Relationships Between Biomarkers and Left Ventricular Filling Pressures at Rest and During Exercise in Patients After Myocardial Infarction

Accepted Manuscript

Relationships between biomarkers and left ventricular filling pressures at rest andduring exercise in patients after myocardial infarction

Mads J. Andersen, MD, PhD Mads Ersbøll, MD, PhD John Bro-Jeppesen, MD, PhDJacob E. Møller, MD, PhD, DMSc Christian Hassager, MD, DMSc Lars Køber, MD,DMSc Barry A. Borlaug, MD Jens P. Goetze, MD, DMSc Finn Gustafsson, MD, PhD,DMSc

PII: S1071-9164(14)01222-6

DOI: 10.1016/j.cardfail.2014.09.012

Reference: YJCAF 3416

To appear in: Journal of Cardiac Failure

Received Date: 23 May 2014

Revised Date: 19 September 2014

Accepted Date: 29 September 2014

Please cite this article as: Andersen MJ, Ersbøll M, Bro-Jeppesen J, Møller JE, Hassager C, KøberL, Borlaug BA, Goetze JP, Gustafsson F, Relationships between biomarkers and left ventricular fillingpressures at rest and during exercise in patients after myocardial infarction, Journal of Cardiac Failure(2014), doi: 10.1016/j.cardfail.2014.09.012.

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Relationships between biomarkers and left ventricular

filling pressures at rest and during exercise in patients

after myocardial infarction

Authors

Mads J Andersen, MD, PhD1,2; Mads Ersbøll, MD, PhD1; John Bro-Jeppesen, MD,

PhD1; Jacob E Møller, MD, PhD, DMSc1; Christian Hassager, MD, DMSc1;

Lars Køber, MD, DMSc1; Barry A. Borlaug, MD2;

Jens P Goetze, MD, DMSc3; Finn Gustafsson, MD, PhD, DMSc1

1Department of Cardiology, the Heart Centre, Rigshospitalet & University of Copenhagen,

Denmark; 2Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic,

Rochester, Minnesota; 3Department of Biochemistry, Rigshospitalet & University of Aarhus,

Denmark

Address for correspondence:

Mads J Andersen, MD, Ph.D.

Mayo Clinic College of Medicine

200 First Street SW

Rochester, MN 55905

E-mail: [email protected]

Word count: Abstract 215, total excluding figure legends and references: 3364

Key words: Acute myocardial infarction; Hemodynamics; Exercise testing; Biomarkers

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Abstract Background: Increased pulmonary capillary wedge pressure (PCWP) is an independent

prognostic predictor following myocardial infarction (MI), but is difficult to assess

noninvasively in subjects with preserved ejection fraction (EF). We hypothesized that

biomarkers would provide information regarding PCWP at rest and during exercise in

subjects with preserved EF following MI.

Methods: 74 subjects with EF > 45 % and recent MI underwent right heart catheterization at

rest, during a symptom limited semi-supine cycle exercise test with simultaneous

echocardiography. Plasma samples were collected at rest for assessment of mid-range pro-

atrial natriuretic peptide (MR-proANP), NT pro-natriuretic peptide (NT-proBNP), galectin-3

(Gal-3), copeptin and MR pro- adrenomedullin (MR-proADM).

Results: Plasma levels of MR-proANP and PCWP were associated at rest (r=0.33; p=0.002),

peak exercise (r=0.35; p=0.002) and with changes in PCWP (r=0.23; p=0.03). Plasma levels of

NT-proBNP and PCWP were weakly associated at rest (r=0.23; p=0.03) and at peak exercise

(r=0.26; p=0.02) but not with changes in PCWP r=0.16; p=0.09). In a multivariable analysis

plasma levels of MR-proANP remained associated with rest/exercise PCWP (p<0.01), while

NT-proBNP did not. Plasma levels of Gal-3, copeptin or MR-proADM were not associated with

PCWP at rest or peak exercise.

Conclusion: In subjects recovering from an acute MI with preserved EF, plasma levels of

natriuretic peptides, in particular MR-proANP, are associated with filling pressures at rest and

during exercise.

