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 Jul;21(7):e70482.
doi: 10.1002/alz.70482.

Disease stage-specific atrophy markers in Alzheimer's disease

Hannah Baumeister  1 , Helena M Gellersen  1   2   3 , Sarah E Polk  1 , René Lattmann  1   4 , Anika Wuestefeld  5 , Laura E M Wisse  6 , Trevor Glenn  7 , Renat Yakupov  1   4 , Melina Stark  8   9 , Luca Kleineidam  8   9 , Sandra Roeske  8 , Barbara Marcos Morgado  10 , Hermann Esselmann  10 , Frederic Brosseron  8 , Alfredo Ramirez  8   9   11   12   13 , Falk Lüsebrink  1 , Matthis Synofzik  14   15   16 , Björn H Schott  10   17   18 , Matthias C Schmid  8   19 , Stefan Hetzer  20 , Peter Dechent  21 , Klaus Scheffler  22 , Michael Ewers  23   24 , Julian Hellmann-Regen  25   26   27 , Ersin Ersözlü  25   26   27 , Eike Spruth  25   28 , Maria Gemenetzi  25   28 , Klaus Fliessbach  8   9 , Claudia Bartels  10 , Ayda Rostamzadeh  29 , Wenzel Glanz  1 , Enise I Incesoy  1   4   30 , Daniel Janowitz  24 , Boris-Stephan Rauchmann  31   32   33 , Ingo Kilimann  34   35 , Sebastian Sodenkamp  14   36 , Marie Coenjaerts  8 , Annika Spottke  8   37 , Oliver Peters  25   28 , Josef Priller  25   28   38   39   40 , Anja Schneider  8   9 , Jens Wiltfang  10   17   41 , Katharina Buerger  23   24 , Robert Perneczky  23   31   42   43 , Stefan Teipel  34   35 , Christoph Laske  14   36   44 , Michael Wagner  8   9 , Gabriel Ziegler  1   4 , Frank Jessen  8   11   29 , Emrah Düzel  1   4 , David Berron  1   5   45 ; DELCODE study group
Affiliations

Disease stage-specific atrophy markers in Alzheimer's disease

Hannah Baumeister et al. Alzheimers Dement. 2025 Jul.

Abstract

Introduction: Structural magnetic resonance imaging (MRI) often lacks diagnostic, prognostic, and monitoring value in Alzheimer's disease (AD), particularly in early disease stages. To improve its utility, we aimed to identify optimal atrophy markers for different intended uses.

Methods: We included 363 older adults; cognitively unimpaired individuals who were negative or positive for amyloid beta (Aβ) and Aβ-positive patients with subjective cognitive decline, mild cognitive impairment, or dementia of the Alzheimer type. MRI and neuropsychological assessments were administered annually for up to 3 years.

Results: Accelerated atrophy of medial temporal lobe subregions was evident already during preclinical AD. Symptomatic disease stages most notably differed in their hippocampal and parietal atrophy signatures. Atrophy-cognition relationships varied by intended use and disease stage.

Discussion: With the appropriate marker, MRI can detect abnormal atrophy already during preclinical AD. To optimize performance, atrophy markers should be tailored to the targeted disease stage and intended use.

Highlights: Subregional atrophy markers detect ongoing atrophy in preclinical Alzheimer's disease (AD). Subjective cognitive decline in preclinical AD links to manifest atrophy. Optimal atrophy markers differ by the disease stage and intended use.

Keywords: imaging biomarker; longitudinal atrophy; magnetic resonance imaging; medial temporal lobe; parietal lobe.

PubMed Disclaimer

Conflict of interest statement

J.W. has been an honorary speaker for Beeijing Yibai Science and Technology Ltd, Eisai, Gloryren, Janssen, Pfizer, Med Update GmbH, Roche, Lilly, Roche Pharma; has been a member of the advisory boards of Abbott, Biogen, Boehringer Ingelheim, Lilly, Immungenetics, MSD Sharp‐Dohme, Noselab, Roboscreen, and Roche Pharma; and receives fees as a consultant for Immungenetics, Noselab, and Roboscreen. J.W. holds the following patents: PCT/EP 2011 001724 and PCT/EP 2015 052945. All other authors report no conflicts of interest relevant to this work. Author disclosures are available in the supporting information.

