Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Aug;30(8):3718-3728.
doi: 10.1038/s41380-025-02961-x. Epub 2025 Apr 12.

Neuroimaging-derived biological brain age and its associations with glial reactivity and synaptic dysfunction cerebrospinal fluid biomarkers

Irene Cumplido-Mayoral  1   2   3 , Gonzalo Sánchez-Benavides  1   3   4 , Natalia Vilor-Tejedor  1   5   6 , David López-Martos  1   3 , Anna Brugulat-Serrat  1   3   4   7 , Marta Milà-Alomà  1   3   8   9 , Carles Falcon  1   3 , Raffaele Cacciaglia  1   3   4 , Carolina Minguillón  1   3   4 , Karine Fauria  1   4 , Gwendlyn Kollmorgen  10 , Clara Quijano-Rubio  11 , José Luis Molinuevo  1 , Oriol Grau-Rivera  1   3   4   12 , Marc Suárez-Calvet  13   14   15   16 , Verónica Vilaplana  17 , Juan Domingo Gispert  18   19   20   21   22 ; ALFA; ADNI study
Affiliations

Neuroimaging-derived biological brain age and its associations with glial reactivity and synaptic dysfunction cerebrospinal fluid biomarkers

Irene Cumplido-Mayoral et al. Mol Psychiatry. 2025 Aug.

Abstract

Magnetic resonance Imaging (MRI)-derived brain-age prediction is a promising biomarker of biological brain aging. Accelerated brain aging has been found in Alzheimer's disease (AD) and other neurodegenerative diseases. However, no previous studies have investigated the relationship between specific pathophysiological pathways in AD and biological brain aging. Here, we studied whether glial reactivity and synaptic dysfunction are associated with biological brain aging in the earliest stages of the Alzheimer's continuum, and if these mechanisms are differently associated with AD-related cortical atrophy. We further evaluated their effects on cognitive decline. We included 380 cognitively unimpaired individuals from the ALFA+ study, for which we computed their brain-age deltas by subtracting chronological age from their brain age predicted by machine learning algorithms. We studied the cross-sectional linear associations between brain-age delta and cerebrospinal fluid (CSF) biomarkers of synaptic dysfunction (neurogranin, GAP43, synaptotagmin-1, SNAP25, and α-synuclein), glial reactivity (sTREM2, YKL-40, GFAP, and S100b) and inflammation (interleukin-6). We also studied the cross-sectional linear associations between AD signature and these CSF biomarkers, We further evaluated the mechanisms linking baseline brain-age delta and longitudinal cognitive decline by performing mediation analyses. To reproduce our findings on an independent cohort, we included 152 cognitively unimpaired and 310 mild cognitive impaired (MCI) individuals from the ADNI study. We found that higher CSF sTREM2 was associated with a younger brain-age after adjusting for AD pathology, both in ALFA+ cognitively unimpaired and in ADNI MCI individuals. Furthermore, we found that CSF sTREM2 fully mediated the link between older brain-age and cognitive decline in ALFA+. In summary, we showed that the protective microglial state reflected by higher CSF sTREM2 has a beneficial impact on biological brain aging that may partly explains the variability in cognitive decline in early AD stages, independently of AD pathology.

