Copy-number variation and false positive prenatal aneuploidy screening results.
Ontology highlight
ABSTRACT:
SUBMITTER: Snyder MW
PROVIDER: S-EPMC4411081 | biostudies-literature | 2015 Apr
REPOSITORIES: biostudies-literature
Publications
Copy-number variation and false positive prenatal aneuploidy screening results.
Snyder Matthew W MW Simmons LaVone E LE Kitzman Jacob O JO Coe Bradley P BP Henson Jessica M JM Daza Riza M RM Eichler Evan E EE Shendure Jay J Gammill Hilary S HS
The New England journal of medicine 20150401 17
Investigations of noninvasive prenatal screening for aneuploidy by analysis of circulating cell-free DNA (cfDNA) have shown high sensitivity and specificity in both high-risk and low-risk cohorts. However, the overall low incidence of aneuploidy limits the positive predictive value of these tests. Currently, the causes of false positive results are poorly understood. We investigated four pregnancies with discordant prenatal test results and found in two cases that maternal duplications on chromo ...[more]
Similar Datasets
Project description:BACKGROUND:The noninvasive prenatal testing (NIPT) has been successfully used in the clinical screening of fetal trisomy 13, 18, and 21 in the last few years and researches on detecting sub-chromosomal copy number variations (CNVs) and monogenic diseases are also in progress. To date, multiple tests are needed in order to complete a full set of fetus disorder screening, which is costly and time consuming. Therefore, an integrated 3-in-1 NIPT approach will be in great demand by routine clinical practice in the near future. METHODS:We designed a target capture sequencing panel with an associate bioinformatics pipeline to create a novel multi-functional NIPT method and we evaluated its performance by testing 22 clinical samples containing aneuploidy, CNV, and single-gene disorder. Chromosomal aneuploidy and CNV were detected based on the Z-value approach, whereas single-gene disorder was identified by using the "pseudo-tetraploid" model to estimate the best-suited genotype for each locus. RESULTS:The performance of this newly constructed 3-in-1 system was promising. We achieved a 100% detection rate for chromosomal aneuploidies (7/7), a 100% diagnosis rate for fetus CNVs larger than 20 Mb (3/3), and an 86.4% accuracy for single-gene disorder screening (19/22). CONCLUSION:For the first time, we showed that it is possible to use just a single NIPT test to detect three distinct types of fetus disorder and laid a foundation for developing a cheaper, faster, and multi-functional NIPT method in the future.
| S-EPMC6465655 | biostudies-literature
Project description:BACKGROUND:To evaluate the impact of ultrasonography on identifying noninvasive prenatal screening (NIPS) false-negative aneuploidy. METHODS:Analysis of large population-based NIPS false-negative aneuploidy data comprising karyotypes, clinical outcomes, and ultrasound results. RESULTS:From December 2010 to July 2018, a total of 3,320,457 pregnancies were screened by NIPS performed in BGI; among them, 69 NIPS false-negative aneuploidy cases with informed consent were confirmed, and ultrasound examination data for 48 cases were not available. Of the 21 cases with ultrasound results, 19 (90.5%) had various abnormalities on ultrasound, and two (9.5%) cases were shown to be normal on ultrasound. Additionally, six of seven live-born fetuses (approximately 85.7%) were found to have abnormalities on ultrasound. Ventricular septal defects constituted the most frequently observed ultrasound abnormality type among the 21 NIPS false-negative aneuploidy cases. CONCLUSION:Application of NIPS has increased rapidly worldwide and now accounts for a large proportion of prenatal screening tests in China. This study suggests that ISUOG guideline should be followed practically, and structural abnormal ultrasound findings should not be neglected, even when NIPS produces a negative result. Combining NIPS with an ultrasound examination can further reduce the incidence of live births with aneuploidy.
