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Abstract
Objectives:
Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leukocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.
Methods:
Dense genotype data from the HLA region, from the Immunochip array for 5,043 JIA cases and 14,390 controls, was used to impute SNPs, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.
Results
We identified category-specific associations and have demonstrated for the first time that rheumatoid factor negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.
Conclusions
The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and etiology and facilitate transition from paediatric to adult services.
Juvenile idiopathic arthritis (JIA) is a heterogeneous group of diseases, comprising seven categories. Genetic data could potentially be used to help redefine JIA categories and improve the current classification system. The human leukocyte antigen (HLA) region is strongly associated with JIA. Fine-mapping of the region was performed to look for similarities and differences in HLA associations between the JIA categories and define correspondences with adult inflammatory arthritides.
Methods:
Dense genotype data from the HLA region, from the Immunochip array for 5,043 JIA cases and 14,390 controls, was used to impute SNPs, HLA classical alleles and amino acids. Bivariate analysis was performed to investigate genetic correlation between the JIA categories. Conditional analysis was used to identify additional effects within the region. Comparison of the findings with those in adult inflammatory arthritic diseases was performed.
Results
We identified category-specific associations and have demonstrated for the first time that rheumatoid factor negative polyarticular JIA and oligoarticular JIA are genetically similar in their HLA associations. We also observe that each JIA category potentially has an adult counterpart. The RF-positive polyarthritis association at HLA-DRB1 amino acid at position 13 mirrors the association in adult seropositive rheumatoid arthritis (RA). Interestingly, the combined oligoarthritis and RF-negative polyarthritis dataset shares the same association with adult seronegative RA.
Conclusions
The findings suggest the value of using genetic data in helping to classify the categories of this heterogeneous disease. Mapping JIA categories to adult counterparts could enable shared knowledge of disease pathogenesis and etiology and facilitate transition from paediatric to adult services.
Original language | English |
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Pages (from-to) | 765–772 |
Journal | Annals of the rheumatic diseases |
Volume | 76 |
Issue number | 4 |
Early online date | 20 Dec 2016 |
DOIs | |
Publication status | Published - Apr 2017 |
Keywords
- Juvenile idiopathic arthritis (JIA), Autoimmune disease, Rheumatoid arthritis, Gene polymorphism
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- 1 Finished
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Arthritis Research UK Centre of Excellence in the Genetics of Rheumatic Diseases.
Worthington, J., Barton, A., Black, G., Crow, Y., Eyre, S., Raychaudhuri, S. & Thomson, W.
1/08/13 → 31/07/18
Project: Research