Evaluation of the Z-score accuracy of noninvasive prenatal testing for fetal trisomies 13, 18 and 21 at a single center

NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach

Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population. Subsequently, we proposed a sequence-to-graph alignment method, which considers the read mis-match rates during the mapping process, and an indexing method using hash indexing and adjacency lists to accelerate the read alignment process. Finally, by integrating multi-source aligned read and polymorphic sites across the pan-genome, NIPT-PG obtains a more accurate z-score, thereby improving the accuracy of chromosomal aneuploidy detection. We tested NIPT-PG on two simulated datasets and 745 real-world cell-free DNA sequencing data sets from pregnant women. Results demonstrate that NIPT-PG outperforms the standard z-score test. Furthermore, combining experimental and theoretical analyses, we demonstrate the probably approximately correct learnability of NIPT-PG. In summary, NIPT-PG provides a new perspective for fetal chromosomal aneuploidies detection. NIPT-PG may have broad applications in clinical testing, and its detection results can serve as a reference for false positive samples approaching the critical threshold.

Comparison of the performance of NIPT and NIPT-plus for fetal chromosomal aneuploidy and high Z-score increases the positive predictive value

OBJECTIVE

To evaluate non-invasive prenatal testing (NIPT) and expanded non-invasive prenatal testing (NIPT-plus) for detecting aneuploidies at different sequencing depths and assess Z-score accuracy in predicting trisomies 21, 18, 13, 45X, and 47XXX.

METHODS

Pregnancies with positive NIPT or NIPT-plus results detected at the prenatal diagnosis center of Nanfang Hospital were included in this retrospective study, between January 2017 and December 2022. Invasive prenatal diagnostic results were collected. Logistic regression analyses were used to study the relationship between Z-score and positive predictive value (PPV). Optimal cut-off values were obtained based on receiver operating characteristic analysis, and PPVs were calculated in different groups.

RESULTS

We evaluated 1348 pregnant women with positive results, including 930 reported by NIPT and 418 reported by NIPT-plus. NIPT reported significantly more rare chromosomal aneuploidies (RCAs), and NIPT-plus had a significantly higher PPV for trisomy 21 (T21). Logistic regression analyses showed a significant association (P < 0.001) between Z-score and PPVs for T21 and trisomy 18 (T18). A linear relationship was observed between fetal fraction (FF) and Z-values in the true positive cases of T21 and T18.The high Z-score group had significantly higher PPVs than the low Z-score group for T21, T18, trisomy 13, and 47XXX, but not for 45X.

CONCLUSION

The Z-score is helpful in assessing NIPT or NIPT-plus results. Therefore, we suggest including the Z-score and FF in the results. By combining the Z-score, FF, and maternal age, clinicians can interpret NIPT results more accurately and improve personal counsel to reduce patients' anxiety.

Combined Z-scores to assess the impact of rare autosomal trisomies that results in non-invasive prenatal screening on pregnancy outcomes

OBJECTIVE

This study aimed to combine Z-scores to evaluate the effects of rare autosomal trisomies (RATs) in non-invasive prenatal screening (NIPS) on pregnancy outcomes at a single center.

METHODS

We retrospectively collected the clinical data of women with high-risk RATs results using NIPS at a single center between January 2017 and December 2021. NIPS-positive results were separated into three groups based on the Z-value of RATs (Group1: 6 ≤ Z < 10; Group2: 10 ≤ Z < 15; Group 3: Z ≥ 15). Pregnancy outcomes of women with RATs were compared with the low-risk NIPS group.

RESULTS

Overall, 83 RATs were identified in 23,321 NIPS results at our center. Prenatal diagnosis was conducted for 55 patients, and no case was confirmed, with a positive predictive value (PPV) of zero. Fifteen of these patients had adverse pregnancy outcomes, including delivered preterm and/or birth weight (9/15, 60.0 %), structural abnormalities (4/15, 26.7 %), miscarriage (1/15, 6.7 %), and intrauterine death (1/15, 6.7 %). There were 8 (8/22, 36.4 %) adverse pregnancy outcomes in Group 3, which was significantly higher than that in the low-risk NIPS group (p < 0.01). No significant difference was observed between the control group and Group 1 and Group 2 (p > 0.01).

CONCLUSIONS

Clinicians should pay more attention to the RATs results when the Z-score is ≥ 15. The data are available for clinicians to guide the prenatal diagnosis of RATs and pregnancy management.

A high Z-score might increase the positive predictive value of cell-free noninvasive prenatal testing for singleton-pregnant women

OBJECTIVE

To explore the positive predictive value (PPV) in noninvasive prenatal testing (NIPT)-positive cases and analyze the effect of the Z-score intervals on PPV performance.

