Project description:The 2009 H1N1 influenza A virus that has targeted not only those with chronic medical illness, the very young and old, but also a large segment of the patient population that has previously been afforded relative protection - those who are young, generally healthy, and immune naive. The illness is mild in most, but results in hospitalization and severe ARDS in an important minority. Among those who become critically ill, 20-40% will die, predominantly of severe hypoxic respiratory failure. However, and potentially in part due to the young age of those affected, intensive care with aggressive oxygenation support will allow most people to recover. The volume of patients infected and with critical illness placed substantial strain on the capacity of the health care system and critical care most specifically. Despite this, the 2009 pandemic has engaged our specialty and highlighted its importance like no other. Thus far, the national and global critical care response has been brisk, collaborative and helpful - not only for this pandemic, but for subsequent challenges in years ahead.
Project description:Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.
Project description:The recent outbreaks of influenza A/H5N1 and 'swine influenza' A/H1N1 have caused global concern over the potential for a new influenza pandemic. Although it is impossible to predict when the next pandemic will occur, appropriate planning is still needed to maximize efficient use of resources and to minimize loss of life and productivity. Many tools now exist to assist countries in evaluating their plans but there is little to aid in writing of the plans. This study discusses the process of drafting a pandemic influenza preparedness plan for developing countries that conforms to the International Health Regulations of 2005 and recommendations of the World Health Organization. Stakeholders from many sectors should be involved in drafting a comprehensive pandemic influenza plan that addresses all levels of preparedness.
Project description:MotivationPleiotropic SNPs are associated with multiple traits. Such SNPs can help pinpoint biological processes with an effect on multiple traits or point to a shared etiology between traits. We present PolarMorphism, a new method for the identification of pleiotropic SNPs from genome-wide association studies (GWAS) summary statistics. PolarMorphism can be readily applied to more than two traits or whole trait domains. PolarMorphism makes use of the fact that trait-specific SNP effect sizes can be seen as Cartesian coordinates and can thus be converted to polar coordinates r (distance from the origin) and theta (angle with the Cartesian x-axis, in the case of two traits). r describes the overall effect of a SNP, while theta describes the extent to which a SNP is shared. r and theta are used to determine the significance of SNP sharedness, resulting in a P-value per SNP that can be used for further analysis.ResultsWe apply PolarMorphism to a large collection of publicly available GWAS summary statistics enabling the construction of a pleiotropy network that shows the extent to which traits share SNPs. We show how PolarMorphism can be used to gain insight into relationships between traits and trait domains and contrast it with genetic correlation. Furthermore, pathway analysis of the newly discovered pleiotropic SNPs demonstrates that analysis of more than two traits simultaneously yields more biologically relevant results than the combined results of pairwise analysis of the same traits. Finally, we show that PolarMorphism is more efficient and more powerful than previously published methods.Availability and implementationcode: https://github.com/UMCUGenetics/PolarMorphism, results: 10.5281/zenodo.5844193.Supplementary informationSupplementary data are available at Bioinformatics online.
Project description:Challenges facing seasonal and pandemic influenza vaccination include: increasing the immunogenicity of seasonal vaccines for the most vulnerable, increasing vaccination coverage against seasonal influenza, and developing vaccines against pandemic strains that are immunogenic with very low quantities of antigen to maximize the number of people who can be vaccinated with a finite production capacity. We review Sanofi Pasteur's epidemic and pandemic influenza research and development programmes with emphasis on two key projects: intradermal influenza vaccine for seasonal vaccination of both elderly and younger adults, and pandemic influenza vaccine.
Project description:Blood microbiome is important to investigate microbial-host interactions and the effects on systemic immune perturbations. However, this effort has met with major challenges due to low microbial biomass and background artifacts. In the current study, microbial 16S DNA sequencing was applied to analyze plasma microbiome. We have developed a quality-filtering strategy to evaluate and exclude low levels of microbial sequences, potential contaminations, and artifacts from plasma microbial 16S DNA sequencing analyses. Furthermore, we have applied our technique in three cohorts, including tobacco-smokers, HIV-infected individuals, and individuals with systemic lupus erythematosus (SLE), as well as corresponding controls. More than 97% of total sequence data was removed using stringent quality-filtering strategy analyses; those removed amplicon sequence variants (ASVs) were low levels of microbial sequences, contaminations, and artifacts. The specifically enriched pathobiont bacterial ASVs have been identified in plasmas from tobacco-smokers, HIV-infected individuals, and individuals with SLE but not from control subjects. The associations between these ASVs and disease pathogenesis were demonstrated. The pathologic activities of some identified bacteria were further verified in vitro. We present a quality-filtering strategy to identify pathogenesis-associated plasma microbiome. Our approach provides a method for studying the diagnosis of subclinical microbial infection as well as for understanding the roles of microbiome-host interaction in disease pathogenesis.
