Mentored Scientist Award

Are extracellular vesicles involved in the pathogenesis of HIV-associated cardiovascular disease?

Headshot of Erika Marques de Menezes, PhD
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HIV-infected individuals on antiretroviral therapy have higher than expected rates of cardiovascular disease (CVD) than uninfected individuals, and HIV-induced chronic inflammation is believed to be directly and causally associated with the accelerated atherosclerosis development. Prior studies have revealed that chronic inflammatory states, such as atherosclerosis, show significantly increased levels of circulating endothelium-derived extracellular vesicles (EVs), which are preferentially taken up by monocytes and lead to monocyte activation. EVs are potentially able to transfer their biological content by membrane fusion with the recipient cell, can directly activate target cell surface receptors by bioactive ligands and proteins, and have potential as diagnostic and prognostic biomarkers, which has raised significant interest in the role of EVs in CVD. In addition to monocytes, recent studies have implicated a role for B cells as important immune cells in atherogenesis, revealing that alterations in late-phase activated B cells correlate with carotid artery intima-media thickness (CIMT). While the evidence supporting an association between HIV and CVD is strong, the main mechanisms underlying the association are not well defined. The current proposal is innovative and will reveal whether EVs with an inflammatory phenotype will be related to CIMT in HIV-infected individuals. To date, limited data exist about EVs as predictors of atherosclerosis in HIV-infected subjects at risk for CVD. Our hypothesis is that increased levels of EVs expressing monocyte and B cell markers may serve as novel predictors of CVD in HIV-infected individuals and is consistent with an important role for monocyte and B cell activation in the progression of HIV-related cardiovascular pathology. EV data will be log10-transformed to address rightward skewing. The parametric and nonparametric tests will be used for unpaired comparisons, and false discovery rate correction methods will be computed using the Benjamini-Hochberg method. Statistical significance will be set at a p-value of 0.05.