Genomic risk scores for juvenile idiopathic arthritis and its subtypes

Aims 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, leading to 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, 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 in the Australian and US cohorts. Results The JIA GRS alone achieved cross-validated AUC=0.670 in the UK cohort and externally validated AUCs of 0.657 and 0.671 in US-based and Australian cohorts, respectively. In logistic regression of case/control status, the corresponding odds ratios per standard deviation (s.d.) of GRS were 1.831 [1.685-1.991] and 2.008 [1.731-2.345], and were unattenuated by adjustment for sex or the top 10 genetic principal components. Extending our analysis to JIA subtypes revealed that enthesitis-related JIA had both the longest time-to-referral and the subtype GRS with the strongest predictive capacity overall across datasets: AUCs 0.80 in UK; 0.83 Australian; 0.69 US-based. The particularly common oligoarthritis JIA subtype also had a subtype GRS outperformed those for JIA overall, with AUCs of 0.71, 0.75 and 0.77, respectively. Conclusions A genomic risk score for JIA has potential to augment purely 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.