Literature DB >> 14975093

Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling.

Katrina J Scurrah1, Martin D Tobin, Paul R Burton.   

Abstract

This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time. Generalized linear mixed models were fitted using Gibbs sampling in WinBUGS, and the additive polygenic random effects estimated using these models were then used as continuous phenotypes in a variance components linkage analysis. The first-stage analysis provided evidence for general genetic effects on both the baseline and slope of blood pressure, and the linkage analysis found evidence of several genes, again for both baseline and slope.

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Year:  2003        PMID: 14975093      PMCID: PMC1866460          DOI: 10.1186/1471-2156-4-S1-S25

Source DB:  PubMed          Journal:  BMC Genet        ISSN: 1471-2156            Impact factor:   2.797


  8 in total

1.  Genetic variance components analysis for binary phenotypes using generalized linear mixed models (GLMMs) and Gibbs sampling.

Authors:  P R Burton; K J Tiller; L C Gurrin; W O Cookson; A W Musk; L J Palmer
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Journal:  Nat Genet       Date:  2001-12-03       Impact factor: 38.330

3.  Variance components analysis for pedigree-based censored survival data using generalized linear mixed models (GLMMs) and Gibbs sampling in BUGS.

Authors:  K J Scurrah; L J Palmer; P R Burton
Journal:  Genet Epidemiol       Date:  2000-09       Impact factor: 2.135

4.  Longitudinal data analysis in pedigree studies.

Authors:  W James Gauderman; Stuart Macgregor; Laurent Briollais; Katrina Scurrah; Martin Tobin; Taesung Park; Dai Wang; Shaoqi Rao; Sally John; Shelley Bull
Journal:  Genet Epidemiol       Date:  2003       Impact factor: 2.135

5.  Antihypertensive treatments obscure familial contributions to blood pressure variation.

Authors:  Jisheng S Cui; John L Hopper; Stephen B Harrap
Journal:  Hypertension       Date:  2003-02       Impact factor: 10.190

6.  Genome-wide linkage analysis using genetic variance components of alcohol dependency-associated censored and continuous traits.

Authors:  L J Palmer; K J Tiller; P R Burton
Journal:  Genet Epidemiol       Date:  1999       Impact factor: 2.135

7.  Longitudinal variance-components analysis of the Framingham Heart Study data.

Authors:  Stuart Macgregor; Sara A Knott; Ian White; Peter M Visscher
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

8.  Genetic analyses of longitudinal phenotype data: a comparison of univariate methods and a multivariate approach.

Authors:  Qiong Yang; Irmarie Chazaro; Jing Cui; Chao-Yu Guo; Serkalem Demissie; Martin Larson; Larry D Atwood; L Adrienne Cupples; Anita L DeStefano
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

  8 in total
  3 in total

1.  Segregation and linkage analysis for longitudinal measurements of a quantitative trait.

Authors:  Conway Gee; John L Morrison; Duncan C Thomas; W James Gauderman
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

2.  Multilevel modeling for the analysis of longitudinal blood pressure data in the Framingham Heart Study pedigrees.

Authors:  Laurent Briollais; Anjela Tzontcheva; Shelley Bull
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

3.  Genome-wide linkage analysis of longitudinal phenotypes using sigma2A random effects (SSARs) fitted by Gibbs sampling.

Authors:  Lyle J Palmer; Katrina J Scurrah; Martin Tobin; Sanjay R Patel; Juan C Celedon; Paul R Burton; Scott T Weiss
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

  3 in total

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