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Hematopoietic chimerism monitoring based on STRs: quantitative platform performance on sequential samples.
Authors:Don Kristt  Moshe Israeli  Ronit Narinski  Hagit Or  I Yaniv  Jerry Stein  Tirza Klein
Affiliation:Laboratory of Histocompatibility and Immunogenetics, Rabin Medical Center, Petach Tikvah, Israel. dkristt@clalit.org.il
Abstract:
Hematopoietic stem cell transplantation (HSCT) creates a donor-recipient cellular chimerism in the patient, which is quantitatively assayed from peripheral blood based on STR-DNA. Since chimerism values often vary across a patient's samples, it is important to determine to what extent this variability reflects technical aspects of platform performance. This issue is systematically assessed in the current study for the first time. Using the SGM Plus multiplex PCR kit and ABI platform, the longitudinal performance of STR markers was quantitatively evaluated in two chimeric models with true values, and in patient samples (n >500 marker loci). Computation of percent chimerism for each marker, and mean (sample) percent chimerism, standard deviation, and coefficient of variance was performed by our ChimerTrack utility. In chimeric models with known values, individual markers exhibited an accuracy (observed/true) of 88-98%; replication precision was 92-100% true, with a mean error of 2%. Fragment size calling was greater than 99% accurate and precise. Patient results were comparable for markers, relaive to sample means. One source of technical variability in chimerism estimation was allelic differential amplification efficiency. The latter was influenced by signal amplitude, dye label, marker size, and allelic size interval. It can be concluded that long-term chimeric tracking is routinely feasible using this platform in conjunction with ChimerTrack software. Importantly, mean percent chimerism, for any sample, should closely approximate the true chimeric status, with a technical accuracy of 98%. Guidelines are presented for selecting an optimized marker profile.
Keywords:Chimerism   quantitation   STRs   ssmicrosatellites   stem sscell transplantion   software   hematological malignancies   genetic diseases   PCR   multiplex
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