Understanding the slow depletion of memory CD4+ T cells in HIV infection

Mycobacterium tuberculosis-Human Immunodeficiency Virus Infection and the Role of T Cells in Protection

Tuberculosis (TB), primarily caused by Mycobacterium tuberculosis (M. tb), remains a widespread fatal health issue that becomes significantly detrimental when coupled with HIV. This study explores the host's innate and adaptive immune system response to TB in HIV immunocompromised patients, highlighting the significant role of CD8+ T cells. While the crucial role of macrophages and cytokines, like TNF-α and IFN-γ, in managing the host's immune response to M. tb is examined, the emphasis is on the changes that occur as a result of HIV coinfection. With the progression of HIV infection, the primary source of IFN-γ changes from CD4+ to CD8+ T cells, especially when latent TB advances to an active state. This study sheds light on the necessity of developing new preventative measures such as vaccines and new treatment approaches to TB, especially for immunocompromised patients, who are at a higher risk of life-threatening complications due to TB-HIV coinfection.

Modeling dynamics of acute HIV infection incorporating density-dependent cell death and multiplicity of infection

Understanding the dynamics of acute HIV infection can offer valuable insights into the early stages of viral behavior, potentially helping uncover various aspects of HIV pathogenesis. The standard viral dynamics model explains HIV viral dynamics during acute infection reasonably well. However, the model makes simplifying assumptions, neglecting some aspects of HIV infection. For instance, in the standard model, target cells are infected by a single HIV virion. Yet, cellular multiplicity of infection (MOI) may have considerable effects in pathogenesis and viral evolution. Further, when using the standard model, we take constant infected cell death rates, simplifying the dynamic immune responses. Here, we use four models-1) the standard viral dynamics model, 2) an alternate model incorporating cellular MOI, 3) a model assuming density-dependent death rate of infected cells and 4) a model combining (2) and (3)-to investigate acute infection dynamics in 43 people living with HIV very early after HIV exposure. We find that all models qualitatively describe the data, but none of the tested models is by itself the best to capture different kinds of heterogeneity. Instead, different models describe differing features of the dynamics more accurately. For example, while the standard viral dynamics model may be the most parsimonious across study participants by the corrected Akaike Information Criterion (AICc), we find that viral peaks are better explained by a model allowing for cellular MOI, using a linear regression analysis as analyzed by R2. These results suggest that heterogeneity in within-host viral dynamics cannot be captured by a single model. Depending on the specific aspect of interest, a corresponding model should be employed.

Viral rebound occurrence immediately after drug discontinuation involving neither drug resistance nor latent reservoir

Some viruses exhibit "rebound" when the administration of antiviral drugs is discontinued. Viral rebound caused by resistance mutations or latent reservoirs has been studied mathematically. In this study, we investigated the viral rebound due to other causes. Since immunity is weaker during antiviral treatment than without the treatment, drug discontinuation may lead to an increase in the viral load. We analyzed the dynamics of the number of virus-infected cells, cytotoxic T lymphocytes, and memory cells and identified the conditions under which the viral load increased upon drug discontinuation. If drug is administered for an extended period, a viral rebound occurs when the ratio of viral growth rate in the absence to that in the presence of the antiviral drug exceeds the "rebound threshold." We analyzed how the rebound threshold depended on the patient's conditions and the type of treatment. Mathematical and numerical analyses revealed that rebound after discontinuation was more likely to occur when the drug effectively reduced viral proliferation, drug discontinuation was delayed, and the processes activating immune responses directly were stronger than those occurring indirectly through immune memory formation. We discussed additional reasons for drugs to cause viral rebound more likely.

Mathematical Models of HIV-1 Dynamics, Transcription, and Latency

HIV-1 latency is a major barrier to curing infections with antiretroviral therapy and, consequently, to eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best described with the help of mathematical models followed by experimental validation. Here, we review the use of viral dynamics models for HIV-1, with a focus on applications to the latent reservoir. Such models have been used to explain the multi-phasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of post-treatment control. Finally, we discuss that mathematical models have been used to predict the efficacy of potential HIV-1 cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Modeling T Cell Fate

Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.

Microfluidic Devices for HIV Diagnosis and Monitoring at Point-of-Care (POC) Settings

Human immunodeficiency virus (HIV) is a global epidemic; however, many individuals are able to obtain treatment and manage their condition. Progression to acquired immunodeficiency syndrome (AIDS) occurs during late-stage HIV infection, which compromises the immune system, making it susceptible to infections. While there is no cure, antiretroviral therapy can be used provided that detection occurs, preferably during the early phase. However, the detection of HIV is expensive and resource-intensive when tested with conventional methods, such as flow cytometry, polymerase chain reaction (PCR), or enzyme-linked immunosorbent assays (ELISA). Improving disease detection in resource-constrained areas requires equipment that is affordable, portable, and can deliver rapid results. Microfluidic devices have transformed many benchtop techniques to on-chip detection for portable and rapid point-of-care (POC) testing. These devices are cost-effective, sensitive, and rapid and can be used in areas lacking resources. Moreover, their functionality can rival their benchtop counterparts, making them efficient for disease detection. In this review, we discuss the limitations of currently used conventional HIV diagnostic assays and provide an overview of potential microfluidic technologies that can improve HIV testing in POC settings.

Impact of HIV-1 CRF55_01B infection on the evolution of CD4 count and plasma HIV RNA load in men who have sex with men prior to antiretroviral therapy

Background

CRF55_01B is a newly identified HIV-1 circulating recombinant form originated from MSM in China. However, its impact on the disease progression and transmission risk has not been investigated. This study aimed to determine the impact of CRF55_01B infection on viral dynamics and immunological status so as to provide scientific evidence for further control and prevention effort on CRF55_01B. Linear mixed effect models were applied to evaluate CD4 cell count decline and viral load increase by subtype.

