American Heart Association

Strategically Focused Research

Network

Scientific Meeting

Phoenix, Arizona

March 4, 2016

Toppling the Monolith:

Embracing Heterogeneity and Resilience

In Understanding and Solving Health Disparities

Herman Taylor, Jr., MD, MPH, FAHA, FACCDirector

Background in brief…1. Health disparities negatively impacting Black health are

real, pervasive, and persistent

2. While group differences are important, precisiondemands understanding heterogeneity within groups

3. Blacks are often resilient in the face adversity

4. Resilience -- like risk and disease -- deservesintense study by the cardiovascular research community

Black Health: Focus on Group

Comparisons/Aggregate Data

Hypertension Prevalence

Group comparisons focus on deficits and

obscure within-group successes

Significant Heterogeneity among Blacks

>50% without hypertension

>85% without heart disease

Equal longevity among the elderly

Resilience

Health maintenance in the face of riskUnderstanding the environmental and individual promoters of CV health within the Black population is vastly understudied

Population Sciences Project• Identify “at-risk” and “resilient”

communities in the Atlanta area

Interview and measure AHA LS7 (n=400)

Clinical Sciences Project

• Impact of ‘risk’ and ‘resilience’ on generic

pathophysiologic pathways (n=400)

• Lifestyle Intervention with individuals

from “at-risk” and resilient communities

Basic Sciences Project:

Circulating microRNA and metabolomic

profiling:

• in ‘at risk’ and ‘resilient’ Black

communities

• In response to lifestyle intervention

Other Cohorts Available for Comparison:

Jackson Heart Study, META-Health Study, Predictive Health Study

MECA CENTER FOR HEALTH EQUITY

AHA Strategically Focused Research Network

Biostatistics, Bioinformatics, and Data Management Core

POPULATION PROJECT

Cardiovascular Risk and ResilienceAmong Blacks:

MECA Population Project

Dual PIs: Tené T. Lewis, PhDPeter Baltrus, MD

Co-ls: Viola Vaccarino, MD, PhD

Mario Sims, PhD

• To understand contextual and individual factors that contribute to CV “resilience” among a heterogeneous population of Blacks

Primary Objective

Atlanta is an ideal “laboratory"

• Exceptionally wide within-race Socioeconomic Spectrum

• Heterogeneous Communities• Different Combinations of SES and

Racial Composition• Including High Income Black

Neighborhoods

• Urban and Suburban Areas

• Less Segregation than Northeast and Midwest

• Atlanta has been underrepresented in large-scale studies of CVD in Blacks• CARDIA, MESA, ARIC, JHS

• But has long been known as the “Black Mecca”

Ebony Magazine, 1971

• At the geographic area/census tract level

• At the objective contextual/community level

• At the individual level

Resilience measured in several ways:

Population Project Overview

Aim

3A

im 2

Aim

1

CONTEXTUAL AND INDIVIDUAL LEVEL FACTORS:

Assessed Objectively and Subjectively

ATLANTA

Census Tracts

(N=940)

“AT RISK”

Census Tracts

“RESILIENT”

Census Tracts

High Rates of

CVD

Low Rates of

CVD

N=750 Individuals

Aged 35-64N=750 Individuals

Aged 35-64

Clinic Visit and AHA LS7

Assessment

N=200

Clinic Visit and AHA LS7

Assessment

N=200

ATLANTA

Census Tracts

(N=940)

“AT RISK”

Census Tracts

“RESILIENT”

Census Tracts

High Rates of CVD Low Rates of CVD

“Resilience” at the geographic/area level

• Taken from Georgia Department of Public Health, 2010-2014

• Counts of CVD related deaths among Blacks aged 35-64

• Census tracts in 31 Counties

• Atlanta-Athens-Clarke County-Sandy Springs, GA Combined Statistical Area

Cardiovascular Mortality Rate Data

CVD deaths per thousand among Blacks aged 35-64 in Census Tracts in the Atlanta–

Athens-Clarke County–Sandy Springs, GA Combined Statistical Area

• Black CVD mortality rates for all non-censored census tracts in 31 counties (347 census tracts)– Census tracts with fewer than 5 deaths due to CVD were

excluded (i.e. censored)

– Powered on the lowest expected rate (above 5) for a given population of Blacks

• ensures that “resilient” census tracts aren’t simply tracts with no Black population to sample from.

