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Journal articles on the topic "ACMG classification"
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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 classification of allele variants were recently defined by the ACMG-AMP (2015). Recently, applying ACMG-AMP criteria with inclusion of clinical features the TENGEN French group suggested modifications aiming to refine the classification of variants in MEN1 syndrome. Objective: To classify missense allelic variants found in the MEN1 gene by the ACMG-AMP guideline using VARSOME and by the TENGEN group to support a comparative analysis of the results obtained with these two methodologies (ACMG-AMP; TENGEN). Methods: the classification of 16 different missense allele variants identified in 17 index cases with or suspected to MEN1 syndrome was conducted according to ACMG-AMP criteria using the VARSOME software followed by the analysis defined by the TENGEN group. Results: Of the 16 variants, 6 were new, 1 was recurrent (2 unrelated index cases) and 9 of them occurred in codons with previous reports of different amino acid exchanges in the same region. Differences observed in the classification by ACMG-AMP and TENGEN were: pathogenic variant (6% vs. 65%); probably pathogenic (88% vs. 12%) and variants of uncertain significance (VUS) (6% vs. 23%). The four VUS classified by TENGEN (one of them for ACMG-AMP) were of sporadic cases without clinical diagnosis of MEN1 (2, for one MEN1-related tumor in early age; 1, for suspected MEN1) or with high risk of phenocopy (1, HPT + acromegaly). Conclusion: The difference observed in the classification of the pathogenicity of these variants, especially due to the higher occurrence of VUS in TENGEN, indicates that the criteria adopted by ACMG-VARSOME would have to be refined for clinical features. By other side, TENGEN apparently reinforce the classification of pathogenicity in cases with clinical diagnosis of MEN1 and reduce the definition of pathogenicity to variants found in MEN1-suspected cases without clinical criteria for the MEN1 diagnosis. These protocols apparently need to be investigate, validated and, probably, improved in other cohorts to reduce risks of misinterpretations and classifications that can, lately, interfere in genetic counseling and in the clinical management of patients. Finally, long-term outcome of cases classified as VUS, functional studies and, familial segregation may reinforce the initial impressions obtained with TENGEN classification.
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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 propose a sub-classification scheme for variants of uncertain significance (VUS) according to their proximity either towards the “likely pathogenic” or “likely benign” classes. We also conceived a pathogenicity potential criterion (P_POT) as a proxy for segregation criteria that might be added to a VUS after posterior testing, thus allowing it to upgrade its clinical significance in a diagnostic reporting setting. Finally, we have developed a user-friendly web application based on the MAGI-ACMG algorithm, available to geneticists for variant interpretation.
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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-assessment was performed on 70 MYH7 -variants in 121 unique patients from Mayo Clinic, and an independent cohort of 54 variants in 70 patients from Royal Prince Alfred Hospital (Australia). Qualifying variants were re-adjudicated using both standard ACMG and MYH7 -ACMG guidelines, and HCM Genotype Predictor Score was used to provide a validated measure of strength of clinical phenotype to be incorporated into the MYH7 -ACMG framework. Results: Among Mayo Clinic identified variants, 11/70 (16%) were classified as pathogenic (P), 10/70 (14%) as likely pathogenic, and 49/70 (70%) as a VUS. A similar distribution was seen in the Australian patients (12/54 [22%] P, 12/54 [22%] likely pathogenic, and 30/54 [56%] VUS; P =not significant). Application of the MYH7 -ACMG resulted in a nonsignificant reduction of the VUS burden in both cohorts from 49/70 to 39/70 (56%; P =0.1; Mayo Clinic) and from 30/54 to 20/54 (37%; P =0.1; Australia). Using the combined PE-MYH7-ACMG framework, the VUS decreased significantly from 49 to 27 ( P <0.001, Mayo Clinic) and from 30 to 16 ( P <0.001; Australia). Conclusions: Use of the MYH7 -specific guidelines alone failed to significantly decrease VUS burden in 2 independent cohorts. However, a significant reduction in VUS burden was observed after the addition of phenotypic criteria. Using a patient’s strength of sarcomeric HCM phenotype for variant adjudication can increase significantly the clinical utility of genetic testing for patients with HCM.
