The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Aging effects on DNA methylation modules in human brain and blood tissue
Open accessAbstract
Background: Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues. Results: We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained. Conclusions: Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles.
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Cites
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Self-citationHierarchical Organization of Modularity in Metabolic Networks
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Is My Network Module Preserved and Reproducible?
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Self-citationEigengene networks for studying the relationships between co-expression modules
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Background
Cited by
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075
Self-citationAn epigenetic biomarker of aging for lifespan and healthspan
Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., Bandinelli, S., Hou, L., Baccarelli, A. A., Stewart, J. D., Li, Y., et al. (2018) · Aging · doi:10.18632/aging.101414 · Cited by 3,675
Self-citationDNA methylation-based biomarkers and the epigenetic clock theory of ageing
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Self-citationAccounting for cellular heterogeneity is critical in epigenome-wide association studies
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Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci
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“8,10-12 In this study, we present the results of a statistically rigorous gene discovery effort to identify regions of the genome that are differentially methylated in relation to the burden of AD neuropathology.”
Metadata
- Authors
- Horvath, S., Zhang, Y., Langfelder, P., Kahn, R. S., Boks, M. P., van Eijk, K., van den Berg, L. H., & Ophoff, R. A.
- Venue
- Genome Biology
- Published
- 2012-10-03
- Volume
- 13
- Issue
- 10
- Pages
- R97-R97
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- OpenAlex
- W1990958459
- Cited by
- 645
- References
- 15
- FWCI
- 13.59
- Type
- journal article
- Language
- en
- Open access
- gold
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