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Genomic risk scores for juvenile idiopathic arthritis and its subtypes
  1. Rodrigo Cánovas1,
  2. Joanna Cobb2,3,
  3. Marta Brozynska1,
  4. John Bowes4,5,
  5. Yun R Li6,7,
  6. Samantha Louise Smith4,
  7. Hakon Hakonarson6,8,
  8. Wendy Thomson4,5,
  9. Justine A Ellis3,9,10,
  10. Gad Abraham1,11,12,
  11. Jane E Munro2,3,13,
  12. Michael Inouye1,11,12,14,15,16,17,18
  1. 1 Cambridge Baker Systems Genomics Initiative, Baker Heart Research Institute - BHRI, Melbourne, Victoria, Australia
  2. 2 Childhood Arthritis, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
  3. 3 Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
  4. 4 Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom
  5. 5 National Institute of Health Research Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, United Kingdom
  6. 6 Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  7. 7 Helen Diller Family Comprehensive Cancer Center, Department of Radiation Oncology, University of California San Francisco, San Francisco, California, United States
  8. 8 Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  9. 9 Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia
  10. 10 Faculty of Health, Centre for Social and Early Emotional Development, Deakin University, Burwood, Victoria, Australia
  11. 11 Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
  12. 12 Department of Clinical Pathology, University of Melbourne, Melbourne, Victoria, Australia
  13. 13 Paediatric Rheumatology Unit, Royal Children’s Hospital, Melbourne, Victoria, Australia
  14. 14 British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
  15. 15 British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
  16. 16 National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, United Kingdom
  17. 17 Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
  18. 18 The Alan Turing Institute, London, United Kingdom
  1. Correspondence to Dr Michael Inouye, Systems Genomics, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia; minouye{at}baker.edu.au

Abstract

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.

  • arthritis
  • juvenile
  • polymorphism
  • genetic
  • arthritis
  • rheumatoid
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Footnotes

  • RC and JC are joint first authors.

  • JEM and MI are joint senior authors.

  • Handling editor Josef S Smolen

  • Contributors MI, JM, JE, GA and RC conceived and designed the study. RC, JC, JM, MB, JB, YRL, SLS, HH, WT and JE contributed data. RC and GA performed the statistical analysis. RC, MI, GA, JC and JM wrote the manuscript with contributions by all co-authors. All authors approved of the final version.

  • Funding This study was supported in part by the Victorian Government’s OIS Program, the Australian National Health and Medical Research Council (NHMRC Project no. 1122744), the Murdoch Children’s Research Institute and the Royal Children’s Hospital Foundation (grant no. 2017–896). This work was supported by core funding from the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946) and the National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust)*. It was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. GA was supported by an NHMRC Early Career Fellowship (no. 1090462). MI was supported by the Munz Chair of Cardiovascular Prediction and Prevention. This study acknowledges the use of the following UK JIA cohort collections: The Biologics for Children with Rheumatic Diseases (BCRD) study (funded by Arthritis Research UK Grant 20747). The British Society for Paediatric and Adolescent Rheumatology Etanercept Cohort Study (BSPAR-ETN) (funded by a research grant from the British Society for Rheumatology (BSR). BSR has previously also received restricted income from Pfizer to fund this project). Childhood Arthritis Prospective Study (CAPS) (funded by Versus Arthritis, grant reference number 20542), Childhood Arthritis Response to Medication Study (CHARMS) (funded by Sparks UK, reference 08ICH09, and the Medical Research Council, reference MR/M004600/1), United Kingdom Juvenile Idiopathic Arthritis Genetics Consortium (UKJIAGC). Genotyping of the UK JIA case samples were supported by the Versus Arthritis grants reference numbers 20 385 and 21 754. This research was funded by the NIHR Manchester Biomedical Research Centre and supported by the Manchester Academic Health Sciences Centre (MAHSC). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We would like to acknowledge the assistance given by IT Services and the use of the Computational Shared Facility at The University of Manchester. Finally, the CHOP data used were funded by an Institute Development Fund to the CAG centre from The Children’s Hospital of Philadelphia and by NIH grant, U01-HG006830, from the NHGRI-sponsored eMERGE Network.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Ethics approval All participants gave informed consent and the study protocols were approved by the relevant institutional or national ethics committees. The Australian CLARITY cohort collection was approved by the Royal Children’s Hospital Human Research Ethics Committee; UK ethical approval was obtained from the North West Multicentre for Research Ethics Committee (MREC:02/8/104 and MREC:99/8/84), West Midlands Multicentre Research Ethics Committee (MREC:02/7/106), North West Research Ethics Committee (REC:09/H1008/137) and the NHS Research Ethics Committee (REC:05/Q0508/95); and the US CHOP cohort collection was approved by the institutional review boards of the Texas Scottish Rite Hospital for Children, the Children’s Mercy Hospitals and Clinics and the Children's Hospital of Philadelphia.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. Data are available upon reasonable request. For individual-level data, CHOP is available through the eMERGE Network dbGaP and the WTCCC controls are available through the Wellcome Trust Case Control Consortium webpage (https://www.wtccc.org.uk/). For the individual-level genotype data for the UK JIA cases and CLARITY, researchers should contact the cohort principal investigators (Professor Wendy Thomson (Wendy.Thomson@manchester.ac.uk) and Dr Jane Munro (Jane.Munro@rch.org.au), respectively). Finally, the JIA GRSs presented are publicly available via the Polygenic Score Catalog (www.pgscatalog.org)