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Arthritis Rheumatol. 2017 Nov;69(11):2222-2232. doi: 10.1002/art.40216. Epub 2017 Oct 12.

Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci.

Author information

1
Cincinnati Children's Hospital Medical Center and University of Cincinnati, Cincinnati, Ohio.
2
Wake Forest University School of Medicine, Winston-Salem, North Carolina.
3
Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
4
Children's Mercy-Kansas City, Kansas City, Missouri.
5
University of Utah, Salt Lake City.
6
National Jewish Health and University of Colorado, Denver.
7
Levine Children's Specialty Center, Charlotte, North Carolina.
8
German Center for Pediatric and Adolescent Rheumatology, Garmisch-Partenkirchen, Germany.
9
Boston Children's Hospital and Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
10
Emory University School of Medicine, Atlanta, Georgia.
11
Texas Scottish Rite Hospital for Children and UT Southwestern Medical Center, Dallas, Texas.
12
DuPont Children's Hospital, Wilmington, Delaware.
13
Seattle Children's Hospital and Research Institute, Seattle, Washington.
14
Texas Scottish Rite Hospital for Children, McDermott Center for Human Growth and Development, and UT Southwestern Medical Center, Dallas, Texas.
15
University of Cincinnati, Cincinnati, Ohio.

Abstract

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.

PMID:
28719732
PMCID:
PMC5874801
DOI:
10.1002/art.40216
[Indexed for MEDLINE]
Free PMC Article

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