R W Chiu1, L L Poon, T K Lau, T N Leung, E M Wong, Y M Lo. 1. Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong, SAR.
Abstract
BACKGROUND: Recently, apoptotic cells have been found in plasma obtained by centrifugation of blood from pregnant women, raising the question of what constitutes plasma and whether plasma is truly cell free. We compared the effects of different blood-processing protocols on the quantification, DNA composition, and day-to-day fluctuation of fetal and total DNA in maternal plasma. METHODS: Blood samples were collected from healthy pregnant women. The blood sample from each individual was simultaneously processed by different means, including the following: Percoll separation, centrifugation, microcentrifugation, and filtration. The resulting plasma aliquots were subjected to real-time quantitative amplification of the beta-globin (for total DNA) and SRY (for fetal DNA) genes. The differences in the beta-globin and SRY DNA concentrations and the degree of variation between the various plasma aliquots were assessed statistically. RESULTS: Different protocols of blood processing significantly affected the quantification and the day-to-day fluctuation of total (P <0.001), but not fetal (quantification, P = 0.336; fluctuation, P = 0.206), DNA in maternal plasma. The quantitative difference could be attributed to the fact that efficacies of different protocols for generating cell-free plasma vary. Processing blood samples by centrifugation followed by filtration or microcentrifugation is effective in producing cell-free plasma. CONCLUSIONS: Standardization in plasma-processing protocols is needed for maternal plasma DNA analysis, especially for quantification of total DNA in maternal plasma. Such preanalytic factors may also affect other applications of plasma DNA analysis.
BACKGROUND: Recently, apoptotic cells have been found in plasma obtained by centrifugation of blood from pregnant women, raising the question of what constitutes plasma and whether plasma is truly cell free. We compared the effects of different blood-processing protocols on the quantification, DNA composition, and day-to-day fluctuation of fetal and total DNA in maternal plasma. METHODS: Blood samples were collected from healthy pregnant women. The blood sample from each individual was simultaneously processed by different means, including the following: Percoll separation, centrifugation, microcentrifugation, and filtration. The resulting plasma aliquots were subjected to real-time quantitative amplification of the beta-globin (for total DNA) and SRY (for fetal DNA) genes. The differences in the beta-globin and SRY DNA concentrations and the degree of variation between the various plasma aliquots were assessed statistically. RESULTS: Different protocols of blood processing significantly affected the quantification and the day-to-day fluctuation of total (P <0.001), but not fetal (quantification, P = 0.336; fluctuation, P = 0.206), DNA in maternal plasma. The quantitative difference could be attributed to the fact that efficacies of different protocols for generating cell-free plasma vary. Processing blood samples by centrifugation followed by filtration or microcentrifugation is effective in producing cell-free plasma. CONCLUSIONS: Standardization in plasma-processing protocols is needed for maternal plasma DNA analysis, especially for quantification of total DNA in maternal plasma. Such preanalytic factors may also affect other applications of plasma DNA analysis.
Authors: Chunming Ding; Rossa W K Chiu; Tze K Lau; Tse N Leung; Li C Chan; Amy Y Y Chan; Pimlak Charoenkwan; Ivy S L Ng; Hai-Yang Law; Edmond S K Ma; Xiangmin Xu; Chanane Wanapirak; Torpong Sanguansermsri; Can Liao; Mary Anne Tan Jin Ai; David H K Chui; Charles R Cantor; Y M Dennis Lo Journal: Proc Natl Acad Sci U S A Date: 2004-07-09 Impact factor: 11.205
Authors: Stephen S C Chim; Yu K Tong; Rossa W K Chiu; Tze K Lau; Tse N Leung; Lisa Y S Chan; Cees B M Oudejans; Chunming Ding; Y M Dennis Lo Journal: Proc Natl Acad Sci U S A Date: 2005-10-03 Impact factor: 11.205
Authors: Alain R Thierry; Brice Pastor; Zhi-Qin Jiang; Anastasia D Katsiampoura; Christine Parseghian; Jonathan M Loree; Michael J Overman; Cynthia Sanchez; Safia El Messaoudi; Marc Ychou; Scott Kopetz Journal: Clin Cancer Res Date: 2017-04-11 Impact factor: 12.531
Authors: Macy M S Heung; Shengnan Jin; Nancy B Y Tsui; Chunming Ding; Tak Y Leung; Tze K Lau; Rossa W K Chiu; Y M Dennis Lo Journal: PLoS One Date: 2009-06-10 Impact factor: 3.240