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Journal articles on the topic 'ACMG classification'

Author: Grafiati

Published: 21 December 2024

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1

Lugeiro, Palloma C., Betsaida Urtremari, Lucas S. Santana, Elisangela P. S. Quedas, and Delmar Muniz Lourenco. "Comparative Analysis of Different International Criteria (ACMG-AMP vs. TENGEN) Applied to Classification of Missense Germline Allelic Variants in Patients With Multiple Endocrine Neoplasia Type 1 or Suspected to this Syndrome." Journal of the Endocrine Society 5, Supplement_1 (2021): A1014. http://dx.doi.org/10.1210/jendso/bvab048.2074.

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Abstract Context: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant genetic syndrome caused by germline pathogenic allele variants (PAV) in the MEN1 tumor suppressor gene, which predispose MEN1 carriers to the increased risk of several endocrine neoplasms throughout life. The MEN1 gene (11q13), contains 10 exons encoding the MENIN protein. About 600 different PAVs have been reported, with 25% of them being missense variants. Of value, the definition of pathogenicity can be challenging, especially for missense variants. Thus, international guidelines for improving the clas

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Cristofoli, Francesca, Muharrem Daja, Paolo Enrico Maltese, et al. "MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations." Genes 14, no. 8 (2023): 1600. http://dx.doi.org/10.3390/genes14081600.

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We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG classification algorithm uses information retrieved through the VarSome Application Programming Interface (API), integrates the AutoPVS1 tool in order to evaluate more precisely the attribution of the PVS1 criterion, and performs the customized assignment of specific criteria. In addition, we propo

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Mattivi, Connor L., J. Martijn Bos, Richard D. Bagnall, et al. "Clinical Utility of a Phenotype-Enhanced MYH7 -Specific Variant Classification Framework in Hypertrophic Cardiomyopathy Genetic Testing." Circulation: Genomic and Precision Medicine 13, no. 5 (2020): 453–59. http://dx.doi.org/10.1161/circgen.120.003039.

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Background: Missense variants in the MYH7 -encoded MYH7 (beta myosin heavy chain 7) represent a leading cause of hypertrophic cardiomyopathy (HCM). MYH7 -specific American College of Medical Genetics and Genomics (ACMG) variant classification guidelines were released recently but have yet to be assessed independently. We set out to assess the performance of the MYH7 -specific ACMG guidelines and determine if the addition of phenotype-enhanced criteria (PE-ACMG) using the HCM Genotype Predictor Score can further reduce the burden of variants of uncertain significance (VUS). Methods: Re-assessme

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Cheng, Liting, Xiaoyan Li, Lin Zhao, et al. "Reevaluating the Mutation Classification in Genetic Studies of Bradycardia Using ACMG/AMP Variant Classification Framework." International Journal of Genomics 2020 (February 26, 2020): 1–12. http://dx.doi.org/10.1155/2020/2415850.

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Purpose. Next-generation sequencing (NGS) has become more accessible, leading to an increasing number of genetic studies of familial bradycardia being reported. However, most of the variants lack full evaluation. The relationship between genetic factors and bradycardia should be summarized and reevaluated. Methods. We summarized genetic studies published in the PubMed database from 2008/1/1 to 2019/9/1 and used the ACMG/AMP classification framework to analyze related sequence variants. Results. We identified 88 articles, 99 sequence variants, and 34 genes after searching the PubMed database an

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Brown, Angela, Mansour Zamanpoor, Donald R. Love, and Debra O. Prosser. "Determination of Pathogenicity of Breast Cancer 1 Gene Variants using the American College of Medical Genetics and Genomics and the Association for Molecular Pathology Guidelines." Sultan Qaboos University Medical Journal [SQUMJ] 19, no. 4 (2019): 324. http://dx.doi.org/10.18295/squmj.2019.19.04.008.

