Evidence map›Paper›PMID 41428862›Full record

ArticleEpigenetics2026

A cell type enrichment analysis tool for brain DNA methylation data (CEAM).

Joshua Müller, Valentin T Laroche, Jennifer Imm, Luke Weymouth, Joshua Harvey, Rick A Reijnders, Adam R Smith, Daniel van den Hove, Katie Lunnon, Rachel Cavill and 1 more

Abstract read
In one paragraph

Article in Epigenetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Joshua MüllerDepartment of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.
Valentin T LarocheDepartment of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.ORCID 0009-0002-2952-3043
Jennifer ImmDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.ORCID 0000-0002-8827-8669
Luke WeymouthDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Joshua HarveyDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.ORCID 0000-0001-6423-9983
Rick A ReijndersDepartment of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.ORCID 0000-0001-7599-0385
Adam R SmithDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Daniel van den HoveDepartment of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.ORCID 0000-0003-4047-3198
Katie LunnonDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Rachel CavillDepartment of Advanced Computing Sciences, Faculty of Science and Engineering (FSE), Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-3796-1687
Ehsan PishvaDepartment of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-8964-0682

Funding

A multi-omic approach to elucidate novel disease mechanisms and biomarkers for psychosis in Alzheimer’s diseaseR01AG067015 · NIA · UNIVERSITY OF EXETER · PI KOFLER, JULIA K, LUNNON, KATIE · 2019 to 2023
$1.6M
NIA NIH HHS R01 AG067015
6 · The paper itself

Abstract

DNA methylation (DNAm) signatures are highly cell type-specific, yet most epigenome-wide association studies (EWAS) are performed on bulk tissue, potentially obscuring critical cell type-specific patterns. Existing computational tools for detecting cell type-specific DNAm changes are often limited by the accuracy of cell type deconvolution algorithms. Here, we introduce CEAM (Cell-type Enrichment Analysis for Methylation), a robust and interpretable framework for cell type enrichment analysis in DNA methylation data. CEAM applies over-representation analysis with cell type-specific CpG panels from Illumina EPIC arrays derived from nuclei-sorted cortical post-mortem brains from neurologically healthy aged individuals. The constructed CpG panels were systematically evaluated using both simulated datasets and published EWAS results from Alzheimer's disease, Lewy body disease, and multiple sclerosis. CEAM demonstrated resilience to shifts in cell type composition, a common confounder in EWAS, and remained robust across a wide range of differentially methylated positions, when upstream modeling of cell type composition was modeled with sufficient accuracy. Application to existing EWAS findings generated in neurodegenerative diseases revealed enrichment patterns concordant with established disease biology, confirming CEAM's biological relevance. The workflow is publicly available as an interactive Shiny app (https://um-dementia-systems-biology.shinyapps.io/CEAM/) enabling rapid, interpretable analysis of cell type-specific DNAm changes from bulk EWAS.

Indexed as

BrainDNA MethylationSoftwareAlgorithmsAlzheimer DiseaseCpG IslandsGenome-Wide Association StudyHumansbraincell typeDNA methylationepigenomicsneurodegenerative diseases

Identifiers

PMID41428862
PMCPMC12724277

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Registered trials

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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.