Computational protocol: Genetic architecture distinguishes systemic juvenile idiopathic arthritis from other forms of juvenile idiopathic arthritis: clinical and therapeutic implications

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Protocol publication

[…] Genomic DNA was extracted from peripheral blood samples. Samples were genotyped at the National Human Genome Research Institute (Bethesda, Maryland, USA) using Human Omni1M arrays (Illumina) in accordance with the manufacturer's protocols. SNP genotype data were stratified by country of origin and rigorous quality control (QC) operations were undertaken separately in each case and control population, as previously reported. Principal components analysis and multidimensional scaling were used in each geographically defined case–control collection to generate nine ancestrally matched case–control strata, as previously described. Genomic control inflation factors were calculated, per stratum, as an objective metric of ancestral matching. An overview of the QC parameters is shown in online , and complete details are provided in the online and our previous publication.SNP genotypes were phased using IMPUTE2, and SNP imputation was performed separately for each geographically defined stratum using IMPUTE2 software and the multiancestral 1000 Genomes Project dataset (phase III) as the reference population. Genotype probabilities for common markers (case minor allele frequency ≥0.04) that were imputed with high quality (info scores ≥0.8) were included in subsequent analyses. [...] Association testing of genotype probabilities was performed using logistic regression in each geographically defined stratum with SNPTESTv2, adjusting for gender and ancestry informative principal components. Association results were meta-analysed using GWAMA. Heterogeneity was evaluated in the meta-analyses using the I2 statistic. Weighted genetic risk scores (wGRSs) were calculated and receiver operator characteristic (ROC) curve analyses were performed according to the method of Karlson et al. wGRSs were calculated as the sum of the risk allele counts, weighted by the natural logarithm of the OR. The wGRS for polygoJIA (polygo-wGRS) incorporated 23 independent risk alleles reported by Hinks et al (see online ). The wGRS for RF+polyJIA (RF+poly-wGRS) was based on the RF+polyJIA-associated wGRS-11 (see online ). The case and control distributions of risk alleles and wGRSs were evaluated with the Wilcoxon rank-sum test. Association of wGRSs with sJIA was tested by logistic regression, adjusted for ancestry and gender. The ability of wGRSs to discriminate between sJIA and other JIA subtypes was evaluated with ROC curve analysis and calculation of the area under the curve (AUC) using R. Quantile–quantile (Q–Q) plots were generated using the sJIA association data, conditional on sets of polygoJIA-associated SNPs, as previously described. […]

Pipeline specifications

Software tools IMPUTE, GWAMA
Application GWAS
Diseases Arthritis, Arthritis, Juvenile, Hereditary Autoinflammatory Diseases
Chemicals Nucleotides