Fidelity of SNP array genotyping using Epstein Barr virus-transformed B-lymphocyte cell lines: Implications for genome-wide association studies

Background: As availability of primary cells can be limited for genetic studies of human disease, lymphoblastoid cell lines (LCL) are common sources of genomic DNA. LCL are created in a transformation process that entails in vitro infection of human B-lymphocytes with the Epstein-Barr Virus (EBV). Methodology/Principal Findings: To test for genotypic errors potentially induced by the Epstein-Barr Virus transformation process, we compared single nucleotide polymorphism (SNP) genotype calls in peripheral blood mononuclear cells (PBMC) and LCL from the same individuals. The average mismatch rate across 19 comparisons was 0.12% for SNPs with a population call rate of at least 95%, and 0.03% at SNPs with a call rate of at least 99%. Mismatch rates were not correlated across genotype subarrays run on all sample pairs. Conclusions/Significance: Genotypic discrepancies found in PBMC and LCL pairs were not significantly different than control pairs, and were not correlated across subarrays. These results suggest that mismatch rates are minimal with stringent quality control, and that most genotypic discrepancies are due to technical artifacts rather than the EBV transformation process. Thus, LCL likely constitute a reliable DNA source for host genotype analysis. © 2009 Herbeck et al

Cardiac Calcitropes, Myotropes, and Mitotropes: JACC Review Topic of the Week.

The term "inotrope" is familiar and intimately connected with pharmaceuticals clinically used for treatment of low cardiac output with cardiogenic shock. Traditional inotropic agents exert their effect by modulating calcium signaling in the myocardium. Their use is associated with poor long-term outcomes. Newer molecules in development intend to break from calcium mediation and the associated detrimental long-term effects by targeting distinct mechanisms of action to improve cardiac performance. Thus, "inotropy" does not sufficiently describe the range of potential novel pharmaceutical products. To enhance communication around and evaluation of current, emerging, and potential therapies, this review proposes a novel nuanced and holistic framework to categorize pharmacological agents that improve myocardial performance based on 3 myocardial mechanisms: calcitropes, which alter intracellular calcium concentrations; myotropes, which affect the molecular motor and scaffolding; and mitotropes, which influence energetics. Novel chemical entities can easily be incorporated into this structure, distinguishing themselves based on their mechanisms and clinical outcomes

HIV-2 Integrase Variation in Integrase Inhibitor-Naïve Adults in Senegal, West Africa

Antiretroviral therapy for HIV-2 infection is hampered by intrinsic resistance to many of the drugs used to treat HIV-1. Limited studies suggest that the integrase inhibitors (INIs) raltegravir and elvitegravir have potent activity against HIV-2 in culture and in infected patients. There is a paucity of data on genotypic variation in HIV-2 integrase that might confer intrinsic or transmitted INI resistance.We PCR amplified and analyzed 122 HIV-2 integrase consensus sequences from 39 HIV-2-infected, INI-naive adults in Senegal, West Africa. We assessed genetic variation and canonical mutations known to confer INI-resistance in HIV-1.No amino acid-altering mutations were detected at sites known to be pivotal for INI resistance in HIV-1 (integrase positions 143, 148 and 155). Polymorphisms at several other HIV-1 INI resistance-associated sites were detected at positions 72, 95, 125, 154, 165, 201, 203, and 263 of the HIV-2 integrase protein.Emerging genotypic and phenotypic data suggest that HIV-2 is susceptible to the new class of HIV integrase inhibitors. We hypothesize that intrinsic HIV-2 integrase variation at "secondary" HIV-1 INI-resistance sites may affect the genetic barrier to HIV-2 INI resistance. Further studies will be needed to assess INI efficacy as part of combination antiretroviral therapy in HIV-2-infected patients

Evolution of HIV virulence in response to widespread scale up of antiretroviral therapy: a modeling study

There are global increases in the use of HIV antiretroviral therapy (ART), guided by clinical benefits of early ART initiation and the efficacy of treatment as prevention of transmission. Separately, it has been shown theoretically and empirically that HIV virulence can evolve over time; observed virulence levels may reflect an adaptive balance between infected lifespan and per-contact transmission rate. However, the potential effects of widespread ART usage on HIV virulence are unknown. To predict these effects, we used an agent-based stochastic model to simulate evolutionary trends in HIV virulence, using set point viral load as a proxy for virulence. We calibrated our model to prevalence and incidence trends of South Africa. We explored two distinct ART scenarios: (1) ART initiation based on HIV-infected individuals reaching a CD4 count threshold; and (2) ART initiation based on individual time elapsed since HIV infection (a scenario that mimics “universal testing and treatment” (UTT) aspirations). In each case, we considered a range in population uptake of ART. We found that HIV virulence is generally unchanged in scenarios of CD4-based initiation. However, with ART initiation based on time since infection, virulence can increase moderately within several years of ART rollout, under high coverage levels and early treatment initiation (albeit within the context of epidemics that are rapidly decreasing in size). Sensitivity analyses suggested the impact of ART on virulence is relatively insensitive to model calibration. Our modeling study suggests that increasing HIV virulence driven by UTT is likely not a major public health concern, but should be monitored in sentinel surveillance, in a manner similar to transmitted resistance to antiretroviral drugs

HIV-1 Superinfection in the Antiretroviral Therapy Era: Are Seroconcordant Sexual Partners at Risk?