PubMed Disclaimer

Conflict of interest statement

Competing interests: MS-C has given lectures in symposia sponsored by Almirall, Eli Lilly, Novo Nordisk, Roche Diagnostics, and Roche Farma; received consultancy fees (paid to the institution) from Roche Diagnostics; and served on advisory boards of Roche Diagnostics and Grifols. He was granted a project and is a site investigator of a clinical trial (funded to the institution) by Roche Diagnostics. In-kind support for research (to the institution) was received from ADx Neurosciences, Alamar Biosciences, Avid Radiopharmaceuticals, Eli Lilly, Fujirebio, Janssen Research & Development, and Roche Diagnostics. JLM is currently a full‑time employee of H. Lundbeck A/S and previously has served as a consultant or on advisory boards for the following for‑profit companies or has given lectures in symposia sponsored by the following for‑profit companies: Roche Diagnostics, Genentech, Novartis, Lundbeck, Oryzon, Biogen, Lilly, Janssen, Green Valley, MSD, Eisai, Alector, BioCross, GE Healthcare, and ProMIS Neurosciences. MSC has served as a consultant and at advisory boards for Roche Diagnostics International Ltd. and has given lectures in symposia sponsored by Roche Diagnostics, S.L.U and Roche Farma, S.A. JDG receives research funding from Roche Diagnostics, F. Hoffmann-La Roche and GE Healthcare, has given lectures in symposia sponsored by Biogen, Esteve, Life Molecular Imaging and Philips and served in the Molecular Neuroimaging Scientific Board of Prothena Biosciences. GS-B has served as a consultant for Roche Farma, S.A. OGR receives research funding from F. Hoffmann-La Roche Ltd and has given lectures in symposia sponsored by Roche Diagnostics, S.L.U. GK is a full‑time employee of Roche Diagnostics GmbH, Penzberg, Germany. CQ-R is a full‑time employee of Roche Diagnostics International Ltd, Rotkreuz, Switzerland. Ethics declarations: All participants were enrolled in the ALFA (ALzheimer and FAmilies) study (Clinicaltrials.gov Identifier: NCT01835717). The study was approved by the Independent Ethics Committee “Parc de Salut Mar,” Barcelona, and all participants gave written informed consent. All methods were performed in accordance with the relevant guidelines and regulations.

Figures

Fig. 1
Fig. 1. Associations between CSF sTREM2 and brain-age delta in ALFA+ and ADNI participants.
Linear regression results for Model 1 (brain-age delta ~ CSF biomarker + age + sex + APOE-ε4 status), in blue (A, B), and for Model 2 (brain-age delta ~ CSF biomarker + age + sex + APOE status + Aβ + p-tau), in purple (C, D). In A and C, scatter plots representing the associations of sTREM2 and brain-age delta in ALFA+ cognitively unimpaired (CU), ADNI CU and ADNI MCI. In B and D, standardized estimates of the regression.
Fig. 2
Fig. 2. sTREM2 fully mediates the association between biological brain age and cognitive changes in cognitively unimpaired individuals in ALFA+.
Mediation by CSF sTREM2 of the association between brain-age delta and cognitive changes in (A) ALFA+ and (B) ADNI. Results for Model 1 (in blue) and Model 2 (in purple). Blue lines represent significant negative associations. Red lines represent significant positive associations. Significance given by P < 0.05.
See this image and copyright information in PMC

References

    1. Franke K, Gaser C. Ten years of brainage as a neuroimaging biomarker of brain aging: What insights have we gained? Front Neurol. 2019;10:789. - PMC - PubMed
    1. Beheshti I, Maikusa N, Matsuda H. The association between “Brain-Age Score” (BAS) and traditional neuropsychological screening tools in Alzheimer’s disease. Brain Behav. 2018;8:e01020. - PMC - PubMed
    1. Kaufmann T, van der Meer D, Doan NT, Schwarz E, Lund MJ, Agartz I, et al. Common brain disorders are associated with heritable patterns of apparent aging of the brain. Nat Neurosci. 2019;22:1617–23. - PMC - PubMed
    1. Cole JH. Multimodality neuroimaging brain-age in UK biobank: relationship to biomedical, lifestyle, and cognitive factors. Neurobiol Aging. 2020;92:34–42. - PMC - PubMed
    1. de Lange AMG, Anatürk M, Suri S, Kaufmann T, Cole JH, Griffanti L, et al. Multimodal brain-age prediction and cardiovascular risk: the Whitehall II MRI sub-study. Neuroimage. 2020;222:117292. - PMC - PubMed

MeSH terms