Evaluating the molecular diagnostic yield of joint genotyping–based approach for detecting rare germline pathogenic and putative loss-of-function variants

Genetics in Medicine (2021)Cite this article

Abstract

Purpose

Cohort-based germline variant characterization is the standard approach for pathogenic variant discovery in clinical and research samples. However, the impact of cohort size on the molecular diagnostic yield of joint genotyping is largely unknown.

Methods

Head-to-head comparison of the molecular diagnostic yield of joint genotyping in two cohorts of 239 cancer patients in the absence and then in the presence of 100 additional germline exomes.

Results

In 239 testicular cancer patients, 4 (7.4%, 95% confidence interval [CI]: 2.1–17.9) of 54 pathogenic variants in the cancer predisposition and American College of Medical Genetics and Genomics (ACMG) genes were missed by one or both computational runs of joint genotyping. Similarly, 8 (12.1%, 95% CI: 5.4–22.5) of 66 pathogenic variants in these genes were undetected by joint genotyping in another independent cohort of 239 breast cancer patients. An exome-wide analysis of putative loss-of-function (pLOF) variants in the testicular cancer cohort showed that 162 (8.2%, 95% CI: 7.1–9.6) pLOF variants were only detected in one analysis run but not the other, while 433 (22.0%, 95% CI: 20.2–23.9%) pLOF variants were filtered out by both analyses despite having sufficient sequencing coverage.

Conclusion

Our analysis of the standard germline variant detection method highlighted a substantial impact of concurrently analyzing additional genomic data sets on the ability to detect clinically relevant germline pathogenic variants.

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Fig. 1: Overview of the study design.
Fig. 2: Exome-wide analysis of germline variant discovery in the presence and absence of additional genomics datasets.
Fig. 3: Detection of rare germline pathogenic in cancer patients using GATK-JG.
Fig. 4: Detection of rare germline pLOF variants in cancer patients using GATK-JG.
Fig. 5: Performance of GATK-JG in detecting pathogenic and pLOF variants in 12 clinically oriented phenotype-specific multi-gene panels.

Data and software availability

The raw sequence data for all cohorts utilized in this study can be obtained through dbGaP (https://www.ncbi.nlm.nih.gov/gap) or as described in their original papers (See methods). All software tools used in this study are publicly available.

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Acknowledgements

We thank all individuals who participated in this study. S.H.A. and E.V.A. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. This work was supported by American Society of Clinical Oncology (ASCO) Conquer Cancer Foundation Career Development Award (CCF CDA) CDA#13167 (S.H.A.), the Prostate Cancer Foundation Young Investigator Award YIA#18YOUN02 (S.H.A), the PCF-V Foundation Challenge Award (E.M.V.), the National Institutes of Health R37CA222574 (E.M.V.), R01 CA227388 (E.M.V.), and King Abdulaziz City for Science and Technology grant 12-MED2226–46 (M.A.). The funding organizations were not responsible for the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The results published here are in part based upon data generated by the Cancer Genome Atlas managed by the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI). Information about TCGA can be found at http://cancergenome.nih.gov.

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Affiliations

  1. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Sabrina Y. Camp, Eric Kofman, Brendan Reardon, Eliezer M. Van Allen & Saud H. AlDubayan

  2. Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Sabrina Y. Camp, Eric Kofman, Brendan Reardon, Eliezer M. Van Allen, Amaro Taylor-Weiner & Saud H. AlDubayan

  3. Internal Medicine Residency Program, University of Cincinnati, Cincinnati, OH, USA

    Nathanael D. Moore

  4. College of Medicine, Imam Abdulrahman bin Faisal University, Dammam, Saudi Arabia

    Abdullah M. Al-Rubaish, Mohammed Aljumaan & Amein K. Al-Ali

  5. Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA

    Saud H. AlDubayan

  6. College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia

    Saud H. AlDubayan

Authors
  1. Sabrina Y. Camp
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  2. Eric Kofman
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  3. Brendan Reardon
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  4. Nathanael D. Moore
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  5. Abdullah M. Al-Rubaish
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  7. Amein K. Al-Ali
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  9. Amaro Taylor-Weiner
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  10. Saud H. AlDubayan
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Contributions

S.Y.C., E.K., B.R., N.M., E.M.V., A.T.W., S.H.A. generated the germline variant callsets and performed genomic analysis of sequencing data. S.H.A. performed germline variant pathogenicity assessment. S.H.A., A.M.A., M.A., A.K.A. performed analysis of clinical characteristics. S.H.A., E.M.V., S.Y.C., wrote the manuscript. S.H.A., S.Y.C. prepared the main and supplementary figures. All authors reviewed and edited the manuscript.

Corresponding authors

Correspondence to Amaro Taylor-Weiner or Saud H. AlDubayan.

Ethics declarations

Ethics declaration

All individuals in this study consented to institutional review board–approved protocols that allowed for comprehensive genetic analysis of germline samples (methods). This study conforms to the Declaration of Helsinki.

Competing interests

E.V.A. has the following disclosures; advisory and/or consulting for Tango Therapeutics, Genome Medical, Invitae, Illumina, and Ervaxx; research support from Novartis and BMS; equity in Tango Therapeutics, Genome Medical, Syapse, Ervaxx, and Microsoft; travel reimbursement from Roche and Genentech; and institutional patents (ERCC2 mutations and chemotherapy response, chromatin mutations and immunotherapy response, and methods for clinical interpretation). The other authors declare no competing interests.

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Camp, S.Y., Kofman, E., Reardon, B. et al. Evaluating the molecular diagnostic yield of joint genotyping–based approach for detecting rare germline pathogenic and putative loss-of-function variants. Genet Med (2021). https://doi.org/10.1038/s41436-020-01074-w

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