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Journal of Genetic Counseling

, Volume 16, Issue 1, pp 29–39 | Cite as

Bayesian Risk Assessment in Genetic Testing for Autosomal Dominant Disorders with Age-Dependent Penetrance

  • Shuji OginoEmail author
  • Robert B. Wilson
  • Bert Gold
  • Pamela Flodman
Original Research

Risk assessment is an essential component of genetic counseling and testing, and the accuracy of risk assessment is critical for decision making by consultands. However, it has been shown that genetic risk calculations may have high error rates in practice. Risk calculations for autosomal dominant disorders are frequently complicated by age-dependent penetrance and sensitivities of less than 100% in genetic testing. We provide methods of risk calculation for prototypical pedigrees of a family at risk for an autosomal dominant disorder with age-dependent penetrance. Our risk calculations include scenarios in which the sensitivity of genetic testing is less than 100%, and in which the sensitivity of genetic testing varies for different family members at risk. Our Bayesian methods permit autosomal dominant disease probabilities to be calculated accurately, taking into account all relevant information. Our methods are particularly useful for hereditary cancer syndromes, in which genetic testing can seldom achieve 100% sensitivity. Our methods can be applied to many different scenarios, including those where the sensitivity of genetic testing varies for different family members at risk.

KEY WORDS

bayes bayesian genetic risk risk assessment genetic counseling autosomal dominant hereditary cancer penetrance sensitivity 

Notes

ACKNOWLEDGMENTS

This project has been funded in part with Federal Funds from the National Cancer Institute, National Institutes of Health. We thank Lindsay Middelton and Mei-Chiung Shih for critical reading of the manuscript.

REFERENCES

  1. Biesecker, L. (2005). Accuracy and precision in Bayesian analysis. Am J Med Genet A, 134, 111.CrossRefGoogle Scholar
  2. Bonke, B., Tibben, A., Lindhout, D., Clarke, A. J., & Stijnen, T. (2005). Genetic risk estimation by healthcare professionals. Med J Aust, 182, 116118.PubMedGoogle Scholar
  3. Bonke, B., Tibben, A., Lindhout, D., & Stijnen, T. (2002). Favourable mutation test outcomes for individuals at risk for Huntington disease change the perspectives of first-degree relatives. Hum Genet, 111, 297298.CrossRefGoogle Scholar
  4. Bonke, B., Tibben, A., Lindhout, D., & Stijnen, T. (2006). Calculating risk changes after negative mutation test outcomes for autosomal dominant hereditary late-onset disorders. Heredity, 96, 259261.CrossRefGoogle Scholar
  5. Bridge, P. J. (1997). The Calculation of Genetic Risks: Worked Examples in DNA Diagnostics. Second Edition edn. The Johns Hopkins University Press, Baltimore.Google Scholar
  6. Flodman, P., & Hodge, S. E. (2001). A genetic risk calculation surprise. Am J Med Genet, 100, 169171.CrossRefGoogle Scholar
  7. Hodge, S. E. (1998). A simple, unified approach to Bayesian risk calculations. J Genet Couns, 7, 235261.CrossRefGoogle Scholar
  8. Hodge, S. E., & Flodman, P. L. (2004). Risk calculations: still essential in the molecular age. Am J Med Genet, 129A, 215–217.CrossRefGoogle Scholar
  9. Ogino, S., Flodman, P., Wilson, R. B., Gold, B., & Grody, W. W. (2005). Risk calculations for cystic fibrosis in neonatal screening by immunoreactive trypsinogen and CFTR mutation tests. Genet Med, 7, 317327.CrossRefGoogle Scholar
  10. Ogino, S., Leonard, D. G., Rennert, H., Ewens, W. J., & Wilson, R. B. (2002). Genetic risk assessment in carrier testing for spinal muscular atrophy. Am J Med Genet, 110, 301307.CrossRefGoogle Scholar
  11. Ogino, S., & Wilson, R. B. (2002). Genetic testing and risk assessment for spinal muscular atrophy (SMA). Hum Genet, 111, 477500.CrossRefGoogle Scholar
  12. Ogino, S., & Wilson, R. B. (2004). Bayesian Analysis and Risk Assessment in Genetic Counseling and Testing. J Mol Diagn, 6, 19.CrossRefGoogle Scholar
  13. Ogino, S., Wilson, R. B., Gold, B., Hawley, P., & Grody, W. W. (2004a). Bayesian analysis for cystic fibrosis risks in prenatal and carrier screening. Genet Med, 6, 439449.CrossRefGoogle Scholar
  14. Ogino, S., Wilson, R. B., & Grody, W. W. (2004b). Bayesian risk assessment for autosomal recessive diseases: fetal echogenic bowel with one or no detectable CFTR mutation. J Med Genet, 41, e70.CrossRefGoogle Scholar
  15. Otto, P. A., & Maestrelli, S. R. (2000). Heterozygosity probabilities for normal relatives of isolated cases affected by incompletely penetrant conditions and the calculation of recurrence risks for their offspring. I. Autosomal dominant genes. Am J Med Genet, 95, 4348.CrossRefGoogle Scholar
  16. Young, I. D. (1999). Introduction to risk calculation in genetic counseling. 2nd edn. Oxford University Press, Oxford.Google Scholar

Copyright information

© National Society of Genetic Counselors, Inc. 2007

Authors and Affiliations

  • Shuji Ogino
    • 1
    • 2
    • 6
    Email author
  • Robert B. Wilson
    • 3
  • Bert Gold
    • 4
  • Pamela Flodman
    • 5
  1. 1.Department of Medical OncologyDana-Farber Cancer InstituteBostonUSA
  2. 2.Department of PathologyBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA
  3. 3.Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Medical CenterPhiladelphiaUSA
  4. 4.Human Genetics SectionLaboratory of Genomic Diversity, National Cancer Institute at FrederickFrederickUSA
  5. 5.Department of PediatricsUniversity of California IrvineIrvineUSA
  6. 6.Department of PathologyBrigham and Women’s Hospital, Harvard Medical SchoolBostonUSA

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