arg Phe 50 55 60 Ser Gly Ser Gly Ser Gly Thr Gln Phe Thr Leu Thr Ile Ser Gly Val 65 70 75 80 Gln Cys Glu Asp Ala Ala Thr Tyr Tyr Cys Gln Gly Thr Phe Glu Cys 85 90 95 Ser Ser Ala Asp Cys Phe Gly Phe Gly Gly Gly Thr Glu Val Val Val 100 105 110 Lys <210> 23 <211> 112 <212> PRT <213> Artificial Sequence <220> <223> VL-8 <400> 23 Asp Ile Val Met Thr Gln Thr Pro Ala Ser Val Glu Ala Ala Val Gly 1 5 10 15 Gly Thr Val Thr Ile Lys Cys Gln Ala Ser Gln Ser Ile Ser Ser Tyr 20 25 30 Leu Ala Trp Tyr Gln Gln Lys Ser Gly Gln Pro Pro Lys Leu Leu Ile 35 40 45 Tyr Leu Ala Ser Thr Leu Glu Ser Gly Val Pro Ser Arg Phe Lys Gly 50 55 60 Ser Gly Ser Gly Thr Glu Phe Thr Leu Thr Ile Ser Asp Leu Glu Cys 65 70 75 80[[ID=SO]] Ala Asp Ala Ala Thr Tyr Tyr Cys Gln Ser Tyr Tyr Tyr Ser Ser Ser 85 90 95 Ser Ser Tyr Gly Ser Ala Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 110 <210> 24 <211> 109 <212> PRT <213> artificial sequence <220> <223> VL‑9 <400> 24 Asp Val Val Met Thr Gln Thr Pro Ala Ser Val Ser Glu Pro Val Gly 1 5 10 15 Gly Thr Val Thr Ile Lys Cys Gln Ala Ser Glu Asp Ile Tyr Arg Leu 20 25 30 Leu Ala Trp Tyr Gln Gln Lys Pro Gly Gln Pro Pro Lys Leu Leu Ile 35 40 45 Tyr Asp Ala Ser Asp Leu Ala Ser Gly Val Pro Ser Arg Leu Ser Gly 50 55 60 Ser Gly Ser Gly Thr Glu Tyr Thr Leu Ser Ile Ser Asp Leu Glu Cys 65 70 75 80 Ala Asp Ala Ala Thr Tyr Tyr Cys Gln Gln Gly Tyr Tyr Ile Ser Gly 85 90 95 Gly Asp Ser Phe Gly Gly Gly Thr Glu Val Val Val Lys 100 105 <210> 25 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-1 <400> 25 Arg Asn Val Met Ser 1 5 <210> 26 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-2 <400> 26 Ser Tyr Ala Met Ser 1 5 <210> 27 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-3 <400> 27 Arg Asn Leu Met Ser 1 5 <210> 28 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-4 <400> 28 Asn Tyr Ala Met Ser 1 5 <210> 29 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-5 <400> 29 Arg Tyr Ala Met Thr 1 5 <210> 30 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-6 <400> 30 Arg Tyr Val Met Ser 1 5 <210> 31 <211> 5 <212> PRT <213> Artificial sequence <220> <223> CDRH1-8 <400> 31 Lys Tyr Asp Met Ser 1 5 <210> 32 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRH1-8 <400> 32 Ser Ser Ser Tyr Trp Ile Cys 1 5 <210> 33 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRH1-9 <400> 33 Ser Ser Gly Tyr Tyr Met Cys 1 5 <210> 34 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-1 <400> 34 Gln Ala Ser Gln Ser Ile Ser Asn Leu Leu Ala 1 5 10 <210> 35 <211> 13 <212> PRT <213> Artificial sequence <220> <223> CDRL1-2 <400> 35 Gln Ser Ser Gln Ser Val Val Asn Asn Asn Arg Cys Ser 1 5 10 <210> 36 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-3 <400> 36 Gln Ala Ser Gln Ser Val Ser Asn Leu Leu Ala 1 5 10 <210> 37 <211> 13 <212> PRT <213> Artificial sequence <220> <223> CDRL1-4 <400> 37 Gln Ser Ser Gln Ser Val Val Asn Asn Asn Arg Leu Ser 1 5 10 <210> 38 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-5 <400> 38 Gln Ala Ser Glu Asn Ile Tyr Ser Phe Leu Ala 1 5 10 <210> 39 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-6 <400> 39 Gln Ala Ser Gln Asn Ile Tyr Ser Asn Leu Ala 1 5 10 <210> 40 <211> 13 <212> PRT <213> Artificial sequence <220> <223> CDRL1-7 <400> 40 Gln Ala Ser Gln Asn Ile Tyr Lys Tyr Asn Asn Leu Ala 1 5 10 <210> 41 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-8 <400> 41 Gln Ala Ser Gln Ser Ile Ser Ser Tyr Leu Ala 1 5 10 <210> 42 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL1-9 <400> 42 Gln Ala Ser Glu Asp Ile Tyr Arg Leu Leu Ala 1 5 10 <210> 43 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-1 <400> 43 Ser Ile Asn Thr Gly Gly Ser Thr Trp Tyr Ala Ser Trp Ala Glu Gly 1 5 10 15 <210> 44 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-2 <400> 44 Tyr Ile Ser Gly Gly Gly Ser Thr Tyr Tyr Tyr Ala Ser Trp Val Lys Gly 1 5 10 15 <210> 45 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-3 <400> 45 Ser Ile Asn Phe Arg Asn Ile Thr Trp Tyr Ala Ser Trp Ala Lys Gly 1 5 10 15 <210> 46 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-4 <400> 46 Tyr Ile Ser Ala Ser Gly Asn Thr Tyr Tyr Ala Ser Trp Val