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Consequences of insufficient data quality in prenatal testing
The application of NGS technology to prenatal testing is the moststriking and potentially valuable example of the role NGS may playin the near future. However, the application of NGS technology forCAs screening will inevitably be associated with certain limitations.In particular, in the absence of verification tests, the results of NGSresults are likely to be incomplete. For example, in China, some somemicroarrays (such as SNP microarrays) have been used to check thediagnostic results of NGS. However, these microarrays are unableto determine whether the results are correct or not. Some studies haveargued that the quality of data generated by NGS is not sufficiently high(2,19-21).
For prenatal testing, the quality of the sequencing data isimportant. If the data quality is poor, the identification rate of CAsis likely to be low, and testing will be performed to confirmwhether the fetus is alive. Furthermore, the test result itself must beaccurate. Even if NGS is used to investigate possible CAs, therates of false positives and false negatives are relatively high. Theseand other limitations of NGS technology are likely to continue toexist. It is likely that the cost of sequencing will continue to drop,and it is possible that this will lead to an increasing number ofpublication of studies using low-cost NGS to screen for CAs. However,the majority of these studies will still require confirmation testingwith the conventional methods mentioned above. This is likely to happenin the future because low-coverage NGS, even if it is used for CAscreening, still has inferior sensitivity and specificity compared tomicroarray-based assays (2,17). Thus, it is critical to enhance the performance of diagnostic technologies by developing a new generation of CA screening technology, based on the analysis of a sufficient number of sequencevariants, using inexpensive and high-throughput NGS methods.
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