Immune Activation, Cd4+ T Cell Counts, and Viremia Exhibit Oscillatory Patterns over Time in Patients with Highly Resistant HIV Infection

The rates of immunologic and clinical progression are lower in patients with drug-resistant HIV compared to wild-type HIV. This difference is not fully explained by viral load. It has been argued that reductions in T cell activation and/or viral fitness might result in preserved target cells and an altered relationship between the level of viremia and the rate of CD4+ T cell loss. We tested this hypothesis over time in a cohort of patients with highly resistant HIV. Fifty-four antiretroviral-treated patients with multi-drug resistant HIV and detectable plasma HIV RNA were followed longitudinally. CD4+ T cell counts and HIV RNA levels were measured every 4 weeks and T cell activation (CD38/HLA-DR) was measured every 16 weeks. We found that the levels of CD4+ T cell activation over time were a strong independent predictor of CD4+ T cell counts while CD8+ T cell activation was more strongly associated with viremia. Using spectral analysis, we found strong evidence for oscillatory (or cyclic) behavior in CD4+ T cell counts, HIV RNA levels, and T cell activation. Each of the cell populations exhibited an oscillatory behavior with similar frequencies. Collectively, these data suggest that there may be a mechanistic link between T cell activation, CD4+ T cell counts, and viremia and lends support for the hypothesis of altered predator-prey dynamics as a possible explanation of the stability of CD4+ T cell counts in the presence of sustained multi-drug resistant viremia

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society

Targeting c-Mpl for Revival of Human Immunodeficiency Virus Type 1-Induced Hematopoietic Inhibition When CD34(+) Progenitor Cells Are Re-Engrafted into a Fresh Stromal Microenvironment In Vivo

The inhibition of multilineage hematopoiesis which occurs in the severe combined immunodeficiency mouse with transplanted human fetal thymus and liver tissues (SCID-hu Thy/Liv) due to human immunodeficiency virus type 1 (HIV-1) infection is also accompanied by a severe loss of c-Mpl expression on these progenitor cells. Inhibition of colony-forming activity (CFA) of the CD34(+) progenitor cells is partially revived to about 40% of mock-infected Thy/Liv implants, following reconstitution of the CD34(+) cells that were exposed to HIV-1 infection, in a new Thy/Liv stromal microenvironment of irradiated secondary SCID-hu recipients at 3 weeks post-re-engraftment. In addition, in these reconstituted animals, the proportion of c-Mpl(+) CD34(+) cells relative to c-Mpl(−) CD34(+) cells increased by about 25%, to 35% of mock-infected implants, suggesting a reacquirement of c-Mpl phenotype by the c-Mpl(−) CD34(+) cells. These results suggest a correlation between c-Mpl expression and multilineage CFA of the human CD34(+) progenitor cells that have experienced the effects of HIV-1 infection. Treatment of the secondary-recipient animals with the c-Mpl ligand, thrombopoietin (Tpo), further increased c-Mpl expression and CFA of re-engrafted CD34(+) cells previously exposed to virus in the primary implants to about 50 to 70% over that of those re-engrafted CD34(+) cells derived from implants of untreated animals. Blocking of c-Mpl with anti-c-Mpl monoclonal antibody in vivo by injecting the SCID-hu animals resulted in the reduction or loss of CFA. Thus, inhibition, absence, or loss of c-Mpl expression as in the c-Mpl(−) CD34(+) subset of cells is the likely cause of CFA inhibition. Further, CFA of the CD34(+) cells segregates with their c-Mpl expression. Therefore, c-Mpl may play a role in hematopoietic inhibition during HIV-1 infection, and control of its expression levels may aid in hematopoietic recovery and thereby reduce the incidence of cytopenias occurring in infected individuals

HIV-1 viral fitness estimation using exchangeable on subsets priors and prior model selection