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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 and classified ABCC9, ACTN2, CACNA1C, DES, HCN4, KCNQ1, KCNH2, LMNA, MECP2, LAMP2, NPPA, SCN5A, and TRPM4 as high-priority genes causing familial bradycardia. Most mutated genes have been reported as having multiple clinical manifestations. Conclusions. For patients with familial CCD, 13 high-priority genes are recommended for evaluation. For genetic studies, variants should be carefully evaluated using the ACMG/AMP variant classification framework before publication.
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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. Methods: This bioinformatic study was conducted at LabPLUS, Auckland, New Zealand, from February to June 2017. DNA was extracted from peripheral blood samples of 30 patients and gene library construction was carried out using a commercially available targeted panel for the BRCA1 and BRCA2 genes. The genes were subsequently sequenced and the sequence data analysed. The guidelines published by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/ AMP) provides a comprehensive framework for the interpretation of variants in genes that are associated with Mendelian disorders. The use of these guidelines were compared to the variant classifications that were achieved by reference to those reported in the BRCA Exchange database. Results: The results showed concordance between the two classification protocols for a panel of 30 BRCA1 gene variants, although the transparency in following the ACMG/AMP guidelines provides a diagnostic laboratory with a generalisable approach that allows laboratorydirected revisions to be undertaken in light of new information. Conclusion: The ACMG/AMP-based guidelines were applied to a cohort of patients with BRCA1 gene variants. The use of these guidelines provides a system which creates consistency in variant interpretation and supports subsequent clinical management.Keywords: BRCA1 Gene; Bioinformatics; DNA Sequencing; Nonsense Codon; Splice Donor Site; New Zealand.
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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 necessary changes to criterion strength and to add or exclude criteria assigned automatically, ultimately leading to the final variant classification. We also developed a modified ACMG checklist to assist molecular geneticists in adjusting criterion strength and in adding literature-retrieved or patient-specific information, when available. The proposed classifier is an example of integration of automation and human expertise in variant curation, while maintaining the laboratory analytical workflow and the established bioinformatics pipeline.
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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 algorithms, they are not true independent variables. Objective The aim of this study was to develop machine-learning models for interpretation of DNA variants and MODY diagnosis using the ACMG criteria. Methods We applied machine-learning models for interpretation of DNA variants in MODY genes defined by the ACMG criteria based on the Human Gene Mutation Database (HGMD) and ClinVar database. Results With a machine-learning procedure, we found that the weight matrix of the ACMG criteria was significantly different between the three MODY genes HNF1A, HNF4A, and GCK. The models showed high predictive abilities with accuracy over 95%. Conclusions Our results highlight the need for applying different weights of the ACMG criteria in relation to different MODY genes for accurate functional classification. As proof of principle, we applied the ACMG criteria as feature vectors in a machine-learning model and obtained a precision-based result.
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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 of 498 ALS patients using massive parallel sequencing of ALS-associated genes and identified 280 variants with a minor allele frequency < 1%. Examining all variants using the ACMG criteria, thus considering the type of variant, inheritance, familial segregation, and possible functional studies, we classified 20 variants as “pathogenic”. In conclusion, ALS’s genetic complexity, such as oligogenic inheritance, presence of genes acting as risk factors, and reduced penetrance, needs to be considered when interpreting variants. The goal of this work is to provide helpful suggestions to geneticists and clinicians dealing with ALS.
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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 30 variants of the ENG and ACVRL1 genes. Eight of the original ACMG/AMP rules were determined to not be applicable for ENG- or ACVRL1-related HHT or were previously recommended by ClinGen for removal, two rules were unmodified, and the remaining 18 rules were modified according to HHT specifications or previous ClinGen general recommendations. This study demonstrates the importance of HHT-specific criteria in the optimization and standardization of HHT variant classification and conflicting classification resolution.