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Introduction Increased filling pressures independently predict outcome following myocardial

infarction (MI).(1, 2) However, invasive hemodynamic testing is expensive and carries risk of

complications. When left ventricular (LV) ejection fraction (LVEF) is preserved (>45%) non-

invasive demonstration of elevated filling pressure is particularly challenging. Recent

recommendations suggest using the quotient of peak early mitral inflow velocity (E) and peak

early diastolic tissue Doppler velocity in the mitral annulus (e’) which have showed modest

association with invasive obtained filling pressure in most studies(3, 4) but not all.(5)

European guidelines suggest that filling pressures are increased when E/e’ is above 15.(6)

Accordingly studies have demonstrated that echocardiographic indices suggestive of

increased LV filling pressure and pulmonary hypertension are associated with worse outcome

following MI,(7-11), but ~ 25% of subjects with preserved LVEF following MI have E/e’ values

in the intermediate range (8-15) where the association with filling pressure is less clear.(12,

13)

Subjects with heart failure and preserved ejection fraction (HFpEF) (14) and post

MI subjects with preserved LVEF and diastolic dysfunction (13, 15) are prone to elevation in

pulmonary capillary wedge pressure (PCWP) during exercise in relation to limitations in LV

diastolic reserve, but identifying these vulnerable subjects requires invasive assessment. The

ability to non-invasively identify subjects with compromised resting or exercise

hemodynamics has gained increasing interest due to development of experimental therapies

aiming at reducing LV filling pressures.(14, 16)

Natriuretic peptides (N-terminal pro-B-type natriuretic peptide, NT-proBNP;

mid-regional pro-A-type natriuretic peptide, MR-proANP) are released in response to

increases in wall stress (17, 18), but little is known about these correlations with filling

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pressures during exercise. In addition, other candidate biomarkers have been related to filling

pressures, including galectin-3, copeptin and mid-regional proadrenomedullin (MR-proADM),

but comparative data with directly-measured filling pressures is lacking. We hypothesized

that plasma concentrations of these biomarkers would identify subjects with increased filling

pressures at rest or during exercise in post MI subjects with preserved LVEF.

Methods Study design and patient population

We enrolled 80 post MI subjects with preserved LVEF (> 45 %) who all

underwent right heart catheterization at rest and during symptom limited semi-supine cycle

exercise test with simultaneous echocardiography. Inclusion criteria were preserved LVEF

and written informed consent. Subjects with permanent atrial fibrillation, known history of

cardiomyopathy, more than mild valvular heart disease (>mild stenosis or regurgitation),

obstructive or restrictive pulmonary disease and inability to perform exercise testing were

excluded. The majority (70) were post MI subjects with echocardiographic signs of diastolic

dysfunction (E/e’ > 8 and LA > 32ml/m2; MI+DD) and 10 post MI subjects had normal

diastolic function as judged by echocardiography (E/e’ < 8 and LA < 32 ml/m2; MI-DD).

Hemodynamic and echocardiographic data for these subjects has been previously published

(12, 15). Subjects were studied on chronic medications in the fasted state. The subjects were

stratified in a binary fashion using peak exercise PCWP > 25 mmHg as cutoff for abnormal

filling pressure with exercise.(14) The ethics committee in Region Hovedstaden approved the

study and written informed consent was obtained from all subjects.

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Invasive hemodynamic measurements

Right heart catheterization was performed using a standard 7.5-F triple lumen

Swan-Ganz thermistor and balloon-tipped catheter (Edwards Lifesciences, Irvine, California,

USA). The catheter was introduced guided by ultrasound into the right internal jugular vein

and advanced to the pulmonary artery. PCWP, right atrial pressure (RAP), systolic pulmonary

artery pressure (PAP), diastolic PAP, mean PAP, blood pressure (BP) and cardiac output (CO,

thermodilution technique) were measured at rest, at each level of exercise until exhaustion,

and after 5 min of rest. PCWP at rest and post exercise was measured at end-expiration.

During exercise a mean PCWP was used. We considered resting PCWP>15 mmHg and/or

exercise PCWP > 25 mmHg to be abnormally increased.(14)

Exercise protocol

Subjects performed a multistage symptom-limited semi supine cycle exercise test

using an Echo Cardiac Stress Table (Lode B.V., the Netherlands). Workload started at 0 watts

and was increased by 25 watts every 2 min. Subjects were encouraged to maintain a fixed

pedaling speed of 60 RPM for the duration of the exercise. They were also encouraged to

exercise until exhaustion (Borg >18).

