Frequency of genomic secondary findings among 21,915 eMERGE network participants

Abstract

Purpose

Discovering an incidental finding (IF) or secondary finding (SF) is a potential result of genomic testing, but few data exist describing types and frequencies of SFs likely to appear in broader clinical populations.

Methods

The Electronic Medical Records and Genomics Network Phase III (eMERGE III) developed a CLIA-compliant sequencing panel of 109 genes and 1551 variants of clinical relevance or research interest and deployed this panel at ten clinical sites. We evaluated medically actionable SFs across 67 genes and 14 single-nucleotide variants (SNVs) in a diverse cohort of 21,915 participants drawn from a variety of settings (e.g., primary care, biobanks, specialty clinics).

Results

Correcting for testing indication, we found a 3.02% overall frequency of SFs; 2.54% from 59 genes the American College of Medical Genetics and Genomics recommends for SF return, and 0.48% in other genes, primarily HFE and PALB2. SFs associated with cancer susceptibility were most frequent (1.38%), followed by cardiovascular diseases (0.87%), and lipid disorders (0.50%). After removing HFE, the frequency of SFs and proportion of pathogenic versus likely pathogenic SFs did not differ in those self-identifying as White versus others.

Conclusion

Here we present frequencies and types of medically actionable secondary findings to support informed decision making by patients, participants, and practitioners engaged in genomic medicine.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Overall frequency of secondarily findings (SFs) across the eMERGE III-SF cohort.
Fig. 2: Secondary finding (SF) rates.

References

  1. 1.

    Green RC, Berg JS, Grody WW, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15:565–574.

    CAS  Article  Google Scholar 

  2. 2.

    Kalia SS, Adelman K, Bale SJ, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19:249–255.

    Article  Google Scholar 

  3. 3.

    ACMG Board of Directors. The use of ACMG secondary findings recommendations for general population screening: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2019;21:1467–1468.

    Article  Google Scholar 

  4. 4.

    Richards CS, Bale S, Bellissimo DB, et al. ACMG recommendations for standards for interpretation and reporting of sequence variations: revisions 2007. Genet Med. 2008;10:294–300.

    CAS  Article  Google Scholar 

  5. 5.

    Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–424.

    Article  Google Scholar 

  6. 6.

    Olfson E, Cottrell CE, Davidson NO, et al. Identification of medically actionable secondary findings in the 1000 Genomes. PLoS One. 2015;10:e0135193.

    Article  Google Scholar 

  7. 7.

    Amendola LM, Dorschner MO, Robertson PD, et al. Actionable exomic incidental findings in 6503 participants: challenges of variant classification. Genome Res. 2015;25:305–315.

    CAS  Article  Google Scholar 

  8. 8.

    Yang Y, Muzny DM, Xia F, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312:1870–1879.

    CAS  Article  Google Scholar 

  9. 9.

    Schwartz MLB, Mccormick CZ, Lazzeri AL, et al. A model for genome-first care: returning secondary genomic findings to participants and their healthcare providers in a large research cohort. Am J Hum Genet. 2018;103:328–337.

    CAS  Article  Google Scholar 

  10. 10.

    The eMERGE Consortium. Harmonizing clinical sequencing and interpretation for the eMERGE III network. Am J Hum Genet. 2019;105:588–605.

    Article  Google Scholar 

  11. 11.

    Dorschner MO, Amendola LM, Turner EH, et al. Actionable, pathogenic incidental findings in 1,000 participants’ exomes. Am J Hum Genet. 2013;93:631–640.

    CAS  Article  Google Scholar 

  12. 12.

    Gordon A, Rosenthal E, Carrell D, et al. Rates of actionable genetic findings in individuals with colorectal cancer or polyps ascertained from a community medical setting. Am J Hum Genet. 2019;105:526–533.

    CAS  Article  Google Scholar 

  13. 13.

    Berg JS, Foreman AK, O’daniel JM, et al. A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing. Genet Med. 2016;18:467–475.

    Article  Google Scholar 

  14. 14.

    Hunter JE, Irving SA, Biesecker LG, et al. A standardized, evidence-based protocol to assess clinical actionability of genetic disorders associated with genomic variation. Genet Med. 2016;18:1258–1268.

    CAS  Article  Google Scholar 

  15. 15.

    Fossey R, Kochan D, Winkler E, et al. Ethical considerations related to return of results from genomic medicine projects: the eMERGE Network (Phase III) experience. J Pers Med. 2018;8:E2.

    Article  Google Scholar 

  16. 16.

