The genetic aspects of multiple sclerosis.
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ABSTRACT:
SUBMITTER: Sawcer S
PROVIDER: S-EPMC2824946 | biostudies-literature | 2009 Oct
REPOSITORIES: biostudies-literature
Publications
The genetic aspects of multiple sclerosis.
Annals of Indian Academy of Neurology 20091001 4
THE EPIDEMIOLOGY OF MULTIPLE SCLEROSIS HAS BEEN EXTENSIVELY INVESTIGATED AND TWO FEATURES HAVE CONSISTENTLY EMERGED: marked geographical variation in prevalence and substantial familial clustering. At first sight, geographic variation would seem to imply an environmental cause for the disease, while familial clustering would seem to suggest that genetic factors have the predominant etiological effect. However, given that geographic variation in prevalence could result from variation in the frequ ...[more]
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Project description:Importance:Before using brain volume loss (BVL) as a marker of therapeutic response in multiple sclerosis (MS), certain biological and methodological issues must be clarified. Objectives:To assess the dynamics of BVL as MS progresses and to evaluate the repeatability and exchangeability of BVL estimates with Jacobian Integration (JI) and Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) (specifically, the Structural Image Evaluation, Using Normalisation, of Atrophy-Cross-Sectional [SIENA-X] tool or FMRIB's Integrated Registration and Segmentation Tool [FIRST]). Design, Setting, and Participants:A cohort of patients who had either clinically isolated syndrome or MS was enrolled from February 2011 through October 2015. All underwent a series of annual magnetic resonance imaging (MRI) scans. Images from 2 cohorts of healthy volunteers were used to evaluate short-term repeatability of the MRI measurements (n?=?34) and annual BVL (n?=?20). Data analysis occurred from January to May 2017. Main Outcomes and Measures:The goodness of fit of different models to the dynamics of BVL throughout the MS disease course was assessed. The short-term test-retest error was used as a measure of JI and FSL repeatability. The correlations (R2) of the changes quantified in the brain using JI and FSL, together with the accuracy of the annual BVL cutoffs to discriminate patients with MS from healthy volunteers, were used to measure compatibility of imaging methods. Results:A total of 140 patients with clinically isolated syndrome or MS were enrolled, including 95 women (67.9%); the group had a median (interquartile range) age of 40.7 (33.6-48.1) years. Patients underwent 4 MRI scans with a median (interquartile range) interscan period of 364 (351-379) days. The 34 healthy volunteers (of whom 18 [53%] were women; median [IQR] age, 33.5 [26.2-42.5] years) and 20 healthy volunteers (of whom 10 [50%] were women; median [IQR] age, 33.0 [28.7-39.2] years) underwent 2 MRI scans within a median (IQR) of 24.5 (0.0-74.5) days and 384.5 (366.3-407.8) days for the short-term and long-term MRI follow-up, respectively. The BVL rates were higher in the first 5 years after MS onset (R2?=?0.65 for whole-brain volume change and R2?=?0.52 for gray matter volume change) with a direct association with steroids (??=?0.280; P?=?.02) and an inverse association with age at MS onset, particularly in the first 5 years (??=?0.015; P?=?.047). The reproducibility of FSL (SIENA) and JI was similar for whole-brain volume loss, while JI gave more precise, less biased estimates for specific brain regions than FSL (SIENA-X and FIRST). The correlation between whole-brain volume loss using JI and FSL was high (R2?=?0.92), but the same correlations were poor for specific brain regions. The area under curve of the whole-brain volume change to discriminate between patients with MS and healthy volunteers was similar, although the thresholds and accuracy index were distinct for JI and FSL. Conclusions and Relevance:The proposed BVL threshold of less than 0.4% per year as a marker of therapeutic efficiency should be reconsidered because of the different dynamics of BVL as MS progresses and because of the limited reproducibility and variability of estimates using different imaging methods.
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| S-EPMC5722760 | biostudies-literature
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| S-EPMC2696028 | biostudies-literature
Project description:A previous study using cumulative genetic risk estimations in multiple sclerosis (MS) successfully tracked the aggregation of susceptibility variants in multi-case and single-case families. It used a limited description of susceptibility loci available at the time (17 loci). Even though the full roster of MS risk genes remains unavailable, we estimated the genetic burden in MS families and assess its disease predictive power using up to 64 single-nucleotide polymorphism (SNP) markers according to the most recent literature. A total of 708 controls, 3251 MS patients and their relatives, as well as 117 twin pairs were genotyped. We validated the increased aggregation of genetic burden in multi-case compared with single-case families (P=4.14e-03) and confirm that these data offer little opportunity to accurately predict MS, even within sibships (area under receiver operating characteristic (AUROC)=0.59 (0.55, 0.53)). Our results also suggest that the primary progressive and relapsing-type forms of MS share a common genetic architecture (P=0.368; difference being limited to that corresponding to ± 2 typical MS-associated SNPs). We have confirmed the properties of individual genetic risk score in MS. Comparing with previous reference point for MS genetics (17 SNPs), we underlined the corrective consequences of the integration of the new findings from GWAS and meta-analysis.
