4.4 Article

A randomized and blinded comparison of qPCR and NGS-based detection of aneuploidy in a cell line mixture model of blastocyst biopsy mosaicism

Journal

JOURNAL OF ASSISTED REPRODUCTION AND GENETICS
Volume 33, Issue 11, Pages 1473-1480

Publisher

SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10815-016-0784-3

Keywords

Comprehensive chromosome screening; Whole genome amplification; Next-generation sequencing; Quantiative real time PCR; Mosaicism

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A subset of preimplantation stage embryos may possess mosaicism of chromosomal constitution, representing a possible limitation to the clinical predictive value of comprehensive chromosome screening (CCS) from a single biopsy. However, contemporary methods of CCS may be capable of predicting mosaicism in the blastocyst by detecting intermediate levels of aneuploidy within a trophectoderm biopsy. This study evaluates the sensitivity and specificity of aneuploidy detection by two CCS platforms using a cell line mixture model of a mosaic trophectoderm biopsy. Four cell lines with known karyotypes were obtained and mixed together at specific ratios of six total cells (0:6, 1:5, 2:4, 3:3, 4:2, 5:1, and 6:0). A female euploid and a male trisomy 18 cell line were used for one set, and a male trisomy 13 and a male trisomy 15 cell line were used for another. Replicates of each mixture were prepared, randomized, and blinded for analysis by one of two CCS platforms (quantitative polymerase chain reaction (qPCR) or VeriSeq next-generation sequencing (NGS)). Sensitivity and specificity of aneuploidy detection at each level of mosaicism was determined and compared between platforms. With the default settings for each platform, the sensitivity of qPCR and NGS were not statistically different, and 100 % specificity was observed (no false positives) at all levels of mosaicism. However, the use of previously published custom criteria for NGS increased sensitivity but also significantly decreased specificity (33 % false-positive prediction of aneuploidy). By demonstrating increased false-positive diagnoses when reducing the stringency of predicting an abnormality, these data illustrate the importance of preclinical evaluation of new testing paradigms before clinical implementation.

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