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Objectives: Molecular diagnostic laboratories screen for mutations in disease-causing genes in order to confirm a clinical diagnosis. The classification of DNA variants as ‘pathogenic’ or ‘likely pathogenic’ mutations creates a workflow bottleneck, which becomes increasingly challenging as greater number of genes are screened. The classification challenge is also acute if there are conflicting reports regarding pathogenicity and differing classification criteria between laboratories. This study aimed to compare two procedures for the classification of variants in the breast cancer (BRCA)1 gene

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Cristofoli, Francesca, Elisa Sorrentino, Giulia Guerri, et al. "Variant Selection and Interpretation: An Example of Modified VarSome Classifier of ACMG Guidelines in the Diagnostic Setting." Genes 12, no. 12 (2021): 1885. http://dx.doi.org/10.3390/genes12121885.

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Variant interpretation is challenging as it involves combining different levels of evidence in order to evaluate the role of a specific variant in the context of a patient’s disease. Many in-depth refinements followed the original 2015 American College of Medical Genetics (ACMG) guidelines to overcome subjective interpretation of criteria and classification inconsistencies. Here, we developed an ACMG-based classifier that retrieves information for variant interpretation from the VarSome Stable-API environment and allows molecular geneticists involved in clinical reporting to introduce the nece

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Liu, Yichuan, Hui-Qi Qu, Adam S. Wenocur, et al. "Interpretation of Maturity-Onset Diabetes of the Young Genetic Variants Based on American College of Medical Genetics and Genomics Criteria: Machine-Learning Model Development." JMIR Biomedical Engineering 5, no. 1 (2020): e20506. http://dx.doi.org/10.2196/20506.

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Background Maturity-onset diabetes of the young (MODY) is a group of dominantly inherited monogenic diabetes, with HNF4A-MODY, GCK-MODY, and HNF1A-MODY as the three most common forms based on the causal genes. Molecular diagnosis of MODY is important for precise treatment. Although a DNA variant causing MODY can be assessed based on the criteria of the American College of Medical Genetics and Genomics (ACMG) guidelines, gene-specific assessment of disease-causing mutations is important to differentiate among MODY subtypes. As the ACMG criteria were not originally designed for machine-learning

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Tavtigian, Sean V., Marc S. Greenblatt, Steven M. Harrison, et al. "Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework." Genetics in Medicine 20, no. 9 (2018): 1054–60. http://dx.doi.org/10.1038/gim.2017.210.

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Lattante, Serena, Giuseppe Marangi, Paolo Niccolò Doronzio, et al. "High-Throughput Genetic Testing in ALS: The Challenging Path of Variant Classification Considering the ACMG Guidelines." Genes 11, no. 10 (2020): 1123. http://dx.doi.org/10.3390/genes11101123.

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The development of high-throughput sequencing technologies and screening of big patient cohorts with familial and sporadic amyotrophic lateral sclerosis (ALS) led to the identification of a significant number of genetic variants, which are sometimes difficult to interpret. The American College of Medical Genetics and Genomics (ACMG) provided guidelines to help molecular geneticists and pathologists to interpret variants found in laboratory testing. We assessed the application of the ACMG criteria to ALS-related variants, combining data from literature with our experience. We analyzed a cohort

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DeMille, Desiree, Jamie McDonald, Carmelo Bernabeu, et al. "Specifications of the ACMG/AMP Variant Curation Guidelines for Hereditary Hemorrhagic Telangiectasia Genes—ENG and ACVRL1." Human Mutation 2024 (May 18, 2024): 1–13. http://dx.doi.org/10.1155/2024/3043736.

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The 2015 ACMG/AMP standards and guidelines for interpretation of sequence variants are widely used by laboratories, including for variant curation of the hereditary hemorrhagic telangiectasia (HHT) genes. However, the need for gene- and disease-specific modifications and specifications of these general guidelines to optimize and standardize variant classification was recognized at the time of publication. With this goal, the ClinGen HHT variant curation expert panel was formed. Here, we describe our recommended HHT-specific variant classification criteria and the outcomes from pilot testing of

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Tavtigian, S. "Abstract ES3-1: Reclassifying VUS: New techniques can solve the puzzle once and for all." Cancer Research 82, no. 4_Supplement (2022): ES3–1—ES3–1. http://dx.doi.org/10.1158/1538-7445.sabcs21-es3-1.

