An important factor in quality control of non-invasive prenatal screening (NIPS) or testing (NIPT) is a sufficient percentage of fetal DNA to avoid false-negative results. Here we evaluate 14,379 shallow whole-genome sequenced diagnostic NIPS samples, as well as negative controls, for both technical and biological factors that can influence fetal fraction and its assessment. Technically, bioinformatics analyses can have a profound impact on fetal fraction determination. We found best performance for fetal fraction determination with the Y chromosome based tool DEFRAG for male fetuses and the count based tool SeqFF for female fetuses. Biologically, gestational age of up to 21 weeks and maternal age had no influence on fetal fraction, while an increase in weight and BMI had a negative influence on fetal fraction. While a trend was observed, no statistically significant difference in fetal fraction was found between trisomy and normal samples. Overall, these results confirm the influence of biological factors and give insight into technical factors that can affect fetal fractions in NIPS.
Simultaneous analysis of multiple genes using next‐generation sequencing (NGS) technology has become widely available. Copy‐number variations (CNVs) in disease‐associated genes have emerged as a cause for several hereditary disorders. CNVs are, however, not routinely detected using NGS analysis. The aim of this study was to assess the diagnostic yield and the prevalence of CNVs using our panel of Hereditary Thoracic Aortic Disease (H‐TAD)‐associated genes. Eight hundred ten patients suspected of H‐TAD were analyzed by targeted NGS analysis of 21 H‐TAD associated genes. In addition, the eXome hidden Markov model (XHMM; an algorithm to identify CNVs in targeted NGS data) was used to detect CNVs in these genes. A pathogenic or likely pathogenic variant was found in 66 of 810 patients (8.1%). Of these 66 pathogenic or likely pathogenic variants, six (9.1%) were CNVs not detectable by routine NGS analysis. These CNVs were four intragenic (multi‐)exon deletions in MYLK, TGFB2, SMAD3, and PRKG1, respectively. In addition, a large duplication including NOTCH1 and a large deletion encompassing SCARF2 were detected. As confirmed by additional analyses, both CNVs indicated larger chromosomal abnormalities, which could explain the phenotype in both patients. Given the clinical relevance of the identification of a genetic cause, CNV analysis using a method such as XHMM should be incorporated into the clinical diagnostic care for H‐TAD patients.
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