Echocardiography

All subjects underwent resting echocardiographic examinations obtained

according to current guidelines.(19, 20) During exercise 2-dimensional (2D), tissue Doppler

images (TDI) and pulsed - and continuous wave Doppler images were acquired in the apical 4

chamber view. All examinations were performed by an experienced echocardiographer using

a Philips iE33 (Philips Healthcare, Best, the Netherlands) cardiac ultrasound system.

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Echocardiographic cine loops were obtained by recording a minimum of 3 consecutive heart

cycles. Images were stored digitally for offline analysis using Philips Xcelera analysis software

version 3.1 (Philips Healthcare, Best, the Netherlands).

LV volumes and LVEF were assessed using Simpson’s biplane method of discs

from the apical 4 and 2 chamber views at rest. LA volume was measured from the apical 4-

and 2-chamber views using Area-Length method at rest. Volumes were indexed to body

surface area (BSA) when appropriate. Using pulsed wave (PW) Doppler E velocities were

measured with the sample volume placed at the tips of mitral leaflets during diastole. Using

TDI and PW Doppler with the sample volume placed in the septal and lateral mitral annulus e’

velocities were measured and averaged.(4)

For Doppler recordings horizontal sweep was of 75 or 100 mm/s and 3-5

consecutive beats were used and averaged. All analyses were performed blinded to

hemodynamic and biomarker values.

Biomarkers

Plasma samples were collected at rest from the internal jugular vein after

positioning of the Swan-Ganz catheter prior to exercise. Plasma and serum were collected in

EDTA primed glass tubes, centrifuged for 10 minutes at 3,000 rpm and stored at −80°C until

analysis. Samples underwent ≤2 freeze/thaw cycles before analysis. NT-proBNP was

measured on the Modular E platform (Roche Diagnostics) with lower limit of detection (LOD)

at 25 pg/ml and interassay coefficient of variation (CV) of 12.6% at 29.2 pg/ml and 9.6% at

8.5 pg/ml.(21) Plasma concentrations of Copeptin were measured on the automated Kryptor

Plus platform (Thermo-Fischer, Waltham, MA, USA). The interassay CVs were 18.3% for 1.4

pmol/L, 6.8% for 9.3 pmol/L, and less than 3% for concentrations >18 pmol/L.(22) The

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automated Kryptor Plus platform was also used to quantify the plasma levels of MR-proADM

(LOD of 0.08 nmol/L and CV was <20% for values >0.12nmol/L) and MR-proANP (LOD of the

assay is 6.0 pmol/L and CV was 10%). (22-24) Galectin-3 was measured on a VIDAS platform

(Biomérieux, Denmark) with a LOD of 1.13 ng/ml and interassay CV < 10.4%.(25)

Statistical analysis

Data are presented as mean ± standard deviation (SD) for Gaussian distributed

or median (interquartile range, IQR) for non-Gaussian distributed variables unless otherwise

indicated. Between group differences were tested using Student's t-test, χ2 or non-parametric

rank sum test where appropriate. Multivariable analysis was performed in a general linear

model and included resting values of LA volume indexed to BSA, E/e’, age and LVEF as

covariates. All biomarkers were log- transformed and PCWP > 25 mmHg at peak exercise and

> 15 mmHg at rest were used as binary cutoffs to create a logistic regression models.

Predictive capability was assessed by comparing C-statistics derived from the area under the

receiver operating characteristic (ROC) curves using the method proposed by deLong et

al.(26) The C-statistics were then compared using a paired t-test. All tests were two-sided, a

P-value < 0.05 was considered significant, and the explained variation of the general linear

model was derived from the global R2 value. Statistical analyses were performed using R

version 3.0.1 (R Development Core Team 2013, http://www.R-project.org/. library: Hmisc,

psych, pROC).

