Increasing the Power to Detect Causal Associations by Combining Genotypic and Expression Data in Segregating Populations

To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships among variables of interest. Given the complexity of molecular networks underlying common human disease traits, and the fact that biological networks can change depending on environmental conditions and genetic factors, large datasets, generally involving multiple perturbations (experiments), are required to reconstruct and reliably extract information from these networks. With limited resources, the balance of coverage of multiple perturbations and multiple subjects in a single perturbation needs to be considered in the experimental design. Increasing the number of experiments, or the number of subjects in an experiment, is an expensive and time-consuming way to improve network reconstruction. Integrating multiple types of data from existing subjects might be more efficient. For example, it has recently been demonstrated that combining genotypic and gene expression data in a segregating population leads to improved network reconstruction, which in turn may lead to better predictions of the effects of experimental perturbations on any given gene. Here we simulate data based on networks reconstructed from biological data collected in a segregating mouse population and quantify the improvement in network reconstruction achieved using genotypic and gene expression data, compared with reconstruction using gene expression data alone. We demonstrate that networks reconstructed using the combined genotypic and gene expression data achieve a level of reconstruction accuracy that exceeds networks reconstructed from expression data alone, and that fewer subjects may be required to achieve this superior reconstruction accuracy. We conclude that this integrative genomics approach to reconstructing networks not only leads to more predictive network models, but also may save time and money by decreasing the amount of data that must be generated under any given condition of interest to construct predictive network models

Mixed Markov models

Markov random fields can encode complex probabilistic relationships involving multiple variables and admit efficient procedures for probabilistic inference. However, from a knowledge engineering point of view, these models suffer from a serious limitation. The graph of a Markov field must connect all pairs of variables that are conditionally dependent even for a single choice of values of the other variables. This makes it hard to encode interactions that occur only in a certain context and are absent in all others. Furthermore, the requirement that two variables be connected unless always conditionally independent may lead to excessively dense graphs, obscuring the independencies present among the variables and leading to computationally prohibitive inference algorithms. Mumford [Mumford, D. (1996) in ICIAM 95, eds. Kirchgassner, K., Marenholtz, O. & Mennicken, R. (Akademie Verlag, Berlin), pp. 233–256] proposed an alternative modeling framework where the graph need not be rigid and completely determined a priori. Mixed Markov models contain node-valued random variables that, when instantiated, augment the graph by a set of transient edges. A single joint probability distribution relates the values of regular and node-valued variables. In this article, we study the analytical and computational properties of mixed Markov models. In particular, we show that positive mixed models have a local Markov property that is equivalent to their global factorization. We also describe a computationally efficient procedure for answering probabilistic queries in mixed Markov models

PHOSPHATE BINDER THERAPY AND SERUM PHOSPHATE CONTROL FOLLOWING INITIATION OF HAEMODIALYSIS

Hyperphosphataemia is associated with increased all-cause mortality in patients with chronic kidney disease (CKD), but serum phosphate (P) levels can be managed by dialysis, diet and the use of P binders. Serum P data were obtained retrospectively from a US dialysis provider for the 9 months following initiation of haemodialysis (HD) in CKD patients, who were then grouped according to the variations in their serum P. Group baseline characteristics and changes in P binder use over time were described. Variations in average monthly serum P values from months 4 to 9 were classified as either consistently in the target range (CT, 3.5–5.5 mg/dL), consistently low (CL, < 3.5 mg/dL), consistently high (CH, > 5.5 mg/dL), or varying between the low and target (LT), target and high (TH) or the low and high ranges (LH). For each group, baseline characteristics and changes in P binder use during the study were compared with CT (the reference group) to identify differences. In total, 47742 eligible patients were allocated to the six groups: CT, 7301; CL, 131; CH, 5001; LT, 6469; TH, 24469; LH, 4371. CH, TH, and LH were significantly younger than CT, with fewer comorbidities, higher incidence of elevated parathyroid hormone (PTH) and higher mean serum P; CH and TH also had higher levels of P binder use. CL and LT were older, with more comorbidities, lower PTH levels and lower levels of P binder use than CT. Overall, comparing months 8–9 with baseline (months 1–3), more patients received P binder therapy (51.7 vs 35.0%), on a larger percentage of days (50.0 vs 30.9%), but with little change in mean serum P (5.3 vs 5.2 mg/dL). By group, mean serum P increased numerically in CH (7.5 vs 6.6 mg/dL) and TH (5.6 vs 5.4 mg/dL) but decreased in other groups. Serum P can be difficult to control following initiation of HD. Patients with elevated serum P were younger, and most had higher P binder use than the reference group. Overall, binder use was lower than in other studies of HD patients. Dietary education and higher doses of the most effective P binders may be needed to improve P management

