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1.  Vaccine-Induced IgG Antibodies to V1V2 Regions of Multiple HIV-1 Subtypes Correlate with Decreased Risk of HIV-1 Infection 
PLoS ONE  2014;9(2):e87572.
In the RV144 HIV-1 vaccine efficacy trial, IgG antibody (Ab) binding levels to variable regions 1 and 2 (V1V2) of the HIV-1 envelope glycoprotein gp120 were an inverse correlate of risk of HIV-1 infection. To determine if V1V2-specific Abs cross-react with V1V2 from different HIV-1 subtypes, if the nature of the V1V2 antigen used to asses cross-reactivity influenced infection risk, and to identify immune assays for upcoming HIV-1 vaccine efficacy trials, new V1V2-scaffold antigens were designed and tested. Protein scaffold antigens carrying the V1V2 regions from HIV-1 subtypes A, B, C, D or CRF01_AE were assayed in pilot studies, and six were selected to assess cross-reactive Abs in the plasma from the original RV144 case-control cohort (41 infected vaccinees, 205 frequency-matched uninfected vaccinees, and 40 placebo recipients) using ELISA and a binding Ab multiplex assay. IgG levels to these antigens were assessed as correlates of risk in vaccine recipients using weighted logistic regression models. Levels of Abs reactive with subtype A, B, C and CRF01_AE V1V2-scaffold antigens were all significant inverse correlates of risk (p-values of 0.0008–0.05; estimated odds ratios of 0.53–0.68 per 1 standard deviation increase). Thus, levels of vaccine-induced IgG Abs recognizing V1V2 regions from multiple HIV-1 subtypes, and presented on different scaffolds, constitute inverse correlates of risk for HIV-1 infection in the RV144 vaccine trial. The V1V2 antigens provide a link between RV144 and upcoming HIV-1 vaccine trials, and identify reagents and methods for evaluating V1V2 Abs as possible correlates of protection against HIV-1 infection.
Trial Registration
ClinicalTrials.gov NCT00223080
doi:10.1371/journal.pone.0087572
PMCID: PMC3913641  PMID: 24504509
2.  BAYESIAN INFERENCE AND MODEL CHOICE IN A HIDDEN STOCHASTIC TWO-COMPARTMENT MODEL OF HEMATOPOIETIC STEM CELL FATE DECISIONS1 
The annals of applied statistics  2009;3(4):1696-1709.
Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly observed and measured. Previously we modeled feline hematopoiesis using a two-compartment hidden Markov process that had birth and emigration events in the first compartment. Here we perform Bayesian statistical inference on models which contain two additional events in the first compartment in order to determine if HSC fate decisions are linked to cell division or occur independently. Pareto Optimal Model Assessment approach is used to cross check the estimates from Bayesian inference. Our results show that HSC must divide symmetrically (i.e., produce two HSC daughter cells) in order to maintain hematopoiesis. We then demonstrate that the augmented model that adds asymmetric division events provides a better fit to the competitive transplantation data, and we thus provide evidence that HSC fate determination in vivo occurs both in association with cell division and at a separate point in time. Last we show that assuming each cat has a unique set of parameters leads to either a significant decrease or a nonsignificant increase in model fit, suggesting that the kinetic parameters for HSC are not unique attributes of individual animals, but shared within a species.
doi:10.1214/09-AOAS269
PMCID: PMC3783006  PMID: 24078859
Stochastic two-compartment model; hidden Markov models; reversible jump MCMC; hematopoiesis; stem cell; asymmetric division
3.  Optimization and Qualification of a Multiplex Bead Array to Assess Cytokine and Chemokine Production by Vaccine-specific Cells 
Journal of Immunological Methods  2012;382(1-2):117-128.
The magnitude and functional phenotype (e.g. proliferation, immune stimulation) of the vaccine-induced T-cell responses are likely to be critical in defining responses that can control pathogenic challenge. Current multi-parameter flow cytometric techniques may not be sufficient to measure all of these different functions, since characterizing T-cell responses by flow cytometry is presently limited to concurrent measurement of at most 10 cytokines/chemokines. Here, we describe extensive studies conducted using standardized GCLP procedures to optimize and qualitatively/quantitatively qualify a multiplex bead array (MBA) performed on supernatant collected from stimulated peripheral blood mononuclear cells (PBMC) to assess 12 cytokines and chemokines of interest. Our optimized MBA shows good precision (intra-assay, inter-day, inter-technician; coefficients of variation <30%) and linearity for most of the analytes studied. We also developed positivity criteria that allow us to define a response as positive or negative with a high degree of confidence. In conclusion, we provide a detailed description of the qualification of an MBA, which permits quantitative and qualitative evaluation of vaccine-induced immunogenicity and analysis of immune correlates of protection. This assay provides an excellent complement to the existing repertoire of assays for assessing immunogenicity in HIV vaccine clinical trials.
doi:10.1016/j.jim.2012.05.011
PMCID: PMC3406745  PMID: 22626638
Multiplex bead array; Vaccine; HIV; Cytokine; Chemokine
4.  Infectious Virion Capture by HIV-1 gp120-Specific IgG from RV144 Vaccinees 
Journal of Virology  2013;87(14):7828-7836.
