Cmybp-c for the assessment of asymptomatic heart failure

Abstract

The present invention relates to a method for assessing asymptomatic heart failure said method comprising cMyBP-C (Myosin binding protein C, cardiac type), and optionally the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample from the subject. The present invention further relates to computer-implemented methods, databases, devices, kits and uses related thereto.

Description

[0001] Roche Diagnostics GmbH October 30, 2025

[0002] Roche Diagnostics International AG RD39606PC cMyBP-C for the assessment of asymptomatic heart failure

[0003] FIELD OF THE INVENTION

[0004] The present invention relates to a method for assessing asymptomatic heart failure said method comprising cMyBP-C (Myosin binding protein C, cardiac type), and optionally the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample from the subject. The present invention further relates to computer-implemented methods, databases, devices, kits and uses related thereto.

[0005] BACKGROUND

[0006] An aim of modern medicine is to provide personalized or individualized treatment regimens. Those are treatment regimens which take into account a patient's individual needs or risks. Personalized or individual treatment regimens may even be taken into account for measures where it is required to decide on potential treatment regimens.

[0007] Heart failure (HF) is a major and growing public health problem. It is estimated that approximately 5 million patients in the USA have HF, more than 500000 patients are diagnosed with HF for the first time each year, and more than 50.000 patients in the US die each year of HF as a primary cause. Heart failure (HF) is one of the main causes of morbidity and mortality in developed countries. Because of aging of the population and greater longevity of patients with cardiovascular disease incidence and prevalence of HF are increasing.

[0008] In general, HF is diagnosed by e.g. echocardiography and Doppler sonography which, however, only permit to diagnose symptomatic later stages of HF. Individuals suffering from presymptomatic forms of HF cannot be diagnosed by these established methods. Poor diagnostic capabilities is one of the reasons that the survival rate for individuals diagnosed for HF is only 50% for 5 years. Highly sensitive assays of cTnThs or cMyBP-C are suited to detect modest cardiac injury in serum or plasma of ACS patients. The detection of MyL7 in the circulation may be useful to assess the severity of atrial heart tissue damage. The application of NT-proBNP is recommended to exclude the presence of heart failure.

[0009] Heart failure is a complex clinical syndrome that can result from any structural or functional cardiac disorder that impairs the ability of the ventricle to fill with or eject blood and to ensure the body's metabolic needs for supply with blood / oxygen. In such cases, the body tries to compensate lack of supply by structural changes of the myocardium (e.g. fibrosis, apoptosis, necrosis) aiming at maintaining the required supply. First structural changes to the myocardium are, in general, reversible changes but which, when untreated, turn to non reversible permanent changes which finally lead to chronic HF with the final stage of terminal HF. HF is classified into various degrees of severity.

[0010] This classification of American College of Cardiology and the American Heart Association (see Heidenreich et al. 2022 AHA / ACC / HFSA Guideline for the Management of Heart Failure Circulation. 2022;145:e895-el032. DOI: 10.1161 / CIR.0000000000001063) uses the 4 stages A, B, C and D. Stages A and B are not HF but are considered to help identify patients early before developing „truly" HF. Stages A and B patients are best defined as those with risk factors for the development of HF. For example, patients with coronary artery disease, hypertension, or diabetes mellitus who do not yet demonstrate impaired left ventricular (LV) function, hypertrophy, or geometric chamber distortion would be considered stage A, whereas patients who are asymptomatic but demonstrate LV hypertrophy (LVH, a phenomenon in which the walls of the ventricles thicken) and / or impaired LV function would be designated as stage B. Stage C then denotes patients with current or past symptoms of HF associated with underlying structural heart disease (the bulk of patients with HF), and stage D designates patients with truly refractory HF. Arterial hypertension places increased tension on the left ventricular myocardium that is manifested as stiffness and hypertrophy. Independently thereof, atherosclerosis develops within the coronary vessels as a consequence of hypertension. Subjects with hypertension have increased risk of detrimental non-fatal stroke. Antihypertensive medication may help to reduce the risk of detrimental non-fatal stroke. It is known that subjects suffering from diabetes mellitus are at an elevated risk of suffering from atherosclerosis. Subjects suffering from atherosclerosis are at an elevated risk of ischemic stroke. Antihypertensive medication may help to reduce the risk of ischemic stroke and ischemic heart disease.

[0011] Early detection of subtle cardiac alterations (stage B HF) is meaningful to funnel extended echocardiographic assessments or MRI. In particular the sensitive detection of stage B heart failure in asymptomatic patients, e.g. with diabetes or hypertension is an important unmet medical need to improve early preventive patient management. Imaging modalities detect structural changes and LVH relatively late and do not differentiate pathological or molecular processes. Identifying with early HF (stages A / B according to AHA / ACC classification) is important to initiate appropriate preventive treatment before non-reversible progression of HF or major complications occur.

[0012] Several published data describe the association of cTnThs with structural heart disease in asymptomatic patients (stage B heart failure (HF)) including data of the PREDICTOR cohort (see e.g. Masson et al, J Intern Med 2013; 273: 306-317). However, published data of high- sensitivity cardiac troponin and NTproBNP assays show only limited sensitivities for the detection of subtle abnormalities of a cardiac phenotype in general population studies, e.g. cTnThs with a PPV of 33% in Masson et al..

[0013] WO20 16 / 066698 Al discloses a method for predicting the risk of a subject of rapidly progressing to chronic heart failure and / or of hospitalization due to chronic heart failure and / or of death. The method is based on the markers BNP -type peptide, IGFBP7 (IGF binding protein 7), a cardiac Troponin, soluble ST2 (sST2), FGF-23 (Fibroblast Growth Factor 23), Growth Differentiation Factor 15 (GDF-15), Intercellular Adhesion Molecule 1 (ICAM-1) and Angiopoietin-2 (ANG2).

[0014] WO 2012 / 025355A1 discloses biomarkers in the assessment of the early transition from arterial hypertension to heart failure.

[0015] The International patent application PCT / EP2024 / 071529 describes assays for cMyBP-C.

[0016] The European patent application 24164839.3 discloses diagnostic methods based on MyL7. There are no published data available relating to the potential application of cMyBP-C or MyL7 in the assessment of preclinical heart failure.

[0017] Anand et al. describe circulating cMyBP-C concentrations associated with myocardial hypertrophy, fibrosis and increased risk of mortality in patients with aortic stenosis (Mechanism cohort, NCT1755936, Anand A, Heart. 2018 Jul; 104(13): 1101-1108. doi: 10.1136 / heartjnl- 2017-312257. Epub 2017 Dec 1. PMID: 29196542; PMCID: PMC6031261).

[0018] Tong et al. describe that circulating cMyBP-C concentrations have prognostic value for cardiac events within the follow-up period of 1 year in patients undergoing exercise stress echocardiography in a Texas hospital proposed by their physicians. The target population had a higher risk of cardiovascular events versus the general population (Usefulness of Released Cardiac Myosin Binding Protein-C as a Predictor of Cardiovascular Events. Am J Cardiol. 2017 Nov l;120(9):1501-1507. doi: 10.1016 / j.amjcard.2017.07.042. Epub 2017 Jul 31. PMID: 28847594; PMCID: PMC6034604). Kozhuharov et al. disclose that cMyBP-C can be used in the diagnosis and risk stratification of acute heart failure (Eur J Heart Fail. 2021 May;23(5):716-725. doi: 10.1002 / ejhf.2094. Epub 2021 Feb 5. PMID: 33421273).

[0019] Kaier et al. disclose an algorithm using cardiac myosin-binding protein C for early diagnosis of myocardial infarction (European Heart Journal. Acute Cardiovascular Care, Volume 11, Issue 4, April 2022, Pages 325-335).

[0020] Alaour et al. describe acceptable reference change values (RCVs) of cMyBP-C (Alaour et al. Biological variation of cardiac myosin-binding protein C in healthy individuals. Clin Chem Lab Med 2021 https: / / doi.org / 10.1515 / cclm-2021-0306). The authors propose that based on the RCVs serial measurements in disease monitoring might be possible.

[0021] Zhou et al. discloses circulating S-Glutathionylated cMyBP-C as a biomarker for cardiac Diastolic Dysfunction (Zhou et al.. J Am Heart Assoc. 2022 Jun 7;11(1 l):e025295. doi: 10.1161 / JAHA.122.025295. Epub 2022 Jun 3. PMID: 35656993; PMCID: PMC9238749.

[0022] However there are no published data yet available that support the detection of circulating cMyBP-C in association with early stages of structural heart disease (stage B heart failure (HF)) in asymptomatic patients without aortic stenosis. Further, there are no published data describe circulating cMyBP-C for the detection of stage B heart failure in patients with diabetes (stage A HF).

[0023] There is a need for biomarkers, for the assessment of early stages of structural heart disease in asymptomatic patient. It is therefore an objective of the present invention to provide improved means and methods for the assessment of early stages of structural heart disease.

[0024] The present invention, therefore, provides means and methods complying with these needs.

[0025] In the studies underlying the present invention, it was shown that cMyBP-C is a reliable marker for structural heart disease in patients with asymptomatic heart failure, in particular in patients with diabetes and hypertension. Thus, the marker allows, e.g. for the diagnosis of the stage B failure. Advantageously, the marker can be combined with BNP -type peptides, one or more cardiac Troponins, of MyL7 (Myosin light chain 7) and Angiopoietin-2 (Ang-2) to improve the detection. cMyBP-C used for the screening of patients for extended imaging analyses, such as ECG echocardiography or MRI to detect subclinical cardiac phenotypes in heart failure.

[0026] The findings of the present invention are advantageous since they allow for an early diagnosis of structural changes of the heart preceding heart failure and / or preceding left ventricular hypertrophy. Early structural abnormalities of the heart and heart failure often remain undiagnosed, particularly in women. First structural changes to the heart are, in general, reversible changes but which, when untreated, turn to non-rever sible permanent changes which finally may lead to chronic HF with the final stage of terminal HF. Therefore, the early diagnosis of structural changes to the heart since appropriate preventive treatment can be initiated before progression to LVH and / or to heart failure (HF) or other major complications occur.

[0027] THE FIGURES SHOW

[0028] Figure 1: Biomarker concentrations in samples from asymptomatic patients with either Normal classification, stage A or stage B heart failure: A) cMyBP-C, B) Troponin T, C) NT-proBNP, D) MyL7

[0029] Figure 2: Biomarker concentrations in samples from asymptomatic with either stage A or stage B heart failure: A) cMyBP-C, B) Troponin T, C) NT-proBNP D) MyL7

[0030] Figure 3: Biomarker concentrations in samples from asymptomatic patients with diabetes and either stage A or stage B heart failure: A) cMyBP-C, B) Troponin T, C) NT- proBNP D) MyL7

[0031] Figure 4: Biomarker concentrations in samples from asymptomatic patients with normal and elevated LV mass: A) cMyBP-C, B) MyL7 C) Troponin T, D) NT-proBNP E) ANG2

[0032] Figure 5: Biomarker concentrations in samples from asymptomatic patients with hypertension with normal and elevated LV mass: A) cMyBP-C, B) NTproBNP, C) Troponin T D) MyL7, E) ANG2,

[0033] Figure 6: Biomarker concentrations in samples from asymptomatic patients with diabetes with normal and elevated LV mass: A) cMyBP-C, B) ANG2, C) NTproBNP, D) MyL7, E) Troponin T

[0034] BRIEF SUMMARY OF THE PRESENT INVENTION

[0035] The present invention relates to a method for assessing asymptomatic heart failure in a subject, comprising the steps of a) determining the level of cMyBP-C (Myosin binding protein C, cardiac type), and optionally the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample from the subject, and b) assessing asymptomatic heart failure based on the level of cMyBP-C, and, optionally, the level of at least one further biomarker determined in step a).

[0036] In a preferred embodiment of the method of the present invention, step b) comprises comparing the level of cMyBP-C to a reference level and, optionally the level of the at least one further biomarker to a reference level for said at least one biomarker. Preferably, the reference level for each of the determined biomarkers is a predetermined value for the level the respective biomarker which allows for assessing asymptomatic heart failure.

[0037] In a preferred embodiment of the method of the present invention, step b) comprises calculating a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and optionally the level of the at least one further biomarker.

[0038] Preferably, a level of the biomarker cMyBP-C above the reference level for cMyBP-C, optionally, in combination with a level of the at least one further biomarker above the reference level for the at least one further biomarker indicates that the subject suffers from stage B heart failure and / or wherein a level of the biomarker cMyBP-C below the reference level for cMyBP- C, optionally, in combination with a level of the at least one further biomarker below the reference level for the at least one further biomarker indicates that the subject does not suffer from stage B heart failure.

[0039] The present invention further relates to a computer-implemented method for assessing asymptomatic heart failure, comprising a) receiving, at a processing unit, a value for the level of cMyBP-C in a sample from a subject, and, optionally at least one further value for the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2) and at least one BNP -type peptide in said sample, b) comparing, by said processing unit, the value or values received in step a) to a reference or to references and / or calculating, by said processing unit, a score for assessing asymptomatic heart failure, wherein the score is based on the value or values received in step a), and c) assessing, preferably by the processing unit, asymptomatic heart failure based on the result of step b).

[0040] The present invention further relates to the use of a) the biomarker cMyBP-C, or at least one detection agent thereof, and optionally b) at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang- 2), and at least one BNP -type peptide, or at least one detection agent for said at least one further biomarker, in a sample from a subject for assessing asymptomatic heart failure.

[0041] The present invention further relates to a device for assessing asymptomatic heart failure, said device comprising: a) at least one measuring unit for determining an level of the biomarker cMyBP- C and, optionally, an level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2) and at least one BNP -type peptide in sample from a subject, said at least one measuring unit comprising at least one detection agent for the biomarker cMyBP-C and, optionally, at least one detection agent for the biomarker Myl7, at least one detection agent for the biomarker Angiopoietin-2 (Ang-2), at least one detection agent for the at least one BNP -type peptide, at least one detection agent for the at least one cardiac Troponin, and b) an evaluation unit operably linked to the measuring unit, said evaluation unit comprising a data processor comprising instructions for i) carrying out a comparison of the level of the biomarker cMyBP-C and, optionally, of the level of said at least one further biomarker to a reference or references and / or for ii) carrying out a calculation of a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and, optionally, on the level(s) of the at least one further biomarker.

[0042] The present invention further relates to a kit for assessing asymptomatic heart failure, said kit comprising at least one detection agent for the biomarker cMyBP-C and at least one detection agent for the at least one further biomarker selected from the group consisting ofMyL7 (Myosin light chain 7), Ang-2, at least one cardiac Troponin, and at least one BNP -type peptide.

[0043] The present invention further relates to a database comprising one or more stored references for the biomarker cMyBP-C and, optionally one or more stored references for at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), Ang-2, and at least one cardiac Troponin and at least one BNP -type peptide.

[0044] The present invention further relates to a computer program including computer-executable instructions for performing the computer-implemented method according to the present invention, when the program is executed on a computer or computer network. In a preferred embodiment of the methods of the present invention, the use of the present invention, the kit of the present invention and the device of the present invention, the sample is a blood, serum or plasma sample.

[0045] In a preferred embodiment of the present invention, the subject is a human subject. Preferably, the subject is human subject who does not suffer from aortic stenosis.

[0046] In a preferred embodiment of the present invention, the subject does not suffer from stage C or stage D heart failure. Accordingly, the subject is an asymptomatic subject and hence does not show symptoms of heart failure. In a preferred embodiment, the subject does not show the following symptoms of heart failure: Shortness of breath with activity or when lying down, fatigue and weakness, swelling in the legs, ankles and feet, rapid or irregular heartbeat, reduced ability to exercise.

[0047] In a preferred embodiment of the present invention, the subject is suspected to suffer from asymptomatic heart failure. Preferably, a subject who is suspected to suffer from asymptomatic heart failure is suffering from arterial hypertension or diabetes, is obese and / or is 65 years old or older.