Acquisition of more than one strain of human immunodeficiency virus type 1 (HIV-1) has been reported to occur both during and after primary infection, but the risks and repercussions of dual and superinfection are incompletely understood. In this study, we evaluated a longitudinal cohort of chronically HIV-infected men who were sexual partners to determine if individuals acquired their partners' viral strains.Our cohort of HIV-positive men consisted of 8 couples that identified themselves as long-term sexual partners. Viral sequences were isolated from each subject and analyzed using phylogenetic methods. In addition, strain-specific PCR allowed us to search for partners' viruses present at low levels. Finally, we used computational algorithms to evaluate for recombination between partners' viral strains.All couples had at least one factor associated with increased risk for acquisition of new HIV strains during the study, including detectable plasma viral load, sexually transmitted infections, and unprotected sex. One subject was dually HIV-1 infected, but neither strain corresponded to that of his partner. Three couples' sequences formed monophyletic clusters at the entry visit, with phylogenetic analysis suggesting that one member of the couple had acquired an HIV strain from his identified partner or that both had acquired it from the same source outside their partnership. The 5 remaining couples initially displayed no evidence of dual infection, using phylogenetic analysis and strain-specific PCR. However, in 1 of these couples, further analysis revealed recombinant viral strains with segments of viral genomes in one subject that may have derived from the enrolled partner. Thus, chronically HIV-1 infected individuals may become superinfected with additional HIV strains from their seroconcordant sexual partners. In some cases, HIV-1 superinfection may become apparent when recombinant viral strains are detected

Viral population estimation using pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an EM algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure

High sensitivity (1)H-NMR spectroscopy of homeopathic remedies made in water

BACKGROUND: The efficacy of homeopathy is controversial. Homeopathic remedies are made via iterated shaking and dilution, in ethanol or in water, from a starting substance. Remedies of potency 12 C or higher are ultra-dilute (UD), i.e. contain zero molecules of the starting material. Various hypotheses have been advanced to explain how a UD remedy might be different from unprepared solvent. One such hypothesis posits that a remedy contains stable clusters, i.e. localized regions where one or more hydrogen bonds remain fixed on a long time scale. High sensitivity proton nuclear magnetic resonance spectroscopy has not previously been used to look for evidence of differences between UD remedies and controls. METHODS: Homeopathic remedies made in water were studied via high sensitivity proton nuclear magnetic resonance spectroscopy. A total of 57 remedy samples representing six starting materials and spanning a variety of potencies from 6 C to 10 M were tested along with 46 controls. RESULTS: By presaturating on the water peak, signals could be reliably detected that represented H-containing species at concentrations as low as 5 μM. There were 35 positions where a discrete signal was seen in one or more of the 103 spectra, which should theoretically have been absent from the spectrum of pure water. Of these 35, fifteen were identified as machine-generated artifacts, eight were identified as trace levels of organic contaminants, and twelve were unexplained. Of the unexplained signals, six were seen in just one spectrum each. None of the artifacts or unexplained signals occurred more frequently in remedies than in controls, using a p < .05 cutoff. Some commercially prepared samples were found to contain traces of one or more of these small organic molecules: ethanol, acetate, formate, methanol, and acetone. CONCLUSION: No discrete signals suggesting a difference between remedies and controls were seen, via high sensitivity (1)H-NMR spectroscopy. The results failed to support a hypothesis that remedies made in water contain long-lived non-dynamic alterations of the H-bonding pattern of the solvent

Mach-Zehnder-Fano interferometer

We introduce a concept of the Mach-Zehnder-Fano interferometer by inserting a cavity exhibiting Fano resonance into a conventional interferometer. By employing the scattering-matrix approach, we demonstrate that the transmission is sensitive to a position of the cavity such that an asymmetric structure exhibits a series of narrow resonances with almost perfect reflection. We discuss how to implement this novel geometry in two-dimensional photonic crystals and use direct numerical simulations to demonstrate novel regimes of the resonant transmission and reflection.Comment: 3 pages, 3 figure

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.CNPq Brazilian Foundation for Scientific and Technological DevelopmentCNPq - Brazilian Foundation for Scientific and Technological Development [150653/2008-5