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>>>> 24 June 2009 <<<<
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Genomics. 2009 Jun 17.
An Integrated Approach to Infer Causal
Associations among Gene Expression,
Genotype Variation, and Disease.
Lee E, Cho S, Kim K, Park T.
Interdisciplinary Program in Bioinformatics, Seoul
National University, Seoul, Korea.
Gene expression data and genotype variation data
are now capable of providing genome-wide patterns
across many different clinical conditions.
However, the separate analysis of these data has
limitations in elucidating the complex network of
gene interactions underlying complex traits, such as
common human diseases.
More information about the identity of key driver
genes of common diseases comes from integrating
these two heterogeneous types of data.
We developed a two-step procedure to characterize
complex diseases by integrating genotype variation
data and gene expression data.
The first step elucidates the causal relationship
among genetic variation, gene expression level, and
Based on the causal relationship determined at the
first step, the second step identifies significant gene
expression traits whose effects on disease status or
whose responses to disease status are modified by
the specific genotype variation.
For the selected significant genes, a pathway
enrichment analysis can be performed to identify the
genetic mechanism of a complex disease.
The proposed two-step procedure was shown to be
an effective method for integrating three different
levels of data, i.e., genotype variation, gene
expression and disease status.
By applying the proposed procedure to a chronic
fatigue syndrome (CFS) dataset, we identified a list
of potential causal genes for CFS, and found an
evidence for difference in genetic mechanisms of the
etiology between CFS without 'a major depressive
disorder with melancholic features' (CFS) and CFS
with 'a major depressive disorder with melancholic
Especially, the SNPs within NR3C1 gene were shown
to differently influence the susceptibility of
developing CFS and CFS-MDD/m through integrative
action with gene expression levels.
PMID: 19540336 [PubMed - as supplied by publisher]