[0048] In a preferred embodiment of the present invention, the (test) subject has diabetes, in particular type 2 diabetes.

[0049] In a preferred embodiment of the present invention, the (test) subject suffers from arterial hypertension.

[0050] In a preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the diagnosis of stage B heart failure.

[0051] In another preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the diagnosis of structural heart disease preceding symptomatic heart failure.

[0052] In yet another preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the differentiation between stage B heart failure versus stage A heart failure or no heart failure.

[0053] In yet another preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the differentiation a subject who has structural abnormalities of the heart preceding heart failure and a subject bearing only risk factors of heart failure. In preferred embodiment of the method of the present invention the method, the method further comprises the step of initiating or recommending one or more further diagnostic measures for diagnosing stage B heart failure for a subject who has been diagnosed to suffer from stage B heart failure. In a preferred embodiment, the diagnostic measure is echocardiography or MRI, in particular echocardiography or MRI for determining structural changes of the heart preceding heart failure.

[0054] In preferred embodiment of the method of the present invention the method, the method further comprises initiating or recommending a suitable therapeutic measure for a subject diagnosed to suffer from stage B heart failure.

[0055] In yet another preferred embodiment of the present invention, the assessment the assessment of asymptomatic heart failure is the assessment of the severity of asymptomatic heart failure. In yet another preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the assessment of the extent of structural heart disease in asymptomatic heart failure.

[0056] In yet another preferred embodiment of the present invention, the assessment the assessment of asymptomatic heart failure is the monitoring of asymptomatic heart failure.

[0057] In yet another preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the assessment of asymptomatic heart failure is prediction of the risk to suffer from stage C or D heart failure.

[0058] DETAILED SUMMARY OF THE PRESENT INVENTION / DEFINITIONS

[0059] It is to be understood that as used in the specification and in the claims, “a” or “an” can mean one or more, depending upon the context in which it is used. Thus, for example, reference to “an” item can mean that at least one item can be utilized.

[0060] As used in the following, the terms “have”, “comprise” or “include” or any arbitrary grammatical variations thereof are used in a non-exclusive way. Thus, these terms may both refer to a situation in which, besides the feature introduced by these terms, no further features are present in the entity described in this context and to a situation in which one or more further features are present. As an example, the expressions “A has B”, “A comprises B” and “A includes B” may both refer to a situation in which, besides B, no other element is present in A (i.e. a situation in which A solely and exclusively consists of B) and to a situation in which, besides B, one or more further elements are present in entity A, such as element C, elements C and D or even further elements. The term “comprising” also encompasses embodiments where only the items referred to are present, i.e. it has a limiting meaning in the sense of “consisting of’.

[0061] Further, it will be understood that the term “at least one” as used herein means that one or more of the items referred to following the term may be used in accordance with the invention. For example, if the term indicates that at least one sampling unit shall be used this may be understood as one sampling unit or more than one sampling units, i.e. two, three, four, five or any other number. Depending on the item the term refers to, the skilled person understands as to what upper limit the term may refer, if any. For example, the term at least one further biomarker may mean, one, two, three, four or five biomarkers.

[0062] The term “about” as used herein means that with respect to any number recited after said term an interval accuracy exists within in which a technical effect can be achieved. Accordingly, "about" as referred to herein, preferably, refers to the precise numerical value or a range around said precise numerical value of ±20 %, preferably ±15 %, more preferably ±10 %, or even more preferably ±5 %.

[0063] As used herein, the term “level” includes any and all measure of quantity deemed suitable by the skilled person, and in particular includes an absolute amount of a compound referred to herein, a relative level, or a concentration of the compound, as well as any value or parameter which correlates thereto or can be derived therefrom, in an embodiment by standard mathematical operations. Such values or parameters comprise intensity signal values from all specific physical or chemical properties obtained from the said compounds by direct measurements, e.g., intensity values in mass spectra or NMR spectra. Moreover, encompassed are all values or parameters which are obtained by indirect measurements specified elsewhere in this description, e.g., response levels determined from biological read out systems in response to the compounds or intensity signals obtained from specifically bound ligands, such as detection compounds.

[0064] The term “determining” as used herein refers to semiquantitative or quantitative determination of a biomarker referred to herein. Determining the level of a biomarker may be carried out by any technique which allows for establishing a measure of quantity of a biomarker in a semiquantitative or quantitative manner. Suitable techniques depend on the molecular nature and the properties of the biomarkers and are discussed elsewhere herein in more detail.

[0065] The term “comparing” as used herein encompasses comparing the determined level for a biomarker as referred to herein to a reference. It is to be understood that comparing as used herein refers to any kind of comparison made between the value for the level with the reference. However, it is to be understood that, in an embodiment, identical types of values are compared with each other, e.g., if an absolute amount is determined, the reference shall also be an absolute amount, if a relative amount is determined, the reference shall also be a relative amount, etc. The term comparing also encompasses comparing a calculated score with a suitable reference core. The comparison may be carried out manually or computer assisted. The value of the level and the reference can be, e.g., compared to each other and the said comparison can be automatically carried out by a computer program executing an algorithm for the comparison. The computer program carrying out the said evaluation will provide the desired assessment in a suitable output format.

[0066] The term “kit” as used herein refers to a collection of the aforementioned components, typically, provided in separate compound(s) or as a mixture of compounds. The means are, in an embodiment, provided in a single container (i.e. a housing), in a further embodiment enabling common translocation, e.g. transport, of the components. The container also typically comprises instructions for carrying out the method of the present invention. These instructions may be in the form of a manual or may be provided by a computer program code which is capable of carrying out or supports the determination of the biomarkers referred to in the methods of the present invention when implemented on a computer or a data processing device. The computer program code may be provided on a data storage medium or device such as an optical storage medium (e.g., a Compact Disc) or directly on a computer or data processing device or may be provided in a download format such as a link to an accessible server or cloud. Moreover, the kit may, usually, comprise standards for reference levels of biomarkers for calibration purposes. The kit may also comprise further components which are necessary for carrying one of the methods described herein, may assist in doing so, or may provide further functions; in an embodiment, the further component is a solvent, a buffer, a diluent, a washing solution and / or one or more reagent(s) required for detection of the biomarkers. Further, the kit may comprise the device of the invention either in parts or in its entirety.

[0067] The term “device” as used herein relates to a combination of means comprising the aforementioned units operatively linked to each other as to allow the determination of the levels of biomarkers and evaluation thereof according to a method as specified herein such that an assessment can be provided. The device comprises at least one measuring unit and at least one evaluation unit.

[0068] The term “detection agent”, for which also "detection compound" may be used, as used herein, refers to any agent which allows determination, in an embodiment specific determination, of a level of at least one biomarker. Thus, the detection agent may in particular be a reaction substrate, e.g. in case the biomarker has catalytic activity, e.g. is an enzyme; or the detection agent may be an agent binding, in an embodiment specifically, to a biomarker or analyte thereof. The skilled person selects suitable detection substrates in dependence on the biomarker, i.e. catalytic activity, to be detected, based on information available in the art. For specific biomarkers, example substrates are provided herein above. Also, binding agents for specific antigens, as well as methods for providing them, are known in the art. As indicated herein above, the detection agent being a binding agent in an embodiment specifically binds to a biomarker, i.e. does not cross-react with other components present in the sample. Typically, a detection agent specifically binding a biomarker as referred to herein may be an antibody, an antibody fragment or derivative, an aptamer, a ligand for the biomarker, a receptor for the biomarker, an enzyme known to bind and / or convert the biomarker, or a small molecule known to specifically bind to the biomarker. For example, antibodies as referred to herein as detection agents include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments that are capable of binding antigen or hapten. Aptamer detection agents, e.g., may be nucleic acid or peptide aptamers. Methods to prepare such aptamers are well-known in the art. The detection agent may be fused or linked permanently or reversibly to a detectable label. Suitable labels are well known to the skilled artisan. Suitable detectable labels are any labels detectable by an appropriate detection method. Typical labels include gold particles, latex beads, acridan ester, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels ("e.g. magnetic beads", including paramagnetic and superparamagnetic labels), and fluorescent labels.

[0069] In a preferred embodiment, the detection agent is an antibody, or antigen-binding fragment thereof which specifically binds the marker.

[0070] “Specific binding” of a detection agent means that it should not bind substantially to, i.e. crossreact with, another peptide, polypeptide or substance present in the sample to be analyzed. Preferably, the specifically bound biomarker should be bound with at least 3 times higher, more preferably at least 10 times higher and even more preferably at least 50 times higher affinity than any other components of the sample. Non-specific binding may be tolerable, if it can still be distinguished and measured unequivocally, e.g. according to its size on a Western Blot, or by its relatively higher abundance in the sample.

[0071] The term “computer-implemented” as used herein means that the method is carried out in an automated fashion on a data processing unit which is, typically, comprised in a computer or similar data processing device. The data processing unit shall receive values for the level of the biomarkers. Such values can be the levels, relative levels or any other calculated value reflecting the level as described elsewhere herein in detail. Accordingly, it is to be understood that the aforementioned method does not require the determination of levels for the biomarkers but rather uses values for already predetermined levels.

[0072] The term "receiving", as used herein, relates to acquiring the indicated information, in particular a value of a parameter such as a level of a biomarker, in a manner enabling basing the assessment on said information. Thus, in an embodiment, receiving is reading the information from a data carrier, e.g. in the form of a data sheet, analysis device output, e.g. a result of an immunoassay, a mass spectrum, or the like; or from a database comprising at least the relevant information. In an embodiment, the information obtained comprises value(s) for level(s) of biomarkers determined as specified herein above. The data carrier and / or the database may be local, i.e. physically connected to a device used to perform steps of the method; they may, however, also be remote, accessible via a network connection or via the internet; thus, the data carrier and / or the data carrier may e.g. be cloud storage. Also, the method may be implemented as a service provided by means of a network connection, e.g. via internet, in which values of the biomarkers, or one or more score(s) derived therefrom, are obtained from e.g. a device performing the determination or medical practitioner, and the result of the comparison it output.

[0073] The term “database”, as used herein, refers to a collection of data which may be physically and / or logically grouped together. Accordingly, the database in an embodiment comprises an allocation of references to assessment results. As the skilled person understands from the description herein above, "stored references for the biomarker...." may also be one or more scores derived from said references. The database, in an embodiment, comprises further data, such as upper and / or lower detection limits, references for further biomarkers, in particular those described herein above, data relevant for plausibility checks, and the like. In a further embodiment, the database comprises data on one or more assay methods to use, lot-specific data, e.g. for calibrator samples, and the like. In an embodiment, the database may be implemented in a single data storage medium or in physically separated data storage media being operatively linked to each other. In an embodiment, the database comprises a data collection on a suitable storage medium, in an embodiment tangible embedded thereon. Moreover, the database, in an embodiment, further comprises a database management system. The database management system is, in an embodiment, a network-based, hierarchical or object-oriented database management system. Furthermore, the database may be a federal or integrated database. In a further embodiment, the database will be implemented as a distributed (federal) system, e.g. as a Client-Server-System. In a further embodiment, the database is structured as to allow a search algorithm to compare a test data set with the data sets, in particular the references, comprised by the data collection. Specifically, by using such an algorithm, the database can be searched for similar or identical data sets being indicative for a medical condition or effect as set forth above (e.g. a query search). Thus, in an embodiment, if data set fulfilling the comparison criteria as detailed elsewhere herein can be identified in the database, the test data set will be associated with the said medical condition or effect. Consequently, the information obtained from the database can be used, e.g., as a reference for the methods described elsewhere herein.

[0074] The term “heart failure” as used herein relates to an impaired systolic and / or diastolic function of the heart being accompanied by overt signs of heart failure as known to the person skilled in the art. According to some embodiments, heart failure referred to herein is also chronic heart failure. Heart failure according to the present disclosure includes overt and / or advanced heart failure. In overt heart failure, the subject shows symptoms of heart failure as known to the person skilled in the art.

[0075] The present invention deals with the assessment of heart failure stages that precede overt heart failure. The term “overt heart failure” “symptomatic heart failure” as used herein refers to stages C and D of the ACC / AHA classification; in these stages, the subject shows typical symptoms of heart failurem i.e. the subject is not apparently healthy. The subject having heart failure and being classified into stage C or D has undergone permanent, non reversible structural and / or functional changes to his myocardium, and as a consequence of these changes, full health restoration is not possible. A subject having attained stage C or even D of the ACC / AHA classification cannot go back to stage B or even A.

[0076] Permanent structural or functional damages to the myocardium which are typical for heart failure are known to the person skilled in the art and include a variety of molecular cardiac remodelling processes, such as interstitial fibrosis, inflammation, infiltration, scar formation, apoptosis, necrosis. A stiffer ventricular wall due to interstitial fibrosis causes inadequate filling of the ventricle in diastolic dysfunction. Permanent structural or functional damages to the myocardium are caused by dysfunction or destruction of cardiac myocytes. Myocytes and their components can be damaged by inflammation or by infiltration. Toxins and pharmacological agents (such as ethanol, cocaine, and amphetamines) cause intracellular damage and oxidative stress. A common mechanism of damage is ischemia causing infarction and scar formation. After myocardial infarction, dead myocytes are replaced by scar tissue, deleteriously affecting the function of the myocardium. On echocardiogram, this is manifest by abnormal or absent wall motion.

[0077] The present invention refers to the ACC / AHA classification of heart failure. The first 2 stages (A and B) are clearly not HF but are an attempt to help healthcare providers identify patients early who are at risk for developing HF. Stages A and B patients are best defined as those with risk factors that clearly predispose toward the development of HF. Stage C then denotes patients with current or past symptoms of HF associated with underlying structural heart disease, and Stage D designates patients with truly refractory HF who might be eligible for specialized, advanced treatment strategies such as mechanical circulatory support, procedures to facilitate fluid removal, continuous inotropic infusions, or cardiac transplantation or other innovative or experimental surgical procedures, or for end-of-life care, such as hospice. This classification recognizes that there are established risk factors and structural prerequisites for the development of HF and that therapeutic interventions introduced even before the appearance of LV dysfunction or symptoms can reduce the population morbidity and mortality of HF.

[0078] For example, stage A heart failure encompasses patients at high risk of developing HF because of the presence of conditions that are strongly associated with the development of HF. Such patients have no identified structural or functional abnormalities of the pericardium, myocardium, coronary circulation or cardiac valves and have never shown signs or symptoms of HF. Examples are e.g. patients with systemic hypertension; coronary artery disease; diabetes mellitus; history of cardiotoxic drug therapy or alcohol abuse; personal history of rheumatic fever; family history of cardiomyopathy. For example, stage B heart failure encompasses patients which have developed structural heart disease that is strongly associated with the development of HF but who have never shown signs or symptoms of HF.

[0079] Structural heart disease preceding overt heart failure and stage B heart failure typically result from compensatory mechanisms, such as peripheral vasoconstriction, salt and water retention, or enhanced contractility of noninfarcted myocardium, to maintain homeostatic levels of systemic blood flow and pressure. Structural changes (also referred to as “remodeling”) result in an increased LV chamber size (dilatation) and wall thickness (hypertrophy) as compared to the normal heart. Preferably, a subject suffering from structural heart disease preceding over heart failure or stage B heart failure shows one or more of the following: left ventricular structural changes, septum enlargement, an increased LV chamber size and an increased posterial wall diameter.

[0080] The subject to be tested in accordance with present invention preferably does not suffer from aortic stenosis. The term “aortic stenosis” as used herein refers to the narrowing of the exit of the left ventricle of the heart. It is a valvular heart disease. The valve between the lower left heart chamber and the aorta is narrowed and doesn't open fully. This reduces or blocks blood flow from the heart to the aorta and to the rest of the body. The stenonis may occur at the aortic valve as well as above and below this level. It typically gets worse over time. Causes include, e.g. being born with a bicuspid aortic valve and rheumatic fever.

