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Trainer AH, Goode E, Hoskins CN, Wheeler JCW, Best S. Calibrating variant curation by clinical context based on factors that influence patients' tolerance of uncertainty. Genet Med 2023; 25:100982. [PMID: 37724515 DOI: 10.1016/j.gim.2023.100982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 09/05/2023] [Accepted: 09/11/2023] [Indexed: 09/21/2023] Open
Abstract
PURPOSE Shared decision making manages genomic uncertainty by integrating molecular and clinical uncertainties with patient values to craft a person-centered management plan. Laboratories seek genomic report consistency, agnostic to clinical context. Molecular reports often mask laboratory-managed uncertainties from clinical decision making. Better integration of these uncertainty management strategies requires a nuanced understanding of patients' perceptions and reactions to test uncertainties. We explored patients' tolerance to variant uncertainty in 3 parameters: (1) relative causal significance, (2) risk accuracy, and (3) classification validity. METHOD Deliberative forums were undertaken with 18 patients with predictive testing experience. Uncertainty deliberations were elicited for each parameter. A thematic framework was first developed, and then mapped to whether they justified tolerance to more or less parameter-specific uncertainty. RESULTS Six identified themes mapped to clinical and personal domains. These domains generated opposing forces when calibrating uncertainty. Personal themes justified tolerance of higher uncertainty and clinical themes lower uncertainty. Decision making in uncertainty focused on reducing management regret. Open communication increased tolerance of classification validity and risk accuracy uncertainty. Using these data, we have developed a nascent clinical algorithm integrating molecular uncertainty with clinical context through a targeted communication framework. CONCLUSION Maximizing test utility necessitates context-specific recalibration of uncertainty management and communication.
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Affiliation(s)
- Alison H Trainer
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Department of Medicine, University of Melbourne, Melbourne, VIC, Australia; Department of Genomic Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.
| | - Erin Goode
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Department of Genomic Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Cass N Hoskins
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Department of Genomic Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Jack C W Wheeler
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Department of Genomic Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Stephanie Best
- Department of Health Services Research, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia; Victorian Comprehensive Cancer Centre Alliance, Melbourne, VIC, Australia; Australian Genomics, Murdoch Childrens Research Institute, Melbourne, VIC, Australia
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2
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Costa M, García S A, Pastor O. The consequences of data dispersion in genomics: a comparative analysis of data sources for precision medicine. BMC Med Inform Decis Mak 2023; 23:256. [PMID: 37946154 PMCID: PMC10636939 DOI: 10.1186/s12911-023-02342-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 10/13/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Genomics-based clinical diagnosis has emerged as a novel medical approach to improve diagnosis and treatment. However, advances in sequencing techniques have increased the generation of genomics data dramatically. This has led to several data management problems, one of which is data dispersion (i.e., genomics data is scattered across hundreds of data repositories). In this context, geneticists try to remediate the above-mentioned problem by limiting the scope of their work to a single data source they know and trust. This work has studied the consequences of focusing on a single data source rather than considering the many different existing genomics data sources. METHODS The analysis is based on the data associated with two groups of disorders (i.e., oncology and cardiology) accessible from six well-known genomic data sources (i.e., ClinVar, Ensembl, GWAS Catalog, LOVD, CIViC, and CardioDB). Two dimensions have been considered in this analysis, namely, completeness and concordance. Completeness has been evaluated at two levels. First, by analyzing the information provided by each data source with regard to a conceptual schema data model (i.e., the schema level). Second, by analyzing the DNA variations provided by each data source as related to any of the disorders selected (i.e., the data level). Concordance has been evaluated by comparing the consensus among the data sources regarding the clinical relevance of each variation and disorder. RESULTS The data sources with the highest completeness at the schema level are ClinVar, Ensembl, and CIViC. ClinVar has the highest completeness at the data level data source for the oncology and cardiology disorders. However, there are clinically relevant variations that are exclusive to other data sources, and they must be considered in order to provide the best clinical diagnosis. Although the information available in the data sources is predominantly concordant, discordance among the analyzed data exist. This can lead to inaccurate diagnoses. CONCLUSION Precision medicine analyses using a single genomics data source leads to incomplete results. Also, there are concordance problems that threaten the correctness of the genomics-based diagnosis results.
