Short Communication: Carotid Artery Plaque Burden in HIV Is Associated with Soluble Mediators and Monocytes

Abstract

Maximum carotid plaque thickness (MCPT) measures the largest plaque thickness in the carotid artery and reflects atherosclerosis plaque burden. MCPT may be a better predictor of cardiovascular disease than carotid artery intima-media thickness (cIMT) because it identifies potential unstable arterial atherosclerosis plaques. We assessed the relationships of monocyte and T cell populations and plasma soluble mediators with MCPT measures. We performed a cross-sectional and small follow-up analysis in people living with HIV (PLWH) aged >40 years on stable antiretroviral therapy (ART) >6 months. MCPT was acquired by high-resolution B-mode ultrasound. Existing monocyte subsets and T cell activation frequencies were determined by flow cytometry and plasma mediators of inflammation and apolipoproteins were measured by Luminex assay. One hundred twenty-five ART-treated PLWH, 88% male, 55% Caucasian, with a median age of 51 years, median CD4 count of 477 cells/μL (Q1: 325, Q3: 612), 84% undetectable plasma HIV RNA (<50 copies/mL). Twenty-five PLWH had detectable carotid plaque. MCPT correlated with monocyte chemoattractant protein-1 (MCP-1; r = 0.487, p = .016), tumor necrosis factor-α (TNF-α; r = 0.474 p = .019), soluble vascular cell adhesion molecule-1 (sVCAM-1; r = 0.472, p = .020), apolipoprotein B6 (ApoB6; r = −0.473, p = .019), and interleukin-6 (IL-6; r = 0.455, p = .025). In a multivariable regression model, MCP-1, TNF-α, and sVCAM-1 remained significant after adjustment for age. Carotid plaque burden was associated with increased inflammatory, monocyte, and endothelial measures, including MCP-1, TNF-α, and sVCAM-1 levels. Further investigation on the evolution or severity of plaque burden in this population is warranted.

Introduction

Cardiovascular disease (CVD) has become an important cause of morbidity and mortality in persons living with human immunodeficiency virus-1 (PLWH).¹ HIV infection can lead to chronic inflammation and proatherogenic processes.² Nonclassical monocytes are suggested to be responsible for adhering to vascular surfaces and infiltrating endothelial spaces to promote atherogenesis³ and noninvasive imaging has been used to assess the risk of cardiovascular events.⁴ Maximum carotid plaque thickness (MCPT) may be a better predictor of cardiovascular disease than carotid artery intima-media thickness (cIMT) because it identifies potential unstable arterial atherosclerosis plaques. In the Framingham Offspring Study cohort, MCPT in the internal carotid artery significantly predicted CVD events⁴ as it can identify potential unstable arterial atherosclerotic plaques.⁵ This study sought to assess the relationship of monocyte phenotypes and soluble plasma biomarkers with MCPT among participants on stable antiretroviral therapy (ART) over time.

Materials and Methods

We performed a cross-sectional analysis of participants enrolled into the Hawaii Aging with HIV-Cardiovascular Cohort (HAHC-CVD), a 5-year longitudinal study conducted from 2011 to 2016, investigating the role of immune activation and mitochondrial-specific oxidative stress on the pathogenesis of CVD in PLWH.⁶ A 2-year follow-up analysis were performed on a subset of participants with available clinical and blood specimen data. Written informed consent was obtained from all participants. This study was IRB approved by the University of Hawaii.

B-mode ultrasound images of the right carotid artery were acquired from the far wall of the distal, common carotid artery (CCA), and internal carotid bifurcation (BIF), which were obtained within 2 months of clinical visits and blood collections, including peripheral blood mononuclear cells (PBMCs). Imaging took place at The Queen's Medical Center, Honolulu, Hawaii, and were assessed and measured with automated computerized edge detection at the University of Southern California Atherosclerosis Research Unit Core Imaging and Reading Center. Average measurement of intima-media thickness was used to obtain cIMT. MCPT was identified by measuring the largest plaque found in either the carotid BIF, internal carotid artery, or CCA.

