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Abstract Number: 373

Biomarkers of Cardiac Dysfunction and Inflammation in Plasma Predict Occult Coronary Plaque Burden and Composition in Rheumatoid Arthritis

George A. Karpouzas1, Joel Estis2, John Todd2 and Matthew Budoff3, 1Rheumatology, Harbor-UCLA Medical Center, Torrance, CA, 2Singulex, Alameda, California, Alameda, CA, 3Cardiology, Harbor-UCLA Medical Center, Torrance, CA

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Atherosclerosis, coronary artery disease, interleukins (IL) and rheumatoid arthritis (RA)

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Session Information

Title: Rheumatoid Arthritis - Clinical Aspects: Novel Biomarkers and Other Measurements of Disease Activity

Session Type: Abstract Submissions (ACR)

Background/Purpose

Rheumatoid arthritis (RA) is associated with accelerated coronary atherogenesis, myocardial infarction, and mortality. We previously reported a higher prevalence, severity, and different composition of occult coronary plaque in patients with RA compared to age and gender matched non-rheumatic disease controls (NRD). We now explore whether various plasma inflammatory biomarkers, or their combinations, predict occult coronary plaque presence, various burden outcomes, and composition in the same cohort of patients with RA. 

Methods

One hundred and fifty RA subjects without symptoms or prior diagnosis of cardiovascular disease underwent 64-slice computed tomography angiography (CTA). Coronary artery calcium score (CAC), segment involvement score (SIS- n of segments with plaque), stenosis severity score (sum of individual segmental stenosis- SSS) and plaque burden score (sum of segmental plaque burden- PBS) were computed. Plaques were further characterized as non-calcified (NCP), mixed (MP), or calcified (CP). High-sensitivity cardiac Troponin-I (cTnI), tumor necrosis factor-alpha (TNFα), vascular endothelial growth factor (VEGF), interleukin-6 (IL-6), interleukin-17A and F (IL-17A, IL-17F), were quantified at the time of CTA, using Erenna immunoassay (Singulex, Alameda, CA). Associations of individual biomarkers with all plaque outcomes were evaluated with linear regression models. Ability of individual or combinations of binarized biomarkers to predict plaque outcomes was explored in logistic regression models adjusted for age and gender (model 1), or additional cardiac risk factors (CRFs, model 2). 

Results

Higher tertiles of cTnI correlated with plaque prevalence, as well as increasing CAC, SIS, SSS, and PBS (p-values 0.006, 0.005, 0.01, and 0.009 respectively- not shown). IL-6 and cTnI individually and independently predicted various plaque parameters after age and gender adjustments (model 1, table 1). The combination of high cTnI with high IL-6 predicted plaque burden after adjustments both for age and gender, as well as additional CRFs (model 2- table 1). Very high-risk plaque outcomes for future cardiac events (CAC>100, SIS>5, SSS>5, obstructive plaque, or composite outcome) were best predicted by cTnI alone. Similarly, cTnI was the only biomarker predicting presence of higher-risk NCP or MP [OR (95% CI) of 2.37 (1.13-4.94)], however, significance was lost after age and gender adjustments [1.97 (0.92-4.24)].

Conclusion

In patients with RA, biomarkers of cardiac dysfunction (cTnI) and inflammation (IL-6) may predict the presence, various burden outcome severity, and composition of occult coronary plaque as evaluated by CTA. Their associations and prognostic implications for atherosclerosis deserve further evaluation.

Table 1

outcome

Unadjusted

OR (95% CI)

Model 11

OR (95% CI)

Model 22          OR (95% CI)

c-TnI

CAC (>0 vs. 0)

2.5 (1.2-5.2)

1.8 (0.8-4.0)

1.7 (0.8-4)

CAC>100 vs.≤100

7.1 (2.5-20.7)

6 (1.9-19)

10.4 (2.4-45.5)

SIS (>0 vs. 0)

2.8 (1.2-6.2)

2.0 (0.8-4.8)

2.3 (0.8-6.9)

SIS>5 vs. SIS≤5

4 (1.2-13.6)

2.5 (0.7-9.4)

3.6 (0.9-14.7)

SSS (>0 vs. 0)

2.8 (1.2-6.2)

2.0 (0.8-4.8)

2.3 (0.8-6.9)

SSS>5 vs. SSS≤5

2.9 (1.1-7.7)

2.2 (0.8-6.3)

2.6 (0.9-8)

PBS (>2 vs. ≤2)

3.6 (1.7-7.4)

2.9 (1.3-6.5)

3.2 (1.4-7.5)

Obstructive plaque

3.9 (1.2-12.5)

3.1 (0.9-10.7)

3.6 (0.9-13.9)

Composite outcome*

3.2 (1.2-8.3)

2.4 (0.9-6.8)

2.8 (0.9-8.2)

IL-6

CAC (>0 vs. 0)

1.6 (0.8-3.2)

2.0 (0.9-4.4)

1.6 (0.7-3.7)

SIS (>0 vs. 0)

2.1 (0.9-4.9)

3.0 (1.1-7.8)

2.0 (0.8-5.0)

SSS (>0 vs. 0)

2.1 (0.9-4.9)

3.0 (1.1-7.8)

2.0 (0.8-5.0)

PBS (>2 vs. ≤2)

2.1 (1.0-4.2)

2.8 (1.2-6.2)

2.0 (0.8-4.7)

c-TnI+IL-6

CAC (>0 vs. 0)

2.7 (1.1-7.0)

2.1 (0.7-5.9)

1.9 (0.6-5.5)

SIS (>0 vs. 0)

2.7 (1.1-6.3)

2.1 (0.9-5.3)

1.7 (0.7-4.6)

SSS (>0 vs. 0)

2.7 (1.1-6.3)

2.1 (0.9-5.3)

1.7 (0.7-4.6)

PBS (>2 vs. ≤2)

5.1 (1.9-13.8)

4.4 (1.5-12.7)

3.9 (1.3-11.6)

1. adjusted for age, gender, cTnI, IL-6

2. Adjusted for age, gender, hypertension, diabetes, dyslipidemia, smoking, body mass index, prednisone use, cTnI, IL-6

* composite outcome: SIS>5, or SSS>5, or obstructive plaque


Disclosure:

G. A. Karpouzas,
None;

J. Estis,

Singulex,

3,

Singulex,

1;

J. Todd,

Singulex,

1,

Singulex,

3;

M. Budoff,
None.

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