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.
Document Type
Journal Article
Date of Publication
9-1-2025
Volume
318
Funding Information
EU Joint Programme - Neurodegenerative Disease Research (JPND) (MR/T046422/1, 733051106, ANR-19-JPW2–000, 1191535, 2019–2.1.7-ERA-NET-2020–00008) / SURF Cooperative (EINF-5353) / ZonMw (10510032120003, 73305095007) / NIHR Biomedical Research Centre at UCLH / European Union (RRF-2.3.1–21–2022–00015, RRF-2.3.1–21–2022–00004) / UKRI Future Leaders Fellowship (MR/S03546X/1) / European Commission (860197, 831434, 101034344) / European Partnership on Metrology (22HLT07 NEuroBioStand) / Alzheimer Drug Discovery Foundation / Alzheimer Association / Health Holland / Dutch Research Council (ZonMw) / The Selfridges Group Foundation / Alzheimer Netherlands / Health Holland, Topsector Life Sciences & Health (LSHM20106) / National Health & Medical Research Council / Italian Ministry of Health (MoH) / Agence Nationale de la Recherche (ANR-19-JPW2–000)
School
Centre for Precision Health
Grant Number
NHMRC Number : 1191535
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Publisher
Elsevier
Identifier
Simon M. Laws: https://orcid.org/0000-0002-4355-7082
Comments
Venkatraghavan, V., Archetti, D., Bourgeat, P., Jiang, C., Kate, M. T., Van Loenhoud, A. C., Ossenkoppele, R., Teunissen, C. E., Van De Giessen, E., Pijnenburg, Y. a. L., Frisoni, G. B., Weiss, B., Vidnyánszky, Z., Auer, T., Durrleman, S., Redolfi, A., Laws, S. M., Maruff, P., Oxtoby, N. P., . . . Tijms, B. M. (2025). A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s disease. NeuroImage, 318, 121381. https://doi.org/10.1016/j.neuroimage.2025.121381