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

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MD Conference Express AHA 2013

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