• Notable variation in CVD mortality for Blacks

Cardiovascular Mortality Rate Data

Distribution of Cardiovascular Mortality Rates for

Blacks across N=347 Census Tracts

• Identified tracts in the top and bottom 10% of the

mortality rate distribution

– 95% CI for mortality rate did not overlap the weighted

average for all rates

• Assures that census tracts are significantly above or

below average and different from each other

• 19 “Resilient” tracts

• 34 “At Risk” tracts

Selection of “At-Risk” and “Resilient” census tracts

2010-2014 CVD Mortality Rates for Blacks aged 34-65 in DeKalb County, GA

2010-2014 CVD Mortality Rates for Blacks aged 34-65 in Fulton County, GA

• Georgia Hospital Association

• Similar Analysis to Mortality Data

• Expect more census tracts for analysis due

to more events

Next Steps: Hospitalization/ER Visit Data

Next Steps: Obtain a “Social Phenotype” of at-risk and resilient census tracts

Example: Cascade Heights vs. Hapeville

2010-2014 CVD Mortality Rates for Blacks and Whites aged 34-65 in Fulton County, GA

Blacks

Whites

Example: Cascade Heights vs. Hapeville

• 92.2% Black

• 3.06% White

• Low population

density

• 1 in 11 chance of

becoming a victim

of crime– Property crimes

• Cultural Resources!!

• 31.97% Black

• 41.46% White

• High population

density

• 1 in 13 chance of

becoming a victim

of any crime– Assault

• Cultural Resources?

• Objective Community Level Measures– SES (% college educated, affluence, occupation)

– Green Spaces

– Walkability

– Grocery Stores

– % Registered to Vote

– Black-owned Businesses (Atlanta is #2 in the US)

– Churches

• Subjective Measures– Social Cohesion

• We will create an overall composite score and examine individual components

Social Phenotyping:

Contextual Level Measures of Resilience

Population Project: Next Steps

Aim

3A

im 2

Aim

1

CONTEXTUAL AND INDIVIDUAL LEVEL FACTORS:

Assessed Objectively and Subjectively

ATLANTA

Census Tracts

(N=940)

“AT RISK”

Census Tracts

“RESILIENT”

Census Tracts

High Rates of

CVD

Low Rates of

CVD

N=750 Individuals

Aged 35-64N=750 Individuals

Aged 35-64

Clinic Visit and AHA LS7

Assessment

N=200

Clinic Visit and AHA LS7

Assessment

N=200

CLINICAL PROJECT

Clinical Project 2:

Impact of technology-based Intervention for

improving self-management behaviors in Black adults

with poor cardiovascular health

Arshed A. Quyyumi MD Emory University School of Medicine

Priscilla Pemu MD Morehouse School of Medicine

Co-Is:

Sandra Dunbar PhD Emory University School of Nursing

Dual PIs:

Clinical Project 2: Impact of technology-based Intervention for improving

self-management behaviors in Black adults with poor cardiovascular health

Atherosclerosis/

Hypertension/ Heart Failure

Stroke

Risk factors

Oxidative StressInflammation

Regenerative Capacity

Sub-clinical disease

‘Resilient’‘At risk’

Neighborhood and Individual

Social and Environmental Factors

AIM 1

Lifestyle

Intervention

AIMS 2/3

Specific Aim 1: To investigate the impact of social and environmental ‘risk and resilience’

factors on (i) biomarkers of cardiovascular (CV) risk and repair/regeneration, and (ii) sub-

clinical vascular disease in Blacks.

Participants: 400 Black men and women (21-65 y) from ‘at risk’ and ‘resilient’ communities in metro Atlanta.