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Abstract Over the last 10 years, the scale of genetic testing for cancer predisposition has increased dramatically. Two simple facts drive this trend: (1) improving test technology has reduced the costs while increasing clinical yield, and (2) medical and surgical approaches to risk reduction can add years to the lives of carriers of pathogenic variants if these individuals are identified through cascade testing before they develop a metastatic tumor. Initial outcomes from this genetic testing fall into one of three categories: a pathogenic sequence variant(s) is found, no reportable sequence

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Спектор, М. А., Л. А. Ясько, and А. Е. Друй. "The interpretation of somatic genetic variants identified with high-throughput sequencing of DNA from paediatric solid tumors." Nauchno-prakticheskii zhurnal «Medicinskaia genetika, no. 3(224) (March 31, 2021): 3–25. http://dx.doi.org/10.25557/2073-7998.2021.03.3-25.

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Активное внедрение высокопроизводительного секвенирования в клиническую практику требует общего подхода к интерпретации обнаруженных генетических вариантов, в частности, вариантов с соматическим статусом. В 2017 году Ассоциация молекулярной патологии США (AMP), Американская коллегия медицинской генетики и геномики (ACMG), Американское общество клинической онкологии (ASCO) и Коллегия американских патологов (CAP) опубликовали руководство по интерпретации соматических генетических вариантов и выдаче заключений по результатам высокопроизводительного секвенирования опухолевой ДНК. Данный обзор посв

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Hatton, Jessica N., Megan N. Frone, Hannah C. Cox, et al. "Specifications of the ACMG/AMP Variant Classification Guidelines for Germline DICER1 Variant Curation." Human Mutation 2023 (March 29, 2023): 1–15. http://dx.doi.org/10.1155/2023/9537832.

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Germline pathogenic variants in DICER1 predispose individuals to develop a variety of benign and malignant tumors. Accurate variant curation and classification are essential for reliable diagnosis of DICER1-related tumor predisposition and the identification of individuals who may benefit from surveillance. Since 2015, most labs have followed the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) sequence variant classification guidelines for DICER1 germline variant curation. However, these general guidelines lack gene-specific nuances and

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Lesmann, Hellen, Hannah Klinkhammer, and Prof Dr med Dipl Phys Peter M. Krawitz. "The future role of facial image analysis in ACMG classification guidelines." Medizinische Genetik 35, no. 2 (2023): 115–21. http://dx.doi.org/10.1515/medgen-2023-2014.

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Abstract The use of next-generation sequencing (NGS) has dramatically improved the diagnosis of rare diseases. However, the analysis of genomic data has become complex with the increasing detection of variants by exome and genome sequencing. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) developed a 5-tier classification scheme in 2015 for variant interpretation, that has since been widely adopted. Despite efforts to minimise discrepancies in the application of these criteria, inconsistencies still occur. Further specifications fo

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Hirotsu, Yosuke, Udo Schmidt-Edelkraut, Hiroshi Nakagomi, et al. "Consolidated BRCA1/2 Variant Interpretation by MH BRCA Correlates with Predicted PARP Inhibitor Efficacy Association by MH Guide." International Journal of Molecular Sciences 21, no. 11 (2020): 3895. http://dx.doi.org/10.3390/ijms21113895.

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BRCA1/2 variants are prognostic biomarkers for hereditary breast and/or ovarian cancer (HBOC) syndrome and predictive biomarkers for PARP inhibition. In this study, we benchmarked the classification of BRCA1/2 variants from patients with HBOC-related cancer using MH BRCA, a novel computational technology that combines the ACMG guidelines with expert-curated variant annotations. Evaluation of BRCA1/2 variants (n = 1040) taken from four HBOC studies showed strong concordance within the pathogenic (98.1%) subset. Comparison of MH BRCA’s ACMG classification to ClinVar submitter content from ENIGMA

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Huang, Yingzhao, Bowen Liu, Jile Shi, et al. "Landscape of Secondary Findings in Chinese Population: A Practice of ACMG SF v3.0 List." Journal of Personalized Medicine 12, no. 9 (2022): 1503. http://dx.doi.org/10.3390/jpm12091503.