The phenotype-genotype problem is a fundamental problem of biology where an organism's genotype (genetic information) predicts its phenotype (observable characteristic). Viral fitness, defined as the reproductive capacity of a virus compared to a standard, is a continuous phenotype. We construct models to predict viral fitness as a function of mutation away from the standard wildtype virus. Data of this nature are difficult to analyse because there are potentially many more parameters than observations. We treat this issue as a regression problem using a prior with both a shrinkage component and a variable selection component. The key to practical implementation of the model is the prior specification for the regression coefficients. We use results from the scientific literature to construct several informative exchangeable within subsets priors (ESP). We use prior model selection (PMS) to select among our priors. Two novel graphics present results from five models each with 71 predictors

Single Mutations in HIV Integrase Confer High-Level Resistance to Raltegravir in Primary Human Macrophages▿

CD4+ T cells and macrophages are the primary target cells for HIV in vivo, and antiretroviral drugs can vary in their ability to inhibit the infection of these different cell types. Resistance pathways to the HIV integrase inhibitor raltegravir have previously been investigated in T cells. Primary raltegravir resistance mutations, most often at integrase amino acid position 148 or 155, afford some resistance to the drug. The acquisition of pathway-specific secondary mutations then provides higher-level resistance to viruses infecting T cells. We show here that during macrophage infection, the presence of a single primary raltegravir resistance mutation (Q148H, Q148R, N155H, or N155S) is sufficient to provide resistance to raltegravir comparable to that seen in viruses expressing both primary and secondary mutations in costimulated CD4+ T cells. These data implicate macrophages as a potential in vivo reservoir that may facilitate the development of resistance to raltegravir. Notably, the newer integrase inhibitor MK-2048 effectively suppressed the infection of all raltegravir-resistant viruses in both T cells and macrophages, indicating that more recently developed integrase inhibitors are capable of inhibiting infection in both major HIV cellular reservoirs, even in patients harboring raltegravir-resistant viruses

Hierarchical phylogenetic models for analyzing multipartite sequence data

Debate exists over how to incorporate information from multipartite sequence data in phylogenetic analyses. Strict combined-data approaches argue for concatenation of all partitions and estimation of one evolutionary history, maximizing the explanatory power of the data. Consensus/independence approaches endorse a two-step procedure where partitions are analyzed independently and then a consensus is determined from the multiple results. Mixtures across the model space of a strict combined-data approach and a priori independent parameters are popular methods to integrate these methods. We propose an alternative middle ground by constructing a Bayesian hierarchical phylogenetic model. Our hierarchical framework enables researchers to pool information across data partitions to improve estimate precision in individual partitions while permitting estimation and testing of tendencies in across-partition quantities. Such across-partition quantities include the distribution from which individual topologies relating the sequences within a partition are drawn. We propose standard hierarchical priors on continuous evolutionary parameters across partitions, while the structure on topologies varies depending on the research problem. We illustrate our model with three examples. We first explore the evolutionary history of the guinea pig (Cavia porcellus) using alignments of 13 mitochondrial genes. The hierarchical model returns substantially more precise continuous parameter estimates than an independent parameter approach without losing the salient features of the data. Second, we analyze the frequency of horizontal gene transfer using 50 prokaryotic genes. We assume an unknown species-level topology and allow individual gene topologies to differ from this with a small estimable probability. Simultaneously inferring the species and individual gene topologies returns a transfer frequency of 17%. We also examine HIV sequences longitudinally sampled from HIV+ patients. We ask whether posttreatment development of CCR5 coreceptor virus represents concerted evolution from middisease CXCR4 virus or reemergence of initial infecting CCR5 virus. The hierarchical model pools partitions from multiple unrelated patients by assuming that the topology for each patient is drawn from a multinomial distribution with unknown probabilities. Preliminary results suggest evolution and not reemergence

Spectral analysis estimated parameters for CD4 T-cell activation.

<p>For each individual, the mean and standard deviations for wave components for CD4 T cell activation is presented.</p

Spectral analysis estimated parameters for CD8 T cell activation.

<p>For each individual, the mean and standard deviations for wave components for CD8 T cell activation is presented.</p