作者
Seung‐Hyun Jung,Seon‐Hee Yim,Hae‐Jin Hu,Kyu Hoon Lee,Joohyun Lee,Dong‐Hoon Sheen,Myung-Jae Lim,Soon‐Young Kim,Sung‐Won Park,So‐Hee Kim,Kyudong Han,So Yeon Kim,Seung‐Cheol Shim,Yeun‐Jun Chung
摘要
Objective To identify ankylosing spondylitis (AS)–associated copy number variations (CNVs) in Korean subjects and their synergistic roles in the development of AS. Methods A genome‐wide association study (GWAS) was performed in 309 patients with AS and 309 control subjects, using a copy number variant (CNV) microarray. AS‐associated CNV regions were replicated in 2 independent sets (625 patients and 891 control subjects) by quantitative polymerase chain reaction (PCR) and deletion‐typing PCR. Results In the CNV GWAS, 227 CNV regions were shown to be significantly associated with the risk of AS. Of the candidate CNV regions, 9 were successfully replicated in the first replication analysis: 1q32.2 ( HHAT ), 1p34.2 ( BMP8A ), 2q31.2 ( PRKRA ), 6p21.32 ( HLA–DPB1 ), 11q22.1 ( CNTN5 ), 13q13.1 ( EEF1DP3 ), 14q24.2 ( RGS6 ), 16p13.3, and 22q11.1 ( IL17RA ). The 5 deletion‐type CNV regions, in 1q32.2, 2q31.2, 6p21.32, 13q13.1, and 16p13.3, were associated with an increased risk of AS, and the other 4 CNV regions were protective. In the second replication analysis, 4 CNV regions in 1q32.2, 2q31.2, 6p21.32, and 16p13.3 were replicated. Among patients with CNV regions in ≥4 risk‐increasing loci, the risk was 18.0 times higher than that in patients without any deletions (odds ratio [OR] 17.98, P = 2.3 × 10 −7 ). Among patients with CNV regions in ≥2 protective loci, the risk was 5.2 times lower than that in those without any deletions (OR 0.19, P = 4.0 × 10 −10 ). The additive effects of simultaneous events were shown to be dependent on the frequency of CNV regions. Through deletion‐typing PCR and sequencing, the exact sizes and breakpoint sequences were defined in 4 CNV regions. The mechanism of all 3 deletions was shown to be microhomology‐based nonhomologous end joining. Conclusion The results of this study can help to identify pathogenic mechanisms of AS and can easily be applied in the development of algorithms estimating the risk of AS.