[0081] As set forth above, the present invention relates to method for assessing asymptomatic heart failure, such as the diagnosis of structural heart disease preceding overt heart failure (e.g. stage B heart failure). The method will be described herein below in more detail. The present invention further relates to computer-implemented methods, databases, devices, kits and uses related thereto. The definition and explanations given in connection with the method for assessing asymptomatic heart failure in a subject, preferably, apply mutatis mutandis to computer-implemented methods, databases, devices, kits and uses related thereto.

[0082] The assessment made in accordance with the method of the present invention is preferably based on the biomarker cMyBP-C. Accordingly, the method of the present invention comprises step a) of determining the level of cMyBP-C in a sample, such as a blood, serum or plasma sample, from the subject. In a preferred embodiment, the method of the present invention, the method further comprises in step a) the determination of the level(s) of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide

[0083] Thus, the present invention method for assessing asymptomatic heart failure in a subject, comprising the steps of a) determining the level of cMyBP-C and optionally, the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample, such as a blood, serum or plasma sample, from the subject, and b) assessing asymptomatic heart failure based on the level of the biomarker cMyBP-C and optionally the level of the at least one further biomarker as determined in step a).

[0084] In an embodiment, step b) of the above method comprises comparing the level of cMyBP-C to a reference level for cMyBP-C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker. Thereby, asymptomatic heart failure is assessed (i.e. based on the comparison step).

[0085] In an alternative embodiment, step b) of the above method comprises calculating a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and, optionally, the level(s) of the at least one further biomarker, Thereby, asymptomatic heart failure is assessed (i.e. based on the calculated score).

[0086] The method as referred to in accordance with the present invention preferably, is an ex vivo and more preferably an in vitro method. Moreover, the method may be a method which essentially consists of the aforementioned steps or a method which includes further steps. Thus, it may comprise steps in addition to those explicitly mentioned above. For example, the method comprise prior to step a) the step of selecting a sample from a subject as referred to herein, e.g. a patient suspected to suffer from asymptomatic heart failure. For example, further steps may relate to the determination of further markers and / or evaluation of the results obtained by the method. The method may be carried out manually or assisted by automation. Preferably, the method may in total or in part be assisted by automation, e.g., by a suitable robotic and sensory equipment for the determination in step (a) or a computer-implemented calculation step or comparison step.

[0087] In accordance with the present invention, asymptomatic heart failure shall be assessed. Preferably, the term “for assessing asymptomatic heart failure”, relates to

[0088] • the diagnosis of structural heart disease preceding symptomatic heart failure, in particular the diagnosis of stage B heart failure • the identification of a subject who is eligible to a further diagnostic measures for assessing asymptomatic heart failure,

[0089] • the differentiation between i) stage B heart failure versus ii) stage A heart failure or no heart failure,

[0090] • the differentiation between i) stage B heart failure versus ii) stage A heart failure,

[0091] • the differentiation between a subject who has structural abnormalities of the heart preceding heart failure and a subject bearing only risk factors of heart failure.

[0092] • the assessment of the severity of asymptomatic heart failure,

[0093] • the monitoring of asymptomatic heart failure,

[0094] • the prediction of the risk to suffer from stage C or D heart failure, or

[0095] • the identification of a subject who is eligible to a heart failure therapy

[0096] The various assessments of the present invention are described herein below in more detail. As will be understood by those skilled in the art, the assessment of the present invention is usually not intended to be correct for 100% of the subjects to be tested. The term, typically, requires that a correct assessment (such as the diagnosis, differentiation, monitoring, or identification of a subject as referred as referred to herein) can be made for a statistically significant portion of subjects. Whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p- value determination, Student's t-test, Mann- Whitney test etc. Details are found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Typically envisaged confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%. The p-values are, typically, 0.2, 0.1, 0.05. Also typically, the assessment may be done with a preselected sensitivity and specificity.

[0097] Establishing an assessment as referred to herein may be based on the aforesaid assessment. For example, the diagnosis of stage B heart failure may be based on the determined level of the biomarker cMyBP-C and optionally on the determined level of the at least one further biomarker. However, in a further embodiment, the assessment based on the aforesaid assessment is based on the determined level(s) of the biomarker in combination with further diagnostic information, such as the results from one or more further diagnostic measures for assessing asymptomatic heart failure.

[0098] Preferred further diagnostic measures for assessing asymptomatic heart failure are echocardiography, electrocardiography, or MRI (Magnetic resonance imaging). In an embodiment, the further diagnostic measure for assessing asymptomatic heart failure is echocardiography. In another embodiment, the further diagnostic measure for assessing asymptomatic heart failure is electrocardiography. In yet another embodiment, the further diagnostic measure for assessing asymptomatic heart failure is MRI. Preferably, the further diagnostic measure is carried out for determining structural changes of the heart preceding heart failure.

[0099] Diagnosing structural heart disease preceding symptomatic heart failure / stage B heart failure

[0100] In a preferred embodiment of the present invention, the assessment of asymptomatic heart failure is the diagnosis of structural heart disease preceding symptomatic, i.e. overt, heart failure, i.e. it is diagnosed whether a test subject is likely to suffer from said structural heart disease, or is not likely to suffer therefrom. In case a subject is diagnosed to be likely to suffer from said structural heart disease, a further diagnostic measure such as echocardiography or MRI for determining structural changes could be recommended or initiated.

[0101] Accordingly, the present invention envisages a method for diagnosing structural heart disease preceding symptomatic heart failure in a subject, comprising the steps of a) determining the level of cMyBP-C and, optionally, the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample from the subject, and b) diagnosing structural heart disease preceding symptomatic heart failure based on the level of cMyBP-C and, optionally, the level of the at least one further biomarker determined in step a).

[0102] In preferred embodiment, step b) of the above diagnostic method comprises

[0103] (b) comparing the level of the biomarker cMyBP-C to a reference level for cMyBP-C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker, whereby structural heart disease preceding symptomatic heart failure is to be diagnosed.

[0104] Alternatively, a score may be calculated for the diagnosis of structural heart disease (such as stage B heart failure). Thus, the diagnosis is based on the score. Accordingly, in an another preferred embodiment, step b) of the above diagnostic method comprises

[0105] (b) calculating a score for diagnosing structural heart disease preceding symptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and, optionally, the level(s) of the at least one further biomarker, whereby structural heart disease preceding symptomatic heart failure is to be diagnosed.

[0106] In accordance with the above method, it shall be diagnosed whether a test subject is likely to suffer from structural heart disease (such as stage B heart failure), or is not likely to suffer from structural heart disease (such as stage B heart failure). Accordingly, the term “diagnosing” typically refers to assessing the probability of a subject to suffer from the disease or not (at the time of the testing).

[0107] A subject who is likely to suffer from a disease or condition has higher probability of suffering from the disease or condition as compared to the average risk in a cohort of subjects (i.e. a group of subjects). The probability depends on the preselected sensitivity of the assay. A subject who is not likely to suffer from a disease or condition has lower probability of suffering from the disease or condition as compared to the average risk in a cohort of subjects (i.e. a group of subjects).

[0108] Preferably, the subject to be tested in connection with method for diagnosing of structural heart disease (such as stage B heart failure) thereof is a subject who is suspected to suffer from asymptomatic heart failure (as described elsewhere herein). However, it is also contemplated that the subject already has been diagnosed previously to suffer from structural heart disease (such as stage B heart failure) and that the previous diagnosis is confirmed by carrying out the method of the present invention.

[0109] In a preferred embodiment of the diagnostic method, structural heart disease (such as stage B heart failure is ruled in. A patient in which the diagnosis is ruled in has high likelihood to suffer from structural heart disease (such as stage B heart failure).

[0110] In another preferred embodiment of the diagnostic method, structural heart disease (such as stage B heart failure) is ruled out. Thus, a diagnosis of structural heart disease (such as stage B heart failure) is excluded. A patient in which the diagnosis is ruled out has a low likelihood to suffer from structural heart disease (such as stage B heart failure). Typically, such a patient does not require further diagnostic or therapeutic measures with respect to asymptomatic heart failure. A rule out of a disease requires a reference level which allows for a high sensitivity.

[0111] In an embodiment of the method of diagnosing structural heart disease preceding symptomatic heart failure, said method further comprises a step of recommending and / or initiating one or more therapeutic methods that aim to treat structural heart disease (such as stage B heart failure). Preferably, said one or more therapeutic measures are recommended or initiated if it is diagnosed that the subject suffers from structural heart disease (such as stage B heart failure). Preferred therapeutic measures are described elsewhere herein.

[0112] Typically, increased level of the markers as referred to herein (as compared to the reference) are indicative for the presence of structural heart disease (such as stage B heart failure). Typically, decreased level of the markers (as compared to the reference) are indicative for the absence of structural heart disease (such as stage B heart failure). Method for differentiation

[0113] The term “differentiating” as used herein, in an embodiment, means differentiating whether i) a subject has stage B heart failure or ii) the subject has stage A heart failure or no heart failure. In another embodiment, the term refers the differentiation whether a subject suffers from stage B heart failure or from stage A heart failure, In yet another embodiment, is it differentiated between i) a subject who has structural abnormalities of the heart preceding heart failure and ii) a subject bearing only risk factors of heart failure.

[0114] In an embodiment, the present invention, thus, relates to a method for differentiating between i) a subject who has stage B heart failure or ii) a subject who has stage A heart failure or no heart failure, comprising the steps of a) determining the level of cMyBP-C and, optionally, the level of at least one further biomarker selected from the group MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample from the subject, and b) comparing the level of the biomarker cMyBP-C to a reference level for cMyBP- C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker, whereby it is differentiated between i) or ii).

[0115] In another embodiment, the present invention relates to a method for differentiating between i) a subject who has stage B heart failure or ii) a subject who has stage A heart failure or no heart failure, comprising the steps of a) determining the level of cMyBP-C and, optionally, the level of at least one further biomarker selected from the group MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample from the subject, and b) comparing the level of the biomarker cMyBP-C to a reference level for cMyBP- C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker, whereby it is differentiated between i) or ii).

[0116] In yet another embodiment,, the present invention relates to a method for differentiating between i) a subject who has structural abnormalities of the heart preceding heart failure and ii) a subject bearing only risk factors of heart failure, comprising the steps of a) determining the level of cMyBP-C and, optionally, the level of at least one further biomarker selected from the group MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample from the subject, and b) comparing the level of the biomarker cMyBP-C to a reference level for cMyBP- C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker, whereby it is differentiated between i) a subject who has structural abnormalities of the heart preceding heart failure and ii) a subject bearing only risk factors of heart failure

[0117] Alternatively, step b) may comprise calculating a score for differentiating between i) and ii), wherein the score is calculated based on the level of cMyBP-C and, optionally, the level(s) of the at least one further biomarker.

[0118] In some embodiments, the differentiation may comprise further steps such as the confirmation of the differentiation (by further therapeutic measures described herein below). Thus, the term “differentiation” in the context of the present invention also encompasses aiding a physician in the differentiation as referred to herein. In some embodiments, the differentiation may comprise further diagnostic measures.

[0119] Method for identifying a subject who is eligible to further diagnostic measures

[0120] In accordance with this embodiment of method of the present invention, it shall be assessed whether a subject is eligible to further diagnostic measures for assessing asymptomatic heart failure. Thus, the biomarker can be used for the screening of larger cohorts. The term “identifying a subject” as used herein preferably refers to using the information or data generated relating to the level of cMyBP-C and optionally relating to the level of the at least one further biomarker as referred to herein to herein in a sample to identify a subject who is eligible to such further diagnostic measures. Thus, it is assessed whether the subject should be subjected to such further diagnostic methods. In a preferred embodiment, a subject who has been identified as a subject who suffers from structural heart disease (based on the level of the biomarker(s)) is eligible to such further diagnostic measures. Typically, the further measures are applied in order to confirm the diagnosis, or not.

[0121] Accordingly, the present invention relates to a method for identifying a subject who is eligible to one or more further diagnostic measures for assessing asymptomatic heart failure, comprising the steps of a) determining the level of cMyBP-C and, optionally, the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample from the subject, and b) comparing the level of the biomarker cMyBP-C to a reference level for cMyBP- C and, optionally, comparing the level of the at least one further biomarker to a reference level for said at least one further biomarker, whereby it is assessed whether a subject is eligible to one or more further diagnostic measures for assessing asymptomatic heart failure

[0122] Alternatively, step b) may comprise calculating a score for differentiating between i) and ii), wherein the score is calculated based on the level of cMyBP-C and, optionally, the level(s) of the at least one further biomarker, whereby it is assessed whether a subject is eligible to one or more further diagnostic measures for assessing asymptomatic heart failure.

[0123] In another preferred embodiment of the method of identification, the one or more further diagnostic measure is ruled out. Thus, the patient is not eligible to said one or more diagnostic measures, i.e. does require a further assessment. A patient who is not eligible to said one or more diagnostic measures is a patient who is unlikely to suffer from structural heart disease (such as stage B heart failure) (based on the level of the biomarkers).

[0124] Specifically, the measure is ruled in, if the patient is likely to suffer from structural heart disease, such as stage B heart failure, (based on the level of the biomarkers). Thus, the patient is eligible to said one or more diagnostic measures.

[0125] The further diagnostic measure for diagnosing structural heart disease can be any measure which allows for diagnosing such changes. In a preferred embodiment, the further diagnostic measure is echocardiography, electrocardiography, or MRI.

[0126] In case, the patient is identified by the above method, the method may comprise the further step of recommending said one or more further diagnostic measures. Alternatively, the method may comprise the further step of subjecting the identified patient to said one or more diagnostic measures to assess structural heart disease. For example, the subject may be subjected to echocardiography or MRI. Moreover, a suitable therapeutic measure may be initiated once the disease is diagnosed.

[0127] Method for determining the severity of asymptomatic heart failure.

[0128] Advantageously, it was shown that cMyBP-C levels and the levels of the at least one marker as referred to herein increase for cases with rising heart failure stages. The same applies to the further markers tested in the Examples. Therefore, the determination of the level cMyBP-C allows for determining the severity of asymptomatic heart failure. Typically, the term "determining the severity of asymptomatic heart failure" as used herein, preferably, means to differentiate between various stages of heart failure. In a preferred embodiment, the term refers the determination of the extent of structural changes of the heart in the subject (as compared to a normal heart). The higher the level(s) of the biomarker(s) as referred to herein, the larger is the extent of the structural changes and the more advanced is the structural heart disease.

[0129] Method for monitoring of asymptomatic heart failure

[0130] In an embodiment of the assessment of the present invention, the assessment is the monitoring of asymptomatic heart failure. Thus, the progression of asymptomatic heart failure is monitored.

[0131] The method, preferably, comprises step a) of determining the level of cMyBP-C and optionally the level(s) of at least further biomarker selected from MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a first sample and a second sample obtained from a subject suffering from asymptomatic heart failure, and comparing the level(s) in the second sample to the first sample. Preferably, an increased level(s) of cMyBP-C in the second sample as compared to the first sample is indicative for the progression, i.e. worsening, of asymptomatic heart failure.

[0132] If additionally the level of MyL7, ANG2, the cardiac Troponin or the BNP -type peptide is determined in step a) the following applies.

[0133] Preferably, an increased level(s) of cMyBP-C in combination with an increased level of MyL7, ANG2, the cardiac Troponin, or the BNP -type peptide (in the 2ndsample as compared to the 1stsample) is indicative for the progression, i.e. worsening, of asymptomatic heart failure.

[0134] It is to be understood that the second sample has been obtained from the subject after the first sample, such as at least one month, at least two months or at least three months after the first sample.

[0135] The subject to be tested

[0136] The subject or subject to be tested in accordance with the methods of the present invention can include, but is not limited to, mammals such as bovine, avian, canine, equine, feline, ovine, porcine, or primate animals (including humans and non-human primates). In a preferred embodiment, the subject is a human subject. The terms “subject” and “patient” are used interchangeably herein.

