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 da...

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Main Authors: Vikram Venkatraghavan, Damiano Archetti, Pierrick Bourgeat, Chenyang Jiang, Mara ten Kate, Anna C. van Loenhoud, Rik Ossenkoppele, Charlotte E. Teunissen, Elsmarieke van de Giessen, Yolande A.L. Pijnenburg, Giovanni B. Frisoni, Béla Weiss, Zoltán Vidnyánszky, Tibor Auer, Stanley Durrleman, Alberto Redolfi, Simon M. Laws, Paul Maruff, Neil P. Oxtoby, Andre Altmann, Daniel C. Alexander, Wiesje M. van der Flier, Frederik Barkhof, Betty M. Tijms
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Language:English
Published: Elsevier 2025-09-01
Series:NeuroImage
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Online Access:http://www.sciencedirect.com/science/article/pii/S1053811925003842
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author Vikram Venkatraghavan
Damiano Archetti
Pierrick Bourgeat
Chenyang Jiang
Mara ten Kate
Anna C. van Loenhoud
Rik Ossenkoppele
Charlotte E. Teunissen
Elsmarieke van de Giessen
Yolande A.L. Pijnenburg
Giovanni B. Frisoni
Béla Weiss
Zoltán Vidnyánszky
Tibor Auer
Stanley Durrleman
Alberto Redolfi
Simon M. Laws
Paul Maruff
Neil P. Oxtoby
Andre Altmann
Daniel C. Alexander
Wiesje M. van der Flier
Frederik Barkhof
Betty M. Tijms
author_facet Vikram Venkatraghavan
Damiano Archetti
Pierrick Bourgeat
Chenyang Jiang
Mara ten Kate
Anna C. van Loenhoud
Rik Ossenkoppele
Charlotte E. Teunissen
Elsmarieke van de Giessen
Yolande A.L. Pijnenburg
Giovanni B. Frisoni
Béla Weiss
Zoltán Vidnyánszky
Tibor Auer
Stanley Durrleman
Alberto Redolfi
Simon M. Laws
Paul Maruff
Neil P. Oxtoby
Andre Altmann
Daniel C. Alexander
Wiesje M. van der Flier
Frederik Barkhof
Betty M. Tijms
author_sort Vikram Venkatraghavan
collection DOAJ
description 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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spelling doaj-art-0d9f01fb54bd4cecaf1739de9f2d7b942025-08-20T03:56:41ZengElsevierNeuroImage1095-95722025-09-0131812138110.1016/j.neuroimage.2025.121381A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s diseaseVikram Venkatraghavan0Damiano Archetti1Pierrick Bourgeat2Chenyang Jiang3Mara ten Kate4Anna C. van Loenhoud5Rik Ossenkoppele6Charlotte E. Teunissen7Elsmarieke van de Giessen8Yolande A.L. Pijnenburg9Giovanni B. Frisoni10Béla Weiss11Zoltán Vidnyánszky12Tibor Auer13Stanley Durrleman14Alberto Redolfi15Simon M. Laws16Paul Maruff17Neil P. Oxtoby18Andre Altmann19Daniel C. Alexander20Wiesje M. van der Flier21Frederik Barkhof22Betty M. Tijms23Alzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands; Corresponding author at: Alzheimer Center Amsterdam, Amsterdam UMC, location VUmc, PO Box 7057, 1007 MB Amsterdam, the NetherlandsLaboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, ItalyThe Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, Queensland, AustraliaAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the NetherlandsDepartment of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Amsterdam, the NetherlandsAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the NetherlandsAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands; Clinical Memory Research Unit, Lund University, SwedenAmsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands; Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the NetherlandsDepartment of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, the NetherlandsAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the NetherlandsLaboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, SwitzerlandBrain Imaging Centre, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary; Machine Perception Research Laboratory, HUN-REN Institute for Computer Science and Control, Budapest, HungaryBrain Imaging Centre, HUN-REN Research Centre for Natural Sciences, Budapest, HungaryBrain Imaging Centre, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary; School of Psychology, University of Surrey, Guildford, United KingdomSorbonne Université, Institut du Cerveau - Paris Brain Institute – ICM, CNRS, Inria, Inserm, AP-HP, Hôpital Pitié-Salpêtrière, Paris, FranceLaboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, ItalyCentre for Precision Health, Edith Cowan University, Joondalup, Western Australia, AustraliaCogstate Ltd., Melbourne, Victoria, AustraliaCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Computer Science, University College London, UKCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Computer Science, University College London, UKCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Computer Science, University College London, UKAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands; Department of Epidemiology and Data Science, Vrije Universiteit, Amsterdam UMC, location VUmc, the NetherlandsDepartment of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering and Department of Computer Science, University College London, UK; Queen Square Institute of Neurology, University College London, UKAlzheimer Centre Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the NetherlandsPrevious 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.http://www.sciencedirect.com/science/article/pii/S1053811925003842Alzheimer’s diseaseHeterogeneitySubtypesData-drivenMRI
spellingShingle Vikram Venkatraghavan
Damiano Archetti
Pierrick Bourgeat
Chenyang Jiang
Mara ten Kate
Anna C. van Loenhoud
Rik Ossenkoppele
Charlotte E. Teunissen
Elsmarieke van de Giessen
Yolande A.L. Pijnenburg
Giovanni B. Frisoni
Béla Weiss
Zoltán Vidnyánszky
Tibor Auer
Stanley Durrleman
Alberto Redolfi
Simon M. Laws
Paul Maruff
Neil P. Oxtoby
Andre Altmann
Daniel C. Alexander
Wiesje M. van der Flier
Frederik Barkhof
Betty M. Tijms
A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
NeuroImage
Alzheimer’s disease
Heterogeneity
Subtypes
Data-driven
MRI
title A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
title_full A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
title_fullStr A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
title_full_unstemmed A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
title_short A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease
title_sort large scale multi centre study characterising atrophy heterogeneity in alzheimer s disease
topic Alzheimer’s disease
Heterogeneity
Subtypes
Data-driven
MRI
url http://www.sciencedirect.com/science/article/pii/S1053811925003842
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