Lys Gly 1 5 10 15 <210> 47 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-5 <400> 47 Ile Ile Gly Ala Ser Ser Gly Thr Trp Tyr Ala Ser Trp Ala Lys Gly 1 5 10 15 <210> 48 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-6 <400> 48 Phe Ile Asn Ala Ser Gly Ser Thr Ser Tyr Ala Ser Trp Ala Lys Gly 1 5 10 15 <210> 49 <211> 16 <212> PRT <213> Artificial sequence <220> <223> CDRH2-7 <400> 49 Ala Ile Gly Gly Arg Gly Val Thr Asp Tyr Thr Thr Trp Ala Lys Gly 1 5 10 15 <210> 50 <211> 18 <212> PRT <213> Artificial sequence <220> <223> CDRH2-8 <400> 50 Cys Ile Tyr Ala Gly Ser Ser Asp Ile Thr Tyr Tyr Ala Ser Trp Ala 1 5 10 15 Lys Gly <210> 51 <211> 18 <212> PRT <213> Artificial sequence <220> <223> CDRH2-9 <400> 51 Cys Ile Tyr Ala Gly Ser Ser Ser Gly Thr Thr Tyr Tyr Ala Ser Trp Ala 1 5 10 15 Lys Gly <210> 52 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-1 <400> 52 Ala Ala Ser Pro Leu Ala Ser 1 5 <210> 53 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-2 <400> 53 Ser Ala Ser Thr Leu Ala Ser 1 5 <210> 54 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-3 <400> 54 Gly Ala Ser Lys Leu Glu Ser 1 5 <210> 55 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-5 <400> 55 Arg Ala Ser Thr Leu Ala Ser 1 5 <210> 56 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-5 <400> 56 Phe Ala Ser Lys Leu Val Ser 1 5 <210> 57 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-6 <400> 57 Tyr Ala Ser Thr Leu Val Ser 1 5 <210> 58 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-7 <400> 58 Glu Ala Ser Lys Leu Ala Ser 1 5 <210> 59 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-8 <400> 59 Leu Ala Ser Thr Leu Glu Ser 1 5 <210> 60 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRL2-9 <400> 60 Asp Ala Ser Asp Leu Ala Ser 1 5 <210> 61 <211> 12 <212> PRT <213> Artificial sequence <220> <223> CDRH3-1 <400> 61 Gly Val Tyr Gly His Ser Asn Gly Tyr Tyr Ser Leu 1 5 10 <210> 62 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRH3-2 <400> 62 Gly Tyr Pro Gly Tyr Ile Ser Gly Thr Trp Ala 1 5 10 <210> 63 <211> 12 <212> PRT <213> Artificial sequence <220> <223> CDRH3-4 <400> 63 Gly Val Tyr Val Asn Ser Asn Gly Tyr Tyr Ser Leu 1 5 10 <210> 64 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRH3-4 <400> 64 Gly Tyr Ser Gly Trp Ile Ser Gly Thr Trp Ala 1 5 10 <210> 65 <211> 12 <212> PRT <213> Artificial sequence <220> <223> CDRH3-5 <400> 65 Asp Asn Gly Asp Ser Lys Asp Tyr Ala Phe Asp Pro 1 5 10 <210> 66 <400> 66 000 <210> 67 <211> 7 <212> PRT <213> Artificial sequence <220> <223> CDRH3-7 <400> 67 Ala Leu Ala Gly Asp Thr Leu 1 5 <210> 68 <211> 18 <212> PRT <213> Artificial sequence <220> <223> CDRH3-8 <400> 68 Gly Arg Tyr Tyr Val Asp Gly Tyr Ala Asp Tyr Tyr Pro Gly Asp Phe 1 5 10 15 Asn Leu <210> 69 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRH3-9 <400> 69 Gly Pro Gly Ala Ser Gly Tyr Arg Leu Gly Leu 1 5 10 <210> 70 <211> 14 <212> PRT <213> Artificial sequence <220> <223> CDRL3-1 <400> 70 Gln Ser Tyr Trp Gly Gly Ser Gly Glu Arg Tyr Leu Asn Thr 1 5 10 <210> 71 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL3-2 <400> 71 Leu Gly Asp Tyr Val Ser Tyr Gly Asp Ser Ala 1 5 10 <210> 72 <211> 14 <212> PRT <213> Artificial sequence <220> <223> CDRL3-3 <400> 72 Gln Thr Tyr Trp Gly Gly Asp Gly Thr Ser Tyr Leu Asn Pro 1 5 10 <210> 73 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL3-5 <400> 73 Leu Gly Asp Tyr Val Ser Tyr Ser Glu Ala Ala 1 5 10 <210> 74 <211> 12 <212> PRT <213> Artificial sequence <220> <223> CDRL3-5 <400> 74 Gln Gln Thr Tyr Thr Tyr Ser Asn Gly Asp Asn Pro 1 5 10 <210> 75 <211> 13 <212> PRT <213> Artificial sequence <220> <223> CDRL3-8 <400> 75 Gln Ser Lys Asp Gly Pro Thr Ser Ser Thr Tyr Gly Ala 1 5 10 <210> 76 <211> 13 <212> PRT <213> Artificial sequence <220> <223> CDRL3-7 <400> 76 Gln Gly Thr Phe Glu Cys Ser Ser Ala Asp Cys Phe Gly 1 5 10 <210> 77 <211> 14 <212> PRT <213> Artificial sequence <220> <223> CDRL3-8 <400> 77 Gln Ser Tyr Tyr Tyr Ser Ser Ser Ser Ser Tyr Gly Ser Ala 1 5 10 <210> 78 <211> 11 <212> PRT <213> Artificial sequence <220> <223> CDRL3‑9 <400> 78 Gln Gln Gly Tyr Tyr Ile Ser Gly Gly Asp Ser 1 5 10

