CIRCULATING BMP10 (BONE MORPHOGENIC PROTEIN 10) IN THE ASSESSMENT OF ATRIAL FIBRILLATION

Abstract

The present invention relates to a method for assessing atrial fibrillation in a subject, said method comprising the steps of determining the amount of BMP 10 in a sample from the subject, and comparing the amount of BMP 10 to a reference amount, whereby atrial fibrillation is to be assessed. Moreover, the present invention relates to a method for diagnosing heart failure based on the determination of BMP 10 in a sample from a subject. Further, the present invention relates to a method for predicting the risk of a subject of hospitalization due to heart failure based on the determination of a BMP 10-type peptide in a sample from a subject.

Claims

1. A method for assessing atrial fibrillation in a subject, comprising the steps of a) determining, in at least one sample from the subject, the amount of a BMP 10-type peptide (Bone Morphogenic Protein 10-type peptide) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 (Angiopoietin 2) and FABP3 (Fatty Acid Binding Protein 3), and b) comparing the amount of the BMP 10-type peptide to a reference amount for the BMP 10-type peptide and, optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, whereby atrial fibrillation is to be assessed.

2. The method of claim 1, wherein the sample is selected from the group consisting of a blood, serum and plasma sample.

3. The method of claim 1, wherein the assessment of atrial fibrillation is the diagnosis of atrial fibrillation.

4. The method of claim 3, wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject suffering from atrial fibrillation and/or wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject not suffering from atrial fibrillation.

5. The method of claim 1, wherein the subject is suffering from atrial fibrillation, and wherein the assessment of atrial fibrillation is the differentiation between paroxysmal and persistent atrial fibrillation.

6. The method of claim 5, wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject suffering from persistent atrial fibrillation and/or wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject suffering from paroxysmal atrial fibrillation.

7. The method of claim 1, wherein the assessment of atrial fibrillation is the prediction of the risk of an adverse event associated with atrial fibrillation.

8. The method of claim 7, wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker above the reference amount is indicative for a subject who is at risk of suffering from an adverse event associated with atrial fibrillation and/or wherein an amount of the BMP 10-type peptide and, optionally, an amount of the at least one further biomarker below the reference amount is indicative for a subject who is not at risk of suffering from an adverse event associated with atrial fibrillation.

9. The method of claim 1, wherein the assessment of atrial fibrillation is the assessment of a therapy for atrial fibrillation.

10. A method of aiding in the assessment of atrial fibrillation, said method comprising the steps of: a) providing at least one sample from a subject, b) determining, in the at least one sample provided in step a), the amount of a BMP 10-type peptide (Bone Morphogenic Protein 10-type peptide) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and FABP3 (Fatty Acid Binding Protein 3), and c) providing information on the determined amount of the BMP 10-type peptide and optionally on the determined amount of the at least one further biomarker to a physician, thereby aiding in the assessment of atrial fibrillation.

11. A method for aiding in the assessment of atrial fibrillation, comprising: a) providing an assay for a BMP 10-type peptide and, optionally, at least one further assay for a further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and FABP3 (Fatty Acid Binding Protein 3), and b) providing instructions for using of the assay results obtained or obtainable by said assay(s) in the assessment of atrial fibrillation.

12. A computer-implemented method for assessing atrial fibrillation, comprising a) receiving, at a processing unit, a value for the amount of a BMP 10-type peptide, and, optionally at least one further value for the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and FABP3 (Fatty Acid Binding Protein 3), wherein said amount of the BMP 10-type peptide and, optionally, the amount of the at least one further biomarker have been determined in a sample from a subject, b) comparing, by said processing unit, the value or values received in step (a) to a reference or to references, and c) assessing atrial fibrillation based in the comparison step b).

13. A method for diagnosing heart failure, said method comprising the steps of (a) determining, in at least one sample from the subject, the amount of a BMP 10-type peptide (Bone Morphogenic Protein 10-type peptide) and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2, and FABP3 (Fatty Acid Binding Protein 3), and (b) comparing the amount of the BMP 10-type peptide to a reference amount for the BMP 10-type peptide and, optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, whereby heart failure is to be diagnosed.

