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      Absolute CD4 + T cell count overstate immune recovery assessed by CD4 +/CD8 + ratio in HIV-infected patients on treatment

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          Abstract

          Objectives

          To analyse the correlation and concordance between aCD4, CD4%, CD4/CD8, their intra-patient variability, and to compare the immune recovery (IR) rates based on the three parameters in HIV-infected patients after starting antiretroviral therapy.

          Methods

          From a prospectively followed cohort, patients who maintained HIV-RNA suppression in ≥95% of the determinations throughout the follow-up were selected. IR was defined as aCD4 >650/μl, CD4% ≥38% or CD4/CD8 ≥1.

          Results

          A total of 1164 patients with a median follow-up of 5 years were analysed. The increases in aCD4, CD4% and CD4/CD8 were highest during the first year and considerably lower thereafter regardless of baseline aCD4. The annual increases in aCD4 showed poor correlations with those of CD4% (r = 0.143–0.250) and CD4/CD8 (r = 0.101–0.192) but were high between CD4% and CD4/CD8 (r = 0.765–0.844; p<0.001). The median intra-annual coefficients of variation for aCD4, CD4/CD8 and CD4% were 12.5, 8.5 and 6.6, respectively. After five years, 66.7%, 41.6% and 42.1% of the patients reached aCD4 >650/μl, CD4% ≥38%, and CD4/CD8 ≥1, respectively, while only 31% achieved both aCD4 and CD4/CD8 target values.

          Conclusions

          The increases in aCD4 poorly correlate with those of CD4% and CD4/CD8. IR rates based on aCD4 significantly overstate those obtained by CD4% and CD4/CD8. CD4% and CD4/CD8 are more stable markers than aCD4 and should be taken into account to monitor the IR after treatment initiation.

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          Most cited references 33

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          A concordance correlation coefficient to evaluate reproducibility.

           Aigu L. Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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            Effects of early versus delayed initiation of antiretroviral treatment on clinical outcomes of HIV-1 infection: results from the phase 3 HPTN 052 randomised controlled trial.

            Use of antiretroviral treatment for HIV-1 infection has decreased AIDS-related morbidity and mortality and prevents sexual transmission of HIV-1. However, the best time to initiate antiretroviral treatment to reduce progression of HIV-1 infection or non-AIDS clinical events is unknown. We reported previously that early antiretroviral treatment reduced HIV-1 transmission by 96%. We aimed to compare the effects of early and delayed initiation of antiretroviral treatment on clinical outcomes. The HPTN 052 trial is a randomised controlled trial done at 13 sites in nine countries. We enrolled HIV-1-serodiscordant couples to the study and randomly allocated them to either early or delayed antiretroviral treatment by use of permuted block randomisation, stratified by site. Random assignment was unblinded. The HIV-1-infected member of every couple initiated antiretroviral treatment either on entry into the study (early treatment group) or after a decline in CD4 count or with onset of an AIDS-related illness (delayed treatment group). Primary events were AIDS clinical events (WHO stage 4 HIV-1 disease, tuberculosis, and severe bacterial infections) and the following serious medical conditions unrelated to AIDS: serious cardiovascular or vascular disease, serious liver disease, end-stage renal disease, new-onset diabetes mellitus, and non-AIDS malignant disease. Analysis was by intention-to-treat. This trial is registered with ClinicalTrials.gov, number NCT00074581. 1763 people with HIV-1 infection and a serodiscordant partner were enrolled in the study; 886 were assigned early antiretroviral treatment and 877 to the delayed treatment group (two individuals were excluded from this group after randomisation). Median CD4 counts at randomisation were 442 (IQR 373-522) cells per μL in patients assigned to the early treatment group and 428 (357-522) cells per μL in those allocated delayed antiretroviral treatment. In the delayed group, antiretroviral treatment was initiated at a median CD4 count of 230 (IQR 197-249) cells per μL. Primary clinical events were reported in 57 individuals assigned to early treatment initiation versus 77 people allocated to delayed antiretroviral treatment (hazard ratio 0·73, 95% CI 0·52-1·03; p=0·074). New-onset AIDS events were recorded in 40 participants assigned to early antiretroviral treatment versus 61 allocated delayed initiation (0·64, 0·43-0·96; p=0·031), tuberculosis developed in 17 versus 34 patients, respectively (0·49, 0·28-0·89, p=0·018), and primary non-AIDS events were rare (12 in the early group vs nine with delayed treatment). In total, 498 primary and secondary outcomes occurred in the early treatment group (incidence 24·9 per 100 person-years, 95% CI 22·5-27·5) versus 585 in the delayed treatment group (29·2 per 100 person-years, 26·5-32·1; p=0·025). 26 people died, 11 who were allocated to early antiretroviral treatment and 15 who were assigned to the delayed treatment group. Early initiation of antiretroviral treatment delayed the time to AIDS events and decreased the incidence of primary and secondary outcomes. The clinical benefits recorded, combined with the striking reduction in HIV-1 transmission risk previously reported, provides strong support for earlier initiation of antiretroviral treatment. US National Institute of Allergy and Infectious Diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.
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              HIV-Infected Individuals with Low CD4/CD8 Ratio despite Effective Antiretroviral Therapy Exhibit Altered T Cell Subsets, Heightened CD8+ T Cell Activation, and Increased Risk of Non-AIDS Morbidity and Mortality

