MD Conference Express AHA 2013 - (Page 10)
FEATURE
Figure 3. Association of NT-proBNP Levels and
Development of AF
Q5: >290.3 pg/dL
Q2: 50.82-91.78 pg/dL
Cumulative AF Incidence
7.5
Quintile
Q5
Q4
Q3
Q2
Q1
6.0
Q4: 156.1-290.3 pg/dL
Q1: 5.0-50.81 pg/dL
HR (95% CI)
4.0 (3.2-5.0)
2.4 (1.9-3.0)
1.8 (1.5-2.3)
1.4 (1.1-1.8)
Ref
Q3: 91.79-156.09 pg/dL
p
<0.001
<0.001
<0.001
<0.005
-
4.5
3.0
1.5
0
0
2
4
6
8
10
Time to AF (Years)
12
14
16
HR, 1.66 (1.75-2.01) per 1-SD unit change; Higher RRs for prevalent AF (up to 147.3).
AF=atrial fibrillation; Q=quintile.
Reproduced from Patton KK et al. N-Terminal Pro-B-Natriuretic Peptide is a Major Predictor
of the Development of Atrial Fibrillation. The Cardiovascular Health Study. Circulation 2009.
With permission from Lippincott, Williams and Wilkins.
Other potential biomarkers include troponin I, matrix
metallopeptidase 9 (MMP-9). In plasma samples from 6189
patients with AF in the RE-LY trial, increased troponin I
levels were associated with an increase in cumulative events
[Hijazi Z et al. Circulation 2012]. In the Atherosclerosis Risk
in Communities [ARIC] cohort of 13718 without AF during
the early 1990s, MMP levels were assessed in a random
sample of 500 patients without AF and 580 patients that
had developed AF during the follow-up time of ~12 years
[Huxley RR et al. PLoS One 2013]. Patients that developed
AF were more likely to have elevated MMP-9 levels
than patients without AF (HR, 1.27; 95% CI, 1.07 to 1.50;
p=0.006) compared with other markers, such as MMP-1,
MMP-2, TIMP-1, TIMP-2, and CICP. In addition, higher
concentration of MMP-9 is associated with recurrence of
AF following cardioversion (p<0.01) [Mukherjee R et al.
J Cardiovasc Trans Res 2013].
Patrick T. Ellinor, MD, PhD, Harvard Medical School,
Boston, Massachusetts, USA, discussed genetic risk markers
of AF. According to data from the Framingham Heart Study,
strong clinical risk factors for the development of AF include
congestive heart failure and valve dysfunction, followed by
age, diabetes, hypertension, and myocardial infarction.
In addition, the presence of AF in a first-degree relative is
associated with an increased risk of AF (HR, 1.39; 95% CI,
1.12 to 1.73; p=0.003) [Lubitz SA et al. JAMA 2010].
In 2012, a genome-wide association study (GWAS) of
16 studies that included 6624 patients with AF and 52426
patients without AF identified 9 genetic loci for AF [Ellinor
PT et al. Nat Genet 2012; Ellinor PT et al. Nat Genet 2010;
Benjamin EJ et al. Nat Genet 2009; Gudbjartsson DF et al.
10
December 2013
Nat Genet 2009; Gudbjartsson DF et al. Nature 2007]. The
loci identified included KCNN3, PRRX1, PITX2, CAV1,
C9ORF3, MYOZ1, SYNE2, HCN4, and ZFHX3. Multiple
genetic signals have been identified around PITX2, a gene
that is associated with developing AF. In addition, a recent
GWAS found that the top two genetic loci for AF, PITX2 and
ZFHX3, were also strongly associated with cardioembolic
stroke [Bellenguez C et al. Nat Genet 2012]. Interestingly,
PITX2 is expressed only in the left atrium [Kirchhof P et al.
Circ Cardiovasc Genet 2011].
Paulus Kirchhof, MD, University of Birmingham,
Birmingham, United Kingdom, discussed the potential
personalization of rhythm control therapy in patients
with AF with a focus on imaging and electrocardiogram
(ECG) markers.
Imaging markers may provide individualized data that
may improve outcomes. For example, focal impulse and
rotor modulation ablation guided by ECG resulted in a
significant increase in event-free survival in patients with
AF (p<0.016) [Narayan S et al. J Am Coll Cardiol 2012]. In a
study of 635 patients with persistent AF, ECG and response
to flecainide that guided cardioversion resulted in a survival
probability of 86% at 6 months [Kirchhof P et al. Lancet 2012
(subanalysis pending publication)].
Prof. Kirchhof pointed out that the management of
patients with AF is already personalized as it is dependent
on clinical information. However, improvement is needed in
treatment that targets individual AF-causing mechanisms,
which may reduce the high rates of complications of
AF therapy.
In conclusion, the optimal treatment of AF is dependent
on the severity of AF and comorbid conditions, such as the
presence of hypertension, coronary artery disease, and
heart failure. Personalized management of AF is becoming
increasingly refined and in the future is likely to include a
broad range of factors beyond clinical characteristics such
as evidence of atrial remodeling, measurement of atrial
stress/strain, biomarker concentrations, genomics, ECG
patterns and AF patterns, state of the disease, and biologic
age and well-being [Gillis AM et al. Can J Cardiol 2013].
Join our mailing list!
Click here to receive notifications
when new reports are available
www.mdconferencexpress.com/newsletter
www.mdconferencexpress.com
http://www.mdconferencexpress.com/newsletter
http://www.mdconferencexpress.com
Table of Contents for the Digital Edition of MD Conference Express AHA 2013
Contents
MD Conference Express AHA 2013
https://www.nxtbook.com/nxtbooks/md_conference_express/AHA2013
https://www.nxtbookmedia.com