Literature DB >> 25834947

The challenge of comprehensive and consistent sequence variant interpretation between clinical laboratories.

Melanie G Pepin1, Mitzi L Murray1,2, Samuel Bailey1, Dru Leistritz-Kessler1, Ulrike Schwarze1, Peter H Byers1,2.   

Abstract

PURPOSE: Genetic testing has shifted from academic laboratories with expertise in specific genes to commercial laboratories that offer tests of a diverse array of genes. The purpose of this comparative study was to determine whether one academic laboratory's model of variant interpretation is similar to that of several commercial laboratories.
METHODS: The Collagen Diagnostic Laboratory (CDL) received, over a 14-month period, 38 requests to interpret variants originally identified by an outside laboratory (OL). The interpretations by the OL and CDL were compared and discrepancies were assessed.
RESULTS: Interpretations from the OL and CDL were concordant in 11 inquiries (29%); discrepancies were moderate in 11 instances (29%) and significant in 16 (42%). Factors that caused discrepancies included the following: (i) private data were not shared in a public database (n = 9); (ii) publicly available allele frequency data were not referenced and used as evidence (n = 5); and (iii) important aspects of protein structure and function were not taken into account (n = 13).
CONCLUSION: Comprehensive interpretation of sequence variants depends on good functional tests and well-curated variant databases. Provision of clinical information to the clinical laboratory, mandatory submission of identified variants with phenotype data to common resources, and collaboration between clinical laboratories and recognized experts is likely to improve consistency in variant interpretation among clinical laboratories.Genet Med 18 1, 20-24.

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Year:  2015        PMID: 25834947     DOI: 10.1038/gim.2015.31

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  19 in total

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Journal:  Nucleic Acids Res       Date:  1998-01-01       Impact factor: 16.971

2.  Annotating DNA variants is the next major goal for human genetics.

Authors:  Garry R Cutting
Journal:  Am J Hum Genet       Date:  2014-01-02       Impact factor: 11.025

3.  ENIGMA--evidence-based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes.

Authors:  Amanda B Spurdle; Sue Healey; Andrew Devereau; Frans B L Hogervorst; Alvaro N A Monteiro; Katherine L Nathanson; Paolo Radice; Dominique Stoppa-Lyonnet; Sean Tavtigian; Barbara Wappenschmidt; Fergus J Couch; David E Goldgar
Journal:  Hum Mutat       Date:  2011-11-03       Impact factor: 4.878

Review 4.  Update of the UMD-FBN1 mutation database and creation of an FBN1 polymorphism database.

Authors:  Gwenaëlle Collod-Béroud; Saga Le Bourdelles; Lesley Ades; Leena Ala-Kokko; Patrick Booms; Maureen Boxer; Anne Child; Paolo Comeglio; Anne De Paepe; James C Hyland; Katerine Holman; Ilkka Kaitila; Bart Loeys; Gabor Matyas; Lieve Nuytinck; Leena Peltonen; Terhi Rantamaki; Peter Robinson; Beat Steinmann; Claudine Junien; Christophe Béroud; Catherine Boileau
Journal:  Hum Mutat       Date:  2003-09       Impact factor: 4.878

5.  Predicting functional effect of human missense mutations using PolyPhen-2.

Authors:  Ivan Adzhubei; Daniel M Jordan; Shamil R Sunyaev
Journal:  Curr Protoc Hum Genet       Date:  2013-01

6.  A new locus-specific database (LSDB) for mutations in the TGFBR2 gene: UMD-TGFBR2.

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Journal:  Hum Mutat       Date:  2008-01       Impact factor: 4.878

7.  Variability in interpreting and reporting copy number changes detected by array-based technology in clinical laboratories.

