Disclosures Research: NIH Novel Predictors of Atrial PCORI - PDF document

8/16/2016 Disclosures • Research: – NIH Novel Predictors of Atrial – PCORI Fibrillation – Pfizer – Medtronic …and why should we care? – SentreHeart – Rhythm Diagnostic Systems • Consulting and Equity: Gregory M Marcus, MD, MAS – InCarda Therapuetics Associate Professor of Medicine Division of Cardiology University of California, San Francisco Kindling for investigators and clinicians Mechanistic Concepts  modifiable risk factors  new methods for research 1

8/16/2016 “Convictions are more dangerous enemies of truth than lies." - Friedrich Nietzsche “It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so.” - Mark Twain Wavelength=Conduction velocity X refractory period Mechanism • According to Moe’s multiple wavelet hypothesis, AF requires the presence of a critical number of partially reentrant wavelets 1,2 1. Moe GK et al. Am Heart J 1964:200-220 2. Allessie MS et al. Cardiac Electrophysiology and Arrhythmias 1985. 2

8/16/2016 Wavelength=Conduction velocity X refractory period Can we easily glean a patient’s AERP clinically? Can we easily glean a patient’s AERP clinically? • Patients with the short QT syndrome have a higher risk of AF 1 • Patients with the long QT syndrome have a higher risk of AF 2,3,4 • An increased late sodium current induces delayed afterdepolarizations and sustained triggered activity in atrial myocytes 5 – May be enhanced with SR leak/ increased intracellular calcium 6 1. Gaita et al. Circulation 2003 2. Kirchhof et al. JCE 2003. 3. Johnson et al. Heart Rhythm 2008 4. Zellerhoff et al. JCE 2009 5. Song et al. Am J Physiol Heart Circ Physiol 2008 6. Voigt et al. Circulation 2012 3

8/16/2016 Mean AERP (ms) QT C interval (ms) r=0.5, p=0.017 Multivariable Adjusted beta coefficient 0.7 (95% CI .1-1.3, p=0.02) Lee et al. Heart Rhythm 2016 4

8/16/2016 Wavelength=Conduction velocity X refractory period Number of wavelets= wavelength and atrial mass Hematoxylin and eosin–stained Sesano T. Nat Med 2006: 1256- 1258 Can we easily glean a patient’s propensity to left heart fibrosis clinically? 5

8/16/2016 QT and LAFB independently predict AF Nguyen K et al. Am J Cardiol (in press) So why do some patients have this? Familial AF Marcus et al. Heart Rhythm 2008 Mahida et al. Cardiovasc Res 2011 6

8/16/2016 Genome Wide Association Studies Gudbjartsson et al. Nature 2007 %cases (%controls) Ellinor et al. Nat Genet 2012 A Different Approach Ancestral Informative Marker • Despite having more AF risk factors, African Americans have a significantly lower Cytosine prevalence of atrial fibrillation compared to Whites. 1-4 Guanine 1. Psaty et al. Circulation 1997 2. Go et al. JAMA 2001 3. Alonso et al. Am Heart J 2009 4. Marcus et al. Am J Med 2010 7

8/16/2016 African Ancestry European Ancestry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X Y CARDIA Study Year 5 – LA Diameter (average age 30 ± 4) Admixture Mapping in AF Larger LA Diameter in Blacks Larger LA Diameter in Whites β * 95% CI P Value -0.35 -0.64 to -0.07 Unadjusted 0.014 Model 1 -0.58 -0.86 to -0.30 < 0.001 Model 2 0.39 0.13 to 0.64 0.003 Model 3 0.49 0.23 to 0.74 < 0.001 Model 4 0.70 0.34 to 1.05 < 0.001 N=4,201 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 Mean LA Diameter Difference (in mm) CARDIA Study Year 25 – LA Diameter (average age 50 ± 4) Larger LA Diameter in Blacks Larger LA Diameter in Whites β * 95% CI P Value Unadjusted -0.53 -0.87 to -0.20 0.002 Model 1 -0.85 -1.18 to -0.52 < 0.001 Model 2 0.29 -0.02 to 0.60 0.07 Model 3 0.56 0.24 to 0.88 0.001 Model 4 0.64 0.31 to 0.98 < 0.001 N=3,498 Roberts et al. JAMA Cardiol 2016 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 Mean LA Diameter Difference (in mm) Model 1: Adjusted for age and gender. Dewland et al. PloS One 2016 Model 2: Adjusted for Model 1 variables, smoking status, alcohol consumption, and BMI. Model 3: Adjusted for Model 2 variables, HR, SBP, and antihypertensive treatment. Model 4: Adjusted for Model 3 variables, LV mass, and LV ejection fraction. 8

