CLINICAL RESEARCH
European Heart Journal (2014) 35, 2106–2114
doi:10.1093/eurheartj/ehu151
Coronary artery disease
Assessment of microRNAs in patients with
unstable angina pectoris
Tanja Zeller 1,2†, Till Keller 1,3†‡, Francisco Ojeda 1, Tobias Reichlin 4,5,
Raphael Twerenbold4,5, Stergios Tzikas 6}, Philipp S Wild 3,6,7, Miriam Reiter 4,5,
Ewa Czyz6, Karl J Lackner 3,8, Thomas Munzel 3,6, Christian Mueller 4,5‡,
and Stefan Blankenberg 1,2*
1
Department of General and Interventional Cardiology, University Heart Center Hamburg, Martinistr. 52, 20246 Hamburg, Germany; 2German Center for Cardiovascular Research
(DZHK), Partner Site Hamburg, Lübeck, Kiel, Hamburg, Germany; 3German Center for Cardiovascular Research (DZHK), Partner Site Rhein-Main, Mainz, Germany; 4Department of
Internal Medicine, University Hospital, Basel, Switzerland; 5Department of Cardiology, University Hospital, Basel, Switzerland; 6Department of Medicine II, University Medical Center,
Johannes Gutenberg University Mainz, Mainz, Germany; 7Clinical Epidemiology, Center for Thrombosis and Haemostasis, University Medical Center Mainz, Langenbeckstraße
1, 55131 Mainz, Germany; and 8Department of Laboratory Medicine, University Medical Center, Johannes Gutenberg University Mainz, Germany
Received 18 January 2013; revised 8 February 2014; accepted 18 March 2014; online publish-ahead-of-print 11 April 2014
Aims
While cardiac troponin measurements have significantly improved the early diagnosis of myocardial infarction, the timely
biomarker-based diagnosis of unstable angina pectoris (UAP) remains a major unmet clinical challenge. The aim of this
study was to assess levels of circulating microRNAs (miRNAs) as possible novel biomarkers in patients with UAP.
.....................................................................................................................................................................................
Methods
A three-phase approach was conducted, comprising (i) profiling of miRNAs in patients with UAP and controls groups;
and results
(ii) replication of significant miRNAs in an independent patient cohort, (iii) validation of a multi-miRNAs panel in a third
cohort. Out of 25 miRNAs selected for replication, 8 miRNAs remained significantly associated with UAP. In a validation
phase, a miRNA panel including miR-132, miR-150, and miR-186 showed the highest discriminatory power [area under
the receiver-operating-characteristic curve (AUC): 0.91; CI: 0.84– 0.98].
.....................................................................................................................................................................................
Conclusion
Using a profiling-replication-validation model, we identified eight miRNAs, which may facilitate the diagnosis of UAP.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Circulating microRNA † Myocardial infarction † Unstable angina pectoris † Acute myocardial infarction †
Diagnosis
Introduction
Acute coronary syndrome comprises two entities: acute myocardial
infarction (AMI) and unstable angina pectoris (UAP). Their rapid and
accurate diagnosis is critical for the initiation of effective evidencebased medical management and treatment but is still an unmet clinical
need. Delayed ‘rule-in’ increases morbidity and mortality. Delayed
‘rule-out’ prolongs the time spent in the emergency department,
delays the recognition and treatment of the actual cause of chest
pain, increases patients’ uncertainty and anxiety, and causes costs
for the health care system.
MicroRNAs (miRNAs) are endogenous, small non-coding RNAs
involved in the regulation of gene expression.1 They control expression on a posttranscriptional level as intracellular RNAs and are discussed as therapeutic targets.2 MicroRNAs are involved in the
pathogenesis of various cardiovascular conditions such as angiogenesis, hypertrophy, heart failure, and fibrosis.2 – 4 Recent studies
revealed that miRNAs are reliably detected as cell-free RNAs in circulating blood and other body fluids. Because of their stability,
miRNAs may serve as novel disease biomarkers.3,5,6 Several studies
suggested an involvement of cardiomyocyte-enriched miRNAs
(miR-1, miR133a, miR-133b, miR-208a, miR-208b, and miR-499) in
* Corresponding author. Tel: +49 40 7410 53972; Fax: +49 40 7410 53622, Email: [email protected]
†
These authors contribute equally.
Present address: Division of Cardiology, Department of Medicine III, Goethe University Frankfurt, Theodor Stern Kai 7, Frankfurt 60590, Germany.
}
Present address: Department of Cardiology, Ruhr University Bochum, Marienhospital Herne, Herne, Germany.
‡
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2014. For permissions please email: [email protected]
2107
Assessment of microRNAs in patients with UAP
cardiac injury and myocardial infarction,4,7 – 12 others highlighted
the potential of circulating miRNAs as diagnostic and prognostic
biomarkers in AMI.12 – 14
While sensitive cardiac troponin assays have significantly improved
the early diagnosis of AMI,15 – 18 the early diagnosis of UAP remains a
major unmet clinical challenge. None of the currently available biomarkers seems to provide clinically useful information. We therefore
assessed levels of circulating miRNAs as possible novel biomarkers in
patients with UAP and explored their diagnostic value.
Methods
Overall study concept and study flow
Selection of samples
The overall study concept consisted of an initial profiling phase of
miRNAs in patients with UAP compared with two different control
groups, (i) a replication phase and (ii) a subsequent validation phase
(Figure 1). For the profiling phase, UAP patients were selected from the
stenoCardia study; controls were selected from the stenoCardia study
(control group 1) and the population-based Gutenberg Health Study
(GHS) (control group 2), respectively. The selection was performed as
a ‘case– control’ approach with unstable angina patients considered as
cases and non-coronary chest pain patients (NCCP) as control group 1.
Patients were randomly selected from an overall pool of n ¼ 240 UAP
patients and n ¼ 1165 NCCP patients of the stenoCardia study.16 Randomization was done using standard spreadsheet software functions
blinded to any patient characteristics or laboratory results without
further stratification after patients selection based on the stringent criteria for UAP and NCCP outlined below. Supplementary material
online, Table S1 places the study characteristics of the selected UAP
and NCCP patients into the context of the overall stenoCardia
cohort’s characteristics. For NCCP, patients without angiographically
proven coronary artery disease (CAD) had been preselected. The comparison between the 10 NCCP profiling patients (see below) and the preselected NCCP cohort is provided in Supplementary material online,
Table S1.
