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Fitting ACE structural equation models to case-control family data.

K N Javaras1, J I Hudson, N M Laird

  • 1Waisman Laboratory for Brain Imaging & Behavior, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA. javaras@wisc.edu

Genetic Epidemiology
|November 18, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method to analyze family disease data, accurately estimating genetic and environmental factors contributing to diseases like depression. The approach provides reliable heritability estimates from case-control family studies.

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Area of Science:

  • Behavioral Genetics
  • Biostatistics
  • Psychiatric Epidemiology

Background:

  • Family studies are crucial for understanding disease aggregation.
  • Case-control family data are often collected but underutilized for genetic and environmental analyses.
  • Classic twin models (ACE) estimate additive genetic (A), shared environment (C), and unique environment (E) effects.

Purpose of the Study:

  • To develop a likelihood-based method for fitting ACE models to case-control family data.
  • To enable valid estimation of genetic and environmental variance components from case-control data.
  • To extend the application of ACE models beyond population-based family studies.

Main Methods:

  • Description of a structural equation ACE model for binary family data.
  • Development of a likelihood-based fitting approach for singly ascertained case-control family data.
  • Conditioning on proband disease status and setting prevalence to estimate variance components.

Main Results:

  • Simulation studies indicate approximately unbiased estimates of A, C, and E variance components.
  • The method successfully estimates genetic and environmental contributions to disease risk.
  • Application to Austrian depression data yielded heritability estimates comparable to twin studies.

Conclusions:

  • The proposed likelihood-based approach enables robust estimation of genetic and environmental influences on disease from case-control family data.
  • This method expands the utility of case-control family studies for etiological research.
  • Accurate estimation of heritability and environmental factors is now possible using case-control family designs.