Show simple item record

dc.contributor.authorYarwood, Annieen_US
dc.contributor.authorHan, Buhmen_US
dc.contributor.authorRaychaudhuri, Soumyaen_US
dc.contributor.authorBowes, Johnen_US
dc.contributor.authorLunt, Marken_US
dc.contributor.authorPappas, Dimitrios Aen_US
dc.contributor.authorKremer, Joelen_US
dc.contributor.authorGreenberg, Jeffrey Den_US
dc.contributor.authorPlenge, Roberten_US
dc.contributor.authorWorthington, Janeen_US
dc.contributor.authorBarton, Anneen_US
dc.contributor.authorEyre, Steveen_US
dc.date.accessioned2015-02-02T15:32:41Z
dc.date.issued2015en_US
dc.identifier.citationYarwood, A., B. Han, S. Raychaudhuri, J. Bowes, M. Lunt, D. A. Pappas, J. Kremer, et al. 2015. “A weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risk.” Annals of the Rheumatic Diseases 74 (1): 170-176. doi:10.1136/annrheumdis-2013-204133. http://dx.doi.org/10.1136/annrheumdis-2013-204133.en
dc.identifier.issn0003-4967en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:13890673
dc.description.abstractBackground: There is currently great interest in the incorporation of genetic susceptibility loci into screening models to identify individuals at high risk of disease. Here, we present the first risk prediction model including all 46 known genetic loci associated with rheumatoid arthritis (RA). Methods: A weighted genetic risk score (wGRS) was created using 45 RA non-human leucocyte antigen (HLA) susceptibility loci, imputed amino acids at HLA-DRB1 (11, 71 and 74), HLA-DPB1 (position 9) HLA-B (position 9) and gender. The wGRS was tested in 11 366 RA cases and 15 489 healthy controls. The risk of developing RA was estimated using logistic regression by dividing the wGRS into quintiles. The ability of the wGRS to discriminate between cases and controls was assessed by receiver operator characteristic analysis and discrimination improvement tests. Results: Individuals in the highest risk group showed significantly increased odds of developing anti-cyclic citrullinated peptide-positive RA compared to the lowest risk group (OR 27.13, 95% CI 23.70 to 31.05). The wGRS was validated in an independent cohort that showed similar results (area under the curve 0.78, OR 18.00, 95% CI 13.67 to 23.71). Comparison of the full wGRS with a wGRS in which HLA amino acids were replaced by a HLA tag single-nucleotide polymorphism showed a significant loss of sensitivity and specificity. Conclusions: Our study suggests that in RA, even when using all known genetic susceptibility variants, prediction performance remains modest; while this is insufficiently accurate for general population screening, it may prove of more use in targeted studies. Our study has also highlighted the importance of including HLA variation in risk prediction models.en
dc.language.isoen_USen
dc.publisherBMJ Publishing Groupen
dc.relation.isversionofdoi:10.1136/annrheumdis-2013-204133en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283663/pdf/en
dash.licenseLAAen_US
dc.subjectRheumatoid Arthritisen
dc.subjectGene Polymorphismen
dc.subjectAutoimmune Diseasesen
dc.titleA weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risken
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalAnnals of the Rheumatic Diseasesen
dc.date.available2015-02-02T15:32:41Z
dc.identifier.doi10.1136/annrheumdis-2013-204133*
dash.authorsorderedfalse


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record