A second case– control approach was applied selecting control group
2 from the population-based Gutenberg Health Study (GHS). Here,
healthy controls were age- and sex-matched to the UAP patients. The
R statistical software was used to perform the matching.
Definition of unstable angina, non-coronary chest pain,
and acute myocardial infarction
Unstable angina patients had been adjudicated by two independent cardiologists as having unstable angina if they (i) presented with typical clinical symptoms of chest pain, (ii) the electrocardiogram did not show
ST-segment elevations or new left bundle block, and (iii) the coronary
angiography revealed a culprit lesion with the need for intervention in
at least one major coronary artery. (iv) Cardiac troponin I (TnI)
assayed by a contemporary-sensitivity test (TnI-Ultra, Siemens Healthcare Diagnostics, Germany) never exceeded the 99th percentile
(0.04 ng/mL) at baseline, 3- or 6-h blood draw (troponin-negative).
Patients with a history of aortocoronary bypass surgery were excluded.
Criteria for NCCP individuals had been presentation with chest pain,
never exceeding the 99th percentile of the contemporary sensitive troponin I ultra (0.04 ng/mL) during hospital stay and—most importantly—
having an angiographically proven exclusion of any coronary stenosis (profiling phase). Additional criteria for this group were normal renal function
(creatinine ,1.3 mg/dL) and no alternative cardiac diagnosis explaining the
symptoms. Often, a clear alternative cause of chest pain such as pleuritis,
pneumonia, or musculoskeletal pain was identified in these patients.
Acute myocardial infarction was defined by electrocardiographic
changes indicative of new ischaemia (new ST-T segment changes or
new left bundle branch block) and elevated TnI-Ultra with a clear rising
or falling pattern according to the Universal Definition of Myocardial
Infarction.19,20
Study phases
Profiling phase
The miRNA profiling phase served as hypothesis generating phase. This
phase consisted of 40 individuals: 10 diagnosed with UAP, 10 with
NCCP, and 20 healthy, population-based controls. The phenotype ‘unstable angina’ had been selected carefully according to the definitions
described above. In the profiling phase, 667 human miRNAs were
tested and out of those, 25 were selected to enter phase 2, the replication
phase.
Replication phase
Figure 1 Study design. The present study was conducted in three
phases: (i) an initial miRNA profiling phase including patients diagnosed with UAP compared with non-coronary chest pain
(NCCP) patients and healthy controls (HC), (ii) a replication
phase of selected miRNAs in UAP and NCCP patients from an independent study cohort, and (iii) a validation phase. UAP, unstable
angina pectoris; NCCP, non-coronary chest pain; HC, healthy controls; STEMI, ST elevation myocardial infarction. stenoCardia, study
for evaluation of newly onset chest pain and rapid diagnosis of myocardial necrosis; APACE, Advantageous Predictors of Acute Coronary Syndromes Evaluation study.
Patients for the replication phase had been taken from an independent
study cohort, the APACE study (description see below). We selected
49 patients classified as UAP and 48 as NCCP. The selection process
had been identical to that described for the profiling phase. Most importantly, the same troponin I test (TnI-Ultra, 99th percentile at 0.04 ng/mL)
had been applied and all patients classified as UAP or NCCP had been an
angiographically proven diagnosis of either culprit lesion (UAP) or exclusion of CAD (NCCP). Out of the 25 miRNAs replicated in this phase, 8
entered the validation phase.
Validation phase
The validation phase tested the diagnostic potential of the selected eight
miRNAs for the diagnosis UAP, their kinetics over time, and their
2108
behaviour in individuals presenting with AMI. From the stenoCardia study,
46 patients had been selected with the diagnosis UAP, 63 patients with
NCCP, both as defined above.
To directly test the kinetics of the eight miRNAs over time in response
to myocyte necrosis in 29 AMI patients, we selected the baseline and 6 h
blood draw.
T. Zeller et al.
Park, USA) with a measuring range of 0.005 – 10 mg/dL. The assay measuring range was 10 –5000 pg/mL. Inter-assay CV was 3.96%, and
intra-assay CV was 2.25%.
Lipid values and C-reactive protein had been determined using routine
methods.
Isolation of circulating RNA from serum
Underlying study populations used for sample selection
Study for evaluation of newly onset chest pain and rapid diagnosis
of myocardial necrosis (stenoCardia)
Patients with acute chest pain presenting consecutively at the chest pain
unit of the Johannes Gutenberg-University Medical Centre Mainz
between January 2007 and December 2008 were enrolled in this allcomers prospective biomarker assessment registry as described
earlier.15,16,21 Blood samples were obtained on admission and after 3
and 6 h. Routine laboratory parameters including C-reactive protein
were measured immediately after blood withdrawal by standardized
methods. Additionally, EDTA plasma and serum samples were collected
at each time point, centrifuged, aliquoted, and stored at 2808C. The
study was approved by the local ethics committees. Participation was
voluntary; each patient gave written, informed consent.
Advantageous predictors of Acute Coronary Syndromes Evaluation
study (APACE)
Consecutive patients who presented to the emergency department with
symptoms suggestive of AMI between April 2006 and June 2009 were enrolled in this prospective, international, multi-centre study as described
previously.17 Blood samples were collected in serum or EDTA plasma
tubes at the time of presentation and additional samples were obtained
1, 2, 3, and 6 h after presentation. Samples were centrifuged and aliquots
were stored at 2808C. The study was approved by the local ethics committee and each patient gave written informed consent.
Gutenberg Health Study (GHS)
Apparently healthy individuals of the Rhine-Main area in Germany were
enrolled in this ongoing community-based, prospective, observational
single-centre cohort study as described earlier.22,23 Participants were
selected from the local registry offices. Individuals between 35 and 74
years of age were eligible to participate in the study. The study protocol
and sample drawing have been approved by the local ethics committee
and each participant gave written informed consent.
Measurement of protein-based biomarkers
In both the stenoCardia and the APACE study, cardiac troponin I using a
commercially available contemporary-sensitivity assay (TnI-Ultra,
ADVIA Centaur XP system, Siemens Healthcare Diagnostics, Germany)
was used to establish the diagnosis ‘unstable angina’. The assay detection
limit was 0.006 ng/mL, the assay range was 0.006–50 ng/mL, and 10% coefficient of variation (CV) was at 0.03 ng/mL. This cardiac TnI-Ultra test
detects troponin in 20% of the general population.
