Plasma viral load and CD4+ lymphocytes as prognostic markers of HIV-1 infection.
ABSTRACT The rate of disease progression among persons infected with human immunodeficiency virus type 1 (HIV-1) varies widely, and the relative prognostic value of markers of disease activity has not been defined.
To compare clinical, serologic, cellular, and virologic markers for their ability to predict progression to the acquired immunodeficiency syndrome (AIDS) and death during a 10-year period.
Prospective, multicenter cohort study.
Four university-based clinical centers participating in the Multicenter AIDS Cohort Study.
1604 men infected with HIV-1.
The markers compared were oral candidiasis (thrush) or fever; serum neopterin levels; serum beta 2-microglobulin levels; number and percentage of CD3+, CD4+, and CD8+ lymphocytes; and plasma viral load, which was measured as the concentration of HIV-1 RNA found using a sensitive branched-DNA signal-amplification assay.
Plasma viral load was the single best predictor of progression to AIDS and death, followed (in order of predictive strength) by CD4+ lymphocyte count and serum neopterin levels, serum beta 2-microglobulin levels, and thrush or fever. Plasma viral load discriminated risk at all levels of CD4+ lymphocyte counts and predicted their subsequent rate of decline. Five risk categories were defined by plasma HIV-1 RNA concentrations: 500 copies/mL or less, 501 to 3000 copies/mL, 3001 to 10000 copies/mL, 10001 to 30000 copies/mL, and more than 30000 copies/mL. Highly significant (P < 0.001) differences in the percentages of participants who progressed to AIDS within 6 years were seen in the five risk categories: 5.4%, 16.6%, 31.7%, 55.2%, and 80.0%, respectively. Highly significant (P < 0.001) differences in the percentages of participants who died of AIDS within 6 years were also seen in the five risk categories: 0.9%, 6.3%, 18.1%, 34.9%, and 69.5%, respectively. A regression tree incorporating both HIV-1 RNA measurements and CD4+ lymphocyte counts provided better discrimination of outcome than did either marker alone; use of both variables defined categories of risk for AIDS within 6 years that ranged from less than 2% to 98%.
Plasma viral load strongly predicts the rate of decrease in CD4+ lymphocyte count and progression to AIDS and death, but the prognosis of HIV-infected persons is more accurately defined by combined measurement of plasma HIV-1 RNA and CD4+ lymphocytes.
SourceAvailable from: Huldrych F Günthard[Show abstract] [Hide abstract]
ABSTRACT: Best long-term practice in primary HIV-1 infection (PHI) remains unknown for the individual. A risk-based scoring system associated with surrogate markers of HIV-1 disease progression could be helpful to stratify patients with PHI at highest risk for HIV-1 disease progression. We prospectively enrolled 290 individuals with well-documented PHI in the Zurich Primary HIV-1 Infection Study, an open-label, non-randomized, observational, single-center study. Patients could choose to undergo early antiretroviral treatment (eART) and stop it after one year of undetectable viremia, to go on with treatment indefinitely, or to defer treatment. For each patient we calculated an a priori defined "Acute Retroviral Syndrome Severity Score" (ARSSS), consisting of clinical and basic laboratory variables, ranging from zero to ten points. We used linear regression models to assess the association between ARSSS and log baseline viral load (VL), baseline CD4+ cell count, and log viral setpoint (sVL) (i.e. VL measured ≥90 days after infection or treatment interruption). Mean ARSSS was 2.89. CD4+ cell count at baseline was negatively correlated with ARSSS (p = 0.03, n = 289), whereas HIV-RNA levels at baseline showed a strong positive correlation with ARSSS (p<0.001, n = 290). In the regression models, a 1-point increase in the score corresponded to a 0.10 log increase in baseline VL and a CD4+cell count decline of 12/µl, respectively. In patients with PHI and not undergoing eART, higher ARSSS were significantly associated with higher sVL (p = 0.029, n = 64). In contrast, in patients undergoing eART with subsequent structured treatment interruption, no correlation was found between sVL and ARSSS (p = 0.28, n = 40). The ARSSS is a simple clinical score that correlates with the best-validated surrogate markers of HIV-1 disease progression. In regions where ART is not universally available and eART is not standard this score may help identifying patients who will profit the most from early antiretroviral therapy.PLoS ONE 12/2014; 9(12):e114111. DOI:10.1371/journal.pone.0114111 · 3.53 Impact Factor
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ABSTRACT: Flow cytometry (FC) is a single-cell profiling platform for measuring the phenotypes of individual cells from millions of cells in biological samples. FC employs high-throughput technologies and generates high-dimensional data, and hence algorithms for analyzing the data represent a bottleneck. This dissertation addresses several computational challenges arising in modern cytometry while mining information from high-dimensional and high-content biological data. A collection of combinatorial and statistical algorithms for locating, matching, prototyping, and classifying cellular populations from multi-parametric FC data is developed. The algorithmic pipeline, flowMatch, developed in this dissertation consists of five well-defined algorithmic modules to (1) transform data to stabilize within-population variance, (2) identify cell populations by robust clustering algorithms, (3) register cell populations across samples, (4) encapsulate a class of samples with templates, and (5) classify samples based on their similarity with the templates. Components of flowMatch can work independently or collaborate with each other to perform the complete data analysis. flowMatch is made available as an open-source R package in Bioconductor. We have employed flowMatch for classifying leukemia samples, evaluating the phosphorylation effects on T cells, classifying healthy immune profiles, and classifying the vaccination status of HIV patients. In these analyses, the pipeline is able to reach biologically meaningful conclusions quickly and efficiently with the automated algorithms. The algorithms included in flowMatch can also be applied to problems outside of flow cytometry such as in microarray data analysis and image recognition. Therefore, this dissertation contributes to the solution of fundamental problems in computational cytometry and related domains.
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ABSTRACT: Many wild koalas are infected with the koala retrovirus, KoRV, some of which suffer from lymphoma and chlamydial disease. Three subgroups, KoRV-A, KoRV-B and KoRV-J, have so far been described. It is well known that other closely related gammaretroviruses can induce tumours and severe immunodeficiencies in their respective hosts and a possible role for KoRV infection in lymphoma and chlamydial disease in koalas has been suggested. In many wild koalas, KoRV-A has become endogenised, i.e., it is integrated in the germ-line and is passed on with normal cellular genes. In this study, sera from koalas in European zoos and from wild animals in Australia were screened for antibodies against KoRV-A. These naturally infected animals all carry endogenous KoRV-A and two zoo animals are also infected with KoRV-B. The antibody response is generally an important diagnostic tool for detecting retrovirus infections. However, when Western blot analyses were performed using purified virus or recombinant proteins corresponding to KoRV-A, none of the koalas tested positive for specific antibodies, suggesting a state of tolerance. These results have implications for koala vaccination, as they suggest that therapeutic immunisation of animals carrying and expressing endogenous KoRV-A will not be successful. However, it remains unclear whether these animals can be immunised against KoRV-B and immunisation of uninfected koalas could still be worthwhile. Copyright © 2015. Published by Elsevier B.V.Virus Research 01/2015; 198. DOI:10.1016/j.virusres.2015.01.002 · 2.83 Impact Factor