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This article is part of the supplement: Tenth International Conference on Bioinformatics. First ISCB Asia Joint Conference 2011 (InCoB/ISCB-Asia 2011): Computational Biology

Open Access Proceedings

Genetic copy number variants in myocardial infarction patients with hyperlipidemia

Wei-Chung Shia1, Tien-Hsiung Ku2, Yu-Ming Tsao3, Chien-Hsun Hsia4, Yung-Ming Chang4, Ching-Hui Huang4, Yeh-Ching Chung5, Shih-Lan Hsu6, Kae-Woei Liang7 and Fang-Rong Hsu18*

Author affiliations

1 Department of Information Engineering and Computer Science, Feng Chia University, Taichung City, Taiwan

2 Department of Anesthesia, Changhua Christian Hospital, Changhua County, Taiwan

3 Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

4 Department of Cardiovascular Medicine, Changhua Christian Hospital, Changhua County, Taiwan

5 Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan

6 Department of Medical Education and Research, Taichung Veterans General Hospital, Taichung City, Taiwan

7 Department of Cardiovascular Medicine, Taichung Veterans General Hospital, Taichung City, Taiwan

8 Master's Program in Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung City, Taiwan

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Citation and License

BMC Genomics 2011, 12(Suppl 3):S23  doi:10.1186/1471-2164-12-S3-S23

Published: 30 November 2011

Abstract

Background

Cardiovascular disease is the chief cause of death in Taiwan and many countries, of which myocardial infarction (MI) is the most serious condition. Hyperlipidemia appears to be a significant cause of myocardial infarction, because it causes atherosclerosis directly. In recent years, copy number variation (CNV) has been analyzed in genomewide association studies of complex diseases. In this study, CNV was analyzed in blood samples and SNP arrays from 31 myocardial infarction patients with hyperlipidemia.

Results

We identified seven CNV regions that were associated significantly with hyperlipidemia and myocardial infarction in our patients through multistage analysis (P<0.001), at 1p21.3, 1q31.2 (CDC73), 1q42.2 (DISC1), 3p21.31 (CDCP1), 10q11.21 (RET) 12p12.3 (PIK3C2G) and 16q23.3 (CDH13), respectively. In particular, the CNV region at 10q11.21 was examined by quantitative real-time PCR, the results of which were consistent with microarray findings.

Conclusions

Our preliminary results constitute an alternative method of evaluating the relationship between CNV regions and cardiovascular disease. These susceptibility CNV regions may be used as biomarkers for early-stage diagnosis of hyperlipidemia and myocardial infarction, rendering them valuable for further research and discussion.