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A Risk Score for Predicting Multiple Sclerosis.

Authors :
Dobson R
Ramagopalan S
Topping J
Smith P
Solanky B
Schmierer K
Chard D
Giovannoni G
Source :
PloS one [PLoS One] 2016 Nov 01; Vol. 11 (11), pp. e0164992. Date of Electronic Publication: 2016 Nov 01 (Print Publication: 2016).
Publication Year :
2016

Abstract

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.<br />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.<br />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).<br />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.<br />Competing Interests: RD, SR, JT, and BS have no conflicts of interest to declare. KS is PI of trials sponsored by Novartis & Roche. He is involved in trials sponsored by Biogen, Genzyme, Teva, Merck Inc. and BIAL. Speaking honoraria from, and/or in an advisory role for, Novartis, Sanofi-Aventis, Merck-Serono and Merck Inc. DC has received research support from the MS Society of Great Britain and Northern Ireland, and the National Institute for Health Research University College London Hospitals Biomedical Research Centre. He has received honoraria (paid to his employer) from Ismar Healthcare NV, Swiss MS Society, Excemed (previously Serono Symposia International Foundation), Merck, Bayer and Teva for faculty-led education work; Teva for advisory board work; meeting expenses from Merck, Teva, Novartis, the MS Trust and National MS Society; and has previously held stock in GlaxoSmithKline. He is a member of the MS Society of Great Britain and Northern Ireland's Biomedical Grant Review Panel. He is a member of the Data Safety Monitoring Committee for the PROXIMUS study, which is funded by National Multiple Sclerosis Society and Novartis. Both of these roles are unpaid. GG has received research grant support from Bayer-Schering Healthcare, Biogen-Idec, GW Pharma, Merck Serono, Merz, Novartis, Teva and Sanofi-Aventis. He has received personal compensation for participating on Advisory Boards in relation to clinical trial design, trial steering committees and data and safety monitoring committees from: Bayer-Schering Healthcare, Biogen-Idec, Eisai, Elan, Fiveprime, Genzyme, Genentech, GSK, GW Pharma, Ironwood, Merck-Serono, Novartis, Pfizer, Roche, Sanofi-Aventis, Synthon BV, Teva, UCB Pharma and Vertex Pharmaceuticals. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Details

Language :
English
ISSN :
1932-6203
Volume :
11
Issue :
11
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
27802296
Full Text :
https://doi.org/10.1371/journal.pone.0164992