14. A method for predicting the risk of a subject of hospitalization due to heart failure, said method comprising the steps of (a) determining, in at least one sample from the subject, the amount of a BMP 10-type peptide (Bone Morphogenic Protein 10-type peptide), and, optionally, the amount of at least one further biomarker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and FABP3 (Fatty Acid Binding Protein 3), (b) comparing the amount of the BMP 10-type peptide to a reference amount, and optionally, comparing the amount of the at least one further biomarker to a reference amount for said at least one further biomarker, and (c) predicting the risk of a subject of hospitalization due to heart failure.

15. A kit comprising an agent which specifically binds to a BMP 10-type peptide and at least one further agent selected from the group consisting of an agent which specifically binds to a natriuretic peptide, an agent which specifically binds to ESM-1, an agent which specifically binds Ang2 and an agent which specifically binds to FABP3.

16. In vitro use of (a) a BMP 10-type peptide, and/or (b) at least one agent that specifically binds to a BMP 10-type peptide, for predicting the risk of a subject of hospitalization due to heart failure.

17. In vitro use of i) a BMP 10-type peptide and optionally of at least one further bio marker selected from the group consisting of a natriuretic peptide, ESM-1 (Endocan), Ang2 and FABP3 (Fatty Acid Binding Protein 3), and/or ii) at least one agent that specifically binds to a BMP 10-type peptide, and, optionally, at least one further agent selected from the group consisting of an agent which specifically binds to a natriuretic peptide, an agent which specifically binds to ESM-1, an agent which specifically binds to Ang2 and an agent which specifically binds to FABP3, for assessing atrial fibrillation or for diagnosing heart failure.

18. In vitro use of claim 16, wherein the agent is an antibody, or an antigen-binding fragment thereof.

19. In vitro use of claim 18, wherein the antibody is a monoclonal antibody.

20. The method of claim 7, wherein the adverse event associated with atrial fibrillation is recurrence of atrial fibrillation and/or stroke.

Description

[0351] The figures show:

[0352] FIG. 1: Measurement of BMP10 ELISA in three patient groups (paroxysmal atrial fibrillation, persistent atrial fibrillation and patients in sinus rhythm)

[0353] FIG. 2: ROC curve for BMP10 in paroxysmal Afib; AUC=0.68

[0354] FIG. 3: ROC curve for BMP10 in persistent Afib; AUC=0.90 (Exploratory AFib panel: Patients with a history of atrial fibrillation covering 14 cases of paroxysmal AFib, 16 cases of persistent Afib and 30 Controls)

[0355] FIG. 4: BMP10 in differentiation of patients with Heart Failure and patients without heart failure [unit: ng/ml]

[0356] FIG. 5. BMP10 in differentiation of Heart Failure; ROC curve for BMP10; AUC=0.76

[0357] FIG. 6. Kaplan-Meier curve showing the risk for a HF hospitalization by quartiles of BMP-10 in patients with a prior history of heart failure.

[0358] FIG. 7. Kaplan-Meier curve showing the risk for a HF hospitalization by quartiles of BMP-10 in patients without a prior history of heart failure.

[0359] FIG. 8. Kaplan-Meier curve showing the risk for a stroke by dichotomized of BMP-10 (at median).

EXAMPLES

[0360] The invention will be merely illustrated by the following Examples. The said Examples shall, whatsoever, not be construed in a manner limiting the scope of the invention.

Example 1: Mapping Trial—Diagnose Patients with Atrial Fibrillation as Compared to Patients Based on their Different Circulating BMPO Levels

[0361] The MAPPING study related to patients undergoing open chest surgery. Samples were obtained before anesthesia and surgery. Patients were electrophysiologically characterized using high-density epicardial mapping with multi-electrode arrays (high density mapping). The trial comprised 14 patients with paroxysmal atrial fibrillation, 10 patients with persistent atrial fibrillation and 28 controls, matched to best possible (on age, gender, comorbidities). BMP10 was determined in serum samples of the MAPPING study. Elevated BMP10 levels were observed in patients with atrial fibrillation versus controls. BMP10 levels were elevated in patients with paroxysmal atrial fibrillation versus matched controls, as well as in patients with persistent atrial fibrillation versus controls.