Results

Of the 3418 blood samples, 1446 (42.3%) were CRF07_BC, 1169 (34.2%) CRF01_AE, 467 (13.7%) CRF55_01B, 249 (7.3%) type B, and 87 (2.5%) other subtypes (CRF_08BC, CRF_01B, C). CRF55_01B had become the third predominant strain since 2012 in Shenzhen, China. CRF55_01B-infected MSM showed lower median of CD4 count than CRF07_BC-infected MSM (349.5 [IQR, 250.2–474.8] vs. 370.0 [IQR, 278.0–501.0], P < 0.05). CRF55_01B infection was associated with slower loss of CD4 count than CRF01_AE (13.6 vs. 23.3 [cells/µl]¹/²/year, P < 0.05)among MSM with initial CD4 count of 200–350 cells/µl. On the other hand, those infected with CRF55_01B showed higher median plasma HIV RNA load (5.4 [IQR, 5.0–5.9]) than both CRF01_AE (5.3 [IQR, 4.8–5.7], P < 0.05) and CRF07_BC (5.0 log10 [IQR, 4.5–5.5], P < 0.001) at the initiation of antiretroviral therapy. Furthermore, the annual increasing rate of viral load for CRF55_01B infection was significantly higher than that of CRF07_BC (2.0 vs. 0.7 log10 copies/ml/year, P < 0.01).

Conclusions

The relatively lower CD4 count and faster increase of plasma HIV RNA load of CRF55_01B-infected MSM without antiretroviral therapy suggest that CRF55_01B may lead to longer asymptomatic phase and higher risk of HIV transmission. Strengthened surveillance, tailored prevention strategies and interventions, and in-depth research focusing on CRF55_01B are urgently needed to forestall potential epidemic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12977-021-00567-z.

Dual Antiretroviral Therapy-All Quiet Beneath the Surface?

Infection with the human immunodeficiency virus (HIV) is characterized by progressive depletion of CD4+ lymphocytes cells as a result of chronic immune activation. Next to the decreases in the number of CD4+ cells which leads to opportunistic infections, HIV-related immune activation is associated with several prevalent comorbidities in the HIV-positive population such as cardiovascular and bone disease. Traditionally, combination antiretroviral therapy (cART) consists of three drugs with activity against HIV and is highly effective in diminishing the degree of immune activation. Over the years, questions were raised whether virological suppression could also be achieved with fewer antiretroviral drugs, i.e., dual- or even monotherapy. This is an intriguing question considering the fact that antiretroviral drugs should be used lifelong and their use could also induce cardiovascular and bone disease. Therefore, the equilibrium between drug-induced toxicity and immune activation related comorbidity is delicate. Recently, two large clinical trials evaluating two-drug cART showed non-inferiority with respect to virological outcomes when compared to triple-drug regimens. This led to adoption of dual antiretroviral therapy in current HIV treatment guidelines. However, it is largely unknown whether dual therapy is also able to suppress immune activation to the same degree as triple therapy. This poses a risk for an imbalance in the delicate equilibrium. This mini review gives an overview of the current available evidence concerning immune activation in the setting of cART with less than three antiretroviral drugs.

Sharing CD4+ T Cell Loss: When COVID-19 and HIV Collide on Immune System

COVID-19 is a distinctive infection characterized by elevated inter-human transmission and presenting from absence of symptoms to severe cytokine storm that can lead to dismal prognosis. Like for HIV, lymphopenia and drastic reduction of CD4+ T cell counts in COVID-19 patients have been linked with poor clinical outcome. As CD4+ T cells play a critical role in orchestrating responses against viral infections, important lessons can be drawn by comparing T cell response in COVID-19 and in HIV infection and by studying HIV-infected patients who became infected by SARS-CoV-2. We critically reviewed host characteristics and hyper-inflammatory response in these two viral infections to have a better insight on the large difference in clinical outcome in persons being infected by SARS-CoV-2. The better understanding of mechanism of T cell dysfunction will contribute to the development of targeted therapy against severe COVID-19 and will help to rationally design vaccine involving T cell response for the long-term control of viral infection.

The Rules of Human T Cell Fate in vivo

The processes governing lymphocyte fate (division, differentiation, and death), are typically assumed to be independent of cell age. This assumption has been challenged by a series of elegant studies which clearly show that, for murine cells in vitro, lymphocyte fate is age-dependent and that younger cells (i.e., cells which have recently divided) are less likely to divide or die. Here we investigate whether the same rules determine human T cell fate in vivo. We combined data from in vivo stable isotope labeling in healthy humans with stochastic, agent-based mathematical modeling. We show firstly that the choice of model paradigm has a large impact on parameter estimates obtained using stable isotope labeling i.e., different models fitted to the same data can yield very different estimates of T cell lifespan. Secondly, we found no evidence in humans in vivo to support the model in which younger T cells are less likely to divide or die. This age-dependent model never provided the best description of isotope labeling; this was true for naïve and memory, CD4⁺ and CD8⁺ T cells. Furthermore, this age-dependent model also failed to predict an independent data set in which the link between division and death was explored using Annexin V and deuterated glucose. In contrast, the age-independent model provided the best description of both naïve and memory T cell dynamics and was also able to predict the independent dataset.

Simulating the entire natural course of HIV infection by extending the basic viral dynamics equations to include declining viral clearance

The basic model of viral dynamics is a relatively simple set of equations describing the most essential features of the host-pathogen interactions. Coupled with data, it has been used extensively and successfully to reproduce and explain the features of the early acute phase of HIV infection and the effects of antiretroviral treatment, as well as to estimate the lifespan of infected cells, viral growth and clearance rates and predict early outcomes under different circumstances. However, it cannot reproduce the entire natural course of untreated HIV infection consistently with constant parameters. Here we show that it is possible to qualitatively reproduce the whole course of untreated HIV infection within the general framework of the basic model by assuming progressively declining viral clearance coupled with viral load. We discuss the interpretation of this model as proof-of-concept that may inspire further research into the role of viral clearance in HIV infection.