We used previously generated immunophenotyping data assessing monocyte and T cell subpopulations frequencies.⁷ In brief, cryopreserved PBMCs were surface stained to identify monocyte subpopulations using conjugated monoclonal antibodies (mAbs), V500-conjugated antiCD3, Qdot605-conjugated anti-CD14, Alexa700-conjugated anti-CD16, PE-Cy7-conjugated anti-CD56, PE-Cy7-conjugated anti-CD19, PE-Cy7-conjugated anti-CD20, and APC-H7-conjugated HLA-DR mAbs.⁸ The analysis excluded lymphocytes, B cells, and natural killer cells. Monocytes identified in the HLA-DR positive gate were further defined for monocyte subpopulations by the expression of CD14 and CD16 as previously described.⁶ All antibodies were from BD Biosciences, except for Q605-conjugated anti-CD14 and Live/Dead yellow amine-reactive dye (Life Technologies). Stained PBMCs were acquired by flow cytometry, using a 4-laser custom BD-Fortessa instrument (Becton Dickinson) and analyzed with FlowJo software (Treestar, Inc., Ashland, OR) as previously described.⁷ Total monocyte count was calculated from white blood cell count and percentage monocyte values on the complete blood count conducted as part of entry evaluations on the same blood specimen utilized for flow cytometry as previous reports.⁷

Similarly, previously generated plasma soluble biomarkers from this cohort were used in the analysis. These markers were measured with a Milliplex Human Cardiovascular Disease panels (EMD Millipore). Soluble biomarkers of inflammation, including monocyte chemoattractant protein-1 (MCP-1), sE-selectin, soluble vascular cell adhesion molecule-1 (sVCAM-1), soluble intercellular adhesion molecule-1 (sICAM-1), matrix metalloproteinase-9 (MMP-9), myeloperoxidase (MPO), tissue plasminogen activator-1 (tPA-1), C-reactive protein (CRP), serum amyloid A (SAA), serum amyloid P (SAP), interleukin-1β (IL-1β), IL-6, IL-8, IL-10, vascular endothelial growth factor (VEGF), interferon-γ (IFN-γ), N-terminal pro b-type natriuretic peptide (NT-ProBNP), tumor necrosis factor-α (TNF-α), and apolipoprotein B6 (ApoB6), were assessed as stated by the manufacturer's protocols.⁶

Associations between baseline MCPT and soluble biomarkers were evaluated by Spearman correlation. Group comparison on numerical and categorical variables were performed using Mann–Whitney U test and chi-square tests, respectively. Significant factors associated with MCPT were then analyzed using linear regression analysis adjusted for age. A two-sided p-value <.05 was considered statistically significant. Analyses were performed by SPSS (Version 24; IBM, Armonk, NY).

Results

A total of 125 participants had available monocyte phenotypic characterization data and plasma biomarkers. The median age of the participants was 51 years. Majority were male (88%) and Caucasian (55%). Twenty-five individuals had detectable carotid plaque. HIV-infected individuals with and without presence of carotid plaque had similar rates of undetectable plasma HIV RNA (<50 copies/mL) (84%). There was no significant difference in CD4 count between the participants with presence of carotid plaque [466.0 cells/mm³ (291.0, 718.5)] and those without carotid plaque [478.5 cells/mm³ (339.3, 606.3)]. There was no significant difference in baseline characteristics among participants with and without the presence of carotid plaque, including age, history of hypertension, diabetes, and tobacco use, median blood pressure and lipid parameters (Supplementary Table S1).

Using Spearman's correlation, MCPT was significantly positively correlated with MCP-1 (r = 0.487, p = .016), TNF-α (r = 0.474, p = .019), sVCAM-1 (r = 0.472, p = .020), and IL-6 (r = 0.455, p = .025). There was a borderline significance with nonclassical monocytes (r = 0.409, p = .073). In addition, MCPT was found to be negatively correlated with ApoB6 (r = −0.473, p = .019). Nonclassical monocytes, MCP-1, TNF-α, sVCAM-1, IL-6, and ApoB6 were chosen for multivariable linear regression of MCPT, adjusted for age. MCP-1, TNF-α, and sVCAM-1 were significantly associated with MCPT. There was no association seen in adjusted ApoB6 or adjusted IL-6. Results of Spearman's correlation and multivariable linear regression adjusted for age are shown in Table 1.

Table 1.