METHODS

In this retrospective study, 26,667 pregnant women underwent NIPT from November 2014 to August 2022, of which 169 were NIPT-positive cases. NIPT-positive cases were divided into three groups according to the Z-score: 3 ≤ Z < 6, 6 ≤ Z < 10, and Z ≥ 10.

RESULTS

The PPVs of NIPT were 91.26% (94/103) for trisomy (T) 21, 80.65% (25/31) for T18, and 36.84% (7/19) for T13. The PPVs for the 3 ≤ Z < 6, 6 ≤ Z < 10, and Z ≥ 10 groups were 50%, 84.62%, and 87.95%, respectively. A higher PPV was found in the NIPT results when the Z-score was larger, with significant differences. The PPVs for T21/T18/T13 were 71.43%/42.86%/25% for 3 ≤ Z < 6, 90.32%/85.71%/57.14% for 6 ≤ Z < 10, and 93.85%/100%/25% for Z ≥ 10. For T21, T18, and T13, the correlations between the Z-score and fetal fraction concentration in true positives were r = 0.85, r = 0.59, and r = 0.71 (all p < .001), respectively.

CONCLUSION

Z-score is associated with the PPV performance of NIPT in fetal T13, T18, and T21. The possibility of false positives caused by placental chimerism should be considered when determining whether high Z-values lead to high PPVs.

Non-invasive prenatal testing for the diagnosis of congenital abnormalities: Insights from a large multicenter study in southern China

Although non-invasive prenatal testing (NIPT) is widely used to detect fetal abnormalities, the results of NIPT vary by population, and data for the screening efficiency of NIPT positive predictive value (PPV) from different populations is limited. Herein, we retrospectively analyzed the NIPT results in a large multicenter study involving 52,855 pregnant women. Depending on gestational age, amniotic fluid or umbilical cord blood was extracted for karyotype and/or chromosome microarray analysis (CMA) in NIPT-positive patients, and the PPV and follow-up data were evaluated to determine its clinical value. Among the 52,855 cases, 754 were NIPT-positive, with a positivity rate of 1.4%. Karyotype analysis and/or CMA confirmed 323 chromosomal abnormalities, with a PPV of 45.1%. PPV for trisomy 21 (T21), trisomy 18 (T18), trisomy 13 (T13), sex chromosomal aneuploidies (SCAs), and copy number variations (CNVs) were 78.9, 35.3, 22.2, 36.9, and 32.9%, respectively. The PPVs for T21, T18, and T13 increased with age, whereas the PPVs for SCAs and CNVs had little correlation with age. The PPV was significantly higher in patients with advanced age and abnormal ultrasound. The NIPT results are affected by population characteristics. NIPT had a high PPV for T21 and a low PPV for T13 and T18, and screening for SCAs and CNVs showed clinical significance in southern China.

Combined fetal fraction to analyze the Z-score accuracy of noninvasive prenatal testing for fetal trisomies 13, 18, and 21

OBJECTIVE

This study aims to evaluate the correlation combined fetal fraction and Z-score for fetal trisomies 13, 18, and 21 of NIPT by the semiconductor sequencing platform and further analyze the differences of different sequencing depths.

METHODS

A cohort of 61,581 pregnancies were recruited for NIPT. Invasive prenatal diagnostic confirmation is recommended in all high-risk NIPT cases. Logistic regression and rank correlation analysis were applied to analyze the relationship between different parameters. ROC curve analysis was adopted to analyze the cutoff values of Z-score and fetal fraction.

RESULTS

A total of 278 common trisomy pregnancies were verified in 377 NIPT-positive results. The fitted logistic regression models revealed that Z-scores of NIPT-positive results were significantly associated with PPVs (p < 0.05). The ROC curve analysis showed that the optimal cutoff value of Z-scores for T21, T18, and T13 was 7.597, 4.944, and 9.135 for NIPT and 9.489, 8.004, and 12.4 for NIPT-plus. If combing fetal fraction as another evaluation factor, the PPV of trisomy 21 gradually improved. We analyzed the correlation between the fetal fraction and the PPV, which revealed that the fetal fraction was significantly correlated with PPV. By analyzing the PPV of different groups divided by the associated criteria obtained from ROC curve, the PPV of high Z-score and high fetal fraction is higher in groups of Z-score > the optimal cutoff value.

CONCLUSION

The results of this study show that the fetal fraction is significantly correlated with the PPV. Combining fetal fraction with Z-score is significantly better than in groups of Z-score-associated criteria; clinicians can give more accurate and efficient prenatal genetic counseling.

