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Association of intronic sequence variant in the gene encoding spleen tyrosine kinase with susceptibility to vascular dementia

Authors
Kim, YounyoungKong, MinyoungLee, Chaeyoung
Issue Date
Apr-2013
Publisher
INFORMA HEALTHCARE
Keywords
Dementia; genetics; genome-wide association study; polymorphism; spleen tyrosine kinase
Citation
WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY, v.14, no.3, pp.220 - 226
Journal Title
WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY
Volume
14
Number
3
Start Page
220
End Page
226
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/11298
DOI
10.3109/15622975.2011.559272
ISSN
1562-2975
Abstract
Objectives. This study was aimed to identify a novel strong candidate gene for the susceptibility to vascular dementia (VaD) with comprehensive evidences. Methods. A preliminary genome-wide association study (GWAS) was conducted to identify nucleotide sequence variants susceptible to VaD. Literature-based analysis and network analysis were conducted to single out the best candidate gene, and its association was thoroughly examined over its whole sequences. Functions of the most probable variant were predicted by in silico alternative splicing analysis and evaluated by minigene assay. Results. The GWAS showed the most significant variant in spleen tyrosine kinase (SYK) gene. This concurred with the suggestions from both literature-based analysis and network analysis. Further association analysis over the whole SYK gene revealed that rs290227 in intron 8 was the most signifi cant (P = 7.38 x 10(-11)). The subsequent in silico analysis showed that the intronic variant played potential roles in alternative splicing by skipping exon 8 or by truncating exon 9. It was validated by in vivo minigene assay that the G allele of rs290227 induced the delayed splicing. Conclusions. We suggested a novel association of the VaD susceptibility with an intronic variant of rs290227 in the SYK gene. Its G allele could render mature transcripts inappropriately by intron retention and thus lead to a genetic risk for VaD.
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College of Natural Sciences (Department of Bioinformatics & Life Science)
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