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Viruses 2018, 10(1), 34; doi:10.3390/v10010034

Biomarkers of Progression after HIV Acute/Early Infection: Nothing Compares to CD4+ T-cell Count?

1
CONICET-Universidad de Buenos Aires, Instituto de Investigaciones Biomédicas en Retrovirus y SIDA (INBIRS), Universidad de Buenos Aires- CONICET, Paraguay 2155 Piso 11, Buenos Aires C1121ABG, Argentina
2
Fundación Huésped, Buenos Aires C1202ABB, Argentina
3
Hospital Juan A. Fernández, Unidad Enfermedades Infecciosas, Buenos Aires C1425AGP, Argentina
4
Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
5
Facultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina
*
Author to whom correspondence should be addressed.
Received: 12 December 2017 / Revised: 10 January 2018 / Accepted: 12 January 2018 / Published: 13 January 2018
(This article belongs to the Special Issue Homage to Mark Wainberg)
View Full-Text   |   Download PDF [1689 KB, uploaded 13 January 2018]   |  

Abstract

Progression of HIV infection is variable among individuals, and definition disease progression biomarkers is still needed. Here, we aimed to categorize the predictive potential of several variables using feature selection methods and decision trees. A total of seventy-five treatment-naïve subjects were enrolled during acute/early HIV infection. CD4+ T-cell counts (CD4TC) and viral load (VL) levels were determined at enrollment and for one year. Immune activation, HIV-specific immune response, Human Leukocyte Antigen (HLA) and C-C chemokine receptor type 5 (CCR5) genotypes, and plasma levels of 39 cytokines were determined. Data were analyzed by machine learning and non-parametric methods. Variable hierarchization was performed by Weka correlation-based feature selection and J48 decision tree. Plasma interleukin (IL)-10, interferon gamma-induced protein (IP)-10, soluble IL-2 receptor alpha (sIL-2Rα) and tumor necrosis factor alpha (TNF-α) levels correlated directly with baseline VL, whereas IL-2, TNF-α, fibroblast growth factor (FGF)-2 and macrophage inflammatory protein (MIP)-1β correlated directly with CD4+ T-cell activation (p < 0.05). However, none of these cytokines had good predictive values to distinguish “progressors” from “non-progressors”. Similarly, immune activation, HIV-specific immune responses and HLA/CCR5 genotypes had low discrimination power. Baseline CD4TC was the most potent discerning variable with a cut-off of 438 cells/μL (accuracy = 0.93, κ-Cohen = 0.85). Limited discerning power of the other factors might be related to frequency, variability and/or sampling time. Future studies based on decision trees to identify biomarkers of post-treatment control are warrantied. View Full-Text
Keywords: HIV; biomarkers; acute infection; disease progression; decision trees; soluble plasma factors; HLA; immune responses HIV; biomarkers; acute infection; disease progression; decision trees; soluble plasma factors; HLA; immune responses
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MDPI and ACS Style

Turk, G.; Ghiglione, Y.; Hormanstorfer, M.; Laufer, N.; Coloccini, R.; Salido, J.; Trifone, C.; Ruiz, M.J.; Falivene, J.; Holgado, M.P.; Caruso, M.P.; Figueroa, M.I.; Salomón, H.; Giavedoni, L.D.; Pando, M.Á.; Gherardi, M.M.; Rabinovich, R.D.; Pury, P.A.; Sued, O. Biomarkers of Progression after HIV Acute/Early Infection: Nothing Compares to CD4+ T-cell Count? Viruses 2018, 10, 34.

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