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

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

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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,

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8/16/2016 1 Novel Predictors of Atrial Fibrillation

…and why should we care?

Gregory M Marcus, MD, MAS Associate Professor of Medicine Division of Cardiology University of California, San Francisco

Disclosures

  • Research:

– NIH – PCORI – Pfizer – Medtronic – SentreHeart – Rhythm Diagnostic Systems

  • Consulting and Equity:

– InCarda Therapuetics

Kindling for investigators and clinicians

Mechanistic Concepts modifiable risk factors new methods for research

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“Convictions are more dangerous enemies

  • f 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

Mechanism

  • According to Moe’s multiple wavelet hypothesis, AF requires

the presence of a critical number of partially reentrant wavelets1,2

  • 1. Moe GK et al. Am Heart J 1964:200-220
  • 2. Allessie MS et al. Cardiac Electrophysiology

and Arrhythmias 1985.

Wavelength=Conduction velocity X refractory period

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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 AF1

  • Patients with the long QT syndrome have a

higher risk of AF2,3,4

  • An increased late sodium current induces

delayed afterdepolarizations and sustained triggered activity in atrial myocytes5

– May be enhanced with SR leak/ increased intracellular calcium6

  • 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
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Mean AERP (ms) QTC 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

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Wavelength=Conduction velocity X refractory period

Hematoxylin and eosin–stained Sesano T. Nat Med 2006: 1256- 1258

Number of wavelets= wavelength and atrial mass

Can we easily glean a patient’s propensity to left heart fibrosis clinically?

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QT and LAFB independently predict AF

Nguyen K et al. Am J Cardiol (in press)

So why do some patients have this?

Marcus et al. Heart Rhythm 2008

Familial AF

Mahida et al. Cardiovasc Res 2011

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Ellinor et al. Nat Genet 2012

Genome Wide Association Studies

Gudbjartsson et al. Nature 2007

%cases (%controls)

A Different Approach

  • Despite having more AF risk factors, African

Americans have a significantly lower prevalence of atrial fibrillation compared to Whites.1-4

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

Ancestral Informative Marker

Cytosine Guanine

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African Ancestry European Ancestry

13 14 15 16 17 18 19 20 21 22 X Y 1 3 4 5 6 7 8 9 10 11 12 2

Admixture Mapping in AF

Roberts et al. JAMA Cardiol 2016

Mean LA Diameter Difference (in mm) Larger LA Diameter in Blacks Larger LA Diameter in Whites

  • 0.53
  • 0.87 to -0.20

0.002

  • 0.85
  • 1.18 to -0.52

< 0.001 0.29

  • 0.02 to 0.60

0.07 0.56 0.24 to 0.88 0.001 0.64 0.31 to 0.98 < 0.001 95% CI P Value Unadjusted Model 1 Model 2 Model 3 Model 4 β*

  • 1.2
  • 1
  • 0.8
  • 0.6
  • 0.4
  • 0.2

0.2 0.4 0.6 0.8 1 1.2

Model 1: Adjusted for age and gender. 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.

CARDIA Study Year 25 – LA Diameter (average age 50 ± 4)

Unadjusted Model 1 Model 2 Model 3 Model 4 Mean LA Diameter Difference (in mm) Larger LA Diameter in Blacks Larger LA Diameter in Whites

  • 0.35
  • 0.64 to -0.07

0.014

  • 0.58
  • 0.86 to -0.30

< 0.001 0.39 0.13 to 0.64 0.003 0.49 0.23 to 0.74 < 0.001 0.70 0.34 to 1.05 < 0.001 95% CI P Value β*

  • 1.2
  • 1
  • 0.8
  • 0.6
  • 0.4
  • 0.2

0.2 0.4 0.6 0.8 1 1.2

CARDIA Study Year 5 – LA Diameter (average age 30 ± 4)

N=4,201 N=3,498

Dewland et al. PloS One 2016

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Health ABC Study

n=2,768 (43% black) 721 incident AF events over median of 11 years

5 10 15 20 25 30 35 40 45 Adiponectin TNF-α TNF-α SR I TNF-α SR II All Cytokines*

Percent of Association Mediated

Percent of Race-AF Association Mediated by Inflammatory Cytokines

Cytokine concentrations in whites (left) and blacks (right)

Dewland et al. JACC EP 2015

ALL-HAT Trial n=21,129

Hazard Ratio

Demographics <0.001 <0.001 0.97 Body Mass Index‡ Current Smoker Prior HTN Treatment Aspirin Diabetes Coronary Heart Disease Prior MI or Stroke ASCVD Left Ventricular Hypertrophy 0.07 Medical Comorbidities Lab Values GFR§ Serum Potassiumǁ ‖ Total Cholesterol¶ HDL Cholesterol¶ LDL Cholesterol¶ 95% CI P Value <0.001 0.04 0.001 0.73 0.001 0.76 Age* Male Gender Black Race† Hispanic Ethnicity† Other Race† 0.14 0.69 <0.001 0.06 0.95 0.52 0.57 0.49 0.93 HR 1.45 1.31 to 1.59 1.88 0.61 1.00 0.54 1.07 1.31 1.04 1.02 1.27 1.14 1.19 1.04 2.73 1.00 1.05 1.01 1.00 0.98 1.61 to 2.21 0.51 to 0.71 0.81 to 1.23 0.28 to 1.05 1.00 to 1.13 1.11 to 1.55 0.83 to 1.30 0.89 to 1.18 1.11 to 1.46 0.96 to 1.36 1.00 to 1.41 0.87 to 1.24 2.25 to 3.32 0.96 to 1.04 0.92 to 1.19 0.97 to 1.06 0.94 to 1.06 0.93 to 1.03