We determined troponin I in the study samples using a high-sensitivity
cardiac troponin I (hsTnI) assay (STAT high sensitive Troponin, Abbott
Diagnostics, Abbott Park, USA, ARCHITECT i2000SR). The established
limit of detection (LoD) for the assay is 1.9 pg/mL with an assay range
between 0 and 50.000 pg/mL. This assay detects troponin I concentrations
in 90% of the general population and was used as a troponin test to be
compared against the diagnostic capability of the 3-miRNA panel.
B-type natriuretic peptide (BNP) was measured in EDTA plasma using
the ARCHITECT i2000SR BNP assay (Abbott Diagnostics, Abbott Park,
USA). The assay measuring range was 10 – 5000 pg/mL. Inter-assay CV
was 5.96%, and intra-assay CV was 4.67%. Cystatin C was measured by
the ARCHITECT c8000 Cystatin C assay (Abbott Diagnostics, Abbott
Circulating cell-free RNA was isolated from frozen serum samples. The
maximum storage time of the samples at 2808C was 5 years. Briefly, 3
volumes of TRIzol (Invitrogen) were mixed with 1 volume of serum
and incubated for 5 min at room temperature to ensure complete dissociation of nucleoprotein complexes. Chloroform was added, and the
mixture was shaken vigorously. After 5 min at room temperature, the
mixture was centrifuged at 14 000g and 48C for 15 min. The upper
aqueous phase was transferred to a fresh reagent tube and 1.5 volumes
of ethanol were added. Purification of RNA was performed with the miRNeasy kit (Qiagen) according to the manufactures’ recommendations.
RNA was eluted in 30 mL RNAse-free H2O. For normalization, serum
samples were supplemented with 10 nM Caenorhabditis elegans miR-39
(cel-miR-39) after addition of TRIzol as previously described.3,24
Detection of circulating microRNA
For miRNA profiling, total RNA from serum was analysed using the lowdensity TaqMan Array Human MicroRNA A + B Cards Set v2.0 (Applied
Biosystems) according to the manufacturer’s protocol. This array card set
contains a total of 384 TaqMan miRNA assays per card and enables assaying of 667 specific human microRNA. Briefly, RNA was reversely transcribed to cDNA with MegaPlex RT primers (MegaPlex RT Primer
Pool, Applied Biosystems) followed by a pre-amplification step using
MegaPlex PreAmp Primer Pool Set v2.0 (Applied Biosystems). Subsequently, real-time PCR amplification of miRNAs using low-density
TaqMan Arrays was performed on an Applied Biosystem 7900 HT
system using SDS software v2.3. For validation of miRNAs and miR-39
spike-in, single miRNA assays (Applied Biosystems) were used for
miRNA detection.
Statistical analysis
Cycle threshold (Ct) values were normalized to cel-miR-39 by the
formula 22(Ct[miRNA] – Ct[cel2miRNA239]) for Ct , 40 and 2240 in the
case Ct ≥ 40 (considered as undetermined). Difference in miRNA
levels groups was tested by the Mann– Whitney test, the Wilcoxon
signed-rank test, or the Skillings – Mack test as appropriate. As a
measure of effect strength and direction when using the Mann–
Whitney test, the area under the receiver operating characteristic
(ROC) curve was computed.25
Selected miRNAs (n ¼ 8) from the profiling and replication phases, together with the biomarkers hsTnI, BNP, C-reactive protein, and Cystatin
C were examined in the validation phase with respect to the diagnosis of
UAP. For these analyses, the average of the normalized miRNA values
measured on admission and at 6 h was used. Combinations of miRNAs
and/or biomarker were obtained via logistic regression. In the biomarker
combination principal component analysis was used to reduce the
number of covariates used in the model. The miRNA combination was
produced using logistic regression with variable selection via the elastic
net.26 Receiver operating characteristic curves and areas under the
curve (AUCs) were computed. All biomarkers levels were used after a
logarithmic transformation.
A pooled analysis using a random effects model was performed with
the selected eight miRNAs. As before, the average of the normalized
miRNA values measured on admission and at 6 h was used. The studies
combined were APACE (replication phase) and stenoCardia (validation
2109
Assessment of microRNAs in patients with UAP
phase). All statistical testing was two-tailed, and P-values ,0.05 were
considered statistically significant. All statistical analyses were performed
using R 2.14.2 (http://www.r-project.org/).
Results
Profiling of circulating microRNAs in
unstable angina pectoris patients
Table 1 provides baseline characteristics of the study cohorts. To determine miRNAs in acute myocardial ischaemia without evident necrosis (¼ UAP), we compared levels of 667 circulating miRNAs in
serum samples of patients adjudicated to have UAP to NCCP
patients and healthy controls. The level of various circulating
miRNAs differed profoundly and several miRNAs showed significant
changes in UAP patients (Supplementary material online, Table S2).
Primarily, most miRNA levels were lower in patients with UAP,
19.5% of all miRNAs showed lower levels in UAP patients compared
with NCCP (26.5% compared with healthy controls). Circulating
levels of miRNAs with known cardiac relevance (miR-1, miR-208a,
and miR-208b) did not differ in UAP patients at the time of admission.
Of note, levels of miR-208b were mainly undetectable in UAP
patients and controls at the time of admission (Ct ≥ 40), whereas
miR-208a and miR-1 were detectable but showed no significant difference between patients and controls.
Replication of circulating microRNA in
patients adjudicated to have unstable
angina pectoris
For replication, 25 miRNAs were selected based on their association
with UAP in the initial profiling phase (P ≤ 0.05 for association). In
addition, we included miRNAs miR-1, miR-208a, and miR-208b
based on their potential role as biomarkers for AMI,3,11,27 although
Table 1
these miRNAs showed no significant difference between UAP
patients and controls in our initial profiling phase. The 28 miRNAs
were forwarded into the replication phase and circulating miRNA
levels were determined in an independent study cohort (APACE).
The results of the profiling and replication phases of these 28
miRNAs are presented in Table 2. Eight miRNAs showed significantly
differential levels in UAP patients in both the profiling and replication
phase and were selected for the validation phase. Those miRNAs
included miR-19a, miR-19b, miR-132, miR-140-3p, miR-142-5p,
miR-150, miR-186, and miR-210.
