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The Genetic Effect of Copy Number Variations on the Risk of Type 2 Diabetes in a Korean Population

Authors
Bae, Joon SeolCheong, Hyun SubKim, Ji-HongPark, Byung LaeKim, Jeong-HyunPark, Tae JoonKim, Jason YonghaPasaje, Charisse Flerida A.Lee, Jin SolPark, Yun-JuPark, MieyPark, ChanKoh, InSongChung, Yeun-JunLee, Jong-YoungShin, Hyoung Doo
Issue Date
Apr-2011
Publisher
Public Library of Science
Citation
PLoS ONE, v.6, no.4, pp 1 - 7
Pages
7
Indexed
SCIE
SCOPUS
Journal Title
PLoS ONE
Volume
6
Number
4
Start Page
1
End Page
7
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/168762
DOI
10.1371/journal.pone.0019091
ISSN
1932-6203
1932-6203
Abstract
Background: Unlike Caucasian populations, genetic factors contributing to the risk of type 2 diabetes mellitus (T2DM) are not well studied in Asian populations. In light of this, and the fact that copy number variation (CNV) is emerging as a new way to understand human genomic variation, the objective of this study was to identify type 2 diabetes-associated CNV in a Korean cohort. Methodology/Principal Findings: Using the Illumina HumanHap300 BeadChip (317,503 markers), genome-wide genotyping was performed to obtain signal and allelic intensities from 275 patients with type 2 diabetes mellitus (T2DM) and 496 nondiabetic subjects (Total n = 771). To increase the sensitivity of CNV identification, we incorporated multiple factors using PennCNV, a program that is based on the hidden Markov model (HMM). To assess the genetic effect of CNV on T2DM, a multivariate logistic regression model controlling for age and gender was used. We identified a total of 7,478 CNVs (average of 9.7 CNVs per individual) and 2,554 CNV regions (CNVRs; 164 common CNVRs for frequency>1%) in this study. Although we failed to demonstrate robust associations between CNVs and the risk of T2DM, our results revealed a putative association between several CNVRs including chr15:45994758-45999227 (P = 8.6E-04, P-corr = 0.01) and the risk of T2DM. The identified CNVs in this study were validated using overlapping analysis with the Database of Genomic Variants (DGV; 71.7% overlap), and quantitative PCR (qPCR). The identified variations, which encompassed functional genes, were significantly enriched in the cellular part, in the membrane-bound organelle, in the development process, in cell communication, in signal transduction, and in biological regulation. Conclusion/Significance: We expect that the methods and findings in this study will contribute in particular to genome studies of Asian populations.
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