286, P = 0.038) HDL-c¶ (β = 0.411; CI 0.059, 0.764; P = 0.023) LDL-c¶ (β = 0.185; CI 0.020, 0.349; P = 0.029) Δ Total-c§ (r = −0.315, P = 0.026) LDL-c* (r = 0.346, P = 0.041). CD4* (β = −0.001; CI −0.002, −0.0001; P = 0.037) TC arm (β = −0.739; CI −1.229,

−0.249; P = 0.004) Age (β = −0.049; CI −0.089, −0.009; P = 0.018) Previous HAART (β = 0.222; CI 0.030, 0.414; P = 0.024) HDL-c† (β = 0.939; CI 0.187, 1.691; P = 0.016) VL¶ (r = 0.325, P = 0.046) HDL-c¶ (r = 0.294, P = 0.042) TG* (r = −0.299, P = 0.029) TG* (β = −0.132; CI −0.248, −0.016; P = 0.027) TC¶ (β = 0.229; CI 0.013, 0.445; P = 0.038) Viral load strongly correlated with MCP-1 concentration at months 12 and 24; no correlations were found between viral load and the other biomarkers. Several correlations were found between this website the biomarkers and lipid variables. MCP-1 negatively correlated with baseline HDL-c at months 12, 24 and 36. Multivariate analysis confirmed selleck this association: lower HDL-c levels at baseline were associated with higher plasma MCP-1 concentrations at all time-points. sVCAM-1 negatively correlated with HDL-c at baseline and at the three time-points. In addition, the sVCAM-1 increase

at month 36 from baseline correlated with total-c and LDL-c. Some of these correlations persisted in the multivariate analysis. Correlations and multivariate analysis of t-PA, sP-selectin and sCD40L are showed in Table 2. Viral load negatively correlated with total-c (r = −0.416, P = 0.002; r = −0.418, P = 0.002, and r = −0.643, P < 0.001 at months 12, 24 and 36, respectively), HDL-c (r = −0.385, P = 0.017; r = −0.340, P = 0.030, and r = −0.322, P = 0.045 at months 12, 24 and 36, respectively) and LDL-c (r = −0.491, P = 0.004; r = −0.708, P < 0.001, and r = −0.583, P < 0.001 at months 12, 24 and 36, respectively). In this study, cART interruption was associated with a rise in the concentrations

Parvulin of biomarkers involved in various pathways related to the pathogenesis of atherosclerosis, including endothelial dysfunction (MCP-1 and sVCAM-1), platelet activation (sP-selectin and sCD40L), and coagulation (t-PA). The increases persisted at 36 months of follow-up. In addition, correlations were documented among HIV viral load, lipid values, and plasma concentrations of some biomarkers. The biomarkers studied express a proatherogenic environment that is likely to be involved in the increased cardiovascular risk observed in the SMART study [4]. The risk of developing cardiovascular disease is higher in HIV-infected patients than in the general population. Antiretroviral therapy, classic risk factors, and HIV itself may contribute to the pathogenesis of cardiovascular disease in these patients [12]. Although the mechanism by which HIV infection produces early atherosclerosis is not completely understood, HIV-induced endothelial dysfunction and chronic inflammation seem to be important in the formation of atherosclerotic plaques [13].