Figures

FIGURE 1
FIGURE 1
Baseline and longitudinal MTL and parietal subregional atrophy markers across the clinical AD continuum. A, Boxplot diagrams of baseline gray matter volumes and average cortical thicknesses across ROIs and clinical disease stages, grouped by meta‐region. B, Annual change of of atrophy markers across ROIs and clinical disease stages, grouped by meta‐region. The shown slopes were estimated from linear mixed effects models. Error bars denote 95% confidence intervals. Asterisks highlight significant slopes, that is, significant change over time. C, Matrix displaying estimates from analysis of covariance post hoc group comparisons of baseline atrophy markers. The striped pattern indicates markers with non‐significant main effects of clinical disease stage (not passed to post hoc tests). D, Estimates from pairwise stage comparisons of longitudinal atrophy marker slopes. *P < 0.05. **P < 0.01. ***P < 0.001. Aβ, amyloid beta; BA, Brodmann area; CA, cornu ammonis; CA23DG, cornu ammonis 2, 3, and dentate gyrus; CU, cognitively unimpaired; DAT, dementia of the Alzheimer's disease type; FDR, false discovery rate; IPC, inferior parietal cortex; MCI, mild cognitive impairment; MRI, magnetic resonance imaging; MTL, medial temporal lobe; ROI, region of interest; SCD, subjective cognitive decline; SUB, subiculum.
FIGURE 2
FIGURE 2
Non‐linear changes in MTL and parietal subregional atrophy markers along continuous, data‐driven disease stages. A, Boxplot diagrams of baseline data‐driven disease stages by clinical disease stage, centered to the median of the CU Aβ+ group. B, Cubic B‐splines and their first derivatives were used to assess the development of atrophy markers across data‐driven disease stages. The estimated trajectories with bootstrapped confidence intervals are also shown in (C), where they are clustered by meta‐region. D, For each atrophy marker, the predicted curves are plotted along with the observed participant‐level trajectories. ***P < 0.001. Aβ, amyloid beta; AMY, amygdala; BA; Brodmann area; CA, cornu ammonis; CA23DG, cornu ammonis 2, 3, and dentate gyrus; CU, cognitively unimpaired; DAT, dementia of the Alzheimer's disease type; ERC, entorhinal cortex; HC, healthy control; IPC, inferior parietal cortex; MCI, mild cognitive impairment; MTL, medial temporal lobe; PCC, posterior cingulate cortex; PHC, parahippocampal cortex; PRE, precuneus; ROI, region of interest; RSC, retrosplenial cortex; SCD, subjective cognitive decline; SUB, subiculum; TAIL, hippocampal tail.
FIGURE 3
FIGURE 3
Estimates from bivariate LGCMs capturing the disease stage–specific cross‐sectional and longitudinal relationships of subregional atrophy markers and neuropsychological test scores. The covariance parameters of interest represented the (A) baseline–baseline, (B) baseline–slope, and (C) slope–slope pairwise associations of atrophy markers and neuropsychological test scores. Aβ, amyloid beta; ADAS‐Cog, Alzheimer's Disease Assessment Scale‐Cognitive subscale; AMY, amygdala; BA, Brodmann area; CA, cornu ammonis; CA23DG, cornu ammonis 2, 3, and dentate gyrus; CSD‐SB, Clinical Dementia Rating Sum of Boxes scale; ERC, entorhinal cortex; FAQ, Functional Activities Questionnaire; FCSRT, Free and Cued Selective Reminding Test; FDR, false discovery rate; IPC, inferior parietal cortex; LGCM, latent growth curve model; MMSE, Mini‐Mental State Examination; MTL, medial temporal lobe; PACC‐5, Preclinical Alzheimer Cognitive Composite; PHC, parahippocampal cortex; PRE, precuneus; RSC, retrosplenial cortex; SUB, subiculum; TAIL, hippocampal tail; WMS‐IV, Wechsler Memory Scale IV.
See this image and copyright information in PMC

Update of

  • Disease stage-specific atrophy markers in Alzheimer's disease.
    Baumeister H, Gellersen HM, Polk SE, Lattmann R, Wuestefeld A, Wisse LEM, Glenn T, Yakupov R, Stark M, Kleineidam L, Roeske S, Morgado BM, Esselmann H, Brosseron F, Ramirez A, Lüsebrink F, Synofzik M, Schott BH, Schmid MC, Hetzer S, Dechent P, Scheffler K, Ewers M, Hellmann-Regen J, Ersözlü E, Spruth E, Gemenetzi M, Fliessbach K, Bartels C, Rostamzadeh A, Glanz W, Incesoy EI, Janowitz D, Rauchmann BS, Kilimann I, Sodenkamp S, Coenjaerts M, Spottke A, Peters O, Priller J, Schneider A, Wiltfang J, Buerger K, Perneczky R, Teipel S, Laske C, Wagner M, Ziegler G, Jessen F, Düzel E, Berron D; DELCODE study group. Baumeister H, et al. medRxiv [Preprint]. 2025 Mar 14:2025.03.13.25323904. doi: 10.1101/2025.03.13.25323904. medRxiv. 2025. Update in: Alzheimers Dement. 2025 Jul;21(7):e70482. doi: 10.1002/alz.70482. PMID: 40162264 Free PMC article. Updated. Preprint.

References

    1. Jack CR Jr, Andrews JS, Beach TG, et al. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement. 2024;20(8):5143‐5169. doi: 10.1002/alz.13859 - DOI - PMC - PubMed
    1. Baumeister H, Vogel JW, Insel PS, et al. A generalizable data‐driven model of atrophy heterogeneity and progression in memory clinic settings. Brain. 2024;147(7):2400‐2413. doi: 10.1093/brain/awae118 - DOI - PMC - PubMed
    1. Bejanin A, Schonhaut DR, Joie RL, et al. Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer's disease. Brain. 2017;140(12):3286‐3300. doi: 10.1093/brain/awx243 - DOI - PMC - PubMed
    1. Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer's disease. Alzheimers Dement. 2021;17(12):1998‐2008. doi: 10.1002/alz.12356 - DOI - PubMed
    1. Ossenkoppele R, Smith R, Mattsson‐Carlgren N, et al. Accuracy of tau positron emission tomography as a prognostic marker in preclinical and prodromal Alzheimer disease: a head‐to‐head comparison against amyloid positron emission tomography and magnetic resonance imaging. JAMA Neurol. 2021;78(8):961‐971. doi: 10.1001/jamaneurol.2021.1858 - DOI - PMC - PubMed