ReviewHuman molecular genetics2017
Cell-type deconvolution from DNA methylation: a review of recent applications.
Review in Human molecular genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers, 5 of them syntheses that pooled it.
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
136 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Recent developments in omics studies and artificial intelligence in depression and suicide.Translational psychiatry · 2025Pooled it
- Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.PLoS pathogens · 2024Pooled it
- Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review.Neuroscience and biobehavioral reviews · 2023Pooled it
- Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis.Neuroscience and biobehavioral reviews · 2023Pooled it
- An effective processing pipeline for harmonizing DNA methylation data from Illumina's 450K and EPIC platforms for epidemiological studies.BMC research notes · 2021Pooled it
- An analysis of the effect of mu-opioid receptor gene (OPRM1) promoter region DNA methylation on the response of naltrexone treatment of alcohol dependence.The pharmacogenomics journal · 2020Trial
- Methylation-derived Neutrophil-to-Lymphocyte Ratio and Lung Cancer Risk in Heavy Smokers.Cancer prevention research (Philadelphia, Pa.) · 2018Trial
- Evaluation of DNA methylation-based age prediction accuracy in leukemia patients using a six-CpG model trained on healthy blood.Forensic science, medicine, and pathology · 2026Article
- Metastasis-associated DNA methylation alterations persist after accounting for immune and stromal cell heterogeneity in primary colorectal tumors.Research square · 2026Article
- Article
- Inflammatory and Epigenetic Biomarkers in Prostate Disease: Current Evidence, Clinical Limitations, and Future Multimarker Strategies.Diagnostics (Basel, Switzerland) · 2026Review
- Methylome-wide association study in blood suggests cell type-specific relationships between DNA methylation and lifetime anxiety.Nature communications · 2026Article
- A large-scale DNA methylation study of alcohol use identified robust associations and cell-type specific insights.Molecular psychiatry · 2026Article
- Cardiac epigenome in heart development and disease.Nature reviews. Cardiology · 2026Review
- Ontology-aware DNA methylation classification with a curated atlas of human tissues and cell types.Cell reports methods · 2026Article
- Immune Cell Type-Specific DNA Methylation Regions Associate With 24-Hour Blood Pressure Regulation in Black People.Journal of the American Heart Association · 2026Article
- Environmental exposures and epigenetic alterations in common chronic diseases: insights and challenges.Environmental epigenetics · 2026Review
- Circulating neuron-derived cfDNA for blood-based detection of Alzheimer's and other neurodegenerative conditions.Frontiers in neurology · 2026Article
- Article
- Article
76 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
4 authors.
Funding
Abstract
Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).
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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.