Mixed effects modeling of proliferation rates in cell-based models: Consequence for pharmacogenomics and Cancer

Hae Kyung Im, Eric R. Gamazon, Amy L. Stark, R. Stephanie Huang, Nancy J. Cox, M. Eileen Dolan

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

The International HapMap project has made publicly available extensive genotypic data on a number of lymphoblastoid cell lines (LCLs). Building on this resource, many research groups have generated a large amount of phenotypic data on these cell lines to facilitate genetic studies of disease risk or drug response. However, one problem that may reduce the usefulness of these resources is the biological noise inherent to cellular phenotypes. We developed a novel method, termed Mixed Effects Model Averaging (MEM), which pools data from multiple sources and generates an intrinsic cellular growth rate phenotype. This intrinsic growth rate was estimated for each of over 500 HapMap cell lines. We then examined the association of this intrinsic growth rate with gene expression levels and found that almost 30% (2,967 out of 10,748) of the genes tested were significant with FDR less than 10%. We probed further to demonstrate evidence of a genetic effect on intrinsic growth rate by determining a significant enrichment in growth-associated genes among genes targeted by top growth-associated SNPs (as eQTLs). The estimated intrinsic growth rate as well as the strength of the association with genetic variants and gene expression traits are made publicly available through a cell-based pharmacogenomics database, PACdb. This resource should enable researchers to explore the mediating effects of proliferation rate on other phenotypes.

Original languageEnglish (US)
Article numbere1002525
JournalPLoS genetics
Volume8
Issue number2
DOIs
StatePublished - Feb 1 2012

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pharmacogenomics
Pharmacogenetics
cancer
cell lines
phenotype
neoplasms
Growth
modeling
Neoplasms
gene expression
HapMap Project
genes
cells
gene
resource
Phenotype
Cell Line
researchers
drugs
Genes

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Mixed effects modeling of proliferation rates in cell-based models : Consequence for pharmacogenomics and Cancer. / Im, Hae Kyung; Gamazon, Eric R.; Stark, Amy L.; Huang, R. Stephanie; Cox, Nancy J.; Dolan, M. Eileen.

In: PLoS genetics, Vol. 8, No. 2, e1002525, 01.02.2012.

Research output: Contribution to journalArticle

Im, Hae Kyung ; Gamazon, Eric R. ; Stark, Amy L. ; Huang, R. Stephanie ; Cox, Nancy J. ; Dolan, M. Eileen. / Mixed effects modeling of proliferation rates in cell-based models : Consequence for pharmacogenomics and Cancer. In: PLoS genetics. 2012 ; Vol. 8, No. 2.
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