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A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer's disease

Venkatraghavan, V; Archetti, D; Bourgeat, P; Jiang, C; ten Kate, M; van Loenhoud, AC; Ossenkoppele, R; ... Tijms, BM; + view all (2025) A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer's disease. Neuroimage , 318 , Article 121381. 10.1016/j.neuroimage.2025.121381. Green open access

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Abstract

Previous studies identified atrophy-based Alzheimer's disease(AD) subtypes linked to distinct clinical symptoms, but their consistency across subtyping approaches remains unclear. This large-scale study evaluates subtype concordance using two data-driven approaches. In this work, we analyzed data from n=10,011 patients across 10 AD cohorts spanning Europe, the US, and Australia, extracting regional volumes using Freesurfer. To characterize atrophy heterogeneity in the AD continuum, we developed a two-step approach, Snowphlake (Staging NeurOdegeneration With PHenotype informed progression timeLine of biomarKErs), to identify subtypes and atrophy-event sequences within each subtype. Results were compared with SuStaIn (Subtype and Stage Inference), which jointly estimates subtypes and staging, using similar training and validation. Training included Aβ+ participants (n=1,195) and Aβ− cognitively unimpaired controls (n=1,692). We validated model-staging in a held-out clinical dataset (n=6,362) and an independent dataset (n=762), and assessed clinical significance in Aβ+ subsets(n=1,796 held-out; n=159 external). Concordance analysis evaluated consistency between methods. In the AD dementia(AD-D) training data, both Snowphlake and SuStaIn identified four subtypes. In the validation datasets, staging with both methods correlated with Mini-Mental State Examination(MMSE) scores. The Snowphlake subtypes assigned in Aβ+ validation datasets were associated with alterations in specific cognitive domains(Cohen's f: [0.15−0.33]). Similarly, the SuStaIn subtypes were also associated specific cognitive domains(Cohen's f:[0.17−0.34]). However, we observed low concordance between Snowphlake and SuStaIn, with 39.7% of AD-D patients grouped in concordant subtypes by both methods. In conclusion, Snowphlake and SuStaIn identified four atrophy-based subtypes that linked to distinct symptom profiles. While this highlights that the neuro-anatomically defined subtypes also meaningfully associate with different cognitive impairments at a group level, the low concordance between methods suggests that future research is needed to better understand the biological and methodological factors contributing to the observed variability.

Type: Article
Title: A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer's disease
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2025.121381
Publisher version: https://doi.org/10.1016/j.neuroimage.2025.121381
Language: English
Additional information: © 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Alzheimer’s disease, Data-driven, Heterogeneity, MRI, Subtypes
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10212875
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