Predicting disease severity in metachromatic leukodystrophy using protein activity and a patient phenotype matrix.

BACKGROUND: Metachromatic leukodystrophy (MLD) is a lysosomal storage disorder caused by mutations in the arylsulfatase A gene (ARSA) and categorized into three subtypes according to age of onset. The functional effect of most ARSA mutants remains unknown; better understanding of the genotype-phenotype relationship is required to support newborn screening (NBS) and guide treatment. RESULTS: We collected a patient data set from the literature that relates disease severity to ARSA genotype in 489 individuals with MLD. Patient-based data were used to develop a phenotype matrix that predicts MLD phenotype given ARSA alleles in a patient's genotype with 76% accuracy. We then employed a high-throughput enzyme activity assay using mass spectrometry to explore the function of ARSA variants from the curated patient data set and the Genome Aggregation Database (gnomAD). We observed evidence that 36% of variants of unknown significance (VUS) in ARSA may be pathogenic. By classifying functional effects for 251 VUS from gnomAD, we reduced the incidence of genotypes of unknown significance (GUS) by over 98.5% in the overall population. CONCLUSIONS: These results provide an additional tool for clinicians to anticipate the disease course in MLD patients, identifying individuals at high risk of severe disease to support treatment access. Our results suggest that more than 1 in 3 VUS in ARSA may be pathogenic. We show that combining genetic and biochemical information increases diagnostic yield. Our strategy may apply to other recessive diseases, providing a tool to address the challenge of interpreting VUS within genotype-phenotype relationships and NBS.

First-Tier Next Generation Sequencing for Newborn Screening: An Important Role for Biochemical Second-Tier Testing.

There is discussion of expanding newborn screening (NBS) through the use of genomic sequence data; yet, challenges remain in the interpretation of DNA variants. Population-level DNA variant databases are available, and it is possible to estimate the number of newborns who would be flagged as having a risk for a genetic disease (including rare variants of unknown significance, VUS) via next-generation sequencing (NGS) positive. Estimates of the number of newborns screened as NGS positive for monogenic recessive diseases were obtained by analysis of the Genome Aggregation Database (gnomAD). For a collection of diseases for which there is interest in NBS, we provided 2 estimates for the expected number of newborns screened as NGS positive. For a set of lysosomal storage diseases, we estimated that 100 to approximately 600 NGS screen positives would be found per disease per year in a large NBS laboratory (California), and this figure may be expected to rise to a limit of about 1000 if we account for the fact that gnomAD does not contain all worldwide variants. The number of positives would drop 2.5- to 10-fold if the 10 VUS with highest allele frequency were biochemically annotated as benign. It is proposed that a second-tier biochemical assay using the same dried blood spot could be carried out as a filter and as part of NBS to reduce the number of high-risk NGS positive newborns to a manageable number.