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Dive into the research topics where Lisa M. Vincent is active.

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Featured researches published by Lisa M. Vincent.


Genetics in Medicine | 2017

Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar

Steven M. Harrison; Jill S. Dolinsky; Amy Knight Johnson; Tina Pesaran; Danielle R. Azzariti; Sherri J. Bale; Elizabeth C. Chao; Soma Das; Lisa M. Vincent; Heidi L. Rehm

Purpose:Data sharing through ClinVar offers a unique opportunity to identify interpretation differences between laboratories. As part of a ClinGen initiative, four clinical laboratories (Ambry, GeneDx, Partners Healthcare Laboratory for Molecular Medicine, and University of Chicago Genetic Services Laboratory) collaborated to identify the basis of interpretation differences and to investigate if data sharing and reassessment resolve interpretation differences by analyzing a subset of variants.Methods:ClinVar variants with submissions from at least two of the four participating laboratories were compared. For a subset of identified differences, laboratories documented the basis for discordance, shared internal data, independently reassessed with the American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG-AMP) guidelines, and then compared interpretations.Results:At least two of the participating laboratories interpreted 6,169 variants in ClinVar, of which 88.3% were initially concordant. Laboratories reassessed 242/724 initially discordant variants, of which 87.2% (211) were resolved by reassessment with current criteria and/or internal data sharing; 12.8% (31) of reassessed variants remained discordant owing to differences in the application of the ACMG-AMP guidelines.Conclusion:Participating laboratories increased their overall concordance from 88.3 to 91.7%, indicating that sharing variant interpretations in ClinVar—thereby allowing identification of differences and motivation to resolve those differences—is critical to moving toward more consistent variant interpretations.Genet Med advance online publication 09 March 2017


American Journal of Human Genetics | 2016

Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine

Kathryn B. Garber; Lisa M. Vincent; John J. Alexander; Lora J. H. Bean; Sherri J. Bale; Madhuri Hegde

Accurate interpretation of DNA sequence variation is a prerequisite for implementing personalized medicine. Discrepancies in interpretation between testing laboratories impede the effective use of genetic test results in clinical medicine. To better understand the underpinnings of these discrepancies, we quantified differences in variant classification internally over time and those between our diagnostic laboratory and other laboratories and resources. We assessed the factors that contribute to these discrepancies and those that facilitate their resolution. Our process resolved 72% of nearly 300 discrepancies between pairs of laboratories to within a one-step classification difference and identified key sources of data that facilitate changes in variant interpretation. The identification and harmonization of variant discrepancies will maximize the clinical use of genetic information; these processes will be fostered by the accumulation of additional population data as well as the sharing of data between diagnostic laboratories.


Genetics in Medicine | 2018

Adaptation and validation of the ACMG/AMP variant classification framework for MYH7 -associated inherited cardiomyopathies: recommendations by ClinGen’s Inherited Cardiomyopathy Expert Panel

Melissa A. Kelly; Colleen Caleshu; Ana Morales; Jillian G Buchan; Zena Wolf; Steven M. Harrison; Stuart A. Cook; Mitchell W Dillon; John Garcia; Eden Haverfield; Jan D. H. Jongbloed; Daniela Macaya; Arjun K. Manrai; Kate M. Orland; Gabriele Richard; Katherine G. Spoonamore; Matthew Thomas; K Thomson; Lisa M. Vincent; Roddy Walsh; Hugh Watkins; Nicola Whiffin; Jodie Ingles; J. Peter van Tintelen; Christopher Semsarian; James S. Ware; Ray E. Hershberger; Birgit Funke

PurposeIntegrating genomic sequencing in clinical care requires standardization of variant interpretation practices. The Clinical Genome Resource has established expert panels to adapt the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification framework for specific genes and diseases. The Cardiomyopathy Expert Panel selected MYH7, a key contributor to inherited cardiomyopathies, as a pilot gene to develop a broadly applicable approach.MethodsExpert revisions were tested with 60 variants using a structured double review by pairs of clinical and diagnostic laboratory experts. Final consensus rules were established via iterative discussions.ResultsAdjustments represented disease-/gene-informed specifications (12) or strength adjustments of existing rules (5). Nine rules were deemed not applicable. Key specifications included quantitative frameworks for minor allele frequency thresholds, the use of segregation data, and a semiquantitative approach to counting multiple independent variant occurrences where fully controlled case-control studies are lacking. Initial inter-expert classification concordance was 93%. Internal data from participating diagnostic laboratories changed the classification of 20% of the variants (n = 12), highlighting the critical importance of data sharing.ConclusionThese adapted rules provide increased specificity for use in MYH7-associated disorders in combination with expert review and clinical judgment and serve as a stepping stone for genes and disorders with similar genetic and clinical characteristics.


