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. 2011 Oct;7(10):e1002341.
doi: 10.1371/journal.pgen.1002341. Epub 2011 Oct 27.

Association of NCF2, IKZF1, IRF8, IFIH1, and TYK2 with systemic lupus erythematosus

Affiliations

Association of NCF2, IKZF1, IRF8, IFIH1, and TYK2 with systemic lupus erythematosus

Deborah S Cunninghame Graham et al. PLoS Genet. 2011 Oct.

Abstract

Systemic lupus erythematosus (SLE) is a complex trait characterised by the production of a range of auto-antibodies and a diverse set of clinical phenotypes. Currently, ~8% of the genetic contribution to SLE in Europeans is known, following publication of several moderate-sized genome-wide (GW) association studies, which identified loci with a strong effect (OR>1.3). In order to identify additional genes contributing to SLE susceptibility, we conducted a replication study in a UK dataset (870 cases, 5,551 controls) of 23 variants that showed moderate-risk for lupus in previous studies. Association analysis in the UK dataset and subsequent meta-analysis with the published data identified five SLE susceptibility genes reaching genome-wide levels of significance (P(comb)<5×10(-8)): NCF2 (P(comb) = 2.87×10(-11)), IKZF1 (P(comb) = 2.33×10(-9)), IRF8 (P(comb) = 1.24×10(-8)), IFIH1 (P(comb) = 1.63×10(-8)), and TYK2 (P(comb) = 3.88×10(-8)). Each of the five new loci identified here can be mapped into interferon signalling pathways, which are known to play a key role in the pathogenesis of SLE. These results increase the number of established susceptibility genes for lupus to ~30 and validate the importance of using large datasets to confirm associations of loci which moderately increase the risk for disease.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Pathways of immuno-dysregulation by five new susceptibility genes for SLE.
The figure shows the interferon-related pathways involving NCF2, IKZF1, IRF8, IFIH1 and TYK2 and and the ways in which these pathways may contribute to lupus susceptibility. In SLE these five genes contribute to increasing the levels of type-I and –II interferons, imbalances in Th1/Th2 related to disease severity, perturbations in B cell physiology and production of a diverse set of auto-antibodies.
Figure 2
Figure 2. Expression pattern in EBV-transformed lymphoblastoid cell lines.
Regression analysis, as described in the materials and methods, was performed on publically available genotype data from EBV-transformed B cells which were part of the HAPMAP collection and expression data on the same individuals taken from the GEO database. Four populations were used: CEPH, YRI and CHB/JPT (ASN) . The GEO dataset was GSE12526 and the expression probes were: A) NCF2 (209949_at), B) IRF8 (204057_at). For each graph, the mean expression per risk (R) allele and that for the non-risk (r) allele was plotted for each population. The alleles are listed on each bar and for each SNP, the total number of individuals for which there was both genotype and expression data are quoted for the three populations analysed. C) Heritability estimates for each locus were taken from the mRNA by SNP browser (http://www.sph.umich.edu/csg/liang/asthma/).

References

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