Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1

Massive research efforts are now underway to develop a cure for HIV infection, allowing patients to discontinue lifelong combination antiretroviral therapy (ART). New latency-reversing agents (LRAs) may be able to purge the persistent reservoir of latent virus in resting memory CD4+ T cells, but the degree of reservoir reduction needed for cure remains unknown. Here we use a stochastic model of infection dynamics to estimate the efficacy of LRA needed to prevent viral rebound after ART interruption. We incorporate clinical data to estimate population-level parameter distributions and outcomes. Our findings suggest that approximately 2,000-fold reductions are required to permit a majority of patients to interrupt ART for one year without rebound and that rebound may occur suddenly after multiple years. Greater than 10,000-fold reductions may be required to prevent rebound altogether. Our results predict large variation in rebound times following LRA therapy, which will complicate clinical management. This model provides benchmarks for moving LRAs from the lab to the clinic and can aid in the design and interpretation of clinical trials. These results also apply to other interventions to reduce the latent reservoir and can explain the observed return of viremia after months of apparent cure in recent bone marrow transplant recipients and an immediately-treated neonate.Comment: 8 pages main text (4 figures). In PNAS Early Edition http://www.pnas.org/content/early/2014/08/05/1406663111. Ancillary files: SI, 24 pages SI (7 figures). File .htm opens a browser-based application to calculate rebound times (see SI). Or, the .cdf file can be run with Mathematica. The most up-to-date version of the code is available at http://www.danielrosenbloom.com/reboundtimes

Life cycle synchronization is a viral drug resistance mechanism

Viral infections are one of the major causes of death worldwide, with HIV infection alone resulting in over 1.2 million casualties per year. Antiviral drugs are now being administered for a variety of viral infections, including HIV, hepatitis B and C, and influenza. These therapies target a specific phase of the virus’s life cycle, yet their ultimate success depends on a variety of factors, such as adherence to a prescribed regimen and the emergence of viral drug resistance. The epidemiology and evolution of drug resistance have been extensively characterized, and it is generally assumed that drug resistance arises from mutations that alter the virus’s susceptibility to the direct action of the drug. In this paper, we consider the possibility that a virus population can evolve towards synchronizing its life cycle with the pattern of drug therapy. The periodicity of the drug treatment could then allow for a virus strain whose life cycle length is a multiple of the dosing interval to replicate only when the concentration of the drug is lowest. This process, referred to as “drug tolerance by synchronization”, could allow the virus population to maximize its overall fitness without having to alter drug binding or complete its life cycle in the drug’s presence. We use mathematical models and stochastic simulations to show that life cycle synchronization can indeed be a mechanism of viral drug tolerance. We show that this effect is more likely to occur when the variability in both viral life cycle and drug dose timing are low. More generally, we find that in the presence of periodic drug levels, time-averaged calculations of viral fitness do not accurately predict drug levels needed to eradicate infection, even if there is no synchronization. We derive an analytical expression for viral fitness that is sufficient to explain the drug-pattern-dependent survival of strains with any life cycle length. We discuss the implications of these findings for clinically relevant antiviral strategies

Insufficient Evidence for Rare Activation of Latent HIV in the Absence of Reservoir-Reducing Interventions

<p>Insufficient Evidence for Rare Activation of Latent HIV in the Absence of Reservoir-Reducing Interventions</p

Designing and Interpreting Limiting Dilution Assays: General Principles and Applications to the Latent Reservoir for Human Immunodeficiency Virus-1

Limiting dilution assays are widely used in infectious disease research. These assays are crucial for current human immunodeficiency virus (HIV)-1 cure research in particular. In this study, we offer new tools to help investigators design and analyze dilution assays based on their specific research needs. Limiting dilution assays are commonly used to measure the extent of infection, and in the context of HIV they represent an essential tool for studying latency and potential curative strategies. Yet standard assay designs may not discern whether an intervention reduces an already miniscule latent infection. This review addresses challenges arising in this setting and in the general use of dilution assays. We illustrate the major statistical method for estimating frequency of infectious units from assay results, and we offer an online tool for computing this estimate. We recommend a procedure for customizing assay design to achieve desired sensitivity and precision goals, subject to experimental constraints. We consider experiments in which no viral outgrowth is observed and explain how using alternatives to viral outgrowth may make measurement of HIV latency more efficient. Finally, we discuss how biological complications, such as probabilistic growth of small infections, alter interpretations of experimental results

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Elite squash players nutrition knowledge and influencing factors

Background There is a reported mismatch between macronutrient consumption and contemporary macronutrient guidelines in elite standard squash players. Suboptimal dietary practices could be due to a lack of nutrition knowledge among players. Subsequently, the purpose of this study was to assess the sports nutrition knowledge of elite squash players through the Nutrition for Sport Knowledge Questionnaire (NSKQ) and provide an indication of whether players require nutrition support to increase their nutrition knowledge. Methods This cross-sectional study assessed the nutrition knowledge of 77 elite squash players via the NSKQ over the period of June 2020 to August 2020. Results Players conveyed average nutrition knowledge with a mean NSKQ score of 48.78 ± 10.06 (56.07% ± 11.56%). There were no significant differences in NSKQ score between male and female players (p = .532). There was found to be a weak positive association between world ranking and NSKQ score (r = .208) and age and NSKQ score (r = .281). Players who had a relevant undergraduate degree (e.g. BSc Sport & Exercise Science) had significantly greater NSKQ score than players with no relevant qualifications (p = .022). Players who consulted a sports nutritionist to obtain their main source of nutrition information were shown to have significantly greater knowledge than those who acquired knowledge from a sports scientist (p = .01) or the internet / social media (p = .007). Conclusions Players should consult with a sports nutritionist to increase their sport nutrition knowledge. Future research should quantify the effectiveness of a nutritional education intervention at increasing nutrition knowledge in players

How do patient reported outcome measures (PROMs) support clinician-patient communication and patient care? A realist synthesis

Background: In this paper, we report the findings of a realist synthesis that aimed to understand how and in what circumstances patient reported outcome measures (PROMs) support patient-clinician communication and subsequent care processes and outcomes in clinical care. We tested two overarching programme theories: (1) PROMs completion prompts a process of self-reflection and supports patients to raise issues with clinicians and (2) PROMs scores raise clinicians’ awareness of patients’ problems and prompts discussion and action. We examined how the structure of the PROM and care context shaped the ways in which PROMs support clinician-patient communication and subsequent care processes. Results: PROMs completion prompts patients to reflect on their health and gives them permission to raise issues with clinicians. However, clinicians found standardised PROMs completion during patient assessments sometimes constrained rather than supported communication. In response, clinicians adapted their use of PROMs to render them compatible with the ongoing management of patient relationships. Individualised PROMs supported dialogue by enabling the patient to tell their story. In oncology, PROMs completion outside of the consultation enabled clinicians to identify problematic symptoms when the PROM acted as a substitute rather than addition to the clinical encounter and when the PROM focused on symptoms and side effects, rather than health related quality of life (HRQoL). Patients did not always feel it was appropriate to discuss emotional, functional or HRQoL issues with doctors and doctors did not perceive this was within their remit. Conclusions: This paper makes two important contributions to the literature. First, our findings show that PROMs completion is not a neutral act of information retrieval but can change how patients think about their condition. Second, our findings reveal that the ways in which clinicians use PROMs is shaped by their relationships with patients and professional roles and boundaries. Future research should examine how PROMs completion and feedback shapes and is influenced by the process of building relationships with patients, rather than just their impact on information exchange and decision making

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease