PMID- 20718044
OWN - NLM
STAT- MEDLINE
DCOM- 20110114
LR  - 20100906
IS  - 1098-2272 (Electronic)
IS  - 0741-0395 (Linking)
VI  - 34
IP  - 6
DP  - 2010 Sep
TI  - A variance components factor model for genetic association studies: a Bayesian 
      analysis.
PG  - 529-36
LID - 10.1002/gepi.20503 [doi]
AB  - Studies of gene-trait associations for complex diseases often involve multiple 
      traits that may vary by genotype groups or patterns. Such traits are usually 
      manifestations of lower-dimensional latent factors or disease syndromes. We 
      illustrate the use of a variance components factor (VCF) model to model the 
      association between multiple traits and genotype groups as well as any other 
      existing patient-level covariates. This model characterizes the correlations 
      between traits as underlying latent factors that can be used in clinical 
      decision-making. We apply it within the Bayesian framework and provide a 
      straightforward implementation using the WinBUGS software. The VCF model is 
      illustrated with simulated data and an example that comprises changes in plasma 
      lipid measurements of patients who were treated with statins to lower low-density 
      lipoprotein cholesterol, and polymorphisms from the apolipoprotein-E gene. The 
      simulation shows that this model clearly characterizes existing multiple trait 
      manifestations across genotype groups where individuals' group assignments are 
      fully observed or can be deduced from the observed data. It also allows one to 
      investigate covariate by genotype group interactions that may explain the 
      variability in the traits. The flexibility to characterize such multiple trait 
      manifestations makes the VCF model more desirable than the univariate variance 
      components model, which is applied to each trait separately. The Bayesian 
      framework offers a flexible approach that allows one to incorporate prior 
      information.
CI  - (c) 2010 Wiley-Liss, Inc.
FAU - Nonyane, B A S
AU  - Nonyane BA
AD  - Department of Epidemiology and Population Health, London School of Hygiene and 
      Tropical Medicine, London, UK. sannyb05@yahoo.co.uk
FAU - Whittaker, J C
AU  - Whittaker JC
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Genet Epidemiol
JT  - Genetic epidemiology
JID - 8411723
RN  - 0 (Apolipoproteins E)
SB  - IM
MH  - Apolipoproteins E/genetics
MH  - *Bayes Theorem
MH  - Body Mass Index
MH  - Computer Simulation
MH  - Factor Analysis, Statistical
MH  - Genetic Association Studies/*methods
MH  - Genotype
MH  - Humans
MH  - *Models, Genetic
MH  - Polymorphism, Single Nucleotide
MH  - Quantitative Trait Loci
EDAT- 2010/08/19 06:00
MHDA- 2011/01/15 06:00
CRDT- 2010/08/19 06:00
PHST- 2010/08/19 06:00 [entrez]
PHST- 2010/08/19 06:00 [pubmed]
PHST- 2011/01/15 06:00 [medline]
AID - 10.1002/gepi.20503 [doi]
PST - ppublish
SO  - Genet Epidemiol. 2010 Sep;34(6):529-36. doi: 10.1002/gepi.20503.