Single Nucleotide Variant (SNV) analysis
Data were aligned to the hg19/GRCh37 reference genome and were quality trimmed via Ion Torrent Suite (Life Technologies). Variants were then called against the panel BED file (Ion_AmpliSeq_Inborn_Errors_of_Metabolism_v2.20160503 BED file), filtered and analyzed using the Ion Reporter Pipeline (Life Technologies). Analysis was firstly focused on 11 genes involved in MPSs and if no variant was identified, further analyses were performed on the other 583 genes associated with inborn errors of metabolism. We firstly removed intergenic, 3’/5’ UTR, non-splice related intronic variants and variants with high allele frequency (mean allele frequency >1%) in known genome reference databases including The Genome Aggregation Database (gnomAD), 1000 Genomes, 5000 Exomes, UCSC genome browser, Exome Aggregation Consortium (ExAC), dbSNP and an in-house database. The remaining variants were then classified according to the recommendations of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP)5 using VarSome (https://varsome.com/). Variants were considered putatively causal if: they were classified as pathogenic/likely pathogenic (P/LP) according to the triggered ACMG rules; or they were variants of unknown significance (VUS) in which at least half of the in-silico predictors predicted a deleterious effect. Prioritized variants in each family were individually reviewed in terms of the proband’s clinical findings and pedigree analysis to be matched to the clinically diagnosed MPS type.