Salp15, a Multifunctional Protein From Tick Saliva With Potential Pharmaceutical Effects

Ixodes ticks are the main vectors for a number of zoonotic diseases, including Lyme disease. Ticks secrete saliva directly into a mammalian host while feeding on the host's blood. This action serves to modulate host immunity and coagulation, thus allowing ticks to attach and feed upon their host. One of the most extensively studied components of tick saliva is Salp15. Research has shown that this protein binds specifically to CD4 molecules on the surface of T lymphocytes, interferes with TCR-mediated signaling transduction, inhibits CD4+ T cell activation and proliferation, and impedes the secretion of interleukin 2 (IL-2). Salp15 also binds specifically to dendritic cell dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN) to up-regulate the expression of CD73 in regulatory T cells. Collectively, these findings render this salivary protein a potential candidate for a range of therapeutic applications. Here, we discuss our current understanding of Salp15 and the mechanisms that might be used to treat disease.

Insight into treatment of HIV infection from viral dynamics models

The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.

Modeling Kick-Kill Strategies toward HIV Cure

Although combinatorial antiretroviral therapy (cART) potently suppresses the virus, a sterile or functional cure still remains one of the greatest therapeutic challenges worldwide. Reservoirs are infected cells that can maintain HIV persistence for several years in patients with optimal cART, which is a leading obstacle to eradicate the virus. Despite the significant progress that has been made in our understanding of the diversity of cells that promote HIV persistence, many aspects that are critical to the development of effective therapeutic approaches able to purge the latent CD4+ T cell reservoir are poorly understood. Simultaneous purging strategies known as “kick-kill” have been pointed out as promising therapeutic approaches to eliminate the viral reservoir. However, long-term outcomes of purging strategies as well as the effect on the HIV reservoir are still largely fragmented. In this context, mathematical modeling can provide a rationale not only to evaluate the impact on the HIV reservoir but also to facilitate the formulation of hypotheses about potential therapeutic strategies. This review aims to discuss briefly the most recent mathematical modeling contributions, harnessing our knowledge toward the uncharted territory of HIV eradication. In addition, problems associated with current models are discussed, in particular, mathematical models consider only T cell responses but HIV control may also depend on other cell responses as well as chemokines and cytokines dynamics.

Pathophysiology of CD4+ T-Cell Depletion in HIV-1 and HIV-2 Infections

The hall mark of human immunodeficiency virus (HIV) infection is a gradual loss of CD4+ T-cells and imbalance in CD4+ T-cell homeostasis, with progressive impairment of immunity that leads ultimately to death. HIV infection in humans is caused by two related yet distinct viruses: HIV-1 and HIV-2. HIV-2 is typically less virulent than HIV-1 and permits the host to mount a more effective and sustained T-cell immunity. Although both infections manifest the same clinical spectrum, the much lower rate of CD4+ T-cell decline and slower progression of disease in HIV-2 infected individuals have grabbed the attention of several researchers. Here, we review the most recent findings on the differential rate of decline of CD4+ T-cell in HIV-1 and HIV-2 infections and provide plausible reasons for the observed differences between the two groups.

Mathematical Models of HIV Latency

Viral latency is a major barrier to curing HIV infection with antiretroviral therapy, and consequently, for eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best understood and described with the help of mathematical models. Here we review the use of viral dynamics models for HIV, with a focus on applications to the latent reservoir. Such models have been used to explain the multiphasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of posttreatment control. In addition, mathematical models have been used to predict the efficacy of potential HIV cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Analysis of Practical Identifiability of a Viral Infection Model

Mathematical modelling approaches have granted a significant contribution to life sciences and beyond to understand experimental results. However, incomplete and inadequate assessments in parameter estimation practices hamper the parameter reliability, and consequently the insights that ultimately could arise from a mathematical model. To keep the diligent works in modelling biological systems from being mistrusted, potential sources of error must be acknowledged. Employing a popular mathematical model in viral infection research, existing means and practices in parameter estimation are exemplified. Numerical results show that poor experimental data is a main source that can lead to erroneous parameter estimates despite the use of innovative parameter estimation algorithms. Arbitrary choices of initial conditions as well as data asynchrony distort the parameter estimates but are often overlooked in modelling studies. This work stresses the existence of several sources of error buried in reports of modelling biological systems, voicing the need for assessing the sources of error, consolidating efforts in solving the immediate difficulties, and possibly reconsidering the use of mathematical modelling to quantify experimental data.

Kynurenine Reduces Memory CD4 T-Cell Survival by Interfering with Interleukin-2 Signaling Early during HIV-1 Infection

Early HIV-1 infection is characterized by enhanced tryptophan catabolism, which contributes to immune suppression and disease progression. However, the mechanism by which kynurenine, a tryptophan-related metabolite, induces immune suppression remains poorly understood. Herein, we show that the increased production of kynurenine correlates with defective interleukin-2 (IL-2) signaling in memory CD4 T cells from HIV-infected subjects. Defective IL-2 signaling in these subjects, which drives reduced protection from Fas-mediated apoptosis, was also associated with memory CD4 T-cell loss. Treatment of memory CD4 T cells with the concentration of kynurenine found in plasma inhibited IL-2 signaling through the production of reactive oxygen species. We further show that IL-2 signaling in memory CD4 T cells is improved by the antioxidant N-acetylcysteine. Early initiation of antiretroviral therapy restored the IL-2 response in memory CD4 T cells by reducing reactive oxygen species and kynurenine production. The study findings provide a kynurenine-dependent mechanism through IL-2 signaling for reduced CD4 T-cell survival, which can be reversed by early treatment initiation in HIV-1 infection.

