Including endophenotypes as covariates in variance component heritability and linkage analysis
2005

Incorporating Endophenotypes in Genetic Analysis

Sample size: 23 publication Evidence: moderate

Author Information

Author(s): Joan E Bailey-Wilson, Laura Almasy, Mariza de Andrade, Julia Bailey, Heike Bickeböller, Heather J Cordell, E Warwick Daw, Lynn Goldin, Ellen L Goode, Courtney Gray-McGuire, Wayne Hening, Gail Jarvik, Brion S Maher, Nancy Mendell, Andrew D Paterson, John Rice, Glen Satten, Brian Suarez, Veronica Vieland, Marsha Wilcox, Heping Zhang, Andreas Ziegler, Jean W MacCluer

Primary Institution: University of California at Los Angeles School of Medicine

Hypothesis

Does including covariates improve genetic analyses of heritability and linkage?

Conclusion

Incorporating endophenotypes as covariates did not consistently improve the results of genetic analyses for Kofendrerd Personality Disorder.

Supporting Evidence

  • Kofendrerd Personality Disorder was not heritable without covariates.
  • Seven out of twelve associated phenotypes were significant when included.
  • The inclusion of covariates did not consistently alter false-positive rates.

Takeaway

The study looked at whether adding extra information helps in understanding genetic traits, but it found that it didn't always make a difference.

Methodology

Variance component analyses were performed using a simulated dataset with different covariate models.

Potential Biases

Potential false positives due to violations of assumptions about trait distribution.

Limitations

The study used a simulated dataset, which may not fully represent real-world complexities.

Participant Demographics

Data from four different populations with varying ascertainment schemes.

Statistical Information

P-Value

p < 0.000001

Statistical Significance

p < 0.000001

Digital Object Identifier (DOI)

10.1186/1471-2156-6-S1-S49

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication