Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data of skeletal muscle from HRT users and non-users

ABSTRACT: Modification of Gene Expression of Skeletal Muscle in Response to postmenopause with or without Hormone Replacement Therapy. Even though menopause is often accompanied with first signs of age-associated changes in muscle structure and function, the effects of hormone replacement therapy (HRT) or menopause-related decline in estrogen production in the muscles of postmenopausal women is not well understood. We have used a randomized double-blinded study design together with an explorative microarray experiment to characterize possible effects of continuous, combined HRT and estrogen deprivation on the skeletal muscle of fifteen early postmenopausal women from which 10 used HRT and 5 used placebo for 12-months in a douple-blinded design. Keywords: time course analysis from HRT users and non-users comparison of gene expression in skeletal muscle of healthy postmenopausel women using HRT (n=10) vs not-using HRT (n=5)

ORGANISM(S): Homo sapiens

SUBMITTER: Eija Pöllänen

PROVIDER: E-GEOD-6348 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Muscular transcriptome in postmenopausal women with or without hormone replacement.

Pöllänen Eija E Ronkainen Paula H A PH Suominen Harri H Takala Timo T Koskinen Satu S Puolakka Jukka J Sipilä Sarianna S Kovanen Vuokko V

Rejuvenation research 20071201 4

The loss of muscle mass and strength with aging is well characterized, but our knowledge of the molecular mechanisms underlying the development of sarcopenia remains incomplete. Although menopause is often accompanied with first signs of age-associated changes in muscle structure and function, the effects of hormone replacement therapy (HRT) or menopause-related decline in estrogen production in the muscles of postmenopausal women is not well understood. Furthermore the knowledge of the global t ...[more]

PMID: 17985945

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Project description:A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on DNA methylation, mRNA expression and microRNA (miRNA) expression in four distinct human brain regions. We show that brain tissues may be readily distinguished based on methylation status or expression profile. We find an abundance of genetic cis regulation mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation. Authorized Access data: Mapping of GEO sample accessions to dbGaP subject/sample IDs is available through dbGaP Authorized Access, see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000249.v1.p1 Because of our interest in genomic regulation of expression and neurological disorders we embarked upon a series of experiments to provide a brain region-specific contextual framework for genetic and epigenetic regulation of gene expression. We obtained frozen brain tissue from the cerebellum, frontal cortex, pons and temporal cortex from 150 subjects (total 600 tissue samples). We undertook four separate assays across this series; first, genome-wide SNP genotyping; second, assay of >27,000 CpG methylation sites in each of the four brain regions; third, mRNA expression profiling of >22,000 transcripts in all four brain regions; and, fourth, miRNA expression profiling of 735 miRNA transcripts. Here we discuss the results of these experiments, particularly in the context of integrated datasets to define expression and CpG methylation quantitative trait loci (eQTL and methQTL) and detailing differences and similarities across brain regions.

Dataset Information

Expression data of skeletal muscle from HRT users and non-users

Publications

Muscular transcriptome in postmenopausal women with or without hormone replacement.

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