Validation of circulating microRNAs
To further explore the applicability of circulating miRNAs as potential diagnostic biomarkers of UAP in troponin-negative patients, subsequent ROC analyses were performed in samples of the validation
phase (n ¼ 46 UAP, n ¼ 63 NCCP). First, AUCs were calculated
for the eight selected miRNAs individually. Of all miRNAs, miR-186
showed the highest AUC (0.78; CI: 0.67 –0.88) (Table 3). In a next
step, we selected a ‘miRNA panel’ of the most discriminatory
miRNAs out of the eight selected miRNAs. A panel of three
miRNAs including miR-132, miR-150, and miR-186 showed the
highest AUC (0.91; CI: 0.84 –0.98), thus improving the AUC compared with that of miR-186 alone. If the high-sensitivity assayed
troponin I (hsTnI) was applied in this validation phase detecting concentrations above the LoD of 1.9 pg/mL in nearly 100% of the study
participants, an AUC of 0.57 (CI:0.44– 0.70) was achieved for the
diagnosis of unstable angina. Even combing the four markers hsTnI,
BNP, C-reactive protein, and Cystatin C did not improve the diagnostic sensitivity substantially [AUC: 0.63 (CI: 0.5 –0.76) (Figure 2)]. Thus,
the highest diagnostic accuracy for unstable angina was achieved by
applying the 3-miRNA combination of miR-132, miR-150, and
miR-186.
Characteristics of the study populations
Characteristics
stenoCardia/GHS (profiling)
.......................................................
UAP
NCCP
HC
APACE (replication)
stenoCardia (validation)
UAP
UAP
...................................
NCCP
.................................
NCCP
...............................................................................................................................................................................
No. of patients
10
10
20
48
47
46
63
Age (years)
Male gender (%)
65.3 + 12
6 (60)
60.6 + 14.2
5 (50)
60.5 + 10.3
11 (55)
65.6 + 11.4
34 (71)
62.4 + 14.6
32 (68)
65.5 + 10.1
32 (70)
61.8 + 10
38 (60)
Hypertension (%)
9 (90)
8 (80)
8 (40)
33 (69)
27 (57)
34 (74)
42 (67)
Body mass index (kg/m2)
Diabetes mellitus (%)
26.8 + 3.7
1 (10)
26.5 + 3.9
2 (20)
25.9 + 4.2
1 (5)
25.7 + 3.9
10 (21)
27.6 + 4.7
6 (13)
27.8 + 3.4
12 (26)
28.1 + 5.4
7 (11)
Current smoker (%)
Former smoker (%)
1 (10)
7 (70)
3 (30)
5 (50)
3 (15)
11 (55)
9 (19)
21 (43)
7 (15)
17 (36.2)
9 (20)
17 (37)
13 (21)
15 (25)
Known CAD (%)
CPO (chest pain onset)
4 (44)
2.59
0 (0)
3.87
0 (0)
24 (50)
6
20 (43)
10
20 (45)
5.44
0 (0)
4.28
time (h)
(1.9/13.6)
(2.6/6.8)
–
(3/12)
(2.2/27.3)
(2.0/20.7)
(2.1/10.3)
Smoking status
...............................................................................................................................................................................
Data are summarized by either mean + standard deviation or 50th (25th/75th) percentiles for continuous variables and n (%) for binary variables. UAP, unstable angina pectoris;
HC, healthy controls; NCCP, non-cardiac chest pain; stenoCardia, study for evaluation of newly onset chest pain and rapid diagnosis of myocardial necrosis; APACE: Advantageous
Predictors of Acute Coronary Syndromes Evaluation study, GHS: Gutenberg Health Study.
2110
T. Zeller et al.
Table 2 Results of the profiling and replication phase of circulating microRNAs in patients with unstable angina pectoris,
chest pain of non-coronary cause, and healthy controls
miRNA
Profiling stenoCardia (UAP vs. NCCP)
P-value (AUC)
Profiling stenoCardia (UAP vs. HC)
P-value (AUC)
Replication APACE (UAP vs. NCCP)
P-value (AUC)
...............................................................................................................................................................................
let-7b
0.023 (0.2)
0.019 (0.24)
0.06 (0.39)
miR-1
miR-7-1*
0.14 (0.30)
0.009 (0.16)
0.12 (0.32)
0.004 (0.18)
0.07 (0.61)
0.3 (0.44)
miR-10a
0.007 (0.15)
0.12 (0.32)
0.35 (0.44)
miR-17
miR-19a
0.019 (0.19)
0.019 (0.19)
0.015 (0.23)
0.01 (0.21)
0.28 (0.44)
0.003 (0.33)
miR-19b
0.029 (0.21)
0.013 (0.22)
0.003 (0.33)
miR-20a
miR-92a
0.015 (0.18)
0.011 (0.17)
0.1 (0.31)
0.31 (0.38)
0.025 (0.37)
0.13 (0.41)
miR-100
0.015 (0.18)
0.68 (0.45)
0.021 (0.36)
miR-126
miR-132
0.029 (0.21)
0.011 (0.17)
0.024 (0.25)
0.011 (0.22)
0.28 (0.44)
0.005 (0.33)
miR-134
0.011 (0.16)
0.007 (0.19)
miR-140-3p
miR-142-5p
0.029 (0.21)
0.035 (0.22)
0.011 (0.22)
0.013 (0.22)
NA
0.002 (0.32)
0.001 (0.31)
miR-145
0.019 (0.14)
0.07 (0.29)
0.14 (0.41)
miR-150
miR-186
0.015 (0.18)
0.035 (0.22)
0.013 (0.22)
0.015 (0.23)
1.2 3 1026 (0.22)
0.007 (0.34)
miR-204
0.005 (0.12)
0.008 (0.20)
0.13 (0.41)
miR-208a
miR-208b
0.33 (0.37)
1 (0.50)
0.14 (0.33)
0.49 (0.43)
0.039 (0.38)
0.11 (0.42)
miR-210
0.014 (0.17)
0.04 (0.27)
2.2 3 1024 (0.28)
miR-339-5p
miR-375
0.23 (0.35)
0.023 (0.16)
0.002 (0.14)
0.049 (0.28)
0.009 (0.66)
0.16 (0.42)
miR-551b*
0.017 (0.79)
0.77 (0.54)
2.5 × 1027 (0.79)
0.37 (0.62)
0.006 (0.15)
3.2 × 10 (0.03)
0.003 (0.16)
0.27 (0.43)
0.09 (0.4)
0.1 (0.31)
9.5 × 1025 (0.06)
0.21 (0.43)
miR-580
miR-629
miR-768-3p
25
The profiling phase was performed in patients diagnosed with unstable angina pectoris (UAP, n ¼ 10) compared with non-coronary chest pain (n ¼ 10, NCCP) patients and healthy
controls (n ¼ 10, HC) at the time of admission to the chest pain unit. Twenty-eight miRNAs were selected for replication based on a P-value ≤ 0.05. Replication was performed in UAP
patients (n ¼ 49) and NCCP controls (n ¼ 48) in an independent study cohort (APACE). miR-1, miR-208, and miR-208b were selected for further analyses based on potential role as
biomarkers for acute myocardial infarction described in the literature. miRNAs shown in bold denote miRNAs for which levels were significantly different (P-value ≤ 0.05) in all
profiling and replication phases and which were selected for further analyses. AUC: area under the receiver operating characteristic (ROC) curve, gives direction of the miRNA level
(.0.5 ¼ higher in UAP, ,0.5 ¼ lower in UAP compared with controls). NA indicates ‘not available’ due to Ct values ,40 in both groups.