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Results Of 80 subjects enrolled, six subjects (all MI+DD) were excluded due to missing

blood samples. Thus the total study population consisted of 74 subjects (mean age 62 ± 8

years, 86.5% male) with a recent myocardial infarction (31 days (IQR; 23-43 days) prior to

catheterization. Baseline characteristics and demographics are presented in table 1.

Compared to subject with exercise PCWP > 25 mmHg, subjects with exercise PCWP ≤ 25

mmHg had lower use of beta blockers, lower levels of natriuretic peptides, better diastolic

function but similar LVEF and plasma levels of copeptin, MR-proADM and Galectin-3

compared to subjects with exercise PCWP > 25 mmHg. The use of beta blockers was not

associated with increased filling pressure in a logistic regression analysis.

Hemodynamic response to exercise is presented in table 2. All subjects in both

groups exercised to exhaustion (>18 Borg scale) and all significantly increased lactate levels

from rest to peak exercise. During exercise no subjects complained of chest pain, no

significant ischemia was noted on the ECG nor was any regional wall motion abnormality

observed on the simultaneous echocardiography. The hemodynamic response to exercise and

workload achieved were similar in subjects with abnormal and normal exercise PCWP except

for right-sided and PA pressures (table 2).

MR-proANP

The median MR-proANP plasmal levels were significantly higher in MI+DD

compared to MI-DD (136 IQR: 93-188 vs 89 IQR: 65-120, p=0.01). Even larger differences

were seen when comparing subjects with normal and elevated PCWP at peak exercise (Table

1) where the MR-proANP plasma levels in subjects with normal PCWP were 68% (CI 53 –

87%) of the MR-proANP plasma levels of subjects with increased PCWP at peak exercise.

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There was a moderate but significant association between MR-proANP and PCWP at rest

(r=0.33; p=0.002), at peak exercise (r=0.35; p=0.002) and with the changes in PCWP from

baseline to peak exercise (r=0.23; p=0.03, Figure 1). Similar association was found between

MR-proANP and E/e’ (r=0.37; p=0.0008) and MR-proANP and LA volume index (r=0.41;

p=0.0002).

There was a significant association between MR-proANP and PCWP in the

multivariable analysis at rest (r=0.60; p=0.003, entire model), at peak exercise (r =0.39,

p=0.04, entire model) but not between changes in MR-proANP and PCWP. Interestingly, MR-

proANP was the only significant variable at peak exercise, superior to echocardiographic

variables (LVEF p=0.71; E/e’ p=0.07, LAvoli p=0.27) and age (p=0.28).

A receiver operating characteristic (ROC) analysis of the ability of MR-proANP to

predict elevated PCWP was evaluated by ROC curve analysis and revealed an area under the

curve (AUC) of 0.78 (CI 0.65 – 0.90) at rest and 0.73 (CI 0.60-0.87) at peak exercise (Figure 2).

Resting MR-proANP levels >140 pmol/L predicted high peak exercise PCWP with 43%

sensitivity and 88% specificity and levels <90 pmol/L predicted peak exercise PCWP ≤ 25

mmHg with 78% sensitivity and 44% specificity.

NT-proBNP

The median NT-proBNP concentration was significantly higher in MI+DD

compared to MI-DD (59 IQR: 29-99 vs 27 IQR: 12-32, p=0.02). However opposed to MR-

proANP plasma levels of NT-proBNP did not differ between subjects with peak PCWP ≤ 25

mmHg and PCWP > 25 mmHg (Table 1). The NT-proBNP plasma levels in subjects with

normal filling pressure were on average 63% (CI 35 – 112%) of the plasma levels in subjects

with elevated filling pressure at peak exercise. Despite, no significant differences between

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groups, a weak association between NT-proBNP and PCWP was found at rest (r=0.22; p=0.03)

and at peak exercise (r=0.25; p=0.02) but not between changes in PCWP from baseline to peak

exercise (p=0.09) Figure 3. In a multivariable analysis NT-proBNP was no longer associated

with PCWP at rest (p=0.39) or at peak exercise (p=0.29).

In a ROC analysis of the ability of NT-proBNP to predict elevated PCWP we found

an AUC of 0.70 (0.55-0.86) at rest and 0.64 (0.47-0.82) at peak exercise (figure 4). Despite

poorer AUC there were no significant differences between MR-proANP and NT-proBNP as

predictors of elevated PCWP at rest (0.78 vs 0.70; p=0.24) or with peak exercise (0.73 vs 0.64;

p=0.40).

