A head-to-head evaluation of the diagnostic efficacy and costs of trio versus singleton exome sequencing analysis

Abstract

Diagnostic exome sequencing (ES) can be performed on the proband only (singleton; sES) or with additional samples, often including both biological parents with the proband (trio; tES). In this study we sought to compare the efficiencies of exome sequencing (ES) by trio (tES) versus singleton (sES) approach, determine costs, and identify factors to consider when deciding on optimal implementation strategies for the diagnosis of monogenic disorders. We undertook ES in 30 trios and analysed each proband’s sES and tES data in parallel. Two teams were randomly allocated to either sES or tES analysis for each case and blinded to each other’s work. Each task was timed and cost analyses were based on time taken and diagnostic yield. We modelled three scenarios to determine the factors to consider in the implementation of tES. sES diagnosed 11/30 (36.7%) cases and tES identified one additional diagnosis (12/30 (40.0%)). tES obviated the need for Sanger segregation, reduced the number of variants for curation, and had lower cost-per-diagnosis when considering analysis alone. When sequencing costs were included, tES nearly doubled the cost of sES. Reflexing to tES in those who remain undiagnosed after sES was cost-saving over tES in all as first-line. This approach requires a large differential in diagnostic yield between sES and tES for maximal benefit given current sequencing costs. tES may be preferable when scaling up laboratory throughput due to efficiency gains and opportunity cost considerations. Our findings are relevant to clinicians, laboratories and health services considering tES over sES.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Baldridge D, Heeley J, Vineyard M, Manwaring L, Toler TL, Fassi E et al. The Exome Clinic and the role of medical genetics expertise in the interpretation of exome sequencing results. Genet Med. 2017;19:1040–8.

  2. 2.

    Bick D, Fraser PC, Gutzeit MF, Harris JM, Hambuch TM, Helbling DC, et al. Successful application of whole genome sequencing in a medical genetics clinic. J Pedia Genet. 2017;6:61–76.

  3. 3.

    Farwell KD, Shahmirzadi L, El-Khechen D, Powis Z, Chao EC, Tippin Davis B, et al. Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions. Genet Med. 2015;17:578–86.

  4. 4.

    Iglesias A, Anyane-Yeboa K, Wynn J, Wilson A, Truitt Cho M, Guzman E, et al. The usefulness of whole-exome sequencing in routine clinical practice. Genet Med. 2014;16:922–31.

  5. 5.

    Kuperberg M, Lev D, Blumkin L, Zerem A, Ginsberg M, Linder I, et al. Utility of whole exome sequencing for genetic diagnosis of previously undiagnosed pediatric neurology patients. J Child Neurol. 2016;31:1534–9.

  6. 6.

    Lee H, Deignan JL, Dorrani N, Strom SP, Kantarci S, Quintero-Rivera F, et al. Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA. 2014;312:1880–7.

  7. 7.

    Meng L, Pammi M, Saronwala A, Magoulas P, Ghazi AR, Vetrini F, et al. Use of exome sequencing for infants in intensive care units: ascertainment of severe single-gene disorders and effect on medical management. JAMA Pedia. 2017;171:e173438.

  8. 8.

    Srivastava S, Cohen JS, Vernon H, Baranano K, McClellan R, Jamal L, et al. Clinical whole exome sequencing in child neurology practice. Ann Neurol. 2014;76:473–83.

  9. 9.

    Stark Z, Tan TY, Chong B, Brett GR, Yap P, Walsh M et al. A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med. 2016;18:1090–6.

  10. 10.

    Stavropoulos DJ, Merico D, Jobling R, Bowdin S, Monfared N, Thiruvahindrapuram B et al. Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine. NPJ Genom Med. 2016; 1.

  11. 11.

    Thevenon J, Duffourd Y, Masurel-Paulet A, Lefebvre M, Feillet F, El Chehadeh-Djebbar S, et al. Diagnostic odyssey in severe neurodevelopmental disorders: toward clinical whole-exome sequencing as a first-line diagnostic test. Clin Genet. 2016;89:700–7.

  12. 12.

    Yang Y, Muzny DM, Reid JG, Bainbridge MN, Willis A, Ward PA, et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N Engl J Med. 2013;369:1502–11.

  13. 13.

    Yang Y, Muzny DM, Xia F, Niu Z, Person R, Ding Y, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312:1870–9.

  14. 14.

    Lionel AC, Costain G, Monfared N, Walker S, Reuter MS, Hosseini SM et al. Improved diagnostic yield compared with targeted gene sequencing panels suggests a role for whole-genome sequencing as a first-tier genetic test. Genet Med. 2014;312:1870–9.

  15. 15.

    Monies D, Abouelhoda M, AlSayed M, Alhassnan Z, Alotaibi M, Kayyali H, et al. The landscape of genetic diseases in Saudi Arabia based on the first 1000 diagnostic panels and exomes. Hum Genet. 2017;136:921–39.

  16. 16.

    Tan TY, Dillon OJ, Stark Z, Schofield D, Alam K, Shrestha R, et al. Diagnostic impact and cost-effectiveness of whole-exome sequencing for ambulant children with suspected monogenic conditions. JAMA Pedia. 2017;171:855–62.

  17. 17.

    Sawyer SL, Hartley T, Dyment DA, Beaulieu CL, Schwartzentruber J, Smith A, et al. Utility of whole-exome sequencing for those near the end of the diagnostic odyssey: time to address gaps in care. Clin Genet. 2016;89:275–84.

  18. 18.

    Retterer K, Juusola J, Cho MT, Vitazka P, Millan F, Gibellini F et al. Clinical application of whole-exome sequencing across clinical indications. Genet Med. 2015;18:696–704.

