Onderzoekers van de Duke Universiteit, Harvard Universiteit en de Universiteit van Otago in Nieuw-Zeeland hebben de DunedinPACNI een software tool, een hulpmiddel, ontwikkeld waarmee op basis van één hersenscan - MRI tientallen jaren vantevoren kan voorspellen wie snel zal verouderen en wie langzaam zal verouderen. De DunedinPACNI voorspelt met name wie en ongeveer op welke leeftijd iemand de ziekte van Alzheimer - Dementie zal krijgen en daaraan zal overlijden.
De DunedinPACNI is ontwikkeld op basis van één hersenscan - MRI die bij 850 deelnemers aan de Dunedin studie op 45-jarige leeftijd werd genomen. De DunedinPACNI kan tekenen van toekomstige ziekten zoals de ziekte van Alzheimer - dementie opsporen tientallen jaren voordat de symptomen zich openbaren. Mensen die sneller verouderen, hadden een zwakker geheugen, meer gezondheidsproblemen en zelfs een hoger risico op vroegtijdig overlijden.
De onderzoekers ontdekten ook dat mensen met een DunedinPACNI-score die aangaf dat ze sneller verouderen, vaker te maken hadden met een afnemende algehele gezondheid, niet alleen wat betreft hun hersenfunctie. Uit datasets bleek dat mensen die volgens deze maatstaf sneller verouderden, slechter presteerden op cognitieve tests en een snellere krimp vertoonden in de hippocampus, een hersengebied dat cruciaal is voor het geheugen.
Mensen met een snellere verouderingsscore waren kwetsbaarder en hadden meer kans op leeftijdsgerelateerde gezondheidsproblemen zoals hartaanvallen, longziekten of beroertes.
De snelst verouderende mensen hadden 18% meer kans om binnen enkele jaren de diagnose van een chronische ziekte te krijgen, vergeleken met mensen met een gemiddelde verouderingssnelheid.
Nog alarmerender was dat ze binnen die tijdspanne ook 40% meer kans hadden om te overlijden dan degenen die langzamer verouderden, ontdekten de onderzoekers.
"Het verband tussen de veroudering van de hersenen en het lichaam is behoorlijk overtuigend", aldus een van de onderzoeksleiders prof. MD Ahmed Hariri. "De correlaties tussen verouderingssnelheid en dementie waren net zo sterk in andere demografische en sociaaleconomische groepen dan die waarop het model was getraind, waaronder een steekproef van mensen uit Latijns-Amerika, evenals deelnemers uit het Verenigd Koninkrijk met een laag inkomen of een niet-blanke huidskleur."
Het mooie is wel dat wanneer de DunedinPACNI-score eern slechte prognose geeft direct zou kunnen worden gestart met manieren om de aankomende de ziekte van Alzheimer - dementie te remmen, waarbij vooral ook een gezonde leefstijl en gezond voedingspatroon een grote rol zouden kunnen spelen. Zegt ook prof. MD Ahmed Hariri.
Onderstaande grafiek is gekopieerd uit het studieverslag:
a, Plot of mean scores for all 19 biomarkers comprising the Pace of Aging across four waves of observation at ages 26, 32, 38 and 45 years in the Dunedin Study. Hypothetical individual trajectories are shown for people with relatively slow, average and fast Pace of Aging from ages 26 to 45 years. b, Distribution of Pace of Aging scores in Dunedin Study members at age 45. Warmer colors represent a faster Pace of Aging; cooler colors represent a slower Pace of Aging. c, A single T1-weighted MRI scan collected from 860 Dunedin Study members at age 45 years was used to train an elastic net regression model to predict the Pace of Aging. We call the resulting measure DunedinPACNI. d, Regression weights from the DunedinPACNI model developed in the Dunedin Study were applied to T1-weighted MRI scans collected in the ADNI and UKB datasets to derive DunedinPACNI scores. Those scores were then related to aging-related phenotypes. AL, attachment loss; Apo, apolipoprotein; BMI, body mass index; FEV1, forced expiratory volume in 1 s; eGFR, estimated glomerular filtration rate; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; hsCRP, high sensitivity C-reactive protein; VO2max, maximal oxygen uptake.
Het volledige studierapport is gratis in te zien of te downloaden. Klik daarvoor op de titel van het studieverslag:
- Technical Report
- Open access
- Published:
DunedinPACNI estimates the longitudinal Pace of Aging from a single brain image to track health and disease
Nature Aging (2025)
Abstract
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.
Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Data availability
The Dunedin Study data are available via managed access. Researchers who wish to use the Dunedin Study data are invited to submit a concept paper proposing the data analysis project they wish to carry out, subject to the approval of the Dunedin Study investigators. Complete instructions on accessing the Dunedin Study data can be found at https://sites.duke.edu/moffittcaspiprojects/data-use-guidelines/. The HCP data are publicly available at www.humanconnectomeproject.org/data/. The ADNI data are publicly available at https://adni.loni.usc.edu/. Researchers can apply to access all UKB data at https://ams.ukbiobank.ac.uk/ams/. The BrainLat data are publicly available at www.synapse.org/Synapse:syn51549340/wiki/624187. Source data for Fig. 1b, Fig. 2a,b, Fig. 3a,b, Fig. 4b, Fig. 5a, Fig. 6 and Fig. 7, and Extended Data Figs. 1–3 and 5–9) are published with this article.
Code availability
The DunedinPACNI algorithm is publicly available at GitHub (https://github.com/etw11/DunedinPACNI). All scripts used in the analyses presented in this article are publicly available at GitHub (https://github.com/etw11/WhitmanElliott_2024).
Acknowledgements
This research received support from the National Institute on Aging (grant no. R01AG049789 to A.R.H. and T.E.M.; grant no. R01AG032282 to A.C. and T.E.M.; grant no. R01AG073207 to A.C. and T.E.M.) and the UK Medical Research Council (grant no. MR/X021149/1 to A.C. and T.E.M.). The Dunedin Multidisciplinary Health and Development Research Unit is supported by the New Zealand Health Research Council (program grant no. 16-604). We thank the Dunedin Study members, Unit research staff, the previous Study Director, Emeritus Distinguished Professor, the late R. Poulton, for his leadership during the study’s research transition from young adulthood to aging (2000–2023), and Study founder P. A. Silva. The Dunedin Unit is located within the Ngāi Tahu tribal area who we acknowledge as first peoples, tangata whenua (people of this land). This research has been conducted using the UKB Resource under application no. 67237. Data collection and sharing for ADNI is funded by the National Institute on Aging (National Institutes of Health grant no. U19 AG024904). The grantee organization is the Northern California Institute for Research and Education. In the past, ADNI has also received funding from the National Institute of Biomedical Imaging and Bioengineering, the Canadian Institutes of Health Research and private sector contributions through the Foundation for the NIH, including generous contributions from the following: AbbVie, Alzheimer’s Association, Alzheimer’s Drug Discovery Foundation, Araclon Biotech, BioClinica, Biogen, Bristol Myers Squibb, CereSpir, Cogstate, Eisai, Elan Pharmaceuticals, Eli Lilly and Company, EuroImmun, F. Hoffmann-La Roche and its affiliated company Genentech, Fujirebio, GE Healthcare, IXICO, Janssen Alzheimer Immunotherapy Research & Development, Johnson & Johnson Pharmaceutical Research & Development, Lumosity, Lundbeck, Merck & Co., Meso Scale Diagnostics, NeuroRx Research, Neurotrack Technologies, Novartis Pharmaceuticals Corporation, Pfizer, Piramal Imaging, Servier, Takeda Pharmaceutical Company and Transition Therapeutics. We thank BrainLat and associated investigators for sharing the BrainLat dataset.
Author information
Authors and Affiliations
Contributions
E.T.W., M.L.E., A.R.K., A.C., T.E.M. and A.R.H. designed the research. E.T.W., M.L.E., A.R.K., W.C.A., T.J.A., N.J.C., S.H., D.I., T.R.M., S.R., K.S., R.T., B.S.W., A.C., T.E.M. and A.R.H. performed the research. E.T.W., M.L.E. and A.R.K. analyzed the data. E.T.W., M.L.E., A.R.K., A.C., T.E.M. and A.R.H. wrote the paper.
Corresponding authors
Ethics declarations
Competing interests
K.S., A.C. and T.E.M. are listed as inventors of DunedinPACE, a Duke University and University of Otago invention licensed to TruDiagnostic for commercial uses; however, the DunedinPACE algorithm is open access for research purposes. The other authors declare no competing interests.
Peer review
Peer review information
Nature Aging thanks Denise C. Park and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Change history
-
03 July 2025
In the version of the article initially published, Terrie Moffitt was incorrectly listed as an equally contributing author. This has now been corrected so that Ethan Whitman and Maxwell Elliott are listed as the two equally contributing authors in the HTML and PDF versions of the article.
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