              Introduction It is now anticipated that HIV-infected adults who have access to modern antiretroviral therapy (ART) should be able to suppress HIV replication indefinitely. Although treatment-mediated increases in the peripheral CD4 count are associated with reduced morbidity and mortality, compared to age-matched individuals without HIV infection, those on ART have a higher risk of morbidity and mortality. This risk is predicted in part by the on therapy CD4 count, although achieving an apparent normal CD4 count may not fully restore health [1]–[5]. Indeed, it has been shown that even those treated patients with CD4+ T cell counts above 500 cells/mm3, a further CD4+ T cell count increase is still associated with a slight benefit in terms of mortality [6]. The decreased life expectancy during ART-mediated viral suppression is largely explained by a higher than expected risk of non-AIDS-morbidity, a term that entails a group of conditions generally associated with aging, including cardiovascular, renal, liver, neurologic, and bone disease, as well as cancer [4], [7], [8]. While the mechanisms driving the increased burden of aging-associated disease in HIV-infected individuals are not fully understood, an emerging body of evidence suggests that persistent innate and adaptive immune dysfunction and/or activation are major risk factors [9]–[12]. Many of the immunologic abnormalities that persist during therapy are similar to those observed in the elderly, raising the hypothesis that age-associated decline in immune function (“immunosenescence”) contributes to disease progression and adverse outcomes [13]–[16]. Markers of innate immune activation [e.g. interleukin (IL)-6, high-sensitivity C reactive protein (hs-CRP) and soluble CD14 (sCD14)], coagulation (fibrinogen, D-dimers), bacterial translocation (lipopolysaccharide), and T cell activation (HLADR and CD38 co-expression) are elevated despite effective ART and associated with subsequent morbidity and mortality, even after adjustment for CD4+ T cell count [17]–[21]. Induction of indoleamine 2,3-dioxygenase-1 (IDO) in monocytes and dendritic cells occurs during HIV infection and has been associated with impairment of the mucosal immunity and the maintenance of a chronic inflammatory state [22]. Collectively, these observations strongly suggest that an underlying mechanism not captured by CD4+ T cell count and HIV replication might be contributing to disease progression. The importance of CD4 counts as a strong predictor of opportunistic infections and non-AIDS events has been widely investigated, but little attention has been paid to the prognostic significance of CD8 counts. During untreated HIV infection, CD8 counts increase as CD4 counts decline [23]. During ART-mediated viral suppression, some individuals achieving CD4 counts above 500 cells/mm3 experience a simultaneous decline in CD8 counts, leading to normalization of the CD4/CD8 ratio. Others, however, maintain high levels of circulating CD8+ T cells, and hence a persistently low CD4/CD8 ratio [24]. Among elderly HIV-uninfected adults, inversion of the CD4/CD8 ratio ( 0.1% pp65/IE-specific IFN-γ+ CD8+ T cell responses by cytokine flow cytometry (ten-fold increase over limit of detection) as previously described [44]. Statistical methods Cross-sectional pairwise comparisons between groups were performed using Wilcoxon rank sum tests. Since a “normal” CD4/CD8 ratio remains poorly defined, for the between-group comparisons of T cell subsets and percentages of activated/senescent CD8+ T cells, we classified individuals according to the lowest quartile (≤0.4) and highest quartile (≥1.0) of SCOPE participants with ≥500 CD4+ T cells/mm3. A CD4/CD8 ratio ≤0.4 has been defined previously as the best cutoff that may predict serious non-AIDS events in well-treated HIV-infected patients [36], and 1.0 has been suggested in the general population as the cutoff for the “immune risk profile” associated with immunosenescence