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자료유형
학술저널
저자정보
Lee, Hyeseon (Asan Institute for Life Sciences, University of Ulsan College of Medicine) Park, Young-Mi (Asan Institute for Life Sciences, University of Ulsan College of Medicine) We, Yu-Mee (Asan Institute for Life Sciences, University of Ulsan College of Medicine) Han, Duck Jong (Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine) Seo, Jung-Woo (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Moon, Haena (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Lee, Yu-Ho (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Kim, Yang-Gyun (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Moon, Ju-Young (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Lee, Sang-Ho (Department of Internal Medicine, Kyung Hee University Hospital at Gangdong) Lee, Jong-Keuk (Asan Institute for Life Sciences, University of Ulsan College of Medicine)
저널정보
한국유전체학회 Genomics & informatics Genomics & informatics 제15권 제1호
발행연도
2017.1
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2 - 10 (9page)

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Early detection and proper management of kidney rejection are crucial for the long-term health of a transplant recipient. Recipients are normally monitored by serum creatinine measurement and sometimes with graft biopsies. Donor-derived cell-free deoxyribonucleic acid (cfDNA) in the recipient's plasma and/or urine may be a better indicator of acute rejection. We evaluated digital PCR (dPCR) as a system for monitoring graft status using single nucleotide polymorphism (SNP)-based detection of donor DNA in plasma or urine. We compared the detection abilities of the QX200, RainDrop, and QuantStudio 3D dPCR systems. The QX200 was the most accurate and sensitive. Plasma and/or urine samples were isolated from 34 kidney recipients at multiple time points after transplantation, and analyzed by dPCR using the QX200. We found that donor DNA was almost undetectable in plasma DNA samples, whereas a high percentage of donor DNA was measured in urine DNA samples, indicating that urine is a good source of cfDNA for patient monitoring. We found that at least 24% of the highly polymorphic SNPs used to identify individuals could also identify donor cfDNA in transplant patient samples. Our results further showed that autosomal, sex-specific, and mitochondrial SNPs were suitable markers for identifying donor cfDNA. Finally, we found that donor-derived cfDNA measurement by dPCR was not sufficient to predict a patient's clinical condition. Our results indicate that donor-derived cfDNA is not an accurate predictor of kidney status in kidney transplant patients.

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