Fig. 5

Frequently inconsistent MLD genotypes and estimated burden of MLD. A Summary of the genotypes whose phenotypes did not match the patient data set and were predicted incorrectly using the phenotype matrix. These genotypes manifested with multiple phenotypes within the patient data set. We considered genotypes where each mutation occurred at least five times in the overall patient data set and ignored any patient where two mutations were not identified. We then considered the predicted phenotype based on the finalized severity of each mutation. For each genotype, we counted the number of times the predicted phenotype agreed with the observed phenotype. B Classifying VUS improves the accuracy of MLD disease burden estimates using allele frequencies from multiple subpopulations in gnomAD. This is demonstrated by estimation of the burden of MLD in a bar chart including the proportion of each MLD subtype. These calculations were carried out before (light bars) and after (saturated bars) VUS were characterized for ARSA enzymatic activity in HEK293T cells. Classifying VUS decreased the number of GUS, improving the estimates of disease burden. ARSA, arylsulfatase A; gnomAD, Genome Aggregation Database; NFE, non-Finnish European; VUS, variants of unknown significance