Copeptin

The median copeptin concentration was significantly higher in subjects with

MI+DD compared to MI-DD (6.4 IQR: 4.4-15.5 vs 3.8 IQR: 3.1-5.3 pmol/l; p=0.03). This seems

unrelated to filling pressure as plasma levels of copeptin did not significantly differ between

subjects with peak PCWP ≤ 25 mmHg and peak PCWP > 25 mmHg (Table 1). The copeptin

plasma levels in subjects with normal filling pressure were on average 73% (CI 49-109%) of

the plasma levels in subjects with elevated filling pressure at peak exercise. There was no

association between copeptin and PCWP at rest (p=0.88), at peak exercise (p=0.24) or with

changes in PCWP (p=0.22).

MR-proADM

The median MR-proADM concentration did not differ between subjects with

MI+DD and MI-DD (p=0.11); similarly plasma concentrations did not differ between subjects

with peak PCWP ≤ 25 mmHg and peak PCWP > 25 mmHg (Table 1). The MR-proADM plasma

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levels in subjects with normal filling pressure on average were 102% (CI 90% - 116%) of the

plasma levels in subjects with elevated filling pressure at peak exercise. There was no

association between plasma levels of MR-proADM and PCWP at rest (p=0.25), at peak exercise

(p=0.59) or with changes in PCWP (p=0.88).

Galectin-3

The median Gal-3 concentration did not differ between subjects with MI+DD and

MI-DD (p=0.09) similarly there was no difference between subjects with peak PCWP ≤ 25

mmHg and peak PCWP > 25 mmHg (Table 1). The average Gal-3 plasma levels in subjects with

normal filling pressure were 119% (CI 97% - 147%) of the plasma levels in subjects with

elevated filling pressure at peak exercise. There was no association between plasma levels of

Gal-3 and PCWP at rest (p=0.62), peak exercise (p=0.18) or with changes in PCWP (p=0.11).

Discussion This is, to our knowledge, the first study to report associations or lack of

association between MR-proANP, NT-proBNP, Gal-3, copeptin or MR-proADM and LV filling

pressure at rest and during exercise in humans. We found that resting plasma levels of

natriuretic peptides – in particular MR-proANP– were associated with PCWP both at rest and

at peak exercise in subjects with preserved LVEF post myocardial infarction, whereas

copeptin, galectin-3 and pro-adrenomedullin were not predictive of PCWP.

The increase in filling pressure is abrupt and abnormal even with minimal effort

in post MI subjects with diastolic dysfunction and in subjects suffering from HFpEF. (14, 15)

The natriuretic peptides are secreted by cardiomyocytes in response to elevated wall tension,

which varies directly with PCWP and chamber dimension.(17, 18) Prior studies have shown

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tight correlations between diastolic wall stress and natriuretic peptide levels at rest.(18) As

the majority of time is spent under some form of physical exercise, filling pressure would be

elevated accordingly increasing wall stress. However, it has remained unclear how well

natriuretic peptide levels might reflect PCWP during exercise. We show that natriuretic

peptide plasma levels apart from the association with resting PCWP are reflective of peak

exercise PCWP that MR-proANP is associated with changes in PCWP and that MR-proANP is

the more robust marker as compared to NT-proBNP.

The fact that MR-proANP is a more robust marker of elevated filling pressure

compared to NT-proBNP could be explained by differences in location of secretion of the

natriuretic peptides as MR-proANP is believed to be secreted primarily from the atria and NT-

proBNP primarily from the ventricles. The relative steeper and more rapid exercise induced

increase in atrial pressures in patients with elevated filling pressures could explain the better

association between MR-proANP and PCWP. Similarly, the relative increase in mean blood

pressure did not differ between groups thus explaining the lesser association between NT-

proBNP as only the LA pressures would differ between groups.

While correlations are significant, the AUC indicates that natriuretic peptide

levels may be less helpful in the intermediate range. MR-proANP levels >140 pmol/L were

indicative of high PCWP with exercise, but although the specificity was high (88%) the

sensitivity was low (<50%) which limits the ability of MR-proANP as a sole marker for

increased filling pressure.

