Modeling of multivariate longitudinal phenotypes in family genetic studies with Bayesian multiplicity adjustment.

BMC Proc 2014 17;8(Suppl 1):S69. Epub 2014 Jun 17.

Department of Pediatrics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA ; Department of Pediatrics, University of Cincinnati College of Medicine, 3235 Eden Avenue,Cincinnati, OH 45267, USA.

Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family members. We developed a Bayesian model for analysis of bivariate quantitative traits measured longitudinally in family genetic studies. For a given trait, family-specific and subject-specific random effects account for correlation among family members and repeated measures, respectively. Correlation between traits is introduced by incorporating multivariate random effects and allowing time-specific trait residuals to correlate as in seemingly unrelated regressions. The proposed model can examine multiple single-nucleotide variations simultaneously, as well as incorporate familyspecific, subject-specific, or time-varying covariates. Bayesian multiplicity technique is used to effectively control false positives. Genetic Analysis Workshop 18 simulated data illustrate the proposed approach's applicability in modeling longitudinal multivariate outcomes in family genetic association studies.

Download full-text PDF

Source
http://dx.doi.org/10.1186/1753-6561-8-S1-S69DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143665PMC
December 2014
35 Reads

Publication Analysis

Top Keywords

genetic studies
12
correlation traits
12
family genetic
12
genetic association
8
random effects
8
bayesian multiplicity
8
traits measured
8
modeling multivariate
8
family members
8
multiple traits
8
multivariate outcomes
8
traits
7
genetic
6
family
5
introduced incorporating
4
measures correlation
4
incorporating multivariate
4
traits introduced
4
allowing time-specific
4
residuals correlate
4

References

(Supplied by CrossRef)

D Shriner et al.
Front Genet 2012

WS Zhu et al.
J Korean Stat Soc 2009

L Almasy et al.
Genet Epidemiol 1997

G Reinsel et al.
J Am Stat Assoc 1982

A Zellner et al.
J Am Stat Assoc 1962

JG Scott et al.
Ann Stat 2010

MA Wilson et al.
Ann Appl Stat 2010

MD Tobin et al.
Stat Med 2005

E Boerwinkle et al.
Ann Hum Genet 1986

JF Liu et al.
Genet Epidemiol 2009

A Teixeira-Pinto et al.
Stat Med 2009

Similar Publications