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Clinical exome sequencing (CES) has shown great utility in the diagnosis of Mendelian disorders. CES can unravel secondary findings (SFs) unrelated to the primary diagnosis but with potential health implications. The American College of Medical Genetics and Genomics (ACMG) has published a guideline for reporting secondary findings and recently updated an ACMG SF v3.0 list comprising 73 genes. Several studies have been performed to explore the prevalence of SFs. However, the data were limited in the Chinese population. In this study, we evaluated the genetic data of 2987 individuals from the De

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Ji, Jianling, Ryan Schmidt, Westley Sherman, et al. "Automated classification of copy number variants based on 2019 ACMG standards." Molecular Genetics and Metabolism 132 (April 2021): S287—S288. http://dx.doi.org/10.1016/s1096-7192(21)00531-x.

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Dent, C., A. Hills, J. Honeychurch, et al. "Standardising genetic variant classification for FH – application of the ACMG guidelines." Atherosclerosis Supplements 28 (September 2017): e7. http://dx.doi.org/10.1016/j.atherosclerosissup.2017.08.012.

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Nykamp, Keith, Michael Anderson, Martin Powers, et al. "Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria." Genetics in Medicine 19, no. 10 (2017): 1105–17. http://dx.doi.org/10.1038/gim.2017.37.

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Joseph, Vijai, Vignesh Ravichandran, and Kenneth Offit. "Pathogenicity of mutation analyzer (PathoMAN): A fast automation of germline genomic variant curation in clinical sequencing." Journal of Clinical Oncology 35, no. 15_suppl (2017): 1529. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.1529.

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1529 Background: A challenge in clinical oncology is interpretation of multiplexed gene sequencing of patients at risk. The plethora of variants to be curated for pathogenicity or actionability poses a growing burden for cancer care professionals. Current guidelines by the ACMG requires the aggregation of multiple lines of genomic data evidences from diverse resources. A computational tool that automates, provide uniformity and significantly speed the interpretive process is thus necessary. Methods: The Pathogenicity of Mutation Analyzer (PathoMAN), is a tool that automates germline genomic va

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Westphal, Dominik Sebastian, Kathrin Pollmann, Christoph Marschall, et al. "It Is Not Carved in Stone—The Need for a Genetic Reevaluation of Variants in Pediatric Cardiomyopathies." Journal of Cardiovascular Development and Disease 9, no. 2 (2022): 41. http://dx.doi.org/10.3390/jcdd9020041.

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(1) Background: In cardiomyopathies, identification of genetic variants is important for the correct diagnosis and impacts family cascade screening. A classification system was published by the American College of Medical Genetics and Genomics (ACMG) in 2015 to standardize variants’ classification. The aim of the study was to determine the rate of reclassification of previously identified variants in patients with childhood-onset cardiomyopathies. (2) Methods: Medical records of patients and their relatives were screened for clinical and genetic information at the Department of Congenital Hear

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Melidis, Damianos P., Christian Landgraf, Gunnar Schmidt, et al. "GenOtoScope: Towards automating ACMG classification of variants associated with congenital hearing loss." PLOS Computational Biology 18, no. 9 (2022): e1009785. http://dx.doi.org/10.1371/journal.pcbi.1009785.

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Since next-generation sequencing (NGS) has become widely available, large gene panels containing up to several hundred genes can be sequenced cost-efficiently. However, the interpretation of the often large numbers of sequence variants detected when using NGS is laborious, prone to errors and is often difficult to compare across laboratories. To overcome this challenge, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have introduced standards and guidelines for the interpretation of sequencing variants. Additionally, disease-specific

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Nykamp, Keith, Michael Anderson, Martin Powers, et al. "Correction: Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria." Genetics in Medicine 22, no. 1 (2019): 240. http://dx.doi.org/10.1038/s41436-019-0624-9.

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Karalidou, Vasiliki, Despoina Kalfakakou, Athanasios Papathanasiou, Florentia Fostira, and George K. Matsopoulos. "MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model." Biomolecules 12, no. 11 (2022): 1552. http://dx.doi.org/10.3390/biom12111552.

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Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL 1.0.0, a machine learning (ML)-based software for the interpretation of rare BRCA1 and BRCA2 germline variants. MARGINAL software classifies variants into three categories, namely, (likely) pathogenic, of uncertain significance and (likely) benign, implementing the criteria est

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Motta, Fabiana, Renan Martin, Fernanda Porto, et al. "Pathogenicity Reclassification of RPE65 Missense Variants Related to Leber Congenital Amaurosis and Early-Onset Retinal Dystrophy." Genes 11, no. 1 (2019): 24. http://dx.doi.org/10.3390/genes11010024.

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A challenge in molecular diagnosis and genetic counseling is the interpretation of variants of uncertain significance. Proper pathogenicity classification of new variants is important for the conclusion of molecular diagnosis and the medical management of patient treatments. The purpose of this study was to reclassify two RPE65 missense variants, c.247T>C (p.Phe83Leu) and c.560G>A (p.Gly187Glu), found in Brazilian families. To achieve this aim, we reviewed the sequencing data of a 224-gene retinopathy panel from 556 patients (513 families) with inherited retinal dystrophies. Five patient

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Rossen, Jennifer L., Brenda L. Bohnsack, Kevin X. Zhang, et al. "Evaluation of Genetic Testing in a Cohort of Diverse Pediatric Patients in the United States with Congenital Cataracts." Genes 14, no. 3 (2023): 608. http://dx.doi.org/10.3390/genes14030608.

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The aim of this study was to evaluate the diagnostic yield from prior genetic testing in a 20-year cohort of pediatric patients with congenital cataracts. A retrospective review of patients with congenital cataracts who underwent genetic testing was completed from 2003–2022. The diagnostic yield of the test was determined by variant classification and inheritance pattern. Variants from initial testing underwent reclassification in accordance with ACMG-AMP (American College of Medical Genetics and Genomics—American Association of Molecular Pathology) 2015 or 2020 ACMG CNV guidelines. A total of

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Cornelis, Stéphanie S., Miriam Bauwens, Lonneke Haer-Wigman, et al. "Compendium of Clinical Variant Classification for 2,246 Unique ABCA4 Variants to Clarify Variant Pathogenicity in Stargardt Disease Using a Modified ACMG/AMP Framework." Human Mutation 2023 (December 26, 2023): 1–12. http://dx.doi.org/10.1155/2023/6815504.

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Biallelic variants in ABCA4 cause Stargardt disease (STGD1), the most frequent heritable macular disease. Determination of the pathogenicity of variants in ABCA4 proves to be difficult due to (1) the high number of benign and pathogenic variants in the gene; (2) the presence of many rare ABCA4 variants; (3) the presence of complex alleles for which phasing data are absent; (4) the extensive variable expressivity of this disease and (5) reduced penetrance of hypomorphic variants. Therefore, the classification of many variants in ABCA4 is currently of uncertain significance. Here, we complemente

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Davieson, Connor D., Katie E. Joyce, Lakshya Sharma, and Claire L. Shovlin. "DNA variant classification–reconsidering “allele rarity” and “phenotype” criteria in ACMG/AMP guidelines." European Journal of Medical Genetics 64, no. 10 (2021): 104312. http://dx.doi.org/10.1016/j.ejmg.2021.104312.

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Brandt, Tracy, Laura M. Sack, Dolores Arjona, et al. "Adapting ACMG/AMP sequence variant classification guidelines for single-gene copy number variants." Genetics in Medicine 22, no. 2 (2019): 336–44. http://dx.doi.org/10.1038/s41436-019-0655-2.

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Tavtigian, Sean V., Steven M. Harrison, Kenneth M. Boucher, and Leslie G. Biesecker. "Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines." Human Mutation 41, no. 10 (2020): 1734–37. http://dx.doi.org/10.1002/humu.24088.