Authors:  Karen D Tsuchiya; Lisa G Shaffer; Swaroop Aradhya; Julie M Gastier-Foster; Ankita Patel; M Katharine Rudd; Julie Sanford Biggerstaff; Warren G Sanger; Stuart Schwartz; James H Tepperberg; Erik C Thorland; Beth A Torchia; Arthur R Brothman
Journal:  Genet Med       Date:  2009-12       Impact factor: 8.822

8.  SDS, a structural disruption score for assessment of missense variant deleteriousness.

Authors:  Thanawadee Preeprem; Greg Gibson
Journal:  Front Genet       Date:  2014-04-21       Impact factor: 4.599

9.  An integrated map of genetic variation from 1,092 human genomes.

Authors:  Goncalo R Abecasis; Adam Auton; Lisa D Brooks; Mark A DePristo; Richard M Durbin; Robert E Handsaker; Hyun Min Kang; Gabor T Marth; Gil A McVean
Journal:  Nature       Date:  2012-11-01       Impact factor: 49.962

10.  ClinVar: public archive of relationships among sequence variation and human phenotype.

Authors:  Melissa J Landrum; Jennifer M Lee; George R Riley; Wonhee Jang; Wendy S Rubinstein; Deanna M Church; Donna R Maglott
Journal:  Nucleic Acids Res       Date:  2013-11-14       Impact factor: 16.971

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  26 in total

Review 1.  The current state of clinical interpretation of sequence variants.

Authors:  Derick C Hoskinson; Adrian M Dubuc; Heather Mason-Suares
Journal:  Curr Opin Genet Dev       Date:  2017-01-31       Impact factor: 5.578

Review 2.  First Responder to Genomic Information: A Guide for Primary Care Providers.

Authors:  Susanne B Haga
Journal:  Mol Diagn Ther       Date:  2019-08       Impact factor: 4.074

3.  Variability in gene-based knowledge impacts variant classification: an analysis of FBN1 missense variants in ClinVar.

Authors:  Linnea M Baudhuin; Michelle L Kluge; Katrina E Kotzer; Susan A Lagerstedt
Journal:  Eur J Hum Genet       Date:  2019-06-21       Impact factor: 4.246

4.  Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory.

Authors:  William Gradishar; KariAnne Johnson; Krystal Brown; Erin Mundt; Susan Manley
Journal:  Oncologist       Date:  2017-04-13

5.  Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine.

Authors:  Kathryn B Garber; Lisa M Vincent; John J Alexander; Lora J H Bean; Sherri Bale; Madhuri Hegde
Journal:  Am J Hum Genet       Date:  2016-10-27       Impact factor: 11.025

6.  Ability of Patients to Distinguish Among Cardiac Genomic Variant Subclassifications.

Authors:  Lydia D Hellwig; Barbara B Biesecker; Katie L Lewis; Leslie G Biesecker; Cynthia A James; William M P Klein
Journal:  Circ Genom Precis Med       Date:  2018-06

7.  Implementing the VMC Specification to Reduce Ambiguity in Genomic Variant Representation.

Authors:  Michael Watkins; Shawn Rynearson; Alex Henrie; Karen Eilbeck
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

8.  From the laboratory to the clinic: sharing BRCA VUS reclassification tools with practicing genetics professionals.

Authors:  Bianca M Augusto; Paige Lake; Courtney L Scherr; Fergus J Couch; Noralane M Lindor; Susan T Vadaparampil
Journal:  J Community Genet       Date:  2017-11-09

9.  Expert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss.

Authors:  Andrea M Oza; Marina T DiStefano; Sarah E Hemphill; Brandon J Cushman; Andrew R Grant; Rebecca K Siegert; Jun Shen; Alex Chapin; Nicole J Boczek; Lisa A Schimmenti; Jaclyn B Murry; Linda Hasadsri; Kiyomitsu Nara; Margaret Kenna; Kevin T Booth; Hela Azaiez; Andrew Griffith; Karen B Avraham; Hannie Kremer; Heidi L Rehm; Sami S Amr; Ahmad N Abou Tayoun
Journal:  Hum Mutat       Date:  2018-11       Impact factor: 4.878

Review 10.  Defining the Clinical Value of a Genomic Diagnosis in the Era of Next-Generation Sequencing.

Authors:  Natasha T Strande; Jonathan S Berg
Journal:  Annu Rev Genomics Hum Genet       Date:  2016-05-26       Impact factor: 8.929

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