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Related Experiment Videos

Testing for familial correlation in age-at-onset.

Daniel Rabinowitz1, Rebecca A Betensky

  • 1Department of Statistics, MC4403, Columbia University, New York, NY 10027, USA. dan@stat.columbia.edu

Biostatistics (Oxford, England)
|August 23, 2003
PubMed
Summary

This study introduces a new method to analyze familial clustering of disease onset age, accounting for age at ascertainment. The approach helps avoid artificial correlations in family studies of traits like panic disorder.

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Area of Science:

  • Genetics
  • Epidemiology
  • Biostatistics

Background:

  • Family studies often examine trait clustering within families.
  • Investigating familial clustering of age-at-onset for traits with variable onset is of interest.
  • Censoring by age-at-ascertainment can create artifactual familial correlations in age-at-onset data.

Purpose of the Study:

  • To present a statistical approach for testing familial correlation in age-at-onset.
  • To address confounding factors like censoring by age-at-ascertainment.
  • To provide a method applicable with diverse sample inclusion criteria.

Main Methods:

  • Utilizes regression statistics.
  • Incorporates covariate terms reflecting age-at-onset information from affected family members.

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  • Applies the method to family study data.

    • Main Results:

    • The proposed approach effectively tests for familial correlation in age-at-onset.
    • Demonstrates the method's utility in a family study of panic disorder.
    • The results illustrate that the approach is not confounded by age-at-ascertainment.

    Conclusions:

    • The presented regression-based method provides a robust way to test for familial clustering of age-at-onset.
    • This approach mitigates confounding from age-at-ascertainment and accommodates various inclusion criteria.
    • The findings are relevant for family studies in psychiatric and other genetic disorders.