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Vargas‐Parra, Gardenia, Jesús Valle, Paula Rofes, et al. "Comprehensive analysis and ACMG‐based classification of CHEK2 variants in hereditary cancer patients." Human Mutation 41, no. 12 (2020): 2128–42. http://dx.doi.org/10.1002/humu.24110.

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Nieto-Patlán, Alejandro, Lindsay Worley, William Hankey, et al. "177 ClinGen Framework for PIK3CD Variant Classification: Use of Adapted ACMG/AMP Guidelines." Clinical Immunology 262 (May 2024): 110119. http://dx.doi.org/10.1016/j.clim.2024.110119.

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Lee, Jee-Soo, Sohee Oh, Sue Kyung Park, et al. "Reclassification of BRCA1 and BRCA2 variants of uncertain significance: a multifactorial analysis of multicentre prospective cohort." Journal of Medical Genetics 55, no. 12 (2018): 794–802. http://dx.doi.org/10.1136/jmedgenet-2018-105565.

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BackgroundBRCA1 and BRCA2 (BRCA1/2) variants classified ambiguously as variants of uncertain significance (VUS) are a major challenge for clinical genetic testing in breast cancer; their relevance to the cancer risk is unclear and the association with the response to specific BRCA1/2-targeted agents is uncertain. To minimise the proportion of VUS in BRCA1/2, we performed the multifactorial likelihood analysis and validated this method using an independent cohort of patients with breast cancer.MethodsWe used a data set of 2115 patients with breast cancer from the nationwide multicentre prospect

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Vatsyayan, Aastha, Mukesh Kumar, Bhaskar Jyoti Saikia, Vinod Scaria, and Binukumar B. K. "WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease." PLOS ONE 19, no. 5 (2024): e0303787. http://dx.doi.org/10.1371/journal.pone.0303787.

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Background Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as

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Ruffo, Paola, Benedetta Perrone, and Francesca Luisa Conforti. "SOD-1 Variants in Amyotrophic Lateral Sclerosis: Systematic Re-Evaluation According to ACMG-AMP Guidelines." Genes 13, no. 3 (2022): 537. http://dx.doi.org/10.3390/genes13030537.

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Amyotrophic lateral sclerosis (ALS) is the most common type of motor neuron disease whose causes are unclear. The first ALS gene associated with the autosomal dominant form of the disease was SOD1. This gene has a high rate of rare variants, and an appropriate classification is essential for a correct ALS diagnosis. In this study, we re-evaluated the classification of all previously reported SOD1 variants (n = 202) from ALSoD, project MinE, and in-house databases by applying the ACMG-AMP criteria to ALS. New bioinformatics analysis, frequency rating, and a thorough search for functional studie

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Godley, Lucy, Xi Luo, Justyne Ross, et al. "Myeloid Malignancy Variant Curation Expert Panel: An ASH-Sponsored Clingen Expert Panel to Optimize and Validate Acmg/AMP Variant Interpretation Guidelines for Genes Associated with Inherited Myeloid Neoplasms." Blood 132, Supplement 1 (2018): 5849. http://dx.doi.org/10.1182/blood-2018-99-118979.

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Abstract Clinical Genome Resource (ClinGen) is an NIH/NHGRI-funded effort dedicated to building an authoritative central resource that defines the clinical relevance of genes and variants for use in precision medicine and research. ClinGen has developed both gene and variant expert panels to adapt the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for consistent and accurate variant classification of specific genes and diseases. Here, we describe a new effort initiated in 2018 and supported by the American Society of Hematology (ASH)

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Ross, Justyne E., Bing M. Zhang, Kristy Lee, et al. "Specifications of the variant curation guidelines for ITGA2B/ITGB3: ClinGen Platelet Disorder Variant Curation Panel." Blood Advances 5, no. 2 (2021): 414–31. http://dx.doi.org/10.1182/bloodadvances.2020003712.

