Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach. Issue 11 (11th October 2018) - Harrison, Steven M.; Dolinksy, Jill S.; Chen, Wenjie; Collins, Christin D.; Das, Soma; Deignan, Joshua L.; Garber, Kathryn B.; Garcia, John; Jarinova, Olga; Knight Johnson, Amy E.; Koskenvuo, Juha W.; Lee, Hane; et al.
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. Abstract : To facilitate resolution of sequence variant classification differences in ClinVar, clinical laboratories were sent a custom report of outlier interpretations and encouraged to reassess variants. Among 650 variants with medically significant differences between laboratories, 31% (204 variants) had an outlier classification, of which 62.3% (127 variants) were reclassified and resolved upon outlier laboratory reassessment alone. This study demonstrates a scalable approach to tackle a portion of classification resolution and capitalizes on the value of data sharing within ClinVar.