[0362] In addition, the biomarker ESM-1 was determined in samples from the MAPPING cohort. Interestingly, it was shown that the combined determination of BMP10 with ESM-1 allowed for an increase of the AUC to 0.92 for the differentiation between persistent AF vs. SR (sinus rhythm).

[0363] In addition, the biomarker FABP-3 was determined in samples from the MAPPING cohort. Interestingly, it was shown that the combined determination of BMP10 with FABP-3 allowed for an increase of the AUC to 0.73 for the differentiation between paroxysmal AF vs. SR (sinus rhythm).

Example 2: Heart Failure Panel

[0364] The heart failure panel included 60 patients with chronic heart failure. According to the ESC guidelines criteria, heart failure was diagnosed in patients with typical signs and symptoms and objective evidence of a structural or functional abnormality of the heart at rest. Patients between 18 and 80 years with ischemic or dilated cardiomyopathy or significant valvular disease and who were able to sign the consent form were included into the study. Patients with acute myocardial infarction, pulmonary embolism or stroke in the last 6 months, further with severe pulmonary hypertension and end stage renal disease were excluded. The patients suffered predominantly from heart failure stages NYHA II-IV.

[0365] The healthy control cohort included 33 subjects. The healthy status was verified by assessing status of ECG and echocardiography results. Participants with any abnormality were excluded.

[0366] Elevated BMP10 levels were observed in serum samples of patients with heart failure versus controls.

Example 3: Biomarker Measurements

[0367] BMP10 was measured in an research grade ECLIA assay for Bone Morphogenic Protein 10 (BMP10); ECLIA Assay from Roche Diagnostics, Germany.

[0368] For detection of BMP10 in human serum and plasma samples an antibody sandwich which specifically binds to the N-terminal prosegment of BMP10 was used. Such antibodies also bind to proBMP10 and preproBMP10. Thus, the sum of the amounts of the N-terminal prosegment of BMP10, proBMP10 and preproBMP10 was determined. Structural prediction based on findings from other BMP-type proteins as e.g. BMP9 show that BMP10 remains in a complex with proBMP10, thus detection of N-term prosegement also reflects the amount of BMP10. Moreover, the homodimeric form of BMP10 can be detected, as well as heterodimeric structures, as e.g. the combination with BMP9 or other BMP-type proteins.

Example 4: The SWISS AF Study—Risk Prediction of Heart Failure Hospitalization

[0369] The data from the SWISS-AF study includes 2387 patients from which 617 have a history of heart failure (HF). BMP-10 was measured in these patients to assess its ability to predict the risk of a hospitalization due to heart failure.

[0370] As heart failure hospitalization can occur in patients with a history of heart failure and in patients without a known history heart failure the ability was assessed to predict future heart failure hospitalization was assessed in these groups independently. In total for 233 patients a hospitalization due to HF was recorded during follow-up. 125 of the 233 hospitalization occurred in patients with a prior known HF.

Prediction of HF Hospitalization in Patients with a Known History in HF

[0371] Table 1 shows the result of a cox proportional hazard model including in patients with a known history of HF. Dependent variable is the time until HF hospitalization and independent variable are log-2 the transformed BMP-10 values.

[0372] As visible by the hazard ratio and the low p-value BMP-10 is able to predict the risk for HF hospitalization significantly in patients with a known history of HF. As BMP-10 values were log-2 transformed before they were entered into the model the hazard ratio can interpreted that risk increase by 3.43 for a patient if the value of BMP-10 doubles

TABLE-US-00001 TABLE 1 Summary of cox proportional hazard model for BMP-10 (log-2 transformed) predicting the risk of HF hospitalization in patients with a known history of HF. Hazard Ratio 95% Confidence Interval P-Value 3.43 2.23-05.27 <0.001

[0373] FIG. 6 shows a Kaplan-Meier curve which displays the risk of HF hospitalization by quartiles of BMP-10. It is visible that the risk increases constantly with increasing BMP-10 values and the highest risk is observed for patients with BMP-10 levels within the highest quartile.