8/16/2016 Health ABC Study ALL-HAT Trial n=2,768 (43% black) n=21,129 721 incident AF events over median of 11 years Multivariate Clinical Predictors of Incident Conduction System Disease Demographics HR 95% CI P Value Age * 1.45 1.31 to 1.59 <0.001 Male Gender 1.88 1.61 to 2.21 <0.001 Black Race † 0.61 0.51 to 0.71 <0.001 45 Percent of Race-AF Association Hispanic Ethnicity † 0.81 to 1.23 1.00 0.97 Other Race † 0.54 0.28 to 1.05 0.07 40 Mediated by Inflammatory Medical Comorbidities Percent of Association Mediated Cytokines Body Mass Index ‡ 1.07 1.00 to 1.13 0.04 35 Current Smoker 1.31 1.11 to 1.55 0.001 Prior HTN Treatment 1.04 0.83 to 1.30 0.76 30 0.73 Aspirin 1.02 0.89 to 1.18 1.27 0.001 Diabetes 1.11 to 1.46 25 Coronary Heart Disease 1.14 0.96 to 1.36 0.14 Prior MI or Stroke 1.19 1.00 to 1.41 0.06 20 ASCVD 1.04 0.87 to 1.24 0.69 Left Ventricular Hypertrophy 2.73 2.25 to 3.32 <0.001 15 Lab Values GFR § 1.00 0.96 to 1.04 0.93 Serum Potassium ǁ ‖ 0.92 to 1.19 10 1.05 0.49 Total Cholesterol ¶ 1.01 0.97 to 1.06 0.57 HDL Cholesterol ¶ 1.00 0.94 to 1.06 0.95 5 LDL Cholesterol ¶ 0.98 0.93 to 1.03 0.52 0 Cytokine concentrations in Adiponectin TNF- α TNF- α SR I TNF- α SR II All Cytokines* 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Dewland et al. JACC EP 2015 whites (left) and blacks Hazard Ratio Dewland et al. JAMA Intern Med 2016 (right) Theoretical Targets  Readily Modifiable Risk Factors Haissaguerre M . N Engl J Med 1998 9

8/16/2016 Model C-Stat for 95% CI 5 year AF risk Framingham 0.68 0.62-0.72 PACs 0.73 0.68-0.77 Combined 0.76 0.72-0.79 Nguyen K et al. Am J Cardiol (in press) Theoretical Example Abnormal QT Conduction disease PACs Ca Na K Drug Rx 10

8/16/2016 Dixit et al. Heart Rhythm 2015 11

8/16/2016 A Natural Experiment Dukes JW et al. BMJ 2016 Black=adjusted analysis White= propensity score based analysis The Atherosclerosis Risk in A Natural Experiment Communities Study (ARIC) Unadjusted 95% P Value Adjusted 95% P Value Hazard Ratio Confidence Hazard Ratio Confidence Interval Interval Average Number of 1.07 1.03-1.10 <0.001 1.04 1.01-1.08 0.020 Drinks Per Day * Number of Years 1.30 1.19-1.42 <0.001 1.13 1.02-1.24 0.014 Consumed Alcohol ** Number of Years 0.89 0.81-0.99 0.033 0.79 0.72-0.88 <0.001 Abstinent ** Dukes JW et al. BMJ 2016 Dixit S et al. AHA 2015 12

8/16/2016 The HOLIDAY Study • R01 funded randomized trial of comprehensive atrial EP studies before and after intravenous ethanol versus placebo titrated using the “breath alcohol concentration (BrAC) quick clamp method” U.S. Technology Trends Smartphone users Tablet users 91% of smartphone owners 350 Total US Population keep their smartphones 300 Total online population within 3 feet , 24/ day. 250 Consumer computers —Morgan Stanley (m illio n s) 200 Regular mobile Internet use 150 100 50 0 2010 2011 2012 2013 2014 2015 2016 Whitman, IR– NRSA award Source: Forrester Research 13

8/16/2016 External Sensors The Health e Heart Study https://www. health - eheartstudy .org/ Enrollment A. Christensen, M— Sarnoff Fellowship Nguyen K et al. HRS 2016 B. Cardiogram app on the AppleWatch (using PPG) 14

8/16/2016 Thank You UCSF Faculty Jeff Olgin EP Fellows Mel Scheinman Conclusions Ed Gerstenfeld Byron Lee EP nurses Zian Tseng Vasanth Vedantham Nitish Badhwar Research Coordinators • Clinical research can be utilized to Randy Lee Lisa Smith Rahul Deo Sayed Abu-Tahir Research Mentees Elyse Foster Rachel Gladstone understand mechanisms underlying atrial Jonathan Hsu Nelson Schiller Pui-Yan Kwok UCSF Infrastructure Thomas Dewland fibrillation Mark Pletcher Coordinators Eric Vittinghoff Jason Roberts Sarahmay Sanchez Elad Ziv Jiaqi Liu • Consideration of mechanistic subtypes is Jonathan Dukes Steve Cummings Kirsten Bibbins-Domingo Isaac Whitman Outside Collaborators important Susan Heckbert (UW) Mala Mandyam Olgin Lab Bruce Psaty (UW) Duolikun Rehemudula David Siscovick (UW/ NYA Medicine) Shalini Dixit Emily Wilson • Future emphasis on prevention and patient- Alvaro Alonso (U Minn) Kaylin Nguyen Elsayed Soliman (Wake Forest) Kwok Lab Emelia Benjamin (BU) specific targeted prevention strategies and Matt Christensen Annie Poon Research Support therapies Health eHeart Team NIH (NCATS, NHLBI, NIAAA, NIA, NIBIB) Carol Maguire Joseph Drown Foundation Kourtney Imburgia AHA (National Center and Western States • The internet and new technologies can be Laura Bettencourt Affiliate) Madelena Ng PCORI Cathy Stolitzka leveraged to gain insights in a cost-efficient John Sperling philanthropic fund Software Nextdoor ACC Merck Cognitive Digital fashion Thank You 15

8/16/2016 SUBSTRATE TRIGGERS LA ENLARGEMENT STRUCTURAL ELECTRICAL FIBROSIS AF INFLAMMATION AERP • Three of 15 lone AF patients were found to have somatic mutation in GJA5 • Functional studies supported dysfunctional Marcus et al. Heart Rhythm 2008 effects of the mutations observed fibrillation 16