Treating Systematic Errors in Multiple Sclerosis Data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

The multiple sclerosis risk sharing scheme monitoring study - early results and lessons for the future

Background: Risk sharing schemes represent an innovative and important approach to the problems of rationing and achieving cost-effectiveness in high cost or controversial health interventions. This study aimed to assess the feasibility of risk sharing schemes, looking at long term clinical outcomes, to determine the price at which high cost treatments would be acceptable to the NHS. Methods: This case study of the first NHS risk sharing scheme, a long term prospective cohort study of beta interferon and glatiramer acetate in multiple sclerosis ( MS) patients in 71 specialist MS centres in UK NHS hospitals, recruited adults with relapsing forms of MS, meeting Association of British Neurologists (ABN) criteria for disease modifying therapy. Outcome measures were: success of recruitment and follow up over the first three years, analysis of baseline and initial follow up data and the prospect of estimating the long term cost-effectiveness of these treatments. Results: Centres consented 5560 patients. Of the 4240 patients who had been in the study for a least one year, annual review data were available for 3730 (88.0%). Of the patients who had been in the study for at least two years and three years, subsequent annual review data were available for 2055 (78.5%) and 265 (71.8%) patients respectively. Baseline characteristics and a small but statistically significant progression of disease were similar to those reported in previous pivotal studies. Conclusion: Successful recruitment, follow up and early data analysis suggest that risk sharing schemes should be able to deliver their objectives. However, important issues of analysis, and political and commercial conflicts of interest still need to be addressed

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

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

PMCID: PMC3566971This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

HLA-class I markers and multiple sclerosis susceptibility in the Italian population

Previous studies reported an association with multiple sclerosis (MS) of distinct HLA-class I markers, namely HLA-A*02, HLA-Cw*05 and MOG-142L. In this work, we tested the association with MS of A*02 and Cw*05 in 1273 Italian MS patients and 1075 matched controls, which were previously analyzed for MOG-142, and explored the relationship among these three markers in modulating MS risk. HLA-A*02 conferred a statistically robust MS protection (odds ratio, OR=0.61; 95% confidence intervals, CI=0.51–0.72, P<10−9), which was independent of DRB1*15 and of any other DRB1* allele and remained similar after accounting for the other two analyzed class I markers. Conversely, the protective effect we previously observed for MOG-142L was secondary to its linkage disequilibrium with A*02. Cw*05 was not associated considering the whole sample, but its presence significantly enhanced the protection in the HLA-A*02-positive group, independently of DRB1: the OR conferred by A*02 in Cw*05-positive individuals (0.22, 95% CI=0.13–0.38) was significantly lower than in Cw*05-negative individuals (0.69, 95% CI=0.58–0.83) with a significant (P=4.94 × 10−5) multiplicative interaction between the two markers. In the absence of A*02, Cw*05 behaved as a risk factor, particularly in combination with DRB1*03 (OR=3.89, P=0.0006), indicating that Cw*05 might be a marker of protective or risk haplotypes, respectively

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

Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibelt® Platform

Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibelt®) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92–0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12–0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure

Environmental factors in early childhood are associated with multiple sclerosis: a case-control study

<p>Abstract</p> <p>Background</p> <p>Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS) with increasing incidence mainly in high-income countries. One explanation of this phenomenon may be a higher prevalence of allergic and autoimmune diseases in industrialized countries as a consequence of otherwise beneficial advances in sanitation (hygiene hypothesis). We investigated environmental factors in early childhood associated with MS.</p> <p>Methods</p> <p>A case-control study was performed of 245 MS patients and 296 population-based controls in Berlin. The study participants completed a standardized questionnaire on environmental factors in childhood and youth, including aspects of personal and community hygiene. Multivariable logistic regression analysis was performed to investigate factors in childhood and youth associated with the occurrence of MS.</p> <p>Results</p> <p>Mean age was 46 years (range, 20-80) in the MS group and 42 years (range 18-80) in the control group, of which 73.9% in the MS and 61.5% in the control group were female. The multivariable analysis showed that having at least two older siblings (OR 0.54; p = 0.05, for individuals with two older siblings compared to individuals without older siblings), attending a day-care center (OR 0.5; p = 0.004) and growing up in an urban center with more than 100, 000 inhabitants (OR 0.43; p = 0.009) were factors independently associated with a lower chance for MS.</p> <p>Conclusions</p> <p>The hygiene hypothesis may play a role in the occurrence of MS and could explain disease distribution and increasing incidence.</p

Identification of Protein Networks Involved in the Disease Course of Experimental Autoimmune Encephalomyelitis, an Animal Model of Multiple Sclerosis

A more detailed insight into disease mechanisms of multiple sclerosis (MS) is crucial for the development of new and more effective therapies. MS is a chronic inflammatory autoimmune disease of the central nervous system. The aim of this study is to identify novel disease associated proteins involved in the development of inflammatory brain lesions, to help unravel underlying disease processes. Brainstem proteins were obtained from rats with MBP induced acute experimental autoimmune encephalomyelitis (EAE), a well characterized disease model of MS. Samples were collected at different time points: just before onset of symptoms, at the top of the disease and following recovery. To analyze changes in the brainstem proteome during the disease course, a quantitative proteomics study was performed using two-dimensional difference in-gel electrophoresis (2D-DIGE) followed by mass spectrometry. We identified 75 unique proteins in 92 spots with a significant abundance difference between the experimental groups. To find disease-related networks, these regulated proteins were mapped to existing biological networks by Ingenuity Pathway Analysis (IPA). The analysis revealed that 70% of these proteins have been described to take part in neurological disease. Furthermore, some focus networks were created by IPA. These networks suggest an integrated regulation of the identified proteins with the addition of some putative regulators. Post-synaptic density protein 95 (DLG4), a key player in neuronal signalling and calcium-activated potassium channel alpha 1 (KCNMA1), involved in neurotransmitter release, are 2 putative regulators connecting 64% of the identified proteins. Functional blocking of the KCNMA1 in macrophages was able to alter myelin phagocytosis, a disease mechanism highly involved in EAE and MS pathology. Quantitative analysis of differentially expressed brainstem proteins in an animal model of MS is a first step to identify disease-associated proteins and networks that warrant further research to study their actual contribution to disease pathology