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

Authors :
Harrison SM
Dolinksy JS
Chen W
Collins CD
Das S
Deignan JL
Garber KB
Garcia J
Jarinova O
Knight Johnson AE
Koskenvuo JW
Lee H
Mao R
Mar-Heyming R
McFaddin AS
Moyer K
Nagan N
Rentas S
Santani AB
Seppälä EH
Shirts BH
Tidwell T
Topper S
Vincent LM
Vinette K
Rehm HL
Source :
Human mutation [Hum Mutat] 2018 Nov; Vol. 39 (11), pp. 1641-1649.
Publication Year :
2018

Abstract

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.<br /> (© 2018 Wiley Periodicals, Inc.)

Details

Language :
English
ISSN :
1098-1004
Volume :
39
Issue :
11
Database :
MEDLINE
Journal :
Human mutation
Publication Type :
Academic Journal
Accession number :
30311378
Full Text :
https://doi.org/10.1002/humu.23643