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DOI 10.1155/2017/4683857

Медицинская библиотека · Journal of diabetes research · 2017

Rapid Detection of the mt3243A > G Mutation Using Urine Sediment in Elderly Chinese Type 2 Diabetic Patients.

Zhang Yinan, Du Xiujuan, Geng Xinqian, Chu Chen, Lu Huijuan, Shen Yixie, Chen Ruihua, Fang Pingyan, Feng Yanmei, Zhang Xiaojie, Chen Yan, Zhou Yanping, Wang Congrong, Jia Weiping

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Аннотация

OBJECTIVE

In this study, we aimed to identify mt3243A > G mutation carriers in a group of Chinese elderly type 2 diabetic patients by a rapid and noninvasive diagnostic system.

METHODS

DNA was extracted from blood, saliva, and urine sediment samples. The mutation screening and quantitation of heteroplasmy were performed by high-resolution melting (HRM) curve and pyrosequencing, respectively. Patients with mt3243A > G mutation underwent a detailed audiometric, ophthalmologic, neurological, and cardiac examination.

RESULTS

Two patients (2/1041) carrying the mt3243A > G mutation were detected among all type 2 diabetic patients. In patient 1, the heteroplasmy was 0.8%, 2.8%, and 14.7% in peripheral blood leukocytes, saliva, and urine sediment, respectively. In patient 2, the heteroplasmy was 5.3%, 8.4%, and 37.7% in peripheral blood leukocytes, saliva, and urine sediment, respectively. Both of the two patients showed hearing impairment. Abnormal ophthalmologic conditions and hyperintensity on T2-weighted magnetic resonance images were showed in patient 1.

CONCLUSION

The occurrence of mt3243 A > G mutation was 0.2% in Chinese elderly type 2 diabetic patients. Moreover, detection of mt3243 A > G mutation in urine sediment with high-resolution melting (HRM) curve and pyrosequencing is feasible in molecular genetic diagnosis.

Для цитирования: Zhang Yinan, Du Xiujuan, Geng Xinqian, Chu Chen, Lu Huijuan, Shen Yixie, Chen Ruihua, Fang Pingyan, Feng Yanmei, Zhang Xiaojie, Chen Yan, Zhou Yanping, Wang Congrong, Jia Weiping. Rapid Detection of the mt3243A > G Mutation Using Urine Sediment in Elderly Chinese Type 2 Diabetic Patients.. Journal of diabetes research. 2017. DOI: 10.1155/2017/4683857.

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