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The lack of association between filling pressures and Galectin-3, Copeptin and MR-

proADM

In recent studies Gal-3 has been related to mortality in patients with acute and

chronic HF and has also been proposed as a novel marker of HFpEF.(27) Galectin is thought to

play an important role in cardiac fibrosis and since cardiac fibrosis is an important

contributor to the pathophysiology of diastolic dysfunction, we hypothesized that the marker

would identify subjects with elevated filling pressure. However, this hypothesis was rejected

by the data. One possible explanation might be that the subjects in the present study had a

recently suffered from a MI, where remodeling with development of scar tissue (fibrosis)

might not be completed. Furthermore, fibrosis is not the sole contributing factor to LV

diastolic dysfunction.

Mid-regional prohormone adrenomedullin (MR-proADM) is another notable

biomarker in HF. MR-proADM is increased in hypertension, chronic renal disease and chronic

HF(28) and has been shown to be an independent predictor of all-cause mortality in stable

outpatients with stage A-D HF.(29) Concurrent with this evidence we found a higher level of

MR-proADM in subjects with MI+DD. Although when comparing MR-proADM levels with peak

exercise PCWP we did not find any association with resting or peak exercise PCWP.

Copeptin, a novel biomarker of arginine vasopressin, has antidiuretic properties

and is a potent vasoconstrictor.(30) Given, the known association between filling pressures

and outcome in HF and the fact that vasopressin blockade in acute HF reduces dyspnea,

lowers PCWP, (31)we speculated that copeptin might be associated with filling pressures.

This hypothesis could not be confirmed in the current study population with early stage heart

failure although this does not preclude an association in more advanced HF.

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There are several perspectives of the current study. Randomized clinical drug

trials in HFpEF have generally not been able to show any beneficial effects of the tested drug

on morbidity and mortality in HFpEF.(32-36) While lack of efficacy of the tested interventions

may be a likely explanation, the inability to identify and select the optimal candidates for

therapy might also contribute. Most therapies in one way or another have targeted the

common denominator in HFpEF – the elevated filling pressure (at rest or during exercise) –

but most studies did not include measurement of these parameters for practical reasons.

Hence biomarkers that could provide reliable information regarding filling pressure and help

identifying suitable candidates for therapeutic interventions, would be of considerable clinical

significance. The current study suggests that MR-proANP deserves greater study in this

context.

Limitations:

The small sample size increases the risk of a type II error nevertheless the

present study is to our knowledge the largest study to assess the association between

biomarkers and exercise hemodynamics in subjects with ischemic heart disease and

preserved LVEF. Furthermore this limitation does not affect the main result of the study that

natriuretic peptides are associated with filling pressure and that MR-proANP is superior to

NT-proBNP.

Acknowledging the skewed inclusion of MI-DD and MI+DD subjects we sought to

reclassify subjects, by applying a physiological approach, according to their filling pressure at

peak exercise in order to have a more even distribution between groups. Despite being

selected in two groups we pooled all data to increase the strength of the data. Although, all

subjects were examined using the same protocol one should always be careful when

interpreting the results of pooled data due to selection bias and the occurrence of spurious

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correlation. We cannot safely state that the significant association between natriuretic

peptides and filling pressure is not partly caused by a spurious correlation.

Due to some variation in time from myocardial infarction to enrollment we

cannot safely state that this did not affect the results. However 32 MI+DD subjects enrolled in

the SIDAMI trial(13) as placebo group had the exact same invasive hemodynamic exercise test

including biomarker sampling performed after 9 weeks of treatment. In those 32 subjects

receiving placebo NT-proBNP and Copeptin decreased significantly while Galectin-3 increased

whereas MR-proANP and MR-proADM did not change significantly over 9 weeks

(supplementary table 1). Furthermore the decrease was significant the absolute changes over

63 days were small therefore the variation in time from MI to enrollment would not

significantly affect the overall results of the present study.