Kinetic profiling and Influence of
ST-elevation myocardial infarction on
validated microRNAs identified in unstable
angina pectoris
We further addressed the kinetic profiling and the impact of transmural
myocardial necrosis on the eight selected miRNAs. For kinetic profiling, we determined circulating levels of the eight validated miRNAs in
UAP patients of the validation study sample collected at the time of
admission and after 6 h. We found profoundly decreased levels of
miR-140-3p and miR-186 in serum of UAP patients 6 h after admission,
whereas levels of the remaining six miRNAs did not change considerably (Figure 3). Additionally, miRNAs with known cardiac relevance
(miR-1, miR-208a, miR208b) showed no significant change in abundance between time of admission and after 6 h in UAP patients.
As it is known that miRNAs are released from the cells under conditions of myocardial necrosis, we also addressed the impact of transmural myocardial necrosis on levels of the eight miRNAs in 29 STEMI
patients and 63 NCCP controls and compared miRNA levels on admission, after 3 h and after 6 h. Levels of miR-19b, miR-132, miR-186,
and miR-210 showed a profound increase within 6 h, whereas circulating miR-140-3p slightly decreased (Supplementary material online,
Figure S1). As expected, levels of miR-1, miR-208a, and miR-208b
showed significant increase in their abundance in STEMI patients
within 6 h after admission.
Discussion
Recent studies revealed that miRNAs are implicated in the pathogenesis of various cardiovascular conditions.1 – 4 Accumulating evidence
2111
Assessment of microRNAs in patients with UAP
Table 3
Validation of selected circulating microRNAs
miRNA
AUC (95% CI)
miR-19a
0.44 (0.32– 0.56)
miR-19b
miR-132
0.42 (0.30– 0.54)
0.43 (0.30– 0.55)
miR-140-3p
0.48 (0.35– 0.60)
miR-142-5p
miR-150
0.46 (0.33– 0.58)
0.41 (0.29– 0.54)
miR-186
0.78 (0.67– 0.88)
miR-210
0.43 (0.31– 0.55)
................................................................................
miRNAs selected from the profiling and replication phases were further validated in
n ¼ 46 UAP patients and n ¼ NCCP controls of the stenoCardia study. CI,
confidence interval. AUC, area under the receiver operating characteristic curve.
AUC ,0.5 indicates miRNA levels in patients with UAP lower than in controls,
AUC .0.5 indicates miRNA levels in patients with UAP higher than in controls.
Figure 2 Discriminatory power of the 3-miRNA panel. Receiver
operator characteristic (ROC) curves and area under the ROC
curve (AUC) are given for the 3-miRNA panel compared with
troponin I measured by a high-sensitivity assay (hsTnI) and a
model including hsTnI, B-type natriuretic peptide (BNP), C-reactive
protein, and Cystatin C (4-marker combination). The 3-miRNA
panel includes the miRNAs miR-132, miR-150, and miR-186.
suggest a potential role for miRNAs as efficient diagnostic tools in the
evaluation of patients with suspected acute coronary syndrome.12,13,28 In the present study, we provide evidence for the potential use of circulating miRNAs as a diagnostic tool in patients with
UAP. We profiled and replicated levels of circulating miRNAs as possible novel biomarkers for the early diagnosis of UAP. We report
three major findings: first, eight miRNAs were significantly associated
with UAP in both the profiling and the replication cohort. Most of
these miRNAs had lower levels in UAP than in control patients.
Second, of all single miRNAs miR-186 showed the highest
discriminatory power and had moderate accuracy in the early diagnosis of UAP. Third, the discriminatory power of a panel of three
miRNAs (miR-132, -150, and -186) was highest, with an AUC of
0.91 (CI: 0.84– 0.98), suggesting that a multi-miRNA approach provides more clinically useful information compared with single
miRNAs. Of particular importance, in our study the diagnosis UAP
had been confirmed by coronary angiography with at least one
culprit coronary lesion, accompanied by typical clinical symptoms
of chest pain, electrocardiogram without ST-elevations or new left
bundle block, and negative troponin I measured by a contemporarysensitivity assay in serial measurements up to 6 h after admission.
Recently published studies suggest a role in cardiovascular conditions for most of the miRNAs related to UAP in our study: dysregulation of miR-150 under conditions of hypoxia and an upregulation of
miR-186, miR-210, and miR-150 in myocardial infarction had been
reported.29 Likewise, a crucial cardiac role has also been implicated
for mirR-210 in the endothelial cell response to hypoxia.30
miR-19a and -19b are members of the miR-19-92 cluster;31 a
recent study showed the relation of decreased miR-19a and
miR-19b expression with age-related remodelling in the heart32 supporting a role of these miRNAs during cardiac aging and heart failure.
However, conflicting results regarding the regulation (up/downregulation) of miRNA levels are currently available in the literature and
need to be investigated further.
