Peripheral blood DNA methylation partially reports on immune cell type composition in the frontal brain.

Overview

1. Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
2. British Columbia Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada
3. Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada
4. Edwin S. H. Leong Centre for Healthy Aging, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
5. Department of Psychiatry, McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
6. Department of Human Development and Family Science, Purdue University, West Lafayette, IN, USA

Abstract

Most existing DNA methylation (DNAm) studies have used peripheral surrogate tissues to research molecular mechanisms underlying brain disorders and diseases. Initial studies comparing brain to blood primarily at the individual CpG level analysis have generally pointed to a limited overlap of epigenetic patterns, consistent with DNAm being largely tissue- and even cell type-specific. Expanding on these studies, we employed a more complex analysis strategy aimed to 1) identify single DNAm sites associated with deconvolution-estimated brain cell type proportions, the principal measure in this study, in both the frontal brain and peripheral blood, 2) combine blood DNAm sites to predict brain cell type proportions through multivariate models, and 3) examine the association of blood DNAm, age, and epigenetic age acceleration (EAA) on brain cell type proportions. Epigenome-wide association studies for seven brain cell type proportions in matched frontal brain and peripheral blood samples (n = 104) revealed that ∼10% of brain cell type-associated DNAm sites had correlating DNAm levels in peripheral blood (p < 0.05). However, only three peripheral blood DNAm sites were significantly associated with endothelial and stromal brain cell type proportions (adjusted p < 0.05). Brain cell type proportion predictions trained with machine learning approaches using peripheral blood DNAm showed the strongest, although still modest correlations with microglia proportions estimated through cell deconvolution using brain DNAm. Further, deconvolution-estimated blood immune cell type proportions showed a nominally significant association with estimated brain stromal cell proportions, driven primarily by NK cells; however, this association was dependent on chronological age and did not survive age-residualization. Lastly, brain EAA was not associated with brain and blood cell type proportions (adjusted p < 0.05). Collectively, these results suggested that in the context of broad tissue-specificity of DNAm patterns, DNAm levels in peripheral blood might actually inform on some immune brain cell type proportions. The correlations between DNAm profiles specific to immune cell types in blood and brain were consistent with a potential link between peripheral immune and central nervous system immune functions.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

The paper's code and data availability statement is in the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Data links

• ncbi.nlm.nih.gov/geo, NCBI; found in “Availability of data and materials”

Data availability

All data used in this manuscript is publicly available.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Availability of data and materials

The datasets analyzed during the current study are available in the Gene Expression Omnibus repository, https://www.ncbi.nlm.nih.gov/geo/. We used the datasets with the following GEO Accession codes: GSE214901; GSE95049; GSE111165; GSE59685.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

• Authors: added Hannah-Ruth Engelbrecht (0000-0002-6627-4114); Meingold Hiu-ming Chan (0000-0001-9108-2504); removed Hannah-Ruth Engelbrecht; Meingold Hiu-ming Chan

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 7 authors, 9 keywords, 2 funders, 104 references.

Cite

This paper

Meijer, M., Fu, M. P. Y., Navarro-Delgado, E. I., Engelbrecht, H.-R., Turecki, G., Chan, M. H.-m., & Kobor, M. S. (2026). Peripheral blood DNA methylation partially reports on immune cell type composition in the frontal brain. Brain, behavior, & immunity - health, 56, 101316. https://doi.org/10.1016/j.bbih.2026.101316

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1186/s13073-026-01698-8 [code]

From aging to Alzheimer's disease: concordant brain DNA methylation changes in late life.

Journal: Genome medicine

In common: genetics / omics, 5 references

[2] doi:10.3389/fneur.2026.1822479 [code]

Circulating neuron-derived cfDNA for blood-based detection of Alzheimer's and other neurodegenerative conditions.

Journal: Frontiers in neurology

In common: genetics / omics, 4 references

[3] doi:10.1038/s41467-026-71542-5 [code]

Astrocyte fatty acid metabolism as a driver of risk for major depressive disorder.

Journal: Nature communications

In common: genetics / omics, cellular / molecular, 1 reference, author Gustavo Turecki

[4] doi:10.1186/s13148-026-02124-x

Comparison of DNA methylation measured in saliva and peripheral blood as a marker of exposure and outcome: a scoping review.

Journal: Clinical epigenetics

In common: genetics / omics, 4 references

[5] doi:10.1016/j.xgen.2026.101278 [code]

Single-cell profiling of DNA methylation in autism spectrum disorder prefrontal cortex reveals distinct regulatory and aging signatures.

Journal: Cell genomics

In common: genetics / omics, 4 references

[6] doi:10.1038/s41514-026-00391-9 [code]

Region-specific transcriptional signatures of brain aging in the absence of neuropathology at the single-cell level.

Journal: npj aging

In common: genetics / omics, cellular / molecular, 4 references

[7] doi:10.18632/aging.206369 [code]

Association of epigenetic age acceleration with MRI biomarkers of aging and Alzheimer's disease neurodegeneration.

Journal: Aging

In common: 4 references

[8] doi:10.1038/s41586-026-10509-4

Dopamine drives persistent remodelling of the maternal brain.

Journal: Nature

In common: genetics / omics, cellular / molecular, author Gustavo Turecki

[9] doi:10.1038/s41593-026-02247-7 [code]

Transcriptomic and phenotypic convergence of neurodevelopmental disorder risk genes in vitro and in vivo.

Journal: Nature neuroscience

In common: genetics / omics, cellular / molecular, 3 references

[10] doi:10.1002/advs.77524 [code]

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi-Scale Information and Metric Learning Framework for scDNAm Data.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)

In common: genetics / omics, 3 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.