ArticleScientific data2025
MethAgingDB: a comprehensive DNA methylation database for aging biology.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications.Molecular therapy. Nucleic acids · 2026Article
- High-fidelity bidirectional translation between single-cell transcriptomes and DNA methylomes with scBOND.Genome research · 2026Article
- TranslAGE: A Comprehensive Platform for Systematic Validation of Epigenetic Aging Biomarkers.bioRxiv : the preprint server for biology · 2025Article
- MethAgingDB: a comprehensive DNA methylation database for aging biology.Scientific data · 2025Article
- DNA methylation and prediction of biological age.Frontiers in molecular biosciences · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurately quantifying biological age is crucial for understanding the mechanisms of aging and developing effective interventions. Molecular aging clocks, particularly epigenetic clocks that use DNA methylation data to estimate biological age, have become essential tools in this area of research. However, the lack of a comprehensive, publicly accessible database with uniformly formatted DNA methylation datasets across various ages and tissues complicates the investigation of epigenetic clocks. Researchers face significant challenges in locating relevant datasets, accessing key information from raw data, and managing inconsistent data formats and metadata annotations. Additionally, there is a lack of dedicated resources for aging-related differentially methylated sites (DMSs, also named differentially methylated positions or differentially methylated cytosines) and regions (DMRs), which hinders progress in understanding the epigenetic mechanisms of aging. To address these challenges, we developed MethAgingDB, a comprehensive DNA methylation database for aging biology. MethAgingDB includes 93 datasets, with 11474 profiles from 13 distinct human tissues and 1361 profiles from 9 distinct mouse tissues. The database provides preprocessed DNA methylation data in a consistent matrix format, along with tissue-specific DMSs and DMRs, gene-centric aging insights, and an extensive collection of epigenetic clocks. Together, MethAgingDB is expected to streamline aging-related epigenetic research and support the development of robust, biologically informed aging biomarkers.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.