Reduced penetrance of pathogenic ACMG variants in a deeply phenotyped cohort study and evaluation of ClinVar classification over time
Purpose: We studied the penetrance of pathogenically classified variants in an elderly Dutch population from the Rotterdam Study, for which deep phenotyping is available. We screened the 59 actionable genes for which reporting of known pathogenic variants was recommended by the American College of Medical Genetics and Genomics (ACMG), and demonstrate that determining what constitutes a known pathogenic variant can be quite challenging. Methods: We defined “known pathogenic” as classified pathogenic by both ClinVar and the Human Gene Mutation Database (HGMD). In 2628 individuals, we performed exome sequencing and identified known pathogenic variants. We investigated the clinical records of carriers and evaluated clinical events during 25 years of follow-up for evidence of variant pathogenicity. Results: Of 3815 variants detected in the 59 ACMG genes, 17 variants were considered known pathogenic. For 14/17 variants the ClinVar classification had changed over time. Of 24 confirmed carriers of these variants, we observed at least one clinical event possibly caused by the variant in only three participants (13%). Conclusion: We show that the definition of “known pathogenic” is often unclear and should be approached carefully. Additionally variants marked as known pathogenic do not always have clinical impact on their carriers. Definition and classification of true (individual) expected pathogenic impact should be defined carefully.
|Keywords||ACMG genes, clinical interpretation, exome sequencing, pathogenic variants, penetrance|
|Persistent URL||dx.doi.org/10.1038/s41436-020-0900-8, hdl.handle.net/1765/128926|
|Journal||Genetics in Medicine|
Van Rooij, J, Arp, P.P, Broer, L. (Linda), Verlouw, J.A.M, van Rooij, F.J.A, Kraaij, R. (Robert), … Verkerk, A. (2020). Reduced penetrance of pathogenic ACMG variants in a deeply phenotyped cohort study and evaluation of ClinVar classification over time. Genetics in Medicine. doi:10.1038/s41436-020-0900-8