Abstract
Purpose
The American College of Medical Genetics and Genomics and the Association for Molecular
Pathology guidelines for germline variant interpretation are implemented as a broad
framework by standardizing variant interpretation. These rules were designed to be
specified, but this process has not been performed for most of the 200 genes associated
with inherited hematopoietic malignancies, bone marrow failure, and cytopenias. Because
guidelines on how to perform these gene specifications are lacking, variant interpretation
is less reliable and reproducible.
Methods
We have used a variety of methods such as calculations of minor allele frequencies,
quasi-case–control studies to establish thresholds, proband counting, and plotting
of receiver operating characteristic curves to compare different in silico prediction
tools to design recommendations for variant interpretation.
Results
We herein provide practical recommendations for the creation of thresholds for minor
allele frequencies, in silico predictions, counting of probands, identification of
functional domains with minimal benign variation, use of constraint Z-scores and functional
evidence, prediction of nonsense-mediated decay, and assessment of phenotype specificity.
Conclusion
These guidelines can be used by anyone interpreting variants associated with inherited
hematopoietic malignancies, bone marrow failure, and cytopenias to develop criteria
for reliable, accurate, and reproducible germline variant interpretation.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
ACMG Member Login
Are you an ACMG Member? Sign in for online access.Subscribe:
Subscribe to Genetics in MedicineAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- 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.Genet Med. 2015; 17: 405-424https://doi.org/10.1038/gim.2015.30
- ClinGen Sequence Variant Interpretation Working Group. The ACMG/AMP reputable source criteria for the interpretation of sequence variants.Genet Med. 2018; 20: 1687-1688https://doi.org/10.1038/gim.2018.42
- Quantifying the potential of functional evidence to reclassify variants of uncertain significance in the categorical and Bayesian interpretation frameworks.Hum Mutat. 2018; 39: 1531-1541https://doi.org/10.1002/humu.23609
- Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.Genome Med. 2019; 12: 3https://doi.org/10.1186/s13073-019-0690-2
- ClinGen Sequence Variant Interpretation Working Group. Updated recommendation for the benign stand-alone ACMG/AMP criterion.Hum Mutat. 2018; 39: 1525-1530https://doi.org/10.1002/humu.23642
- Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen).Genet Med. 2020; 22 (Published correction appears in Genet Med. 2021;23(11):2230): 245-257https://doi.org/10.1038/s41436-019-0686-8
- Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion.Hum Mutat. 2018; 39: 1517-1524https://doi.org/10.1002/humu.23626
- Navigating the nuances of clinical sequence variant interpretation in Mendelian disease.Genet Med. 2018; 20: 918-926https://doi.org/10.1038/s41436-018-0100-y
- Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.Genet Med. 2018; 20: 1054-1060https://doi.org/10.1038/gim.2017.210
- Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes.Hum Mutat. 2018; 39: 1542-1552https://doi.org/10.1002/humu.23640
- Consideration of cosegregation in the pathogenicity classification of genomic variants.Am J Hum Genet. 2016; 98: 1077-1081https://doi.org/10.1016/j.ajhg.2016.04.003
- Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants.Hum Mutat. 2018; 39: 1553-1568https://doi.org/10.1002/humu.23650
- Specifications of the variant curation guidelines for ITGA2B/ITGB3: ClinGen platelet disorder variant curation panel.Blood Adv. 2021; 5: 414-431https://doi.org/10.1182/bloodadvances.2020003712
- Adaptation and validation of the ACMG/AMP variant classification framework for MYH7-associated inherited cardiomyopathies: recommendations by ClinGen’s inherited cardiomyopathy expert panel.Genet Med. 2018; 20: 351-359https://doi.org/10.1038/gim.2017.218
- Unique aspects of sequence variant interpretation for inborn errors of metabolism (IEM): the ClinGen IEM working group and the phenylalanine hydroxylase gene.Hum Mutat. 2018; 39: 1569-1580https://doi.org/10.1002/humu.23649
- Gene-specific criteria for PTEN variant curation: recommendations from the ClinGen PTEN expert panel.Hum Mutat. 2018; 39: 1581-1592https://doi.org/10.1002/humu.23636
- ClinGen myeloid malignancy variant curation expert panel recommendations for germline RUNX1 variants.Blood Adv. 2019; 3: 2962-2979https://doi.org/10.1182/bloodadvances.2019000644
- Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants.Hum Mutat. 2021; 42: 223-236https://doi.org/10.1002/humu.24152
- Expert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss.Hum Mutat. 2018; 39: 1593-1613https://doi.org/10.1002/humu.23630
- ClinGen’s RASopathy expert panel consensus methods for variant interpretation.Genet Med. 2018; 20: 1334-1345https://doi.org/10.1038/gim.2018.3
- Germline predisposition to haematopoietic malignancies.Hum Mol Genet. 2021; 30: R225-R235https://doi.org/10.1093/hmg/ddab141
- The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia.Blood. 2016; 127: 2391-2405https://doi.org/10.1182/blood-2016-03-643544
- How I curate: applying American Society of Hematology-Clinical Genome Resource Myeloid Malignancy Variant Curation Expert Panel rules for RUNX1 variant curation for germline predisposition to myeloid malignancies.Haematologica. 2020; 105: 870-887https://doi.org/10.3324/haematol.2018.214221
- Accurate germline RUNX1 variant interpretation and its clinical significance.Blood Adv. 2020; 4: 6199-6203https://doi.org/10.1182/bloodadvances.2020003304
- Inherited and somatic defects in DDX41 in myeloid neoplasms.Cancer Cell. 2015; 27: 658-670https://doi.org/10.1016/j.ccell.2015.03.017
- Novel germ line DDX41 mutations define families with a lower age of MDS/AML onset and lymphoid malignancies.Blood. 2016; 127: 1017-1023https://doi.org/10.1182/blood-2015-10-676098
- Germline DDX41 mutations define a significant entity within adult MDS/AML patients.Blood. 2019; 134: 1441-1444https://doi.org/10.1182/blood.2019000909
- SEER cancer statistics review, 1975-2017. National Cancer Institute. Published April 2020.(Accessed January 7, 2022)
- Using high-resolution variant frequencies to empower clinical genome interpretation.Genet Med. 2017; 19: 1151-1158https://doi.org/10.1038/gim.2017.26
- Disease evolution and outcomes in familial AML with germline CEBPA mutations.Blood. 2015; 126: 1214-1223https://doi.org/10.1182/blood-2015-05-647172
- CEBPA –double-mutated acute myeloid leukemia displays a unique phenotypic profile: a reliable screening method and insight into biological features.Haematologica. 2017; 102: 529-540https://doi.org/10.3324/haematol.2016.151910
- Prognostic impact, concurrent genetic mutations, and gene expression features of AML with CEBPA mutations in a cohort of 1182 cytogenetically normal AML patients: further evidence for CEBPA double mutant AML as a distinctive disease entity.Blood. 2011; 117: 2469-2475https://doi.org/10.1182/blood-2010-09-307280
- Somatic CEBPA mutations are a frequent second event in families with germline CEBPA mutations and familial acute myeloid leukemia.J Clin Oncol. 2008; 26: 5088-5093https://doi.org/10.1200/JCO.2008.16.5563
- Predicting splicing from primary sequence with deep learning.Cell. 2019; 176: 535-548.e24https://doi.org/10.1016/j.cell.2018.12.015
- Clinical impact of splicing in neurodevelopmental disorders.Genome Med. 2020; 12: 36https://doi.org/10.1186/s13073-020-00737-2
- Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance.Genet Med. 2020; 22 (Published correction appears in Genet Med. 2020;22(6):1129): 1005-1014https://doi.org/10.1038/s41436-020-0766-9
- Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants.Hum Mutat. 2012; 33: 1228-1238https://doi.org/10.1002/humu.22101
- In silico prediction of splice-altering single nucleotide variants in the human genome.Nucleic Acids Res. 2014; 42: 13534-13544https://doi.org/10.1093/nar/gku1206
- Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.Nucleic Acids Res. 2018; 46 (Published correction appears in Nucleic Acids Res. 2018;46(21):11656-11657. Published correction appears in Nucleic Acids Res. 2020;48(3):1600-1601): 7913-7923https://doi.org/10.1093/nar/gky372
- Evaluation of bioinformatic programmes for the analysis of variants within splice site consensus regions.Adv Bioinformatics. 2016; 20165614058https://doi.org/10.1155/2016/5614058
- Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation.Genome Med. 2017; 9: 13https://doi.org/10.1186/s13073-017-0403-7
- Variable population prevalence estimates of germline TP53 variants: a gnomAD-based analysis.Hum Mutat. 2019; 40: 97-105https://doi.org/10.1002/humu.23673
- Clinical consequences of clonal hematopoiesis of indeterminate potential.Blood Adv. 2018; 2: 3404-3410https://doi.org/10.1182/bloodadvances.2018020222
- Analysis of protein-coding genetic variation in 60,706 humans.Nature. 2016; 536: 285-291https://doi.org/10.1038/nature19057
