Evidence map›Paper›PMID 42304519›Full record

ArticleGenome medicine2026

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

David Lukacsovich, Juan I Young, Lissette Gomez, Michael A Schmidt, Wei Zhang, Brian W Kunkle, Xi Steven Chen, Eden R Martin, Lily Wang, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Genome medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

David LukacsovichDivision of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Juan I YoungDr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Lissette GomezJohn P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
Michael A SchmidtDr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Wei ZhangDivision of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Brian W KunkleDr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Xi Steven ChenDivision of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Eden R MartinDr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA.
Lily WangDivision of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, 33136, USA. lily.wangg@gmail.com.ORCID http://orcid.org/0000-0002-8311-4251
Alzheimer’s Disease Neuroimaging Initiative

Funding

Integrative Genomic Approaches for Understanding Sex Differences in Alzheimer's DiseaseR01AG062634 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI KUNKLE, BRIAN WILLIAM, MARTIN, EDEN R. · 2019 to 2023
$3.8M
New computational tools for understanding and predicting AD via age-associated DNA methylation changesRF1NS128145 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI WANG, LILY · 2022 to 2022
$2.0M
New DNA methylation biomarkers for predicting AD and cognitive declineR61NS135587 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI WANG, LILY · 2024 to 2025
$1.5M
New computational tools for understanding and predicting AD via age-associated DNA methylation changesR01NS128145 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Lily Wang · 2025 to 2026
$1.1M
NIA NIH HHS R01 AG062634NIA NIH HHS R01AG062634NINDS NIH HHS R01 NS128145NINDS NIH HHS R61 NS135587NINDS NIH HHS R61NS135587NINDS NIH HHS RF1 NS128145
6 · The paper itself

Abstract

backgroundAging is the strongest risk factor for Alzheimer's disease (AD), but the molecular connections between aging and AD remain unclear. DNA methylation (DNAm) is implicated in both processes.

methodsWe conducted a meta-analysis of DNAm in prefrontal cortex from two independent postmortem cohorts: the Religious Orders Study and Memory and Aging Project (ROSMAP) and Brains for Dementia Research (BDR). Age-associated CpG sites were identified using cohort-specific linear models adjusted for neuronal proportion, sex, and batch, followed by meta-analysis. We computed epigenetic age acceleration in brain samples as delta-age (DNAmAge - chronological age), and compared clinically diagnosed AD with cognitively unimpaired participants. Functional analyses included genomic feature enrichment, pathway analysis, brain-blood DNAm correlation, and colocalization with genome-wide association study (GWAS) loci. Prognostic relevance of age-associated CpGs was tested in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset using Cox proportional hazards models for disease progression.

resultsWe identified 3264 CpG sites associated with aging; most were hypermethylated and enriched in promoters and CpG islands, and involved genes related to immune regulation and metabolism. Comparison with AD neuropathology-associated methylation showed substantial overlap, with nearly all shared CpGs and regions showing concordant directional changes. Cortical epigenetic age acceleration was higher in ROSMAP participants with clinical AD than in cognitively unimpaired individuals after covariates adjustment, and this association persisted when the cortical clock was restricted to the aging-associated CpGs identified here, suggesting that acceleration in AD is attributable to age-related CpGs. Several CpGs showed significant brain-blood methylation correlations or were linked to AD GWAS risk loci through colocalization analyses. In ADNI, among 33 candidate CpGs selected for concordant aging- and AD-associated changes in cortex and significant brain-blood methylation correlations, baseline methylation at one CpG (cg10752406 in AZU1 promoter) was associated with progression at a 5% false discovery rate after covariate adjustment.

conclusionsAging-associated DNAm changes in prefrontal cortex overlap with AD neuropathology-related changes and are involved in accelerated epigenetic aging in clinical AD. Our study provides valuable insights into the epigenetic landscape of aging and its implications for AD.

Indexed as

AgingAlzheimer DiseaseBrainDNA MethylationAgedAged, 80 and overCpG IslandsEpigenesis, GeneticFemaleGenome-Wide Association StudyHumansMaleAgingAlzheimer’s diseaseBiomarkersDNA methylationEpigenetics

Identifiers

PMID42304519
PMCPMC13505181

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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.