2.5 | Interpretation of candidate genetic variants by
WES and CNVs by CMA or LD-WGS
Candidate variants were classified according to the standards and
guidelines of the American College of Medical Genetics and Genomics
(ACMG) and Association for Molecular Pathology (AMP) (Richards et al.,
2015). These guidelines recommend classifying variants into five
categories: PV, LPV, variant of uncertain significance (VUS), likely
benign variant (LBV), and benign variant (BV) based on combined lines of
weighted evidences, including population, computational, functional,
segregation, de novo , allelic, and other data. To assess the
frequency of a variant in a control or general population, we used the
KRGDB, which consists of publicly available race-matched control data
from WGS of 1100 Korean individuals, as well as other public databases
such as the 1000 Genomes Project database, ExAC database, and gnomAD. A
primary literature review was conducted using various sources cited in
the Human Gene Mutation Database (HGMD) professional version, release
2018.02 (http://www.hgmd.org/), and ClinVar
(https://www.ncbi.nlm.nih.gov/clinvar/), as well as PubMed, to determine
the potential pathogenicity of all identified variants. Various in
silico tools, including SIFT, Polyphen2, and MutationTaster, all of
which use missense prediction algorithms, were used to determine the
predicted impact of missense change.
To interpret CNVs, we used DGV (http://dgv.tcag.ca/dgv/app/home),
DECIPHER (https://decipher.sanger.ac.uk/), and dbVar
(https://www.ncbi.nlm.nih.gov/dbvar/) databases as well as OMIM
(https://www.omim.org/). In addition, the clinical findings were
compared with those reported in the literature.