Abstract
HIV causes inflammatory immune responses that induces the exhaustion of CD4+ T cells. We hypothesize that not only does HIV use the vesiculation pathway for its assembly and dissemination, but also exploits the transfer of extracellular vesicles to mediate immune signaling. Extracellular vesicles express different markers on their surface, depending on the cells from which they originate, including bone-forming cells. These vesicles may contain RNA, lipids, and proteins, providing valuable information about the health status of the cell of origin. Therefore, we will work with the interaction between HIV and bone metabolism and the involvement of extracellular vesicles and pro-inflammatory cytokines to better understand the HIV-mediated molecular mechanisms in bone cells. Objective: To evaluate the concentration of extracellular vesicles, particularly those derived from osteoclasts in HIV-seropositive subjects with or without osteopenia and in HIV-negative healthy subjects. Methods: A cross-sectional study will be conducted on 60 adult women, aged between 18 and 40. Study participants will be subdivided in three groups, HIV+ women on successful antiretroviral therapy (ART, HIV RNA level <50 copies/ml) with osteopenia (n=20) or with normal bone mineral density group (n=20) and HIV-negative healthy control subjects (n=20). Cryopreserved plasma samples will be tested to determine the concentrations of extracellular vesicles using the fluorochrome-conjugated monoclonal antibodies, including CD41a-PerCP/Cy5.5 (platelet markers), CD3-PerCP/Cy5.5, CD19-Alexa/700 (T and B cell markers), CD14-APC/Cy7 (monocyte marker), CD254/biotin (RANK ligand), and annexin V-PE (bone cell markers). Plasma levels of IL-17 and tumor necrosis factor-± (TNF-±) will be assayed using the standard-sensitivity Milliplex Luminex assay. Statistical tests will be performed to test for equality between groups. Analysis of variance will be used to identify significant differences among groups, using an appropriate post-test. Correlations between quantitative variables will be assessed by linear regression. For the analysis values will be considered significant when p<0.05, and correction for multiple comparisons will be performed.
|