Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 3 complete abstracts (443 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Addition of methyl groups. In histo-chemistry methylation is used to esterify carboxyl groups and remove sulfate groups by treating tissue sections with hot methanol in the presence of hydrochloric acid. (From Stedman, 25th ed)
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Methylations.
Where it fits in the MeSH classification
- Broader topics
- Alkylation
- Narrower topics
- DNA Methylation; RNA Methylation
Research landscape
PubMed indexes 111,108 records tagged with the MeSH heading “Methylation” (counts retrieved 2026-10-29). 32,155 of them (28.9%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 44,139 records.
Reviews account for 14,815 records (13.3%) and meta-analyses for 698. Randomized controlled trials number 461 (0.4%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 15,858 |
| 2000-2009 | 18,956 |
| 2010-2019 | 44,139 |
| 2020 onward | 32,155 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 14,815 | 13.3% |
| Meta-analyses | 698 | 0.6% |
| Randomized controlled trials | 461 | 0.4% |
Method: PubMed query "Methylation"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in molecular biology
Molecular biology establishes mechanisms through controlled experiments, often in simplified systems such as purified proteins, cultured cells or model organisms. Such work can show what is possible in a defined system, but whether a pathway matters in a whole organism or in human disease needs further evidence. Check the experimental system, whether findings were reproduced by independent groups, and whether the authors tested the mechanism directly or inferred it from correlation.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Identification of methylation-sensitive human transcription factors using meSMiLE-seq | 2026 | Research article Design not recorded in structured metadata | 6 | cc by PMID 42557242 · DOI · PMC13444138 |
| Longitudinal changes in DNA methylation in IDH-mutant glioma fuel disease progression through altered cell state differentiation | 2026 | Research article Design not recorded in structured metadata | 6 | cc by PMID 42332268 · DOI · PMC13364636 |
| Meta-analysis of DNA methylation aging signatures in 17 human tissues | 2026 | Meta-analysis Design not recorded in structured metadata | 6 | cc by PMID 42362890 · DOI · PMC13375584 |
Identification of methylation-sensitive human transcription factors using meSMiLE-seq [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown.
- Closing excerpt
- Altogether, our study significantly expands the human TF codebook, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (150 words)
Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown. Here, we assay 284 mostly uncharacterized putative human TFs using selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq), revealing 74 new DNA binding motifs. To investigate whether TFs lacking detectable motifs preferably bind epigenetically modified DNA, we develop methylation-sensitive SMiLE-seq (meSMiLE-seq), a microfluidic assay that simultaneously probes binding to methylated and unmethylated DNA. Using meSMiLE-seq, we assay 114 TFs and identify DNA-binding models for 48 proteins, including known methylation-sensitive binding modes for POU5F1 and RFX5. 11 TFs prefer methylated DNA or display alternative methylation-dependent motifs (e.g. PRDM13), while 13 show aversion to methylated sequences (e.g. USF3). Finally, we identify ZHX2 as a putative Z-DNA binder. Altogether, our study significantly expands the human TF codebook, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42557242 · DOI · PMC13444138
Longitudinal changes in DNA methylation in IDH-mutant glioma fuel disease progression through altered cell state differentiation [2]
Abstract reading summary — source excerpts
- Opening excerpt
- The progression of isocitrate dehydrogenase-mutant glioma (IDH-G) from slow-growing tumor to fatal disease is associated with transcriptional and DNA methylation changes that remain poorly understood.
- Closing excerpt
- Our study offers insights into how DNA methylation loss reshapes cellular transitions and how it may mark clinically more aggressive tumors across IDH-G subsets.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (148 words)
The progression of isocitrate dehydrogenase-mutant glioma (IDH-G) from slow-growing tumor to fatal disease is associated with transcriptional and DNA methylation changes that remain poorly understood. Here, we profiled a longitudinal cohort of 36 IDH-G samples from 19 patients by joint-capture multi-omic single-nucleus DNA methylation, single-nucleus RNA sequencing and bulk exome sequencing. We show that IDH-G progression is associated with an increase in malignant stem-like states, decreased differentiation and methylation loss, which marks tumors with worse clinical outcome. Methylation loss was uniformly observed across malignant cells within individual tumors, suggesting that it may underlie rather than result from the increase in stem-like states. Analysis of cell-state heritability and plasticity using high-resolution phylogenetic trees links DNA methylation loss to alterations in glioma cell-state encoding and heritability. Our study offers insights into how DNA methylation loss reshapes cellular transitions and how it may mark clinically more aggressive tumors across IDH-G subsets.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42332268 · DOI · PMC13364636
Meta-analysis of DNA methylation aging signatures in 17 human tissues [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Epigenetic changes, in particular DNA methylation, accumulate with age across different tissues, but whether these changes follow consistent patterns across different organs remains poorly understood.