Measurements:

Neighborhood/Individual ‘resilience’

Endpoints: • Inflammation: HsCRP, • Oxidative stress: plasma cystine, glutathione • Regenerative capacity: CD34+ and subset cell counts. • Vascular measures: pulse wave velocity and PAT

reactive hyperemia index, augmentation index and CIMT.

• Adjust above markers for AHA LS7 score

‘Resilient’ Communities

‘At Risk’ Communities

AIM 1

Vascular dysfunction

Oxidative Stress, Inflammation, regenerative capacity

AHA Life 7s score

• (All

Regenerative Capacity

CD34+/CD133+ cells905 patients

Glutathione/cystine ratio

Hs CRP

(N=1245)

Oxidative stress/Inflammation

PVA‡ RHI CAIx PWVBlacks 275±6** 2.1±0.04** 21.2±0.6** 7.3±0.1**Whites 328±6 2.3±0.03 16.6±0.6 7.1±0.1

Vascular Function

Patel RS, Quyyumi AA. Circ Res. 2015 Jan 16;116(2):289-97Morris AA, Quyyumi A. J Am Heart Assoc. 2013 Apr 8;2(2):e002154.

Neighborhood Effects

Vascular Function

Variables Environment Walkability Cohesion

Low High Low High Low High

Age, M (SD), yrs 50.7(±9.1) 50.8(±9.2) 50.8(±9.6) 50.8(±9.2) 49.4(±9.6)* 52.0(±9.0)*

Black, n (%) 92(55.4)* 82(42.7)* 104(58.1)* 67(41.9)* 99(60.7)* 110(40.6)*

Female, n (%) 100(60.2) 115(59.9) 111(62.0) 93(58.1) 93(57.1) 177(65.6)

Education, n (%)

High School or GED 39 (25.2) 22 (12.4) 35 (21.3) 16 (10.8) 34 (23.3) 38 (15.3)

Some College 54 (34.8) 33 (18.5) 61 (37.2) 28 (18.9) 52 (35.6) 49 (19.8)

College Graduate 62 (40.0)* 123 (69.1)* 68 (41.5)* 104 (70.3)* 60 (41.1)* 161 (64.9)*

BMI, M (SD) (kg/m2) 30.4 (±7.7) 28.9(±7.4) 30.5 (±7.6)* 28.8 (±7.6)* 31.6 (±8.3)* 29.2 (±7.3)*

BDI, M (SD) 11.3 (±9.0)* 7.5 (±7.6)* 6.8(±0.5)* 9.5 (±0.7)* 9.3 (±0.7)* 7.1 (±0.7)*

Hypertension, n (%) 80(48.2) 73(38.0) 88(49.2) 63(39.4) 79(48.5) 110(40.6)

Diabetes, n (%) 20(12.0) 17(8.9) 22(12.3) 12(7.5) 19(11.7) 24(8.9)

LDL-C, M (SD) 120 (35) 115(32) 120(36) 116(32) 122(37)* 119(334)*

HDL-C, M (SD) 57.(16) 60 (186) 59 (16) 61 (17) 56 (15)* 60(19)*

Smoking, n (%) 52(31)* 39(22)* 51(29) 31(21) 48(31)* 51(20)*(*=P<0.05)

LogIL6 LogTNFα LogCRP

NEIGHBORHOOD

Environment -0.143** -0.090* -0.112*

Walkability -0.061 0.029 -0.123*

Cohesion -0.152** -0.099* -0.085

Aim 2: Investigate effective method for driving behavior change using ehealth among Black participants with low AHA LS7 scores.

Aim 3: Effects of the two life-style interventions on biomarkers, repair/regeneration, and vascular function.

Participants:

• 150 participants from Aim 1;

• 75 from ‘resilient’ and 75 from ‘at risk neighborhoods

• AHA LS7 scores of ≤4

• Internet access, can participate in physical activity

Randomization:

Initial 6 months: 75 subjects to interventional

randomization and 75 subjects to wait list controls.

Following 6 months: the 75 randomized to wait list controls

will be randomized to one of two interventions.