Drag from fishing gear entangling North Atlantic right whales

Lethal and sublethal fishing gear entanglement is pervasive in North Atlantic right whales (Eubalaena glacialis). Entanglement can lead to direct injury and is likely to incur substantial energetic costs. This study (1) evaluates drag characteristics of entangled right whales, (2) contextualizes gear drag measurements for individual whales, and (3) quantifies the benefits of partial disentanglement. A load cell measured drag forces on 15 sets of fishing gear removed from entangled right whales, a towed satellite telemetry buoy, and 200 m of polypropylene line as it was shortened to 25 m, as they were towed behind a vessel at ~0.77, 1.3, and 2.1 m/s (~1.5, 2.5, and 4 knots) and ~0, 3, and 6 m depth. Mean drag ranges from 8.5 N to 315 N, and can be predicted from the dry weight or length of the gear. Combining gear drag measurements with theoretical estimates of drag on whales’ bodies suggests that on average, entanglement increases drag and propulsive power by 1.47 fold. Reducing trailing line length by 75% can reduce parasitic gear drag by 85%, reinforcing current disentanglement response practices. These drag measurements can be incorporated into disentanglement response, serious injury determination, and evaluation of sublethal effects on population dynamics

Evaluation of HSV-2 gE Binding to IgG-Fc and Application for Vaccine Development

Glycoprotein E (gE) and glycoprotein I (gI) are expressed as a heterodimer on the surface of Herpes simplex virus (HSV). Glycoprotein E binds Fc domain of immunoglobulin G (IgG) and inhibits activities mediated by the IgG Fc domain, contributing to immune evasion by HSV. It has been reported that HSV type 1 gE (gE-1) is capable of binding IgG Fc as a monomer and in a heterodimeric complex with gI, with the heterodimer having 50- to100-fold greater affinity for Fc than gE alone. We report the production of both a soluble form of HSV type 2 gE (gE-2) and a soluble HSV-2 gE/gI heterodimer (gE-2/gI-2). Characterization of soluble gE-2 by surface plasmon resonance (SPR) demonstrates that it is incapable of binding human IgG or the IgG Fc domain. Co-expression with HSV-2 gI (gI-2) and purification of the gE-2/gI-2 heterodimer enable gE-2 to bind human IgG through its Fc domain. We hypothesize that functional epitopes of wildtype gE-2 may be masked by plasma IgG Fc and affect the immunogenicity of the gE-2/gI-2 heterodimer as a vaccine antigen. A series of gE-2 mutations within the surface-exposed Fc:gE-2 interface was designed, and gE-2 mutants were co-expressed with gI-2. Evaluation of twelve gE-2 mutant heterodimers by SPR assay identified nine gE-2 mutations which abrogated or reduced Fc binding while maintaining heterodimer formation with gI. Vaccinating rabbits with the four most Fc-binding deficient gE-2/gI-2 heterodimers elicited comparable anti-heterodimer binding antibody titers and statistically significantly higher serum neutralization antibody levels than wildtype heterodimers. Taken together, these data support the concept of rational antigen design for improved vaccine candidates

High-Potency Human Immunodeficiency Virus Vaccination Leads to Delayed and Reduced CD8(+) T-Cell Expansion but Improved Virus Control

CD8(+) T lymphocytes are thought to play an important role in the control of acute and chronic human immunodeficiency virus infections. However, there is a significant delay between infection and the first observed increase in virus-specific CD8(+) T-cell numbers. Prior to this time, viral kinetics are not significantly different between controls and vaccinees. Surprisingly, higher initial virus-specific CD8(+) T-cell numbers lead to a longer delay prior to initial CD8(+) T-cell expansion, and slower CD8(+) T-cell increases. Nevertheless, higher initial CD8(+) T-cell numbers were associated with reduced peak and chronic viral loads and reduced CD4(+) T-cell depletion

