TY - JOUR
T1 - A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer's disease
AU - Venkatraghavan, Vikram
AU - Archetti, Damiano
AU - Bourgeat, Pierrick
AU - Jiang, Chenyang
AU - ten Kate, Mara
AU - van Loenhoud, Anna C.
AU - Ossenkoppele, Rik
AU - Teunissen, Charlotte E.
AU - van de Giessen, Elsmarieke
AU - Pijnenburg, Yolande A. L.
AU - Frisoni, Giovanni B.
AU - Weiss, B. la
AU - Vidnyánszky, Zoltán
AU - Auer, Tibor
AU - Durrleman, Stanley
AU - Redolfi, Alberto
AU - Laws, Simon M.
AU - Maruff, Paul
AU - Oxtoby, Neil P.
AU - Altmann, Andre
AU - Alexander, Daniel C.
AU - Australian Imaging Biomarkers and Lifestyle Study, for the Alzheimer's Disease Neuroimaging Initiative, for the E-DADS Consortium
AU - van der Flier, Wiesje M.
AU - Barkhof, Frederik
AU - Tijms, Betty M.
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/9/1
Y1 - 2025/9/1
N2 - 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.
AB - 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.
KW - Alzheimer's disease
KW - Data-driven
KW - Heterogeneity
KW - MRI
KW - Subtypes
UR - https://www.scopus.com/pages/publications/105011514007
U2 - 10.1016/j.neuroimage.2025.121381
DO - 10.1016/j.neuroimage.2025.121381
M3 - Article
C2 - 40695406
SN - 1053-8119
VL - 318
JO - NeuroImage
JF - NeuroImage
M1 - 121381
ER -