Genetics in Medicine | 2018

ClinGen’s RASopathy Expert Panel consensus methods for variant interpretation

Bruce D. Gelb; Hélène Cavé; Mitchell W Dillon; Karen W. Gripp; Jennifer A. Lee; Heather Mason-Suares; Katherine A. Rauen; Bradley Williams; Martin Zenker; Lisa M. Vincent

PurposeStandardized and accurate variant assessment is essential for effective medical care. To that end, Clinical Genome (ClinGen) Resource clinical domain working groups (CDWGs) are systematically reviewing disease-associated genes for sufficient evidence to support disease causality and creating disease-specific specifications of American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG-AMP) guidelines for consistent and accurate variant classification.MethodsThe ClinGen RASopathy CDWG established an expert panel to curate gene information and generate gene- and disease-specific specifications to ACMG-AMP variant classification framework. These specifications were tested by classifying 37 exemplar pathogenic variants plus an additional 66 variants in ClinVar distributed across nine RASopathy genes.ResultsRASopathy-related specifications were applied to 16 ACMG-AMP criteria, with 5 also having adjustable strength with availability of additional evidence. Another 5 criteria were deemed not applicable. Key adjustments to minor allele frequency thresholds, multiple de novo occurrence events and/or segregation, and strength adjustments impacted 60% of variant classifications. Unpublished case-level data from participating laboratories impacted 45% of classifications supporting the need for data sharing.ConclusionRAS-specific ACMG-AMP specifications optimized the utility of available clinical evidence and Ras/MAPK pathway–specific characteristics to consistently classify RASopathy-associated variants. These specifications highlight how grouping genes by shared features promotes rapid multigenic variant assessment without sacrificing specificity and accuracy.


American Journal of Medical Genetics Part A | 2017

Noonan syndrome in diverse populations

Paul Kruszka; Antonio R. Porras; Yonit A Addissie; Angélica Moresco; Sofia Medrano; Gary T. K. Mok; Gordon Ka Chun Leung; Cedrik Tekendo-Ngongang; Annette Uwineza; Meow-Keong Thong; Premala Muthukumarasamy; Engela Honey; Ekanem N. Ekure; Ogochukwu J. Sokunbi; Nnenna Kalu; Kelly L. Jones; Julie D. Kaplan; Omar A. Abdul-Rahman; Lisa M. Vincent; Amber Love; Khadija Belhassan; Karim Ouldim; Ihssane El Bouchikhi; Anju Shukla; Katta M. Girisha; Siddaramappa J. Patil; Nirmala D. Sirisena; Vajira H. W. Dissanayake; C. Sampath Paththinige; Rupesh Mishra

Noonan syndrome (NS) is a common genetic syndrome associated with gain of function variants in genes in the Ras/MAPK pathway. The phenotype of NS has been well characterized in populations of European descent with less attention given to other groups. In this study, individuals from diverse populations with NS were evaluated clinically and by facial analysis technology. Clinical data and images from 125 individuals with NS were obtained from 20 countries with an average age of 8 years and female composition of 46%. Individuals were grouped into categories of African descent (African), Asian, Latin American, and additional/other. Across these different population groups, NS was phenotypically similar with only 2 of 21 clinical elements showing a statistically significant difference. The most common clinical characteristics found in all population groups included widely spaced eyes and low‐set ears in 80% or greater of participants, short stature in more than 70%, and pulmonary stenosis in roughly half of study individuals. Using facial analysis technology, we compared 161 Caucasian, African, Asian, and Latin American individuals with NS with 161 gender and age matched controls and found that sensitivity was equal to or greater than 94% for all groups, and specificity was equal to or greater than 90%. In summary, we present consistent clinical findings from global populations with NS and additionally demonstrate how facial analysis technology can support clinicians in making accurate NS diagnoses. This work will assist in earlier detection and in increasing recognition of NS throughout the world.


Human Mutation | 2018

Assessing the gene-disease association of 19 genes with the RASopathies using the ClinGen gene curation framework

Andrew R. Grant; Brandon J. Cushman; Hélène Cavé; Mitchell W. Dillon; Bruce D. Gelb; Karen W. Gripp; Jennifer A. Lee; Heather Mason-Suares; Katherine A. Rauen; Marco Tartaglia; Lisa M. Vincent; Martin Zenker

The RASopathies are a complex group of conditions regarding phenotype and genetic etiology. The ClinGen RASopathy Expert Panel (RAS EP) assessed published and other publicly available evidence supporting the association of 19 genes with RASopathy conditions. Using the semiquantitative literature curation method developed by the ClinGen Gene Curation Working Group, evidence for each gene was curated and scored for Noonan syndrome (NS), Costello syndrome, cardiofaciocutaneous syndrome, NS with multiple lentigines, and Noonan‐like syndrome with loose anagen hair.