The detailed examination of the antibody repertoire from RV144 provides a unique template for understanding potentially protective antibody functions. Some potential immune correlates of protection were untested in the correlates analyses due to inherent assay limitations, as well as the need to keep the correlates analysis focused on a limited number of endpoints to achieve statistical power. In an RV144 pilot study, we determined that RV144 vaccination elicited antibodies that could bind infectious virions (including the vaccine strains HIV-1 CM244 and HIV-1 MN and an HIV-1 strain expressing transmitted/founder Env, B.WITO.c). Among vaccinees with the highest IgG binding antibody profile, the majority (78%) captured the infectious vaccine strain virus (CM244), while a smaller proportion of vaccinees (26%) captured HIV-1 transmitted/founder Env virus. We demonstrated that vaccine-elicited HIV-1 gp120 antibodies of multiple specificities (V3, V2, conformational C1, and gp120 conformational) mediated capture of infectious virions. Although capture of infectious HIV-1 correlated with other humoral immune responses, the extent of variation between these humoral responses and virion capture indicates that virion capture antibodies occupy unique immunological space.
doi:10.1128/JVI.02737-12
PMCID: PMC3700223  PMID: 23658446
5.  Quality control, analysis and secure sharing of Luminex® immunoassay data using the open source LabKey Server platform 
BMC Bioinformatics  2013;14:145.
Background
Immunoassays that employ multiplexed bead arrays produce high information content per sample. Such assays are now frequently used to evaluate humoral responses in clinical trials. Integrated software is needed for the analysis, quality control, and secure sharing of the high volume of data produced by such multiplexed assays. Software that facilitates data exchange and provides flexibility to perform customized analyses (including multiple curve fits and visualizations of assay performance over time) could increase scientists’ capacity to use these immunoassays to evaluate human clinical trials.
Results
The HIV Vaccine Trials Network and the Statistical Center for HIV/AIDS Research and Prevention collaborated with LabKey Software to enhance the open source LabKey Server platform to facilitate workflows for multiplexed bead assays. This system now supports the management, analysis, quality control, and secure sharing of data from multiplexed immunoassays that leverage Luminex xMAP® technology. These assays may be custom or kit-based. Newly added features enable labs to: (i) import run data from spreadsheets output by Bio-Plex Manager™ software; (ii) customize data processing, curve fits, and algorithms through scripts written in common languages, such as R; (iii) select script-defined calculation options through a graphical user interface; (iv) collect custom metadata for each titration, analyte, run and batch of runs; (v) calculate dose–response curves for titrations; (vi) interpolate unknown concentrations from curves for titrated standards; (vii) flag run data for exclusion from analysis; (viii) track quality control metrics across runs using Levey-Jennings plots; and (ix) automatically flag outliers based on expected values. Existing system features allow researchers to analyze, integrate, visualize, export and securely share their data, as well as to construct custom user interfaces and workflows.
Conclusions
Unlike other tools tailored for Luminex immunoassays, LabKey Server allows labs to customize their Luminex analyses using scripting while still presenting users with a single, graphical interface for processing and analyzing data. The LabKey Server system also stands out among Luminex tools for enabling smooth, secure transfer of data, quality control information, and analyses between collaborators. LabKey Server and its Luminex features are freely available as open source software at http://www.labkey.com under the Apache 2.0 license.
doi:10.1186/1471-2105-14-145
PMCID: PMC3671158  PMID: 23631706
6.  Immune-Correlates Analysis of an HIV-1 Vaccine Efficacy Trial 
The New England Journal of Medicine  2012;366(14):1275-1286.
BACKGROUND
In the RV144 trial, the estimated efficacy of a vaccine regimen against human immunodeficiency virus type 1 (HIV-1) was 31.2%. We performed a case–control analysis to identify antibody and cellular immune correlates of infection risk.
METHODS
In pilot studies conducted with RV144 blood samples, 17 antibody or cellular assays met prespecified criteria, of which 6 were chosen for primary analysis to determine the roles of T-cell, IgG antibody, and IgA antibody responses in the modulation of infection risk. Assays were performed on samples from 41 vaccinees who became infected and 205 uninfected vaccinees, obtained 2 weeks after final immunization, to evaluate whether immune-response variables predicted HIV-1 infection through 42 months of follow-up.