IMPORTANCE

The persistence of functional memory CD4 T cells represents the basis for long-lasting immune protection in individuals after exposure to HIV-1. Unfortunately, primary HIV-1 infection results in the massive loss of these cells within weeks of infection, which is mainly driven by inflammation and massive infection by the virus. These new findings show that the enhanced production of kynurenine, a metabolite related to tryptophan catabolism, also impairs memory CD4 T-cell survival and interferes with IL-2 signaling early during HIV-1 infection.

T cell and reticular network co-dependence in HIV infection

Fibroblastic reticular cells (FRC) are arranged on a network in the T cell zone of lymph nodes, forming a scaffold for T cell migration, and providing survival factors, especially interleukin-7 (IL-7). Conversely, CD4(+) T cells are the major producers of lymphotoxin-β (LT-β), necessary for the construction and maintenance of the FRC network. This interdependence creates the possibility of a vicious cycle, perpetuating loss of both FRC and T cells. Furthermore, evidence that HIV infection is responsible for collagenation of the network suggests that long term loss of network function might be responsible for the attenuated recovery in T cell count seen in HIV patients undergoing antiretroviral therapy (ART). We present computational and mathematical models of this interaction mechanism and subsequent naive CD4(+) T-cell depletion in which (1) collagen deposition impedes access of naive T cells to IL-7 on the FRC and loss of IL-7 production by loss of FRC network itself, leading to the depletion of naive T cells through increased apoptosis; and (2) depletion of naive T cells as the source of LT-β on which the FRC depend for survival leads to loss of the network, thereby amplifying and perpetuating the cycle of depletion of both naive T cells and stromal cells. Our computational model explicitly includes an FRC network and its cytokine exchange with a heterogeneous T-cell population. We also derive lumped models, in terms of partial differential equations and reduced to ordinary differential equations, that provide additional insight into the mechanisms at work. The central conclusions are that (1) damage to the reticular network, caused by HIV infection is a plausible mechanism for attenuated recovery post-ART; (2) within this, the production of T cell survival factors by FRCs may be the key rate-limiting step; and (3) the methods of model reduction and analysis presented are useful for both immunological studies and other contexts in which agent-based models are severely limited by computational cost.

Modeling the Slow CD4+ T Cell Decline in HIV-Infected Individuals

The progressive loss of CD4+ T cell population is the hallmark of HIV-1 infection but the mechanism underlying the slow T cell decline remains unclear. Some recent studies suggested that pyroptosis, a form of programmed cell death triggered during abortive HIV infection, is associated with the release of inflammatory cytokines, which can attract more CD4+ T cells to be infected. In this paper, we developed mathematical models to study whether this mechanism can explain the time scale of CD4+ T cell decline during HIV infection. Simulations of the models showed that cytokine induced T cell movement can explain the very slow decline of CD4+ T cells within untreated patients. The long-term CD4+ T cell dynamics predicted by the models were shown to be consistent with available data from patients in Rio de Janeiro, Brazil. Highly active antiretroviral therapy has the potential to restore the CD4+ T cell population but CD4+ response depends on the effectiveness of the therapy, when the therapy is initiated, and whether there are drug sanctuary sites. The model also showed that chronic inflammation induced by pyroptosis may facilitate persistence of the HIV latent reservoir by promoting homeostatic proliferation of memory CD4+ cells. These results improve our understanding of the long-term T cell dynamics in HIV-1 infection, and support that new treatment strategies, such as the use of caspase-1 inhibitors that inhibit pyroptosis, may maintain the CD4+ T cell population and reduce the latent reservoir size.

The CD4+ T cell population within HIV-infected individuals declines slowly as disease progresses. When CD4+ cells drop to below 200 cells/ul, the infection is usually considered to enter the late stage, i.e., acquired immune deficiency syndrome (AIDS). CD4+ T cell depletion can take many years but the biological events underlying such slow decline are not well understood. Some studies showed that the majority of infected T cells in lymph nodes die by pyroptosis, a form of programmed cell death, which can release inflammatory signals attracting more CD4+ T cells to be infected. We developed mathematical models to describe this process and explored whether they can generate the long-term CD4+ T cell decline. We showed that pyroptosis induced cell movement can explain the slow time scale of CD4+ T cell depletion and that pyroptosis may also contribute to the persistence of latently infected cells, which represent a major obstacle to HIV eradication. The modeling prediction agrees with patient data in Rio de Janeiro, Brazil. These results suggest that a combination of current treatment regimens and caspase-1 inhibitor that can inhibit pyroptosis might provide a new way to maintain the CD4+ T cell population and eradicate the HIV latent reservoir.

A non-synonymous polymorphism in IL-23R Gene (rs1884444) is associated with reduced risk to schistosomiasis-associated Immune Reconstitution Inflammatory Syndrome in a Kenyan population

Background

Human Immunodeficiency Virus (HIV) and Schistosomiasis co-infection is common among residents at the shores of Lake Victoria in Kenya. About 36% of this population initiating antiretroviral therapy (ART) experience Immune Reconstitution Inflammatory Syndrome (IRIS) that complicates recovery. Several IL-23R alleles have been associated with susceptibility to both autoimmune and inflammatory diseases through T-helper type 17 (TH₁₇) cells. However, whether or not variants within the IL-23R increase susceptibility to IRIS in western Kenya is unknown. The objective of the current study was to determine the association between IL-23R gene polymorphisms, CD4+ cell counts and HIV RNA levels and IRIS in HIV and Schistosoma mansoni co-infected patients undergoing highly active anti-retroviral therapy (HAART).

