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Series GSE22309 Query DataSets for GSE22309
Status Public on Jun 16, 2010
Title Expression data from human skeletal muscle
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Insulin is a potent pleiotropic hormone that affects processes such as cellular growth, differentiation, apoptosis, ion flux, energy expenditure, and carbohydrate, lipid, and protein metabolism.
We used microarrays to detail the global programme of gene expression underlying the influence of insulin in human skeletal muscle collected from different human individuals including 20 insulin sensitive, 20 insulin resistant and 15 diabetic patients. We identified distinct classes of up-regulated and down-regulated genes during these processes.
The pathophysiology of obesity represents an imbalance between a high energy intake and/or low energy expenditure. Resting energy expenditure (REE) comprises 60-75% of total energy expenditure. The respiratory quotient (RQ) is used to estimate fuel partitioning between fat and carbohydrate as preferred substrates for energy generation, and fuel preferences to generate REE also exhibit individual variation. Genes influencing REE and RQ could represent candidate genes for obesity, Metabolic Syndrome, and Type 2 Diabetes due to the involvement of these traits in energy balance and substrate oxidation.
We used microarrays to explore the molecular bases for individual variation in REE and fuel partitioning as reflected by RQ. We performed microarray studies in human vastus lateralis muscle biopsies from 40 healthy subjects with measured REE and RQ values. We identified genes significantly correlated with REE and RQ, respectively.
 
Overall design Human skeletal muscle samples were biopsied from different individuals before and after insulin treatment for RNA extraction and hybridization on Affymetrix microarrays.
 
Contributor(s) Garvey TW, Maianu L, Martin M, Wu X, Page GP, Wang J, Allison DB
Citation(s) 17709892, 21109598
Submission date Jun 11, 2010
Last update date Jul 08, 2016
Contact name Jelai Wang
E-mail(s) jwang@ms.soph.uab.edu
URL http://www.ssg.uab.edu
Organization name University of Alabama at Birmingham
Department Biostatistics
Street address 1665 University Blvd, Ryals 327
City Birmingham
State/province AL
ZIP/Postal code 35294
Country USA
 
Platforms (1)
GPL91 [HG_U95A] Affymetrix Human Genome U95A Array
Samples (110)
GSM555237 a10a.000606jd.2.SkMNor907.CEL-IS basal
GSM555238 a10a.000606jd.2.SkMNor908.CEL-IS stimulate
GSM555239 a10a.000606jd.2.SkMNor911.CEL-IS basal
Relations
BioProject PRJNA127389

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE22309_MAS5-processed-data.txt.gz 2.7 Mb (ftp)(http) TXT
GSE22309_RAW.tar 344.2 Mb (http)(custom) TAR (of CEL)
GSE22309_design.txt.gz 1.1 Kb (ftp)(http) TXT
Processed data included within Sample table
Processed data are available on Series record
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