Dataset Information


Transcription profiling of human skeletal muscle from males with type 2 diabetes to identify genes involved in oxidative phosphorylation

ABSTRACT: DNA microarrays can be used to discover gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1a, and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism, and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

INSTRUMENT(S): Affymetrix Fluidics Station 400

ORGANISM(S): Homo sapiens  

DISEASE(S): Abnormal Glucose Tolerance,Diabetes Mellitus Type 2,Normal

SUBMITTER: David Altshuler   Junmin Liu  

PROVIDER: E-CBIL-30 | ArrayExpress | 2007-07-17


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Disease and phenotype gene set analysis of disease-based gene expression in mouse and human.

De Supriyo S   Zhang Yongqing Y   Garner John R JR   Wang S Alex SA   Becker Kevin G KG  

Physiological genomics 20100803 2

The genetic contributions to common disease and complex disease phenotypes are pleiotropic, multifactorial, and combinatorial. Gene set analysis is a computational approach used in the analysis of microarray data to rapidly query gene combinations and multifactorial processes. Here we use novel gene sets based on population-based human genetic associations in common human disease or experimental genetic mouse models to analyze disease-related microarray studies. We developed a web-based analysis  ...[more]

Publication: 1/2

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