Conclusion: In subjects recovering from an acute myocardial infarction with preserved

ejection fraction, plasma levels of natriuretic peptides, in particular MR-proANP, reflect the

filling pressures of the left ventricle at rest and with exercise. In contrast, no association

between filling pressures (rest or exercise) and copeptin, Galectin-3 or MR-proADM was

found. Further studies are required to determine if MR-proANP might be a useful non-

invasive marker to identify subjects with elevated filling pressures, which potentially could

have important implications for identification and selection of subjects for novel treatments.

Disclosures: Nothing to disclose.

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Figure Legend:

Figure 1

Plot of correlation between log10(MR-proANP (pmol/L)) and pulmonary capillary wedge

pressure (mmHg) at rest (A) at peak exercise (B) and changes from rest to peak exercise (C).

Subjects with myocardial infarction and no diastolic dysfunction (MI-DD, blue squares), and

subjects with myocardial infarction with diastolic dysfunction (MI+DD, red circles). Reported

p-value is testing for association between MR-proANP plasma levels and PCWP by linear

regression. Y is slope of the regression line.

Figure 2

Univariate logistic models of the ability to predict elevated filling pressure with receiver

operating characteristic (ROC) curves and C-statistics at rest (A) and at peak exercise (B) for

MR-proANP the shaded area represents 95% CI.

Figure 3

Plot of correlation between log10(NT-proBNP (pmol/L and pulmonary capillary wedge

pressure (mmHg) at rest (A) at peak exercise (B) and changes from rest to peak exercise (C).

Subjects with myocardial infarction without diastolic dysfunction (MI-DD, blue squares), and

subjects with myocardial infarction with diastolic dysfunction (MI+DD, red circles). Reported

p-value is testing for association between NT-proBNP plasma levels and PCWP by linear

regression. Y is slope of the regression line.

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Figure 4

Univariate logistic models of the ability to predict elevated filling pressure with receiver

operating characteristic (ROC) curves and C-statistics at rest (A) and at peak exercise (B) for

NT-proBNP the shaded area represents 95% CI.

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Figur 1

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Figure 2

ROC curve (Area) = 0.78(CI 0.65-0.90) ROC curve (Area) = 0.73 (CI 0.60-0.87)

A) Rest B) Peak Exercise

MR-proANP

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Figure 3

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Figure 4

ROC curve (Area) = 0.70 (CI 0.55-0.86) ROC curve (Area) = 0.64 (CI 0.47-0.82)

A) Rest B) Peak Exercise

NT-proBNP

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Highlights

• Invasive hemodynamic exercise approach and biomarkers in post MI patients

• 74 post MI with LVEF >45%

• No association with filling pressures and Copeptin, MR-proADM or Galectin-3

• Natriuretic peptides were associated with resting, exercise and changes in PCWP

• MR-proANP was superior to NT-proBNP

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BSA = Body Surface Area; MI, = myocardial infarction; DD=diastolic dysfunction; eGFR = estimated

glomerular filtration rate; ACE/ARB = angiotensin converting enzyme/aldosterone receptor blocker; NT-

proBNP = N-terminal pro-B-type natriuretic peptide; MR-proANP = mid regional pro-A-type natriuretic

peptide; MR-proADM = mid-regional pro-adrenomedullin; LVEF = left ventricular ejection fraction; LAVOLi =

left atrial volume indexed to body surface area; E/e’ = ratio of peak early mitral inflow velocity to peak early

diastolic tissue velocity. P-value calculated by unpaired t-test or non-parametric test where appropriate.

Table 1. Baseline Demographic, Clinical Characteristics and Cardiovascular Parameters for the total study population

