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

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.

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Journal
NeuroImage
Published
2025-07-20
DOI
https://doi.org/10.1016/j.neuroimage.2025.121381
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
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article

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

Damiano Archetti, Rik Ossenkoppele, Betty Marije Tijms, Tibor Auer et al.
NeuroImage
Dementia and Cognitive Impairment Research
article

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

Damiano Archetti, Rik Ossenkoppele, Betty Marije Tijms, Tibor Auer, Wiesje M. van der Flier, Daniel C. Alexander, Chenyang Jiang, Pierrick Bourgeat, Elsmarieke van de Giessen, Béla Weiss, Anna C. van Loenhoud, Vikram Venkatraghavan, Frederik Barkhof, Paul T. Maruff, André Altmann, Alberto Redolfi, Neil P. Oxtoby, Charlotte Elisabeth Teunissen, Mara ten Kate, Stanley Durrleman, Simon Matthew Laws, Zoltán Vidnyánszky, Yolande A.L. Pijnenburg, Giovanni B. Frisoni
article en

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.

NeuroImageVol. 318
University of Geneva (CH), Edith Cowan University (AU), Centre National de la Recherche Scientifique (FR), Inserm (FR), University of Surrey (GB), Sorbonne Université (FR), Assistance Publique – Hôpitaux de Paris (FR), University Hospital of Geneva (CH), Amsterdam Neuroscience (NL), Centro San Giovanni di Dio Fatebenefratelli (IT), Australian e-Health Research Centre (AU), CSIRO Health and Biosecurity (AU), Amsterdam University Medical Centers (NL), Institut du Cerveau (FR), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University College London (GB), Geneva College (US), HUN-REN Research Centre for Natural Sciences (HU), Vrije Universiteit Amsterdam (NL)
U.S. Department of Defense, Alzheimer's Association, Alzheimer's Disease Neuroimaging Initiative, EU Joint Programme – Neurodegenerative Disease Research, Agence Nationale de la Recherche, ZonMw, Ministero della Salute, National Institutes of Health, Medical Research Council, National Research, Development and Innovation Office
Openalex Percentile: Top 79%
Dementia and Cognitive Impairment Research
DOIOpen Access PDFOpenAlex
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