and mortality [26], [45]. To assess the intra-individual variability of the CD4/CD8 ratio, we used data from the control arms of ART intensification trials with raltegravir [38] and maraviroc [39], [40] to calculate the coefficient of variation (standard deviation/mean) for the CD4+ and CD8+ T cell counts and for the CD4/CD8 ratio. To analyze the association between the CD4/CD8 ratio and the KT ratio in SOCA, we fitted a linear regression model using CD4/CD8 ratio as the dependent variable, and KT ratio as the explanatory variable, adjusting the model by age, gender, time under viral suppression and CD4 nadir. To evaluate the relative contribution of the CD4+ and CD8+ T cells to this association, we also fitted another model with both CD4+ and CD8+ T cells in which the CD4/CD8 ratio was not considered because of colinearity, adjusting for the same covariates. We analyzed the correlations between the CD4/CD8 ratio in blood, with the ratio in lymph nodes and in GALT. For the GALT CD4/CD8 ratio measured in the MVC and RAL studies, we used only baseline measurements (before ART intensification). Since a different panel of antibodies was used for each study for flow-cytometry analysis, we fitted a linear regression analysis adjusting by the source study. We analyzed the impact of early ART initiation on the CD4/CD8 ratio in the OPTIONS cohort among recently HIV-infected participants, focusing on those who either started ART within six months of infection (early ART) or who deferred therapy for at least two years (later ART) [37]. Longitudinal changes in CD4 and CD8 counts and in the CD4/CD8 ratio were assessed using linear mixed models with random intercepts. Age, gender, and pre-ART CD4 counts were included in multivariate analyses as fixed-effects. Interaction terms were created to assess whether these changes over time differed significantly between the early and later ART initiators. Changes in slopes before and after ART time points were assessed using linear splines. We used data from the Madrid and SOCA cohorts to evaluate whether the CD4/CD8 ratio might be a marker of non-AIDS-related morbidity and mortality, respectively. In the nested case-control analysis in the Madrid cohort, cases who developed serious non-AIDS events and had ≥500 CD4+ T cells/mm3, were each matched to one controls by age, sex, nadir CD4, and proximal CD4 counts (N = 66). In the nested case-control study of immunological predictors of mortality in SOCA, cases with non-accidental death who had PBMC and plasma samples available within 18 months of death with confirmed plasma HIV RNA levels 500 cells/mm3 stratified by a normal (4th quartile, ≥1) or low (1st quartile, ≤0.4) CD4/CD8 ratio. HIV-infected individuals with low CD4/CD8 ratio had lower percentages of TN, TCM, and TTR CD8+ cells, higher TEM and TEMRA (A), and higher absolute counts (B) of all subsets compared to those with higher CD4/CD8 ratio and with healthy controls. 10.1371/journal.ppat.1004078.g002 Figure 2 Percentages and absolute counts of CD8+ activation phenotypes among HIV-/CMV+ individuals and ART-suppressed HIV-infected patients with CD4 counts >500 cells/mm3 stratified by a normal (4th quartile, ≥1, in green) or low (1st quartile, ≤0.4, in red) CD4/CD8 ratio. Subjects with low CD4/CD8 ratio showed higher percentages (A) and absolute counts (B) of HLADR+, CD28− and CD28−CD57+, and higher absolute counts of PD1+ cells (B). There were no differences in HIV-infected individuals in the proportion of CD28−CD8+ T cells expressing CD57, being significantly lower in both groups compared to HIV-/CMV+ controls. We sought to validate these findings among effectively treated subjects (undetectable viral load, ≥500 CD4+ T cells/mm3) within the SOCA cohort (general characteristics summarized in Table S3 ), and found comparable correlations between the CD4/CD8 ratio and different phenotypes of activated/senescent CD8+ T cells among ART-suppressed subjects with CD4>500 T cells/mm3. The most consistent