The current state of clinical interpretation of sequence variants

Abstract

Accurate and consistent variant classification is required for Precision Medicine. But clinical variant classification remains in its infancy. While recent guidelines put forth jointly by the American College of Medical Genetics and Genomics (ACMG) and Association of Molecular Pathology (AMP) for the classification of Mendelian variants has advanced the field, the degree of subjectivity allowed by these guidelines can still lead to inconsistent classification across clinical molecular genetic laboratories. In addition, there are currently no such guidelines for somatic cancer variants, only published institutional practices. Additional variant classification guidelines, including disease- or gene-specific criteria, along with inter-laboratory data sharing is critical for accurate and consistent variant interpretation.

CardioVAI: An automatic implementation of ACMG-AMP variant interpretation guidelines in the diagnosis of cardiovascular diseases

“…The comparison with similar tools (InterVar and CardioClassifier) showed that CardioVAI is the most sensitive and specific tool and was able to reduce the number of VUS up to 70.9%. These differences in interpretation confirm the flexibility of ACMG–AMP criteria implementation (Hoskinson et al., ). We reported major differences in the assessment of the proposed criteria.…”

“…Since pathogenicity assessment is a complex process and relies on different sources of information that can be updated over time, discrepancies in interpretation among different laboratories are frequent (Garber et al., ) and the adoption of a common framework is required to decrease the number of variants with conflicting pathogenicity assessments (Hoskinson, Dubuc, & Mason‐Suares, ).…”

Spanish Guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia

“…Similarly, Li et al () classify variants from Tier I (Variants with Strong Clinical Significance) to Tier IV (Benign or Likely Benign Variants) based on the clinical impact of a given variant, which is determined according to currently available evidence. It is of high importance to include a separate category for benign variants, to inform clinicians and patients and to reduce the burden on laboratories (Hoskinson et al , ). Based on our experience, the use of specific standard terminology (pathogenic, likely pathogenic, uncertain significance, likely benign and benign) facilitates the use of classification systems, especially for clinicians.…”

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community‐driven standards

“…As clinical analysis of large volumes of patient variant data becomes increasingly difficult, inconsistencies increase both in variant interpretation and reporting between laboratories (Harrison et al., 2017). This issue is compounded by propagation of these inconsistencies to widely accessed knowledgebases (Hoskinson, Dubuc, & Mason‐Suares, 2017; Yorczyk, Robinson, & Ross, 2015). This underscores the need for regularized clinical classification and representation, as well as open distribution of standardized somatic cancer variant knowledge (Amendola et al., 2015; Shah & Nathanson, 2017).…”

“…However, currently the field of somatic cancer variant classification is still in development, especially when compared to variant interpretation for germline or Mendelian disorders (Richards et al., 2008; Richards et al., 2015). Besides the AMP cancer variant interpretation guidelines, there have been several other proposed systems for somatic cancer variant classification, which focus on variant therapeutic value (actionability), broader clinical value, or use more complex bioinformatic approaches to the problem (Hoskinson et al., 2017; Sukhai et al., 2016; Van Allen et al., 2014). Minimum variant level data (MVLD; described below and in reference) was developed by The Clinical Genome Resource (ClinGen) Somatic WG (WG) to provide a consensus‐based, lightweight, and modular format to transfer somatic variant data of clinical relevance (Ritter et al., 2016).…”