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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)...

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Autores principales: Matthews, Abigail G, Li, Jia, He, Chunsheng, Ott, Jurg, Andrade, Mariza de
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
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.
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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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