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Complex genetic susceptibility to vascular dementia and an evidence for its underlying genetic factors associated with memory and associative learning

Authors
Lee, ChaeyoungKim, Younyoung
Issue Date
Mar-2013
Publisher
ELSEVIER SCIENCE BV
Keywords
Complex disease; Genomewide association study; Single nucleotide polymorphism; Vascular dementia
Citation
GENE, v.516, no.1, pp.152 - 157
Journal Title
GENE
Volume
516
Number
1
Start Page
152
End Page
157
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/11327
DOI
10.1016/j.gene.2012.12.032
ISSN
0378-1119
Abstract
Genetic basis for vascular dementia (VD) as a typical complex disease has been limitedly reported from association studies conducted with candidate genes. Even recent genomewide association studies (GWAS) could hardly identify additional genetic factors for VD. Although a considerable complexity for its genetic architecture was suspected, there were some challenges to identify false negative associations that resulted from the GWAS. Challenges to identifying genetic factors and their functions after the trials of GWAS revealed that splicing of primary transcript was inhibited (SYK) or delayed (PHLDB2) by a nucleotide substitution of the corresponding gene. The studies gave us the lesson that integrated investigations with statistical genomics as well as functional genomics are needed to identify false negatives from the GWAS. Such endeavors would provide key insights into aspects of underlying nucleotide architectures of VD and incorporate the genetic factors into clinical practice. The recent genetic association studies for susceptibility to VD were briefly overviewed in this article. We also showed a challenge to understanding genetic dissection of VD by a genomic region enrichment analysis with distal cis-regulatory sequences. The analysis with a variant set of potential false negatives from the GWAS revealed that the variants were significantly enriched near genes involved in critical biological processes to VD. (C) 2012 Elsevier B.V. All rights reserved.
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College of Natural Sciences (Department of Bioinformatics & Life Science)
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