- Improved pathogenic variant localization via a hierarchical model of sub-regional intolerance.Am J Hum Genet. 2019; 104: 299-309https://doi.org/10.1016/j.ajhg.2018.12.020
- The intolerance to functional genetic variation of protein domains predicts the localization of pathogenic mutations within genes.Genome Biol. 2016; 17: 9https://doi.org/10.1186/s13059-016-0869-4
- A map of constrained coding regions in the human genome.Nat Genet. 2019; 51: 88-95https://doi.org/10.1038/s41588-018-0294-6
- Mutations in ANKRD26 are responsible for a frequent form of inherited thrombocytopenia: analysis of 78 patients from 21 families.Blood. 2011; 117: 6673-6680https://doi.org/10.1182/blood-2011-02-336537
- ANKRD26-related thrombocytopenia and myeloid malignancies.Blood. 2013; 122: 1987-1989https://doi.org/10.1182/blood-2013-04-499319
- Mutations in the 5′ UTR of ANKRD26, the ankirin repeat domain 26 gene, cause an autosomal-dominant form of inherited thrombocytopenia, THC2.Am J Hum Genet. 2011; 88: 115-120https://doi.org/10.1016/j.ajhg.2010.12.006
- Thrombocytopenia-associated mutations in the ANKRD26 regulatory region induce MAPK hyperactivation.J Clin Invest. 2014; 124: 580-591https://doi.org/10.1172/JCI71861
- Evidence for the widespread coupling of alternative splicing and nonsense-mediated mRNA decay in humans.Proc Natl Acad Sci U S A. 2003; 100: 189-192https://doi.org/10.1073/pnas.0136770100
- The nonsense-mediated decay RNA surveillance pathway.Annu Rev Biochem. 2007; 76: 51-74https://doi.org/10.1146/annurev.biochem.76.050106.093909
- Connections between alternative transcription and alternative splicing in mammals.Genome Biol Evol. 2010; 2: 791-799https://doi.org/10.1093/gbe/evq058
- A nonsense mutation in the DNA repair factor Hebo causes mild bone marrow failure and microcephaly.J Exp Med. 2016; 213: 1011-1028https://doi.org/10.1084/jem.20151183
- Genome instability is a consequence of transcription deficiency in patients with bone marrow failure harboring biallelic ERCC6L2 variants.Proc Natl Acad Sci U S A. 2018; 115: 7777-7782https://doi.org/10.1073/pnas.1803275115
- ERCC6L2 mutations link a distinct bone-marrow-failure syndrome to DNA repair and mitochondrial function.Am J Hum Genet. 2014; 94: 246-256https://doi.org/10.1016/j.ajhg.2014.01.007
- REVEL: an ensemble method for predicting the pathogenicity of rare missense variants.Am J Hum Genet. 2016; 99: 877-885https://doi.org/10.1016/j.ajhg.2016.08.016
- How good are pathogenicity predictors in detecting benign variants?.PLoS Comput Biol. 2019; 15e1006481https://doi.org/10.1371/journal.pcbi.1006481
- The experimentally obtained functional impact assessments of 5′ splice site GT′GC variants differ markedly from those predicted.Curr Genomics. 2020; 21: 56-66https://doi.org/10.2174/1389202921666200210141701
- Germline mutations in ETV6 are associated with thrombocytopenia, red cell macrocytosis and predisposition to lymphoblastic leukemia.Nat Genet. 2015; 47: 535-538https://doi.org/10.1038/ng.3253
- Functional characterization of a germline ETV6 variant associated with inherited thrombocytopenia, acute lymphoblastic leukemia, and salivary gland carcinoma in childhood.Int J Hematol. 2020; 112: 217-222https://doi.org/10.1007/s12185-020-02885-y
- Germline variants in ETV6 underlie reduced platelet formation, platelet dysfunction and increased levels of circulating CD34+ progenitors.Haematologica. 2017; 102: 282-294https://doi.org/10.3324/haematol.2016.147694
- Germline ETV6 mutations in familial thrombocytopenia and hematologic malignancy.Nat Genet. 2015; 47: 180-185https://doi.org/10.1038/ng.3177
- Germline ETV6 mutations confer susceptibility to acute lymphoblastic leukemia and thrombocytopenia.PLoS Genet. 2015; 11e1005262https://doi.org/10.1371/journal.pgen.1005262
- Mutations in STN1 cause Coats plus syndrome and are associated with genomic and telomere defects.J Exp Med. 2016; 213: 1429-1440https://doi.org/10.1084/jem.20151618
- Mutations in CTC1, encoding conserved telomere maintenance component 1, cause Coats plus.Nat Genet. 2012; 44: 338-342https://doi.org/10.1038/ng.1084
- Using deep mutational scanning to benchmark variant effect predictors and identify disease mutations.Mol Syst Biol. 2020; 16e9380https://doi.org/10.15252/msb.20199380
Article info
Publication history
Published online: February 17, 2022
Accepted:
December 14,
2021
Received:
December 14,
2021
Identification
Copyright
© 2021 by American College of Medical Genetics and Genomics. Published by Elsevier Inc.
