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Abstract Number: 177

Differences and Overlap Of Immunological Pathways Implicated In The Aetiology Of Anti-Citrullinated Peptide Antibody Positive and Negative Rheumatoid Arthritis

Sebastien Viatte1, Paul Martin2, Andrew Brass3, Mark Lunt4, Anne Barton5 and Stephen Eyre5, 1Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom, 2Arthritis Research UK Epidemiology Unit, Manchester Academic Health Sciences Centre, Institute of Inflammation and Repair, The University of Manchester, Manchester, United Kingdom, 3School of Computer Science, University of Manchester, Manchester, United Kingdom, Manchester, United Kingdom, 4Arthritis Research UK Centre for Epidemiology, University of Manchester, Manchester, United Kingdom, 5Arthritis Research UK Epidemiology Unit, University of Manchester, Manchester, United Kingdom

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: ACPA, citrulline, Etiopathogenesis, pathogenesis and rheumatoid arthritis (RA)

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Session Information

Title: Genetics and Genomics of Rheumatic Disease I

Session Type: Abstract Submissions (ACR)

Background/Purpose: Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with disease. However, previous studies have been under-powered to detect differences between anti-citrullinated peptide antibody (ACPA) positive and negative patients. Using a custom Illumina® Infinium® array, the RA Consortium for Immunochip (RACI) allows comprehensive analysis of disease associations in both ACPA positive and negative patients. Pathway analyses can identify whether a molecular pathway is associated with disease by testing for enrichment of genes associated with disease. This involves mapping SNP associations to genes, which can often be subjective.

Objectives: The objectives of this study, therefore, were to develop a robust workflow-based method to assign SNPs to genes and to compare the pathways significantly enriched in ACPA positive and negative patients.

Methods: Excluding HLA, the top 100 most associated SNPs from the Immunochip analysis were selected for ACPA positive patients along with the top 100 most associated SNPs from the ACPA negative analysis. Genes were assigned to these SNPs using a Taverna workflow which defines an associated region using SNPs in linkage disequilibrium (LD) with the associated SNP. This prevents the bias introduced by researchers assigning SNPs to ‘biologically plausible’ genes and provides a robust, reproducible method for assigning genetic associations to genes. These genes were subsequently tested for enrichment in PANTHER pathways and Gene Ontologies (GO) using the Expression Analysis tool to calculate an enrichment binomial probability. To correct for the enrichment of genes with immunological functions present on the Immunochip, the statistical significance of enrichment binomial probabilities was calculated by permutation.

Results: Overall we show that the proportion of pathways shared between the two RA serological subtypes is significantly larger than expected by chance, indicating a high degree of overlap. On the other hand, we identified some pathways specifically and significantly enriched in the ACPA positive gene list (Interleukin Signalling Pathway: permutation p-value for enrichment = 7.0E-03, while in ACPA negative p = 0.46) and in the ACPA negative gene list (Interferon-Gamma Signalling Pathway: p = 1.2E-03, while in ACPA positive p = 0.33).

Conclusion: This study provides the first comparative pathway analysis of RA serological subtypes based on large numbers of RA cases. The methods developed here present a quantitative framework to compare different diseases at the pathway level. The findings not only suggest shared processes between the two disease sub-groups, but also identify serotype-specific pathways.


Disclosure:

S. Viatte,
None;

P. Martin,
None;

A. Brass,
None;

M. Lunt,
None;

A. Barton,
None;

S. Eyre,
None.

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