Cherlin, S, Plant, D, Taylor, JC orcid.org/0000-0002-2518-5799 et al. (11 more authors) (2018) Prediction of treatment response in Rheumatoid Arthritis patients using genome-wide SNP data. Genetic Epidemiology, 42 (8). pp. 754-771. ISSN 0741-0395
Abstract
Although a number of treatments are available for rheumatoid arthritis (RA), each of them shows a significant nonresponse rate in patients. Therefore, predicting a priori the likelihood of treatment response would be of great patient benefit. Here, we conducted a comparison of a variety of statistical methods for predicting three measures of treatment response, between baseline and 3 or 6 months, using genome‐wide SNP data from RA patients available from the MAximising Therapeutic Utility in Rheumatoid Arthritis (MATURA) consortium. Two different treatments and 11 different statistical methods were evaluated. We used 10‐fold cross validation to assess predictive performance, with nested 10‐fold cross validation used to tune the model hyperparameters when required. Overall, we found that SNPs added very little prediction information to that obtained using clinical characteristics only, such as baseline trait value. This observation can be explained by the lack of strong genetic effects and the relatively small sample sizes available; in analysis of simulated and real data, with larger effects and/or larger sample sizes, prediction performance was much improved. Overall, methods that were consistent with the genetic architecture of the trait were able to achieve better predictive ability than methods that were not. For treatment response in RA, methods that assumed a complex underlying genetic architecture achieved slightly better prediction performance than methods that assumed a simplified genetic architecture.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 The Authors. Genetic Epidemiology Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited |
Keywords: | Cross validation; prediction; snp data; treatment response |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Discovery & Translational Science Dept (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Epidemiology and Biostatistics (Leeds) |
Funding Information: | Funder Grant number NIHR National Inst Health Research LMBRU NIHR National Inst Health Research NONE GIVEN MRC R116825 NIHR National Inst Health Research BRC NIHR National Inst Health Research LMBRC |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Oct 2018 13:14 |
Last Modified: | 25 Jun 2023 21:33 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/gepi.22159 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:137386 |
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