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• W2896501664 abstract "HomeCirculation: Cardiovascular Quality and OutcomesVol. 11, No. 10Machine-Assisted Genotype Update System (MAGUS) for Inherited Cardiomyopathies Free AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissionsDownload Articles + Supplements ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toSupplemental MaterialFree AccessResearch ArticlePDF/EPUBMachine-Assisted Genotype Update System (MAGUS) for Inherited Cardiomyopathies Nikolaos Papoutsidakis, MD, PhD, Stephen B. Heitner, MD, Meghan C. Mannello, MS, CGC, Anna Rodonski, MS, William Campbell, MS, CGC, Kylie McElheran, BS and Daniel L. Jacoby, MD Nikolaos PapoutsidakisNikolaos Papoutsidakis Section of Cardiovascular Medicine, Department of Internal Medicine Yale School of Medicine, New Haven, CT (N.P., D.L.J.). Search for more papers by this author , Stephen B. HeitnerStephen B. Heitner Oregon Health and Science University, Knight Cardiovascular Institute Hypertrophic Cardiomyopathy and Cardiogenetics Centers, Portland (S.B.H., M.C.M., K.E.). Search for more papers by this author , Meghan C. MannelloMeghan C. Mannello Oregon Health and Science University, Knight Cardiovascular Institute Hypertrophic Cardiomyopathy and Cardiogenetics Centers, Portland (S.B.H., M.C.M., K.E.). Search for more papers by this author , Anna RodonskiAnna Rodonski Yale New Haven Hospital Heart and Vascular Center, New Haven, CT (A.R.). Search for more papers by this author , William CampbellWilliam Campbell Yale New Haven Hospital Heart and Vascular Center, New Haven, CT (A.R.). Search for more papers by this author , Kylie McElheranKylie McElheran Oregon Health and Science University, Knight Cardiovascular Institute Hypertrophic Cardiomyopathy and Cardiogenetics Centers, Portland (S.B.H., M.C.M., K.E.). Search for more papers by this author and Daniel L. JacobyDaniel L. Jacoby Correspondence to Daniel L. Jacoby, MD, Department of Cardiology, Yale School of Medicine, 333 Cedar St, New Haven, CT 06510. Email E-mail Address: [email protected] Section of Cardiovascular Medicine, Department of Internal Medicine Yale School of Medicine, New Haven, CT (N.P., D.L.J.). Search for more papers by this author Originally published11 Oct 2018https://doi.org/10.1161/CIRCOUTCOMES.118.004835Circulation: Cardiovascular Quality and Outcomes. 2018;11:e004835This article is commented on by the following:MAGUS: A Shared Tool for the Genetic CommunitySee Editorial by Golbus et alGoals and Vision of the ProgramInherited cardiomyopathies (hypertrophic, dilated, and arrhythmogenic) affect a substantial proportion of the global population.1 When a cardiomyopathy patient is identified (the proband), standard of care mandates cascade screening of all at-risk family members. Phenotypic screening is labor intensive and costly,2 requiring repeated office visits and testing. Consequently, genetic screening is now common practice and endorsed by societal guidelines. Once a genetic variant is detected in the proband, the significance of that variant is assessed using standardized criteria.3 A designation is assigned to each variant: pathogenic, likely pathogenic (LP), variant of unknown significance (VUS), or benign. The genetic laboratory that performs the sequencing applies one of these designations in its clinical report to the provider, who then determines the screening strategy (genetic testing or repeated clinical visits) for at-risk family members.Although guidelines exist for variant classification, commercial laboratories often differ in the interpretation of available evidence. These differences can lead to disagreements between laboratories on the classification of a specific variant.4 Additionally, although an individual’s genetic profile does not change over time, available information for accurately assessing a genetic variant’s significance often does. For example, the discovery of additional families that harbor the same genetic changes, the inclusion of racial and ethnic minorities in genetic population databases,5 and advances in functional genomics can influence how we perceive these variations. As evidence evolves, a variant previously thought to be either benign or VUS may subsequently be considered pathogenic and vice versa. This problem will become exponentially worse over time, as the proliferation of clinical programs that use next-generation sequencing (whole exome or genome sequencing) will lead to marked increases in the number of variants requiring reevaluation and possible reclassification. Commercial genetic test panels for inherited cardiomyopathies rarely identify more than 4 to 5 variants per patient, whereas next-generation sequencing routinely comes up with hundreds or thousands. In a busy clinical practice, this presents a nearly insurmountable problem—how is one able to keep abreast with the ever-changing landscape of variant classification and reclassification?ClinVar (https://www.ncbi.nlm.nih.gov/clinvar) is an excellent resource for up-to-date variant classification information that provides access to aggregated