Suzanne de Bruijn

50 Chapter 1.2 In 2015, the American College of Medical Genetics (ACMG) provided a framework that shouldutilize and standardize sequence variant interpretation forMendeliandisorders. 84 Each variant is categorized using a uniform scoring system: benign, likely benign, uncertain significance, likely pathogenic, or pathogenic. The classification system employs several hierarchical steps which include the use of literature and databases, computational and predictive data, functional data, and segregation analysis. Variant classification is the cornerstone of clinical molecular genetic testing. Therefore, the ACMG guidelines provide a consistent and well applicable system to guide this process. On the other hand, for research focused on the identification of novel gene-disease associations, the ACMG guidelines are more difficult to apply and less suitable. Literature and database use Variant frequency databases are useful resources for allele frequencies of variants in large populations. As a rule of thumb, the frequency of a disease-causing variant should not be higher than expected based on the incidence or prevalence of the genetic disorder. 85 The most comprehensive allele frequency database today is gnomAD (successor of ExAC), which contains frequency data for both SNVs and SVs based on 91,864 genomes and 125,748 exomes. 86 Additionally, this database provides variant frequencies for many subpopulations, which allows the usage of population-matched control data. Nevertheless, some populations (e.g. African/African-American) remain underrepresented which limits efforts in precision and personalized medicine for these ethnicities. Several efforts are ongoing to obtain more (high-quality) genomes from these populations. 87,88 Databases such as gnomAD 86 , goNL 89 , UK10K 90 and Wellderly 91 contain sequencing data of (presumably) healthy cohorts. However, important caveats related to age-of-onset and reduced penetrance should not be ignored. Unlike population databases, disease databases such as ClinGen 92 , ClinVar 93 , Leiden Open (source) Variation Databases (LOVDs) 94 , and the Human Gene Mutation Database (HGMD) 44 also provide genotype-phenotype information. All the variants collected in theHGMDdatabase have been reported in patients and likely disease causing. They have been published in literature and manually curated. The Deafness Variation Database (DVD) provides a comprehensive catalog for genetic variation in genes associated with HL. 95 Efforts are ongoing to collect and annotate all published variants associated with inherited non-syndromic RDs, Bardet-Biedl syndrome and Usher syndrome into 195 gene-specific LOVDs. 23,96-100 Several studies have proven the value of incorporating population frequency data as a variant prioritization strategy and have successfully clarified variants of unknown