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Project description:Elevated genetic risk for multiple sclerosis originated in Steppe Pastoralist populations
| PRJEB65098 | ENA
Project description:BackgroundNurse practitioners (NPs) play a critical role in the multidisciplinary management of patients with multiple sclerosis (MS). Neurologists´ behavioral characteristics have been associated with suboptimal clinical decisions. However, limited information is available on their impact among NPs involved in MS care. The aim of this study was to assess nurses´ therapeutic choices to understand behavioral factors influencing their decision making process.MethodsA non-interventional, cross-sectional, web-based study was conducted. NPs actively involved in the care of patients with MS were invited to participate in the study by the Spanish Society of Neurology Nursing. Participants answered questions regarding their standard practice and therapeutic management of seven simulated relapsing-remitting MS (RRMS) case scenarios. A behavioral battery was used to measure participants´ life satisfaction, mood, positive social behaviors, feeling of helpfulness, attitudes toward adoption of evidence-based innovations, occupational burnout, and healthcare-related regret. The outcome of interest was therapeutic inertia (TI), defined as the lack of treatment escalation when there is clinical and radiological evidence of disease activity. A score to quantify TI was created based on the number of simulated scenarios where treatment intensification was warranted.ResultsOverall, 331 NPs were invited to participate, 130 initiated the study, and 96 (29%) completed the study. The mean age (SD) was 44.6 (9.8) years and 91.7% were female. Seventy-three participants (76.0%) felt their opinions had a significant influence on neurologists´ therapeutic decisions. Sixteen NPs (16.5%) showed severe emotional exhaustion related to work and 13 (13.5%) had depressive symptoms. The mean (SD) TI score was 0.97 (1.1). Fifty-six of NPs showed TI in at least one case scenario. Higher years of nursing experience (p = 0.014), feeling of helpfulness (p = 0.014), positive attitudes toward innovations (p = 0.046), and a higher intensity of care-related regret (p = 0.021) were associated with a lower risk of TI (adjusted R2 = 0.28). Burnout was associated with higher risk of TI (p = 0.001).ConclusionsAlthough NPs cannot prescribe MS treatments in Spain, their behavioral characteristics may influence the management of patients with RRMS. Continuing education and specific strategies for reducing occupational burnout may lead to better management skills and improve MS care.
| S-EPMC8654214 | biostudies-literature
Project description:Brigham & Women's Hospital Multiple Sclerosis Genetic Collection
| PRJNA171427 | ENA
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| S-EPMC8352072 | biostudies-literature
Project description:(1) Background: Complex genetic relationships, including gene-gene (G × G; epistasis), gene(n), and gene-environment (G × E) interactions, explain a substantial portion of the heritability in multiple sclerosis (MS). Machine learning and data mining methods are promising approaches for uncovering higher order genetic relationships, but their use in MS have been limited. (2) Methods: Association rule mining (ARM), a combinatorial rule-based machine learning algorithm, was applied to genetic data for non-Latinx MS cases (n = 207) and controls (n = 179). The objective was to identify patterns (rules) amongst the known MS risk variants, including HLA-DRB1*15:01 presence, HLA-A*02:01 absence, and 194 of the 200 common autosomal variants. Probabilistic measures (confidence and support) were used to mine rules. (3) Results: 114 rules met minimum requirements of 80% confidence and 5% support. The top ranking rule by confidence consisted of HLA-DRB1*15:01, SLC30A7-rs56678847 and AC093277.1-rs6880809; carriers of these variants had a significantly greater risk for MS (odds ratio = 20.2, 95% CI: 8.5, 37.5; p = 4 × 10-9). Several variants were shared across rules, the most common was INTS8-rs78727559, which was in 32.5% of rules. (4) Conclusions: In summary, we demonstrate evidence that specific combinations of MS risk variants disproportionately confer elevated risk by applying a robust analytical framework to a modestly sized study population.
| S-EPMC7967327 | biostudies-literature