In our study, levels of known cardiac-enriched miRNAs miR-1,
miR-208a, and miR-208b after serial measurements were not different in UAP patients, but showed increased levels in STEMI patients,
indicating different pathophysiological mechanisms of miRNA
release during ischaemia and necrosis events. These observations
are in line with results of a recently published study,12 showing
higher miR-1 and miR-208b levels in patients with STEMI and
NSTEMI than in UAP patients.
From a clinical perspective, a biomarker-based diagnosis of UAP is
highly relevant to improve the differential diagnosis of chest pain.
Aortic dissection, peri-/myocarditis and pulmonary embolism are
the main differential diagnostic aspects in patients presenting with
severe chest pain. To date, no specific biomarker diagnosis is available
to facilitate differential diagnosis in these clinical conditions. Therefore, a miRNA panel which leads to the assumption that chest pain
derives from coronary causes even in the absence of troponin elevation is of immediate clinical interest.
Several limitations of our study merit consideration. Because of the
relatively small profiling sample size some miRNAs relevant for UAP
diagnosis might not have been detected, although an overestimation
of identified miRNAs should be minimized by our multiple phases approach. Further to this, the observed miRNA differences between
UAP cases and controls might simply represent the prevalence of
CAD. However, as NCCP controls of the replication phase included
CAD cases, and the UAP case selection was strictly related to the
prevalence of a culprit lesion (in half of the cases even without underlying severe CAD), the observed miRNA differences should mainly
be driven by the phenotype UAP. Thus, an appropriate sampling
design to ensure representation of the population of interest needs
to be implemented in future studies; our results are a first step in
that process. Second, we also acknowledge that we did not provide
other diagnostic performance characteristics than AUC values
such as sensitivity/specificity and predictive values for our
2112
T. Zeller et al.
Figure 3 Kinetic profiles of circulating miRNA on admission (0 h) and 6 h after admission in patients diagnosed with UAP. miRNA levels were
categorized as undetermined, low, and high depending on their abundance. The categories were defined using the 2log2(Ct miRNA 2 Ct
cel-miR-39) values as follows: undetermined: Ct values ¼ 240; low abundance: Ct values . 240 and ≤ median of miRNA values at time 0 h;
high abundance: Ct values . 240 and . median of miRNA values at time 0 h.
3-miRNA panel. Due to the small sample size, we were not able to
compute stable cut-offs for theses test performance measures.
Thus, a replication of our findings in a larger samples size and the
evaluation of the concept of clinical application and usefulness of
the 3-miRNA panel in a prospective ‘real-world clinical setting’
needs to be further evaluated.
From a laboratory view, C. elegans miR-39 had been used for normalization of miRNA data in our study. Using other ‘housekeeping’
miRNAs or small RNAs as recently discussed24,33,34 might result in
differently normalized data and thus might have an influence on the
results. Finally, the methodology of RT-PCR used in this study does
not allow an easy and rapid application in a clinical setting. However,
further development of semi-automated protocols might overcome
this limitation in the future.
In conclusion, using a profiling-replication-validation model, we
were able to identify miRNAs, which when used in a multi-miRNA
panel seem to provide clinically useful information for the early diagnosis of UAP.
Supplementary material
Supplementary material is available at European Heart Journal online.
Assessment of microRNAs in patients with UAP
Acknowledgements
We thank the patients who participated in the studies, the staff of the
emergency departments and central laboratories for all their efforts.
Especially, we thank Beate Stradmann and Katharina Perius for their
excellent technical assistance.
Funding
This work was supported by the research programs ‘Wissen schafft
Zukunft’, ‘Schwerpunkt Vaskulaere Praevention’ and ‘MAIFOR 2010’ of
the Medical University Center Mainz for the stenoCardia study as well
as funding by the European Union Seventh Framework Programme
(FP7/2007– 13) under grant agreement No. HEALTH-F2-2011-278913
(BiomarCaRE). In addition, funding was provided by unrestricted grants
of the Brahms AG and Abbott Diagnostics. The APACE study was supported by research grants from Swiss National Science Foundation,
Swiss Heart Foundation, the Department of Internal Medicine, University
Hospital Basel, the University Basel, Abbott, Brahms, Roche, and
Siemens. The Gutenberg Health Study is funded through the government
of Rheinland-Pfalz (No. AZ 961-386261/733), the research program
‘Wissen schafft Zukunft’ and the ‘Schwerpunkt Vaskuläre Prävention’
of the University Medical Center Mainz and its contract with Boehringer
Ingelheim and PHILIPS medical systems, including an unrestricted grant
for the Gutenberg Health Study. This project was further supported by
the MAIFOR program of the University Medical Center Mainz and the
National Genome Network ‘NGFNplus’ by the federal Ministry of Education and Research, Germany (No. 01GS0833 and 01GS0831, projects
A3/D1).
Conflict of interest: Abbott Diagnostics provided test reagents
for high-sensitive troponin I determinations within the frame of the
stenoCardia Study. S.B. has received honoraria from Abbott Diagnostics,
Siemens, Brahms/Thermo Fisher, and Roche Diagnostics and is a consultant for Thermo Fisher. C.M. received research grants from Abbott,
Brahms, Nanoshere, Roche and Siemens, consulting fees from Abbott,
and lecture fees from Abbott, Biosite, Brahms, Roche and Siemens. All
other co-authors report no conflict of interest.
References
1. van Rooij E. The art of microRNA research. Circ Res 2011;108:219 –234.
2. Small EM, Frost RJ, Olson EN. MicroRNAs add a new dimension to cardiovascular
disease. Circulation 2010;121:1022 –1032.
3. Fichtlscherer S, De Rosa S, Fox H, Schwietz T, Fischer A, Liebetrau C, Weber M,
Hamm CW, Roxe T, Muller-Ardogan M, Bonauer A, Zeiher AM, Dimmeler S. Circulating microRNAs in patients with coronary artery disease. Circ Res 2010;107:
677 –684.
4. Corsten MF, Dennert R, Jochems S, Kuznetsova T, Devaux Y, Hofstra L, Wagner DR,
Staessen JA, Heymans S, Schroen B. Circulating MicroRNA-208b and
MicroRNA-499 reflect myocardial damage in cardiovascular disease. Circ Cardiovasc
Genet 2010;3:499–506.
5. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL,
Peterson A, Noteboom J, O’Briant KC, Allen A, Lin DW, Urban N,
Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS,
Martin DB, Tewari M. Circulating microRNAs as stable blood-based markers for
cancer detection. Proc Natl Acad Sci USA 2008;105:10513 –10518.