High tech high touch, vs. High tech vs wait list controls

Low AHA LS7(n=150)

eHealthyStrides +Coach

eHealthyStrides

Wait listcontrols

eHealthyStrides +Coach

eHealthyStrides

N=75

N=75

6 months

6 months

Aim 2: Investigate effective method for driving behavior change using ehealth among Black participants with low AHA LS7 scores.

Aim 3: Effects of the two life-style interventions on biomarkers, repair/regeneration, and vascular function.

Interventions

• eHealthystrides intervention: internet or mobile

application (www. ehealthystrides.org)

– Supports behavior change by improving health

literacy, self-efficacy with in-built coaching

support

– a social networking forum to promote

motivation and community

• Health coach: trained in the use of behavioral

strategies and interpersonal motivational approaches.

Assist the participant to generate a personalized action

plan using the goal-setting tool embedded in

ehealthystrides

eHealthy Strides +Coach

eHealthy Strides

Weekly Meetings x 4 Biweekly Meetings x4 Monthly Meetings x3

No scheduled Meetings. Tailored

Reminders

Aim 2AHA LS7

Aim 3Vascular Function,

Biomarkers

Health Coach intervention eHealthyStrides

Table 5: Effects of Health Partner Intervention (Change)

6 months P-value

Systolic BP (mmHg) 3.89 ± 0.66 <.001

Mean arterial pressure (mmHg) 2.72 ± 0.45 <.001

Aortic (central) pulse pressure 3.07 ± 0.67 <.001

Pulse wave velocity (m/s) 0.31 ± 0.08 <.001

Weight (lbs) 2.2 ± 0.42 <.001

BMI (kg/m2) 0.36 ± 0.07 <.001

Waist-hip ratio 0.009 ± 0.003 .001

% Android fat 1.06 ± 0.17 <.001

Total cholesterol (mg/dL) 7.75 ± 1.73 <.001

LDL cholesterol (mg/dL) 6.17 ± 1.57 <.001

Insulin sensitivity index* -0.008 ± 0.004 .051

Preliminary data on effectiveness of health coach and eHealth

Mean (SD) Baseline 12wks P value

BP (mmHg) 134(22) 128(17) p<0.0001

Glucose mg/dL 137(54) 122(43) <0.0001

Exercise (miles) 1.4(1.7) 2.0(1.8) <0.0001

N= 244 subjects

N= 712 subjects

Blood Pressure

Control Cholesterol

Reduce BloodSugar

Track Activity

Nutrition

Weight Management

Stop Smoking

Blood Pressure

Control Cholesterol

Reduce Blood Sugar

Track Activity

Nutrition

Weight Management

Stop Smoking

HDL

LDL

Triglyceride

Total Cholesterol

Date

Time

5/10/2015

12:15 p.m.

32

85

145

145

Update

01:08:05

Years

Months

Days

Have you smoked today?

Yes No

Click here for tips to quit smoking

BASIC PROJECT

MicroRNA and metabolomic profiles

associated with social and environmental risk

factors in blacks

Charles Searles, MD, FAHADean Jones, PhD

Dong Liu, PhDTianwei Yu, PhD

Amanda James, PhD

Environmental/

Social Factors

Community/

Contextual

Regenerative

Capacity

Response

Inflammation

CVD Risk

Atherosclerosis

Endothelial

dysfunction

miRNAs and metabolites

Resilience Allostatic load

Individual

Oxidative

stress

Basic Sciences Project: MicroRNA and metabolomics profiles

associated with environmental and social factors in blacks

Population Project

Clinical Project

Basic Project

AIM

1

META-Health

Emory/GA Tech CHDWBWHITE BLACK

Low/High CVD Risk

Subaims: in vitro

angiogenesis

DiscoveryNGS

HR Metabolomics

miRNA target and

KEGG pathways Validation

qRT-PCR

Low/High CVD RiskA

IM 2

Compare with META-Health Cohort

400 subjects recruited by Population Project

“At Risk” Communities

AHA LS7: 0-7

n=200

“Resilient” Communities

AHA LS7: 0-7

n=200

AIM

3

Low AHA LS7 Scores

n=75

Low AHA LS7 Scores

n=75

miRNA/isomiR and

metabolomics profiles

Intervention by Clinical Project

miRNA/isomiR and metabolomic

profiles in blacks

miRNA/isomiR and metabolomic profiles

in blacks: low vs high CVD Risk

New high-resolution metabolomics (HRM) measures >20,000 chemicals in human serum

Jones, Park Ziegler Annu Rev Nutr 2012

100,000 registered with EPA

10,000 with high volume use

Largely uncharacterized (may be 10-40%

of plasma metabolome)

