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.