| S-EPMC7284037 | biostudies-literature
Project description:BackgroundThe present study aimed to explore the etiological relationship between fetal abnormalities and copy number variations (CNVs) with the aim of intervening and preventing the birth of children with birth defects in time.MethodsSamples of 913 fetuses with puncture indications were collected from January 2017 to December 2019. Karyotype analysis and CNV sequencing (CNV-seq) testing was performed for fetuses with ultrasonic abnormalities, a high risk of Down's syndrome and an adverse birth history. All cases were followed up.ResultsIn total, 123 cases (13.47%) had abnormal karyotypes, including 109 cases with chromosome number abnormalities and 14 cases of chromosomal structural abnormalities. Thirty-seven (4.05%) cases with pathogenic CNVs were detected. The detection rate of pathogenicity CNVs was 12.82% for mixed indications, followed by 7.5% for an adverse birth history, 5.88% at high risk of non-invasive prenatal testing, 5.00% with an abnormal ultrasonic marker, 1.89% at high risk of screening for Down's syndrome and 1.45% with advanced maternal age. There were 12 (1.31%) cases with microduplications and 25 (2.74%) cases with microdeletions. Trisomy 21 (39.02%), trisomy 18 (13.82%) and Turner syndrome (9.76%) were the top three chromosome abnormalities. There were 104, 746 and 63 cases in the 11-13 weeks, 14-27 weeks 28-38 weeks gestational ages, respectively. The abnormal rates of fetal chromosome aneuploidy and the rate of pathogenic CNVs were decreased and increased with the increase of gestational age (p < 0.05), respectively.ConclusionsCompared with karyotype analysis, CNV-seq can improve the detection rate of chromosomal abnormalities. CNV-seq combined karyotype analysis should be performed simultaneously in fetuses with puncture indications.
| S-EPMC8243933 | biostudies-literature
Project description:Newborn screening (NBS) for inborn metabolic disorders is a highly successful public health program that by design is accompanied by false-positive results. Here we trained a Random Forest machine learning classifier on screening data to improve prediction of true and false positives. Data included 39 metabolic analytes detected by tandem mass spectrometry and clinical variables such as gestational age and birth weight. Analytical performance was evaluated for a cohort of 2777 screen positives reported by the California NBS program, which consisted of 235 confirmed cases and 2542 false positives for one of four disorders: glutaric acidemia type 1 (GA-1), methylmalonic acidemia (MMA), ornithine transcarbamylase deficiency (OTCD), and very long-chain acyl-CoA dehydrogenase deficiency (VLCADD). Without changing the sensitivity to detect these disorders in screening, Random Forest-based analysis of all metabolites reduced the number of false positives for GA-1 by 89%, for MMA by 45%, for OTCD by 98%, and for VLCADD by 2%. All primary disease markers and previously reported analytes such as methionine for MMA and OTCD were among the top-ranked analytes. Random Forest's ability to classify GA-1 false positives was found similar to results obtained using Clinical Laboratory Integrated Reports (CLIR). We developed an online Random Forest tool for interpretive analysis of increasingly complex data from newborn screening.
| S-EPMC7080200 | biostudies-literature
Project description: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.
| S-EPMC9201951 | biostudies-literature
Project description:MotivationCopy number variation (CNV) is a type of structural variation, usually defined as genomic segments that are 1?kb or larger, which present variable copy numbers when compared with a reference genome. The screening and ranking algorithm (SaRa) was recently proposed as an efficient approach for multiple change-points detection, which can be applied to CNV detection. However, some practical issues arise from application of SaRa to single nucleotide polymorphism data.ResultsIn this study, we propose a modified SaRa on CNV detection to address these issues. First, we use the quantile normalization on the original intensities to guarantee that the normal mean model-based SaRa is a robust method. Second, a novel normal mixture model coupled with a modified Bayesian information criterion is proposed for candidate change-point selection and further clustering the potential CNV segments to copy number states. Simulations revealed that the modified SaRa became a robust method for identifying change-points and achieved better performance than the circular binary segmentation (CBS) method. By applying the modified SaRa to real data from the HapMap project, we illustrated its performance on detecting CNV segments. In conclusion, our modified SaRa method improves SaRa theoretically and numerically, for identifying CNVs with high-throughput genotyping data.Availability and implementationThe modSaRa package is implemented in R program and freely available at http://c2s2.yale.edu/software/modSaRa.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4410664 | biostudies-literature
Project description:OBJECTIVES: As more families participate expanded newborn screening for metabolic disorders in China, the overall number of false positives increases. Our goal was to assess the potential impact on parental stress, perceptions of the child's health, and family relationships. METHODS: Parents of 49 infants with false-positive screening results for metabolic disorders in the expanded newborn screening panel were compared with parents of 42 children with normal screening results. Parents first completed structured interview using likert scales, closed and open questions. Parents also completed the parenting stress index. RESULTS: A total of 88 mothers and 41 fathers were interviewed. More mothers in the false-positive group reported that their children required extra parental care (21%), compared with 5% of mothers in the normal-screened group (P<0.001). 39% of mothers in the false-positive group reported that they worry about their child's future development, compared with 10% of mothers in the normal-screened group (P<0.001). Fathers in the false-positive group did not differ from fathers in the normal-screened group in reporting worry about their child's extra care requirements, and their child's future development. Children with false-positive results compared with children with normal results were triple as likely to experience hospitalization (27%vs 9%, respectively; P<0.001). CONCLUSIONS: The results showing false-positive screening results may affect parental stress and the parent-child relationship. Parental stress and anxiety can be reduced with improved education and communication to parents about false-positive results.
