Genome-wide association and targeted analysis of copy number variants with psoriatic arthritis in German patients.

backgroundPsoriatic Arthritis (PsA) is a chronic inflammatory disease of the joints. PsA is etiologically complex, and 11 susceptibility loci have been identified so far. Most of these overlap with loci associated with psoriasis vulgaris (PsV), the most common psoriatic skin manifestation which is also frequently seen in PsA patients. In addition, two copy number variants (CNVs) are associated with PsV, one of which, located within the LCE3 gene cluster, is also associated with PsA. Finally, an intergenic deletion has been reported as a PsA-specific CNV.

methodsWe performed a genome-wide association study (GWAS) of CNVs in PsA and assessed the contribution to disease risk by CNVs at known psoriasis susceptibility loci.

resultsAfter stringent quality assessment and validation of CNVs of the GWAS with an alternative quantitative method, two significantly associated CNVs remained, one near UXS1, the other one at the TRB locus. However, MLPA analysis did not confirm the CN state in ~1/3 of individuals, and an analysis of an independent case-control-study failed to confirm the initial associations. Furthermore, detailed PCR-based analysis of the sequence at TRB revealed the existence of a more complex genomic sequence most accurately represented by freeze hg18 which accordingly failed to confirm the hg19 sequence. Only rare CNVs were detected at psoriasis susceptibility loci. At three of 12 susceptibility loci with CNVs (CSMD1, IL12B, RYR2), CN variability was confirmed independently by MLPA. Overall, the rate of CNV confirmation by MLPA was strongly dependent upon CNV type, CNV size and the number of array markers involved in a CNV.

conclusionAlthough we identified PsA associations at several loci and confirmed that the common CNVs at these sites were real, ~1/3 of the common CNV states could not be reproduced. Furthermore, replication analysis failed to confirm the original association. Furthermore, SNP array-based analyses of CNVs were found to be more reliable for deletions than duplications, independent of the respective CNV allele frequency. CNVs are thus good candidate disease variants, while the methods to detect them should be applied cautiously and reproduced by an independent method.