{'fraction_non_alphanumeric': 0.038880248833592534, 'fraction_numerical': 0.02021772939346812, 'mean_word_length': 5.321867321867322, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
GG-11 Systemic lupus erythematosus (SLE) susceptibility loci in association with age of SLE diagnosis and subphenotypes of SLE in an ancestrally complex childhood-onset SLE longitudinal cohort

Background Recent large scale meta-genome-wide association studies (GWAS) of systemic lupus erythematosus (SLE) in Europeans have confirmed and identified new loci (Bentham et al. Nat Gen 2015). Up to 20% of those affected with SLE are diagnosed in childhood (cSLE). There is evidence for a higher burden of SLE susceptibility loci in those diagnosed in childhood compared to those diagnosed as adults. However, few studies have investigated how known susceptibility loci influence the timing of disease onset and sub-phenotype manifestations in cSLE across different ancestral groups. Materials and methods We will examine SLE-susceptibility single nucleotide polymorphisms (SNPs) individually and in a weighted genetic risk score (GRS), for association with age of SLE diagnosis and sub-phenotype (eg: lupus nephritis (LN), dsDNA, CNS disease). We used a population of children diagnosed and followed for cSLE at the Hospital for Sick Children, Toronto (≥4/11 ACR classification criteria and/or ≥4/11 SLICC classification criteria) between 1982–2014. Participants were genotyped on the Illumina Immunochip. We examined ancestry by comparing with the 1000 genomes data using population stratification and ADMIXTURE. We will use additive genetic models to test the association of each SLE SNP with age of SLE diagnosis (linear regression), and the presence of subphenotypes (logistic regression) in the total cohort, and stratified by ancestral group. Results In our cohort of 342 cSLE patients, the median age of SLE diagnosis was 13 (interquartile range: 10–15) years and the median duration of follow-up was 4.1 (IQR 2.7, 6.1) years. 44% of participants were of a single Ancestry (>95% of the genome from a single ancestral group: 16% European, 23% East Asian, 4% African), and 56% were admixed (genome comprised of more than one ancestral group). Conclusions Our findings will provide insight into the generalizability of a SLE susceptibility GRS across ancestral groups, as it relates to age of diagnosis and subphenotypes of SLE in a cSLE population. Replication and meta-analyses in independent cohorts are planned. Acknowledgements Andrew D. Paterson, Genetics and Genome Biology, Research Institute, the Hospital for Sick Children, Toronto, Canada John Harley, Centre for Autoimmune Genomics and Aetiology, Cincinnati Children’s Hospital Medical Centre, Cincinnati, USA