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Genomic risk scores for juvenile idiopathic arthritis and its subtypes
OBJECTIVES: Juvenile idiopathic arthritis (JIA) is an autoimmune disease and a common cause of chronic disability in children. Diagnosis of JIA is based purely on clinical symptoms, which can be variable, leading to diagnosis and treatment delays. Despite JIA having substantial heritability, the con...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677485/ https://www.ncbi.nlm.nih.gov/pubmed/32887683 http://dx.doi.org/10.1136/annrheumdis-2020-217421 |
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author | Cánovas, Rodrigo Cobb, Joanna Brozynska, Marta Bowes, John Li, Yun R Smith, Samantha Louise Hakonarson, Hakon Thomson, Wendy Ellis, Justine A Abraham, Gad Munro, Jane E Inouye, Michael |
author_facet | Cánovas, Rodrigo Cobb, Joanna Brozynska, Marta Bowes, John Li, Yun R Smith, Samantha Louise Hakonarson, Hakon Thomson, Wendy Ellis, Justine A Abraham, Gad Munro, Jane E Inouye, Michael |
author_sort | Cánovas, Rodrigo |
collection | PubMed |
description | OBJECTIVES: Juvenile idiopathic arthritis (JIA) is an autoimmune disease and a common cause of chronic disability in children. Diagnosis of JIA is based purely on clinical symptoms, which can be variable, leading to diagnosis and treatment delays. Despite JIA having substantial heritability, the construction of genomic risk scores (GRSs) to aid or expedite diagnosis has not been assessed. Here, we generate GRSs for JIA and its subtypes and evaluate their performance. METHODS: We examined three case/control cohorts (UK, US-based and Australia) with genome-wide single nucleotide polymorphism (SNP) genotypes. We trained GRSs for JIA and its subtypes using lasso-penalised linear models in cross-validation on the UK cohort, and externally tested it in the other cohorts. RESULTS: The JIA GRS alone achieved cross-validated area under the receiver operating characteristic curve (AUC)=0.670 in the UK cohort and externally-validated AUCs of 0.657 and 0.671 in the US-based and Australian cohorts, respectively. In logistic regression of case/control status, the corresponding odds ratios (ORs) per standard deviation (SD) of GRS were 1.831 (1.685 to 1.991) and 2.008 (1.731 to 2.345), and were unattenuated by adjustment for sex or the top 10 genetic principal components. Extending our analysis to JIA subtypes revealed that the enthesitis-related JIA had both the longest time-to-referral and the subtype GRS with the strongest predictive capacity overall across data sets: AUCs 0.82 in UK; 0.84 in Australian; and 0.70 in US-based. The particularly common oligoarthritis JIA also had a GRS that outperformed those for JIA overall, with AUCs of 0.72, 0.74 and 0.77, respectively. CONCLUSIONS: A GRS for JIA has potential to augment clinical JIA diagnosis protocols, prioritising higher-risk individuals for follow-up and treatment. Consistent with JIA heterogeneity, subtype-specific GRSs showed particularly high performance for enthesitis-related and oligoarthritis JIA. |
format | Online Article Text |
id | pubmed-7677485 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-76774852020-11-30 Genomic risk scores for juvenile idiopathic arthritis and its subtypes Cánovas, Rodrigo Cobb, Joanna Brozynska, Marta Bowes, John Li, Yun R Smith, Samantha Louise Hakonarson, Hakon Thomson, Wendy Ellis, Justine A Abraham, Gad Munro, Jane E Inouye, Michael Ann Rheum Dis Paediatric Rheumatology OBJECTIVES: Juvenile idiopathic arthritis (JIA) is an autoimmune disease and a common cause of chronic disability in children. Diagnosis of JIA is based purely on clinical symptoms, which can be variable, leading to diagnosis and treatment delays. Despite JIA having substantial heritability, the construction of genomic risk scores (GRSs) to aid or expedite diagnosis has not been assessed. Here, we generate GRSs for JIA and its subtypes and evaluate their performance. METHODS: We examined three case/control cohorts (UK, US-based and Australia) with genome-wide single nucleotide polymorphism (SNP) genotypes. We trained GRSs for JIA and its subtypes using lasso-penalised linear models in cross-validation on the UK cohort, and externally tested it in the other cohorts. RESULTS: The JIA GRS alone achieved cross-validated area under the receiver operating characteristic curve (AUC)=0.670 in the UK cohort and externally-validated AUCs of 0.657 and 0.671 in the US-based and Australian cohorts, respectively. In logistic regression of case/control status, the corresponding odds ratios (ORs) per standard deviation (SD) of GRS were 1.831 (1.685 to 1.991) and 2.008 (1.731 to 2.345), and were unattenuated by adjustment for sex or the top 10 genetic principal components. Extending our analysis to JIA subtypes revealed that the enthesitis-related JIA had both the longest time-to-referral and the subtype GRS with the strongest predictive capacity overall across data sets: AUCs 0.82 in UK; 0.84 in Australian; and 0.70 in US-based. The particularly common oligoarthritis JIA also had a GRS that outperformed those for JIA overall, with AUCs of 0.72, 0.74 and 0.77, respectively. CONCLUSIONS: A GRS for JIA has potential to augment clinical JIA diagnosis protocols, prioritising higher-risk individuals for follow-up and treatment. Consistent with JIA heterogeneity, subtype-specific GRSs showed particularly high performance for enthesitis-related and oligoarthritis JIA. BMJ Publishing Group 2020-12 2020-09-04 /pmc/articles/PMC7677485/ /pubmed/32887683 http://dx.doi.org/10.1136/annrheumdis-2020-217421 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Paediatric Rheumatology Cánovas, Rodrigo Cobb, Joanna Brozynska, Marta Bowes, John Li, Yun R Smith, Samantha Louise Hakonarson, Hakon Thomson, Wendy Ellis, Justine A Abraham, Gad Munro, Jane E Inouye, Michael Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title | Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title_full | Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title_fullStr | Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title_full_unstemmed | Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title_short | Genomic risk scores for juvenile idiopathic arthritis and its subtypes |
title_sort | genomic risk scores for juvenile idiopathic arthritis and its subtypes |
topic | Paediatric Rheumatology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677485/ https://www.ncbi.nlm.nih.gov/pubmed/32887683 http://dx.doi.org/10.1136/annrheumdis-2020-217421 |
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