6. Gupta SK, Bang C, Thum T. Circulating microRNAs as biomarkers and potential paracrine mediators of cardiovascular disease. Circ Cardiovasc Genet 2010;3:484–488.
7. D’Alessandra Y, Devanna P, Limana F, Straino S, Di Carlo A, Brambilla PG, Rubino M,
Carena MC, Spazzafumo L, De Simone M, Micheli B, Biglioli P, Achilli F, Martelli F,
Maggiolini S, Marenzi G, Pompilio G, Capogrossi MC. Circulating microRNAs are
new and sensitive biomarkers of myocardial infarction. Eur Heart J 2010;31:
2765– 2773.
8. Ai J, Zhang R, Li Y, Pu J, Lu Y, Jiao J, Li K, Yu B, Li Z, Wang R, Wang L, Li Q, Wang N,
Shan H, Yang B. Circulating microRNA-1 as a potential novel biomarker for acute
myocardial infarction. Biochem Biophys Res Commun 2009;391:73 –77.
2113
9. Bostjancic E, Zidar N, Stajer D, Glavac D. MicroRNAs miR-1, miR-133a, miR-133b
and miR-208 are dysregulated in human myocardial infarction. Cardiology 2009;
115:163–169.
10. Adachi T, Nakanishi M, Otsuka Y, Nishimura K, Hirokawa G, Goto Y, Nonogi H,
Iwai N. Plasma microRNA 499 as a biomarker of acute myocardial infarction. Clin
Chem 2010;56:1183 –1185.
11. Wang GK, Zhu JQ, Zhang JT, Li Q, Li Y, He J, Qin YW, Jing Q. Circulating microRNA: a
novel potential biomarker for early diagnosis of acute myocardial infarction in
humans. Eur Heart J 2010;31:659–666.
12. Widera C, Gupta SK, Lorenzen JM, Bang C, Bauersachs J, Bethmann K, Kempf T,
Wollert KC, Thum T. Diagnostic and prognostic impact of six circulating microRNAs
in acute coronary syndrome. J Mol Cell Cardiol 2011;51:872 – 875.
13. Meder B, Keller A, Vogel B, Haas J, Sedaghat-Hamedani F, Kayvanpour E, Just S,
Borries A, Rudloff J, Leidinger P, MEese E, Katus HA, Rottbauer W. MicroRNA signatures in total peripheral blood as novel biomarkers for acute myocardial infarction.
Basic Res Cardiol 2011;106:13–23.
14. Zampetaki A, Willeit P, Tilling L, Drozdov I, Prokopi M, Renard JM, Mayr A, Weger S,
Schett G, Shah A, Boulanger CM, Willeit J, Chowienczyk PJ, Kiechl S, Mayr M. Prospective study on circulating MicroRNAs and risk of myocardial infarction. J Am
Coll Cardiol 2012;60:290 – 299.
15. Keller T, Zeller T, Ojeda F, Tzikas S, Lillpopp L, Sinning C, Wild P, Genth-Zotz S,
Warnholtz A, Giannitsis E, Mockel M, Bickel C, Peetz D, Lackner K, Baldus S,
Munzel T, Blankenberg S. Serial changes in highly sensitive troponin I assay and
early diagnosis of myocardial infarction. JAMA 2011;306:2684 –2693.
16. Keller T, Zeller T, Peetz D, Tzikas S, Roth A, Czyz E, Bickel C, Baldus S, Warnholtz A,
Frohlich M, Sinning CR, Eleftheriadis MS, Wild PS, Schnabel RB, Lubos E, Jachmann N,
Genth-Zotz S, Post F, Nicaud V, Tiret L, Lackner KJ, Munzel TF, Blankenberg S. Sensitive troponin I assay in early diagnosis of acute myocardial infarction. N Engl J Med
2009;361:868 –877.
17. Reichlin T, Hochholzer W, Bassetti S, Steuer S, Stelzig C, Hartwiger S, Biedert S,
Schaub N, Buerge C, Potocki M, Noveanu M, Breidthardt T, Twerenbold R,
Winkler K, Bingisser R, Mueller C. Early diagnosis of myocardial infarction with sensitive cardiac troponin assays. N Engl J Med 2009;361:858 –867.
18. Mills NL, Churchhouse AM, Lee KK, Anand A, Gamble D, Shah AS, Shah AS,
Paterson E, MacLeod M, Graham C, Walker S, Denvir MA, Fox KA, Newby DE. Implementation of a sensitive troponin I assay and risk of recurrent myocardial infarction and death in patients with suspected acute coronary syndrome. JAMA 2011;305:
1210 –1216.
19. Thygesen K, Alpert JS, White HD, Jaffe AS, Apple FS, Galvani M, Katus HA,
Newby LK, Ravkilde J, Chaitman B, Clemmensen PM, Dellborg M, Hod H,
Porela P, Underwood R, Bax JJ, Beller GA, Bonow R, Van der Wall EE, Bassand JP,
Wijns W, Ferguson TB, Steg PG, Uretsky BF, Williams DO, Armstrong PW,
Antman EM, Fox KA, Hamm CW, Ohman EM, Simoons ML, Poole-Wilson PA,
Gurfinkel EP, Lopez-Sendon JL, Pais P, Mendis S, Zhu JR, Wallentin LC,
Fernandez-Aviles F, Fox KM, Parkhomenko AN, Priori SG, Tendera M,
Voipio-Pulkki LM, Vahanian A, Camm AJ, De Caterina R, Dean V, Dickstein K,
Filippatos G, Funck-Brentano C, Hellemans I, Kristensen SD, McGregor K,
Sechtem U, Silber S, Widimsky P, Zamorano JL, Morais J, Brener S, Harrington R,
Morrow D, Lim M, Martinez-Rios MA, Steinhubl S, Levine GN, Gibler WB,
Goff D, Tubaro M, Dudek D, Al-Attar N. Universal definition of myocardial infarction. Circulation 2007;116:2634 –2653.
20. Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD. Third universal definition of myocardial infarction. J Am Coll Cardiol 2012;60:1581 –1598.
