Dataset Information

Effective noninvasive zygosity determination by maternal plasma target region sequencing.

ABSTRACT:

Background

Currently very few noninvasive molecular genetic approaches are available to determine zygosity for twin pregnancies in clinical laboratories. This study aimed to develop a novel method to determine zygosity by using maternal plasma target region sequencing.

Methods

We constructed a statistic model to calculate the possibility of each zygosity type using likelihood ratios ( Li ) and empirical dynamic thresholds targeting at 4,524 single nucleotide polymorphisms (SNPs) loci on 22 autosomes. Then two dizygotic (DZ) twin pregnancies,two monozygotic (MZ) twin pregnancies and two singletons were recruited to evaluate the performance of our novel method. Finally we estimated the sensitivity and specificity of the model in silico under different cell-free fetal DNA (cff-DNA) concentration and sequence depth.

Results/conclusions

We obtained 8.90 Gbp sequencing data on average for six clinical samples. Two samples were classified as DZ with L values of 1.891 and 1.554, higher than the dynamic DZ cut-off values of 1.162 and 1.172, respectively. Another two samples were judged as MZ with 0.763 and 0.784 of L values, lower than the MZ cut-off values of 0.903 and 0.918. And the rest two singleton samples were regarded as MZ twins, with L values of 0.639 and 0.757, lower than the MZ cut-off values of 0.921 and 0.799. In silico, the estimated sensitivity of our noninvasive zygosity determination was 99.90% under 10% total cff-DNA concentration with 2 Gbp sequence data. As the cff-DNA concentration increased to 15%, the specificity was as high as 97% with 3.50 Gbp sequence data, much higher than 80% with 10% cff-DNA concentration.

Significance

This study presents the feasibility to noninvasively determine zygosity of twin pregnancy using target region sequencing, and illustrates the sensitivity and specificity under various detecting condition. Our method can act as an alternative approach for zygosity determination of twin pregnancies in clinical practice.

SUBMITTER: Zheng J

PROVIDER: S-EPMC3677919 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Effective noninvasive zygosity determination by maternal plasma target region sequencing.

Zheng Jing J Xu Chenming C Guo Jing J Wei Yuan Y Ge Huijuan H Li Xuchao X Zhang Chunlei C Jiang Haojun H Pan Ling L Tang Weiping W Xie Weiwei W Zhang Hongyun H Zhao Yangyu Y Jiang Fuman F Chen Shengpei S Wang Wei W Xu Xun X Chen Fang F Huang Hefeng H Jiang Hui H

PloS one 20130610 6

<h4>Background</h4>Currently very few noninvasive molecular genetic approaches are available to determine zygosity for twin pregnancies in clinical laboratories. This study aimed to develop a novel method to determine zygosity by using maternal plasma target region sequencing.<h4>Methods</h4>We constructed a statistic model to calculate the possibility of each zygosity type using likelihood ratios ( Li ) and empirical dynamic thresholds targeting at 4,524 single nucleotide polymorphisms (SNPs) l ...[more]

PMID: 23762285

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Project description:Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types. Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables. Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11-96.79%) and specificity of 80% (95% CI, 72.41-88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively. Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.

Project description:BackgroundPlasma DNA obtained from a pregnant woman contains a mixture of maternal and fetal DNA. The fetal DNA proportion in maternal plasma is relatively consistent as determined using polymorphic genetic markers across different chromosomes in euploid pregnancies. For aneuploid pregnancies, the observed fetal DNA proportion measured using polymorphic genetic markers for the aneuploid chromosome would be perturbed. In this study, we investigated the feasibility of analyzing single nucleotide polymorphisms using targeted massively parallel sequencing to detect such perturbations in mothers carrying trisomy 21 fetuses.Methodology/principal findingsDNA was extracted from plasma samples collected from fourteen pregnant women carrying singleton fetuses. Hybridization-based targeted sequencing was used to enrich 2 906 single nucleotide polymorphism loci on chr7, chr13, chr18 and chr21. Plasma DNA libraries with and without target enrichment were analyzed by massively parallel sequencing. Genomic DNA samples of both the mother and fetus for each case were genotyped by single nucleotide polymorphism microarray analysis. For the targeted regions, the mean sequencing depth of the enriched samples was 225-fold higher than that of the non-enriched samples. From the targeted sequencing data, the ratio between fetus-specific and shared alleles increased by approximately 2-fold on chr21 in the paternally-derived trisomy 21 case. In comparison, the ratio is decreased by approximately 11% on chr21 in the maternally-derived trisomy 21 cases but with much overlap with the ratio of the euploid cases. Computer simulation revealed the relationship between the fetal DNA proportion, the number of informative alleles and the depth of sequencing.Conclusions/significanceTargeted massively parallel sequencing of single nucleotide polymorphism loci in maternal plasma DNA is a potential approach for trisomy 21 detection. However, the method appears to be less robust than approaches using non-polymorphism-based counting of sequence tags in plasma.

Dataset Information

Effective noninvasive zygosity determination by maternal plasma target region sequencing.

Background

Methods

Results/conclusions

Significance

Publications

Effective noninvasive zygosity determination by maternal plasma target region sequencing.

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