[0137] In a preferred embodiment, the subject is a male subject.

[0138] In another preferred embodiment, the subject is a female subject. In case the assessment is the diagnosis, the differentiation or the identification as described above, the subject to be tested is, preferably, a subject who is suspected to suffer from asymptomatic heart failure. In a preferred embodiment, the subject is a subject aged 65 and above (such as aged 70 and above).

[0139] Preferably, the subject to be tested is asymptomatic with respect to heart failure and hence does not show symptoms of heart failure. Symptoms of heart failure, may include shortness of breath with activity or when lying down, fatigue and weakness, rapid or irregular heartbeat, swelling in the legs, ankles and feet, reduced ability to exercise. Thus, the subject to be tested typically shows none of the aforementioned symptoms.

[0140] Typically, a subject who is suspected to suffer from asymptomatic heart failure is a subject who has one or more risk factors of suffering from heart failure. More typically, the subject has one or more risk factors of suffering from heart failure of suffering from heart failure: obesity, metabolic syndrome, diabetes type 1 or type 2, arterial hypertension. Thus, the subject to be tested, preferably, suffers from hypertension, diabetes, obesity and / or the metabolic syndrome. Moreover, the presence of a documented clinical history of atherosclerotic disease or a positive case history for use of cardiotoxins, without evidence of structural heart disease and any signs or symptoms of HF are considered as risk factors of suffering from heart failure.

[0141] In a particularly preferred embodiment, the subject to be tested suffers from arterial hypertension. Arterial hypertension, also referred to as high blood pressure, is a long-term medical condition in which the blood pressure in the arteries is persistently elevated. In accordance with the present invention, a subject is considered to suffer from arterial hypertension if resting blood pressure is 130 / 85 mmHg or higher, or if the subject is treated for hypertension (e.g. if the subject receives antihypertensive medication.

[0142] In another particularly preferred embodiment, the subject tested suffers from diabetes type 2.

[0143] In the context of the methods of the present invention, structural changes of the heart preceding heart failure can be diagnosed even before the subject suffers from left ventricular hypertrophy. Thus, the method of the present disclosure allows for diagnosing structural changes of the heart preceding heart failure and / or preceding left ventricular hypertrophy.

[0144] Accordingly, the subject to be subject to be tested does not suffer from left ventricular hypertrophy (LVH). Preferably, a female subject does not suffer from left ventricular hypertrophy (LVH) if the left ventricular mass (LV mass) is lower than 95 g / m2. Preferably, a male subject does not suffer from left ventricular hypertrophy (LVH) if the left ventricular mass (LV mass) is lower than 115 g / m2 in men. Preferably, the LV mass is assessed by echocardiography The sample

[0145] The term “sample” as used herein refers to any sample that under physiological conditions comprises the biomarkers referred to herein. More typically, the sample is a body fluid sample, e.g. a blood sample or sample derived therefrom (e.g. serum or plasma), a urine sample, a saliva sample, interstitial fluid, a lymphatic fluid sample or the like. In a preferred embodiment, the sample is a blood (i.e. whole blood), serum or plasma sample. Serum is the liquid fraction of whole blood that is obtained after the blood is allowed to clot. For obtaining the serum, the clot is removed by centrifugation and the supernatant is collected. Plasma is the acellular fluid portion of blood. For obtaining 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.

[0146] In a preferred embodiment of the present invention, the sample is a blood (i.e. whole blood), serum or plasma sample. In particular, the sample is serum or plasma sample.

[0147] The biomarkers

[0148] The assessment made in accordance with the present invention, typically, is based on the level of biomarker cMyBP-C, and optionally, on the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide. The term “biomarker”, as used herein, refers to a protein which serves as an indicator for a disease or physiological state as referred to herein. The biomarker may be a derivative of the polypeptide or protein, may be a fragment of the polypeptide or protein, or may be a complex of the polypeptide, e.g. an immunocomplex of the polypeptide or a protein comprising more than one polypeptide. Preferably, however, the biomarker is the full-length polypeptide (in particular, as expressed in humans). Also, in case the biomarker has an activity, e.g. a catalytic activity and / or an activating activity, e.g. on target cells, the biomarker may also be determined via said activity, e.g. in an enzymatic assay. It is to be understood that in the aforesaid cases, the analyte may represent the actual biomarker and has the same potential as an indicator for the respective medical condition as the biomarker would have. Preferred modes of determination and analytes for the biomarkers of the present description are described in the context of the respective biomarkers herein below. A biomarker according to the present invention need not necessarily correspond to one molecular species. As known by the skilled person, a polypeptide may comprise variant molecular species, e.g. translated from splice variants, glycosylation variants, and the like. In an embodiment, the variants share at least one determinable feature, e.g. an epitope or an activity. The biomarkers to be determined in accordance with the present invention are as such known in the art. Moreover, methods for the determination of the biomarkers of the biomarkers are known to the skilled person as well. cMyBP-C (myosin-binding protein C, cardiac-type, also referred to as MYBPC3 CMD1MM, CMH4, FHC, LVNC10, MYBP-C, Myosin binding protein C, cardiac myosin binding protein C3) is produced in heart muscle. It is a 140.5 kDa protein composed of 1273 amino acids cMyBP-C is a myosin-associated protein that binds at 43 nm intervals along the myosin thick filament backbone, stretching for 200 nm on either side of the M-line within the crossbridgebearing zone (C-region) of the A band in striated muscle. The cMyBP-C is encoded by the cMyBP-C gene. Further information on human cMyBP-C can be found in the UniProtKB database under accession number Q14896 (MYPC3 HUMAN).

[0149] The marker "Angiopoietin 2" (ANG2) is well known in the art (see e.g. Sarah Y. Yuan; Robert R. Rigor (30 September 2010). Regulation of Endothelial Barrier Function. Morgan & Claypool Publishers. ISBN 978-1-61504-120-6). Angiopoietin 2 is part of a family of vascular growth factors that play a role in embryonic and postnatal angiogenesis. Angiopoietin-2 is produced and stored in Weibel-Palade bodies in endothelial cells and acts as a TEK tyrosine kinase antagonist, angiopoietin-2 is a marker for early cardiovascular disease in children on chronic dialysis (Shroff et al. (2013). "Circulating angiopoietin-2 is a marker for early cardiovascular disease in children on chronic dialysis.". PLoS ONE 8 (2): e56273). The sequence of ANG2 is e.g. accessible via UniProt (see Accession Number 015123).

[0150] The Brain Natriuretic Peptid type peptide (herein also referred to as BNP -type peptide) is prefer- ably selected from the group consisting of pre-proBNP, proBNP, NT-proBNP, and BNP. The pre-pro peptide (134 amino acids in the case of pre-proBNP) comprises a short signal peptide, which is enzymatically cleaved off to release the pro peptide (108 amino acids in the case of proBNP). The pro peptide is further cleaved into an N-terminal pro peptide (NT -pro peptide, 76 amino acids in case of NT-proBNP) and the active hormone (32 amino acids in the case of BNP). Preferably, brain natriuretic peptides according to the present invention are NT- proBNP, BNP, and variants thereof. BNP is the active hormone and has a shorter half-life than its respective inactive counterpart NT-proBNP. In a preferred embodiment, the Brain Natriuretic Peptid-type peptide is BNP (Brain natriuretic peptide) or NT-proBNP (N-terminal of the prohormone brain natriuretic peptide). In particularly preferred embodiment, it is NT- proBNP (N-terminal of the prohormone brain natriuretic peptide).

[0151] The term "cardiac Troponin" refers to all Troponin isoforms expressed in cells of the heart and, preferably, the subendocardial cells. These isoforms are well characterized in the art as described, e.g., in Anderson 1995, Circulation Research, vol. 76, no. 4: 681-686 and Ferrieres 1998, Clinical Chemistry, 44: 487-493. Preferably, cardiac Troponin refers to cardiac Troponin T and / or to cardiacTroponin I, and, most preferably, to cardiac Troponin T.

[0152] MyL7 is a protein that in humans is encoded by the MYL7 gene. The protein is also known as Atrial Light Chain-2 (ALC-2), as Myosin regulatory light chain 2, atrial isoform (MLC2a), or a MyL2A. The protein has a molecular weight of about 19.4 kDa and comprises 175 amino acids. It is an EF hand protein that binds to the neck region of alpha myosin heavy chain. The sequence of MyL7 is well known in the art. It can be e.g. assessed under UniProt accession number Q01449 (MLRA HUMAN). The biomarker is known to be expressed in both atria (see Hailstones et al., Journal of Biological Chemistry, Volume 267, Issue 32, 1992, Pages 23295- 23300).

[0153] Step a) of the method of the present invention comprises the determination of the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide. Preferably, the level of the protein biomarker(s) is determined.

[0154] Preferred combination of biomarkers in accordance with the methods, uses, devices, kits and databases of the present invention are as follows:

[0155] In preferred embodiment, the levels of the biomarkers cMyBP-C and Myl7 are determined. In preferred embodiment, the levels of the biomarkers cMyBP-C and ANG2 are determined.

[0156] In preferred embodiment, the levels of the biomarkers cMyBP-C and a BNP -type peptide are determined, such as BNP or NT-proBNP.

[0157] In preferred embodiment, the levels of the biomarkers cMyBP-C and a cardiac Troponin are determined, such as cardiac Troponin T or I, in particular Troponin T.

[0158] In another preferred embodiment, the levels of cMyBP-C, a BNP -type peptide, Myl7 and a cardiac troponin are determined.

[0159] In another preferred embodiment, the levels of cMyBP-C, a BNP -type peptide, Myl7 a cardiac troponin and ANG2 are determined.

[0160] The determination of biomarker levels

[0161] Step a) of the method of the present invention comprises the determination of the level of the biomarker cMyBP-C, and optionally, the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide. It is to be understood that the level of the protein biomarker(s) is determined, rather than the level of the mRNA.

[0162] Typically, the level of a biomarker can be determined by determining a complex of the analyte with a detection compound, in particular an antibody or fragment thereof, i.e. in an immunoassay. Said determining of a complex of the analyte may be performed in any format deemed appropriate by the skilled person, in particular a sandwich, competition, or other assay format. Said assays will develop a signal which is indicative for the level of a biomarker. Thus, determining may include micro-plate ELISA-based methods, fully-automated or robotic immunoassays (available, e.g., from Roche). Suitable measurement methods may also include precipitation (particularly immunoprecipitation), electrochemiluminescence (electro-generated chemiluminescence), RIA (radioimmunoassay), ELISA (enzyme-linked immunosorbent assay), fluorescent immunoassay (FIA), electrochemiluminescence sandwich immunoassays (ECLIA), dissociation-enhanced lanthanide fluoro immuno assay (DELFIA), scintillation proximity assay (SPA), turbidimetry, nephelometry, latex-enhanced turbidimetry or nephelometry, or solid phase immune tests. Further methods known in the art such as gel electrophoresis, 2D gel electrophoresis, SDS polyacrylamid gel electrophoresis (SDS-PAGE) or Western Blotting. More typically, techniques particularly envisaged for determining the biomarkers referred to herein are described herein below.

[0163] In a preferred embodiment of the present invention, the amount of cMyBP-C is determined with the assay disclosed in the international patent application PCT / EP2024 / 071529 or the Chinese patent application CN117517671A which both are incorporated by reference with respect to the entire disclosure content. In particularly preferred embodiment of the present invention, the amount of cMyBP-C is determined with the sandwich assay disclosed in the aforementioned patent applications.

[0164] In preferred embodiment, the determination comprises i) contacting a sample comprising cMyBP-C from the subject, such as a human blood, serum or plasma sample, with the first monoclonal antibody, or fragment thereof, and / or the second monoclonal antibody, or fragment thereof, disclosed in in the international patent application PCT / EP2024 / 071529 or the Chinese patent application CN117517671A, thereby forming a complex comprising cMyBP-C and said monoclonal antibody (or both monoclonal antibodies), or the fragment(s) thereof, and ii) determining the amount of the complex formed in step (i), thereby determining the amount of cMyBP-C in said sample.

[0165] Preferably, the first monoclonal antibody, or antigen-binding fragment thereof, which binds to cMyBP-C comprises

[0166] (a) a light chain variable domain comprising

[0167] (al) a light chain CDR1 having a sequence as shown in SEQ ID NO: 1 (QASQSIGNALA),

[0168] (a2) a light chain CDR2 having a sequence as shown in SEQ ID NO: 2 (STSYLPS), and (a3) a light chain CDR3 having a sequence as shown in SEQ ID NO: 3 (QSYYVSTSSSDRSS), and

[0169] (b) a heavy chain variable domain comprising

[0170] (bl) a heavy chain CDR1 having a sequence as shown in SEQ ID NO: 4 (SGYDMC),

[0171] (b2) a heavy chain CDR2 having a sequence as shown in SEQ ID NO: 5 (CIGSSSASTWYANWVNG), and

[0172] (b3) a heavy chain CDR3 having a sequence as shown in SEQ ID NO: 6 (ESSTEYYYNL).

[0173] In particular, the first monoclonal antibody, or antigen-binding fragment thereof, which binds to MYBPC3 (Myosin binding protein C, cardiac type), comprises a) a light chain variable domain comprising a sequence as shown in SEQ ID NO: 7 (DIVMTQTPASVEAAVGGTVTIKC QASQSIGNALA WYQQKPGQPPKLLIY STSYLPS GVPSRFKGGGSGAEYTLTISDLECADAATYYC QSYYVSTSSSDRSS FGGGTEVVVK), and b) a heavy chain variable domain comprising a sequence as shown in SEQ ID NO: 8 (QEQLEESGGGLVKPGGTLTLTCKVSGFDFS SGYDMC WVRQAPGKGLESIA CIGSSSASTWYANWVNG RFTVSRSTSLNTVDLKMTSLTVADTATYFCAR ESSTEYYYNL WGPGTLVTVSS).

[0174] Preferably, a biotinylated F(ab')2 fragment of the first monoclonal antibody of the first antibody is used.

[0175] Preferably, the second monoclonal antibody, or antigen-binding fragment thereof, which binds to cMyBP-C (Myosin binding protein C, cardiac type), comprises

[0176] (a) a light chain variable domain comprising

[0177] (al) a light chain CDR1 having a sequence as shown in SEQ ID NO: 9 (RASQNIGTNMH),

[0178] (a2) a light chain CDR2 having a sequence as shown in SEQ ID NO: 10 (FASESFS), and

[0179] (a3) a light chain CDR3 having a sequence as shown in SEQ ID NO: 11 (QQSYNWPFT), and

[0180] (b) a heavy chain variable domain comprising

[0181] (bl) a heavy chain CDR1 having a sequence as shown in SEQ ID NO: 12 (GYGVN), (b2) a chain CDR2 having a sequence as shown in SEQ ID NO: 13 (MIWGDGSTDYNSVYKS), and

[0182] (b3) a heavy chain CDR3 having a sequence as shown in SEQ ID NO: 14 (RDTGGASMDY).

[0183] Preferably, the second monoclonal antibody, or antigen-binding fragment thereof, which binds to cMyBP-C (Myosin binding protein C, cardiac type), comprises a) a light chain variable domain comprising a sequence as shown in SEQ ID NO: 15 (DILMTQSPAILSVSPGERVSFSC RASQNIGTNMH WYQQRTNGSPRLLIR FASESFS GIPSRFSGTGSGTDFTLRINSVESEDIADYYC QQSYNWPFT FGAGTKLELK), and b) a heavy chain variable domain comprising a sequence as shown in SEQ ID NO: 16 (QVQLKESGPGLVAPSQSLSITCTVSGFSLT GYGVN WVRQPPGKGLEWLG MIWGDGSTDYNSVYKS RLSISKDNSKSQVFLKMNSLQTDDTARYYCAR RDTGGASMDY WGQGTSVTVSS).

[0184] Preferably the second antibody used in the assay is ruthenylated.