laboratory-reported designations for genetic variants. This enables users to identify potential discrepancies between laboratories and collect all available evidence on the variant’s classification to make fully informed decisions.Despite its value, efforts to incorporate ClinVar into clinical practice have been limited by the need for providers to repeatedly search for information on the same variants over time, to keep up-to-date with accumulating data. We envisioned an innovative solution that would (1) ensure up-to-date reassessment of all genetic variants at a reasonable interval and (2) highlight interlaboratory conflicts in a tiered fashion for further investigation. To achieve this, we leveraged the combined power of the ClinVar data aggregator and our internal Quality Assurance Database (QAD), to create a semiautomated tool for the identification of inconsistencies in classification.Design and Implementation of the InitiativeOur initiative, which we have named machine-assisted genotype update system (MAGUS), comprises 3 steps to be repeated at reasonable (suggested, 6 months) intervals (Figure):Download figureDownload PowerPointFigure. Schematic of the machine-assisted genotype update system (MAGUS) pathway, as implemented at our institutions. The first 2 steps containing a gear icon are performed by automated computer scripts (MAGUS step A), whereas the rest of the pathway involves Conflict Resolution meetings of care providers (MAGUS steps B and C). Numbers reflect combined cases from both institutions. LP indicates likely pathogenic; P, pathogenic; and VUS, variant of unknown significance.Cross-check our population’s genetic variant designations against current ClinVar aggregated data, using a semiautomated informatics system, and assign a conflict rank score.Readjudicate high-conflict variants immediately and implement appropriate screening and communication strategies as per the American College of Medical Genetics.3Assess and readjudicate moderate conflict variants at the time of the next follow-up visit.Semiautomated ClinVar Queries and Conflict Rank Scoring (MAGUS Step A)ClinVar offers programmatic access to its records, meaning that it is possible to send a search command to retrieve information about an arbitrary number of specific variants, without having to visit the site through a web browser and manually perform a search for each. Detailed instructions on how to do this can be found on the ClinVar website https://www.ncbi.nlm.nih.gov/clinvar/docs/maintenance_use/#api. This publicly available functionality does not require proprietary software or high-end infrastructure to access.At our institutions, genetic test results (variants and their significance as provided by the laboratory) are stored at the QAD, based on the FileMaker platform (FileMaker, Inc). We created a script that (1) looped through each genetic record in our QAD dataset; (2) sent a search command to ClinVar for each record to retrieve the most recent designation (pathogenic, LP, VUS, and benign); and (3) compared the designations noted in ClinVar and internal QAD, assigning a conflict score as outlined below:Pathogenic or LP versus VUS or benign (ClinVar/QAD disagreement), score of 3.ClinVar conflicting interpretations of pathogenicity (ie, disagreement within ClinVar), score of 2.Not found on ClinVar (ie, no relevant ClinVar entry), score of 1.Agreement between ClinVar/QAD designations, score of 0.The overall process (ClinVar queries and conflict scoring) takes about 6 minutes per 1000 variants. Because our database is stored on an HIPAA-compliant server, search queries were performed over secure connections. No patient identifiers are required to execute either script; therefore, there was no risk to our patients’ protected health information.Conflict Adjudication and Impact on Patient Care (MAGUS Steps B and C)The last 2 steps of the MAGUS initiative consist of weekly Conflict Resolution meetings, where assessment of identified genetic conflicts is tiered according to score (Figure). Variants with a score of 3, indicating a direct disagreement over pathogenicity between ClinVar and our local database, require immediate reassessment. For variants where pathogenicity according to ClinVar is not firmly established (score of 2, conflicting interpretations), cases are discussed at future Conflict Resolution meetings, as patients revisit our clinic. If new evidence is deemed important enough to warrant reassessment, the same algorithm is used as in tier 3 conflicts (Figure). For variants with scores of 1 (not found in ClinVar) or 0 (assessment agreement), no action is taken.Success of the InitiativeThe MAGUS initiative was evaluated at 2 centers that provide care to patients with inherited cardiomyopathies, with an emphasis on hypertrophic cardiomyopathy (Hypertrophic Cardiomyopathy Centers of Excellence), the Yale Inherited Cardiomyopathy Program and Oregon Health and Science University Knight Cardiovascular Institute Hypertrophic Cardiomyopathy and Cardiogenetics Centers. Combined, these provide care to >2500 patients with cardiomyopathy, of