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Multivariate Clinical Predictors of Incident Conduction System Disease

Dewland et al. JAMA Intern Med 2016

Theoretical Targets Readily Modifiable Risk Factors

Haissaguerre M. N Engl J Med 1998

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Model C-Stat for 5 year AF risk 95% CI

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

Conduction disease PACs Abnormal QT

Na K Ca Drug Rx

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Dixit et al. Heart Rhythm 2015

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A Natural Experiment

Black=adjusted analysis White= propensity score based analysis

Dukes JW et al. BMJ 2016

A Natural Experiment

Dukes JW et al. BMJ 2016

The Atherosclerosis Risk in Communities Study (ARIC)

Unadjusted Hazard Ratio 95% Confidence Interval P Value Adjusted Hazard Ratio 95% Confidence Interval P Value Average Number of Drinks Per Day* 1.07 1.03-1.10 <0.001 1.04 1.01-1.08 0.020 Number of Years Consumed Alcohol** 1.30 1.19-1.42 <0.001 1.13 1.02-1.24 0.014 Number of Years Abstinent** 0.89 0.81-0.99 0.033 0.79 0.72-0.88 <0.001

Dixit S et al. AHA 2015

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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”

Whitman, IR– NRSA award

U.S. Technology Trends

Total US Population Total online population

Consumer computers

Regular mobile Internet use

2016 2015 2014 2013 2012 2011 2010 350 300 250 200 150 100 50 (m illio n s) Smartphone users Tablet users

Source: Forrester Research

91% of smartphone owners keep their smartphones within 3 feet, 24/day.

—Morgan Stanley

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The Health eHeart Study

https://www.health-eheartstudy.org/

External Sensors Enrollment

A. B.

Christensen, M— Sarnoff Fellowship Nguyen K et al. HRS 2016 Cardiogram app on the AppleWatch (using PPG)

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Conclusions

  • Clinical research can be utilized to

understand mechanisms underlying atrial fibrillation

  • Consideration of mechanistic subtypes is

important

  • Future emphasis on prevention and patient-

specific targeted prevention strategies and therapies

  • The internet and new technologies can be

leveraged to gain insights in a cost-efficient fashion

Thank You

UCSF Faculty Jeff Olgin Mel Scheinman Ed Gerstenfeld Byron Lee Zian Tseng Vasanth Vedantham Nitish Badhwar Randy Lee Rahul Deo Elyse Foster Nelson Schiller Pui-Yan Kwok Mark Pletcher Eric Vittinghoff Elad Ziv Steve Cummings Kirsten Bibbins-Domingo Olgin Lab Duolikun Rehemudula Emily Wilson Kwok Lab Annie Poon Health eHeart Team Carol Maguire Kourtney Imburgia Laura Bettencourt Madelena Ng Cathy Stolitzka Software Nextdoor Cognitive Digital EP Fellows Research Support NIH (NCATS, NHLBI, NIAAA, NIA, NIBIB) Joseph Drown Foundation AHA (National Center and Western States Affiliate) PCORI John Sperling philanthropic fund ACC Merck

Research Mentees Jonathan Hsu Thomas Dewland Jason Roberts Jonathan Dukes Isaac Whitman Mala Mandyam Shalini Dixit Kaylin Nguyen Matt Christensen

EP nurses Research Coordinators Lisa Smith Sayed Abu-Tahir Rachel Gladstone UCSF Infrastructure Coordinators Sarahmay Sanchez Jiaqi Liu Outside Collaborators Susan Heckbert (UW) Bruce Psaty (UW) David Siscovick (UW/ NYA Medicine) Alvaro Alonso (U Minn) Elsayed Soliman (Wake Forest) Emelia Benjamin (BU)

Thank You

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SUBSTRATE TRIGGERS STRUCTURAL ELECTRICAL

LA ENLARGEMENT FIBROSIS INFLAMMATION AERP

AF

Marcus et al. Heart Rhythm 2008

  • Three of 15 lone AF patients were found to have

somatic mutation in GJA5

  • Functional studies supported dysfunctional

effects of the mutations observed fibrillation

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  • Next generation sequencing in 560 genes

(including genetic culprits in AF, Mendelian cardiomyopathies and channelopathies and all ion channels in the genome)

  • 34 patients (25 with AF)
  • No evidence of somatic mutations

Whitman, IR– NRSA award

N=1,000,000; 60,285 with AF (HCUP)

Admixture Mapping in lone AF