Abstract

Nucleated red blood cells (NRBCs) of fetal origin appear to have distinguishable characteristics from that of maternal NRBCs in both nuclear morphology and properties of hemoglobin staining. However, these differences have yet to be quantified. Our aim was to develop an erythroblast scoring system using four distinct phenotypic parameters (nuclear roundness, nuclear morphology, gamma hemoglobin staining intensity, and peripheral brightness of the stained cytoplasm) to address this issue. NRBCs were isolated from four maternal blood samples by density gradient separation, CD15/45 depletion, and gamma hemoglobin positive selection after elective termination of a trisomy 21 male fetus (47,XY,+21). All cells were deposited onto microscope slides and every NRBC was analyzed according to the scoring system. Each of the four individual parameters was given a value from 0 to 3 points and a combined score was obtained for each cell (range 0-12). Fluorescence in situ hybridization (FISH) using X- and Y-specific probes was performed to determine, on the basis of interphase karyotype, whether the cell was maternal or fetal. The majority of maternal NRBCs were found to have a combined score of 6 or less (103/117) and the majority of fetal NRBCs were found to have a score of 7 or greater (43/53). The proportion of cells that were identified correctly as fetal increased with each ascending category of combined score. For example, 5.7% of NRBCs with a combined score of 5 points or less were found to be fetal, whereas 19.2% of NRBCs with a combined score of 6 points were fetal. At combined scores of 11 and 12 points, 100% of NRBCs were found to be fetal. Fetal NRBCs have characteristic morphology and a gamma hemoglobin staining appearance that makes them distinguishable from maternal NRBCs. The scoring system presented here is a simple and sensitive method to distinguish fetal NRBCs from adult cells in maternal blood. This system may have clinical utility for noninvasive prenatal diagnosis as well as applications for basic research into the developmental biology of NRBCs. In addition, these defined parameters may serve as computational classifiers for the automated detection of fetal cells in maternal blood.

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