Disclosures

• Department of Cardiac Sciences and Libin

Cardiovascular Institute – U of Calgary

• Grant support by HSF, AI-HS

• Grant support

– Roche, Merck, Abbott

• Characteristics of biomarkers

• Imaging Biomarkers for intermediate risk

– Carotid ultrasound or MR

– Calcium scoring – coronary or abdominal

– Cardiac MR

Assessment of Vascular Risk

Objectives

• Biomarker intended to substitute for a clinical

endpoint

• Expected to predict clinical outcomes (feels, functions

or survives, including harm)

• Does epidemiological data suggest that the

biomarkers adds to the ability to detect risk

independently of established risk factors?

• Examples:

– Blood pressure

– LDL cholesterol

•

Characteristics of a Surrogate

•

How to evaluate new biomarker

• Univariate and multivariate relationship with CV

outcomes – Cox proportional hazard

• Compared with existing model – individual risk

factors or Framingham risk score

– Global measures of model fit

– Calibration

– Discrimination

– Reclassification

Mc Geechan et al. Arch Int Med 2008;168:2304

Assessment of Vascular Risk – Why do we need

• ARIC study n=15732 with 461 events

• FRS had a C statistic of 0.75

• At cut-off of >20% risk only 22% of those with

hard events would have been identified

• Negative predictive value was 97%

CV Biomarkers Today Inflammation and Proliferation CRP

Lp-PLA2

MCSF

PDGF

FDF

FGF

Interleukins (1,6,8,10,12,15)

MMPs (1,2,3,9)

MIP1 (alpha and beta)

TNF alpha

Proliferating cell nuclear antigen

Hyaluronan receptors

SR-A, SR-B1

TGF

SM myacin heavy chains

CD 11, 18, 36, 40, 68

MCP-1

CCR2

Pentraxin-3

C4b binding protein

I kappa B-alpha

Total sialic acid

Osteopontin

Adhesion molecules s-ICAM

s-VCAM

P-selectin

E-selectin

Serum glycoproteins Alpha 1-antitrypsin

Alpha 1 acid glycoprotein

Alpha 2-macroglobulin

Ceruloplasmin

haptoglobin

Coagulation VWF

tPA

PAI-1

PF4

D-dimer

Tissue factor

Fibrinogen

Beta thromboglobulin

Erythrocyte sed. Rate

RBC adhesiveness/aggreg

Genetics ACE polymorphism

methylenetetrahydrofolate reductase [MTHFR]

apolipoprotein E [apo E]

paraoxonase [PON] Immunology

Anti-oxLDL IgG

Imaging Angiography

IVUS

3D reconstruction IVUS MDCT (coronary Ca++)

Carotid ultrasound – IMT

MRI (carotid, PAD, aortic)

PET

Aortic CT

Scintigraphy (thallium, sestimibe)

Intracoronary endo fct (Ach)

Brachial ultrasound

Plethysmography

TEE (aortic)

Skin cholesterol

Monoclonal antibody imaging

Pulsatile flow visualization (aorta)

Regional aortic distensibility

Aortic stiffness (Doppler)

Coronary thermography

Coronary elastography

Coronary NIR spectroscopy

Lipids lipoproteins

lipoprotein subfractions

(L1-3, V1-6, H1-5)

Apolipoproteins

(CIII, AII:E, LpB…)

Lp(a)

Lipid ratios

2012 CCS Dyslipidemia Guidelines

1. We recommend secondary testing for further risk assessment in

“intermediate risk” (10-20% FRS after adjustment for family history)

subjects who are not candidates for lipid treatment based on

conventional risk factors or for whom treatment decisions are

uncertain.

(Strong/moderate evidence)

2. We suggest that secondary testing may be considered for a selected

subset of “low to intermediate risk” (5-10% FRS after adjustment for

family history) subjects for whom further risk assessment is indicated,

e.g. strong family history of premature CAD, abdominal obesity, South

Asian ancestry or impaired glucose tolerance.

(Weak/low evidence)

Wang TJ et al. N Engl J Med 2006; 355:2631-2639.