  19. 19.

    Costain G, Jobling R, Walker S, Reuter MS, Snell M, Bowdin S, et al. Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing. Eur J Hum Genet. 2018;26:740–4.

  20. 20.

    Ewans LJ, Schofield D, Shrestha R, Zhu Y, Gayevskiy V, Ying K, et al. Whole-exome sequencing reanalysis at 12 months boosts diagnosis and is cost-effective when applied early in Mendelian disorders. Genet Med. 2018;20:1564–74.

  21. 21.

    Wenger AM, Guturu H, Bernstein JA, Bejerano G. Systematic reanalysis of clinical exome data yields additional diagnoses: implications for providers. Genet Med. 2017;19:209–14.

  22. 22.

    Stark Z, Schofield D, Martyn M, Rynehart L, Shrestha R, Alam K et al. Does genomic sequencing early in the diagnostic trajectory make a difference? A follow-up study of clinical outcomes and cost-effectiveness. Genet Med. 2018;21:173–80.

  23. 23.

    Nambot S, Thevenon J, Kuentz P, Duffourd Y, Tisserant E, Bruel AL, et al. Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis. Genet Med. 2018;20:645–54.

  24. 24.

    Wright CF, McRae JF, Clayton S, Gallone G, Aitken S, FitzGerald TW, et al. Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders. Genet Med. 2018;20:1216–23.

  25. 25.

    Clark MM, Stark Z, Farnaes L, Tan TY, White SM, Dimmock D, et al. Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases. NPJ Genom Med. 2018;3:16.

  26. 26.

    Gaff CL, M. Winship I, M. Forrest S, P. Hansen D, Clark J, M. Waring P, et al. Preparing for genomic medicine: a real world demonstration of health system change. npj Genom Med. 2017;2:16.

  27. 27.

    Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inf. 2009;42:377–81.

  28. 28.

    Girdea M, Dumitriu S, Fiume M, Bowdin S, Boycott KM, Chenier S, et al. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat. 2013;34:1057–65.

  29. 29.

    Sadedin SP, Dashnow H, James PA, Bahlo M, Bauer DC, Lonie A, et al. Cpipe: a shared variant detection pipeline designed for diagnostic settings. Genome Med. 2015;7:68.

  30. 30.

    Fokkema IF, Taschner PE, Schaafsma GC, Celli J, Laros JF, den Dunnen JT. LOVD v.2.0: the next generation in gene variant databases. Hum Mutat. 2011;32:557–63.

  31. 31.

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

  32. 32.

    Goranitis I, Coast J, Day E, Copello A, Freemantle N, Frew E. Maximizing Health or Sufficient Capability in Economic Evaluation? A Methodological Experiment of Treatment for Drug Addiction. Med Decis Mak. 2017;37:498–511.

  33. 33.

    Goranitis I, Bellanca L, Daley AJ, Thomas A, Stokes-Lampard H, Roalfe AK, et al. Aerobic exercise for vasomotor menopausal symptoms: a cost-utility analysis based on the Active Women trial. PLoS ONE. 2017;12:e0184328.

  34. 34.

    Bramswig NC, Ludecke HJ, Hamdan FF, Altmuller J, Beleggia F, Elcioglu NH, et al. Heterozygous HNRNPU variants cause early onset epilepsy and severe intellectual disability. Hum Genet. 2017;136:821–34.

  35. 35.

    Epi KC, Epilepsy Phenome/Genome P, Allen AS, Berkovic SF, Cossette P, Delanty N, et al. De novo mutations in epileptic encephalopathies. Nature. 2013;501:217–21.

  36. 36.

    de Ligt J, Willemsen MH, van Bon BW, Kleefstra T, Yntema HG, Kroes T, et al. Diagnostic exome sequencing in persons with severe intellectual disability. N Engl J Med. 2012;367:1921–9.

  37. 37.

    Best S, Wou K, Vora N, Van der Veyver IB, Wapner R, Chitty LS. Promises, pitfalls and practicalities of prenatal whole exome sequencing. Prenat Diagn. 2018;38:10–19.

  38. 38.

    Aten E, Fountain MD, van Haeringen A, Schaaf CP, Santen GW. Imprinting: the Achilles heel of trio-based exome sequencing. Genet Med. 2016;18:1163–4.

  39. 39.

    Salmon LB, Orenstein N, Markus-Bustani K, Ruhrman-Shahar N, Kilim Y, Magal N et al. Improved diagnostics by exome sequencing following raw data reevaluation by clinical geneticists involved in the medical care of the individuals tested. Genet Med. 2018;21:1443–51.

Download references

Acknowledgements

The authors thank all doctors who referred patients to the study, and the families who participated.

Funding

The study was funded by the State Government of Victoria (Department of Health and Human Services) and the 10 member organisations of the Melbourne Genomics Health Alliance (The Royal Melbourne Hospital, The Royal Children’s Hospital, The University of Melbourne, The Walter and Eliza Hall Institute, Murdoch Children’s Research Institute, CSIRO, Australian Genome Research Facility, Peter MacCallum Cancer Centre, Austin Health and Monash Health).

Author information

Project conception, design, leadership: TYT, SL, CLG, SMW. Data generation: SL, BC, DP, MFF, JEM, VSK, ZS, AY, NJB, CS, MBD, SS, MM, IG. Cost and statistical analyses: MM, IG, NT. Manuscript major draft writing: TYT, SMW.

Correspondence to Tiong Yang Tan or Susan M. White.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

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

Manuscript editing: all authors contributed to manuscript review and editing

Supplementary information

Supplementary Table 1

Supplementary Table 2

Supplementary Table 3

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark