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PMID: 16451585 Published · epublish English Journal Article Research Support, N.I.H., Extramural

Mixed-effects Cox models of alcohol dependence in extended families.

BMC genetics ·Vol. 6 Suppl 1 ·2005-12-30 ·Pages S127

Zhao Jh

Abstract

The presence of disease is commonly used in genetic studies; however, the time to onset often provides additional information. To apply the popular Cox model for such data, it is desirable to consider the familial correlation, which involves kinship or identity by descent (IBD) information between family members. Recently, such a framework has been developed and implemented in a UNIX-based S-PLUS package called kinship, extending the Cox model with mixed effects and familial relationship. The model is of great potential in joint analysis of family data with genetic and environmental factors. We apply this framework to data from the Collaborative Study on the Genetics of Alcoholism data as part of Genetic Analysis Workshop 14. We use the S-PLUS package, ported into the R environment http://www.r-project.org, for the analysis of microsatellite data on chromosomes 4 and 7. In these analyses, IBD information at those markers is used in addition to the basic Cox model with mixed effects, which provides estimates of the relative contribution of specific genetic markers. D4S1645 had the largest variance and contribution to the log-likelihood on chromosome 4, but the significance of this finding requires further investigation.

MeSH Terms
Alcoholism/epidemiology,genetics Family Female Genetic Markers Humans Male Models, Genetic Proportional Hazards Models
Chemicals
Genetic Markers
Authors & Affiliations
1 authors, click to expand affiliations / ORCID
Zhao Jing hua
Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK. j.zhao@ucl.ac.uk
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Article Info
Journal
BMC genetics
Abbr.
BMC Genet
ISSN
1471-2156
Published
2005-12-30
Epub
2005-00-30
Pages
S127
Language
English
Region
England
NLM ID
100966978
PMCID
PMC1866810
Subset
IM
Grants
NIA NIH HHS · R01 AG013196 · United States
NIA NIH HHS · R37 AG013196 · United States
NIA NIH HHS · AG13196 · United States
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