whom 1082 have had genetic testing from 2011 until January 1, 2018. Testing has uncovered a total of 1138 variants (346 pathogenic or LP, 526 VUS, and 266 benign).During a 7-year period, our programs’ reliance on commercial genetics laboratory-initiated reassessment has led to no conflict identification and no genetic diagnosis reassignment. On implementation of MAGUS across both institutions, a total of 22 major conflicts were discovered (pathogenic/LP or VUS with a reverse ClinVar classification; conflict score of 3), and 198 variants were flagged as having conflicting interpretations of pathogenicity (conflict score of 2). Of the 22 patients with major conflicts, 12 had hypertrophic cardiomyopathy, 5 had familial dilated cardiomyopathy, 2 had arrhythmogenic cardiomyopathy, whereas the remaining 3 were diagnosed with left ventricular noncompaction, long-QT syndrome, and mitochondrial disease, respectively. Based on MAGUS review, 11 of 22 patients were deemed to be in need of a different family screening strategy and were contacted and informed about this. The potential clinical impact was the greatest for the families of 9 of these 11 patients, who had variants that were classified originally as pathogenic but were reclassified as VUS. First-degree relatives who had previously tested negative for the gene required reengagement in routine clinical visits and imaging tests from which they had previously been dismissed. The remaining 2 changes in family screening strategy resulted from reclassification of VUS to pathogenic, allowing cascade genetic screening and release from prospective follow-up of those testing negative. Of the remaining 11 patients with major conflicts, 2 had conflicts in variants affecting noncardiomyopathy-related genes and were referred to a specialized genetics program for adjudication, whereas the rest, after careful review, were determined to lack compelling evidence for changing their family screening strategy.The importance of the MAGUS initiative lies not only in effortlessly identifying current conflicts between ClinVar and local records but also in that any future change in variant pathogenicity will be promptly detected and presented to the clinical team. The simplicity of this intervention, together with the peace of mind it offers providers, has led to its integration in our standard workflow. Our respective institutions have initiated a full MAGUS database review every 6 months, which takes only a few minutes with the help of this informatics tool. The discrepancies are then highlighted by our genetic counselors and brought up for discussion at the weekly Conflict Resolution meetings.Because MAGUS inherently depends on the quality and quantity of data available on ClinVar, ongoing ClinVar support by public institutions and genetic testing companies is critical for long-term success. We think that implementation of MAGUS will be a step in this direction. Commercial genetic testing laboratories will benefit from a symbiotic relationship between community users and other laboratories by ensuring timely updates to ClinVar, which can then be mined for information with the help of MAGUS.Potential Challenges in MAGUS ImplementationAlthough this initiative has been a success at our institutions, certain challenges may arise during implementation. On the technical side, variant annotations that do not conform to the ClinVar standard (Human Genome Variation Society) may erroneously return a not-found-on-ClinVar result. It is prudent to ensure that these variants are indeed missing from ClinVar by performing manual searches using wider filters, such as wild cards. Additionally, it is possible that patients who are being informed about a change in their screening strategy may become confused or apprehensive, especially if they underwent genotyping in the remote past. Although this has not been our experience to date, care should be taken to thoroughly explain to patients why this happened and what it means for them and their families.Translation to Other SettingsTo implement MAGUS in other institutions, providers would only need a list of their patients’ genetic variants and their reported classification, information technology support for adding ClinVar query scripts (Data Supplement) to the local patient database, and a routine process for assessing MAGUS-uncovered conflicts. Instead of electronic medical record integration, providers may choose to use the free MAGUS online tool (https://is.gd/MAGUS). Each step in our initiative can be potentially modified to increase efficiency and yield or to better suit local practices. ClinVar allows access to granular genetic variant data, including the number of laboratories that are in agreement and date of assessment by each laboratory, and this information can be incorporated into a more sophisticated conflict scoring system.This pathway is relevant to all clinical settings where genetic testing plays a part in patient management. ClinVar provides data on a broad scope of genetic diseases, not solely cardiac diagnoses. Because the MAGUS algorithm is not