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. 2013 Apr;65(4):1055-63.
doi: 10.1002/art.37854.

Deletion variants of RABGAP1L, 10q21.3, and C4 are associated with the risk of systemic lupus erythematosus in Korean women

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Deletion variants of RABGAP1L, 10q21.3, and C4 are associated with the risk of systemic lupus erythematosus in Korean women

Ji-Hong Kim et al. Arthritis Rheum. 2013 Apr.

Abstract

Objective: Several copy number variations (CNVs) have been found to be associated with systemic lupus erythematosus (SLE) through the target gene approach. However, genome-wide features of CNVs and their role in the risk of SLE remain unknown. The aim of this study was to identify SLE-associated CNVs in Korean women.

Methods: Genome-wide assessments of CNVs were performed in 382 SLE patients and 191 control subjects, using an Illumina HumanHap610 BeadChip genotyping platform. SLE-associated CNV regions that were identified by genome-wide association study (GWAS) were replicated in quantitative polymerase chain reaction (PCR) and deletion-typing PCR analyses in an independent sample set comprising 564 SLE patients and 511 control subjects.

Results: Of 144 common CNV regions, 3 deletion-type CNV regions in 1q25.1, 8q23.3, and 10q21.3 were found to be significantly associated with SLE by GWAS analysis. In the independent replication, the CNV regions in 1q25.1 (RABGAP1L) and 10q21.3 were successfully replicated (odds ratio [OR] 1.30, P=0.038 and OR 1.90, P=3.6×10(-5), respectively), and the associations were confirmed again by deletion-typing PCR. The CNV region in the C4 gene, which showed a potential association in the discovery stage, was included in the replication analysis and was found to be significantly associated with the risk of SLE (OR 1.88, P=0.01). Through deletion-typing PCR, the exact sizes and breakpoint sequences of the deletions were defined. Individuals with the deletions in all 3 loci (RABGAP1L, 10q21.3, and C4) had a much higher risk of SLE than did those without any deletions in the 3 loci (OR 5.52, P=3.9×10(-4)).

Conclusion: These CNV regions can be useful to identify the pathogenic mechanisms of SLE, and might be used to more accurately predict the risk of SLE by taking into consideration their synergistic effects on disease susceptibility.

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