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      Expanding ACMG variant classification guidelines into a general framework

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          Abstract

          Background

          The American College of Medical Genetics and Genomics (ACMG)-recommended five variant classification categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) have been widely used in medical genetics. However, these guidelines are fundamentally constrained in practice owing to their focus upon Mendelian disease genes and their dichotomous classification of variants as being either causal or not. Herein, we attempt to expand the ACMG guidelines into a general variant classification framework that takes into account not only the continuum of clinical phenotypes, but also the continuum of the variants’ genetic effects, and the different pathological roles of the implicated genes.

          Main body

          As a disease model, we employed chronic pancreatitis (CP), which manifests clinically as a spectrum from monogenic to multifactorial. Bearing in mind that any general conceptual proposal should be based upon sound data, we focused our analysis on the four most extensively studied CP genes, PRSS1, CFTR, SPINK1 and CTRC. Based upon several cross-gene and cross-variant comparisons, we first assigned the different genes to two distinct categories in terms of disease causation: CP-causing ( PRSS1 and SPINK1) and CP-predisposing ( CFTR and CTRC). We then employed two new classificatory categories, “predisposing” and “likely predisposing”, to replace ACMG’s “pathogenic” and “likely pathogenic” categories in the context of CP-predisposing genes, thereby classifying all pathologically relevant variants in these genes as “predisposing”. In the case of CP-causing genes, the two new classificatory categories served to extend the five ACMG categories whilst two thresholds (allele frequency and functional) were introduced to discriminate “pathogenic” from “predisposing” variants.

          Conclusion

          Employing CP as a disease model, we expand ACMG guidelines into a five-category classification system (predisposing, likely predisposing, uncertain significance, likely benign, and benign) and a seven-category classification system (pathogenic, likely pathogenic, predisposing, likely predisposing, uncertain significance, likely benign, and benign) in the context of disease-predisposing and disease-causing genes, respectively. Taken together, the two systems constitute a general variant classification framework that, in principle, should span the entire spectrum of variants in any disease-related gene. The maximal compliance of our five-category and seven-category classification systems with the ACMG guidelines ought to facilitate their practical application.

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          Most cited references91

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          Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

          The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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            The mutational constraint spectrum quantified from variation in 141,456 humans

            Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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              Finding the missing heritability of complex diseases.

              Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
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                Author and article information

                Contributors
                jian-min.chen@univ-brest.fr
                Journal
                Hum Genomics
                Hum Genomics
                Human Genomics
                BioMed Central (London )
                1473-9542
                1479-7364
                16 August 2022
                16 August 2022
                2022
                : 16
                : 31
                Affiliations
                [1 ]GRID grid.6289.5, ISNI 0000 0001 2188 0893, Univ Brest, Inserm, EFS, UMR 1078, , GGB, ; 22 Avenue Camille Desmoulins, F-29200 Brest, France
                [2 ]GRID grid.411766.3, ISNI 0000 0004 0472 3249, Service de Génétique Médicale et de Biologie de la Reproduction, , CHRU Brest, ; F-29200 Brest, France
                [3 ]GRID grid.73113.37, ISNI 0000 0004 0369 1660, Department of Gastroenterology, Changhai Hospital, , The Secondary Military Medical University, ; Shanghai, China
                [4 ]GRID grid.16821.3c, ISNI 0000 0004 0368 8293, Shanghai Institute of Pancreatic Diseases, ; Shanghai, China
                [5 ]GRID grid.5600.3, ISNI 0000 0001 0807 5670, Institute of Medical Genetics, School of Medicine, , Cardiff University, ; Cardiff, UK
                [6 ]GRID grid.41156.37, ISNI 0000 0001 2314 964X, Department of Critical Care Medicine, Research Institute of General Surgery, Jinling Hospital, , Medical School of Nanjing University, ; Nanjing, China
                [7 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, Department of Gastroenterology and Pancreatology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, , Université de Paris, ; Paris, France
                Article
                407
                10.1186/s40246-022-00407-x
                9380380
                35974416
                d8fb3cea-aea2-4b62-a9df-03418005f07d
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 16 June 2022
                : 10 August 2022
                Funding
                Funded by: Institut National de la Santé et de la Recherche Médicale (INSERM)
                Funded by: China Scholarship Council
                Award ID: 202006190267
                Award Recipient :
                Funded by: Association des Pancréatites Chroniques Héréditaires
                Funded by: National Natural Science Foundation of China
                Award ID: 82120108006
                Award Recipient :
                Funded by: Association Gaétan Saleün
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Genetics
                acmg guidelines,allele frequency threshold,allelic heterogeneity,disease prevalence,exome sequencing,genetic heterogeneity,incomplete penetrance,multifactorial/complex disease,pathogenicity,variant interpretation

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