Project description:The unprecedented global spread of highly pathogenic avian H5N1 influenza viruses within the past ten years and their extreme lethality to poultry and humans has underscored their potential to cause an influenza pandemic. Combating the threat of an impending H5N1 influenza pandemic will require a combination of pharmaceutical and nonpharmaceutical intervention strategies. The emergence of the H1N1 pandemic in 2009 emphasised the unpredictable nature of a pandemic influenza. Undoubtedly, vaccines offer the most viable means to combat a pandemic threat. Current egg-based influenza vaccine manufacturing strategies are unlikely to be able to cater to the huge, rapid global demand because of the anticipated scarcity of embryonated eggs in an avian influenza pandemic and other factors associated with the vaccine production process. Therefore, alternative, egg-independent vaccine manufacturing strategies should be evaluated to supplement the traditional egg-derived influenza vaccine manufacturing. Furthermore, evaluation of dose-sparing strategies that offer protection with a reduced antigen dose will be critical for pandemic influenza preparedness. Development of new antiviral therapeutics and other, nonpharmaceutical intervention strategies will further supplement pandemic preparedness. This review highlights the current status of egg-dependent and egg-independent strategies against an avian influenza pandemic.
Project description:More than 15 years after the first human cases of influenza A/H5N1 in Hong Kong, the world remains at risk for an H5N1 pandemic. Preparedness activities have focused on antiviral stockpiling and distribution, development of a human H5N1 vaccine, operationalizing screening and social distancing policies, and other non-pharmaceutical interventions. The planning of these interventions has been done in an attempt to lessen the cumulative mortality resulting from a hypothetical H5N1 pandemic. In this theoretical study, we consider the natural limitations on an H5N1 pandemic's mortality imposed by the virus' epidemiological-evolutionary constraints. Evolutionary theory dictates that pathogens should evolve to be relatively benign, depending on the magnitude of the correlation between a pathogen's virulence and its transmissibility. Because the case fatality of H5N1 infections in humans is currently 60 per cent, it is doubtful that the current viruses are close to their evolutionary optimum for transmission among humans. To describe the dynamics of virulence evolution during an H5N1 pandemic, we build a mathematical model based on the patterns of clinical progression in past H5N1 cases. Using both a deterministic model and a stochastic individual-based simulation, we describe (i) the drivers of evolutionary dynamics during an H5N1 pandemic, (ii) the range of case fatalities for which H5N1 viruses can successfully cause outbreaks in humans, and (iii) the effects of different kinds of social distancing on virulence evolution. We discuss two main epidemiological-evolutionary features of this system (i) the delaying or slowing of an epidemic which results in a majority of hosts experiencing an attenuated virulence phenotype and (ii) the strong evolutionary pressure for lower virulence experienced by the virus during a period of intense social distancing.
Project description:Recent studies suggest excessive complement activation in severe coronavirus disease-19 (COVID-19). The latter shares common characteristics with complement-mediated thrombotic microangiopathy (TMA). We hypothesized that genetic susceptibility would be evident in patients with severe COVID-19 (similar to TMA) and associated with disease severity. We analyzed genetic and clinical data from 97 patients hospitalized for COVID-19. Through targeted next-generation-sequencing we found an ADAMTS13 variant in 49 patients, along with two risk factor variants (C3, 21 patients; CFH,34 patients). 31 (32%) patients had a combination of these, which was independently associated with ICU hospitalization (p = 0.022). Analysis of almost infinite variant combinations showed that patients with rs1042580 in thrombomodulin and without rs800292 in complement factor H did not require ICU hospitalization. We also observed gender differences in ADAMTS13 and complement-related variants. In light of encouraging results by complement inhibitors, our study highlights a patient population that might benefit from early initiation of specific treatment.
Project description:Bacterial membranes are complex and dynamic, arising from an array of evolutionary pressures. One enzyme that alters membrane compositions through covalent lipid modification is MprF. We recently identified that Streptococcus agalactiae MprF synthesizes lysyl-phosphatidylglycerol (Lys-PG) from anionic PG, and a novel cationic lipid, lysyl-glucosyl-diacylglycerol (Lys-Glc-DAG), from neutral glycolipid Glc-DAG. This unexpected result prompted us to investigate whether Lys-Glc-DAG occurs in other MprF-containing bacteria, and whether other novel MprF products exist. Here, we studied protein sequence features determining MprF substrate specificity. First, pairwise analyses identified several streptococcal MprFs synthesizing Lys-Glc-DAG. Second, a restricted Boltzmann machine-guided approach led us to discover an entirely new substrate for MprF in Enterococcus, diglucosyl-diacylglycerol (Glc2-DAG), and an expanded set of organisms that modify glycolipid substrates using MprF. Overall, we combined the wealth of available sequence data with machine learning to model evolutionary constraints on MprF sequences across the bacterial domain, thereby identifying a novel cationic lipid.