Methods

A three-month case–control study was conducted on antiretroviral naïve schistosomiasis/HIV co-infected fishermen starting HAART in Uyoma Rarieda, Siaya County, Kenya. Seventy one patients were sampled at baseline and followed up for three months, to establish if they developed Schistosoma-related IRIS. In addition, the CD4+ cell counts and HIV RNA levels were determined in pre- and post-administration of HAART. Variations at five polymorphic sites of IL-23R (rs1884444, rs11465754, rs6682925, rs7530511 and rs7539625) based on >10% minor allele frequency in Yoruban reference population was determined using Allelic Discrimination Assay. The association between the five variants and susceptibility to IRIS was determined using logistic regression while controlling for potential confounders. In addition, the functional differences between the baseline CD4 + Cell counts and viral loads were determined using medians while across IL-23R genotypes were determined using Kruskal-Wallis tests.

Results

Overall, 26 (36.6%) patients developed schistosomiasis-associated IRIS at a median age of 35.5 years. Carriage of the TT genotype at the non-synonymous rs1884444 T > G relative to GG, was associated with a decreased risk of schistosomiasis-associated IRIS (OR, 0.25, 95% CI, 0.07-0.96, P = 0.043) while both baseline CD4+ cell counts and viral loads had no association with IRIS.

Conclusion

These findings indicate that the non-synonymous variant rs1884444 T > G of IL-23R is associated with a decreased risk to schistosomiasis-associated IRIS. However, additional studies in a larger cohort and with an all inclusive polymorphic variants in the synonymous and non-synonymous regions need to be evaluated.

Computational study to determine when to initiate and alternate therapy in HIV infection

HIV is a widespread viral infection without cure. Drug treatment has transformed HIV disease into a treatable long-term infection. However, the appearance of mutations within the viral genome reduces the susceptibility of HIV to drugs. Therefore, a key goal is to extend the time until patients exhibit resistance to all existing drugs. Current HIV treatment guidelines seem poorly supported as practitioners have not achieved a consensus on the optimal time to initiate and to switch antiretroviral treatments. We contribute to this discussion with predictions derived from a mathematical model of HIV dynamics. Our results indicate that early therapy initiation (within 2 years postinfection) is critical to delay AIDS progression. For patients who have not received any therapy during the first 3 years postinfection, switch in response to virological failure may outperform proactive switching strategies. In case that proactive switching is opted, the switching time between therapies should not be larger than 100 days. Further clinical trials are needed to either confirm or falsify these predictions.

A mechanistic model for naive CD4 T cell homeostasis in healthy adults and children

The size and composition of the T lymphocyte compartment is subject to strict homeostatic regulation and is remarkably stable throughout life in spite of variable dynamics in cell production and death during T cell development and immune responses. Homeostasis is achieved by careful orchestration of lymphocyte survival and cell division. New T cells are generated from the thymus and the number of peripheral T cells is regulated by controlling survival and proliferation. How these processes combine is however very complex. Thymic output increases in the first year of life and then decreases but is crucial for establishing repertoire diversity. Proliferation of new naive T cells plays a crucial role for maintaining numbers but at a potential cost to TCR repertoire diversity. A mechanistic two-compartment model of T cell homeostasis is described here that includes specific terms for thymic output, cell proliferation, and cell death of both resting and dividing cells. The model successfully predicts the homeostatic set point for T cells in adults and identifies variables that determine the total number of T cells. It also accurately predicts T cell numbers in children in early life despite rapid changes in thymic output and growth over this period.

Dynamical models of biomarkers and clinical progression for personalized medicine: the HIV context

Mechanistic models, based on ordinary differential equation systems, can exhibit very good predictive abilities that will be useful to build treatment monitoring strategies. In this review, we present the potential and the limitations of such models for guiding treatment (monitoring and optimizing) in HIV-infected patients. In the context of antiretroviral therapy, several biological processes should be considered in addition to the interaction between viruses and the host immune system: the mechanisms of action of the drugs, their pharmacokinetics and pharmacodynamics, as well as the viral and host characteristics. Another important aspect to take into account is clinical progression, although its implementation in such modelling approaches is not easy. Finally, the control theory and the use of intrinsic properties of mechanistic models make them very relevant for dynamic treatment adaptation. Their implementation would nevertheless require their evaluation through clinical trials.

Accelerated in vivo proliferation of memory phenotype CD4+ T-cells in human HIV-1 infection irrespective of viral chemokine co-receptor tropism

CD4⁺ T-cell loss is the hallmark of HIV-1 infection. CD4 counts fall more rapidly in advanced disease when CCR5-tropic viral strains tend to be replaced by X4-tropic viruses. We hypothesized: (i) that the early dominance of CCR5-tropic viruses results from faster turnover rates of CCR5⁺ cells, and (ii) that X4-tropic strains exert greater pathogenicity by preferentially increasing turnover rates within the CXCR4⁺ compartment. To test these hypotheses we measured in vivo turnover rates of CD4⁺ T-cell subpopulations sorted by chemokine receptor expression, using in vivo deuterium-glucose labeling. Deuterium enrichment was modeled to derive in vivo proliferation (p) and disappearance (d*) rates which were related to viral tropism data. 13 healthy controls and 13 treatment-naive HIV-1-infected subjects (CD4 143–569 cells/ul) participated. CCR5-expression defined a CD4⁺ subpopulation of predominantly CD45R0⁺ memory cells with accelerated in vivo proliferation (p = 2.50 vs 1.60%/d, CCR5⁺ vs CCR5⁻; healthy controls; P<0.01). Conversely, CXCR4 expression defined CD4⁺ T-cells (predominantly CD45RA⁺ naive cells) with low turnover rates. The dominant effect of HIV infection was accelerated turnover of CCR5⁺CD45R0⁺CD4⁺ memory T-cells (p = 5.16 vs 2.50%/d, HIV vs controls; P<0.05), naïve cells being relatively unaffected. Similar patterns were observed whether the dominant circulating HIV-1 strain was R5-tropic (n = 9) or X4-tropic (n = 4). Although numbers were small, X4-tropic viruses did not appear to specifically drive turnover of CXCR4-expressing cells (p = 0.54 vs 0.72 vs 0.44%/d in control, R5-tropic, and X4-tropic groups respectively). Our data are most consistent with models in which CD4⁺ T-cell loss is primarily driven by non-specific immune activation.