21. Keller T, Tzikas S, Zeller T, Czyz E, Lillpopp L, Ojeda FM, Roth A, Bickel C, Baldus S,
Sinning CR, Wild PS, Lubos E, Peetz D, Kunde J, Hartmann O, Bergmann A, Post F,
Lackner KJ, Genth-Zotz S, Nicaud V, Tiret L, Munzel TF, Blankenberg S. Copeptin
improves early diagnosis of acute myocardial infarction. J Am Coll Cardiol 2010;55:
2096 –2106.
22. Wild PS, Sinning CR, Roth A, Wilde S, Schnabel RB, Lubos E, Zeller T, Keller T,
Lackner KJ, Blettner M, Vasan RS, Munzel T, Blankenberg S. Distribution and categorization of left ventricular measurements in the general population: results from the
population-based Gutenberg Heart Study. Circ Cardiovasc Imaging 2010;3:604 – 613.
23. Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, Castagne R, Maouche S,
Germain M, Lackner K, Rossmann H, Eleftheriadis M, Sinning CR, Schnabel RB,
Lubos E, Mennerich D, Rust W, Perret C, Proust C, Nicaud V, Loscalzo J,
Hubner N, Tregouet D, Munzel T, Ziegler A, Tiret L, Blankenberg S, Cambien F. Genetics and beyond—the transcriptome of human monocytes and disease susceptibility. PLoS ONE 2010;5:e10.
24. Brase JC, Wuttig D, Kuner R, Sultmann H. Serum microRNAs as non-invasive biomarkers for cancer. Mol Cancer 2010;9:306.
25. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating
characteristic (ROC) curve. Radiology 1982;143:29– 36.
26. Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Statist Soc
B 2005;67 Part 2:301 –320.
2114
27. Gidlof O, Andersson P, van der Pals J, Gotberg M, Erlinge D. Cardiospecific
microRNA plasma levels correlate with troponin and cardiac function in
patients with ST elevation myocardial infarction, are selectively dependent on
renal elimination, and can be detected in urine samples. Cardiology 2011;118:
217 –226.
28. Oerlemans MI, Mosterd A, Dekker MS, de Vrey EA, van Mil A, Pasterkamp G,
Doevendans PA, Hoes AW, Sluijter JP. Early assessment of acute coronary syndromes in the emergency department: the potential diagnostic value of circulating
microRNAs. EMBO Mol Med 2012;
29. Bostjancic E, Zidar N, Glavac D. MicroRNA microarray expression profiling in
human myocardial infarction. Dis Markers 2009;27:255 – 268.
30. Wu F, Yang Z, Li G. Role of specific microRNAs for endothelial function and angiogenesis. Biochem Biophys Res Commun 2009;386:549 –553.
T. Zeller et al.
31. Bonauer A, Dimmeler S. The microRNA-17 –92 cluster: still a miRacle?. Cell Cycle
2009;8:3866 –3873.
32. van Almen GC, Verhesen W, van Leeuwen RE, van de Vrie M, Eurlings C,
Schellings MW, Swinnen M, Cleutjens JP, van Zandvoort MA, Heymans S,
Schroen B. MicroRNA-18 and microRNA-19 regulate CTGF and TSP-1 expression
in age-related heart failure. Aging Cell 2011;10:769 –779.
33. Sanders I, Holdenrieder S, Walgenbach-Brunagel G, von Ruecker A, Kristiansen G,
Muller SC, Ellinger J. Evaluation of reference genes for the analysis of serum miRNA
in patients with prostate cancer, bladder cancer and renal cell carcinoma. Int J Urol
2012;19:1017 –1025.
34. Blondal T, Jensby Nielsen S, Baker A, Andreasen D, Mouritzen P, Wrang Teilum M,
Dahlsveen IK. Assessing sample and miRNA profile quality in serum and plasma or
other biofluids. Methods 2013;59:S1 –S6.
CARDIOVASCULAR FLASHLIGHT
doi:10.1093/eurheartj/ehu135
Online publish-ahead-of-print 8 April 2014
.............................................................................................................................................................................
Massive intracardiac thromboembolism following spinal surgery
Daniel Alyeshmerni*, Brahmajee K. Nallamothu, and Jonathan Haft
Department of Cardiovascular Medicine, University of Michigan Health System, 1500 E. Medical Center Dr., Ann Arbor, MI 48109, USA
* Corresponding author. Tel: +1 8582040966, Fax: +1 7342324132, Email: [email protected]
A 71-year-old female with scoliosis and multiple
laminectomies underwent C3-5 laminectomy
with root decompression for bilateral lower
extremity pain and weakness. Four days after
discharge, while recovering at a skilled nursing
facility, she developed vague chest pain and
presented to her orthopaedic surgeon’s office
who referred her immediately to the emergency
department (ED) for suspected pulmonary
embolism. Upon presentation to the ED, she transiently required respiratory support with face
mask ventilation. Her work-up identified biatrial
thrombus connecting through a patent foramen
ovale (PFO), saddle pulmonary embolus, multiple
bilateral segmental and subsegmental PEs, and
residual bilateral lower extremity DVTs. Transoesophageal echocardiography confirmed these
findings (Panels A and B; Supplementary material
online, Videos S1 and 2). She was transferred to a
tertiary-care centre and went urgently to the
operating room. In the operating room, the intracardiac thrombus was exposed via the right atrium and the septum secundum was
opened to ensure complete removal of the thrombus. The PFO was closed and the pulmonary emboli were removed with separate incisions in each pulmonary artery during a brief period of hypothermic circulatory arrest (Panels C and D). She was discharged 10 days after her
operation after an uncomplicated post-operative course. At 1-month follow-up, she was asymptomatic with 97% oxygen saturation on
room air and is currently on a 6-month course of Coumadin with a plan for subsequent hypercoagulable work-up. The patient described
is extremely fortunate to have not had a stroke. According to the current literature, the PFO closure is still under debate, but this case
illustrates the potential catastrophic consequences of a PFO.
(Panel A) Transoesophageal echocardiography revealing a large intracardiac thrombus (white arrows) in the right and left atria (RA, LA)
connecting through a PFO (arrowhead). (Panel B) Transoesophageal echocardiography revealing a large intracardiac thrombus (white
arrow) in the LA extending across an open mitral valve (arrowhead) into the LV. (Panels C and D) Photographs taken in the operating
room. (C ) The intracardiac thrombus after removal from the atria. (D) The pulmonary embolus extracted from the right pulmonary artery.
Supplementary material is available at European Heart Journal online.
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2014. For permissions please email: [email protected]