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Consistency of variant interpretations among bioinformaticians and clinical geneticists in hereditary cancer panels

European Journal of Human Genetics volume 30, pages 378–383 (2022)Cite this article

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Abstract

Next-generation sequencing (NGS) is used increasingly in hereditary cancer patients' (HCP) management. While enabling evaluation of multiple genes simultaneously, the technology brings to light the dilemma of variant interpretation. Here, we aimed to reveal the underlying reasons for the discrepancy in the evidence titles used during variant classification according to ACMG guidelines by two different bioinformatic specialists (BIs) and two different clinical geneticists (CGs). We evaluated final reports of 1920 cancer patients and 189 different variants from 285 HCP were enrolled to the study. A total of 173 of these variants were classified as pathogenic (n = 132) and likely pathogenic (n = 41) by the BI and an additional 16 variants, that were classified as VUS by at least one interpreter and their classification would change the clinical management, were compared for their evidence titles between different specialists. The attributed evidence titles and the final classification of the variants among BIs and CGs were compared. The discrepancy between P/LP final reports was 22.5%. The discordance between CGs was 30% whereas the discordance between two BIs was almost 75%. The use of PVS1, PS3, PP3, PP5, PM1, PM2, BP1, BP4 criteria markedly varied from one expert to another. This difference was particularly noticeable in PP3, PP5, and PM1 evidence and mostly in the variants affecting splice sites like BRCA1(NM_007294.4) c.4096 + 1 G > A and CHEK2(NM_007194.4) c.592 + 3 A > T. With recent advancements in precision medicine, the importance of variant interpretations is emerging. Our study shows that variant interpretation is subjective process that is in need of concrete definitions for accurate and standard interpretation.

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Fig. 1: The workflow of variant interpretation by bioinformation (BI) and clinical geneticist (CG). The BI follows a partially automated workflow during the variant interpretation.

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Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Authors would like to thank Sharon Lynn Pugh, Associate Professor Emeritus of Education at Indiana University Bloomington for language editing.

Funding

This study was partially supported by Istanbul Development Agency (IDA) project number YNY2016/144.

Author information

Authors and Affiliations

  1. Department of Medical Genetics, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey

    Nihat Bugra Agaoglu & Busra Unal

  2. Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey

    Nihat Bugra Agaoglu, Busra Unal, Ozlem Akgun Dogan, Payam Zolfagharian & Levent Doganay

  3. Department of Pediatric Genetics, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey

    Ozlem Akgun Dogan

  4. Department of Biotechnology and Genetic, Institute of Science, Trakya University, Edirne, Turkey

    Martin Orlinov Kanev

  5. Department of Medical Genetics, Faculty of Medicine, Bursa Uludag University, Bursa, Turkey

    Sebnem Ozemri Sag & Sehime Gulsun Temel

  6. Department of Histology and Embryology, Faculty of Medicine, Bursa Uludag University, Bursa, Turkey

    Sehime Gulsun Temel

  7. Department of Translational Medicine, Institute of Health Sciences, Bursa Uludag University, Bursa, Turkey

    Sehime Gulsun Temel

  8. Department of Medical Genetics PhD. Program, Institute of Health Sciences, Faculty of Medicine, Baskent University, Ankara, Turkey

    Sehime Gulsun Temel

Authors
  1. Nihat Bugra Agaoglu
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Contributions

NBA: formal analysis investigation methodology supervision writing — original draft writing — review & editing. BU: formal analysis investigation writing — original draft writing — review & editing. OAD: formal analysis methodology writing — review & editing. MOK: formal analysis writing — review & editing. PZ and SOS: formal analysis. SGT: formal analysis writing — review & editing. LD: project administration resources writing — review & editing.

Corresponding author

Correspondence to Nihat Bugra Agaoglu.

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The authors declare no competing interests.

Ethics approval and consent to participate

All procedures performed in studies involving humans were in accordance with the ethical standards (Umraniye Teaching and Research Hospital No:49/24.03.2016).

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Agaoglu, N.B., Unal, B., Akgun Dogan, O. et al. Consistency of variant interpretations among bioinformaticians and clinical geneticists in hereditary cancer panels. Eur J Hum Genet 30, 378–383 (2022). https://doi.org/10.1038/s41431-022-01060-7

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  • DOI: https://doi.org/10.1038/s41431-022-01060-7

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