DunedinPACNI estimates the longitudinal pace of aging from a single brain image to track health and disease
Open accessAbstract
To understand how aging affects functional decline and increases disease risk, it is necessary to develop measures of how fast a person is aging. Using data from the Dunedin Study, we introduce an accurate and reliable measure for the rate of longitudinal aging derived from cross-sectional brain magnetic resonance imaging, that is, the Dunedin Pace of Aging Calculated from NeuroImaging (DunedinPACNI). Exporting this measure to the Alzheimer’s Disease Neuroimaging Initiative, UK Biobank and BrainLat datasets revealed that faster DunedinPACNI predicted cognitive impairment, accelerated brain atrophy and conversion to diagnosed dementia. Faster DunedinPACNI also predicted physical frailty, poor health, future chronic diseases and mortality in older adults. When compared to brain age gap, DunedinPACNI was similarly or more strongly related to clinical outcomes. DunedinPACNI is a next-generation brain magnetic resonance imaging biomarker that can help researchers explore aging effects on health outcomes and evaluate the effectiveness of antiaging strategies.
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Single-timepoint MRI predicts decade-long cognitive decline and mortality, validated across multiethnic cohorts including Latino populations.
“single-timepoint MRI predicts decade-long cognitive decline and mortality, which has been validated across multiethnic cohorts, including Latino populations”
From Multimodal neuroimaging and AI integration in cognitive disorders: advances, challenges, and future directions for precision medicine (2026) · cites this paper as Whitman et al., 2025
The Results sections on future cognitive decline and on mortality report that a baseline MRI-derived DunedinPACNI score predicted later cognitive impairment in ADNI and death in UK Biobank. ADNI follow-up extended to 16 years, but averaged about five years; the paper does not establish a decade-long prediction for every participant. The Latin American results show associations with existing diagnoses and cognitive scores, not validation of future decline or mortality prediction in that population (page numbers unavailable in our copy). (LLM, conf=0.90)
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- [34]Sluiskes MH Clarifying the biological and statistical assumptions of cross-sectional biological age predictors. bioRxiv (2023) doi: 10.1101/2023.01.01.522413. PMC10921716 38459475 · DOI
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- Authors
- Whitman, E. T., Elliott, M. L., Knodt, A. R., Abraham, W. C., Anderson, T. J., Cutfield, N. J., Hogan, S., Ireland, D., Melzer, T. R., Ramrakha, S., Sugden, K., Theodore, R., Williams, B. S., Caspi, A., Moffitt, T. E., & Hariri, A. R.
- Affiliations
- Duke University (US)
- Harvard University (US)
- University of Otago (NZ)
- Christchurch Hospital (NZ)
- University of Canterbury (NZ)
- Corresponding author
- Whitman, Ethan T.
- Moffitt, Terrie E.
- ORCID
- Venue
- Nature Aging
- Published
- 2025-07-01
- Volume
- 5
- Issue
- 8
- Pages
- 1619-1636
- ISSN
- 2662-8465 (ISSN-L)
- PMC
- PMC12350157
- OpenAlex
- W4411900345
- Cited by
- 37
- References
- 121
- Citations by year
- 2026: 31 · 2025: 6
- FWCI
- 24.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Aging (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (R01AG032282, R01AG073207, R01AG049789)
- RCUK | Medical Research Council (MR/X021149/1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
- Keywords
- pace of aging, brain age gap, brain atrophy, cognitive impairment, conversion to dementia, physical frailty, mortality, chronic disease, aging, Dunedin Study, Alzheimer's Disease Neuroimaging Initiative, UK Biobank
- MeSH terms
- Aged, Aged, 80 and over, Aging, Alzheimer Disease, Atrophy, Brain, Cross-Sectional Studies, Dementia, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Cognitive Dysfunction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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