Human Monocytes - CD14, CD16 - Ziegler-Heitbrock


Shift of monocyte subsets along their continuum predicts cardiovascular outcomes.


BACKGROUND AND AIMS: Distribution of monocyte subsets has been shown to predict cardiovascular outcomes. However, monocytes form a continuum and categorization into discrete subsets may be an oversimplification. We herein aimed at establishing whether distribution of monocytes based on CD14 and CD16 fluorescence intensity provides incremental and complementary information on cardiovascular outcomes beyond enumeration of traditional subsets. METHODS: A cohort of 227 patients at high cardiovascular risk was characterized at baseline and followed for a median of 4 years. We quantified monocytes subsets by flow cytometry based on CD14 and CD16 expression and evaluated the continuous distribution of CD14 and CD16 fluorescence within each subset. RESULTS: A consistent shift toward higher CD16 fluorescence intensity within each monocyte subset was observed in patients with type 2 diabetes, despite no change in their frequencies. Patients with coronary artery disease (CAD) at baseline showed a doubling of CD14++CD16+ intermediate monocytes and a shift of non-classical and classical monocytes towards intermediates ones. During follow-up, cardiovascular death or cardiovascular events occurred in 26 patients, who showed monocyte skewing similar to those of patients with baseline CAD. In fully adjusted Cox proportional hazard regression models, higher CD16 expression on classical monocytes, but not the level of intermediate monocytes or other subsets, independently predicted adverse cardiovascular outcomes. CONCLUSIONS: Shift of monocyte subsets along the CD14/CD16 continuum, more than their frequencies, predicted adverse cardiovascular outcomes. This finding illustrates how the concept of monocyte continuum can be used to model the cardiovascular risk.

Authors: Cappellari R, D Anna M, Bonora BM, Rigato M, Cignarella A, Avogaro A, Fadini GP.
Journal: Atherosclerosis. 2017 Nov;266:95-102
Year: 2017
PubMed: Find in PubMed