RESULTS
Of six primary variables, two correlated significantly with infection risk: the binding of IgG antibodies to variable regions 1 and 2 (V1V2) of HIV-1 envelope proteins (Env) correlated inversely with the rate of HIV-1 infection (estimated odds ratio, 0.57 per 1-SD increase; P = 0.02; q = 0.08), and the binding of plasma IgA antibodies to Env correlated directly with the rate of infection (estimated odds ratio, 1.54 per 1-SD increase; P = 0.03; q = 0.08). Neither low levels of V1V2 antibodies nor high levels of Env-specific IgA antibodies were associated with higher rates of infection than were found in the placebo group. Secondary analyses suggested that Env-specific IgA antibodies may mitigate the effects of potentially protective antibodies.
CONCLUSIONS
This immune-correlates study generated the hypotheses that V1V2 antibodies may have contributed to protection against HIV-1 infection, whereas high levels of Env-specific IgA antibodies may have mitigated the effects of protective antibodies. Vaccines that are designed to induce higher levels of V1V2 antibodies and lower levels of Env-specific IgA antibodies than are induced by the RV144 vaccine may have improved efficacy against HIV-1 infection.
doi:10.1056/NEJMoa1113425
PMCID: PMC3371689  PMID: 22475592
7.  Borrowing Information across Populations in Estimating Positive and Negative Predictive Values 
Summary
A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy.
doi:10.1111/j.1467-9876.2011.00761.x
PMCID: PMC3196635  PMID: 22021938
Biomarker; Classification; NPV; PPV; Sensitivity; Specificity
8.  Bayesian inference for generalized linear mixed models 
Biostatistics (Oxford, England)  2010;11(3):397-412.
Generalized linear mixed models (GLMMs) continue to grow in popularity due to their ability to directly acknowledge multiple levels of dependency and model different data types. For small sample sizes especially, likelihood-based inference can be unreliable with variance components being particularly difficult to estimate. A Bayesian approach is appealing but has been hampered by the lack of a fast implementation, and the difficulty in specifying prior distributions with variance components again being particularly problematic. Here, we briefly review previous approaches to computation in Bayesian implementations of GLMMs and illustrate in detail, the use of integrated nested Laplace approximations in this context. We consider a number of examples, carefully specifying prior distributions on meaningful quantities in each case. The examples cover a wide range of data types including those requiring smoothing over time and a relatively complicated spline model for which we examine our prior specification in terms of the implied degrees of freedom. We conclude that Bayesian inference is now practically feasible for GLMMs and provides an attractive alternative to likelihood-based approaches such as penalized quasi-likelihood. As with likelihood-based approaches, great care is required in the analysis of clustered binary data since approximation strategies may be less accurate for such data.
doi:10.1093/biostatistics/kxp053
PMCID: PMC2883299  PMID: 19966070
Integrated nested Laplace approximations; Longitudinal data; Penalized quasi-likelihood; Prior specification; Spline models
9.  Regulation of the Different Chromatin States of Autosomes and X Chromosomes in the Germ Line of C. elegans 
Science (New York, N.Y.)  2002;296(5576):2235-2238.
The Maternal-Effect Sterile (MES) proteins are essential for germline viability in Caenorhabditis elegans. Here, we report that MES-4, a SET-domain protein, binds to the autosomes but not to the X chromosomes. MES-2, MES-3, and MES-6 are required to exclude MES-4 and markers of active chromatin from the X chromosomes. These findings strengthen the emerging view that in the C. elegans germ line, the X chromosomes differ in chromatin state from the autosomes and are generally silenced. We propose that all four MES proteins participate in X-chromosome silencing, and that the role of MES-4 is to exclude repressors from the autosomes, thus enabling efficient repression of the Xs.
doi:10.1126/science.1070790
PMCID: PMC2435369  PMID: 12077420
10.  MES-4: an autosome-associated histone methyltransferase that participates in silencing the X chromosomes in the C. elegans germ line 
Development (Cambridge, England)  2006;133(19):3907-3917.
Germ cell development in C. elegans requires that the X chromosomes be globally silenced during mitosis and early meiosis. We previously found that the nuclear proteins MES-2, MES-3, MES-4 and MES-6 regulate the different chromatin states of autosomes versus X chromosomes and are required for germline viability. Strikingly, the SET-domain protein MES-4 is concentrated on autosomes and excluded from the X chromosomes. Here, we show that MES-4 has histone H3 methyltransferase (HMT) activity in vitro, and is required for histone H3K36 dimethylation in mitotic and early meiotic germline nuclei and early embryos. MES-4 appears unlinked to transcription elongation, thus distinguishing it from other known H3K36 HMTs. Based on microarray analysis, loss of MES-4 leads to derepression of X-linked genes in the germ line. We discuss how an autosomally associated HMT may participate in silencing genes on the X chromosome, in coordination with the direct silencing effects of the other MES proteins.
doi:10.1242/dev.02584
PMCID: PMC2435371  PMID: 16968818
C. elegans; MES proteins; Histone methylation; Germ line; X-chromosome silencing

Results 1-10 (10)