Loss of CD4⁺ T-cells is the cardinal feature of HIV/AIDS, resulting in pathological susceptibility to opportunistic infections. Mechanisms underlying CD4-depletion remain unclear, although the role of chronic immune activation is now well-recognized. Selectivity of the virus for its co-receptor target (either chemokine-receptor CCR5 or CXCR4) is also pivotal. We explored the relationship between these two factors by directly measuring in vivo proliferation rates of CD4⁺ T-cell subpopulations according to their expression of chemokine-receptors and the tropism of circulating virus in clinically-well people with HIV infection, and healthy human controls. We used stable isotope labeling with deuterium-labeled glucose to quantify proliferation and disappearance rate constants of CD4⁺ T-cells sorted by CCR5, CXCR4 and CD45R0/RA expression. We found that CCR5-expression defines a high turnover subpopulation which is therefore likely to be preferentially infected and produce more (CCR5-tropic) virus. CXCR4-tropic viruses induced a similar pattern of proliferation as R5-tropic strains, with no apparent selectivity for viral strains to induce proliferation in their targeted subpopulations. This study is significant in providing directly-measured in vivo human data supporting postulates generated in ex vivo human studies and SIV models suggesting that non-specific factors, such as immune activation, rather than cell-specific cytotoxicity, are dominant drivers for HIV pathogenesis.

Modeling the three stages in HIV infection

A typical HIV infection response consists of three stages: an initial acute infection, a long asymptomatic period and a final increase in viral load with simultaneous collapse in healthy CD4+T cell counts. The majority of existing mathematical models give a good representation of either the first two stages or the last stage of the infection. Using macrophages as a long-term active reservoir, a deterministic model is proposed to explain the three stages of the infection including the progression to AIDS. Simulation results illustrate how chronic infected macrophages can explain the progression to AIDS provoking viral explosion. Further simulation studies suggest that the proposed model retains its key properties even under moderately large parameter variations. This model provides important insights on how macrophages might play a crucial role in the long term behavior of HIV infection.

Modelling the course of an HIV infection: insights from ecology and evolution

The Human Immunodeficiency Virus (HIV) is one of the most threatening viral agents. This virus infects approximately 33 million people, many of whom are unaware of their status because, except for flu-like symptoms right at the beginning of the infection during the acute phase, the disease progresses more or less symptom-free for 5 to 10 years. During this asymptomatic phase, the virus slowly destroys the immune system until the onset of AIDS when opportunistic infections like pneumonia or Kaposi’s sarcoma can overcome immune defenses. Mathematical models have played a decisive role in estimating important parameters (e.g., virion clearance rate or life-span of infected cells). However, most models only account for the acute and asymptomatic latency phase and cannot explain the progression to AIDS. Models that account for the whole course of the infection rely on different hypotheses to explain the progression to AIDS. The aim of this study is to review these models, present their technical approaches and discuss the robustness of their biological hypotheses. Among the few models capturing all three phases of an HIV infection, we can distinguish between those that mainly rely on population dynamics and those that involve virus evolution. Overall, the modeling quest to capture the dynamics of an HIV infection has improved our understanding of the progression to AIDS but, more generally, it has also led to the insight that population dynamics and evolutionary processes can be necessary to explain the course of an infection.

Evolutionary dynamics of HIV at multiple spatial and temporal scales

Infectious diseases remain a formidable challenge to human health, and understanding pathogen evolution is crucial to designing effective therapeutics and control strategies. Here, we review important evolutionary aspects of HIV infection, highlighting the concept of selection at multiple spatial and temporal scales. At the smallest scale, a single cell may be infected by multiple virions competing for intracellular resources. Recombination and phenotypic mixing introduce novel evolutionary dynamics. As the virus spreads between cells in an infected individual, it continually evolves to circumvent the immune system. We discuss evolutionary mechanisms of HIV pathogenesis and progression to AIDS. Viral spread throughout the human population can lead to changes in virulence and the transmission of immune-evading variation. HIV emerged as a human pathogen due to selection occurring between different species, adapting from related viruses of primates. HIV also evolves resistance to antiretroviral drugs within a single infected host, and we explore the possibility for the spread of these strains between hosts, leading to a drug-resistant epidemic. We investigate the role of latency, drug-protected compartments, and direct cell-to-cell transmission on viral evolution. The introduction of an HIV vaccine may select for viral variants that escape vaccine control, both within an individual and throughout the population. Due to the strong selective pressure exerted by HIV-induced morbidity and mortality in many parts of the world, the human population itself may be co-evolving in response to the HIV pandemic. Throughout the paper, we focus on trade-offs between costs and benefits that constrain viral evolution and accentuate how selection pressures differ at different levels of selection.

