Genome-wide association analysis of copy number variations in subarachnoid aneurysmal hemorrhage

Abstract

Subarachnoid aneurysmal hemorrhage (SAH) due to cerebral aneurysm rupture is a very serious disease resulting in high mortality rate. It has been known that genetic factors are involved in the risk of SAH. A recent breakthrough in genomic variation called copy number variation (CNV) has been revealed to be involved in risks of human diseases. In this study, we hypothesized that CNVs can predict the risk of SAH. We used the Illumina HumanHap300 BeadChip (317 503 markers) to genotype 497 individuals in a Japanese population. Furthermore, individual CNVs were identified using signal and allelic intensities. The genetic effect of CNV on the risk of SAH was evaluated using multivariate logistic regression controlling for age and gender in 187 common CNV regions (frequency >1%). From a total of 4574 individual CNVs identified in this study (9.7 CNVs per individual), we were able to discover 1644 unique CNV regions containing 1232 genes. The identified variations were validated using visual examination of the genoplot image, overlapping analysis with the Database of Genomic Variants (73.2%), CNVpartition (72.4%) and quantitative PCR. Interestingly, two CNV regions, chr4:153210505-153212191 (deletion, 4q31.3, P=0.0005, P(corr) (corrected P-value)=0.04) and chr10:6265006-6267388 (duplication, 10p15.1, P=0.0006, P(corr)=0.05), were significantly associated with the risk of SAH after multiple testing corrections. Our results suggest that the newly identified CNV regions may contribute to SAH disease susceptibility.