selective for specific genes or variants when accessing ClinVar, it can be used as is to efficiently keep providers up-to-date on pathogenicity assessments for any previously discovered genetic variant, in any medical field. There is clearly a growing need for this in multiple medical specialties.6Summary of the Experience, Future Directions, and ChallengesAs we continue to incorporate genotyping into our clinical practice, we learn more about the clinical impact of the variants we discover. This requires the assistance of high-throughput information technologies to maintain contemporary screening practices for the patients we care for. We have created a working solution for this challenge. Further, we have successfully implemented this solution at 2 different institutions, demonstrating that not only is this feasible but also is potentially applicable to other institutions. We also envision that a similar cross talk may be pertinent to other National Institutes of Health public resources and local EMRs. Our tools, from stethoscope to cloud computing, are evolving. The challenge, at the age of big data in medicine, is to remember that decision-making ultimately falls on the shoulders of caregivers—a responsibility that cannot be delegated to machines or algorithms. This makes the careful review of accumulated data by a team of dedicated professionals the most important part of the process.AcknowledgmentsWe would like to express our gratitude to Jeptha P. Curtis, MD, and Michael Singer, MD, PhD, for their advice and support.Sources of FundingThis research was supported by the Joshua C. Gibson, MD, Memorial Fund for Heart Research.DisclosuresNone.FootnotesThe Data Supplement is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCOUTCOMES.118.004835.Correspondence to Daniel L. Jacoby, MD, Department of Cardiology, Yale School of Medicine, 333 Cedar St, New Haven, CT 06510. Email daniel.[email protected]eduReferences1. Maron BJ, Towbin JA, Thiene G, Antzelevitch C, Corrado D, Arnett D, Moss AJ, Seidman CE, Young JB; American Heart Association; Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; Council on Epidemiology and Prevention. Contemporary definitions and classification of the cardiomyopathies: an American Heart Association Scientific Statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention.Circulation. 2006; 113:1807–1816. doi: 10.1161/CIRCULATIONAHA.106.174287LinkGoogle Scholar2. Wordsworth S, Leal J, Blair E, Legood R, Thomson K, Seller A, Taylor J, Watkins H. DNA testing for hypertrophic cardiomyopathy: a cost-effectiveness model.Eur Heart J. 2010; 31:926–935. doi: 10.1093/eurheartj/ehq067CrossrefMedlineGoogle Scholar3. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL; ACMG Laboratory Quality Assurance Committee. 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; 17:405–424. doi: 10.1038/gim.2015.30CrossrefMedlineGoogle Scholar4. Furqan A, Arscott P, Girolami F, Cirino AL, Michels M, Day SM, Olivotto I, Ho CY, Ashley E, Green EM, Caleshu C; SHaRe Consortium. Care inspecializedcenters anddatasharingincreaseagreement inhypertrophiccardiomyopathygenetictestinterpretation.Circ Cardiovasc Genet. 2017; 10:e001700. doi: 10.1161/CIRCGENETICS.116.001700LinkGoogle Scholar5. Manrai AK, Funke BH, Rehm HL, Olesen MS, Maron BA, Szolovits P, Margulies DM, Loscalzo J, Kohane IS. Geneticmisdiagnoses and thepotential forhealthdisparities.N Engl J Med. 2016; 375:655–665. doi: 10.1056/NEJMsa1507092CrossrefMedlineGoogle Scholar6. Gradishar W, Johnson K, Brown K, Mundt E, Manley S. Clinicalvariantclassification:acomparison ofpublicdatabases and acommercialtestinglaboratory.Oncologist. 2017; 22:797–803. doi: 10.1634/theoncologist.2016-0431CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Yogasundaram H, Alhumaid W, Dzwiniel T, Christian S and Oudit G (2021) Cardiomyopathies and Genetic Testing in Heart Failure: Role in Defining Phenotype-Targeted Approaches and Management, Canadian Journal of Cardiology, 10.1016/j.cjca.2021.01.016, 37:4, (547-559), Online publication date: 1-Apr-2021. Masri A, Nazer B, Al-Rashdan L, Mannello M, Fischer K, Akhavein R, Divanji P, Song H and Heitner S (2021) Thirty Controversies and Considerations in Hypertrophic Cardiomyopathy, Structural Heart, 10.1080/24748706.2020.1844926, 5:1, (39-54), Online publication date: 1-Jan-2021. Golbus J, Nallamothu B and Deo R (2018) MAGUS: A Shared Tool for the Genetic Community, Circulation: Cardiovascular Quality and Outcomes, 11:10, Online publication date: 1-Oct-2018.Related articlesMAGUS: A Shared Tool for the Genetic CommunityJessica R. Golbus, et al. Circulation: Cardiovascular Quality and Outcomes. 2018;11 October 2018Vol 11, Issue 10 Advertisement Article InformationMetrics © 2018 American Heart Association, Inc.https://doi.org/10.1161/CIRCOUTCOMES.118.004835PMID: 30354577 Originally publishedOctober 11, 2018 Keywordscomputational biologyhumansgenetic testingcardiomyopathiesgeneticsPDF download Advertisement SubjectsCardiomyopathyCost-EffectivenessPrecision MedicineQuality and Outcomes" @default.
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