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Affiliation(s)
- Mireia Costa
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain.
| | - Alberto García S
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
| | - Oscar Pastor
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
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Zukin E, Culver JO, Liu Y, Yang Y, Ricker CN, Hodan R, Sturgeon D, Kingham K, Chun NM, Rowe-Teeter C, Singh K, Zell JA, Ladabaum U, McDonnell KJ, Ford JM, Parmigiani G, Braun D, Kurian AW, Gruber SB, Idos GE. Clinical implications of conflicting variant interpretations in the cancer genetics clinic. Genet Med 2023; 25:100837. [PMID: 37057674 PMCID: PMC10416421 DOI: 10.1016/j.gim.2023.100837] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 04/15/2023] Open
Abstract
PURPOSE The aim of this study was to describe the clinical impact of commercial laboratories issuing conflicting classifications of genetic variants. METHODS Results from 2000 patients undergoing a multigene hereditary cancer panel by a single laboratory were analyzed. Clinically significant discrepancies between the laboratory-provided test reports and other major commercial laboratories were identified, including differences between pathogenic/likely pathogenic and variant of uncertain significance (VUS) classifications, via review of ClinVar archives. For patients carrying a VUS, clinical documentation was assessed for evidence of provider awareness of the conflict. RESULTS Fifty of 975 (5.1%) patients with non-negative results carried a variant with a clinically significant conflict, 19 with a pathogenic/likely pathogenic variant reported in APC or MUTYH, and 31 with a VUS reported in CDKN2A, CHEK2, MLH1, MSH2, MUTYH, RAD51C, or TP53. Only 10 of 28 (36%) patients with a VUS with a clinically significant conflict had a documented discussion by a provider about the conflict. Discrepant counseling strategies were used for different patients with the same variant. Among patients with a CDKN2A variant or a monoallelic MUTYH variant, providers were significantly more likely to make recommendations based on the laboratory-reported classification. CONCLUSION Our findings highlight the frequency of variant interpretation discrepancies and importance of clinician awareness. Guidance is needed on managing patients with discrepant variants to support accurate risk assessment.
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Affiliation(s)
- Elyssa Zukin
- City of Hope National Medical Center, Center for Precision Medicine, Duarte, CA; University of California, Irvine, Irvine, CA
| | - Julie O Culver
- University of Southern California, Keck School of Medicine, Los Angeles, CA
| | - Yuxi Liu
- Dana-Farber Cancer Institute, Boston, MA; Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yunqi Yang
- Dana-Farber Cancer Institute, Boston, MA
| | - Charité N Ricker
- University of Southern California, Keck School of Medicine, Los Angeles, CA
| | - Rachel Hodan
- Stanford University School of Medicine, Stanford, CA
| | - Duveen Sturgeon
- City of Hope National Medical Center, Center for Precision Medicine, Duarte, CA
| | - Kerry Kingham
- Stanford University School of Medicine, Stanford, CA
| | | | | | | | | | - Uri Ladabaum
- Stanford University School of Medicine, Stanford, CA
| | - Kevin J McDonnell
- City of Hope National Medical Center, Center for Precision Medicine, Duarte, CA
| | - James M Ford
- Stanford University School of Medicine, Stanford, CA
| | - Giovanni Parmigiani
- Dana-Farber Cancer Institute, Boston, MA; Harvard T.H. Chan School of Public Health, Boston, MA
| | - Danielle Braun
- Dana-Farber Cancer Institute, Boston, MA; Harvard T.H. Chan School of Public Health, Boston, MA
| | | | - Stephen B Gruber
- City of Hope National Medical Center, Center for Precision Medicine, Duarte, CA
| | - Gregory E Idos
- City of Hope National Medical Center, Center for Precision Medicine, Duarte, CA.
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Berrios C, Hurley EA, Willig L, Thiffault I, Saunders C, Pastinen T, Goggin K, Farrow E. Challenges in genetic testing: clinician variant interpretation processes and the impact on clinical care. Genet Med 2021; 23:2289-2299. [PMID: 34257423 DOI: 10.1038/s41436-021-01267-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 01/24/2023] Open
Abstract
PURPOSE Efforts have been made to standardize laboratory variant interpretation, but clinicians are ultimately tasked with clinical correlation and application of genetic test results in patient care. This study aimed to explore processes clinicians utilize when reviewing and returning genetic test results, and how they impact patient care. METHODS Medical geneticists, genetic counselors, and nongenetics clinicians from two Midwestern states completed surveys (n = 98) and in-depth interviews (n = 29) on practices of reviewing and returning genetic test results. Retrospective chart review (n = 130) examined discordant interpretations and the impact on care. RESULTS Participants reported variable behaviors in both reviewing and returning results based on factors such as confidence, view of role, practice setting, and relationship with the lab. Providers did not report requesting changes to variant classifications from laboratories, but indicated relaying conflicting classifications to patients in some cases. Chart reviews revealed medically impactful differences in interpretation between laboratories and clinicians in 18 (13.8%) records. CONCLUSION Clinician practices for reviewing and integrating genetic test results into patient care vary within and between specialties and impact patient care. Strategies to better incorporate both laboratory and clinician expertise into interpretation of genetic results could result in improved care across providers and settings.
