Publication: Detection of CAPN10 copy number variation in Thai patients with type 2 diabetes by denaturing high performance liquid chromatography and real-time quantitative polymerase chain reaction
Issued Date
2015-01-01
Resource Type
ISSN
20401124
20401116
20401116
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2-s2.0-84945300495
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of Diabetes Investigation. Vol.6, No.6 (2015), 632-639
Suggested Citation
Nattachet Plengvidhya, Kanjana Chanprasert, Watip Tangjittipokin, Wanna Thongnoppakhun, Pa thai Yenchitsomanus Detection of CAPN10 copy number variation in Thai patients with type 2 diabetes by denaturing high performance liquid chromatography and real-time quantitative polymerase chain reaction. Journal of Diabetes Investigation. Vol.6, No.6 (2015), 632-639. doi:10.1111/jdi.12341 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/36675
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Title
Detection of CAPN10 copy number variation in Thai patients with type 2 diabetes by denaturing high performance liquid chromatography and real-time quantitative polymerase chain reaction
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Abstract
© 2015 Asian Association for the Study of Diabetes and Wiley Publishing Asia Pty Ltd. Aims/Introduction: A combination of multiple genetic and environmental factors contribute to the pathogenesis of type 2 diabetes. Copy number variations (CNVs) are associated with complex human diseases. However, CNVs can cause genotype deviation from the Hardy-Weinberg equilibrium (HWE). A genetic case-control association study in 216 Thai diabetic patients and 192 non-diabetic controls found that, after excluding genotyping errors, genotype distribution of calpain 10 (CAPN10) SNP44 (rs2975760) deviated from HWE. Here, we aimed to detect CNV within the CAPN10 SNP44 region. Materials and Methods: CNV within the CAPN10 SNP44 region was detected using denaturing high-performance liquid chromatography, and the results confirmed by real-time quantitative polymerase chain reaction with SYBR Green I. Results: Both methods successfully identified CNV in the CAPN10 SNP44 region, obtaining concordant results. Correction of genotype calling based on the status of identified CNVs showed that the CAPN10 SNP44 genotype is in good agreement with HWE (P > 0.05). However, no association between CNV genotypes and risk of type 2 diabetes was observed. Conclusions: Identified CNVs for CAPN10 SNP44 genotypes lead to deviation from HWE. Furthermore, both denaturing high-performance liquid chromatography and real-time quantitative polymerase chain reaction are useful for detecting CNVs.