Combined Model-Based Prediction for Non-Invasive Prenatal Screening

The risk of chromosomal abnormalities in the child increases with increasing maternal age. Although non-invasive prenatal testing (NIPT) is a safe and effective prenatal screening method, the accuracy of the test results needs to be improved owing to various testing conditions. We attempted to achieve a more accurate and robust prediction of chromosomal abnormalities by combining multiple methods. Here, three different methods, namely standard Z-score, normalized chromosome value, and within-sample reference bin, were used for 1698 reference and 109 test samples of whole-genome sequencing. The logistic regression model combining the three methods achieved a higher accuracy than any single method. In conclusion, the proposed method offers a promising approach for increasing the reliability of NIPT.

Development and performance evaluation of an artificial intelligence algorithm using cell-free DNA fragment distance for non-invasive prenatal testing (aiD-NIPT)

With advances in next-generation sequencing technology, non-invasive prenatal testing (NIPT) has been widely implemented to detect fetal aneuploidies, including trisomy 21, 18, and 13 (T21, T18, and T13). Most NIPT methods use cell-free DNA (cfDNA) fragment count (FC) in maternal blood. In this study, we developed a novel NIPT method using cfDNA fragment distance (FD) and convolutional neural network-based artificial intelligence algorithm (aiD-NIPT). Four types of aiD-NIPT algorithm (mean, median, interquartile range, and its ensemble) were developed using 2,215 samples. In an analysis of 17,678 clinical samples, all algorithms showed &gt;99.40% accuracy for T21/T18/T13, and the ensemble algorithm showed the best performance (sensitivity: 99.07%, positive predictive value (PPV): 88.43%); the FC-based conventional Z-score and normalized chromosomal value showed 98.15% sensitivity, with 40.77% and 36.81% PPV, respectively. In conclusion, FD-based aiD-NIPT was successfully developed, and it showed better performance than FC-based NIPT methods.

A retrospective single-center analysis of prenatal diagnosis and follow-up of 626 chinese patients with positive non-invasive prenatal screening results

This study explored the diagnostic efficiency of different prenatal diagnostic approaches for women with positive non-invasive prenatal screening (NIPS) results by analyzing their clinical information and pregnancy outcomes. We collected data on 626 NIPS-positive pregnant women from January 2017 to June 2021 and arranged subsequent prenatal diagnostic operations for them after genetic counseling, along with long-term intensive follow-up. A total of 567 women accepted invasive prenatal diagnosis (IPD) (90.58%), and 262 cases were confirmed as true positives for NIPS. The positive predictive values for trisomies 21 (T21), 18 (T18), and 13 (T13); sex chromosome aneuploidies (SCAs); rare autosomal trisomies (RATs); and microdeletion and microduplication syndromes (MMS) were 81.13%, 37.93%, 18.42%, 48.83%, 18.37%, and 41.67%, respectively. Discordant results between NIPS and IPD were observed in 48 cases, with the discordance rate being 8.47%. Additionally, there were 43 cases with discordant results between karyotyping and chromosomal microarray analysis (CMA)/copy number variation sequencing. Additional reporting of RATs and MMS with routine NIPS that only detects T21/T18/T13 and SCAs can yield more accurate diagnoses. However, NIPS cannot be used as a substitute for IPD owing to its high false positive rate and discordance with other diagnostic methods. Therefore, we recommend CMA combined with karyotyping as the preferred method for accurately diagnosing NIPS-positive women.

Noninvasive prenatal screening in southeast China: clinical application and accuracy evaluation

OBJECTIVE

To assess the clinical performance of noninvasive prenatal screening (NIPS) for both common trisomy and sex chromosome aneuploidy (SCA).

METHODS

We recruited 71,888 pregnant women to undergo NIPS testing from December 2015 to June 2021. Demographic characteristics, diagnostic results, and follow-up outcomes were collected.

RESULTS

There were a total of 381 high-risk cases for common trisomy and 343 positive screens for SCA. Invasive prenatal diagnosis (IPD) was performed in 507 (70.0%) participants. The positive predictive value (PPV) was 83.7% for T21, 72.5% for T18, 14.3% for T13, 31.9% for 45,X, 72.0% for 47,XXX, 89.8% for 47,XXY, and 72.2% for 47,XYY, respectively. Logistic regression analysis presented a significant association between Z-score and PPV in common trisomy (P < 0.05) while not in SCA (P > 0.05). PPV in the high-risk group (Z-score ≥ cutoff) was superior to that in the intermediate risk group (3 ≤ Z-score < cutoff) for T21/T18/T13. PPV for 45,X, 47,XXY, and 47,XYY tended to be higher with the increasing Z-score, except for 47,XXX.