[0185] The determination of a biomarker as set forth herein may comprise mass spectrometry (MS) which is carried out after the separation step (e.g. by LC or HPLC). Mass spectrometry as used herein encompasses all techniques which allow for the determination of the molecular weight (i.e. the mass) or a mass variable corresponding to a compound, i.e. a biomarker, to be determined in accordance with the present invention. Preferably, mass spectrometry as used herein relates to GC-MS, LC-MS, direct infusion mass spectrometry, FT-ICR-MS, CE-MS, HPLC-MS, quadrupole mass spectrometry, any sequentially coupled mass spectrometry such as MS-MS or MS-MS-MS, ICP-MS, Py-MS, TOF or any combined approaches using the aforementioned techniques. How to apply these techniques is well known to the person skilled in the art. Moreover, suitable devices are commercially available. More preferably, mass spectrometry as used herein relates to LC-MS and / or HPLC-MS, i.e. to mass spectrometry being operatively linked to a prior liquid chromatography separation step. Preferably, the mass spectrometry is tandem mass spectrometry (also known as MS / MS). Tandem mass spectrometry, also known as MS / MS involves two or more mass spectrometry step, with a fragmentation occurring in between the stages. In tandem mass spectrometry two mass spectrometers in a series connected by a collision cell. The mass spectrometers are coupled to the chromatographic device. The sample that has been separated by a chromatography is sorted and weighed in the first mass spectrometer, then fragmented by an inert gas in the collision cell, and a piece or pieces sorted and weighed in the second mass spectrometer. The fragments are sorted and weighed in the second mass spectrometer. Identification by MS / MS is more accurate.

[0186] In an embodiment, the level of a biomarker as set forth herein is determined by Proximity Extension Assay. The biomarker is detected by a matched pair of antibodies that are conjugated to partially complementary oligonucleotides. When both antibodies bind to the biomarker, a partially double-stranded nucleic acid is formed by the hybridization of the partially complementary oligonucleotides. The level of said partially double-stranded nucleic acid can be measured by quantitative real-time PCR or next generation sequencing (see e.g. (Assarsson et al. PLoS One 2014 Apr 22;9(4), doi: 10.1371 / joumal. pone.0095192). The determined level indicates the level of the biomarker.

[0187] In another embodiment, the level of a biomarker as set forth herein is determined by Proximity Ligation Assay which is similar to the Proximity Extension Assay. In this assay, the oligonucleotides are ligated by a ligase to a closed, circle DNA template that can be used for rolling-circle amplification (RCA).

[0188] In step b) of the method of the present invention, asymptomatic heart failure is assessed. Typically, the assessment (such as the diagnosis, differentiation, staging or identification) is based on the level of cMyBP-C and, optionally, the level of the at least one further biomarker as set forth herein above. In an embodiment, asymptomatic heart failure is assessed by comparing the determined level of cMyBP-C to a reference level for this marker, and optionally, by comparing the determined level of the at least one further biomarker to a reference level for the at least one further biomarker (e.g. the level of MyL7 to a reference level of MyL7, or the level of ANG2 to a reference level of ANG2 etc.) Alternatively, the asymptomatic heart failure is assessed by calculating score for assessing asymptomatic heart failure based on the determined level of cMyBP-C and optionally based on the level of the at least one further biomarker.

[0189] As set forth above, it is also envisaged to calculate a score based on the level(s) of the biomarker(s), in particular a single score. The assessment of asymptomatic heart failure is then made based on the score. The assessment may include a comparison of the score to a reference score which allows for the assessment of asymptomatic heart failure as referred to herein. The calculated score, in an embodiment combines, information on the level(s) of the biomarker(s). For example, if two biomarkers are determined, the score is calculated based on the levels of the two markers. In the score, the biomarkers may be weighted in accordance with their contribution to the establishment of the differentiation, wherein the weighting factor of the individual biomarkers may be different. The calculated score combines information on the level(s) of the biomarkers determined in step a) of method of the present invention, (e.g. of two or three biomarkers). Moreover, in the score, the biomarkers are, preferably, weighted in accordance with their contribution to the establishment of the assessment. Thus, the values for the individual markers are weighted and the weighted values are used for calculating the score. Suitable coefficients (weights) can be determined by the skilled person without further ado, e.g. by training the coefficients using the corresponding biomarker information from a representive reference population comprising controls and subjects suffering from the respective medical condition (e.g. stage B heart failure). A score can also be calculated from a decision tree or a set (ensemble) of decision trees that has been trained the two biomarkers. Alternatively, a score can be also calculated by any other supervised and / or unsupervised machine-learning methods used for classification. This includes all kinds of suited artificial neural networks, support vector machines, k-nearest neighbor, boosting and bagging regression and tree-based models. Further, such a score could be created by statistical or closed-form methods like linear and quadratic discriminant analysis or likelihood ratio functions. Based on the combination of biomarkers applied in the method of the invention, the weight of an individual biomarker as well as the structure of machine learning model or mathematical formula may be different. In an embodiment, to calculate a score, the levels of the biomarkers determined may be linearly combined (e.g. Score = c0+ cx* [Biomarker- + c2* [Biomarker2] + •••), preferably with corresponding coefficients (cx, c2, ...) and intercept (c0). In preferred embodiments, the levels of the biomarkers ([Biomarker , [Biomarker2], ...) are log transformed (e.g. natural logarithm, log 2 or log 10, preferably log 10) for the linear combination to a score. The output of such a linear combination may be directly used as score. Alternatively or additionally, the output of this linear combination may be used as input to a mathematical transformation (e.g. a sigmoid transformation such as ( / (%) = 1 / (1 + exp(— %)))) providing a risk score, which maps the output range of the score to 0-1.

[0190] As set forth above, the score can be regarded as a classifier parameter for assessing asymptomatic heart failure as set forth herein. In particular, it enables the person who provides the assessment based on a single score. The reference score is preferably a value, in particular a cut-off value which allows for assessing a subject with suspected infection as set forth herein. Preferably, the reference is a single value. Thus, the person does not have to interpret the entire information on the levels of the individual biomarkers. Using a scoring system as described herein, advantageously, values of different dimensions or units for the biomarkers may be used since the values will be mathematically transformed into the score. Accordingly, e.g. values for absolute concentrations may be combined in a score with peak area ratios. The reference score to be applied may be elected based on the desired sensitivity or the desired specificity. How to elect a suitable reference score is well known in the art. The score as referred to herein is not limited to the biomarkers specifically mentioned herein. For example, the score can also take into account further biomarkers or parameters such as the age and / or sex of the subject to be tested.

[0191] The term “reference” or “reference level”, as used herein, relates to a value, e.g. a level or any value derived therefrom, e.g. a score, which can be correlated to a medical condition and, in an embodiment, which allows for the assessment of the invention to be made, in a further embodiment enables allocation of a subject into either a group of subjects suffering from a disease or condition t, or a group of subjects which do not suffer from said disease or condition. Such a reference can be a threshold value, e.g. a threshold level, which separates these groups from each other. For example, the reference may be a value which allows for allocation of a subject into a group of subjects suffering from structural heart disease preceding overt heart failure, or not suffering from structural heart disease preceding overt heart failure. The reference may, however, also be a reference range, e.g., in an embodiment, a range of values for which structural heart disease preceding overt heart failure can be excluded. Furthermore, the reference may be a value calculated from the aforesaid values, e.g. from the levels of two or more biomarkers, in an embodiment to provide a score. A suitable reference separating the two groups can be provided without further ado e.g. by the statistical tests referred to herein elsewhere based on values of biomarkers from suitable reference groups as specified herein below. As the skilled person understands, it may not always be possible, although particularly envisaged, to provide a reference unambiguously allocating each and every possible value of a biomarker to one of the aforesaid groups; thus, there may be a range of values for which a clear assessment cannot be provided. In an embodiment, however, as indicated above, a reference enables the assessment to be made for each and every value of a biomarker or set of biomarkers which may be measured. As the skilled person understands, the specific value of a reference may depend on the assessment intended and on parameters thereof; thus, the reference value for assessing asymptomatic heart failure may typically different from the reference value for ruling in or ruling out structural heart disease preceding overt heart failure.

[0192] As indicated herein above, a reference may in particular be derived from at least one reference group, the term "reference group" relating to a group of subjects with known status with regard to the assessment. Thus the reference group may e.g. be a group of subjects for which it is known whether they suffer from structural heart disease (such as stage B heart failure) or not. The population of subjects in a reference group in an embodiment comprises a plurality of subjects, e.g. at least 5, 10, 50, 100, 1,000, or 10,000 subjects. Typically, the subject to be diagnosed and the subjects of the said reference group are of the same species. The reference applicable for an individual subject may vary depending on various physiological parameters such as age, gender, or subpopulation. Assuming that contribution of actually afflicted subjects is low, such an average population reference group may be treated as a reference group known not to suffer from structural heart disease (such as stage B heart failure); in an embodiment, in such case, the size of the reference group is sufficiently high, e.g. at least 100, in a further embodiment at least 1000, in a further embodiment at least 10000 subjects. In view of the description herein, the skilled person understands that a reference group may, in principle, also be a mixed population of subjects with regard to asymptomatic heart failure, such as stage B heart failure, provided that the status of each member of said mixed population with regards to asymptomatic heart failure is or becomes known before deriving a reference from such group.

[0193] Reference levels can, in principle, be calculated for a cohort of subjects based on the average or mean values for a given parameter such as biomarker level by applying standard statistically methods. In particular, accuracy of a test such as a method aiming to diagnose an event, or not, is best described by its receiver-operating characteristics (ROC) (see especially Zweig 1993, Clin. Chem. 39:561-577). The ROC graph is a plot of all of the sensitivity / specificity pairs resulting from continuously varying the decision threshold over the entire range of data observed. The clinical performance of a diagnostic method depends on its accuracy, i.e. its ability to correctly allocate subjects to a certain prognosis or diagnosis. The ROC plot indicates the overlap between the two distributions by plotting the sensitivity versus 1 -specificity for the complete range of thresholds suitable for making a distinction. On the y-axis is sensitivity, or the true-positive fraction, which is defined as the ratio of number of true-positive test results to the product of number of true-positive and number of false-negative test results. This has also been referred to as positivity in the presence of a disease or condition. It is calculated solely from the affected subgroup. On the x-axis is the false-positive fraction, or 1 -specificity, which is defined as the ratio of number of false-positive results to the product of number of truenegative and number of false-positive results. It is an index of specificity and is calculated entirely from the unaffected subgroup. Because the true- and false-positive fractions are calculated entirely separately, by using the test results from two different subgroups, the ROC plot is independent of the prevalence of the event in the cohort. Each point on the ROC plot represents a sensitivity / -specificity pair corresponding to a particular decision threshold. A test with perfect discrimination (no overlap in the two distributions of results) has an ROC plot that passes through the upper left corner, where the true-positive fraction is 1.0, or 100% (perfect sensitivity), and the false-positive fraction is 0 (perfect specificity). The theoretical plot for a test with no discrimination (identical distributions of results for the two groups) is a 45° diagonal line from the lower left corner to the upper right corner. Most plots fall in between these two extremes. If the ROC plot falls completely below the 45° diagonal, this is easily remedied by reversing the criterion for "positivity" from "greater than" to "less than" or vice versa. Qualitatively, the closer the plot is to the upper left corner, the higher the overall accuracy of the test. Dependent on a desired confidence interval, a threshold can be derived from the ROC curve allowing for the diagnosis or prediction for a given event with a proper balance of sensitivity and specificity, respectively. Accordingly, the reference to be used for the aforementioned method of the present invention, i.e. a threshold which allows to discriminate between subjects suffering from a disease or not suffering from disease can be generated, usually, by establishing a ROC for said cohort as described above and deriving a threshold level therefrom. Dependent on a desired sensitivity and specificity for a diagnostic method, the ROC plot allows deriving suitable thresholds. It will be understood that an optimal sensitivity may be desired for excluding a subject from suffering from structural heart disease preceding overt heart failure (i.e. a rule-out), whereas an optimal specificity may be envisaged for a subject to be assessed as suffering from structural heart disease preceding overt heart failure (i.e. a rulein).

[0194] As will be understood by the skilled person, the reference level shall be suitable for the assessment are referred to herein, such as for the diagnosis of structural heart disease preceding symptomatic heart failure. Thus, the reference level is, in an embodiment, a predetermined value for the level of biomarker which allows for diagnosing structural heart disease preceding symptomatic heart failure.

[0195] In accordance with the present invention, asymptomatic heart failure is typically assessed based on the comparison and / or the calculation made in step b). The term "assessing" has been specified herein above. Typically, the assessment may in particular be based on the status of the reference group(s) and the reference derived therefrom. As the skilled person understands, a biomarker may be decreased or increased in an afflicted subject compared to a control subject. Thus, in case the reference is derived from a group of subjects known to be afflicted with the disease or condition, a biomarker value essentially identical to the reference in an embodiment leads to an assessment of the subject under investigation being afflicted with the disease or condition, and a value different, in an embodiment significantly different, from said reference in a further embodiment leads to an assessment of the subject under investigation not being afflicted with the disease or condition. Conversely, in case the reference is derived from a group of subjects known not to be afflicted with the disease or condition, a biomarker value essentially identical to the reference in an embodiment leads to an assessment of the subject under investigation not being afflicted with the disease or condition, and a value different, in an embodiment significantly different, from said reference in a further embodiment leads to an assessment of the subject under investigation being afflicted with the disease or condition.

[0196] In a preferred embodiment, the reference may be a threshold value; such a threshold value may be derived from a reference group known to suffer from the disease or condition. In another preferred embodiment, such a threshold value may be derived from a reference group known not to suffer from the disease or condition. Typically, in case a biomarker value of a subject under investigation exceeds the aforesaid threshold reference toward the values of the reference group known to suffer from the disease or condition, it will be assumed that the subject is likely to suffer from the disease or condition; and in case a biomarker value of a subject under investigation exceeds the aforesaid threshold toward the values of the reference group known to not suffer from the disease or condition, it will be assumed that the subject is likely not to suffer from the disease or condition. Thus, depending on the specific biomarker and its correlation with a disease or condition, values found in a sample which are higher than or equal to a threshold may be indicative for the presence of a medical condition while those being lower may be indicative for the absence of the medical condition; or, it may also be that values found in a sample to be investigated which are lower or identical than the threshold are indicative for the presence of a medical condition while those being higher are indicative for the absence of the medical condition.

[0197] As the skilled person understands in view of the description herein, the above applies mutatis mutandis to a score, which may incorporate levels of more than one biomarker, in an embodiment all biomarkers. A reference score may be derived from a reference group known to suffer from the disease or condition, or from a reference group known not to suffer from the disease or condition. Alternatively, reference score may be derived from a mixed population comprising subjects known to suffer from the disease or condition and subjects known not to suffer from the disease or condition.

[0198] In an embodiment, a calculated score which is larger than the reference score indicates that the subject is likely to suffer from the disease or condition. Also, a calculated score which is lower than the reference score indicates that the subject is not likely to suffer from the disease or condition. As specified herein above, a reference score may in particular be calculated by the same mathematical operations applied to calculate a score, but using values from one or more reference group(s). The reference score also may be e.g. a threshold score or a reference score range. As the skilled person will understand as well, the assessment following from the comparison of a score to a reference score will depend on the specificities of score calculation; thus, whether a score above or below a threshold score is indicative of structural heart disease preceding overt heart failurethereof will depend on the specific way of calculating the score. E.g. in the exemplary score calculated according to the Examples, a score higher than the cutoff score is indicative of structural heart disease preceding overt heart failure.

[0199] In an embodiment of the present invention, the assessment is made with a pre-selected sensitivity or specificity. Accordingly, the reference is a level which allows the assessment, such as the diagnosis, the differentiation, the identification of a subject with the preselected sensitivity or specificity.

