GEO series

Human Aging-associated DNA Hypermethylation Occurs Preferentially at Bivalent Chromatin Domains

GSE20242 Homo sapiens (human) DNA methylation 50 samples Submitted 2010/02/10 Platform GPL8490

At a glance

DNA methylation · human · 50 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 50 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

There is a growing realization that some aging-associated phenotypes/diseases have an epigenetic basis. Here we report the first genome-scale study of epigenomic dynamics during normal human aging. We identify aging-associated differentially methylated regions (aDMRs) in whole blood in a discovery cohort, and then replicate these aDMRs in sorted CD4+ T-cells and CD14+ monocytes in an independent cohort, suggesting that aDMRs occur in precursor haematopoietic cells.

Read the full summary ↓

Further replication of the aDMRs in buccal cells, representing a tissue that originates from a different germ-layer compared with blood, demonstrates that the aDMR signature is a multi-tissue phenomenon. Moreover, we demonstrate that aging-associated DNA hypermethylation occurs predominantly at bivalent chromatin domain promoters. This same category of promoters, associated with key developmental genes, is frequently hypermethylated in cancers and in vitro cell culture, pointing to a novel mechanistic link between aberrant hypermethylation in cancer, aging, and cell culture.

This dataset

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Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE20242_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA125673. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 20219945) ↗

Samples in this study

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+ 50 more — browse all 50 samples with per-sample file links →

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