Current non-invasive prenatal screening is targeted toward the detection of chromosomal abnormalities in the fetus1,2. However, screening for many dominant monogenic disorders associated with de novo mutations is not available, despite their relatively high incidence3. Here we report on the development and validation of, and early clinical experience with, a new approach for non-invasive prenatal sequencing for a panel of causative genes for frequent dominant monogenic diseases. Cell-free DNA (cfDNA) extracted from maternal plasma was barcoded, enriched, and then analyzed by next-generation sequencing (NGS) for targeted regions. Low-level fetal variants were identified by a statistical analysis adjusted for NGS read count and fetal fraction. Pathogenic or likely pathogenic variants were confirmed by a secondary amplicon-based test on cfDNA. Clinical tests were performed on 422 pregnancies with or without abnormal ultrasound findings or family history. Follow-up studies on cases with available outcome results confirmed 20 true-positive, 127 true-negative, zero false-positive, and zero-false negative results. The initial clinical study demonstrated that this non-invasive test can provide valuable molecular information for the detection of a wide spectrum of dominant monogenic diseases, complementing current screening for aneuploidies or carrier screening for recessive disorders.
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The customized script for the UMI-based deduplication of the NGS reads can be found at https://sourceforge.net/projects/BGNIPS.
These authors declare that all essential data supporting the conclusion of the study as well as detailed assay protocols, analytical algorithms, and customized computational codes are within the paper and supplementary materials. All the disease-causing variants and the key phenotypes found in the subjects can be found at the ClinVar database (http://www.ncbi.nlm.nih.gov/clinvar/variation/) with accession numbers SCV000854595–SCV000854628. Subjects’ identifiable information (including their genomic sequencing data) is kept in our clinical laboratory, which is a CLIA and CAP certified laboratory and a HIPAA-compliant environment, to protect subjects’ privacy. Non-identifiable sequencing data (for example, individual variant sequencing data generated by locus-specific sequencing) can be provided on request from the authors. Source data for Fig. 1 and Extended Data Figs. 1 and 2 are available online.
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Baylor Genetics Laboratories and Baylor College of Medicine provided funds to support this study. A.K.M. was supported by institutional funds from Baylor College of Medicine. K.W.C. was partially supported by Vice-Chancellor Discretionary Fund for CUHK-Baylor College of Medicine Joint Centre for Medical Genetics. We thank all contributing healthcare providers for their work and support on this study.