Human Mutation | 2018

ClinGen Variant Curation Expert Panel experiences and standardized processes for disease and gene-level specification of the ACMG/AMP guidelines for sequence variant interpretation

Edgar A. Rivera-Muñoz; Laura V. Milko; Steven M. Harrison; Danielle R. Azzariti; C. Lisa Kurtz; Kristy Lee; Jessica L. Mester; Meredith A. Weaver; Erin Currey; William J. Craigen; Charis Eng; Birgit Funke; Madhuri Hegde; Ray E. Hershberger; Rong Mao; Robert D. Steiner; Lisa M. Vincent; Christa Lese Martin; Sharon E. Plon; Erin M. Ramos; Heidi L. Rehm; Michael S. Watson; Jonathan S. Berg

Genome‐scale sequencing creates vast amounts of genomic data, increasing the challenge of clinical sequence variant interpretation. The demand for high‐quality interpretation requires multiple specialties to join forces to accelerate the interpretation of sequence variant pathogenicity. With over 600 international members including clinicians, researchers, and laboratory diagnosticians, the Clinical Genome Resource (ClinGen), funded by the National Institutes of Health, is forming expert groups to systematically evaluate variants in clinically relevant genes. Here, we describe the first ClinGen variant curation expert panels (VCEPs), development of consistent and streamlined processes for establishing new VCEPs, and creation of standard operating procedures for VCEPs to define application of the ACMG/AMP guidelines for sequence variant interpretation in specific genes or diseases. Additionally, ClinGen has created user interfaces to enhance reliability of curation and a Sequence Variant Interpretation Working Group (SVI WG) to harmonize guideline specifications and ensure consistency between groups. The expansion of VCEPs represents the primary mechanism by which curation of a substantial fraction of genomic variants can be accelerated and ultimately undertaken systematically and comprehensively. We welcome groups to utilize our resources and become involved in our effort to create a publicly accessible, centralized resource for clinically relevant genes and variants.


Human Mutation | 2018

Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach

Steven M. Harrison; Jill S. Dolinksy; Wenjie Chen; Christin D. Collins; Soma Das; Joshua L. Deignan; Kathryn B. Garber; John Garcia; Olga Jarinova; Amy Knight Johnson; Juha W. Koskenvuo; Hane Lee; Rong Mao; Rebecca Mar-Heyming; Andrew S. McFaddin; Krista Moyer; Narasimhan Nagan; Stefan Rentas; Avni Santani; Eija H. Seppälä; Brian H. Shirts; Timothy Tidwell; Scott Topper; Lisa M. Vincent; Kathy M. B. Vinette; Heidi L. Rehm

ClinVar provides open access to variant classifications shared from many clinical laboratories. Although most classifications are consistent across laboratories, classification differences exist. To facilitate resolution of classification differences on a large scale, clinical laboratories were encouraged to reassess outlier classifications of variants with medically significant differences (MSDs). Outliers were identified by first comparing ClinVar submissions from 41 clinical laboratories to detect variants with MSDs between the laboratories (650 variants). Next, MSDs were filtered for variants with ≥3 classifications (244 variants), of which 87.6% (213 variants) had a majority consensus in ClinVar, thus allowing for identification of outlier classifications in need of reassessment. Laboratories with outlier classifications were sent a custom report and encouraged to reassess variants. Results were returned for 204 (96%) variants, of which 62.3% (127) were resolved. Of those 127, 64.6% (82) were resolved due to reassessment prompted by this study and 35.4% (45) resolved by a previously completed reassessment. This study demonstrates a scalable approach to classification resolution and capitalizes on the value of data sharing within ClinVar. These activities will help the community move toward more consistent variant classifications, which will improve the care of patients with, or at risk for, genetic disorders.


Cold Spring Harb Mol Case Stud | 2018

Reclassification of the BRAF p.Ile208Val variant by case-level data sharing

Andrew R. Grant; Sarah E. Hemphill; Lisa M. Vincent; Heidi L. Rehm

The ClinVar database is a useful tool for patients and physicians to view variant interpretations submitted by clinical and nonclinical labs. However, variants of uncertain significance (VUS) in ClinVar can pose a significant burden on patients. If possible, it is important to resolve discrepancies and uncertainties surrounding interpreted variants. Here we highlight a case of a family who received a report of a variant (c.622A>G, p.Ile208Val) in BRAF following prenatal RASopathy testing. The variant had been previously classified by our laboratory as a VUS, so the mother contacted our laboratory via ClinVar for further information, which prompted reevaluation of the variant. Multiple sources of case-level data as well as the presence of the variant in the general population yielded sufficient evidence to reclassify the variant as likely benign. This reclassification alleviated significant concern for the family, and the child was born healthy with no clinical manifestations of Noonan syndrome or a RASopathy.


American Journal of Obstetrics and Gynecology | 2014

148: Increased nuchal translucency and normal karyotype: value of additional testing

Jaclyn Coletta Lucas; Elizabeth Kramer Dugan; Vimla Aggarwal; Sherri J. Bale; Aileen Frayna; Melanie Hussong; Vaidehi Jobanputra; Gabi Richard; Lisa M. Vincent; Bradley Williams; Jeanne Meck; Ronald J. Wapner; Brynn Levy

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Bruce D. Gelb

Icahn School of Medicine at Mount Sinai

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