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      Thymic Function as a Predictor of Immune Recovery in Chronically HIV-Infected Patients Initiating Antiretroviral Therapy

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          Poor immunological responders (PIR) are HIV-infected patients with virologic suppression upon antiretroviral therapy (ART) but persistently low CD4 + T cell counts. Early identification of PIR is important given their higher morbimortality compared to adequate immune responders (AIR). In this study, 33 patients severely lymphopenic at ART onset, were followed for at least 36 months, and classified as PIR or AIR using cluster analysis grounded on their CD4 + T cell count trajectories. Based on a variety of immunological parameters, we built predictive models of PIR/AIR outcome using logistic regression. All PIR had CD4 + T cell counts consistently below 500 cells/μL, while all AIR reached this threshold. AIR showed a higher percentage of recent thymic emigrants among CD4 + T cells; higher numbers of sj-TRECs and greater sj/β TREC ratios; and significant increases in thymic volume from baseline to 12 months of ART. We identified mathematical models that correctly predicted PIR/AIR outcome after 36 months of therapy in 77–87% of the cases, based on observations made until 2–6 months after ART onset. This study highlights the importance of thymic activity in the immune recovery of severely lymphopenic patients, and may help to select the patients that will benefit from closer follow-up or novel therapeutic approaches.

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          CD4+ T Cell Depletion during all Stages of HIV Disease Occurs Predominantly in the Gastrointestinal Tract

          The mechanisms underlying CD4+ T cell depletion in human immunodeficiency virus (HIV) infection are not well understood. Comparative studies of lymphoid tissues, where the vast majority of T cells reside, and peripheral blood can potentially illuminate the pathogenesis of HIV-associated disease. Here, we studied the effect of HIV infection on the activation and depletion of defined subsets of CD4+ and CD8+ T cells in the blood, gastrointestinal (GI) tract, and lymph node (LN). We also measured HIV-specific T cell frequencies in LNs and blood, and LN collagen deposition to define architectural changes associated with chronic inflammation. The major findings to emerge are the following: the GI tract has the most substantial CD4+ T cell depletion at all stages of HIV disease; this depletion occurs preferentially within CCR5+ CD4+ T cells; HIV-associated immune activation results in abnormal accumulation of effector-type T cells within LNs; HIV-specific T cells in LNs do not account for all effector T cells; and T cell activation in LNs is associated with abnormal collagen deposition. Taken together, these findings define the nature and extent of CD4+ T cell depletion in lymphoid tissue and point to mechanisms of profound depletion of specific T cell subsets related to elimination of CCR5+ CD4+ T cell targets and disruption of T cell homeostasis that accompanies chronic immune activation.
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            Plasma viral load and CD4+ lymphocytes as prognostic markers of HIV-1 infection.

            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.
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              HIV infection and the risk of acute myocardial infarction.

              Whether people infected with human immunodeficiency virus (HIV) are at an increased risk of acute myocardial infarction (AMI) compared with uninfected people is not clear. Without demographically and behaviorally similar uninfected comparators and without uniformly measured clinical data on risk factors and fatal and nonfatal AMI events, any potential association between HIV status and AMI may be confounded. To investigate whether HIV is associated with an increased risk of AMI after adjustment for all standard Framingham risk factors among a large cohort of HIV-positive and demographically and behaviorally similar (ie, similar prevalence of smoking, alcohol, and cocaine use) uninfected veterans in care. Participants in the Veterans Aging Cohort Study Virtual Cohort from April 1, 2003, through December 31, 2009. After eliminating those with baseline cardiovascular disease, we analyzed data on HIV status, age, sex, race/ethnicity, hypertension, diabetes mellitus, dyslipidemia, smoking, hepatitis C infection, body mass index, renal disease, anemia, substance use, CD4 cell count, HIV-1 RNA, antiretroviral therapy, and incidence of AMI. Acute myocardial infarction. We analyzed data on 82 459 participants. During a median follow-up of 5.9 years, there were 871 AMI events. Across 3 decades of age, the mean (95% CI) AMI events per 1000 person-years was consistently and significantly higher for HIV-positive compared with uninfected veterans: for those aged 40 to 49 years, 2.0 (1.6-2.4) vs 1.5 (1.3-1.7); for those aged 50 to 59 years, 3.9 (3.3-4.5) vs 2.2 (1.9-2.5); and for those aged 60 to 69 years, 5.0 (3.8-6.7) vs 3.3 (2.6-4.2) (P < .05 for all). After adjusting for Framingham risk factors, comorbidities, and substance use, HIV-positive veterans had an increased risk of incident AMI compared with uninfected veterans (hazard ratio, 1.48; 95% CI, 1.27-1.72). An excess risk remained among those achieving an HIV-1 RNA level less than 500 copies/mL compared with uninfected veterans in time-updated analyses (hazard ratio, 1.39; 95% CI, 1.17-1.66). Infection with HIV is associated with a 50% increased risk of AMI beyond that explained by recognized risk factors.

                Author and article information

                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                05 February 2019
                : 10
                1Population Health Research Domain, Life and Health Sciences Research Institute, School of Medicine, University of Minho , Braga, Portugal
                2ICVS/3B's, PT Government Associate Laboratory , Braga/Guimarães, Portugal
                3Department of Onco-Hematology, Portuguese Institute of Oncology of Porto , Porto, Portugal
                4Department of Mathematics and Applications, School of Sciences, University of Minho , Braga, Portugal
                5Center of Mathematics, University of Minho , Braga, Portugal
                6INSERM, U1016, Institut Cochin , Paris, France
                7CNRS, UMR8104 , Paris, France
                8Department of Infection, Immunity and Inflammation, Université Paris Decartes , Paris, France
                9Department of Pathology & Cell Biology, Columbia University , New York, NY, United States
                10Department of Infectious Diseases, Centro Hospitalar do Porto , Porto, Portugal
                11Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet , Stockholm, Sweden
                Author notes

                Edited by: Francesca Chiodi, Karolinska Institute (KI), Sweden

                Reviewed by: Antonio Bandeira, Center for the National Scientific Research (CNRS), France; Ruy Ribeiro, Los Alamos National Laboratory (DOE), United States

                *Correspondence: Margarida Correia-Neves mcorreianeves@

                This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology

                Copyright © 2019 Rb-Silva, Nobrega, Azevedo, Athayde, Canto-Gomes, Ferreira, Cheynier, Yates, Horta and Correia-Neves.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Figures: 5, Tables: 3, Equations: 4, References: 61, Pages: 13, Words: 9508
                Funded by: European Regional Development Fund 10.13039/501100008530
                Funded by: Fundação para a Ciência e a Tecnologia 10.13039/501100001871
                Funded by: Gilead Sciences 10.13039/100005564
                Original Research


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