[0200] Preferred diagnostic algorithms

[0201] As regards to the diagnosis as referred to herein, an increased level of the biomarker cMyBP-C as compared to the reference level is, typically, indicative for a subject who suffers from structural heart disease preceding symptomatic heart failure (such as stage B heart failure), whereas a decreased level is indicative for a subject who does not suffer from structural heart disease. This applies, e.g., if the reference level is a predetermined value for the level of biomarker which allows for diagnosing structural heart disease preceding symptomatic heart failure.

[0202] In another embodiment, the reference level is a predetermined value for the level of biomarker which allows for ruling out structural heart disease (such as stage B heart failure).. Typically, a decreased level of cMyBP-C as compared to a reference level is indicative for a subject who does not suffer from structural heart disease (such as stage B heart failure). Thus, the diagnosis can be ruled out. In another embodiment, the reference level is predetermined value for the level of biomarker which allows for ruling in structural heart disease (such as stage B heart failure). Typically, an increased level of cMyBP-C as compared to a reference level is indicative for a subject who suffers from structural heart disease preceding overt heart failure.

[0203] In another embodiment, the reference level is predetermined value for the level of biomarker which allows for identifying a subject who is eligible to one or more diagnostic measures for diagnosing structural heart disease preceding symptomatic heart failure. Typically, an increased level of the biomarker cMyBP-C as compared to the reference level is indicative for a subject who is eligible to one or more diagnostic measures, whereas a decreased level is indicative for a subject who is not eligible to said one or more diagnostic measures.

[0204] The biomarkers are referred to herein (cMyBP-C, MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide) increased in structural heart disease (such as stage B heart failure). Thus, a level of cMyBP-C above the reference level for cMyBP-C in combination with a level of the at least one further biomarker selected from MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide above the reference level for said marker is indicative for a subject who suffers from structural heart disease (such as stage B heart failure), wherein a decreased level of the markers (as compared to the reference levels) is indicative for a subject who does not suffer from structural heart disease (such as stage B heart failure).

[0205] This is exemplified for the diagnosis of structural heart disease (preceding overt heart failure):

[0206] Preferably, the following applies, if the biomarkers cMyBP-C and MyL7 are determined in the method of the present invention: a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of MyL7 above the reference level for MyL7 indicates that the subject is likely to suffer from structural heart disease (such as stage B heart failure), whereas a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of MyL7 below the reference level for MyL7 indicates that the subject is not likely to suffer from structural heart disease (such as stage B heart failure). Preferably, the following applies, if the levels of the biomarkers cMyBP-C and ANG2 are determined: a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of ANG2 above the reference level for ANG2 indicates that the subject is likely to suffer from structural heart disease (such as stage B heart failure) , whereas a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of ANG2 below the reference level for ANG2 indicates that the subject is not likely to suffer from structural heart disease (such as stage B heart failure).

[0207] Preferably, the following applies, if the levels of the cMyBP-C and a BNP -type peptide are determined: a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of the BNP -type peptide above the reference level for the BNP -type peptide indicates that the subject is likely to suffer from structural heart disease (such as stage B heart failure), whereas a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of the BNP -type peptide below the reference level for the BNP -type peptide indicates that the subject is not likely to suffer from structural heart disease (such as stage B heart failure).

[0208] Preferably, the following applies, if the levels of the biomarker cMyBP-C and the cardiac Troponin are determined: a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of the cardiac Troponin above the reference level for the the cardiac Troponin indicates that the subject is likely to suffer from structural heart disease (such as stage B heart failure), whereas a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of the cardiac Troponin below the reference level for the the cardiac Troponin indicates that the subject is not likely to suffer from structural heart disease (such as stage B heart failure).

[0209] If the assessment is the identification of a subject who is eligible to one or more diagnostic measures for diagnosing structural heart disease preceding symptomatic heart failure, the diagnostic algorithm in principle corresponds to the above algorithm, with the proviso that a subject who is likely (or who is not likely) to suffer from structural heart disease (such as stage B heart failure) is a subject who is eligible (or who is not eligible) to said one or more diagnostic measures.

[0210] For example, the following applies if the biomarkers cMyBP-C and MyL7: a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of MyL7 above the reference level for MyL7 indicates that the subject is eligible to said one or more diagnostic measures, whereas a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of MyL7 below the reference level for MyL7 indicates that the subject is not eligible to said one or more diagnostic measures. The result of the assessment in the last step of the method of the present invention, in an embodiment, is a statement concerning the status of the subject with regards to asymptomatic heart failure. Said result may be implicit, e.g. by juxtaposing the value determined in the sample to one or more reference(s), which may be further evaluated, e.g. by a medical practitioner. The result may, however, also be explicit, e.g. by annunciating that the comparison suggests a specific status with regards to asymptomatic heart failure. Thus, the method may further comprise a step of annunciating the result of the assessment. Alternatively or in addition, the result of the assessment may also be used in further assessments.

[0211] Additional steps of the method of the present invention (therapeutic and diagnostic methods).

[0212] The result of the assessment is step b) of the method of the present invention may form the basis for a further diagnostic measure for assessing asymptomatic heart failure in the test subject or a recommendation of said further diagnostic measure. Thus, in case a subject is diagnosed to be likely suffer from structural heart disease preceding heart failure, a suitable diagnostic assessment is recommended or initiated in order to confirm the assessment made by the method of the present invention. Preferably, the diagnostic measure is echocardiography, electrocardiography, or MRI. Thus, the diagnosis as referred to herein can be based on the biomarker(s) and images obtained by echocardiography, electrocardiography or MRI from the test subject.

[0213] The result of the assessment of the method of the present invention may form the basis for a treatment of the subject or a decision thereon. In particular, in case a subject is diagnosed to suffer from structural heart disease preceding symptomatic heart failure, such as stage B heart failure, a suitable therapeutic measure is recommended or initiated. Preferably, the therapeutic measure is a measure which aims to treat structural heart disease

[0214] Typically, the therapeutic measure shall aim to treat structural heart disease preceding symptomatic heart failure, such as stage B heart failure. In a preferred embodiment, the therapeutic measure is a measure as disclosed in Fig. 5 of Heidenreich et al. 2022 AHA / ACC / HFSA Guideline for the Management of Heart Failure Circulation. 2022; 145 :e895- el032. DOI: 10.1161 / CIR.0000000000001063).

[0215] In an embodiment, the therapeutic measure is the recommendation or the administration of a medicament (in case the subject suffers from structural heart disease, such as stage B heart failure). Preferably, the medicament is an angiotensin-converting enzyme (ACE) inhibitor and / or a beta blocker. In case, the subject is intolerant to ACE inhibitors, the medicament may be an Angiotensin-II-receptor blocker (ARB) instead of an ACE inhibitor.

[0216] Alternatively, the administration of a cardiac myosin inhibitor may be initiated or recommended. In an embodiment, the beta blocker is selected from proprenolol, metoprolol, bisoprolol, carvedilol, bucindolol and nebivolol.

[0217] In an embodiment, the ACE inhibitor is selected from Enalapril, Captopril, Ramipril and Trandolapril.

[0218] In an embodiment, the Angiotensin-II-receptor blocker is selected from Losartan, Valsartan, Irbesartan, Candesartan, Telmisartan and Eprosartan.

[0219] In an embodiment, the medicament is a cardiac myosin inhibitor. Cardiac myosin inhibitors are a novel treatment option for reducing LV mass and wall thickness (see Masri et al. J Am Coll Cardiol. 2024 Aug 28 :S0735- 1097(24)08167-1. doi: 10.1016 / j.jacc.2024.08.015). Preferred cardiac myosin inhibitors are mavacamten and aficamten.

[0220] Computer-implemented method

[0221] Moreover, the present invention relates to a computer-implemented method for assessing asymptomatic heart failure, comprising a) receiving, at a processing unit, a value for the level of the biomarker cMyBP- C is a sample (such as blood, serum or plasma) from a subject, and, optionally at least one further value for the level of at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide in a sample, b) comparing, by said processing unit, the value or values received in step a) to a reference or to references and / or calculating, by said processing unit, a score for assessing asymptomatic heart failure, wherein the score is based on the value or values received in step a), and c) assessing, preferably, by said processing unit, assessing asymptomatic heart failure based on the result of step b).

[0222] Terms, such as “computer-implemented”, "receiving" and “sample” have been defined above. The definitions apply accordingly. Moreover, preferred references, scores and diagnostic algorithms have been disclosed in connection with the method for assessing asymptomatic heart failure.

[0223] Moreover, the present invention relates to a database comprising one or more stored references for the biomarker cMyBP-C and, optionally one or more stored references for at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide. Preferably, the one or more stored references allow for assessing asymptomatic heart failure.

[0224] The term “database” has been defined above. The definition applies accordingly. Moreover, the present invention relates to a device for assessing asymptomatic heart failure, said device comprising: a) at least one measuring unit for determining an level of the biomarker cMyBP- C and, optionally, an level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2) and at least one BNP -type peptide in sample from a subject, said at least one measuring unit comprising at least one detection agent for the biomarker cMyBP-C and, optionally, at least one detection agent for the biomarker Myl7, at least one detection agent for the biomarker Angiopoietin-2 (Ang-2), at least one detection agent for the at least one BNP -type peptide, at least one detection agent for the at least one cardiac Troponin, and b) an evaluation unit operably linked to the measuring unit, said evaluation unit comprising a data processor comprising instructions for i) carrying out a comparison of the level of the biomarker cMyBP-C and, optionally, of the level of said at least one further biomarker to a reference or references and / or for ii) carrying out a calculation of a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and, optionally, on the level(s) of the at least one further biomarker.

[0225] The term “device” has been defined herein above. The definition applies accordingly.

[0226] The measuring unit, herein also referred to as “analyzing unit”, typically, comprises at least one reaction zone having a first detection agent for the first biomarker and a second detection agent for the second biomarker. The device may comprise one or more further detection agent(s) for one or more further, optional biomarker(s). The detection agent may be comprised in immobilized form on a solid support or carrier which is to be contacted to the sample. The detection agent may, however, also be comprised e.g. in liquid form in the device, e.g. as a stock solution, in particular in case the biomarker is determined in an activity assay. Moreover, in the reaction zone, it is in an embodiment possible to apply conditions which allow for the specific binding of the detection agent(s) to the biomarkers comprised in the sample and / or for a catalytic reaction to occur. The reaction zone may either allow directly for sample application or it may be connected to a loading zone where the sample is applied. In the latter case, the sample can be actively or passively transported via a connection between the loading zone and the reaction zone to the reaction zone. Moreover, the reaction zone shall be also connected to a detector. The connection shall be such that the detector can detect the result of a detection reaction, e.g. the binding of the biomarkers to their detection agents or an enzymatic reaction. Suitable detectors depend on the techniques used for measuring the presence or level of the biomarkers. For example, for optical detection, transmission of light may be required between the detector and the reaction zone while for electrochemical determination a fluidal connection may be required, e.g., between the reaction zone and an electrode. The detector shall be adapted to allow determination of the level of the biomarker(s). The determined level can be subsequently transmitted to the evaluation unit.

[0227] The evaluation unit comprises at least one data processor, which may also be referred to as a data processing unit, such as a computer, with an implemented algorithm for determining the level present in the sample. Appropriate data processing units are known in the art and include in particular a Central Processing Unit (CPU), a Graphics Processing Units (GPU), an Application Specific Integrated Circuit (ASIC), a Tensor Processing Unit (TPU), a field- programmable gate array (FPGA), and other data processing units know in the art. A data processor may e.g. be a general purpose computer or a portable computing device. It should also be understood that multiple computing devices may be used together, such as over a network or other methods of transferring data, for performing one or more steps of the methods disclosed herein. Exemplary computing devices include desktop computers, laptop computers, personal data assistants (“PDA”), cellular devices, smart or mobile devices, tablet computers, servers, and the like. In general, a data processing unit comprises a processor capable of executing a plurality of instructions (such as a program of software).

[0228] The evaluation unit, typically comprises or has access to a memory. A memory is a computer readable information storage medium and may comprise a single storage device or multiple storage devices, located either locally with the computing device or accessible to the computing device across a network, for example. Computer-readable media may be any available media that can be accessed by the computing device and includes both volatile and non-volatile media. Further, computer readable-media may be one or both of removable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media. Exemplary computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or any other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used for storing a plurality of instructions capable of being accessed by the computing device and executed by the processor of the computing device. The evaluation unit, in an embodiment, further comprises a database as specified herein above.

[0229] According to embodiments of the instant disclosure, software may include instructions which, when executed by a processor of the computing device, may perform one or more steps of the methods disclosed herein. Some of the instructions may be adapted to produce signals that control operation of other units of the device, e.g. a measuring unit and / or other devices and thus may operate through those control signals to transform materials far removed from the device itself. These descriptions and representations are the means used by those skilled in the art of data processing, for example, to most effectively convey the substance of their work to others skilled in the art.

[0230] The plurality of instructions may also comprise an algorithm which is generally conceived to be a self-consistent sequence of steps leading to a desired result. These steps may include those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic pulses or signals capable of being stored, transferred, transformed, combined, compared, and otherwise manipulated. It proves convenient at times, principally for reasons of common usage, to refer to these signals as values, characters, display data, numbers, or the like as a reference to the physical items or manifestations in which such signals are embodied or expressed. It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely used here as convenient labels applied to these quantities.

[0231] The evaluation unit may also comprise or have access to an output device. Exemplary output devices include displays, printers, files, and telecommunication devices, such as fax devices, data servers, and the like. According to some embodiments, a computing device may perform one or more steps of a method disclosed herein, and thereafter provide an output, via an output device, relating to an assessment result, indication, ratio or other factor of the method.

[0232] The term “detection agent”, for which also "detection compound" may be used, as used herein, refers to any agent which allows determination, in an embodiment specific determination, of an amount of at least one biomarker. Thus, the detection agent may in particular be a reaction substrate, e.g. in case the biomarker has catalytic activity, e.g. is an enzyme; or the detection agent may be an agent binding, in an embodiment specifically, to a biomarker or analyte thereof.

[0233] The skilled person selects suitable detection substrates in dependence on the biomarker, i.e. catalytic activity, to be detected, based on information available in the art. For specific biomarkers, example substrates are provided herein above.

[0234] Also, binding agents for specific antigens, as well as methods for providing them, are known in the art. As indicated herein above, the detection agent being a binding agent in an embodiment specifically binds to a biomarker, i.e. does not cross-react with other components present in the sample. Typically, a detection agent specifically binding a biomarker as referred to herein may be an antibody, an antibody fragment or derivative, an aptamer, a ligand for the biomarker, a receptor for the biomarker, an enzyme known to bind and / or convert the biomarker, or a small molecule known to specifically bind to the biomarker. For example, antibodies as referred to herein as detection agents include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments that are capable of binding antigen or hapten. Aptamer detection agents, e.g., may be nucleic acid or peptide aptamers. Methods to prepare such aptamers are well-known in the art. The detection agent may be fused or linked permanently or reversibly to a detectable label. Suitable labels are well known to the skilled artisan. Suitable detectable labels are any labels detectable by an appropriate detection method. Typical labels include gold particles, latex beads, acridan ester, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels ("e.g. magnetic beads", including paramagnetic and superparamagnetic labels), and fluorescent labels.

[0235] “Specific binding” of a detection agent means that it should not bind substantially to, i.e. crossreact with, another peptide, polypeptide or substance present in the sample to be analyzed. Preferably, the specifically bound biomarker should be bound with at least 3 times higher, more preferably at least 10 times higher and even more preferably at least 50 times higher affinity than any other components of the sample. Non-specific binding may be tolerable, if it can still be distinguished and measured unequivocally, e.g. according to its size on a Western Blot, or by its relatively higher abundance in the sample.

[0236] Moreover, the present invention relates to a kit for assessing asymptomatic heart failure, said kit comprising at least one detection agent for the biomarker cMyBP-C and at least one detection agent for at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide.

