Objective
To explore the feasibility of noninvasive prenatal diagnoses (NIPD) based on haplotype construction and Bayes factor (BF) for spinal muscular atrophy (SMA) in clinical application.
Methods
36 singleton families with pregnancy risk of SMA were recruited and all the recruited members were conducted MLPA to validate the copy number of exons 7 and 8 in SMN1 and SMN2 genes. The designed capture panel covered the entire SMN1/2 genes, including all exon and intron regions of the two genes. To ensure the NIPD accuracy, four quality control standards were set: sequencing depth, the number of informative SNPs, cell-free DNA fetal fraction, and the recombination event assessment. By enriching targeting genes and informative SNP sites in adjacent regions, the family haplotype was constructed and the fetal genotype was determined based on the dose change of the informative SNPs in cfDNA combined with BF algorithm. All NIPD results were verified by chorionic villus sampling (CVS), amniocentesis, or apoblema testing.
Results
In the 36 recruited SMA families, 34 (94.4%) families were successfully tested for NIPD, and 2 (5.56%) families could not be determined exactly because of the recombination event near the pathogenic mutations. In successful families, the earliest gestational week for NIPD was 7+ 3 weeks, and the lowest free fetal DNA fraction was 1.9%. A total of 8 affected fetuses, 6 paternal carriers, 8 maternal carriers, and 12 unaffected fetuses were detected. The consistency between NIPD results and invasive MLPA diagnosis was 100%. Four (11.1%) of the families obtained accurate results after redrawing blood samples due to low fetal fraction or insufficiency of informative SNPs. Follow-up results showed that all families with affected NIPD results underwent abortions, and the families with carrier and normal results chose to deliver the fetus.
Conclusion
NIPD is a noninvasive, high-accuracy, early pregnancy detection and cost-controllable technical method. The haplotype construction and BF analysis have considerable reliability and feasibility and could be used in the detection of other recessive monogenic diseases.