Integrated Single-Strand DNA Capture and Haplotype-Guided Variant Calling Platform for Non-Invasive Prenatal Testing...

Background/Objectives: Non-invasive prenatal testing for monogenic disorders (NIPT-MD) provides a safe alternative to invasive procedures. However, its clinical utility is often limited by challenges such as low fetal fractions (FF), technical artifacts, and the difficulty in resolving maternally inherited pathogenic variants from the overwhelming background of maternal cell-free DNA (cfDNA). This study aimed to develop and validate a robust NIPT-MD platform for monogenic disorders, applicable across major common Mendelian inheritance patterns, by enhancing the accuracy of fetal variant detection in cfDNA. Methods: We developed a novel NIPT-MD platform validated using both simulated samples and a retrospective clinical cohort. The workflow involves a single-strand capture library preparation incorporating unique molecular identifiers (UMIs) to mitigate amplification artifacts. FF was precisely quantified using a fixed panel of high-minor-allele-frequency single-nucleotide polymorphisms (SNPs). Fetal genotypes were then inferred by resolving parental haplotypes through a statistical model that integrates weighting of variant allele frequency (VAF) and haplotype-informative SNP counts. Results: The single-strand capture protocol incorporating UMIs significantly reduced amplification biases. Validation of the fetal DNA fraction estimation algorithm revealed strong concordance with a Y-chromosome-derived method and expected spike-in samples. Optimization of the FF estimation panel conferred greater experimental stability. The platform reliably detected both paternally and maternally inherited pathogenic variants. In a retrospective cohort of 35 clinical cases, the NIPT-MD platform achieved high concordance with genotypes determined by invasive testing. Conclusions: These findings present an accurate and robust NIPT-MD platform for monogenic disorders, with high concordance to invasive testing validated in a retrospective cohort of 35 clinical cases. This method holds promise for clinical application in managing families at high risk of monogenic diseases.