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. 2022 Jan 8;3(2):100086.
doi: 10.1016/j.xhgg.2022.100086. eCollection 2022 Apr 14.

Clinical validation of genomic functional screen data: Analysis of observed BRCA1 variants in an unselected population cohort

Kelly M Schiabor Barrett  1   2 , Max Masnick  1   3 , Kathryn E Hatchell  1 , Juliann M Savatt  1 , Natalie Banet  4 , Adam Buchanan  1 , Huntington F Willard  1   5
Affiliations

Clinical validation of genomic functional screen data: Analysis of observed BRCA1 variants in an unselected population cohort

Kelly M Schiabor Barrett et al. HGG Adv. .

Abstract

Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.

Keywords: BRCA1; electronic health record; functional screen; hereditary breast and ovarian cancer; population genomics; rare variant interpretation.

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Conflict of interest statement

K.M.S.B. is an employee at Helix. M.M.’s affiliation with The MITRE Corporation is provided for identification purposes only and is not intended to convey or imply MITRE’s concurrence with, or support for, the positions, opinions, or viewpoints expressed by M.M. K.E.H. is an employee of and shareholder in Invitae. H.F.W. is an employee at Genome Medical.

Figures

Figure 1
Figure 1
Frequencies of functionally abnormal;LOF and functionally normal BRCA1 alleles in the DiscovEHR cohort Along the x axis, the histogram displays variants, grouped by SGE classification and binned by number of occurrences in the cohort. The height of the bar corresponds to the percentage of variants, within each classification, that belong to each frequency bin. In accordance with pathogenicity expectations, variants over 40 occurrences are captured in a single bin.
Figure 2
Figure 2
Time-to-event analysis Age at BRCA1-related cancer diagnosis for participants with variants predicted to be functionally abnormal; LOF or functionally normal by results of the SGE assay, compared to participants with non-SGE classified variants. (A and B) All BRCA1-related cancers for all participants, for functionally abnormal; LOF (p = 0.01) and functionally normal (p = 0.4) variants, respectively. (C and D) Only breast and ovarian cancer diagnoses in female participants, for functionally abnormal; LOF (p = 0.001) and functionally normal (p = 0.6) variants, respectively. The p values are from log rank tests for differences between the 2 time-to-event curves in each panel.
See this image and copyright information in PMC

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