Association of Variables of Maximum Carotid Artery Plaque Thickness in Study Participants

Variable	Unadjusteda		Adjusted coefficientb
	Rho	p	β coefficient	p
MCP-1	0.487	.016	0.488	.016
TNF-α	0.474	.019	0.444	.030
sVCAM-1	0.472	.020	0.521	.009
Nonclassical monocytes	0.409	.073	0.351	.137
ApoB6	−0.473	.019	−0.280	.211
IL-6	0.455	.025	0.150	.485

^aSpearman correlation.

^bMultivariable regression adjusting for age.

ApoB6, apolipoprotein B6; IL-6, interleukin-6; MCP-1, monocyte chemoattractant protein-1; sVCAM-1, soluble vascular cell adhesion molecule-1; TNF-α, tumor necrosis factor-α.

In a subset of 15 participants who had follow-up cIMT assessments, 6 showed increased MCPT, whereas 9 showed decreased MCPT. There was no correlation between MCPT changes and tobacco or illicit drug use, changes in total cholesterol, or cardiovascular medications.

Discussion

In this study, we identified three soluble mediators MCP-1, TNF-α, and sVCAM-1 that individually correlated with atherosclerosis plaque as measured by MCPT in PLWH on stable ART. Previously, we showed that cIMT of the CCA and the BIF were associated with HIV infection in a multicenter cohort study.⁹ Furthermore, we found positive correlations of cIMT-BIF and cIMT-CCA, with MCP-1, TNF-α, and nonclassical monocytes, suggesting that these factors are associated with atherosclerotic vascular disease in the CCA.⁸ Feinstein et al. reported that MCPT in combination with cIMT was a superior method in detecting coronary artery disease.¹⁰ Gepner et al. also showed that carotid plaque presence in comparison with risk factors improved predictions of CVD events in PLWH.¹¹ Taken together, our data suggest that nonclassical monocytes are associated with the formation of plaque and a cascade of atherosclerosis events driven by MCP-1, TNF-α, and sVCAM-1 contributing to the accumulation and infiltration of monocytes, which possibly lead to greater plaque thickness among PLWH.

During plaque formation, monocytes respond to chemokines by attaching to endothelial cells and transmigrating into the endothelial space.¹² Once inside the subendothelial space, monocytes respond to inflammation by differentiating into foam cells, secreting chemoattractants, and ultimately sequestering modified lipids into a plaque.¹² We hypothesize that once a plaque is established, growth is perpetuated in part by MCP-1, TNF-α, and sVCAM-1. Proliferation of cells within lesions release hydrolytic enzymes, cytokines, and chemoattractants, resulting in activation of MCP-1, TNF-α, and sVCAM-1. Recruitment of nonclassical monocytes further increases release of MCP-1, which is cytokine specific for regulation and attraction of monocytes. MCP-1 regulates attraction of monocytes through activation of chemokine receptor CCR2.¹³ TNF-α, released from macrophages and T cells, works in concert with MCP-1 as a T-helper type 1 cytokine.¹⁴ Endothelial cells produce VCAM1 for which sVCAM-1 is a direct correlate, allowing binding of the chemoattracted cells to plaque extracellular matrix. In summary, we propose that plaque initiation and evolution is stimulated by release of MCP-1 and TNF-α, whereas sVCAM-1 works to maintain together plaque and accumulating cells.

This study provided clinical and metabolic characterization of the participants in conjunction with the detailed phenotypic characterization of monocytes and plasma biomarkers. Operator variation of cIMT measurements were reduced by using a single sonographer and reading center. Our study was limited by the small sample size, male predominance, and lack of assessment for other infections, such as hepatitis C. The small number of 2-year follow-up participants limited the ability to perform reasonable statistical analyses on follow-up data. We do not have longitudinal monocyte subsets and biomarker values. Owing to this limitation, we do not have the ability to examine the correlation between change in MCPT with the change in monocyte subsets and biomarker levels. In addition, this is a cross-sectional study; despite the association that we found, our results did not confirm the causality of plaque initiation and evolution by MCP-1 and TNF-α.

Conclusion

Maximum carotid artery plaque thickness is associated with increased inflammatory, monocyte, and endothelial cell biomarkers, including MCP-1, TNF-α, and sVCAM-1 in PLWH on stable ART. We speculate that the growth of carotid artery plaque is associated with these biomarkers after the carotid plaque is established.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by the National Institutes of Health (grant numbers: R01HL095135, U54MD007584 and U54MD007601.)

Supplementary Material

Supplementary Table S1