Prediction of HF Hospitalization in Patients without a Known History in HF

[0374] Table 2 shows the result of a cox proportional hazard model including in patients without a known history of HF. Dependent variable is the time until HF hospitalization and independent variable are the log-2 transformed BMP-10 values.

[0375] As visible by the hazard ratio and the low p-value BMP-10 is able to predict the risk for HF hospitalization significantly in patients without a known history of HF. As BMP-10 values were log-2 transformed before they were entered into the model the hazard ratio can interpreted that risk increase by 3.43 for a patient if the value of BMP-10 doubles

TABLE-US-00002 TABLE 2 Summary of cox proportional hazard model for BMP-10 (log-2 transformed) predicting the risk of HF hospitalization in patients without a known history of HF. Hazard Ratio 95% Confidence Interval P-Value 4.24 2.52-7.15 <0.001

[0376] FIG. 7 shows a Kaplan-Meier curve which displays the risk of HF hospitalization by quartiles of BMP-10. It is visible that the risk increases with increasing BMP-10 values and the risk is highest for patients with BMP-10 levels within the two highest quartiles.

Example 5: The SWISS AF Study—Risk Prediction of Stroke

[0377] The ability of circulating BMP10 to predict the risk for the occurrence of stroke was verified (in reference to example 3) in a prospective, multicentric registry of patients with documented atrial fibrillation (Conen D., Swiss Med Wkly. 2017 Jul. 10; 147:w14467). BMP10, results were available for 65 patients with an event and 2269 patients without an event.

[0378] In order to quantify the univariate prognostic value of BMP10 proportional hazard models were used with the outcome stroke.

[0379] The univariate prognostic performance of BMP10 was assessed by two different incorporations of the prognostic information given by BMP10.

[0380] The first proportional hazard model included BMP10 binarized at the median (2.2 ng/mL) and therefore comparing the risk of patients with BMP10 below or equal to the median versus patient with BMP10 above the median.

[0381] The second proportional hazard model included the original BMP10 levels but transformed to a log 2 scale. The log 2 transformation was performed in order to enable a better model calibration.

[0382] In order to get estimates for the absolute survival rates in the two groups based on the dichotomized baseline BMP10 measurement (<=2.2 ng/mL vs >2.2 ng/mL) a Kaplan-Meier plot was created.

[0383] In order to assess if the prognostic value of BMP10 is independent from known clinical and demographic risk factors a weighted proportional cox model including in addition the variables age, and history ofStroke/TIA/Thromboembolism was calculated. These were the only significant clinical risk predictors on the whole cohort (including all controls).

[0384] In order to assess the ability of BMP10 to improve existing risk scores for the prognosis of stroke the CHADS.sub.2 the CHA.sub.2DS.sub.2-VASc and the ABC score were extended by BMP10 (log 2 transformed). Extension was done by creating a portioned hazard model including BMP10 and the respective risk score as independent variables.

[0385] The c-indices of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc and ABC score were compared to the c-indices of these extended models.

Results

[0386] Table 1 shows the results of the two univariate weighted proportional hazard models including the binarized or the log 2 transformed BMP10. The association between the risk for experiencing a stroke with the baseline value of BMP10 is not significant in the model using log 2-transformed BMP10 as a risk predictor but close to the significance level of 0.05.

[0387] For the model using the binarized BMP10 the p-value is slightly higher. It could be argued however with a higher number of events the effect could be statistically significant.

[0388] The hazard ration for the binarized BMP10 implies a 1.5-fold higher risk for a stroke in the patient group with baseline BMP10>2.2 ng/mL versus the patient group with baseline BMP10<=2.2 ng/mL. This can be seen also in FIG. 8 displaying the Kaplan Meier curves for the two groups.

[0389] The results of the proportional hazard model including BMP10 as log 2 transformed linear risk predictor suggest the log 2 transformed values BMP10 are proportional to the risk for experiencing a stroke. The hazard ratio of 2.038 can be interpreted in a way that a 2-fold decrease of BMP10 is associated with 2.038 increase of risk for a stroke.

