Estimating the Burden of Medically Attended Norovirus Gastroenteritis: Modeling Linked Primary Care and Hospitalization Datasets.

Background: Norovirus is the leading cause of community-acquired and nosocomial acute gastroenteritis. Routine testing for norovirus is seldom undertaken, and diagnosis is mainly based on presenting symptoms. This makes understanding the burden of medically attended norovirus-attributable gastroenteritis (MA-NGE) and targeting care and prevention strategies challenging. Methods: We used linked population-based healthcare datasets (Clinical Practice Research Datalink General Practice OnLine Database linked with Hospital Episode Statistics Admitted Patient Care) to model the incidence of MA-NGE associated with primary care consultations or hospitalizations according to age groups in England in the period July 2007-June 2013. Results: Mean annual incidence rates of MA-NGE were 4.9/1000 person-years and 0.7/1000 person-years for episodes involving primary care or hospitalizations, respectively. Incidence rates were highest in children aged 65 years (1.7/1000 person-years). Conclusions: In this particular study, the burden of MA-NGE estimated from healthcare datasets was higher than previously estimated in small cohort studies in England. Routinely collected primary care and hospitalization datasets are useful resources to estimate and monitor the burden of MA-NGE in a population over time

Lower-Order Effects Adjustment in Quantitative Traits Model-Based Multifactor Dimensionality Reduction

Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on “top” findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using “on-the-fly” lower-order effects adjusting when screening for SNP-SNP interactions using Model-Based Multifactor Dimensionality Reduction analysis

Comparison of genetic association strategies in the presence of rare alleles

In the quest for the missing heritability of most complex diseases, rare variants have received increased attention. Advances in large-scale sequencing have led to a shift from the common disease/common variant hypothesis to the common disease/rare variant hypothesis or have at least reopened the debate about the relevance and importance of rare variants for gene discoveries. The investigation of modeling and testing approaches to identify significant disease/rare variant associations is in full motion. New methods to better deal with parameter estimation instabilities, convergence problems, or multiple testing corrections in the presence of rare variants or effect modifiers of rare variants are in their infancy. Using a recently developed semiparametric strategy to detect causal variants, we investigate the performance of the model-based multifactor dimensionality reduction (MB-MDR) technique in terms of power and family-wise error rate (FWER) control in the presence of rare variants, using population-based and family-based data (FAM-MDR). We compare family-based results obtained from MB-MDR analyses to screening findings from a quantitative trait Pedigree-based association test (PBAT). Population-based data were further examined using penalized regression models. We restrict attention to all available single-nucleotide polymorphisms on chromosome 4 and consider Q1 as the outcome of interest. The considered family-based methods identified marker C4S4935 in the VEGFC gene with estimated power not exceeding 0.35 (FAM-MDR), when FWER was kept under control. The considered population-based methods gave rise to highly inflated FWERs (up to 90% for PBAT screening)

FAM-MDR: A Flexible Family-Based Multifactor Dimensionality Reduction Technique to Detect Epistasis Using Related Individuals

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information

Large amplitude solitary waves in space plasmas

The First part of this thesis, comprising the Chapters 1-6, deals with nonlinear electro-static waves. In Chapter 1 we introduce the different methods used in the study of onlinear waves, i.e. the reductive perturbation and Sagdeev pseudopotential methods. In Chapter 2 we then develop the alternative fluid-dynamic McKenzie approach. We derive a general analytic theory for large amplitude stationary electrostatic solitary waves in multispecies plasmas. In the following chapters we apply these general results to certain specific examples. In two-electron plasmas we consider electron-acoustic solitary waves in Chapter 3 and ion-acoustic solitons in Chapter 4. Then we consider dusty plasmas, which allow ion-acoustic and dust-acoustic solitary waves. The former are analogous to those studied in two-electron plasmas and the latter are the subject of Chapter 5. In Chapter 6 our formalism is extended to include self-gravitation, and applied to study self-gravitational solitons in a two-species neutral molecular cloud. The second part of this thesis, i.e. the Chapters 7-10, is concerned with nonlinear electromagnetic modes. In Chapter 7 a general multispecies theoretical framework for large amplitude stationary electromagnetic solitary waves in cold plasmas is developed. In Chapter 8 this is applied to large amplitude electromagnetic solitons in pair plasmas, propagating obliquely to the magnetic field. In ordinary hydrogen plasmas at parallel propagation we find so-called oscillitons, having both stationary amplitude and phase. These are the subject of Chapter 9. In Chapter 10 we study the slow amplitude modulation of electromagnetic waves in pair plasmas, due to coupling with various slow changes in the presence of the wave field. A third part, Chapters 11-13, deals with some dusty plasma problems. The influence of a drift of the dust with respect to the plasma on magnetosonic modes in dusty plasmas is studied in Chapter 11. We focus on dust distributions in Chapter 12 and charge fluctuations in Chapter 13

Large amplitude solitary electromagnetic waves in electron-positron plasmas

Waves in electron-positron plasmas have fundamentally different dispersion characteristics due to the equal charge-to-mass ratios between negative and positive charges, which mix different timescales, and are of interest in understanding aspects of pulsars and active galactic nuclei, where astrophysical electron-positron plasmas occur. Earlier systematic nonlinear treatments of parallel propagating electromagnetic waves via a reductive perturbation analysis had indicated unusual results, namely a vector equivalent of the modified Korteweg-de Vries equation. The latter is nonintegrable except in the case of linear polarization when it becomes equivalent to the scalar (integrable) modified Korteweg-de Vries equation. Here large amplitude purely stationary nonlinear solitary waves are studied in their own reference frame via the McKenzie approach. The behavior of the wave magnetic field can be expressed through an energy integral that involves the Mach number of the structure. Possible solitons are super-Alfvenic and occur symmetrically for positive or negative fields, owing to the obvious symmetry between positive and negative charges with the same mass. The limits on the allowable Mach numbers and soliton amplitudes have also been computed. (C) 2004 American Institute of Physics

Electromagnetic modes in dusty plasmas with charge and mass distributions

Electromagnetic modes in dusty plasmas are studied for polydisperse dust grains with a distribution in charge and mass. Owing to the different charge and mass weightings of the velocities, there occurs an infinite chain of equations of motion, coupled through the magnetic part of the Lorentz force. Depending on the frequency and associated convergence regimes, one has to close the chain in ascending or in descending order. Both series together lead to the polydisperse dispersion law that is a generalization of monodisperse or size distributed dust. Power-law distributions typical for heliospheric plasmas are discussed as an application. (C) 2003 American Institute of Physics

Parallel propagating electromagnetic solitons and oscillitons in space plasmas and in relativistic electron-positron plasmas

An overview is given of methods to study weak and strong nonlinear modes in multispecies plasmas, with a discussion of how they correspond (or not) for phenomena at not too strong amplitudes. Reductive perturbation analysis leads for weak nonlinear waves to several well known nonlinear evolution equations. In contrast, strong nonlinear phenomena are dealt with by immediately looking for stationary solutions of the model equations. While this works well for electrostatic modes via the Sagdeev pseudopotential technique, large amplitude, parallel propagating solitary electromagnetic waves occur as oscillitons, for which the correct nonlinear evolution equation is still lacking. Electromagnetic modes in (relativistic) electron-positron plasmas are an exception, in that they give pure solitons, both at large and smaller nonlinear amplitudes. The behaviour of the wave magnetic field is expressed through an energy integral that involves the Mach number of the structure, thus yielding the limits on the allowable Mach numbers and soliton amplitudes