B cell depletion in HIV-1 subtype A infected Ugandan adults: relationship to CD4 T cell count, viral load and humoral immune responses

To better understand the nature of B cell dysfunctions in subjects infected with HIV-1 subtype A, a rural cohort of 50 treatment-naïve Ugandan patients chronically infected with HIV-1 subtype A was studied, and the relationship between B cell depletion and HIV disease was assessed. B cell absolute counts were found to be significantly lower in HIV-1+ patients, when compared to community matched negative controls (p<0.0001). HIV-1-infected patients displayed variable functional and binding antibody titers that showed no correlation with viral load or CD4+ T cell count. However, B cell absolute counts were found to correlate inversely with neutralizing antibody (NAb) titers against subtype A (p = 0.05) and subtype CRF02_AG (p = 0.02) viruses. A positive correlation was observed between subtype A gp120 binding antibody titers and NAb breadth (p = 0.02) and mean titer against the 10 viruses (p = 0.0002). In addition, HIV-1 subtype A sera showed preferential neutralization of the 5 subtype A or CRF02_AG pseudoviruses, as compared with 5 pseudoviruses from subtypes B, C or D (p<0.001). These data demonstrate that in patients with chronic HIV-1 subtype A infection, significant B cell depletion can be observed, the degree of which does not appear to be associated with a decrease in functional antibodies. These findings also highlight the potential importance of subtype in the specificity of cross-clade neutralization in HIV-1 infection.

A systems model for immune cell interactions unravels the mechanism of inflammation in human skin

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.

A functional immune system requires complex interactions among diverse cell types, mediated by a variety of cytokines. These interactions include phenomena such as positive and negative feedback loops that can be experimentally characterized by dose-dependent cytokine production measurements. However, any experimental approach is not only limited with regard to the number of cell-cell interactions that can be studied at a given time, but also does not have the capacity to assess or predict the overall immune response which is the result of complex interdependent immune cell interactions. Therefore, experimental data need to be viewed from a theoretical perspective allowing the quantitative modeling of immune cell interactions. Here, we propose a strategy for a quantitative description of multiple interactions between immune cell populations based on their cytokine production profiles. The model predicts that the modified feedback loop interactions can result in the appearance of alternative steady-states causing the switch-like immune system effect that is experimentally observed in pathologic phenotypes. Overall, the quantitative description of immune cell interactions via cytokine signaling reported here offers new insights into understanding and predicting normal and pathological immune system responses.

Limited CD4+ T cell proliferation leads to preservation of CD4+ T cell counts in SIV-infected sooty mangabeys

Human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV) infections result in chronic virus replication and progressive depletion of CD4+ T cells, leading to immunodeficiency and death. In contrast, 'natural hosts' of SIV experience persistent infection with high virus replication but no severe CD4+ T cell depletion, and remain AIDS-free. One important difference between pathogenic and non-pathogenic infections is the level of activation and proliferation of CD4+ T cells. We analysed the relationship between CD4+ T cell number and proliferation in HIV, pathogenic SIV in macaques, and non-pathogenic SIV in sooty mangabeys (SMs) and mandrills. We found that CD4+ T cell proliferation was negatively correlated with CD4+ T cell number, suggesting that animals respond to the loss of CD4+ T cells by increasing the proliferation of remaining cells. However, the level of proliferation seen in pathogenic infections (SIV in rhesus macaques and HIV) was much greater than in non-pathogenic infections (SMs and mandrills). We then used a modelling approach to understand how the host proliferative response to CD4+ T cell depletion may impact the outcome of infection. This modelling demonstrates that the rapid proliferation of CD4+ T cells in humans and macaques associated with low CD4+ T cell levels can act to 'fuel the fire' of infection by providing more proliferating cells for infection. Natural host species, on the other hand, have limited proliferation of CD4+ T cells at low CD4+ T cell levels, which allows them to restrict the number of proliferating cells susceptible to infection.

Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection

Computer models of disease take a systems biology approach toward understanding host-pathogen interactions. In particular, data driven computer model calibration is the basis for inference of immunological and pathogen parameters, assessment of model validity, and comparison between alternative models of immune or pathogen behavior. In this paper we describe the calibration and analysis of an agent-based model of Leishmania major infection. A model of macrophage loss following uptake of necrotic tissue is proposed to explain macrophage depletion following peak infection. Using Gaussian processes to approximate the computer code, we perform a sensitivity analysis to identify important parameters and to characterize their influence on the simulated infection. The analysis indicates that increasing growth rate can favor or suppress pathogen loads, depending on the infection stage and the pathogen's ability to avoid detection. Subsequent calibration of the model against previously published biological observations suggests that L. major has a relatively slow growth rate and can replicate for an extended period of time before damaging the host cell.

Maternal hematological and virological characteristics during early feline immunodeficiency virus (FIV) infection of cats as predictors of fetal infection and reproductive outcome at early gestation

The FIV-infected cat is a small animal model for HIV mother-to-child transmission (MTCT) because the two lentiviruses are biologically related and produce similar clinical syndromes. Both viruses are vertically transmissible and may negatively impact reproductive outcome. Maternal hematological and virological parameters are predictors of MTCT in HIV-infected women. Our purpose was to determine whether similar maternal characteristics during early pregnancy in FIV-infected cats influence pregnancy outcome. We inoculated 10 cats with FIV-B-2542; 10 cats were uninoculated. We quantified longitudinal CD4:CD8 T cell ratios, proviral load, and plasma viremia, monitored longitudinal serostatus, and documented clinical and reproductive outcome during early pregnancy. Inoculated queens were seropositive and provirus positive by week 4 post-infection (p.i.). CD4:CD8 ratios were depressed in the infected group by month 3.5 p.i. Proviral load was variable in the animals throughout the course of infection; plasma viremia was below the level of detection in all animals. Reduced litter sizes and increased fetal demise occurred in infected queens. Viral RNA, but not proviral DNA, was detected in representative placentas (14 of 14; 100%) and fetuses (12 of 14; 86%) collected from infected queens. However, maternal virological and hematological characteristics did not correlate either positively or negatively with reproductive outcome.

