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

Laura A. McIntosh, Miranda C. Marion, Marc Sudman, Mary E. Comeau, Mara L. Becker, John F. Bohnsack, Tasha E. Fingerlin, Thomas A. Griffin, J. Peter Haas, Daniel J. Lovell, Lisa A. Maier, Peter A. Nigrovic, Sampath Prahalad, Marilynn Punaro, Carlos D. Rosé, Carol A. Wallace, Carol A. Wise, Halima Moncrieffe, Timothy D. Howard, Carl D. LangefeldSusan D. Thompson

Research output: Contribution to journalArticle

15 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)2222-2232
Number of pages11
JournalArthritis and Rheumatology
Volume69
Issue number11
DOIs
StatePublished - Nov 1 2017

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Juvenile Arthritis
Genome-Wide Association Study
Meta-Analysis
Single Nucleotide Polymorphism
Rheumatoid Factor
Autoimmune Diseases
Genome
Quantitative Trait Loci
Disease Susceptibility
Genetic Association Studies
Rheumatic Diseases
Sample Size
Immunoglobulin M
Pathology
Gene Expression

ASJC Scopus subject areas

  • Immunology and Allergy
  • Rheumatology
  • Immunology

Cite this

McIntosh, L. A., Marion, M. C., Sudman, M., Comeau, M. E., Becker, M. L., Bohnsack, J. F., ... Thompson, S. D. (2017). Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci. Arthritis and Rheumatology, 69(11), 2222-2232. https://doi.org/10.1002/art.40216

Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci. / McIntosh, Laura A.; Marion, Miranda C.; Sudman, Marc; Comeau, Mary E.; Becker, Mara L.; Bohnsack, John F.; Fingerlin, Tasha E.; Griffin, Thomas A.; Haas, J. Peter; Lovell, Daniel J.; Maier, Lisa A.; Nigrovic, Peter A.; Prahalad, Sampath; Punaro, Marilynn; Rosé, Carlos D.; Wallace, Carol A.; Wise, Carol A.; Moncrieffe, Halima; Howard, Timothy D.; Langefeld, Carl D.; Thompson, Susan D.

In: Arthritis and Rheumatology, Vol. 69, No. 11, 01.11.2017, p. 2222-2232.

Research output: Contribution to journalArticle

McIntosh, LA, Marion, MC, Sudman, M, Comeau, ME, Becker, ML, Bohnsack, JF, Fingerlin, TE, Griffin, TA, Haas, JP, Lovell, DJ, Maier, LA, Nigrovic, PA, Prahalad, S, Punaro, M, Rosé, CD, Wallace, CA, Wise, CA, Moncrieffe, H, Howard, TD, Langefeld, CD & Thompson, SD 2017, 'Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci', Arthritis and Rheumatology, vol. 69, no. 11, pp. 2222-2232. https://doi.org/10.1002/art.40216
McIntosh LA, Marion MC, Sudman M, Comeau ME, Becker ML, Bohnsack JF et al. Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci. Arthritis and Rheumatology. 2017 Nov 1;69(11):2222-2232. https://doi.org/10.1002/art.40216
McIntosh, Laura A. ; Marion, Miranda C. ; Sudman, Marc ; Comeau, Mary E. ; Becker, Mara L. ; Bohnsack, John F. ; Fingerlin, Tasha E. ; Griffin, Thomas A. ; Haas, J. Peter ; Lovell, Daniel J. ; Maier, Lisa A. ; Nigrovic, Peter A. ; Prahalad, Sampath ; Punaro, Marilynn ; Rosé, Carlos D. ; Wallace, Carol A. ; Wise, Carol A. ; Moncrieffe, Halima ; Howard, Timothy D. ; Langefeld, Carl D. ; Thompson, Susan D. / Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci. In: Arthritis and Rheumatology. 2017 ; Vol. 69, No. 11. pp. 2222-2232.
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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.",
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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.

PY - 2017/11/1

Y1 - 2017/11/1

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.

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