CONCLUSIONS

NIPS would be a valuable strategy in prenatal screening, while cautions should be kept in mind for subsequent genetic consulting about the risk of Z-score.

Non-invasive prenatal testing for the detection of trisomy 13, 18, and 21 and sex chromosome aneuploidies in 68,763 cases

Objectives: Non-invasive prenatal testing (NIPT) has been widely used in recent years. According to clinical experience from all hospitals providing prenatal screening services in Beijing, we explored the feasibility of using NIPT for the analysis of common foetal aneuploidies among pregnancies.

Methods: In total, 68,763 maternal blood samples were collected from January 2020 to December 2020 at the Beijing prenatal diagnosis agency. Cases with positive screening results by NIPT detection were validated using prenatal diagnosis.

Results: In total, 920 cases had a high-risk NIPT result, and 755 cases were shown to be truly positive by a chromosome karyotyping analysis; the prenatal diagnosis rate was 82.07% (755/920). Of the920 cases, there were 164 cases of T21, 70 cases of T18, 38 cases of T13, 360 cases of SCAs and 288 cases of other chromosomal abnormalities. The positive rates of T21, T18, T13, and SCAs were 0.24% (164/68,763), 0.10% (70/68,763), 0.06% (38/68,763) and 0.52% (360/68,763), respectively. The sensitivity and specificity were 98.17% and 99.92% for T21, 96.15% and 99.93% for T18, and 100% and 99.95% for T13, respectively. The PPVs of T21,T18,T13 and SCAs were65.24% (107/164), 35.71% (25/70), 18.42% (7/38) and 31.39% (113/360), respectively. For all indications, there were more higher T21/18/13 in the high-risk group than in the low-risk group (comprising only cases of voluntary request), with a positive rate of 0.46% vs. 0.27% (p < 0.001), sensitivity of 99.16% vs. 91.30% (p = 0.02) and PPV of 56.73%vs.32.81% (p = 0.001), but there was no significant difference in specificity between the groups (p = 0.71). The detection indication with the highest PPV (100%) by NIPT was ultrasound structural abnormalities and ultrasound soft marker abnormalities for T21 and ultrasound structural abnormalities and NT thickening for T18 and T13. The PPVs of different clinical indications of T21 (p = 0.002), T13 (p = 0.04) and SACs (p = 0.02) were statistically significant.

Conclusion: The high specificity, efficiency and safety (non-invasiveness) of NIPT can effectively improve the detection rate of common chromosomal aneuploidy, thereby reducing the occurrence of birth defects. We should encourage pregnant women with NIPT-high-risk results to undergo a prenatal diagnosis to determine whether the foetus has chromosomal abnormalities. More importantly, the screening efficiency of NIPT in the low-risk group was significantly lower than that in the high-risk group. Therefore, the use of NIPT in low-risk groups should be fully promoted, and socioeconomic benefits should be considered.

Combining Z-Score and Maternal Copy Number Variation Analysis Increases the Positive Rate and Accuracy in Non-Invasive Prenatal Testing

Objective: To evaluate positive rate and accuracy of non-invasive prenatal testing (NIPT) combining Z-score and maternal copy number variation (CNV) analysis. To assess the relationship between Z-score and positive predictive value (PPV). Methods: This prospective study included 61525 pregnancies to determine the correlation between Z-scores and PPV in NIPT, and 3184 pregnancies to perform maternal CNVs analysis. Positive results of NIPT were verified by prenatal diagnosis and/or following-up after birth. Z-score grouping, logistic regression analysis, receiver operating characteristic (ROC) curves, and S-curve trends were applied to correlation analysis of Z-scores and PPV. The maternal CNVs were classified according to the technical standard for the interpretation of ACMG. Through genetic counseling, fetal and maternal phenotypes and family histories were collected. Results: Of the 3184 pregnant women, 22 pregnancies were positive for outlier Z-scores, suggesting fetal aneuploidy. 12 out of 22 pregnancies were true positive (PPV = 54.5%). 17 pregnancies were found maternal pathogenic or likely pathogenic CNVs (> 0.5 Mb) through maternal CNV analysis. Prenatal diagnosis revealed that 7 out of 11 fetuses carried the same CNVs as the mother. Considering the abnormal biochemical indicators during pregnancy and CNV-related clinical phenotypes after birth, two male fetuses without prenatal diagnosis were suspected to carry the maternally-derived CNVs. Further, we identified three CNV-related family histories with variable phenotypes. Statistical analysis of the 61525 pregnancies revealed that Z-scores of chromosomes 21 and 18 were significantly associated with PPV at 3 ≤ Z ≤ 40. Notably, three pregnancies with Z > 40 were both maternal full aneuploidy. At Z < -3, fetuses carried microdeletions instead of monosomies. Sex chromosome trisomy was significantly higher PPV than monosomy. Conclusion: The positive rate of the NIPT screening model combining Z-score and maternal CNV analysis increased from 6.91‰ (22/3184) to 12.25‰ (39/3184) and true positives increased from 12 to 21 pregnancies. We found that this method could improve the positive rate and accuracy of NIPT for aneuploidies and CNVs without increasing testing costs. It provides an early warning for the inheritance of pathogenic CNVs to the next generation.