Ablation of thymic export causes accelerated decay of naive CD4 T cells in the periphery because of activation by environmental antigen

A model of chemical thymectomy by inducible Rag ablation was used to study peripheral T cell homeostasis. Induction of Rag ablation was efficient and complete, leading to cessation of thymic T cell production within 3-4 weeks. The decay of peripheral T cells became apparent with a delay of an additional 2-3 weeks and was entirely accounted for by loss of naïve T cells, whereas numbers of memory phenotype and regulatory T cells were not decreased. Naïve CD4 T cells decayed with an average half-life of 50 days, whereas naïve CD8 T cells exhibited a considerably longer half-life. The rapid decay of naïve CD4 T cells was not caused by intrinsic survival differences compared with naïve CD8 T cells, but was caused by changes in the lymphopenic environment resulting in higher microbial load and consequential activation. This finding suggests that in lymphopenic conditions involving compromised thymic function replenishment and survival of a naïve CD4 T cell repertoire may be severely curtailed because of chronic activation. Such a scenario might play a role in the aging immune system and chronic viral infection, such as HIV infection, and contribute to loss of CD4 T cells and impaired immune function. As our data show, continued replenishment with cells from the thymus seems to be required to maintain efficient gut mucosal defense.

Has HIV evolved to induce immune pathogenesis?

Human immunodeficiency virus (HIV) induces a chronic generalized activation of the immune system, which plays an important role in the pathogenesis of AIDS. This ability of the virus might either be an evolved (adaptive) trait or a coincidental side effect of jumping to a new host species. We argue that selection favours the ability of HIV to induce immune activation at the local sites of infection (e.g. lymph follicles) but not at the systemic level. Immune activation increases the supply of susceptible target cells; however, mutations that increase systemic immune activation benefit all virus variants equally and are therefore selectively neutral. We thus conclude that the generalized immune activation that is probably responsible for pathogenesis is probably not directly under selection.

Prevention of immunodeficiency virus induced CD4+ T-cell depletion by prior infection with a non-pathogenic virus

Immune dysregulation initiated by a profound loss of CD4+ T-cells is fundamental to HIV-induced pathogenesis. Infection of domestic cats with a non-pathogenic lentivirus prevalent in the puma (puma lentivirus, PLV or FIV(pco)) prevented peripheral blood CD4+ T-cell depletion caused by subsequent virulent FIV infection. Maintenance of this critical population was not associated with a significant decrease in FIV viremia, lending support to the hypothesis that direct viral cytopathic effect is not the primary cause of immunodeficiency. Although this approach was analogous to immunization with a modified live vaccine, correlates of immunity such as a serum-neutralizing antibody or virus-specific T-cell proliferative response were not found in protected animals. Differences in cytokine transcription profile, most notably in interferon gamma, were observed between the protected and unprotected groups. These data provide support for the importance of non-adaptive enhancement of the immune response in the prevention of CD4+ T-cell loss.

Normalization of B cell counts and subpopulations after antiretroviral therapy in chronic HIV disease

BACKGROUND

Untreated human immunodeficiency virus (HIV) disease leads to abnormalities in all major lymphocyte populations, including CD4(+) T cells, CD8(+) T cells, and B cells. However, little is known regarding the effect of antiretroviral therapy (ART)-induced decrease in HIV viremia on B cell numbers and subpopulations.

METHODS

We conducted a longitudinal study to evaluate changes in B cell numbers and subpopulations that occur during the course of 12 months of effective ART in a group of individuals with chronic HIV infection.

RESULTS

ART-induced decrease in HIV viremia was associated with a significant increase in B cell counts, similar to increases in CD4(+) T cell counts yet distinct from the lack of increase in CD8(+) T cells. The increase in B cell counts was accompanied by a significant decrease in the frequency of apoptosis-prone B cell subpopulations, namely mature activated and immature transitional B cells, which are overrepresented in untreated HIV disease. The increase in B cell counts was reflected by a significant increase in naive and resting memory B cells, both of which represent populations that are essential for generating adequate humoral immunity.

CONCLUSIONS

Normalization of B cell counts and subpopulations may help to explain the improvement in humoral immunity reported to occur after an ART-induced decrease in HIV viremia.

Chronic CD4+ T-cell activation and depletion in human immunodeficiency virus type 1 infection: type I interferon-mediated disruption of T-cell dynamics

The mechanism of CD4(+) T-cell depletion during chronic human immunodeficiency virus type 1 (HIV-1) infection remains unknown. Many studies suggest a significant role for chronic CD4(+) T-cell activation. We assumed that the pathogenic process of excessive CD4(+) T-cell activation would be reflected in the transcriptional profiles of activated CD4(+) T cells. Here we demonstrate that the transcriptional programs of in vivo-activated CD4(+) T cells from untreated HIV-positive (HIV(+)) individuals are clearly different from those of activated CD4(+) T cells from HIV-negative (HIV(-)) individuals. We observed a dramatic up-regulation of cell cycle-associated and interferon-stimulated transcripts in activated CD4(+) T cells of untreated HIV(+) individuals. Furthermore, we find an enrichment of proliferative and type I interferon-responsive transcription factor binding sites in the promoters of genes that are differentially expressed in activated CD4(+) T cells of untreated HIV(+) individuals compared to those of HIV(-) individuals. We confirm these findings by examination of in vivo-activated CD4(+) T cells. Taken together, these results suggest that activated CD4(+) T cells from untreated HIV(+) individuals are in a hyperproliferative state that is modulated by type I interferons. From these results, we propose a new model for CD4(+) T-cell depletion during chronic HIV-1 infection.

Time scales of CD4+ T cell depletion in HIV infection

Rob De Boer discusses a new study that investigated whether a runaway process of T cell activation/infection would be compatible with the slow time scale of memory CD4⁺ T cell depletion in humans with chronic HIV infection.