Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Systemic infections alter cortical transcriptional signatures in Alzheimer's disease.

Neurobiology of aging·2026

Same author

DNA methylation profiling in Huntington's disease reveals disease associated changes in the striatum.

Clinical epigenetics·2026

Same author

Methylomic signatures of tau and amyloid-beta in transgenic mouse models of Alzheimer's disease neuropathology.

NPJ dementia·2026

Same author

Epigenomic subtypes of late-onset Alzheimer's disease reveal distinct microglial signatures.

Acta neuropathologica·2026

Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025

Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025

Search research articles

Related Experiment Video

Updated: May 2, 2026

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Published on: July 12, 2012

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

Joshua Müller¹, Valentin T Laroche¹, Jennifer Imm²

¹Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, The Netherlands.

|December 22, 2025

Summary

This summary is machine-generated.

We developed CEAM, a new tool to analyze cell type-specific DNA methylation changes in bulk tissue. This method enhances epigenome-wide association studies (EWAS) by improving accuracy in neurodegenerative disease research.

Keywords:

DNA methylation brain cell type epigenomics neurodegenerative diseases

More Related Videos

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

Published on: January 23, 2019

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Related Experiment Videos

Last Updated: May 2, 2026

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Published on: July 12, 2012

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

Published on: January 23, 2019

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Area of Science:

Neuroscience
Genetics
Computational Biology

Background:

DNA methylation (DNAm) patterns are cell type-specific, but bulk tissue analysis in epigenome-wide association studies (EWAS) can obscure these crucial details.
Current computational tools for identifying cell type-specific DNAm changes face limitations due to the accuracy of cell type deconvolution algorithms.

Purpose of the Study:

Introduce CEAM (Cell-type Enrichment Analysis for Methylation), a robust framework for cell type enrichment analysis in DNA methylation data.
To provide an interpretable and accurate method for analyzing cell type-specific DNAm from bulk tissue EWAS data.

Main Methods:

CEAM utilizes over-representation analysis with cell type-specific CpG panels derived from sorted brain nuclei.
CpG panels were validated using simulated data and published EWAS results from Alzheimer's disease, Lewy body disease, and multiple sclerosis.
The framework was tested for resilience to cell type composition shifts and varying accuracy in upstream modeling.

Main Results:

CEAM demonstrated robustness against shifts in cell type composition, a common EWAS confounder.
The tool remained accurate across various differentially methylated positions when cell type composition was adequately modeled.
Application to neurodegenerative disease EWAS data revealed biologically relevant enrichment patterns consistent with known disease mechanisms.

Conclusions:

CEAM offers a reliable and interpretable method for uncovering cell type-specific DNA methylation patterns in bulk tissue.
The framework enhances the biological relevance and accuracy of EWAS findings, particularly in neurodegenerative disease research.
CEAM is available as a public Shiny app for accessible analysis of cell type-specific DNAm changes.