>1000 drugs in use

40 Essential nutrients

2000 intermediates formed by enzymes

encoded by the genome

Plant metabolome >200,000 chemicals

*Metabolome refers to chemicals associated with life

Environmental Chemicals

Core Nutritional Metabolome

Non-nutritive Chemicals in Diet

Microbiome-related Chemicals

Supplements and Pharmaceuticals

Commercial Products Environmental metabolome

Food metabolome

Assay broadly covers human exposures

Novel high-resolution metabolomics EMORY CLINICAL BIOMARKERS LABORATORY: Dean Jones

Extracellular miRNAs as a functional biomarkers

associated with cardiovascular risk

Microparticle

miRNA

Del-1

CVD

CVD

Donor Cell

Recipient Cell

CVD

1. CVD decreased miRNA content of microparticles compared to healthy.

2. CVD altered protein responsible for uptake of microparticles.

3. CVD decreased MP-encapsulated miRNA uptake compared to healthy

Searles Lab: published work

isomiR-10b isomiR-93 isomiR-181a isomiR-182

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20000

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low F

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Low FRS High FRS

Blacks Whites

Black/White Differences in plasma MPs

Plasma MPs in Blacks: low versus high FRS

miR-10b miR-93 imiR-181a miR-182

Black/White Differences in select miRNAs

miRNAs in Blacks: low versus high FRS

Preliminary Analysis of META-Health Plasma

Variable Statistics White (N=52) Black (N=52) P-value*

Female N (%) 21 (40.38) 22 (42.31) 0.84

Smoking N (%) 9 (17.31) 12 (23.08) 0.46

HTN Meds N (%) 12 (23.08) 12 (23.08) 1.00

HTN N (%) 19 (36.54) 25 (48.08) 0.23

DM N (%) 4 (7.69) 6 (11.54) 0.51

Hyperlipidemia N (%) 23 (44.23) 21 (40.38) 0.69

History of MI N (%) 1 (1.92) 3 (5.77) 0.31

Age Mean (SD) 52.54 (10.51) 50.71 (8.90) 0.34

BMI Mean (SD) 29.45 (7.65) 31.02 (5.68) 0.24

SBP Mean (SD) 116.17 (15.51) 117.5 (16.43) 0.67

Total Cholesterol Mean (SD) 203.69 (35.39) 200.6 (39.21) 0.67

HDL Mean (SD) 56.42 (19.90) 54.31 (12.95) 0.52

Glucose Median (Q1, Q3) 90.5 (86.0, 95.5) 92.5 (86.5, 101.5) 0.20

FRS Median (Q1, Q3) 5 (2, 9) 4 (3, 8) 0.84

Preliminary Analysis of META-Health Plasma

Type 1 Manhattan plot: (-)logP vs m/z

26 differentially expressed features at FDR 0.2 (99 at p<0.05)

m/z features above dashed horizonalline are significant after FDR adjustment

FDR 0.2

Pathway enrichment analysis based on the differentially expressed features using Mummichog

0 0.5 1 1.5 2 2.5

Carni neshu le

VitaminEmetabolism

Prostaglandinforma onfromdihomogama-linoleicacid

Drugmetabolism-cytochromeP450

(-) logP

Only the significantly enriched pathways (p<0.05) are shown

miRNA-181a

miRNA-182

Legend

Circles: micro RNAs

Rectangles: metabolome features

miRNA metabolome wide association study (MWAS):