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Affiliation(s)
- Courtney Berrios
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA. .,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.
| | - Emily A Hurley
- University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Health Services and Outcomes Research, Children's Mercy Hospital, Kansas City, MO, USA.,University of Kansas Medical Center, Kansas City, MO, USA
| | - Laurel Willig
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Nephrology, Children's Mercy Hospital, Kansas City, MO, USA
| | - Isabelle Thiffault
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Department of Pathology and Laboratory Medicine, Children's Mercy Hospital, Kansas City, MO, USA
| | - Carol Saunders
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Department of Pathology and Laboratory Medicine, Children's Mercy Hospital, Kansas City, MO, USA
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Pediatrics, Children's Mercy Hospital, Kansas City, MO, USA
| | - Kathy Goggin
- University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Health Services and Outcomes Research, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Pharmacy, Kansas City, MO, USA
| | - Emily Farrow
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, USA.,University of Missouri Kansas City School of Medicine, Kansas City, MO, USA.,Pediatrics, Children's Mercy Hospital, Kansas City, MO, USA
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VanDyke RE, Hashimoto S, Morales A, Pyatt RE, Sturm AC. Impact of variant reclassification in the clinical setting of cardiovascular genetics. J Genet Couns 2020; 30:503-512. [PMID: 33029862 DOI: 10.1002/jgc4.1336] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/25/2020] [Accepted: 08/30/2020] [Indexed: 01/06/2023]
Abstract
Genetic testing for cardiovascular disease (CVD) has advanced over the past ten years, but these advancements have posed new challenges in variant classification. To address these challenges, ACMG/AMP published guidelines for variant interpretation in 2015. This study aimed to determine what impact these guidelines have on variant classification in clinical cardiovascular genetics. A retrospective chart review identified patients who underwent clinical genetic testing and had a variant identified in a gene associated with CVD. For each variant, systematic evidence review was performed and ACMG guidelines were applied for classification. These classifications were compared to those provided on patients' genetic test reports. This study identified 223 unique variants in 237 patients. Seventy-nine (35%) of the variants had classifications that differed from their clinical reports. Twenty-eight (35%) of these reclassifications would have changed medical management recommendations for 38 patients. Application of these guidelines resulted in reclassification for approximately one-third of the variants in this study. Clinicians can have a more active role in the process of variant classification. Variant classifications should be updated over time in the clinical CVD setting due to the impact reclassifications can have on clinical screening recommendations.
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Affiliation(s)
- Rebecca E VanDyke
- Division of Human Genetics, The Ohio State University, Columbus, OH, USA
- Department of Clinical Genetics, Northwestern Medicine Central DuPage Hospital, Winfield, IL, USA
| | - Sayaka Hashimoto
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Ana Morales
- Division of Human Genetics, The Ohio State University, Columbus, OH, USA
| | - Robert E Pyatt
- Division of Human Genetics, The Ohio State University, Columbus, OH, USA
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA
- New Jersey Center for Science, Technology, and Mathematics, Kean University, Union, NJ, USA
| | - Amy C Sturm
- Division of Human Genetics, The Ohio State University, Columbus, OH, USA
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
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Variant interpretation is a component of clinical practice among genetic counselors in multiple specialties. Genet Med 2019; 22:785-792. [PMID: 31754268 PMCID: PMC7127982 DOI: 10.1038/s41436-019-0705-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 11/07/2019] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Genomic testing is routinely utilized across clinical settings and can have significant variant interpretation challenges. The extent of genetic counselor (GC) engagement in variant interpretation in clinical practice is unknown. This study aimed to explore clinical GCs' variant interpretation practice across specialties, understand outcomes of this practice, and identify resource and educational needs. METHODS An online survey was administered to National Society of Genetic Counselors members providing clinical counseling. RESULTS Respondents (n = 239) represented all major clinical specialties. The majority (68%) reported reviewing evidence documented by the laboratory for most (>60%) variants reported; 45.5% report seeking additional evidence. Prenatal GCs were less likely to independently assess reported evidence. Most respondents (67%) report having reached a different conclusion about a variant's classification than the testing laboratory, though infrequently. Time was the most commonly reported barrier (72%) to performing variant interpretation, though the majority (97%) indicated that this practice had an important impact on patient care. When presented with three hypothetical scenarios, evidence typically used for variant interpretation was generally applied correctly. CONCLUSION This study is the first to document variant interpretation practice broadly across clinical GC specialties. Our results suggest that variant interpretation should be considered a practice-based competency for GCs.