Claims

1. Use of at least one reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO: 1 in the preparation of a kit for assessing atrial fibrillation in a subject, comprising the following steps: a) Determine the amount of one or more BMP10-type peptides (bone morphogenetic protein 10-type peptides) in at least one sample from said subject, and b) The amount of the BMP10-type peptide is compared with a reference amount of the BMP10-type peptide to assess atrial fibrillation. Step a) includes contacting the sample with at least one reagent capable of binding within amino acid regions 37 to 299 of the peptide shown in SEQ ID NO: 1, wherein the BMP10-type peptide comprises the amino acid sequence of SEQ ID NO:

6. The reagent is a monoclonal antibody or its antigen-binding fragment, and the monoclonal antibody or its antigen-binding fragment comprises: The heavy chain CDRH1 of SEQ ID NO: 27 (RNLMS), the heavy chain CDRH2 of SEQ ID NO: 45 (SINFRNITWYASWAKG), the heavy chain CDRH3 of SEQ ID NO: 63 (GVYVNSNGYYSL), the light chain CDRL1 of SEQ ID NO: 36 (QASQSVSNLLA), the light chain CDRL2 of SEQ ID NO: 54 (GASKLES), and the light chain CDRL3 of SEQ ID NO: 72 (QTYWGGDGTSYLNP).

2. The use according to claim 1, wherein the monoclonal antibody or its antigen-binding fragment comprises: The heavy chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO: 9, and the light chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO:

18.

