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Record W4410785517 · doi:10.1038/s44400-025-00007-1

DNA methylation age from peripheral blood predicts progression to Alzheimer’s disease, white matter disease burden, and cortical atrophy

2025· article· en· W4410785517 on OpenAlexfundno aff
Luke W. Bonham, Daniel W. Sirkis, Alina P.S. Pang, Leo P. Sugrue, Hernando Santamaría‐García, Agustín Ibáñez, Bruce L. Miller, Jennifer S. Yokoyama, Michael J. Corley

Bibliographic record

Venuenpj Dementia · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasNational Institute on Drug AbuseNational Institute on AgingNational Institutes of HealthAgencia Nacional de Investigación y DesarrolloGenentechNational Institute of Neurological Disorders and StrokeIXICOH. Lundbeck A/SServierEisaiRainwater Charitable FoundationGlobal Brain Health InstituteNorthern California Institute for Research and EducationUniversity of Southern CaliforniaPfizerBioClinicaBiogenRadiological Society of North AmericaNational Institute of Biomedical Imaging and BioengineeringFogarty International CenterCanadian Institutes of Health ResearchRSNA Research and Education FoundationBristol-Myers SquibbEli Lilly and CompanyMeso Scale DiagnosticsAlzheimer's Disease Neuroimaging InitiativeNovartis Pharmaceuticals CorporationAlzheimer's Association
KeywordsEpigeneticsNeuroimagingAlzheimer's Disease Neuroimaging InitiativeDNA methylationNeuroscienceWhite matterDiseaseAlzheimer's diseaseBiologyPsychologyMedicinePathologyGeneticsMagnetic resonance imagingGene expressionGene

Abstract

fetched live from OpenAlex

Cross-sectional studies suggest a limited relationship between accelerated epigenetic aging derived from epigenetic clocks, and Alzheimer's disease (AD) pathophysiology or risk. However, most prior analyses have not utilized longitudinal analyses or whole-brain neuroimaging biomarkers of AD. Herein, we employed longitudinal modeling and structural neuroimaging analyses to test the hypothesis that accelerated epigenetic aging would predict AD progression. Using survival analyses, we found that two second-generation epigenetic clocks, DNAmPhenoAge and DNAmGrimAge, predicted progression from cognitively normal aging to mild cognitive impairment or AD and worse longitudinal cognitive outcomes. Epigenetic age was also strongly associated with cortical thinning in AD-relevant regions and white matter disease burden. Thus, in contrast to earlier work suggesting limited applicability of blood-based epigenetic clocks in AD, our novel analytic framework suggests that second-generation epigenetic clocks have broad utility and may represent promising predictors of AD risk and pathophysiology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.272
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2025
Admission routes1
Has abstractyes

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