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7
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Piccinin C, Panchal S, Watkins N, Kim RH. An update on genetic risk assessment and prevention: the role of genetic testing panels in breast cancer. Expert Rev Anticancer Ther 2019; 19:787-801. [PMID: 31469018 DOI: 10.1080/14737140.2019.1659730] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Introduction: In the past 5 years, multi-gene panels have replaced the practice of BRCA1 and BRCA2 genetic testing in cases of suspected inherited breast cancer susceptibility. A variety of genes have been included on these panels without certainty of their clinical utility. Pertinent current and historical literature was reviewed to provide an up-to-date snapshot of the changing landscape of the use of gene panel tests in the context of breast cancer. Areas covered: Following a recent review of the evidence, 10 genes have been found to have definitive evidence of increased breast cancer risk with variable penetrance. Here, we review the recent changes to the practice of multi-gene panel use in breast cancer diagnoses, including an update on next generation sequencing, alternative models of genetic testing, considerations when ordering these panel tests, and recommendations for management in identified carriers for a variety of genes. A comparison of screening recommendations and carrier frequencies from recent studies is also explored. Lastly, we consider what the future of hereditary oncologic genetic testing holds. Expert opinion: The transition to multi-gene panels in breast cancer patients has improved the likelihood of capturing a rare variant in a well-established gene associated with hereditary breast cancer (e.g. BRCA1 and BRCA2, TP53). There is also an increase in the likelihood of uncovering an uncertain result. This could be in the form of a variant of uncertain significance, or a pathogenic variant in a gene with questionable breast cancer risk-association. Concurrently, a changing landscape of who orders genetic tests will improve access to genetic testing. This pervasiveness of genetic testing must be accompanied with increased genetic literacy in all health-care providers, and access to support from genetics professionals for management of patients and at-risk family members.
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Affiliation(s)
- Carolyn Piccinin
- Familial Breast Cancer Clinic, Mount Sinai Hospital , Toronto , ON , Canada
| | - Seema Panchal
- Familial Breast Cancer Clinic, Mount Sinai Hospital , Toronto , ON , Canada
| | - Nicholas Watkins
- Department of Molecular Genetics, University of Toronto , Toronto , Canada.,Department of Pathology and Laboratory Medicine, Mount Sinai Hospital , Toronto , Canada
| | - Raymond H Kim
- Familial Cancer Clinic, Princess Margaret Cancer Centre, Department of Medicine, University of Toronto , Toronto , Canada
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Wain KE, Palen E, Savatt JM, Shuman D, Finucane B, Seeley A, Challman TD, Myers SM, Martin CL. The value of genomic variant ClinVar submissions from clinical providers: Beyond the addition of novel variants. Hum Mutat 2018; 39:1660-1667. [PMID: 30311381 PMCID: PMC6190575 DOI: 10.1002/humu.23607] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 06/28/2018] [Accepted: 08/02/2018] [Indexed: 12/15/2022]
Abstract
With the increasing use of clinical genomic testing across broad medical disciplines, the need for data sharing and curation efforts to improve variant interpretation is paramount. The National Center for Biotechnology Information (NCBI) ClinVar database facilitates these efforts by serving as a repository for clinical assertions about genomic variants and associations with disease. Most variant submissions are from clinical laboratories, which may lack clinical details. Laboratories may also choose not to submit all variants. Clinical providers can contribute to variant interpretation improvements by submitting variants to ClinVar with their own assertions and supporting evidence. The medical genetics team at Geisinger's Autism & Developmental Medicine Institute routinely reviews the clinical significance of all variants obtained through clinical genomic testing, using published ACMG/AMP guidelines, clinical correlation, and post-test clinical data. We describe the submission of 148 sequence and 155 copy number variants to ClinVar as "provider interpretations." Of these, 192 (63.4%) were novel to ClinVar. Detailed clinical data were provided for 298 (98.3%), and when available, segregation data and follow-up clinical correlation or testing was included. This contribution marks the first large-scale submission from a neurodevelopmental clinical setting and illustrates the importance of clinical providers in collaborative efforts to improve variant interpretation.
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Affiliation(s)
- Karen E Wain
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Emily Palen
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Juliann M Savatt
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Devin Shuman
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Brenda Finucane
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Andrea Seeley
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Thomas D Challman
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Scott M Myers
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
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Wain K. A Commentary on Opportunities for the Genetic Counseling Profession through Genomic Variant Interpretation: Reflections from an Ex-Lab Rat. J Genet Couns 2018. [PMID: 29525931 DOI: 10.1007/s10897-018-0247-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The genetic counseling profession continues to expand and respond to the changing landscape of genomic medicine. "Non-traditional" genetic counseling roles have become more commonplace and the transferability of the genetic counselor skill set has been widely acknowledged, particularly in genetic laboratory settings. As these expanding roles continue to mature, all genetic counselors can benefit by learning and adopting clinically relevant skills, such as genomic variant interpretation, which can be applied to direct patient care. These skills can enrich our patients' understanding of their test results, help ensure quality patient care, and could be useful in positioning genetic counselors as critical members in the medical team as we continue to fully transition into the genomic medicine era.
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Affiliation(s)
- Karen Wain
- Geisinger Health System, Autism & Developmental Medicine Institute, 120 Hamm Drive, Ste 2A, Lewisburg, PA, 17837, USA.
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