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Abstract Accurate and consistent sequence variant interpretation is critical to the correct diagnosis and appropriate clinical management and counseling of patients with inherited genetic disorders. To minimize discrepancies in variant curation and classification among different clinical laboratories, the American College of Medical Genetics and Genomics (ACMG), along with the Association for Molecular Pathology (AMP), published standards and guidelines for the interpretation of sequence variants in 2015. Because the rules are not universally applicable to different genes or disorders, the Cli

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Schmidt-Edelkraut, Udo, Elena Ioana Braicu, Sajo Kaduthanam, et al. "Confident BRCA1/2 variant classification: using ACMG and public data for systematic molecular profiling." Annals of Oncology 29 (October 2018): vii71. http://dx.doi.org/10.1093/annonc/mdy375.025.

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Brandt, Tracy, Laura M. Sack, Dolores Arjona, et al. "Correction: Adapting ACMG/AMP sequence variant classification guidelines for single-gene copy-number variants." Genetics in Medicine 22, no. 3 (2019): 670–71. http://dx.doi.org/10.1038/s41436-019-0725-5.

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Dickson, Alexa, Meagan Corliss, Jonathan Heusel, et al. "P430: Application of ACMG/AMP variant classification guidelines to Alzheimer’s disease-associated genetic variation." Genetics in Medicine Open 1, no. 1 (2023): 100477. http://dx.doi.org/10.1016/j.gimo.2023.100477.

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Walker, Romy, Khalid Mahmood, Julia Como, et al. "DNA Mismatch Repair Gene Variant Classification: Evaluating the Utility of Somatic Mutations and Mismatch Repair Deficient Colonic Crypts and Endometrial Glands." Cancers 15, no. 20 (2023): 4925. http://dx.doi.org/10.3390/cancers15204925.

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Germline pathogenic variants in the DNA mismatch repair (MMR) genes (Lynch syndrome) predispose to colorectal (CRC) and endometrial (EC) cancer. Lynch syndrome specific tumor features were evaluated for their ability to support the ACMG/InSiGHT framework in classifying variants of uncertain clinical significance (VUS) in the MMR genes. Twenty-eight CRC or EC tumors from 25 VUS carriers (6xMLH1, 9xMSH2, 6xMSH6, 4xPMS2), underwent targeted tumor sequencing for the presence of microsatellite instability/MMR-deficiency (MSI-H/dMMR) status and identification of a somatic MMR mutation (second hit).

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Kirkland, Nathan, Marzia Pasquali, Rong Mao, Elena Coupal, and Kianoush Sadre-Bazzaz. "Classification of variants in ACADVL following the 2015 ACMG variant classification guidelines and correlation with clinical and biochemical data." Molecular Genetics and Metabolism 132 (April 2021): S31. http://dx.doi.org/10.1016/s1096-7192(21)00130-x.

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Hopkins, Jasmin J., Matthew N. Wakeling, Matthew B. Johnson, Sarah E. Flanagan, and Thomas W. Laver. "REVEL Is Better at Predicting Pathogenicity of Loss-of-Function than Gain-of-Function Variants." Human Mutation 2023 (December 4, 2023): 1–6. http://dx.doi.org/10.1155/2023/8857940.

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In silico predictive tools can help determine the pathogenicity of variants. The 2015 American College of Medical Genetics and Genomics (ACMG) guidelines recommended that scores from these tools can be used as supporting evidence of pathogenicity. A subsequent publication by the ClinGen Sequence Variant Interpretation Working Group suggested that high scores from some tools were sufficiently predictive to be used as moderate or strong evidence of pathogenicity. REVEL is a widely used metapredictor that uses the scores of 13 individual in silico tools to calculate the pathogenicity of missense

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Froyen, Guy, Marie Le Mercier, Els Lierman, et al. "Standardization of Somatic Variant Classifications in Solid and Haematological Tumours by a Two-Level Approach of Biological and Clinical Classes: An Initiative of the Belgian ComPerMed Expert Panel." Cancers 11, no. 12 (2019): 2030. http://dx.doi.org/10.3390/cancers11122030.