and stratified according to peak exercise PCWP

Total

N=74

PCPW ≤ 25 mmHg

N=17

PCWP > 25 mmHg

N=57

P-value

Age, years 62±8 61±10 62±8 0.48

Male, (%) 64(86%) 16(94%) 48(84%) 0.29

BSA, (m2) 2.03±0.22 2.08±0.2 2.02±0.22 0.32

Comorbidities

MI+DD, n (%) 64(86%) 11(65%) 53(93%) 0.008

Hypertension, n (%) 31(42%) 6(35%) 25(34%) 0.75

NYHA > II, n (%) 0 (0%) 0 (0%) 0 (0%) 0.99

Diabetes, n (%) 6(8%) 0 6(11%) 0.38

eGFR, (ml/min/1.73 m2) 88±24 87±28 88±23 0.87

Ex- or Current smokers, n (%) 46(62%) 11(65%) 35(61%) 0.95

Medication

Diuretics, n (%) 4(5%) 1(6%) 3(5%) 0.92

Beta-blockers, n (%) 64(86%) 12(71%) 52(91%) 0.03

ACEI/ARB, n (%) 20(27%) 2(12%) 18(32) 0.11

Statin, n (%) 73(99%) 16(94%) 57(100%) 0.07

Biomarkers

NT-proBNP, (pmol/l) 51.9(27.9-91.8) 29.4(15.4-71.9) 57.5(29.1-91.8) 0.09

MR-proANP, (pmol/l) 131.9(89.4-165.2) 94.8 (70.0-127.1) 137.8(94.9-192.0) 0.003

Galectin-3, (pmol/l) 11.2(9.6-12.9) 11.8(11.2-14.2) 11.0(8.7-12.7) 0.09

MR-proADM, (pmol/l) 0.55(0.48-0.62) 0.56(0.47-0.62) 0.55(0.49-0.62) 0.92

Copeptin, (pmol/l) 5.6(3.8-10.2) 4.7(3.3-7.1) 6.2(4.5-10.4) 0.13

Echocardiographic

LVEF, (%) 56±6 55±6 56±6 0.46

LAVOLi, (ml/m2) 41±12 36±10 43±12 0.03

E/e’ 10.4±2.8 9.1±3.6 10.8±2.5 0.03

Diastolic dysfunction, n (%) 64(86%) 11(65%) 53(93%) 0.003

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ACCEPTED MANUSCRIPTTable 2. Hemodynamic Characteristics at rest and at peak exercise

PCPW ≤ 25 mmHg

N=17

PCWP > 25 mmHg

N=57

P-value

Resting

CO, (L/min) 5.2±1.4 5.3±1.2 0.78

RAP, (mmHg) 5±2 7±2 0.05

PCWP, (mmHg) 10±2 12±3 0.02

mPAP, (mmHg) 16±2 19±4 0.003

mBP, (mmHg) 89±10 91±11 0.58

HR, (b.p.m.) 61±9 61±10 0.85

LVEF (%) 55±6 56±6 0.46

E/e’ 9.1±3.6 10.8±2.5 0.03

Lactate, (mmol/L) 0.93±0.34 0.92±0.41 0.91

Peak Exercise

CO, (L/min) 15.7±3.7 15.4±3.7 0.81

RAP, (mmHg) 7±4 15±5 <0.0001

PCWP, (mmHg) 21±5 35±6 <0.0001

mPAP, (mmHg) 33±6 48±8 <0.0001

mBP, (mmHg) 116±14 117±16 0.77

HR, (b.p.m.) 125±18 126±17 0.9

LVEF (%) 60±6 60±7 0.77

E/e’ 8.0±3.6 9.6±2.4 0.04

Lactate, (mmol/L) 8.09±2.44 8.25±2.80 0.83

Peak work load, (Watt) 137±41 132±40 0.70

CI = Cardiac Index; RAP= Right atrial pressure; PCWP = Pulmonary capillary wedge pressure; mPAP = Mean

pulmonary arterial pressure; mBP, mean arterial blood pressure; H.R., Heart rate.

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Supplementary Table 1. For changes in baseline to follow-up nine weeks later for 32 MI+DD

patients enrolled in the SIDAMI trial as placebo group.

Baseline Follow-up P-value

Biomarkers

NT-proBNP, (pmol/l) 48.2(27.9-100.0) 34.3(16.6-42.9) <0.0001

MR-proANP, (pmol/l) 145.3(96.9-194.2) 135.6(112.9-154.4) 0.07

Galectin-3, (pmol/l) 11.4(10.6-13.1) 12.1(11.1-14.1) 0.03

MR-proADM, (pmol/l) 0.61(0.52-0.68) 0.56(0.52-0.65) 0.61

Copeptin, (pmol/l) 6.4(5.2-11.7) 4.9(4.0-7.3) 0.01

Supplementary Table 1

MI+DD, myocardial infarction and diastolic dysfunction; p-value calculated with paired Wilcoxon Signed Rank

test.