[0237] The term “detection agent” has been defined above. In a preferred embodiment, the detection agent is an antibody, or antigen-binding fragments thereof, which specifically binds to the biomarker as referred to herein.

[0238] Moreover, the present invention relates to the use of i. the biomarker cMyBP-C, or at least one detection agent thereof, and optionally ii. at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide, or at least one detection agent for said at least one further biomarker, in a sample (such as blood, serum or plasma) from a subject for assessing asymptomatic heart failure.

[0239] Moreover, the present invention relates to the use of i. at least one detection agent for cMyBP-C, and optionally ii. at least one detection agent for at least one further biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide, in for determining the level of cMyBP-C and optionally the level of said at least one further biomarker in a sample (such as blood, serum or plasma) from a subject as referred herein.

[0240] Preferably, said use is an in vitro use. The term “detection agent” has been defined above. In a preferred embodiment, the detection agent is an antibody, or antigen-binding fragments thereof, which specifically binds to the biomarker as referred to herein.

[0241] Preferred detection agents for cMyBP-C are preferably the first and the second monoclonal antibody, or antigen-binding fragments thereof, as defined above.

[0242] Moreover, the present invention relates to a method for determining the level of a first biomarker, said first biomarker being cMyBP-C, the level of a second biomarker and, optionally, the level of a third biomarker in a sample blood, serum or plasma from a subject suspected to suffer from structural heart disease (such as stage B heart failure) comprising i) contacting a portion of said blood, serum or plasma sample with one or more detection agents that specifically bind to the biomarker cMyBP- C present in the sample, thereby allowing the formation of first complex comprising said biomarker and said one or more detection agents and ii) contacting the same or a different portion of said blood, serum or plasma sample with one or more detection agents that specifically bind the second biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide, and thereby allowing the formation of a second complex comprising said second biomarker and said one or more detection agents, and optionally iii) contacting the same portion as in i) or ii), or a different portion of said blood, serum or plasma sample with one or more detection agents that specifically bind a third biomarker selected from the group consisting of MyL7, at least one cardiac Troponin, Angiopoietin-2 and at least one BNP -type peptide, and thereby allowing the formation of a third complex comprising said third biomarker and said one or more detection agents, wherein the third biomarker is not the second biomarker and iv) determining the level of the first biomarker, the second biomarker and, optionally, the third biomarker by determining the level of the first complex, the second complex, and optionally the third complex.

[0243] Preferably, the sample is a blood, serum or plasma sample from a subject suspected to suffer from structural heart disease (such as stage B heart failure). More preferably, the sample is a blood, serum or plasma sample from a subject who suffers from structural heart disease preceding overt heart failure.

[0244] The invention further relates to a computer program including computer-executable instructions for performing the method according to the present invention in one or more of the embodiments enclosed herein when the program is executed on a computer or computer network or a device as specified herein. Specifically, the computer program may be stored on a computer-readable data carrier. Thus, specifically, one, more than one or even all of method steps of the method of the present invention may be performed by using a computer or a computer network, in an embodiment by using a computer program. Thus, the present invention in particular proposes a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out a method as specified herein above; and to a computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out a method as specified herein above; to a computer- readable data carrier having stored thereon the computer program as specified herein above; and to a data carrier signal carrying the computer program as specified herein above. The present invention also relates to a data processing apparatus, device, or system comprising means for carrying out performing the method according to the present invention; to a data processing apparatus, device, or system comprising a processor configured to perform the method according to the present invention.

[0245] The invention further relates to a computer program product having program code means, in order to perform the method according to the present invention in one or more of the embodiments enclosed herein when the program is executed on a computer or computer network. Specifically, the program code means may be stored on a computer-readable data carrier.

[0246] In the following, preferred embodiments of the present invention are disclosed. The definitions above apply accordingly.

[0247] 1. A method for assessing asymptomatic heart failure in a subject, comprising the steps of a) determining the level of cMyBP-C (Myosin binding protein C, cardiac type), and optionally the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample from the subject, and b) assessing asymptomatic heart failure based on the level of cMyBP-C, and, optionally, the level of at least one further biomarker determined in step a).

[0248] 2. The method of embodiment 1, wherein the sample is a blood, serum or plasma sample. The method of embodiment 1 or 2, wherein the subject is a human subject. The method of embodiment 1 to 3, wherein the subject does not show the following symptoms of heart failure: Shortness of breath with activity or when lying down, fatigue and weakness, swelling in the legs, ankles and feet, rapid or irregular heartbeat, reduced ability to exercise. The method of any one of the preceding embodiments, wherein the subject does not suffer from stage C or stage D heart failure. The method of any one of the preceding embodiments, the subject is suspected to suffer from asymptomatic heart failure. The method of embodiment 6, wherein a subject who is suspected to suffer from asymptomatic heart failure has arterial hypertension, diabetes and / or obesity and / or wherein the subject is 65 years old or older. The method of any one of the preceding embodiments wherein the subject has diabetes, in particular type 2 diabetes. The method of any one of the preceding embodiments, wherein the subject suffers from arterial hypertension. The method of any one of the preceding embodiments, wherein the subject does not suffer from aortic stenosis. The method of any one of any one of the preceding embodiments, wherein step b) comprises i. comparing the level of cMyBP-C to a reference level and, optionally the level of the at least one further biomarker to a reference level for said at least one biomarker, and / or ii. calculating a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and optionally the level of the at least one further biomarker. The method of embodiment 11, wherein the reference level is a predetermined value for the level the respective biomarker which allows for assessing asymptomatic heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the diagnosis of stage B heart failure. The method of any one of embodiments 1 to 12 wherein the assessment of asymptomatic heart failure is the diagnosis of structural heart disease preceding symptomatic heart failure. The method of embodiment 13, wherein the level of the biomarker cMyBP-C is determined, and wherein preferably a level of the biomarker cMyBP-C above the reference level indicates that the subject suffers from stage B heart failure and / or wherein a level of the biomarker cMyBP-C below the reference level indicates that the subject does not suffer from stage B heart failure. The method of embodiment 13, wherein the levels of the biomarker cMyBP-C and the at least one further biomarker are determined, wherein preferably a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of the at least one further biomarker above the reference level for at least one further biomarker indicates that the subject suffers from stage B heart failure and / or wherein preferably a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of the at least one further biomarker below the reference level for at the least one further biomarker indicates that the subject does not suffer from stage B heart failure. The method of any one of embodiments 1 to 16, further comprising initiating or recommending one or more further diagnostic measures for diagnosing stage B heart failure for a subject who has been diagnosed to suffer from stage B heart failure. The method of any one of embodiments 1 to 16, further comprising initiating or recommending a suitable therapeutic measure for a subject diagnosed to suffer from stage B heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the differentiation between stage B heart failure versus stage A heart failure or no heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the differentiation a subject who has structural abnormalities of the heart preceding heart failure and a subject bearing only risk factors of heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the assessment of the severity of asymptomatic heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the monitoring of asymptomatic heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is assessment of the extent of structural heart disease in asymptomatic heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is prediction of the risk to suffer from stage C or D heart failure. The method of any one of embodiments 1 to 12, wherein the assessment of asymptomatic heart failure is the identification of a subject who is eligible to a further diagnostic measure for assessing asymptomatic heart failure. The method of embodiment 25, wherein the further diagnostic measure is echocardiography, electrocardiography, or MRI, in particular echocardiography, electrocardiography, or MRI for determining structural changes of the heart preceding heart failure. A computer-implemented method for assessing asymptomatic heart failure, comprising a) receiving, at a processing unit, a value for the level of cMyBP-C in a sample from a subject, and, optionally at least one further value for the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), Angiopoietin-2 (Ang-2), at least one cardiac Troponin and at least one BNP -type peptide in said sample, b) comparing, by said processing unit, the value or values received in step a) to a reference or to references and / or calculating, by said processing unit, a score for assessing asymptomatic heart failure, wherein the score is based on the value or values received in step a), and c) assessing, preferably by the processing unit, asymptomatic heart failure based on the result of step b). The computer-implemented method of embodiment 27, wherein the subject is suspected to suffer from asymptomatic heart failure. The computer-implemented method of embodiment 27 or 28, wherein the reference level is a predetermined value for the level the respective biomarker which allows for assessing asymptomatic heart failure. The computer-implemented method of embodiment 29, wherein the value for level of the biomarker cMyBP-C is received in step a), and wherein preferably wherein preferably a level of the biomarker cMyBP-C above the reference level indicates that the subject suffers from stage B heart failure and / or wherein a level of the biomarker cMyBP-C below the reference level indicates that the subject does not suffer from stage B heart failure. Use of i. the biomarker cMyBP-C, or at least one detection agent thereof, and optionally ii. at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide, or at least one detection agent for said at least one further biomarker, in a sample from a subject for assessing asymptomatic heart failure. A device for assessing asymptomatic heart failure, said device comprising: a) at least one measuring unit for determining an level of the biomarker cMyBP- C and, optionally, an level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2) and at least one BNP -type peptide in a sample from a subject, said at least one measuring unit comprising at least one detection agent for the biomarker cMyBP-C and, optionally, at least one detection agent for the biomarker Myl7, at least one detection agent for the biomarker Angiopoietin-2 (Ang-2), at least one detection agent for at least one BNP -type peptide, at least one detection agent for the at least one cardiac Troponin, and b) an evaluation unit operably linked to the measuring unit, said evaluation unit comprising a data processor comprising instructions for i) carrying out a comparison of the level of the biomarker cMyBP-C and, optionally, of the level of said at least one further biomarker to a reference or references and / or for ii) carrying out a calculation of a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and, optionally, on the level(s) of the at least one further biomarker. 33. A kit for assessing asymptomatic heart failure, said kit comprising at least one detection agent for the biomarker cMyBP-C and at least one detection agent for at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Ang-2 and at least one BNP -type peptide.

[0249] 34. The use, the kit or the device of any one of the preceding embodiments, wherein the detection agent is an antibody that specifically detects the biomarker, or an antigenbinding fragment thereof.

[0250] 35. A database comprising one or more stored references for the biomarker cMyBP-C and, optionally one or more stored references for at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Ang2, and at least one BNP -type peptide.

[0251] 36. A computer program including computer-executable instructions for performing the computer-implemented method according to any one of embodiments 29 to 31, when the program is executed on a computer or computer network.

[0252] All patents, patent applications, and publications or public disclosures referred to or cited herein are incorporated by reference in their entirety.

[0253] The invention will be further described with reference to the examples described herein; however, it is to be understood that the invention is not limited to such examples.

[0254] Example 1: Description of the PREDICTOR cohort

[0255] Biomarker analyses were done in samples of asymptomatic participants of the PREDICTOR study.

[0256] PREDICTOR was a cross-sectional, population-based study to evaluate the prevalence of asymptomatic left ventricular dysfunction and heart failure in elderly subjects of 65 years or older, see High- sensitivity cardiac troponin T for detection of subtle abnormalities of cardiac phenotype in a general population of elderly individuals. J Intern Med 2013; 273: 306-317. Staging of HF in PREDICTOR (and especially stage B) is described in the following paper: Evaluation of different strategies for identifying asymptomatic left ventricular dysfunction and pre-clinical (stage B) heart failure in the elderly. Results from ‘PREDICTOR’, a population based-study in central Italy European Journal of Heart Failure (2013) 15, 1102-1112, doi : 10.1093 / eurj hf / hft098.

[0257] Stage A HF was diagnosed if cardiovascular (CV) RFs such as AH, T2DM, obesity, or metabolic syndrome (METs, ATP-III criteria) were detected, or in the presence of a documented clinical history of atherosclerotic disease or a positive case history for use of cardiotoxins, without evidence of structural heart disease and any signs or symptoms of HF." "Stage B was diagnosed in the presence of asymptomatic left ventricular dysfunction (ALVD) and / or a structural heart disease detected at transthoracic echocardiography, or of a positive clinical history for CV disease or valvular heart disease in the absence of clinical signs or symptoms of HF (Table 2 in Murredu et al. Prevalence of preclinical and clinical heart failure in the elderly. A population-based study in Central Italy. European Journal of Heart Failure (2012) 14, 718-729 doi: 10.1093 / eurjhf / hfs052).

[0258] Left ventricular hypertrophy (LVH) was determined in the presence of elevated left ventricular mass (LV mass) > 95 g / m2 in women and > 115 g / m2 in men.

[0259] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in a subpanel of the PREDICTOR study comprising 430 randomly selected samples matching the distribution of ACC / AHA stage N (Normal), A and B of the full cohort. ACC / AHA classifications are Normal (n=50), stage A HF (n=137) and stage B HF (n=243). Information regarding LV mass was available for 373 patient samples. The subpanel comprised samples of 253 patients with hypertension and 72 patients with diabetes.

[0260] In a first set of analyses markers were evaluated with regard to the assessment of stage B heart failure in samples of asymptomatic participants of the PREDICTOR study, see 2. Similar analyses were done for patients with hypertension and with diabetes, see 2.1 and 2.2 respectively.

[0261] In a second set of analyses, markers were evaluated regarding the assessment of LVH in samples of asymptomatic PREDICTOR study participants, see 3. Similar analyses were done for patients with hypertension, see 3.1. and with diabetes, see 3.2.

[0262] Example 2: Assessment of HF in asymptomatic PREDICTOR study participants

[0263] Five Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] were measured in a subpanel of the PREDICTOR study comprising 430 randomly selected samples matching the distribution of ACC / AHA stage Normal, A and B of the full cohort. ACC / AHA classifications are Normal (n=50), stage A HF (n=137) and stage B HF (n=243). Included are male patients with the following classifications: Normal (n=26), stage A HF (n=68) and stage B HF (n=126) and female patients with the following classifications: Normal (n=24), stage A HF (n=69) and stage B HF (n=l 17).

[0264] The results of analyses relating to biomarker concentrations in samples from asymptomatic patients with either Normal classification, stage A or stage B heart failure are shown in Figure 1. It was shown that circulating levels of all investigated biomarkers increased from normal and stage A to stage B heart failure. Data evaluation showed that patients with cMyBP-C levels above a reference value are suspected to have stage B HF. The observed AUC of cMyBP-C for the detection of stage B HF versus normal or stage A HF was 0.653. In contrast the observed AUCs of cTnThs, NTproBNP or MyL7 for the detection of stage B HF versus normal or stage A HF were 0.604, 0.567 or 0.598 respectively. Thus, in the patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients of the PREDICTOR study without aortic stenosis (normal or stage A HF) versus cTnThs, NTproBNP or MyL7.

[0265] Thus, in the patients analyzed herein, cMyBP-C clearly outperforms cTnThs, NTproBNP or MyL7. The evaluation of cMyBP-C in samples of asymptomatic PREDICTOR study participants demonstrates that modestly elevated circulating cMyBP-C titers are associated with the early detection of heart failure in asymptomatic HF patients without aortic stenosis (normal or stage A HF).

[0266] The finding that cMyBP-C outperforms cTnThs, NTproBNP and MyL7 with the best AUC for stage B detection in asymptomatic patients without aortic stenosis (normal or stage A HF) was confirmed for male patients and for female patients in separate analyses as described below.

[0267] The observed AUC of cMyBP-C for the detection of stage B HF versus normal or stage A HF in male patients was 0.714. In contrast the observed AUCs of cTnThs, NTproBNP or MyL7 for the detection of LVH were 0.630, 0.639 or 0.681 respectively. Thus, in the male patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients without aortic stenosis (normal or stage A HF) versus cTnThs, NTproBNP or MyL7.

[0268] The observed AUC of cMyBP-C for the detection of stage B HF versus normal or stage A HF in female patients was 0.608. In contrast the observed AUCs of cTnThs, NTproBNP or MyL7 for the detection of LVH were 0.600, 0.534 or 0.493 respectively. Thus, in the female patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients without aortic stenosis (normal or stage A HF) versus cTnThs, NTproBNP or MyL7. Thus data show clearly that cMyBP-C outperforms cTnThs, MyL7, NTproBNP for both male and female patients in the detection of stage B heart failure in asymptomatic patients without aortic stenosis (normal or stage A HF).

