Reducing the Probability of False Positive Research Findings by Pre-Publication Validation - Experience with a Large Multiple Sclerosis Database

*Objective*
We have assessed the utility of a pre-publication validation policy in reducing the probability of publishing false positive research findings. 
*Study design and setting*
The large database of the Sylvia Lawry Centre for Multiple Sclerosis Research was split in two parts: one for hypothesis generation and a validation part for confirmation of selected results. We present case studies from 5 finalized projects that have used the validation policy and results from a simulation study.
*Results*
In one project, the "relapse and disability" project as described in section II (example 3), findings could not be confirmed in the validation part of the database. The simulation study showed that the percentage of false positive findings can exceed 20% depending on variable selection. 
*Conclusion*
We conclude that the validation policy has prevented the publication of at least one research finding that could not be validated in an independent data set (and probably would have been a "true" false-positive finding) over the past three years, and has led to improved data analysis, statistical programming, and selection of hypotheses. The advantages outweigh the lost statistical power inherent in the process

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

Genetic-epidemiological studies on monozygotic (MZ) twins have been used for decades to tease out the relative contributions of genes and the environment to a trait. Phenotypic discordance in MZ twins has traditionally been ascribed to non-shared environmental factors acting after birth, however recent data indicate that this explanation is far too simple. In this paper, we review other reasons for discordance, including differences in the in utero environment, genetic mosaicism, and stochastic factors, focusing particularly on epigenetic discordance. Epigenetic differences are gaining increasing recognition. Although it is clear that in specific cases epigenetic alterations provide a causal factor in disease etiology, the overall significance of epigenetics in twin discordance remains unclear. It is also challenging to determine the causality and relative contributions of environmental, genetic, and stochastic factors to epigenetic variability. Epigenomic profiling studies have recently shed more light on the dynamics of temporal methylation change and methylome heritability, yet have not given a definite answer regarding their relevance to disease, because of limitations in establishing causality. Here, we explore the subject of epigenetics as another component in human phenotypic variability and its links to disease focusing particularly on evidence from MZ twin studies

An Extremes of outcome strategy provides evidence that multiple sclerosis severity is determined by alleles at the <i>HLA-DRB1</i> locus

Multiple sclerosis (MS) is a common inflammatory disease of the central nervous system unsurpassed for variability in disease outcome. A cohort of sporadic MS cases (n=63), taken from opposite extremes of the distribution of long-term outcome, was used to determine the role of the HLA-DRB1 locus on MS disease severity. Genotyping sets of benign and malignant MS patients showed that HLA-DRB1*01 was significantly underrepresented in malignant compared with benign cases. This allele appears to attenuate the progressive disability that characterizes MS in the long term. The observation was doubly replicated in (i) Sardinian benign and malignant patients and (ii) a cohort of affected sibling pairs discordant for HLA-DRB1*01. Among the latter, mean disability progression indices were significantly lower in those carrying the HLA-DRB1*01 allele compared with their disease-concordant siblings who did not. The findings were additionally supported by similar transmission distortion of HLA-DRB1*04 subtypes closely related to HLA-DRB1*01. The protective effect of HLA-DRB1*01 in sibling pairs may result from a specific epistatic interaction with the susceptibility allele HLA-DRB1*1501. A high-density (&gt;700) SNP examination of the MHC region in the benign and malignant patients could not identify variants differing significantly between the two groups, suggesting that HLA-DRB1 may itself be the disease-modifying locus. We conclude that HLA-DRB1*01, previously implicated in disease resistance, acts as an independent modifier of disease progression. These results closely link susceptibility to long-term outcome in MS, suggesting that shared quantitative MHC-based mechanisms are common to both, emphasizing the central role of this region in pathogenesis

A whole genome screen for association with multiple sclerosis in portuguese patients

Multiple sclerosis (MS) is common in Europe affecting up to 1:500 people. In an effort to identify genes influencing susceptibility to the disease, we have performed a population-based whole genome screen for association. In this study, 6000 microsatellite markers were typed in separately pooled DNA samples from MS patients (n = 188) and matched controls (n = 188). Interpretable data was obtained from 4661 of these markers. Refining analysis of the most promising markers identified 10 showing potential evidence for association.SERONO (Portugal).Fundação para a Ciência e a Tecnologia (FCT) - grant FRH/BD/9111/2002.British Council/ICCTI.Wellcome Trust, Multiple Sclerosis Societies of the United States and Great Britain, Multiple Sclerosis International Federation - GAMES project - grant 057097

Understanding Interorganizational Learning Based on Social Spaces and Learning Episodes

Different organizational settings have been gaining ground in the world economy, resulting in a proliferation of different forms of strategic alliances that translate into a growth in the number of organizations that have started to deal with interorganizational relationships with different actors. These circumstances reinforce Crossan, Lane, White and Djurfeldt (1995) and Crossan, Mauer and White (2011) in exploring what authors refer to as the fourth, interorganizational, level of learning. These authors, amongst others, suggest that the process of interorganizational learning (IOL) warrants investigation, as its scope of analysis needs widening and deepening. Therefore, this theoretical essay is an attempt to understand IOL as a dynamic process found in interorganizational cooperative relationships that can take place in different structured and unstructured social spaces and that can generate learning episodes. According to this view, IOL is understood as part of an organizational learning continuum and is analyzed within the framework of practical rationality in an approach that is less cognitive and more social-behavioral

Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction

Sensing is one of the most fundamental tasks for the monitoring, forecasting and control of complex, spatio-temporal systems. In many applications, a limited number of sensors are mobile and move with the dynamics, with examples including wearable technology, ocean monitoring buoys, and weather balloons. In these dynamic systems (without regions of statistical-independence), the measurement time history encodes a significant amount of information that can be extracted for critical tasks. Most model-free sensing paradigms aim to map current sparse sensor measurements to the high-dimensional state space, ignoring the time-history all together. Using modern deep learning architectures, we show that a sequence-to-vector model, such as an LSTM (long, short-term memory) network, with a decoder network, dynamic trajectory information can be mapped to full state-space estimates. Indeed, we demonstrate that by leveraging mobile sensor trajectories with shallow recurrent decoder networks, we can train the network (i) to accurately reconstruct the full state space using arbitrary dynamical trajectories of the sensors, (ii) the architecture reduces the variance of the mean-square error of the reconstruction error in comparison with immobile sensors, and (iii) the architecture also allows for rapid generalization (parameterization of dynamics) for data outside the training set. Moreover, the path of the sensor can be chosen arbitrarily, provided training data for the spatial trajectory of the sensor is available. The exceptional performance of the network architecture is demonstrated on three applications: turbulent flows, global sea-surface temperature data, and human movement biomechanics.Comment: 11 pages, 5 figures, 2 table

Transcriptional profiling avian beta-defensins in chicken oviduct epithelial cells before and after infection with Salmonella enterica serovar Enteritidis

<p>Abstract</p> <p>Background</p> <p><it>Salmonella enterica </it>serovar Enteritidis (SE) colonizes the ovary and oviduct of chickens without causing overt clinical signs which can lead to SE-contamination of the content and membrane of shell-eggs as well as hatchery eggs. The organism utilizes the <it>Salmonella </it>Pathogenicity Island-2 encoded type III secretion system (T3SS-2) to promote persistence in the oviduct of laying hens. In this study, reverse transcriptase-polymerase chain reaction (RT-PCR) was carried out to determine the expression profiles of 14 known avian beta defensins (AvBDs) in primary chicken oviduct epithelial cells (COEC) before and after infections with a wild type SE strain and T3SS mutant SE strains carrying an inactivated <it>sipA </it>or <it>pipB </it>gene.</p> <p>Results</p> <p>Based on the expression levels in uninfected COEC, AvBDs can be loosely grouped into three categories with AvBD4-5 and AvBD9-12 being constitutively expressed at high levels; AvBD1, AvBD3, and AvBD13-14 at moderate levels; and AvBD2 and AvBD6-8 at minimal levels. Infection with the wild type SE strain temporarily repressed certain highly expressed AvBDs and induced the expression of minimally expressed AvBDs. The <it>pipB </it>mutant, compared to the wild type strain, had reduced suppressive effect on the expression of highly expressed AvBDs. Moreover, the <it>pipB </it>mutant elicited significantly higher levels of the minimally expressed AvBDs than the wild type SE or the <it>sipA </it>mutant did.</p> <p>Conclusion</p> <p>Chicken oviduct epithelial cells express most of the known AvBD genes in response to SE infection. PipB, a T3SS-2 effector protein, plays a role in dampening the β-defensin arm of innate immunity during SE invasion of chicken oviduct epithelium.</p

Prognosis of the individual course of disease - steps in developing a decision support tool for Multiple Sclerosis

<p>Abstract</p> <p>Background</p> <p>Multiple sclerosis is a chronic disease of uncertain aetiology. Variations in its disease course make it difficult to impossible to accurately determine the prognosis of individual patients. The Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) developed an "online analytical processing (OLAP)" tool that takes advantage of extant clinical trials data and allows one to model the near term future course of this chronic disease for an individual patient.</p> <p>Results</p> <p>For a given patient the most similar patients of the SLCMSR database are intelligently selected by a model-based matching algorithm integrated into an OLAP-tool to enable real time, web-based statistical analyses. The underlying database (last update April 2005) contains 1,059 patients derived from 30 placebo arms of controlled clinical trials. Demographic information on the entire database and the portion selected for comparison are displayed. The result of the statistical comparison is provided as a display of the course of Expanded Disability Status Scale (EDSS) for individuals in the database with regions of probable progression over time, along with their mean relapse rate. Kaplan-Meier curves for time to sustained progression in the EDSS and time to requirement of constant assistance to walk (EDSS 6) are also displayed. The software-application OLAP anticipates the input MS patient's course on the basis of baseline values and the known course of disease for similar patients who have been followed in clinical trials.</p> <p>Conclusion</p> <p>This simulation could be useful for physicians, researchers and other professionals who counsel patients on therapeutic options. The application can be modified for studying the natural history of other chronic diseases, if and when similar datasets on which the OLAP operates exist.</p