Key result
A novel computational protocol based on individual exome data showed complete concordance with the current qPCR-based testing standard for determining spinal muscular atrophy carrier status.
A novel Bayesian hierarchical model using NGS data provides a robust alternative to qPCR for determining SMA carrier status, enabling integration into large multi-gene carrier screens.
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May enable NGS integration into multi-gene carrier screening; leaves open prospective validation before clinical adoption.
BACKGROUND: Spinal muscular atrophy (SMA) is the most common pan-ethnic cause of early childhood death due to mutations in a single gene, SMN1. Most chromosome 5 homologs have a functional gene and dysfunctional copy, SMN2, with a single synonymous base substitution that results in faulty RNA splicing. However, the copy number of SMN1 and SMN2 is highly variable, and one in 60 adults worldwide are SMA carriers. Although population-wide screening is recommended, current SMA carrier tests have not been incorporated into targeted gene panels. METHODS: Here we describe a novel computational protocol for determining SMA carrier status based solely on individual exome data. Our method utilizes a Bayesian hierarchical model to quantify an individual's carrier probability given only his or her SMN1 and SMN2 reads at six loci of interest. RESULTS: We find complete concordance with results obtained with the current qPCR-based testing standard in known SMA carriers and affecteds. We applied our protocol to the phase 3 cohort of the 1,000 Genomes Project and found carrier frequencies in multiple populations consistent with the present literature. CONCLUSION: Our process is a convenient, robust alternative to qPCR, which can easily be integrated into the analysis of large multi-gene NGS carrier screens.
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Larson et al. (2015) studied Spinal muscular atrophy (SMA) carrier status (n=2,572). High resolution NGS method (Bayesian hierarchical model) vs. qPCR-based testing standard (MLPA) was evaluated on Concordance with qPCR-based testing standard in known SMA carriers and affecteds. A novel computational protocol based on individual exome data showed complete concordance with the current qPCR-based testing standard for determining spinal muscular atrophy carrier status.
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