[0269] Additional analyses related to biomarker concentrations in samples from asymptomatic with either stage A or stage B heart failure, see Fig.2.

[0270] The observed AUC of Angiopoietin2 for the detection of stage B HF versus stage A HF in was 0.519, see Table 1.

[0271] The observed AUC of cMyBP-C for the detection of stage B HF versus stage A HF was 0.627. In contrast the observed AUCs of cTnThs, NTproBNP, Angiopoietin2 or MyL7 for the detection of stage B HF versus stage A HF were 0.589, 0.559, 0.519 or 0.595 respectively. Thus, in the patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients without aortic stenosis (stage A HF) versus cTnThs, NTproBNP, Angiopoietin2 or MyL7.

[0272] Thus data show clearly that cMyBP-C outperforms cTnThs, MyL7, NTproBNP or Angiopoietin2 for both male and female patients in the assessment of stage B heart failure in PREDICTOR study participants with asymptomatic heart failure.

[0273] 2.1 Assessment of stage B HF in asymptomatic PREDICTOR study participants with hypertension

[0274] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in samples of 253 asymptomatic PREDICTOR study participants with hypertension. ACC / AHA classifications are stage A HF (n=108) and stage B HF (n=145). Information regarding LV mass was available for 215 patient samples. ). Included are male patients with the following classifications: Stage A HF (n=56) and stage B HF (n=77) and female patients with the following classifications: Stage A HF (n=52) and stage B HF (n=68).

[0275] TABLE 1 : Biomarker concentrations in samples from asymptomatic patients and for the subgroup of asymptomatic patients with hypertension and either stage A or stage B heart failure

[0276] The observed sensitivity for the detection of HF in asymptomatic patients with hypertension was 42,8% at a specificity of 80% for cMyBP-C as well as for cTnThs. In contrast the observed sensitivities of NTproBNP, MYL7 or Angiopoietin2 for the detection of HF in asymptomatic patients with hypertension were 28.3%, 39.9% or 22.1% respectively at a specificity of 80%.

[0277] The observed AUC of cMyBP-C for the detection of stage B HF versus stage A HF in patients with hypertension was 0.664. In contrast the observed AUCs of cTnThs, NTproBNP, Angiopoietin2 or MyL7 for the detection of stage B HF versus stage A HF in patients with hypertension were 0.630, 0.576, 0.513 or 0.608 respectively.

[0278] 2.2 Assessment of stage B HF in asymptomatic PREDICTOR study participants with diabetes

[0279] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in samples of 72 asymptomatic PREDICTOR study participants with diabetes. ACC / AHA classifications are stage A HF (n=25) and stage B HF (n=47). Included are male patients with the following classifications: Stage A HF (n=l l) and stage B HF (n=20) and female patients with the following classifications: Stage A HF (n=14) and stage B HF (n=27). The results are shown in Figure 3.

[0280] The observed AUC of cMyBP-C for the detection of stage B HF versus stage A HF in asymptomatic patients with diabetes was 0.691. In contrast the observed AUCs of cTnThs, NTproBNP or MyL7 for the detection of stage B HF versus stage A HF in asymptomatic patients with diabetes were 0.681, 0.673 or 0.583 respectively. Thus, in the patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients with diabetes and without aortic stenosis (stage A HF) versus cTnThs, NTproBNP or MyL7. Example 3: Assessment of LVH

[0281] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in a subpanel of the PREDICTOR study comprising 430 randomly selected samples matching the distribution of ACC / AHA stage N, A and B of the full cohort. ACC / AHA classifications are Normal (n=50), stage A HF (n=137) and stage B HF (n=243).

[0282] Left ventricular hypertrophy (LVH) was determined in the presence of elevated left ventricular mass (LV mass) > 95 g / m2 in women and > 115 g / m2 in men.

[0283] Information regarding LV mass was available for 373 patient samples. Presence of LVH was determined in 119 patients. Left ventricular mass was confirmed to be not elevated in 254 patients. Included are male patients with LVH (n=60) and without LVH (n=126) and female patients with LVH (n=59) and without LVH (n=128).

[0284] The results are shown in Figure 4.

[0285] The observed AUC of cMyBP-C for the detection of LVH in asymptomatic patients (classified as Normal, stage A or stage B) was 0.717. In contrast the observed AUCs of MyL7, cTnThs, NTproBNP or Angiopoietin2 for detection of LVH in asymptomatic patients (classified as Normal, stage A or stage B) were 0.610, 0.607, 0.635 or 0.538 respectively. Thus, in the patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of stage B HF in asymptomatic patients and without aortic stenosis (stage A HF) versus cTnThs, NTproBNP, Angiopoietin2 or MyL7.

[0286] The finding that cMyBP-C outperforms cTnThs, NTproBNP, Angiopoietin2 and MyL7 with the best performance for LVH detection in asymptomatic patients without aortic stenosis (normal or stage A HF) was confirmed for male patients and for female patients in separate analyses as described below.

[0287] The observed sensitivity of cMyBP-C for the detection of LVH in asymptomatic male patients at a fixed specificity of 80% was 65%. In contrast the observed sensitivities of cTnThs, NTproBNP or MyL7 for the detection of LVH in asymptomatic males at 80% specificity were 35.6%, 54.2%, 46.7% or 38.3% respectively.

[0288] The observed sensitivity of cMyBP-C for the detection of LVH in asymptomatic female patients at a fixed specificity of 80% was 42.4%. In contrast the observed sensitivities of cTnThs, NTproBNP, MyL7 or Angiopoietin2 for the detection of LVH in asymptomatic males at 80% specificity were 32.2%, 16.9%, 24.1% or 27.1% respectively.

[0289] Thus data show clearly that cMyBP-C outperforms cTnThs, MyL7, NTproBNP and Angiopoietin2 for both male and female patients in the detection of elevated LV mass and the presence of LVH in the asymptomatic patients analyzed herein. The biomarker cMyBP-C allows for an improved detection of LVH in asymptomatic patients without aortic stenosis (normal or stage A HF) versus cTnThs, NTproBNP, Angiopoietin2 or MyL7.

[0290] 3.1 Assessment of LVH in asymptomatic PREDICTOR study participants with hypertension

[0291] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in samples of 253 asymptomatic PREDICTOR study participants with hypertension. ACC / AHA classifications are stage A HF (n=108) and stage B HF (n=145).

[0292] Left ventricular hypertrophy (LVH) was determined in the presence of elevated left ventricular mass (LV mass) > 95 g / m2 in women and > 115 g / m2 in men.

[0293] Information regarding LV mass was available for 215 patient samples. Presence of LVH was determined in 82 patients. Left ventricular mass was confirmed to be not elevated in 133 patients. Included are male patients with LVH (n=42) and without LVH (n=69) and female patients with LVH (n=40) and without LVH (n=64).

[0294] The results are shown in Figure 5.

[0295] Data evaluation showed that asymptomatic hypertensive patients with cMyBP-C levels above a reference value were suspected to have left ventricular hypertrophy (LVH). The observed AUC of cMyBP-C for the detection of LVH was 0.714.

[0296] In contrast the observed AUCs of NTproBNP, cTnThs, MyL7 or Angiopoietin2 for the detection of LVH in asymptomatic hypertensive patients were 0.652, 0.620, 0.618 or 0.543 respectively. Thus, in the patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of LVH versus NTproBNP, cTnThs, MyL7 or Angiopoietin2.

[0297] Thus, in the asymptomatic hypertensive patients analyzed herein, cMyBP-C clearly outperforms NTproBNP, cTnThs, MyL7 or Angiopoietin2.

[0298] The marker evaluation in samples of asymptomatic hypertensive PREDICTOR study participants demonstrates that modestly elevated circulating cMyBP-C titers are associated with LVH, and associated diseases.

[0299] The finding that cMyBP-C outperforms cTnThs, NTproBNP, Angiopoietin2 and MyL7 with the best AUC for LVH detection in asymptomatic hypertensive patients was confirmed for male patients and for female patients in separate analyses as described below.

[0300] The observed AUC of cMyBP-C for the detection of LVH in male hypertensive asymptomatic patients was 0.828. In contrast the observed AUCs of cTnThs, NTproBNP, MyL7 or Angiopoietin2 for the detection of LVH in male hypertensive asymptomatic patients were 0.652, 0.760, 0.711 or 0.591 respectively. Thus, in the male asymptomatic hypertensive patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of LVH versus cTnThs, NTproBNP, MyL7 or Angiopoietin2.

[0301] The observed AUC of cMyBP-C for the detection of LVH in female patients was 0.659. In contrast the observed AUCs of cTnThs, NTproBNP, MyL7 or Angiopoietin2 for the detection of LVH were 0.603, 0.518, 0.514 or 0.517 respectively. Thus, in the female hypertensive asymptomatic patients analyzed herein, the biomarker cMyBP-C allows for an improved detection of LVH versus cTnThs, NTproBNP, Angiopoietin2 or MyL7.

[0302] Thus data show clearly that cMyBP-C outperforms cTnThs, MyL7, NTproBNP or Angiopoietin2 for both male and female patients in the detection of elevated LV mass and the presence of LVH in asymptomatic hypertensive patients.

[0303] 3.2 Assessment of LVH in asymptomatic PREDICTOR study participants with diabetes

[0304] Retrospective cross-sectional analyses were performed for 5 Elecsys markers [cMyBP-C, MyL7, cTnThs, NTproBNP and Angiopoietin2] in samples of 72 asymptomatic PREDICTOR study participants with diabetes. ACC / AHA classifications are stage A HF (n=25) and stage B HF (n=47).

[0305] Left ventricular hypertrophy (LVH) was determined in the presence of elevated left ventricular mass (LV mass) > 95 g / m2 in women and > 115 g / m2 in men.

[0306] Information regarding LV mass was available for 61 patient samples. Presence of LVH was determined in 24 patients. Left ventricular mass was confirmed to be not elevated in 37 patients. Included are male patients with LVH (n=9) and without LVH (n=18) and female patients with LVH (n=15) and without LVH (n=19). The results are shown in Figure 6.

[0307] Data evaluation showed that asymptomatic diabetes patients with Angiopoietin2, NTproBNP or cMyBP-C levels above a reference value were suspected to have left ventricular hypertrophy (LVH). The observed AUC of Angiopoietin2, NTproBNP or cMyBP-C for the detection of LVH were 0.664. 0.610 or 0.601 respectively.

[0308] In contrast the observed AUCs of cTnThs or MyL7 for the detection of LVH in asymptomatic diabetes patients were 0.443 or 0.520 respectively. Thus, in the patients analyzed herein, the biomarkers Angiopoietin2, NTproBNP and cMyBP-C allow for an improved detection of LVH versus cTnThs or MyL7.

[0309] Thus, in the asymptomatic diabetes patients analyzed herein, cMyBP-C clearly outperforms cTnThs or MyL7.

[0310] The marker evaluation in samples of asymptomatic PREDICTOR study participants with diabetes demonstrates that modestly elevated circulating cMyBP-C and Angiopoietin2 or NTproBNP titers are associated with LVH, and associated diseases.

Claims

1. Roche Diagnostics GmbH October 30, 2025Roche Diagnostics International AG RD39606PCClaims1. A method for assessing asymptomatic heart failure in a subject who does not suffer from aortic stenosis, comprising the steps of a) determining the level of cMyBP-C (Myosin binding protein C, cardiac type), and optionally the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide in a sample from the subject, and b) assessing asymptomatic heart failure based on the level of cMyBP-C, and, optionally, the level of at least one further biomarker determined in step a).

2. The method of claim 1, wherein the sample is a blood, serum or plasma sample.

3. The method of claim 1 or 2, wherein the subject is a human subject who is suspected to suffer from asymptomatic heart failure, in particular wherein the subject is a human subject has arterial hypertension, diabetes and / or obesity and / or wherein the subject is 65 years old or older.

4. The method of claim 1 to 3, wherein the subject does not show the following symptoms of heart failure: Shortness of breath with activity or when lying down, fatigue and weakness, swelling in the legs, ankles and feet, rapid or irregular heartbeat, and reduced ability to exercise.

5. The method of any one of claims 1 to 4 wherein the subject has diabetes, in particular type 2 diabetes.

6. The method of any one of the preceding claims, wherein the subject suffers from arterial hypertension.

7. The method of any one of any one of the preceding claims, wherein step b) comprises i. comparing the level of cMyBP-C to a reference level and, optionally the level of the at least one further biomarker to a reference level for said at least one biomarker, and / or ii. calculating a score for assessing asymptomatic heart failure, wherein the score is calculated based on the level of cMyBP-C and optionally the level of the at least one further biomarker.

8. The method of any one of claims 1 to 7, wherein the assessment of asymptomatic heart failure is the diagnosis of stage B heart failure, in particular wherein the assessment of asymptomatic heart failure is the diagnosis of structural heart disease preceding symptomatic heart failure.

9. The method of claim 8, wherein the level of the biomarker cMyBP-C is determined, and wherein preferably a level of the biomarker cMyBP-C above the reference level indicates that the subject suffers from stage B heart failure and / or wherein a level of the biomarker cMyBP-C below the reference level indicates that the subject does not suffer from stage B heart failure, or wherein the levels of the biomarker cMyBP-C of at least one further biomarker are determined, wherein preferably a level of the biomarker cMyBP-C above the reference level for cMyBP-C in combination with a level of the at least one further biomarker above the reference level for at least one further biomarker indicates that the subject suffers from stage B heart failure and / or wherein preferably a level of the biomarker cMyBP-C below the reference level for cMyBP-C in combination with a level of the at least one further biomarker below the reference level for at the least one further biomarker indicates that the subject does not suffer from stage B heart failure.

10. The method of any one of claims 1 to 9, further comprising i) initiating or recommending one or more further diagnostic measures for diagnosing stage B heart failure for a subject who has been diagnosed to suffer from stage B heart failure, or ii) initiating or recommending a suitable therapeutic measure for a subject diagnosed to suffer from stage B heart failure.

11. The method of any one of claims 1 to 7, wherein the assessment of asymptomatic heart failure is the differentiation between stage B heart failure versus stage A heart failure or no heart failure.

12. The method of any one of claims 1 to 7, wherein the assessment of asymptomatic heart failure is the differentiation a subject who has structural abnormalities of the heart preceding heart failure and a subject bearing only risk factors of heart failure.

13. The method of any one of claims 1 to 7, wherein the assessment of asymptomatic heart failure is the identification of a subject who is eligible to a further diagnostic measure for assessing asymptomatic heart failure, in particular wherein the further diagnostic measure is echocardiography, electrocardiography, or MRI, in particular echocardiography, electrocardiography, or MRI for determining structural changes of the heart preceding heart failure.

14. A computer-implemented method for assessing asymptomatic heart failure, comprising a) receiving, at a processing unit, a value for the level of cMyBP-C in a sample from a subject who does not suffer from aortic stenosis, and, optionally at least one further value for the level of at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), Angiopoietin-2 (Ang- 2), at least one cardiac Troponin and at least one BNP -type peptide in said sample, b) comparing, by said processing unit, the value or values received in step a) to a reference or to references and / or calculating, by said processing unit, a score for assessing asymptomatic heart failure, wherein the score is based on the value or values received in step a), and c) assessing, preferably by the processing unit, asymptomatic heart failure based on the result of step b).

15. Use of i. the biomarker cMyBP-C, or at least one detection agent thereof, and optionally ii. at least one further biomarker selected from the group consisting of MyL7 (Myosin light chain 7), at least one cardiac Troponin, Angiopoietin-2 (Ang-2), and at least one BNP -type peptide, or at least one detection agent for said at least one further biomarker, in a sample from a subject for assessing asymptomatic heart failure, wherein the subject does not suffer from aortic stenosis.

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