Non-invasive prenatal screening for foetal trisomy: An assessment of reliability and reporting

OBJECTIVE

Non-invasive prenatal screening (NIPS) has been introduced as a routine screening technique for aneuploidies in the clinic. To evaluate its reliability and reporting standardization, the National Center for Clinical Laboratories launched an external quality assessment (EQA) program based on highly simulated samples.

METHODS

Maternal and child paired cell lines were digested by enzymes to obtain DNA fragments for the analysis panel, which were composed of 5% T21, 5% T18, 10% T13, 10% euploid, and 20% T18 samples. The samples were validated and distributed to laboratories along with scenarios and questionnaires for analysis.

RESULTS

Out of 350 participating laboratories, 98.6% correctly identified all samples. The concurrence rates of laboratories for the 5% T21, 5% T18, 10% T13, 10% euploid, and 20% T18 samples were 98.9%, 99.7%, 99.7%, 100%, and 100%, respectively. Enrichment increased the foetal fraction (FF) values by 2 ∼ 3-fold, but the z scores generated by the enrichment group fluctuated greatly. Other FF estimation techniques, such as the size-based and FF-QuantSC methods, generated slightly different FF values from the chr Y-based method. Furthermore, some laboratories omitted the suggestions of results in reports.

CONCLUSIONS

The participating laboratories provided highly reliable results for samples with relatively higher FF values. However, the absence of performance validation, laboratory errors, and low FF values were potential reasons for false-negative results. In addition, enrichment operations should be validated and normalized to guarantee NIPS reproducibility, plus further efforts are required to standardize the NIPS reports.

The Optimal Cutoff Value of Z-scores Enhances the Judgment Accuracy of Noninvasive Prenatal Screening

Objective

To evaluate the accuracy of Z-scores of noninvasive prenatal screening (NIPS) in predicting 21, 18 trisomy, and X chromosome aneuploidy.

Methods

A total of 39,310 prenatal women were recruited for NIPS from September 2015 to September 2020. Interventional prenatal diagnosis was applied to verify the diagnosis of NIPS-positive results. Logistic regression analysis was employed to relate the Z-scores to the positive predictive value (PPV) of NIPS-positive results. Using receiver operating characteristic (ROC) curves, we calculated the optimal cutoff value of Z-scores to predict fetal chromosome aneuploidy. According to the cutoff value, NIPS-positive results were divided into the medium Z-value (MZ) and high Z-value (HZ) groups, and PPV was calculated to access the accuracy of Z-scores.

Results

A total of 288 effective values of Z-scores were used as the final data set. The logistics regression analysis revealed that Z-scores were significantly associated with true-positive results for 21 trisomy (T21) and 18 trisomy (T18) (P < 0.05), whereas the same was not observed for X chromosome aneuploids (P > 0.05). The optimal cutoff value of the Z-score for T21, T18, XO, XXX, and XXY indicated by ROC curve analysis were 5.79, 6.05, −9.56, 5.89, and 4.47, and the area under the curve (AUC) were 0.89, 0.80, 0.48, 0.42, and 0.45, respectively. PPV in the HZ group was higher than that in the MZ group, and the application of the cutoff value reduced the false discovery rate (FDR), which was only 2.9% in the HZ group compared with 61.1% in the MZ group for T21 and T18. The difference in total PPV between the MZ and HZ groups for X chromosome aneuploids was statistically significant. Moreover, the PPV for XXX and XXY seemed to increase with Z-scores but not for XO.

Conclusion

The Z-score is helpful for the accurate judgment of NIPS results and for clinical prenatal counseling. Especially for T21 and T18, Z-scores have an excellent clinical association, which is superior to that seen with X chromosome aneuploids. In addition, using Z-scores to judge NIPS results offers a certain reference value for XXX and XXY but not for XO.