3-way relationship between metabolome, race and miRNAs

Pathway enrichment analysis for global association between

miRNAs and m/z features at correlation threshold 0.3

(-) logP

Only the significantly enriched pathways (p<0.05) are shown

0 0.5 1 1.5 2 2.5 3 3.5

Phytanic acid peroxisomal oxidation

Butanoate metabolism

Biopterin metabolism

Glutathione Metabolism

Aspartate and asparagine metabolism

Glutamate metabolism

Leukotriene metabolism

Linoleate metabolism

Caffeine metabolism

Summary

• High resolution metabolomics: >20k metabolites in a drop of blood, capturing

microbiome, dietary and environmental chemicals and covering most human

pathways.

• Focus on microparticle-encapsulated miRNAs/isomiRs as functional

biomarkers.

• Preliminary data indicating black/white differences in molecular profiles.

• Coexpression of metabolites and miRNA can provide indicators of metabolic

phenotype.

• Network analysis between all m/z features and 99 differentially expressed

features show strong associations between m/z features and miR-181a, -182.

• Future work will examine molecular profiles associated with conventional risk

factors as well as environmental/social risk factors and resilience.

TRAINING PROGRAM

Cardiovascular Health and

Resilience among Blacks

Training Program Update March 2016S. Dunbar and G. Strayhorn – Co Directors

Matt Topel, MD –FellowA. Quyyumi, MD - Mentor

Training environment• Minority Health Genomics and Translational Research Bio-Repository

Database (MH-GRID) (PI: Rakale Quarells)

• Network Emory’s T32 Research Training Program in Academic Cardiology (PI: Robert Taylor)

• T32 Interdisciplinary Research Training for Nurse Scientists (PI: Sandra Dunbar)

• Building Interdisciplinary Research Careers in Women’s Health (BIRCWH) (PI: Clarie Sterk)

• Pending: T32 Training in Health Disparities (PI: Viola Vaccarino)

• MSM-EU Collaborative research and training: Clinical and Translational Science Institute (ACTSI), PI: David Stephens [Emory], PI: Elizabeth Offili [MSM], PI: Ravi Bellamkonda [GATech]

• T32 Training Program in Hypertension (PI: Gordon Williams [Harvard University]), PI Herman Taylor [MSM])

MECA TRAINING AIMS• Aim 1. Select fellows with the training, vision and academic capacity required to complete

the proposed training program in CV health disparities;

• Aim 2. Provide a training program in CV health disparities through mentored research

combined with standardized and individual course work in basic, translational, clinical outcomes, community engaged research, prevention, population, and social determinants concepts related to CV health disparities. Individual fellows will select their mentored research from one or a combination of these areas;

• Aim 3. Create a collaborative interdisciplinary and cross-institutional environment to expose fellows to a variety of ideas and approaches addressing CV health disparities; and

• Aim 4. Promote professional career development through a seminars on communication skills; scientific writing and presentations; grant writing, budgets, and management; work/life balance; seeking foundation and alternate funding; and research ethics.

Activities to Date

• Established the Training Steering Committee (Taylor, Quyyumi Vaccarino, Gee, Quarells, Wilson) Aim I

• Recruited and appointed Matthew Topel as first year fellow Aim I

• Training Program Aim II

– Mentored research: Quyyumi, Lewis (Clinical, Population projects)

– Independent development plan

• Fellow participates in MECA & monthly SFRC Training calls Aim III

• Promote professional career development Aim IV

Next 6 months

• Appoint Year 02 fellow – invite by April 1, 2016

– Several inquiries and 1 application to date

• Review and Reappoint Year 01 fellow

– Update IDP

– Involvement in basic, population, clinical projects

• Participate in SFRC Center activities

Towards a more complete understanding of Black CV Health

Gregory Strayhorn, MD, PhD Sandra B. Dunbar, RN, PhD

Arshed Quyyumi, MDPriscilla Pemu, MD, MS

Charles Searles, MD

Dean Jones, PhD George Rust, MD, MPH Tené Lewis, PhD

Herman A. Taylor, MD, MPH

Priscilla Pemu, MD, MS