Virologic Outcomes with Molnupiravir in Non-hospitalized Adult Patients with COVID-19 from the Randomized, Placebo-Controlled MOVe-OUT Trial

Abstract Introduction The randomized, placebo-controlled, double-blind MOVe-OUT trial demonstrated molnupiravir (800 mg every 12 h for 5 days) as safe and effective for outpatient treatment of mild-to-moderate COVID-19, significantly reducing the risk of hospitalization/death in high-risk adults. At the time of that report, virologic assessments from the trial were partially incomplete as a result of their time-intensive nature. Here we present final results from all prespecified virology endpoints in MOVe-OUT based on the full trial dataset. Methods Nasopharyngeal swabs were collected at baseline (day 1, prior to first dose) and days 3, 5 (end-of-treatment visit), 10, 15, and 29. From these samples, change from baseline in SARS-CoV-2 RNA titers (determined by quantitative PCR), detection of infectious SARS-CoV-2 (by plaque assay), and SARS-CoV-2 viral error induction (determined by whole genome next-generation sequencing) were assessed as exploratory endpoints. Results Molnupiravir was associated with greater mean reductions from baseline in SARS-CoV-2 RNA than placebo (including 50% relative reduction at end-of-treatment) through day 10. Among participants with infectious virus detected at baseline (n = 96 molnupiravir, n = 97 placebo) and evaluable post-baseline samples, no molnupiravir-treated participant had infectious SARS-CoV-2 by day 3, whereas infectious virus was recovered from 21% of placebo-arm participants on day 3 and 2% at end-of-treatment. Consistent with molnupiravir’s mechanism of action, sequence analysis demonstrated that molnupiravir was associated with an increased number of low-frequency transition errors randomly distributed across the SARS-CoV-2 RNA genome compared with placebo (median 143.5 molnupiravir, 15 placebo), while transversion errors were infrequent overall (median 2 in both arms). Outcomes were consistent regardless of baseline SARS-CoV-2 clade, presence of SARS-CoV-2-specific immune response, or viral load. Conclusions A 5-day course of orally administered molnupiravir demonstrated a consistently greater virologic effect than placebo, including rapidly eliminating infectious SARS-CoV-2, in high-risk outpatients with mild-to-moderate COVID-19. Trial Registration ClinicalTrials.gov, NCT04575597

A Rapid and Improved Method to Generate Recombinant Dengue Virus Vaccine Candidates

<div><p>Dengue is one of the most important mosquito-borne infections accounting for severe morbidity and mortality worldwide. Recently, the tetravalent chimeric live attenuated Dengue vaccine Dengvaxia^® was approved for use in several dengue endemic countries. In general, live attenuated vaccines (LAV) are very efficacious and offer long-lasting immunity against virus-induced disease. Rationally designed LAVs can be generated through reverse genetics technology, a method of generating infectious recombinant viruses from full length cDNA contained in bacterial plasmids. <i>In vitro</i> transcribed (IVT) viral RNA from these infectious clones is transfected into susceptible cells to generate recombinant virus. However, the generation of full-length dengue virus cDNA clones can be difficult due to the genetic instability of viral sequences in bacterial plasmids. To circumvent the need for a single plasmid containing a full length cDNA, <i>in vitro</i> ligation of two or three cDNA fragments contained in separate plasmids can be used to generate a full-length dengue viral cDNA template. However, <i>in vitro</i> ligation of multiple fragments often yields low quality template for IVT reactions, resulting in inconsistent low yield RNA. These technical difficulties make recombinant virus recovery less efficient. In this study, we describe a simple, rapid and efficient method of using LONG-PCR to recover recombinant chimeric Yellow fever dengue (CYD) viruses as potential dengue vaccine candidates. Using this method, we were able to efficiently generate several viable recombinant viruses without introducing any artificial mutations into the viral genomes. We believe that the techniques reported here will enable rapid and efficient recovery of recombinant flaviviruses for evaluation as vaccine candidates and, be applicable to the recovery of other RNA viruses.</p></div