- Closing excerpt
- Our methylation atlas therefore provides a resource for dissecting the molecular basis of human aging and for identifying potential biomarkers and translational therapies.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (145 words)
Epigenetic changes, in particular DNA methylation, accumulate with age across different tissues, but whether these changes follow consistent patterns across different organs remains poorly understood. Here we show, through a meta-analysis of more than 15,000 human methylation profiles spanning 17 tissues, that aging produces both conserved and tissue-specific epigenetic signatures. We identify systemic shifts in methylation levels, increases in methylation variability, and growing molecular disorder across tissues. Network analysis revealed tightly connected gene clusters that are not modified by beneficial interventions, alongside a more modifiable cluster linked to NAD+ metabolism, supporting NAD+ as a potential therapeutic target in aging. A gene encoding a cell-adhesion protein, PCDHGA1, emerged as a conserved hub across tissues, implicating cell-to-cell communication pathways in aging across multiple organs. Our methylation atlas therefore provides a resource for dissecting the molecular basis of human aging and for identifying potential biomarkers and translational therapies.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42362890 · DOI · PMC13375584
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article DNA methylation-based measures of biological age: meta-analysis predicting time to death [4]
- Research article Epigenetic Signatures of Cigarette Smoking [5]
- Research article DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis [6]
- Research article The epigenetic clock as a predictor of disease and mortality risk: a systematic review and meta-analysis [7]
- Research article DNA methylation screening identifies driver epigenetic events of cancer cell survival [8]
- Research article Traumatic stress and accelerated DNA methylation age: A meta-analysis [9]
References
- Gralak AJ, Faltejskova K, Yang AWH, Steiner C, Russeil J, Grenningloh N, et al.. Identification of methylation-sensitive human transcription factors using meSMiLE-seq. . 2026. PMID 42557242 · DOI · PMC13444138
- Nomura M, Raviram R, Schiffman JS, Bussema L, Lu V, Wheeler N, et al.. Longitudinal changes in DNA methylation in IDH-mutant glioma fuel disease progression through altered cell state differentiation. . 2026. PMID 42332268 · DOI · PMC13364636
- Jacques M, Seale K, Voisin S, Lysenko A, Grolaux R, Jones-Freeman B, et al.. Meta-analysis of DNA methylation aging signatures in 17 human tissues. . 2026. PMID 42362890 · DOI · PMC13375584
- Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, et al.. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY). 2016. PMID 27690265 · DOI · PMC5076441
- Joehanes R, Just AC, Marioni RE, Pilling LC, Reynolds LM, Mandaviya PR, et al.. Epigenetic Signatures of Cigarette Smoking. Circ Cardiovasc Genet. 2016. PMID 27651444 · DOI · PMC5267325
- Joubert BR, Felix JF, Yousefi P, Bakulski KM, Just AC, Breton C, et al.. DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis. Am J Hum Genet. 2016. PMID 27040690 · DOI · PMC4833289
- Fransquet PD, Wrigglesworth J, Woods RL, Ernst ME, Ryan J. The epigenetic clock as a predictor of disease and mortality risk: a systematic review and meta-analysis. Clin Epigenetics. 2019. PMID 30975202 · DOI · PMC6458841
- De Carvalho DD, De Carvalho DD, Sharma S, You JS, Su SF, Taberlay PC, et al.. DNA methylation screening identifies driver epigenetic events of cancer cell survival. Cancer Cell. 2012. PMID 22624715 · DOI · PMC3395886
- Wolf EJ, Maniates H, Nugent N, Maihofer AX, Armstrong D, Ratanatharathorn A, et al.. Traumatic stress and accelerated DNA methylation age: A meta-analysis. Psychoneuroendocrinology. 2018. PMID 29452766 · DOI · PMC5924645
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.