correlates of the CD4/CD8 ratio were the %HLADR+CD38+ CD8+ T cells (Rho = −0.507, P 500 cells/mm3 stratified by a normal (4th quartile, ≥1) or low (1st quartile, ≤0.4) CD4/CD8 ratio. Individuals with low CD4/CD8 ratio had decreased frequencies of CD4+ TTR and decreased absolute counts of TN, TCM, and TTM CD4+ T cells compared to those HIV-infected patients with normal CD4/CD8 ratio and with healthy controls. (TIF) Click here for additional data file. Figure S3 Intra-individual variability of the CD4/CD8 ratio compared to CD4+ and CD8+ T cell counts. Using data from 38 HIV-infected patients on ART-mediated HIV-RNA suppression in whom a median of 11 determinations of CD4+ and CD8+ T cells measurements were performed during a median of 81 weeks, we calculated the coefficient of variation –within subject standard deviation (blue lines) and the within subject mean (red plus symbols)– for the CD4+ T cell counts, CD8+ T cell counts and the CD4/CD8 ratio. The mean coefficient of variation was significantly lower for the CD4/CD8 ratio (12%) compared to CD4+ T cell counts (16%, P = 0.017) and for CD8+ T cell counts (18%, P = 0.001). (TIF) Click here for additional data file. Table S1 Antibodies used for T-cell immunophenotyping. (DOCX) Click here for additional data file. Table S2 Characteristics of chronically HIV-infected participants and HIV negative controls in SCOPE. (DOCX) Click here for additional data file. Table S3 Characteristics of HIV-infected participants in SOCA cohort. (DOCX) Click here for additional data file. Table S4 General characteristics of participants in the lymph node and GALT analysis. (DOCX) Click here for additional data file. Table S5 General characteristics of OPTIONS participants. (DOCX) Click here for additional data file. Table S6 General characteristics of participants in the Madrid cohort nested study. (DOCX) Click here for additional data file. Table S7 Description of non-AIDS events in the Madrid cohort and causes of death in the SOCA cohort. (DOCX) Click here for additional data file. Text S1 Additional information on the cohorts and the clinical trials analyzed in this work. (DOCX) Click here for additional data file.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: Writing – original draft
                Role: InvestigationRole: Methodology
                Role: Investigation
                Role: Investigation
                Role: ConceptualizationRole: Project administrationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 October 2018
                2018
                : 13
                : 10
                Affiliations
                Enfermedades Infecciosas, Microbiología Clínica y Medicina Preventiva. Instituto de Biomedicina de Sevilla/Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla. Seville, Spain
                University of Pittsburgh Centre for Vaccine Research, UNITED STATES
                Author notes

                Competing Interests: The authors have read the journal's policy and the authors of this manuscript have the following competing interests: LFLC, NE and PV have received unrestricted research funding, consultancy fees, and lecture fees from and have served on the advisory boards of Abbott, Bristol-Myers Squibb, Gilead Sciences, Janssen-Cilag, Merck Sharp & Dohme, and ViiV Healthcare. There are no patents, products in development or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Article
                PONE-D-18-24758
                10.1371/journal.pone.0205777
                6197681
                30346965
                © 2018 Milanés-Guisado et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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                Funded by: RIS
                Award ID: D16/0025/0020-ISCIII-FEDER
                Award Recipient :
                This work was supported by Red de Investigación en SIDA (RIS) RD16/0025/0020-ISCIII-FEDER to LFLC.
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