    Tabor HK, Auer PL, Jamal SM, et al. Pathogenic variants for Mendelian and complex traits in exomes of 6,517 European and African Americans: implications for the return of incidental results. Am J Hum Genet. 2014;95:183–193.

    CAS  Article  Google Scholar 

  17. 17.

    Autore F, Strati P, Laurenti L, Ferrajoli A. Morphological, immunophenotypic, and genetic features of chronic lymphocytic leukemia with trisomy 12: a comprehensive review. Haematologica. 2018;103:931–938.

    CAS  Article  Google Scholar 

  18. 18.

    Gallego CJ, Burt A, Sundaresan AS, et al. Penetrance of hemochromatosis in HFE genotypes resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network. Am J Hum Genet. 2015;97:512–520.

    CAS  Article  Google Scholar 

  19. 19.

    DellaPergola S. World Jewish population, 2012. In: Dashefsky A, Sheskin I (eds.). American Jewish year book. Dordrecht: Springer; 2013:279–358.

  20. 20.

    Retterer K, Juusola J, Cho MT, et al. Clinical application of whole-exome sequencing across clinical indications. Genet Med. 2016;18:696–704.

    CAS  Article  Google Scholar 

  21. 21.

    Lohmueller KE, Indap AR, Schmidt S, et al. Proportionally more deleterious genetic variation in European than in African populations. Nature. 2008;451:994–997.

    CAS  Article  Google Scholar 

  22. 22.

    Fu W, O’connor TD, Jun G, et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature. 2013;493:216–220.

    CAS  Article  Google Scholar 

  23. 23.

    Fullerton SM, Knerr S, Burke W. Finding a place for genomics in health disparities research. Public Health Genomics. 2012;15:156–163.

    CAS  Article  Google Scholar 

  24. 24.

    Fullerton SM, Wolf WA, Brothers KB, et al. Return of individual research results from genome-wide association studies: experience of the Electronic Medical Records and Genomics (eMERGE) Network. Genet Med. 2012;14:424–431.

    Article  Google Scholar 

  25. 25.

    Harrison SM, Dolinsky JS, Knight johnson AE, et al. Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar. Genet Med. 2017;19:1096–1104.

    Article  Google Scholar 

Download references

Acknowledgements

The eMERGE Phase III Network was initiated and funded by NHGRI through the following grants: U01HG8657 (Kaiser Permanente Washington/University of Washington); U01HG8685 (Brigham and Women’s Hospital); U01HG8672 (Vanderbilt University Medical Center); U01HG8666 (Cincinnati Children’s Hospital Medical Center); U01HG6379 (Mayo Clinic); U01HG8679 (Geisinger Clinic); U01HG8680 (Columbia University Health Sciences); U01HG8684 (Children’s Hospital of Philadelphia); U01HG8673 (Northwestern University); MD007593 (Meharry Medical College); U01HG8701 (Vanderbilt University Medical Center serving as the Coordinating Center); U01HG8676 (Partners Healthcare/Broad Institute); and U01HG8664 (Baylor College of Medicine).

Data Access

All data sets summarized here will be publicly available in the dbGaP repository under phs001616.v1.p1 and pre-dbGaP submission access can also be requested on the eMERGE website https://emerge-network.org.

Author information

Affiliations

Consortia

Corresponding author

Correspondence to Adam S. Gordon PhD.

Ethics declarations

Disclosure

D.R.C. serves on a consulting board for UnitedHealth Group with precision medicine efforts, which is unrelated to this paper. C.M.E. is a full-time employee/faculty member of Baylor College of Medicine. Through a professional services agreement, she serves as Chief Medical Officer and Chief Quality Officer of Baylor Genetics. R.A.G. declares that Baylor College of Medicine receives payments from Baylor Genetics Laboratories, which provides services for genetic testing; Baylor College of Medicine is part owner of Codified Genomics. H.L.R. and H.Z. are employed at Massachusetts General Hospital, which receives royalties on sales of GeneInsight Software. E.V. is a cofounder of Codified Genomics. G.L.W. is a member of the External Advisory Panel for the ClinGen Clinical Genome Resource Project. The other authors declare no conflicts of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gordon, A.S., Zouk, H., Venner, E. et al. Frequency of genomic secondary findings among 21,915 eMERGE network participants. Genet Med (2020). https://doi.org/10.1038/s41436-020-0810-9

Download citation

Keywords

  • personal genomics
  • clinical sequencing
  • incidental findings secondary findings
  • eMERGE