3. The use according to claim 1, wherein step a) comprises contacting the sample with at least one additional reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO: 1, wherein the at least one additional reagent is a monoclonal antibody or an antigen-binding fragment thereof, comprising: The heavy chain CDRH1 of SEQ ID NO: 28 (NYAMS), the heavy chain CDRH2 of SEQ ID NO: 46 (YISASGNTYYASWVKG) and the heavy chain CDRH3 of SEQ ID NO: 64 (GYSGWISGTWA), the light chain CDRL1 of SEQ ID NO: 37 (QSSQSVVNNNRLS), the light chain CDRL2 of SEQ ID NO: 55 (RASTLAS) and the light chain CDRL3 of SEQ ID NO: 73 (LGDYVSYSEAA).

4. The use according to claim 3, wherein the at least one additional reagent is a monoclonal antibody or an antigen-binding fragment thereof, comprising: The heavy chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO: 10, and the light chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO:

19.

5. The use according to any one of claims 1 to 3, wherein the assessment of atrial fibrillation is for the diagnosis of atrial fibrillation.

6. The use according to any one of claims 1 to 3, wherein the assessment of atrial fibrillation is a prediction of the risk of adverse events associated with atrial fibrillation, wherein the adverse events associated with atrial fibrillation are recurrence of atrial fibrillation and / or stroke.

7. The use according to claim 6, wherein the recurrence of atrial fibrillation is a recurrence of atrial fibrillation following pulmonary vein isolation or ablation therapy.

8. The use according to claim 6, wherein the amount of the BMP10-type peptide indicates the risk of the subject having adverse events related to atrial fibrillation, and / or wherein the amount of the BMP10-type peptide below the reference amount indicates that the subject does not have the risk of the subject having adverse events related to atrial fibrillation.

9. Use of at least one reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO: 1 in the preparation of a kit for diagnosing heart failure, comprising the following steps: (a) Determining the amount of one or more BMP10-type peptides in at least one sample from a subject, and (b) The amount of the BMP10-type peptide is compared with a reference amount of the BMP10-type peptide to diagnose heart failure. Step a) includes contacting the sample with at least one reagent capable of binding within amino acid regions 37 to 299 of the peptide shown in SEQ ID NO: 1, wherein the at least one reagent is a monoclonal antibody or an antigen-binding fragment thereof as defined in claim 1, wherein the BMP10-type peptide comprises the amino acid sequence of SEQ ID NO:

6.

10. Use of at least one reagent capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO: 1 in the preparation of a kit for diagnosing heart failure, comprising the following steps: (a) Determining the amount of one or more BMP10-type peptides and the amount of at least one other biomarker selected from the group consisting of natriuretic peptides, ESM-1, Ang2, and FABP3 in at least one sample from a subject, and (b) Diagnosing heart failure by comparing the amount of the BMP10-type peptide with a reference amount of the BMP10-type peptide and by comparing the amount of the at least one other biomarker with a reference amount of the at least one other biomarker. Step a) includes contacting the sample with at least one reagent capable of binding within amino acid regions 37 to 299 of the peptide shown in SEQ ID NO: 1, wherein the at least one reagent is a monoclonal antibody or an antigen-binding fragment thereof as defined in claim 1, wherein the BMP10-type peptide comprises the amino acid sequence of SEQ ID NO:

6.

11. A monoclonal antibody or an antigen-binding fragment thereof, capable of binding within amino acid regions 37 to 299 of the polypeptide shown in SEQ ID NO: 1, wherein the antibody or antigen-binding fragment thereof comprises: The heavy chain CDRH1 of SEQ ID NO: 27 (RNLMS), the heavy chain CDRH2 of SEQ ID NO: 45 (SINFRNITWYASWAKG), the heavy chain CDRH3 of SEQ ID NO: 63 (GVYVNSNGYYSL), the light chain CDRL1 of SEQ ID NO: 36 (QASQSVSNLLA), the light chain CDRL2 of SEQ ID NO: 54 (GASKLES), and the light chain CDRL3 of SEQ ID NO: 72 (QTYWGGDGTSYLNP).

12. The monoclonal antibody or antigen-binding fragment thereof according to claim 11, wherein the monoclonal antibody or antigen-binding fragment thereof comprises: The heavy chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO: 9, and the light chain variable domain is at least 90%, 95%, 98%, 99% or 100% identical to the sequence shown in SEQ ID NO:

18.

13. A kit comprising at least one monoclonal antibody or antigen-binding fragment thereof as defined in claim 1 or any one of 11 to 12.

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