Monocyte-activation phenotypes are associated with biomarkers of inflammation and coagulation in chronic HIV infection

Abstract

Background: Soluble biomarkers of inflammation predict non-AIDS related morbidity and mortality among human immunodeficiency virus (HIV)-infected persons. Exploring associations between plasma biomarkers and cellular phenotypes may identify sources of excess inflammation.

Methods: Plasma biomarkers (interleukin 6 [IL-6] level, D-dimer level, high-sensitivity C-reactive protein [hsCRP] level, soluble CD14 [sCD14] level, and soluble CD163 [sCD163] level) were measured from cryopreserved samples from the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (SUN Study). We performed immunophenotyping of peripheral blood mononuclear cells for markers of T-cell and monocyte activation, maturation, and migration. We evaluated associations between cellular phenotypes and soluble biomarkers by Spearman rank correlation and multivariate linear regression.

Results: Participants' (n = 670) median age was 41 years, 88% were prescribed antiretroviral therapy, 72% had a plasma HIV RNA load of <400 copies/mL, and the median CD4(+) T-lymphocyte count was 471 cells/µL. After adjustment, CD14(++)CD16(+) monocytes were associated with higher levels of IL-6, hsCRP, and sCD163; associations with IL-6 and hsCRP persisted in persons with suppressed HIV replication. While CCR5(+) monocytes positively associated with D-dimer levels, CCR2(+) monocytes were inversely associated with hsCRP levels.

Conclusions: Plasma inflammatory biomarkers that predict morbidity and mortality were strongly associated with monocyte activation and migration, modestly associated with T-cell maturation, and not associated with CD8(+) T-cell activation phenotypes. These findings suggest that strategies to control monocyte activation warrant further investigation.

Keywords: C-reactive protein; D-dimer; HIV; IL-6; immune activation; monocytes.

Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Figures

Figure 1.

Representative flow cytometry graphs depicting selected cellular phenotypes. Representative plots showing selected phenotypes. Selected monocytes subsets are shown, defined by CD14 and CD16 expression (A) and by CCR2 and CX3CR1 expression (B). Selected T-cell activation phenotypes are also depicted, defined by HLA-DR and CD38 expression (C) and by CD57 and CD28 expression (D). For compete gating methods, see Supplementary Figure 1.

Figure 2.

Correlations between phenotypes of immune cells and soluble plasma biomarker levels among 670 participants in the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy. Spearman rank correlations of soluble biomarkers with monocyte activation and migration markers (A) and T-cell activation and maturation phenotypes (B) with soluble biomarkers. Colored bars represent statistically significant correlations (P ≤ .01) between the cellular marker and plasma biomarker levels. Open bars represent nonsignificant correlations. Abbreviations: hsCRP, high-sensitivity C-reactive protein; IL-6, interleukin 6; sCD14, soluble CD14; sCD163, soluble CD163.

Figure 2.

Correlations between phenotypes of immune cells and soluble plasma biomarker levels among 670 participants in the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy. Spearman rank correlations of soluble biomarkers with monocyte activation and migration markers (A) and T-cell activation and maturation phenotypes (B) with soluble biomarkers. Colored bars represent statistically significant correlations (P ≤ .01) between the cellular marker and plasma biomarker levels. Open bars represent nonsignificant correlations. Abbreviations: hsCRP, high-sensitivity C-reactive protein; IL-6, interleukin 6; sCD14, soluble CD14; sCD163, soluble CD163.