TY - JOUR
T1 - Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci
AU - McIntosh, Laura A.
AU - Marion, Miranda C.
AU - Sudman, Marc
AU - Comeau, Mary E.
AU - Becker, Mara L.
AU - Bohnsack, John F.
AU - Fingerlin, Tasha E.
AU - Griffin, Thomas A.
AU - Haas, J. Peter
AU - Lovell, Daniel J.
AU - Maier, Lisa A.
AU - Nigrovic, Peter A.
AU - Prahalad, Sampath
AU - Punaro, Marilynn
AU - Rosé, Carlos D.
AU - Wallace, Carol A.
AU - Wise, Carol A.
AU - Moncrieffe, Halima
AU - Howard, Timothy D.
AU - Langefeld, Carl D.
AU - Thompson, Susan D.
N1 - Funding Information:
We would like to thank the Wake Forest School of Medicine Center for Public Health Genomics for providing computational resources and data analytics support.
Funding Information:
Supported in part by the Cincinnati Children's Research Foundation and its Cincinnati Genomic Control Cohort. Recruitment and DNA preparation in the US were supported by the NIH (National Institute of Arthritis and Musculoskeletal and Skin Diseases [NIAMS] grants N01-AR-42272, P01-AR-048929, P30-AR-473639, P30-AR-070549, and P30-AR-070253, National Heart, Lung, and Blood Institute grant R01-HL-11487, National Institute of Environmental Health Sciences grant P0-ES-0118101, and National Institute for Research Resources grant UL1-RR-025780), the Fundación Bechara, the PhRMA Foundation, and the Rheumatology Research Foundation. Genotyping of JIA and control collections in the US was supported by the NIH (NIAMS grant RC1-AR-058587). Recruitment and DNA preparation in Germany were supported by the BMBF (grants 01GM0907 and 01 ZZ 0403).
Publisher Copyright:
© 2017, American College of Rheumatology
PY - 2017/11
Y1 - 2017/11
N2 - Objective: Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, used heterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)−negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes. Methods: Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used for association analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis. Results: Meta-analysis showed evidence of association (P < 1 × 10−6) at 9 regions: PRR9_LOR (P = 5.12 × 10−8), ILDR1_CD86 (P = 6.73 × 10−8), WDFY4 (P = 1.79 × 10−7), PTH1R (P = 1.87 × 10−7), RNF215 (P = 3.09 × 10−7), AHI1_LINC00271 (P = 3.48 × 10−7), JAK1 (P = 4.18 × 10−7), LINC00951 (P = 5.80 × 10−7), and HBP1 (P = 7.29 × 10−7). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22. Conclusion: This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.
AB - Objective: Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, used heterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)−negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes. Methods: Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used for association analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis. Results: Meta-analysis showed evidence of association (P < 1 × 10−6) at 9 regions: PRR9_LOR (P = 5.12 × 10−8), ILDR1_CD86 (P = 6.73 × 10−8), WDFY4 (P = 1.79 × 10−7), PTH1R (P = 1.87 × 10−7), RNF215 (P = 3.09 × 10−7), AHI1_LINC00271 (P = 3.48 × 10−7), JAK1 (P = 4.18 × 10−7), LINC00951 (P = 5.80 × 10−7), and HBP1 (P = 7.29 × 10−7). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22. Conclusion: This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.
UR - http://www.scopus.com/inward/record.url?scp=85031323751&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031323751&partnerID=8YFLogxK
U2 - 10.1002/art.40216
DO - 10.1002/art.40216
M3 - Article
C2 - 28719732
AN - SCOPUS:85031323751
SN - 2326-5191
VL - 69
SP - 2222
EP - 2232
JO - Arthritis and Rheumatology
JF - Arthritis and Rheumatology
IS - 11
ER -