Biomarkers that predicted risk of death

C statistic increases

from 0.76 to 0.77

with all biomarkers

added

Eva Lonn

Novel markers of atherosclerotic risk

Lorenz et al. Circ 2007 115:459

Met-analysis of 37197 subjects

8 studies, 12 pubs of IMT

IMT and Discrimination, Reclassification

• USE-IMT meta-analysis

– 15 large cohort studies

– 45,000 subjects

– 4007 first MI or stroke

– C-statistic 0.757 and not changed with IMT

– NRI significant but 0.8% given sample size

– NCRI for intermediate risk 3.6%

Den Ruijiter JAMA 2012; 308:796-

Plaque Burden

Sillesen et al. JACC CVI 2012;5:681

6101 aSx BioImage Study

Carotid Plaque, CIMT,

ABI, AAD and CAC

Mean age 69 yrs,

Carotid plaque burden was

most strongly correlated

with CAC

Plaque, IMT and Discrimination, Reclassification

Pollak NEJM 2011;365:213

Framingham offspring

2965 with 296 events

NRI 0% for CCA

NRI 7.6% for ICA

And 7.3% for ICA

Plaque

7.2 y follow-up

ASE recommendations - CIMT

• aSx subjects – Carotid IMT might be useful

– Intermediate risk subjects – IIa AHA/ACC

– Subjects with strongly positive family Hx of CAD

– Women less than 60 years with > 2 risk factors

– Genetic dyslipidemia

– Use should be restricted to centres with specific

research experience

– Use of 3D plaque measurements being evaluated

Roman et al. J Am S of Echo 2006; 19:943.

Stein et al. J Am S of Echo 2008;21:93

Greenland et al. JACC 2010;56:Dec 2010

Atherosclerosis 2011; 214:43-46

Coronary Artery Calcium

Due to atherosclerosis

Related to age and risk factors

Not related to stenosis but is

related to plaque volume

Can be detected by EBCT or

MDCT

Radiation dose is moderate

(0.5-1.5 mSev and acquisition

very quick

Variance about 40% for

repeated measures

Coronary calcium score – Prevalence

Tota-Maharaj EHJ 2012;33:2955

aSx group 44,052

CAC related to all cause

mortality across age range

Coronary calcium score – Related to Risk factors

Jenny et al. Athero 2010;209:226

MESA – n=6783

Cross X

Inflammatory

markers weakly

correlated after

adjusting for

traditional

factors

Coronary calcium score - Prognosis

Detrano NEJM 2008;356:1336

MESA – 6722 subjects

162 events

HR 7.08 for major

Coronary event

With CAC >100

Coronary calcium score – Prognosis

Tota-Maharaj EHJ 2012;33:2955

aSx group 44,052

CAC related to all cause

mortality across age range

CAC and Discrimination, Reclassification

Polonsky JAMA 2010;303:1610

5878 MESA subjects

209 CHD events

CAC added to multiple risk factors

NRI 25%

CAC >300

CAC and Discrimination, Reclassification

Elias Smale JACC 2010;56:1407

Rotterdam

2028 aSx subjects

9.2 years with 135 hard EPs

52% of IR reclassified

CAC < 50 or >615

AHA/ACC recommendations - CT

• aSx subjects – MDCT calcium scores

– Low or high risk subjects – Class III – Level B evidence

– Middle risk subjects – Class IIa – Level B evidence

• aSx subjects – MDCT coronary angiography

– All subjects – Class III – Level B evidence

• Serial imaging for athero progression – Class III

Greenland et al. JACC 2010;56:Dec 2010

Comparison of novel risk markers

Yeboah JAMA 2012;308:788

MESA

1330 IR subjects

CAC, IMT, CRP,

FH and ABI

123 CVD events

Carotid IMT not

associated with

events while others

were

CAC was best

Abdominal Calcification

Chuang AJC 2012;110:891

Framingham cohort - N=3285 50y of age

Compared with healthy ref pop - Agaston Ca++ score of AA

AAC widely prevalent and associated FRS

Fayed et al. Lancet Sept 2011

Carotid MR for plaque evaluation

Measuring Atherosclerosis PET/CT

Positron emission tomography (PET) • PET with 18F-fluorodeoxyglucose (18F-FDG) can

identify cells with increased metabolic activity1,2

• 18F-FDG-PET can be used to detect inflammation; e.g. in atherosclerotic plaques1,2

– a potential marker for vulnerable plaques

• Serial PET imaging can assess changes in plaque inflammation over time, including responses to therapy2–4

Positron emission tomography (PET)/Computed tomography (CT) • CT facilitates anatomic location of plaque, allowing

assessment by PET of changes over time in response to therapy2

26

18F-FDG-PET/CT

imaging5

1Rudd et al. Circulation. 2002;105;2708–2711; 2Rudd et al. J Am Coll Cardiol. 2010;55:2527–2735; 3Tahara et al. J Am Coll Cardiol. 2006;48:1825–1831; 4Lee et al. J Nucl Med. 2008;49:1277–1282; 5Fayad et al. Lancet. 2011.

CT

P

ET

/CT

Mewton et al. Hypertension 2013;61:ahead of press

Cardiac MR for Risk Stratification

5004 subjects in MESA

CMR, followed for 7.2 y

LV structure and Fx

LVGFI = SV/LV total V

579 events

Independent predictor of

HF and hard events – better

than EF

HR 0.79 adjusted including

CAC

• Vascular risk can be assessed using risk engines such

as Framingham

• Risk stratification for intermediate risk subjects is

difficult

• The use of imaging biomarkers in these subjects may

aid in risk stratification but randomized trials

utilizing these approaches are required

Assessment of Vascular Risk