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. 2016 Jun 2;98(6):1067-1076.
doi: 10.1016/j.ajhg.2016.03.024. Epub 2016 May 12.

Performance of ACMG-AMP Variant-Interpretation Guidelines Among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium

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Free PMC article

Performance of ACMG-AMP Variant-Interpretation Guidelines Among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium

Laura M Amendola et al. Am J Hum Genet. .
Free PMC article

Erratum in

Abstract

Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease.

Figures

Figure 1
Figure 1
Distribution of Variant-Classification Comparisons according to the Extent of Differences across a Five-Tiered Classification Scheme (A) Intra-laboratory concordance between laboratory and ACMG-AMP classification systems. This graph compares each site’s use of the ACMG-AMP rules to their own laboratory classification methods. (B) Inter-laboratory concordance of 97 variants. This graph compares the same calls, based on either the ACMG-AMP rules or the site’s rules, between laboratories. (C) Inter-laboratory concordance after consensus efforts. This graph shows a final comparison of calls between sites after consensus-building efforts.
Figure 2
Figure 2
Distribution of 99 Variants Submitted for Assessment Gray outlines illustrate the distribution of variant classifications submitted for assessment. Green bars indicate those calls that were agreed upon after initial review, blue bars indicate those calls agreed upon after email exchange, and black bars indicate those calls agreed upon after discussion on conference calls.
Figure 3
Figure 3
Frequency of Use for Each ACMG Line of Evidence

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