One of the immune activation profiles observed in HIV-1-infected adults with suppressed viremia is linked to metabolic syndrome: The ACTIVIH study

• HIV patients aviremic under antiretroviral therapy present with five different profiles of persistent immune activation.
• One of these profiles is strongly linked to marks of metabolic syndrome.Research in context HIV-infected individuals under treatment present with a global activation of their immune system. We show that these patients may be clustered into five groups of immune activation. One of these groups presented with a high frequency of metabolic disorders known to favour cardiovascular and liver diseases. Our data suggest that particular types of immune activation might pave the way for particular chronic diseases. This might be the case in other situations of chronic immune activation, including aging. Unveiling the molecular links between immune activation and chronic diseases might provide with markers predictive of these diseases and with specific therapeutic targets.

Immune activation in HIV-1-infected individuals is reduced under antiretroviral therapies, but persists, resulting in various morbidities. To better characterize this phenomenon, using a panel of 68 soluble and cell surface markers, we measured the level of activation in circulating CD4+ and CD8+ T cells, B cells, monocytes, NK cells, polynuclear and endothelial cells as well as of inflammation and fibrinolysis in 120 virologic responders over 45 years of age. As compared with age- and sex-matched uninfected individuals, we observed a persistence of activation in all the cell subpopulations analyzed, together with marks of inflammation and fibrinolysis. Two independent hierarchical clustering analyses allowed us to identify five clusters of markers that varied concurrently, and five patient groups, each with the same activation profile. The five groups of patients could be characterized by a marker of CD4+ T cell, CD8+ T cell, NK cell, monocyte activation or of inflammation, respectively. One of these profiles was strongly associated with marks of metabolic syndrome, particularly with hyperinsulinemia (OR 12.17 [95% CI 1.79–82.86], p = 0.011). In conclusion, our study unveils biomarkers linked to metabolic syndrome that could be tested as predictive markers, and opens the way to new therapeutic approaches tailored to each patient group.