Correlation between Z score, fetal fraction, and sequencing reads in non-invasive prenatal testing

2017 ◽  
Vol 37 (9) ◽  
pp. 943-945 ◽  
Author(s):  
Marie Balslev-Harder ◽  
Stine R. Richter ◽  
Susanne Kjaergaard ◽  
Peter Johansen
Keyword(s):  
Prenatal Testing ◽  
Z Score ◽  
Non Invasive ◽  
Fetal Fraction

scholarly journals Combination of Fetal Fraction Estimators Based on Fragment Lengths and Fragment Counts in Non-Invasive Prenatal Testing

2019 ◽  
Vol 20 (16) ◽  
pp. 3959 ◽  
Author(s):  
Juraj Gazdarica ◽  
Rastislav Hekel ◽  
Jaroslav Budis ◽  
Marcel Kucharik ◽  
Frantisek Duris ◽  
...  
Keyword(s):  
State Of The Art ◽  
Prenatal Testing ◽  
The State ◽  
Accurate Estimation ◽  
Special Focus ◽  
Dna Fragments ◽  
Sources Of Information ◽  
Non Invasive ◽  
Genomic Locations ◽  
Fetal Fraction

The reliability of non-invasive prenatal testing is highly dependent on accurate estimation of fetal fraction. Several methods have been proposed up to date, utilizing different attributes of analyzed genomic material, for example length and genomic location of sequenced DNA fragments. These two sources of information are relatively unrelated, but so far, there have been no published attempts to combine them to get an improved predictor. We collected 2454 single euploid male fetus samples from women undergoing NIPT testing. Fetal fractions were calculated using several proposed predictors and the state-of-the-art SeqFF method. Predictions were compared with the reference Y-based method. We demonstrate that prediction based on length of sequenced DNA fragments may achieve nearly the same precision as the state-of-the-art methods based on their genomic locations. We also show that combination of several sample attributes leads to a predictor that has superior prediction accuracy over any single approach. Finally, appropriate weighting of samples in the training process may achieve higher accuracy for samples with low fetal fraction and so allow more reliability for subsequent testing for genomic aberrations. We propose several improvements in fetal fraction estimation with a special focus on the samples most prone to wrong conclusion.

scholarly journals Lipid Metabolism Affects Fetal Fraction and Screen Failures in Non-invasive Prenatal Testing

2022 ◽  
Vol 8 ◽  
Author(s):  
Jun Cao ◽  
Longwei Qiao ◽  
Jieyu Jin ◽  
Sheng Zhang ◽  
Ping Chen ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Pregnant Women ◽  
Serum Lipid ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Density Lipoprotein ◽  
Prenatal Testing ◽  
Lipoprotein Cholesterol ◽  
Non Invasive ◽  
Fetal Fraction

Objective: To assess the association between lipid metabolism and fetal fraction, which is a critical factor in ensuring a highly accurate non-invasive prenatal testing (NIPT), and on the rate of screen failures or “no calls” in NIPT.Methods: A total of 4,514 pregnant women at 12–26 weeks of gestation underwent NIPT sequencing and serum lipid measurements. Univariate analysis and multivariate regression models were used to evaluate the associations of serum lipid concentrations with the fetal fraction and the rate of screen failures.Results: The fetal fraction decreased with increased low-density lipoprotein cholesterol and triglyceride (TG) levels, which were significant factors (standardized coefficient: −0.11). Conversely, high-density lipoprotein cholesterol and the interval between the two tests were positively correlated with the fetal fraction. The median fetal fraction was 10.88% (interquartile range, 8.28–13.89%) and this decreased with TG from 11.56% at ≤1.10 mmol/L to 9.51% at >2.30 mmol/L. Meanwhile, multivariate logistic regression analysis revealed that increased TG levels were independently associated with the risk of screen failures. The rate of screen failures showed an increase with TG levels from 1.20% at ≤1.70 mmol/L to 2.41% at >2.30 mmol/L.Conclusions: The fetal fraction and the rate of screen failures in NIPT are affected by TG levels. Meanwhile, in pregnant women with high TG levels, delaying the time between NIPT blood collections can significantly increase the fetal fraction.

scholarly journals Non-invasive prenatal testing by low coverage genomic sequencing: Detection limits of screened chromosomal microdeletions

2019 ◽  
Author(s):  
Marcel Kucharik ◽  
Andrej Gnip ◽  
Michaela Hyblova ◽  
Jaroslav Budis ◽  
Lucia Strieskova ◽  
...  
Keyword(s):  
In Silico ◽  
Detection Limits ◽  
Prenatal Testing ◽  
Systematic Evaluation ◽  
Whole Genome Sequencing Data ◽  
Detection Accuracy ◽  
Sequencing Data ◽  
Non Invasive ◽  
Microdeletion Syndromes ◽  
Fetal Fraction

AbstractObjectiveTo study the detection limits of chromosomal microaberrations in non-invasive prenatal testing with aim for five target microdeletion syndromes, including DiGeorge, Prader-Willi/Angelman, 1p36, Cri-Du-Chat, and Wolf-Hirschhorn syndromes.MethodWe used known cases of pathogenic deletions from ISCA database to specifically define regions critical for the target syndromes. Our approach to detect microdeletions, from whole genome sequencing data, is based on sample normalization and read counting for individual bins. We performed both an in-silico study using artificially created data sets and a laboratory test on mixed DNA samples, with known microdeletions, to assess the sensitivity of prediction for varying fetal fractions, deletion lengths, and sequencing read counts.ResultsThe in-silico study showed sensitivity of 79.3% for 10% fetal fraction with 20M read count, which further increased to 98.4% if we searched only for deletions longer than 3Mb. The test on laboratory-prepared mixed samples was in agreement with in-silico results, while we were able to correctly detect 24 out of 29 control samples.ConclusionOur results suggest that it is possible to incorporate microaberration detection into basic NIPT as part of the offered screening/diagnostics procedure, however, accuracy and reliability depends on several specific factors.What’s already known about this topic?Microdeletion detection accuracy, similarly to most common trisomies detection, was found to be dependent mostly on technical and biological parameters of the test and tested samples, such as coverage of target region, fetal fraction, size and positions of the deletions.What does this study add?Estimation of relevant regions for five chosen microdeletion syndromes. Confirmation and improvement upon previous methods. Systematic evaluation of sensitivity of microdeletion detection with read counts from 10M to 20M.

scholarly journals Calculation of Fetal Fraction for Non-Invasive Prenatal Testing

BioTech ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 17
Author(s):  
Matthew Cserhati
Keyword(s):  
Length Distribution ◽  
Prenatal Testing ◽  
Estimation Methods ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Main Method ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
The Difference ◽  
Fetal Fraction

Estimating the fetal fraction of DNA in a pregnant mother’s blood is a risk-free, non-invasive way of predicting fetal aneuploidy. It is a rapidly developing field of study, offering researchers a plethora of different complementary methods. Such methods include examining the differences in methylation profiles between the fetus and the mother. Others include calculating the average allele frequency based on the difference in genotype of a number of single-nucleotide polymorphisms. Differences in the length distribution of DNA fragments between the mother and the fetus as well as measuring the proportion of DNA reads mapping to the Y chromosome also constitute fetal fraction estimation methods. The advantages and disadvantages of each of these main method types are discussed. Moreover, several well-known fetal fraction estimation methods, such as SeqFF, are described and compared with other methods. These methods are amenable to not only the estimation of fetal fraction but also paternity, cancer, and transplantation monitoring studies. NIPT is safe, and should aneuploidy be detected, this information can help parents prepare mentally and emotionally for the birth of a special needs child.

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