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Mitochondrial DNA copy number augments performance of A(1)C and oral glucose tolerance testing in the prediction of type 2 diabetes

Here, we tested the performance of the mitochondrial DNA copy number (mtDNA-CN) in predicting future type 2 diabetes (n = 1108). We used the baseline clinical data (age, sex, body mass index, waist-to-hip ratio, systolic and diastolic blood pressure) and the mtDNA-CN, hemoglobin A(1c) (A(1)C) levels...

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Detalles Bibliográficos
Autores principales: Cho, Seong Beom, Koh, InSong, Nam, Hye-Young, Jeon, Jae-Pil, Lee, Hong Kyu, Han, Bok-Ghee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333082/
https://www.ncbi.nlm.nih.gov/pubmed/28251996
http://dx.doi.org/10.1038/srep43203
Descripción
Sumario:Here, we tested the performance of the mitochondrial DNA copy number (mtDNA-CN) in predicting future type 2 diabetes (n = 1108). We used the baseline clinical data (age, sex, body mass index, waist-to-hip ratio, systolic and diastolic blood pressure) and the mtDNA-CN, hemoglobin A(1c) (A(1)C) levels and results of oral glucose tolerance test (OGTT) including fasting plasma glucose, 1-hour glucose, and 2-hour glucose levels, to predict future diabetes. We built a prediction model using the baseline data and the diabetes status at biannual follow-up of 8 years. The mean area under curve (AUC) for all follow-ups of the full model including all variables was 0.92 ± 0.04 (mean ± standard deviation), while that of the model excluding the mtDNA-CN was 0.90 ± 0.03. The sensitivity of the f4ull model was much greater than that of the model not including mtDNA-CN: the mean sensitivities of the model with and without mtDNA-CN were 0.60 ± 0.06 and 0.53 ± 0.04, respectively. We found that the mtDNA-CN of peripheral leukocytes is a biomarker that augments the predictive power for future diabetes of A(1)C and OGTT. We believe that these results could provide invaluable information for developing strategies for the management of diabetes.