Abstract
Noninvasive Prenatal Testing (NIPT) has advanced the detection of fetal chromosomal aneuploidy by analyzing cell-free DNA in peripheral maternal blood. The statistic Z-test that it utilizes, which measures the deviation of each chromosome dosage from its negative control, is now widely accepted in clinical practice. However, when a chromosome has loss and gain regions which offset each other in the z-score calculation, merely using the Z-test for the result tends to be erroneous. To improve the performance of NIPT in this aspect, a novel graphic-aided algorithm (gNIPT) that requires no extra experiment procedures is reported in this study. In addition to the Z-test, this method provides a detailed analysis of each chromosome by dividing each chromosome into multiple 2 Mb size windows, calculating the z-score and copy number variation of each window, and visualizing the z-scores for each chromosome in a line chart. Data from 13537 singleton pregnancy women were analyzed and compared using both the normal NIPT (nNIPT) analysis and the gNIPT method. The gNIPT method had significantly improved the overall positive predictive value (PPV) of nNIPT (88.14% vs. 68.00%, p = 0.0041) and the PPV for trisomy 21 (T21) detection (93.02% vs. 71.43%, p = 0.0037). There were no significant differences between gNIPT and nNIPT in PPV for trisomy 18 (T18) detection (88.89% vs. 63.64%, p = 0.1974) and in PPV for trisomy 13 (T13) detection (57.14% vs. 50.00%, p = 0.8004). One false-negative T18 case in nNIPT was detected by gNIPT, which demonstrates the potency of gNIPT in discerning chromosomes that have variation in multiple regions with an offsetting effect in z-score calculation. The gNIPT was also able to detect copy number variation (CNV) in chromosomes, and one case with pathogenic CNV was detected during the study. With no additional test requirement, gNIPT presents a reasonable solution in improving the accuracy of normal NIPT.
Highlights
Since the discovery of the presence of cell-free fetal DNA in maternal peripheral blood in 1997 [1], various strategies have been proposed to develop screening or diagnostic tests for fetal aneuploidy
The noninvasive nature of Noninvasive Prenatal Testing (NIPT) has its strength in avoiding the unnecessary risk of fetal miscarriage, comparing to conventional prenatal diagnosis, such as amniocentesis, which is the golden standard of prenatal diagnosis for fetal chromosomal abnormalities and involves the invasive sampling of fetal materials [6]
The positive predictive value (PPV) for the overall test was significantly increased from 66.67% in the normal NIPT (nNIPT) to 88.14% with the gNIPT test (p = 0:0041)
Summary
Since the discovery of the presence of cell-free fetal DNA (cffDNA) in maternal peripheral blood in 1997 [1], various strategies have been proposed to develop screening or diagnostic tests for fetal aneuploidy. The noninvasive nature of NIPT has its strength in avoiding the unnecessary risk of fetal miscarriage, comparing to conventional prenatal diagnosis, such as amniocentesis, which is the golden standard of prenatal diagnosis for fetal chromosomal abnormalities and involves the invasive sampling of fetal materials [6] Other noninvasive methods, such as serological test or ultrasonography, have a high false-positive rate and BioMed Research International false-negative rate. The statistical Z-test of unique read count analysis was utilized as a significant difference test [2] to overcome the challenge that fetal DNA only represents a small proportion of the maternal plasma with the majority of the plasma being maternal DNA in NIPT [9] It measures the number of standard deviations of the sample chromosome from the mean of a negative reference dataset. This gNIPT method has great potential in improving the accuracy of nNIPT
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