Integration of genetic and clinical risk factors improves the risk classification of uveitis in patients with juvenile idiopathic arthritis

OBJECTIVES: Juvenile idiopathic arthritis (JIA)-associated uveitis (JIAU) is a serious JIA comorbidity that can result in vision impairment. This study aimed to identify genetic risk factors, within the major histocompatibility complex , for JIAU and evaluate their contribution for improving risk classification when combined with clinical risk factors.

METHODS: Data on single nucleotide polymorphisms, amino acids and classical human leukocyte antigen (HLA) alleles were available for 2,497 JIA patients without uveitis and 579 JIAU patients (female=2060, male=1015). Analysis was restricted to patients with inferred European ancestry. Forward conditional logistic regression identified genetic markers exceeding a Bonferroni corrected significance (6x10 -6). Multivariable logistic regression estimated the effects of clinical and genetic risk factors and a likelihood ratio test calculated the improvement in model fit when adding genetic factors. Uveitis risk classification performance of a model integrating genetic and clinical risk factors was estimated using area under the receiver operator characteristic curve and compared to a model of clinical risk factors alone.

RESULTS: Three genetic risk factors were identified mapping to HLA-DRB1, HLA-DPB1 and HLA-A. These markers were statistically independent from clinical risk factors and significantly improved the fit of a model when included with clinical risk factors (P = 3.3x10 -23). The addition of genetic markers improved the classification of JIAU compared to a model of clinical risk factors alone (AUC 0.75 vs. 0.71).

CONCLUSIONS: Integration of a genetic and clinical risk prediction model outperforms a model based solely on clinical risk factors. Future JIAU risk prediction models should include genetic risk factors.