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Item does not contain fulltext, OBJECTIVES: Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. METHODS: Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. RESULTS: All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. CONCLUSIONS: The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices.

Item does not contain fulltext, OBJECTIVES: Juvenile idiopathic arthritis (JIA) is considered a complex genetic autoimmune disease. We investigated the association of genetic variants previously implicated in JIA, autoimmunity and/or immunoregulation, with susceptibility to JIA. METHODS: A genetic association study was performed in 639 JIA patients and 1613 healthy controls of northwest European descent. Ninety-three single nucleotide polymorphisms (SNP) were genotyped in a candidate gene approach. Results of the entire JIA patient group (all subtypes) were compared with results obtained, alternatively, with a clinically homogeneous patient group including only oligoarticular and rheumatoid factor (RF) negative polyarticular JIA patients (n=493). Meta-analyses were performed for all SNPs that have been typed in other Caucasian JIA cohorts before. RESULTS: SNPs in or near PTPN22, VTCN1, the IL2-IL21 region, ANKRD55 and TNFA were confirmed to be associated with JIA (p<0.05), strengthening the evidence for involvement of these genes in JIA. In the majority of these replicated SNPs, effect sizes were larger when analysing a homogeneous patient cohort than when analysing all subtypes. We identified two novel associations with oligoarticular and RF-negative polyarticular JIA: CD226 rs763361 (OR 1.30, 95% CI 1.12 to 1.51, p=0.0006) and CD28 rs1980422 (OR 1.29, 95% CI 1.07 to 1.55, p=0.008). Meta-analyses including reported studies confirmed the association of both SNPs with susceptibility to JIA (OR 1.16, p=0.001 and OR 1.18, p=0.001, for rs763361 and rs1980422, respectively). CONCLUSIONS: The CD226 gene has been identified as novel association with JIA, and a SNP near CD28 as a suggestive association. Both genes are probable candidate risk factors, since they are involved in costimulation of T cells.