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A Risk Score for Predicting Multiple Sclerosis

OBJECTIVE: Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic...

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Autores principales: Dobson, Ruth, Ramagopalan, Sreeram, Topping, Joanne, Smith, Paul, Solanky, Bhavana, Schmierer, Klaus, Chard, Declan, Giovannoni, Gavin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5089761/
https://www.ncbi.nlm.nih.gov/pubmed/27802296
http://dx.doi.org/10.1371/journal.pone.0164992
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author Dobson, Ruth
Ramagopalan, Sreeram
Topping, Joanne
Smith, Paul
Solanky, Bhavana
Schmierer, Klaus
Chard, Declan
Giovannoni, Gavin
author_facet Dobson, Ruth
Ramagopalan, Sreeram
Topping, Joanne
Smith, Paul
Solanky, Bhavana
Schmierer, Klaus
Chard, Declan
Giovannoni, Gavin
author_sort Dobson, Ruth
collection PubMed
description OBJECTIVE: Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI. METHODS: 78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals. RESULTS: There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88). INTERPRETATIONS: The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies.
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spelling pubmed-50897612016-11-15 A Risk Score for Predicting Multiple Sclerosis Dobson, Ruth Ramagopalan, Sreeram Topping, Joanne Smith, Paul Solanky, Bhavana Schmierer, Klaus Chard, Declan Giovannoni, Gavin PLoS One Research Article OBJECTIVE: Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI. METHODS: 78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals. RESULTS: There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88). INTERPRETATIONS: The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies. Public Library of Science 2016-11-01 /pmc/articles/PMC5089761/ /pubmed/27802296 http://dx.doi.org/10.1371/journal.pone.0164992 Text en © 2016 Dobson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dobson, Ruth
Ramagopalan, Sreeram
Topping, Joanne
Smith, Paul
Solanky, Bhavana
Schmierer, Klaus
Chard, Declan
Giovannoni, Gavin
A Risk Score for Predicting Multiple Sclerosis
title A Risk Score for Predicting Multiple Sclerosis
title_full A Risk Score for Predicting Multiple Sclerosis
title_fullStr A Risk Score for Predicting Multiple Sclerosis
title_full_unstemmed A Risk Score for Predicting Multiple Sclerosis
title_short A Risk Score for Predicting Multiple Sclerosis
title_sort risk score for predicting multiple sclerosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5089761/
https://www.ncbi.nlm.nih.gov/pubmed/27802296
http://dx.doi.org/10.1371/journal.pone.0164992
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