Proband-independent noninvasive prenatal diagnosis for spinal muscular atrophy: early detection paving the way for early prenatal treatment
Abstract
To validate the clinical efficacy of non-invasive prenatal diagnosis (NIPD) for spinal muscular atrophy (SMA) in the first trimester and extend its applicability to families without probands. From December 2020 to October 2024, 288 high-risk pregnancies were recruited prospectively, with 81 qualifying for NIPD after genetic counseling. Among the eligible cases, parent-based haplotypes were successfully constructed in 75 families (92.6%), while grandparent-based haplotype reconstruction was performed for the remaining 6 cases (7.4%) where proband samples were unavailable. Through targeted sequencing of the SMN1/SMN2 gene and flanking informative SNPs in maternal plasma, fetal haplotypes were inferred by analyzing dosage changes in cell-free DNA (cfDNA) using Bayes factor. All NIPD results were subsequently validated through invasive diagnostic procedures (chorionic villus sampling or amniocentesis). The haplotypes were successfully constructed in 81 families through parents or grandparents of the identified variant carriers. 76 families (93.8%) successfully obtained NIPD results, among which the earliest gestational week for successful NIPD was 7+3 weeks, with a minimum fetal fraction of 1.9%. 5 cases were classified ‘no call’ results due to pathogenic variant-adjacent recombination events (2/5), insufficient or unevenly distributed informative SNPs (2/5), and subthreshold fetal fraction (1/5). The average gestational age of NIPD blood drawing is 9 weeks. Validation test showed the NIPD results accuracy was 100%. This study demonstrates the clinical feasibility of grandparent-assisted haplotype construction for SMA families without probands and enables accurate early prenatal diagnosis of SMA in first-trimester pregnancies.
Fields of Study & Subjects
Neurogenetic and Muscular Disorders Research
Prenatal Screening and Diagnostics
Fetal and Pediatric Neurological Disorders
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026