scholarly journals Origin of false positives and false negatives in non-invasive preimplantation genetic testing for aneuploidies

2018 ◽  
Vol 110 (4) ◽  
pp. e412
Author(s):  
C. Rubio Lluesa ◽  
L.F. Rienzi ◽  
L. Navarro Sanchez ◽  
D. Cimadomo ◽  
C.M. Garcia-Pascual ◽  
...  
2019 ◽  
Vol 38 ◽  
pp. e41-e42
Author(s):  
Kuznyetsov Valeriy ◽  
Madjunkova Svetlana ◽  
Antes Ran ◽  
Abramov Rina ◽  
Motamedi Gelareh ◽  
...  

2020 ◽  
Vol 114 (3) ◽  
pp. e425
Author(s):  
Meir Olcha ◽  
Manar Elzaky ◽  
Malgorzata Jaremko ◽  
Zaher Merhi ◽  
John J. Zhang

2019 ◽  
Vol 26 (1) ◽  
pp. 16-42 ◽  
Author(s):  
Megan Leaver ◽  
Dagan Wells

Abstract BACKGROUND Preimplantation genetic testing (PGT) encompasses methods that allow embryos to be tested for severe inherited conditions or for chromosome abnormalities, relevant to embryo health and viability. In order to obtain embryonic genetic material for analysis, a biopsy is required, involving the removal of one or more cells. This invasive procedure greatly increases the costs of PGT and there have been concerns that embryo viability could be compromised in some cases. The recent discovery of DNA within the blastocoele fluid (BF) of blastocysts and in spent embryo culture media (SCM) has led to interest in the development of non-invasive methods of PGT (niPGT). OBJECTIVE AND RATIONALE This review evaluates the current scientific evidence regarding non-invasive genetic assessment of preimplantation embryos. The success of different PGT methodologies in collecting and analysing extra-embryonic DNA is evaluated, and consideration is given to the potential biological and technical hindrances to obtaining a reliable clinical diagnosis. SEARCH METHODS Original research and review papers concerning niPGT were sourced by searching PubMed and Google Scholar databases until July 2019. Searches comprised the keywords: ‘non-invasive’; ‘cell-free DNA’; ‘blastocentesis’; ‘blastocoel fluid’; ‘spent culture media’; ‘embryo culture medium’; ‘preimplantation genetic testing’; ‘preimplantation genetic diagnosis’; ‘preimplantation genetic screening’; and ‘aneuploidy’. OUTCOMES Embryonic DNA is frequently detectable in BF and SCM of embryos produced during IVF treatment. Initial studies have achieved some success when performing cytogenetic and molecular genetic analysis. However, in many cases, the efficiency has been restricted by technical complications associated with the low quantity and quality of the DNA. Reported levels of ploidy agreement between SCM/BF samples and biopsied embryonic cells vary widely. In some cases, a discrepancy with respect to cytogenetic data obtained after trophectoderm biopsy may be attributable to embryonic mosaicism or DNA contamination (usually of maternal origin). Some research indicates that aneuploid cells are preferentially eliminated from the embryo, suggesting that their DNA might be over-represented in SCM and BF samples; this hypothesis requires further investigation. WIDER IMPLICATIONS Available data suggest that BF and SCM samples frequently provide DNA templates suitable for genetic analyses, offering a potential means of PGT that is less expensive than traditional methods, requires less micromanipulation skill and poses a lower risk to embryos. Critically, DNA isolation and amplification protocols must be optimised to reproducibly obtain an accurate clinical diagnosis, whilst minimising the impact of confounding factors such as contamination. Further investigations are required to understand the mechanisms underlying the release of embryonic DNA and to determine the extent to which this material reflects the true genetic status of the corresponding embryo. Currently, the clinic al potential of niPGT remains unknown.


2021 ◽  
Vol 116 (3) ◽  
pp. e393-e394
Author(s):  
Jacob Meyers ◽  
Julie Laliberte ◽  
Nao Yasuyama ◽  
Jay Kim ◽  
Karthik Padmanabhan ◽  
...  

2017 ◽  
Author(s):  
Jianfeng Yang ◽  
Xiaofan Ding ◽  
Weidong Zhu

AbstractWith the advance of next-generation sequencing technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal blood. Although Z test is widely used in NIPT nowadays, there is still necessity to improve its accuracy for removing a) false negatives and false positives, and b) the ratio of unclassified data, so as to reduce the potential harm to patients caused by these inaccuracies as well as the induced cost of retests.Employing multiple Z tests with machine-learning algorithm could provide a better prediction on NIPT data. Combining the multiple Z values with indexes of clinical signs and quality control, features were collected from the known samples and scaled for model training in support vector machine (SVM) discrimination. The trained model was applied to predict the unknown samples, which showed significant improvement. In 4752 qualified NIPT data, our method reached 100% accuracies on all three chromosomes, including 151 data that were grouped as unclassified by one-Z-value based method. Moreover, four false positives and four false negatives were corrected by using this machine-learning model.To our knowledge, this is the first study to employ support vector machine in NIPT data analysis. It is expected to replace the current one-Z-value based NIPT analysis in clinical use.


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