| S-EPMC3338668 | biostudies-other
Project description:BackgroundWe aimed to evaluate the clinical value of copy number variation-sequencing (CNV-Seq) in combination with cytogenetic karyotyping in prenatal diagnosis.MethodsCNV-Seq and cytogenetic karyotyping were performed in parallel for 9452 prenatal samples for comparison of the diagnostic performance of the two methods, and to evaluate the screening performance of maternal age, maternal serum screening, fetal ultrasound scanning and noninvasive prenatal testing (NIPT) for fetal pathogenic copy number variation (CNV).ResultsAmong the 9452 prenatal samples, traditional karyotyping detected 704 cases (7.5%) of abnormal cytogenetic karyotypes, 171 (1.8%) chromosome polymorphism, 20 (0.2%) subtle structural variations, 74 (0.7%) mutual translocation (possibly balanced), 52 (0.6%) without karyotyping results, and 8431 (89.2%) normal cytogenetic karyotypes. Among the 8705 cases with normal karyotype, polymorphism, mutual translocation, or marker chromosome, CNV-Seq detected 63 cases (0.7%) of pathogenic chromosome microdeletion/duplication. Retrospectively, noninvasive prenatal testing (NIPT) had high sensitivity and specificity for the screening of fetal pathogenic CNV, and NIPT combining with maternal age, maternal serum screening or fetal ultrasound scanning, which improved the screening performance.ConclusionThe combined application of cytogenetic karyotyping and CNV-Seq significantly improved the detection rate of fetal pathogenic chromosome microdeletion/duplication. NIPT was recommended for the screening of pathogenic chromosome microdeletion/duplication, and NIPT combining with other screening methods further improved the screening performance for pathogenic fetal CNV.
| S-EPMC8265053 | biostudies-literature
Project description:BACKGROUND: Copy number variations (CNVs) represent a significant source of genomic structural variation. Their length ranges from approximately one hundred to millions of base pair. Genome-wide screenings have clarified that CNVs are a ubiquitous phenomenon affecting essentially the whole genome. Although Bos taurus is one of the most important domestic animal species worldwide and one of the most studied ruminant models for metabolism, reproduction, and disease, relatively few studies have investigated CNVs in cattle and little is known about how CNVs contribute to normal phenotypic variation and to disease susceptibility in this species, compared to humans and other model organisms. RESULTS: Here we characterize and compare CNV profiles in 2654 animals from five dairy and beef Bos taurus breeds, using the Illumina BovineSNP50 genotyping array (54001 SNP probes). In this study we applied the two most commonly used algorithms for CNV discovery (QuantiSNP and PennCNV) and identified 4830 unique candidate CNVs belonging to 326 regions. These regions overlap with 5789 known genes, 76.7% of which are significantly co-localized with segmental duplications (SD). CONCLUSIONS: This large scale screening significantly contributes to the enrichment of the Bos taurus CNV map, demonstrates the ubiquity, great diversity and complexity of this type of genomic variation and sets the basis for testing the influence of CNVs on Bos taurus complex functional and production traits.
| S-EPMC3618309 | biostudies-literature
Project description:Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data. Due to the high level of noise and biases of read-count data and complexity of the WES data, existing CNV detection tools identify many false CNV segments. Besides, NGS generates a huge amount of data, requiring to use effective and efficient methods. In this work, we propose a novel segmentation algorithm based on the total variation approach to detect CNVs more precisely and efficiently using WES data. The proposed method also filters out outlier read-counts and identifies significant change points to reduce false positives. We used real and simulated data to evaluate the performance of the proposed method and compare its performance with those of other commonly used CNV detection methods. Using simulated and real data, we show that the proposed method outperforms the existing CNV detection methods in terms of accuracy and false discovery rate and has a faster runtime compared to the circular binary segmentation method.
| S-EPMC7278034 | biostudies-literature