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Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers
BACKGROUND: There is a long-established association between rheumatoid arthritis and HLA-DRβ1. The shared epitope (SE) allele is an indicator of the presence of any of the HLA-DRβ1 alleles associated with RA. Other autoantibodies are also associated with RA, specifically rheumatoid factor IgM (RFUW)...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795892/ https://www.ncbi.nlm.nih.gov/pubmed/20017985 |
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author | Matthews, Abigail G Li, Jia He, Chunsheng Ott, Jurg Andrade, Mariza de |
author_facet | Matthews, Abigail G Li, Jia He, Chunsheng Ott, Jurg Andrade, Mariza de |
author_sort | Matthews, Abigail G |
collection | PubMed |
description | BACKGROUND: There is a long-established association between rheumatoid arthritis and HLA-DRβ1. The shared epitope (SE) allele is an indicator of the presence of any of the HLA-DRβ1 alleles associated with RA. Other autoantibodies are also associated with RA, specifically rheumatoid factor IgM (RFUW) and anti-cyclic citrullinated peptide (anti-CCP). METHODS: Using the Genetic Analysis Workshop 16 North American Rheumatoid Arthritis Consortium genome-wide association data, we sought to find non-HLA-DRβ1 genetic associations by stratifying across SE status, and using the continuous biomarker phenotypes of RFUW and anti-CCP. To evaluate the binary RA phenotype, we applied the recently developed FP test and compared it to logistic regression or a genotype count-based test. We adjusted for multiple testing using the Bonferroni correction, the Q value approach, or permutation-based p-values. A case-only analysis of the biomarkers RFUW and anti-CCP used linear regression and ANOVAs. RESULTS: The initial genome-wide association analysis using all cases and controls provides substantial evidence of an association on chromosomes 9 and 2 within the immune system-related gene UBXD2. In SE-positive subjects, many single-nucleotide polymorphisms were significant, including some on chromosome 6. Due to very few SE negative cases, we had limited power to detect associations in SE negative subjects. We were also unable to find genetic associations with either RFUW or anti-CCP. CONCLUSION: Our analyses have confirmed previous findings for genes PTPN22 and C5. We also identified a novel candidate gene on chromosome 2, UBXD2. Results suggest FP test may be more powerful than the genotype count-based test. |
format | Text |
id | pubmed-2795892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27958922009-12-18 Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers Matthews, Abigail G Li, Jia He, Chunsheng Ott, Jurg Andrade, Mariza de BMC Proc Proceedings BACKGROUND: There is a long-established association between rheumatoid arthritis and HLA-DRβ1. The shared epitope (SE) allele is an indicator of the presence of any of the HLA-DRβ1 alleles associated with RA. Other autoantibodies are also associated with RA, specifically rheumatoid factor IgM (RFUW) and anti-cyclic citrullinated peptide (anti-CCP). METHODS: Using the Genetic Analysis Workshop 16 North American Rheumatoid Arthritis Consortium genome-wide association data, we sought to find non-HLA-DRβ1 genetic associations by stratifying across SE status, and using the continuous biomarker phenotypes of RFUW and anti-CCP. To evaluate the binary RA phenotype, we applied the recently developed FP test and compared it to logistic regression or a genotype count-based test. We adjusted for multiple testing using the Bonferroni correction, the Q value approach, or permutation-based p-values. A case-only analysis of the biomarkers RFUW and anti-CCP used linear regression and ANOVAs. RESULTS: The initial genome-wide association analysis using all cases and controls provides substantial evidence of an association on chromosomes 9 and 2 within the immune system-related gene UBXD2. In SE-positive subjects, many single-nucleotide polymorphisms were significant, including some on chromosome 6. Due to very few SE negative cases, we had limited power to detect associations in SE negative subjects. We were also unable to find genetic associations with either RFUW or anti-CCP. CONCLUSION: Our analyses have confirmed previous findings for genes PTPN22 and C5. We also identified a novel candidate gene on chromosome 2, UBXD2. Results suggest FP test may be more powerful than the genotype count-based test. BioMed Central 2009-12-15 /pmc/articles/PMC2795892/ /pubmed/20017985 Text en Copyright ©2009 Matthews et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Matthews, Abigail G Li, Jia He, Chunsheng Ott, Jurg Andrade, Mariza de Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title | Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title_full | Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title_fullStr | Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title_full_unstemmed | Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title_short | Adjusting for HLA-DRβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
title_sort | adjusting for hla-drβ1 in a genome-wide association analysis of rheumatoid arthritis and related biomarkers |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795892/ https://www.ncbi.nlm.nih.gov/pubmed/20017985 |
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