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In most diagnostic laboratories, targeted next-generation sequencing (NGS) is currently the default assay for the detection of somatic variants in solid as well as haematological tumours. Independent of the method, the final outcome is a list of variants that differ from the human genome reference sequence of which some may relate to the establishment of the tumour in the patient. A critical point towards a uniform patient management is the assignment of the biological contribution of each variant to the malignancy and its subsequent clinical impact in a specific malignancy. These so-called bi

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Lopez-Perolio, Irene, Raphaël Leman, Raquel Behar, et al. "Alternative splicing and ACMG-AMP-2015-based classification of PALB2 genetic variants: an ENIGMA report." Journal of Medical Genetics 56, no. 7 (2019): 453–60. http://dx.doi.org/10.1136/jmedgenet-2018-105834.

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BackgroundPALB2 monoallelic loss-of-function germ-line variants confer a breast cancer risk comparable to the average BRCA2 pathogenic variant. Recommendations for risk reduction strategies in carriers are similar. Elaborating robust criteria to identify loss-of-function variants in PALB2—without incurring overprediction—is thus of paramount clinical relevance. Towards this aim, we have performed a comprehensive characterisation of alternative splicing in PALB2, analysing its relevance for the classification of truncating and splice site variants according to the 2015 American College of Medic

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Abad Baucells, Clàudia, Ria Schönauer, and Jan Halbritter. "The genetics of cystinuria – an update and critical reevaluation." Current Opinion in Nephrology & Hypertension 33, no. 2 (2023): 231–37. http://dx.doi.org/10.1097/mnh.0000000000000949.

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Purpose of review We aimed to critically evaluate how the establishment of genotype-based treatment for cystinuria has been hampered due to the large number of variants of unknown significance (VUS) within the disease causing genes as well as challenges in accessing a large enough sample size for systematic analysis of endpoint parameters that truly reflect disease severity. This review further discusses how to overcome these hurdles with the establishment of a cystinuria-specific refinement of the current American College of Medical Genetics and Genomics (ACMG)-criteria of variant interpretat

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Amendola, Laura M., Kathleen Muenzen, Leslie G. Biesecker, et al. "Variant Classification Concordance using the ACMG-AMP Variant Interpretation Guidelines across Nine Genomic Implementation Research Studies." American Journal of Human Genetics 107, no. 5 (2020): 932–41. http://dx.doi.org/10.1016/j.ajhg.2020.09.011.

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Lyra, Paulo, Lucas Dalcolmo, Michael Parsons, et al. "Abstract 7325: Integration of functional data to classify BRCA1/2 missense variants: An ENIGMA project." Cancer Research 84, no. 6_Supplement (2024): 7325. http://dx.doi.org/10.1158/1538-7445.am2024-7325.

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Abstract The success of precision cancer prevention and treatment hinges on accurate discrimination between benign and pathogenic germline alleles in cancer susceptibility genes. Variants of uncertain clinical significance (VUS) present a challenge for cancer risk assessment and functional data will be essential to resolve many VUS. To address this, we developed a cloud-based environment to collate, curate, integrate and analyze all published functional data related to BRCA1 and BRCA2 missense VUS. Then, functional evidence criteria for pathogenicity were determined for each assay using the Am

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Bhasin, Meghna Ahuja, Alexej Knaus, Pietro Incardona, et al. "Enhancing Variant Prioritization in VarFish through On-Premise Computational Facial Analysis." Genes 15, no. 3 (2024): 370. http://dx.doi.org/10.3390/genes15030370.

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Genomic variant prioritization is crucial for identifying disease-associated genetic variations. Integrating facial and clinical feature analyses into this process enhances performance. This study demonstrates the integration of facial analysis (GestaltMatcher) and Human Phenotype Ontology analysis (CADA) within VarFish, an open-source variant analysis framework. Challenges related to non-open-source components were addressed by providing an open-source version of GestaltMatcher, facilitating on-premise facial analysis to address data privacy concerns. Performance evaluation on 163 patients re

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Osundiji, Mayowa, Jessie Cameron, Rory Olson, Bukola Olarewaju, and Andreas Schulze. "P046: ACMG/AMP variant classification framework in arginase 1 deficiency: Implications for birth prevalence estimates and diagnostics." Genetics in Medicine Open 2 (2024): 100923. http://dx.doi.org/10.1016/j.gimo.2024.100923.

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