Biomarkers of progression after HIV acute/early infection: nothing compares to CD4+ T-cell count?

GABRIELA TURK; NATALIA LAUFER; CÉSAR TRIFONE; MARÍA PÍA HOLGADO; HORACIO SALOMÓN; MARÍA MAGDALENA GHERARDI; OMAR SUED; M. HORMANSTORFER; JIMENA SALIDO; JULIANA FALIVENE; MARÍA INÉS FIGUEROA; MARÍA DE LOS ANGELES PANDO; PEDRO PURY; GHIGLIONE, YANINA; ROMINA COLOCCINI; MARÍA JULIA RUIZ; MARÍA PAULA CARUSO; LUIS GIAVEDONI; DANIEL RABINOVICH

Paris, Francia

Conferencia; 9th IAS Conference on HIV Science; 2017

Background: Progression of HIV infection is variable among individuals. Despite implementation of effective ART, definition of disease progression biomarkers is still fundamental. Apart from CD4+ T-cell count (CD4TC) and viral load (VL), several parameters have been individually proposed as biomarkers by our group and others. Here, we aimed to categorize their predictive potential using decision trees and analyze their possible implementation in the clinical setting.Methods: A total of seventy-five subjects were enrolled during acute/early HIV infection (< 6 months postinfection). CD4TC and VL determinations were performed at enrollment (baseline sample) and during 1 year. This study only included samples and data from subjects while off-treatment. Immune activation (HLA-DR and CD38 expression), HIV-specific immune response (ELISPOT) and HLA haplotype were determined in a subset of 41 individuals at baseline sample. Within this group, plasma levels of 39 cytokines were determined by Luminex in 27 individuals. Progression was defined as CD4TC decreasing below 350 cells/µl or experiencing AIDS-related B/C events within 12 months post-infection. Data was analyzed by machine learning and non-parametric methods and adjusted for multiple comparisons. Variable hierarchization was performed by Weka correlation based feature selection and J48 decision treeResults: Plasma IL-10, IP-10, sIL-2Rα and TNF-α directly correlated with baseline VL while IL-2, TNF-α, FGF-2 and Mip-1β inversely correlated with CD4+ T-cell activation (p< 0.05). However, none of these cytokines had good predictive value to distinguish progressors from non-progressors. Similarly, immune activation, HIV-specific immune responses and HLA haplotypes had lower discrimination power when compared to clinical parameters (CD4TC and VL). Baseline CD4TC was the most potent variable to distinguish progressors from non-progressors with a cut-off of 436 cells/µl (accuracy=0.93, k-Cohen=0.85)Conclusions: In our cohort, baseline CD4TC was the strongest predictor of disease progression early after infection. Limited discerning power of the other factors might be related to frequency, variability and/or sampling time. Surprisingly, high baseline CD4TCs were observed even in subjects that progressed rapidly, reinforcing the importance of early ART initiation. Also, efforts should be made to develop and make available CD4TC determination techniques to all possible settings. Future studies based on decision trees to identify biomarkers of posttreatment control are warrantied.