TABLE-US-00003 TABLE 1 Results result of the univariate weighted proportional hazard model including the binarized and log2 transformed BMP10. Hazard Ratio (HR) 95%-CI HR P-Value BMP10 log2 1.523 0.930-2.495 0.095 Baseline BMP10 <= 2.038 0.994-4.179 0.052 2.2 ng/mL vs BMP10 >2.2 ng/mL

[0390] Table 2 shows the results of a proportional hazard model including BMP10 (log 2 transformed) in the combination with clinical and demographic variables. It is visible that the prognostic value of BMP10 diminishes to some extend but this could be partially also being explained by low statistical power of the model.

TABLE-US-00004 TABLE 2 Multivariate proportional hazard model including BMP10 and relevant clinical and demographic variables. Hazard Ratio (HR) 95%-C1 HR P-Value Age 1.0615 1.0256-1.0987 0.0007 History 1.9186 1.1451-3.2145 0.0133 Stroke/TIA/embolism BMP10 (log2 1.2253 0.5545-2.7076 0.6155 transformed)

[0391] Table 3 shows the results of the weighted proportional hazard model combining the CHADS.sub.2 score with BMP10 (log 2 transformed). In this model BMP10 can add prognostic information to the CHADS.sub.2 score but with a p-value above 0.05 which can however be tolerated with respect to the low sample size.

TABLE-US-00005 TABLE 3 Weighted proportional hazard model combining the CHADS.sub.2 score with BMP10 (log2 transformed) Hazard Ratio (HR) 95%-C1 HR P-Value CHADS.sub.2 score 1.3792 1.1590-1.6413 0.0003 BMP10 (log2 1.5046 0.7094-3.1911 0.2869 transformed)

[0392] Table 4 shows the results of the weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with BMP10 (log 2 transformed). Also in this model BMP10 can add prognostic information to the CHA.sub.2DS.sub.2-VASc score but with a p-value above 0.05 which can however be tolerated with respect to the low sample size.

TABLE-US-00006 TABLE 4 Weighted proportional hazard model combining the CHA.sub.2DS.sub.2-VASc score with BMP10 (log2 transformed) Hazard Ratio (HR) 95%-C1 HR P-Value CHA.sub.2DS.sub.2-VASc 1.2756 1.0992-1.4803 0.1281 score BMP10 (log2 1.4308 0.6645-3.0806 0.3600 transformed)

[0393] Table 5 shows the results of the weighted proportional hazard model combining the ABC score with BMP10 (log 2 transformed). In this model the estimated hazard ratio diminishes and BMP-10 likely can't add any prognostic performance

TABLE-US-00007 TABLE 5 Weighted proportional hazard model combining the ABC score with BMP10 (log2 transformed) Hazard Ratio (HR) 95%-C1 HR P-Value ABC score 1.1839 1.1046-1.2688 <0.0001 BMP10 (log2 0.7321 0.3123-1.7161   0.4731 transformed)

[0394] Table 6 shows the estimated c-indexes of BMP10 alone, of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score and of the weighted proportional hazard model combining the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score with BMP10 (log 2) on the case cohort selection. It can be seen that the addition of BMP10 improves the c-index of the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc score but not the ABC score.

[0395] The differences in c-index are 0.019, 0.015 and −0.002 for the CHADS.sub.2, the CHA.sub.2DS.sub.2-VASc, the ABC score respectively.

TABLE-US-00008 TABLE 6 C-indexes of BMP10, the CHA.sub.2DS.sub.2-VASc score and the combination of the CHA.sub.2DS.sub.2-VASc score with BMP10 and C-indexes of the CHADS.sub.2 and ABC score and their combination with BMP10. C-Index BMP10 univariate 0.577 CHADS.sub.2 0.629 CHADS.sub.2 + BMP10 0.643 CHA.sub.2DS.sub.2-VASc 0.616 CHA.sub.2DS.sub.2-VASc + BMP10 0.627 ABC score 0.692 ABC score + BMP10 0.690