Objective LN is one of the most common and severe manifestations of SLE. Our aim was to test the association of SLE risk loci with LN risk in childhood-onset SLE (cSLE) and adult-onset SLE (aSLE). Methods Two Toronto-based tertiary care SLE cohorts included cSLE (diagnosed <18 years) and aSLE patients (diagnosed ⩾18 years). Patients met ACR and/or SLICC SLE criteria and were genotyped on the Illumina Multi-Ethnic Global Array or Omni1-Quad arrays. We identified those with and without biopsy-confirmed LN. HLA and non-HLA additive SLE risk-weighted genetic risk scores (GRSs) were tested for association with LN risk in logistic models, stratified by cSLE/aSLE and ancestry. Stratified effect estimates were meta-analysed. Results Of 1237 participants, 572 had cSLE (41% with LN) and 665 had aSLE (30% with LN). Increasing non-HLA GRS was significantly associated with increased LN risk [odds ratio (OR) = 1.26; 95% CI 1.09, 1.46; P = 0.0006], as was increasing HLA GRS in Europeans (OR = 1.55; 95% CI 1.07, 2.25; P = 0.03). There was a trend for stronger associations between both GRSs and LN risk in Europeans with cSLE compared with aSLE. When restricting cases to proliferative LN, the magnitude of these associations increased for both the non-HLA (OR = 1.30; 95% CI 1.10, 1.52; P = 0.002) and HLA GRS (OR = 1.99; 95% CI 1.29, 3.08; P = 0.002). Conclusion We observed an association between known SLE risk loci and LN risk in children and adults with SLE, with the strongest effect observed among Europeans with cSLE. Future studies will include SLE-risk single nucleotide polymorphisms specific to non-European ancestral groups and validate findings in an independent cohort.

Background There are no validated screening measures for depressive or anxiety disorders in childhood Systemic Lupus Erythematosus (cSLE). We investigated cross-sectionally (1) the prevalence of depressive and anxiety disorder in cSLE. (2) the validity of the Centre for Epidemiologic Studies Depression Scale for Children (CES-DC) and the Screen for Childhood Anxiety and Related Disorders (SCARED) measures in identifyingthese disorders. Methods Participants 8-18 years with cSLE/incipient cSLE completed CES-DC, SCARED, and Quality OfMy Life (QOML) measures. Parents completed the SCARED-Parent measure. Diagnosis was by gold-standard psychiatric interview and determined prevalence of psychiatric disorder. Receiver Operating Characteristics Area under the Curve (ROCAUC) evaluated screening measure diagnostic performance. Results Ofseventy-two parent-child dyads, 56 interviews were completed. Mean screen scores were: CES-DC = 15 (range 1-49, SD 12), SCARED-C = 22 (range 2-61, SD 14), SCARED-P = 13 (range 0-36, SD 8). Depressive disorder screen positivity (CES-DC ≥ 15) was 35% (vs. prevalence 5%). Anxiety disorder screen positivity (SCARED ≥ 25) was 39% (vs. prevalence 16%). CES-DC ROCAUC = 0.98 and SCARED-C ROCAUC = 0.7 (cut-points 38 and 32 respectively). Conclusions Diagnostic thresholds for depressive and anxiety disorderscreening measures are high for both CES-DC and SCARED-C in cSLE. Brief focused interview should follow to determine whether psychiatric evaluation is warranted.

Objective Specific risk alleles for childhood-onset SLE (cSLE) versus adult-onset SLE (aSLE) patients have not been identified. The aims of this study were to determine if: 1) There is an association between non-HLA-related genetic risk score (GRS) and age of SLE diagnosis; and if 2) There is an association between HLA-related genetic risk score and age of SLE diagnosis. Methods Genomic DNA was obtained from 2,001 multi-ethnic patients and genotyped using the Immunochip. Following quality control, genetic risk counting (GRCS), weighted (GRWS) and standardized counting (GRSCS) and standardized weighted (GRSWS) scores were calculated based on independent SNPs from validated SLE-loci. Scores were analyzed in a regression model and adjusted by sex and ancestral population. Results The analysed cohort consisted of 1,540 patients: 1,351 females and 189 males (675 cSLE and 865 aSLE). There were significant negative associations with age of SLE diagnosis p=0.011 and r2=0.175 for GRWS, p=0.008 and r2=0.178 for GRSCS, p=0.002 and r2=0.176 for GRSWS for all non-HLA genetic risk scores (higher GRS the lower the age of diagnosis.) All HLA genetic risk scores showed significant positive associations with age of diagnosis p=0.049 and r2=0.176 for GRCS, p=0.022 and r2=0.176 for GRWS, p=0.022 and r2=0.176 for GRSCS, p=0.011 and r2=0.177 for GRSWS: higher genetic scores correlated with higher age of diagnosis. Conclusion Our data suggested that there is a linear relationship between genetic risk and age of SLE diagnosis and that HLA and non-HLA genetic risk scores are associated with age of diagnosis in opposite directions.