ArticleNucleic acids research2014
Predicting DNA methylation level across human tissues.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
70 citing papers in PubMed, 121 citations in OpenAlex.
- LINE-1 methylation levels, a biomarker of weight loss in obese subjects, are influenced by dietary antioxidant capacity.Redox report : communications in free radical research · 2016Trial
- No effect of weight loss on LINE-1 methylation levels in peripheral blood leukocytes from postmenopausal overweight women.Obesity (Silver Spring, Md.) · 2014Trial
- Environmental Exposures and Epigenetic Remodeling in Supraventricular Tachycardias: What Atrial Fibrillation Can and Cannot Tell Us.Life (Basel, Switzerland) · 2026Review
- DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.PLoS computational biology · 2026Article
- DNA methylation as a biomarker of prenatal exposures: current challenges and opportunities.Environmental epigenetics · 2026Review
- Blood DNA Methylation Analysis Reveals a Distinctive Epigenetic Signature of Vasospasm in Aneurysmal Subarachnoid Hemorrhage.Translational stroke research · 2025Article
- Longitudinal Analysis of PlacentalInternational journal of molecular sciences · 2025Article
- Blood-Based DNA Methylation Biomarkers to Identify Risk and Progression of Cardiovascular Disease.International journal of molecular sciences · 2025Review
- Epigenetic Clocks: Beyond Biological Age, Using the Past to Predict the Present and Future.Aging and disease · 2024Review
- From Mother to Child: Epigenetic Signatures of Hyperglycemia and Obesity during Pregnancy.Nutrients · 2024Article
- Predicting locus-specific DNA methylation levels in cancer and paracancer tissues.Epigenomics · 2024Article
- DNA methylation is associated with hair trace elements in female adolescents from two vulnerable populations in the Colombian Caribbean.Environmental epigenetics · 2024Article
- MLACNN: an attention mechanism-based CNN architecture for predicting genome-wide DNA methylation.Theory in biosciences = Theorie in den Biowissenschaften · 2023Article
- DNA Methylation and Telomeres-Their Impact on the Occurrence of Atrial Fibrillation during Cardiac Aging.International journal of molecular sciences · 2023Review
- Low H3K27 acetylation of SF1 in PBMC: a biomarker for prenatal dexamethasone exposure-caused adrenal insufficiency of steroid synthesis in male offspring.Cell biology and toxicology · 2023Article
- DNA methylation-based biomarkers for cardiometabolic-related traits and their importance for risk stratification.Current opinion in epidemiology and public health · 2023Article
- Completing Single-Cell DNA Methylome ProfilesFrontiers in genetics · 2022Article
- DNA Methylation Imputation Across Platforms.Methods in molecular biology (Clifton, N.J.) · 2022Review
- DNA methylation profile of genes involved in inflammation and autoimmunity correlates with vascular function in morbidly obese adults.Epigenetics · 2022Article
- Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach.BMC bioinformatics · 2021Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
Abstract
Differences in methylation across tissues are critical to cell differentiation and are key to understanding the role of epigenetics in complex diseases. In this investigation, we found that locus-specific methylation differences between tissues are highly consistent across individuals. We developed a novel statistical model to predict locus-specific methylation in target tissue based on methylation in surrogate tissue. The method was evaluated in publicly available data and in two studies using the latest IlluminaBeadChips: a childhood asthma study with methylation measured in both peripheral blood leukocytes (PBL) and lymphoblastoid cell lines; and a study of postoperative atrial fibrillation with methylation in PBL, atrium and artery. We found that our method can greatly improve accuracy of cross-tissue prediction at CpG sites that are variable in the target tissue [R(2) increases from 0.38 (original R(2) between tissues) to 0.89 for PBL-to-artery prediction; from 0.39 to 0.95 for PBL-to-atrium; and from 0.81 to 0.98 for lymphoblastoid cell line-to-PBL based on cross-validation, and confirmed using cross-study prediction]. An extended model with multiple CpGs further improved performance. Our results suggest that large-scale epidemiology studies using easy-to-access surrogate tissues (e.g. blood) could be recalibrated to improve understanding of epigenetics in hard-to-access tissues (e.g. atrium) and might enable non-invasive disease screening using epigenetic profiles.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.