A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings Article Swipe
Hannah Baumeister
,
Jacob W. Vogel
,
Philip S. Insel
,
Luca Kleineidam
,
Steffen Wolfsgruber
,
Melina Stark
,
Helena M. Gellersen
,
Renat Yakupov
,
Matthias Schmid
,
Falk Lüsebrink
,
Frederic Brosseron
,
Gabriel Ziegler
,
Silka Dawn Freiesleben
,
Lukas Preis
,
Luisa‐Sophie Schneider
,
Eike Spruth
,
Slawek Altenstein
,
Andrea Lohse
,
Klaus Fließbach
,
Ina R. Vogt
,
Claudia Bartels
,
Björn H. Schott
,
Ayda Rostamzadeh
,
Wenzel Glanz
,
Enise I. Incesoy
,
Michaela Butryn
,
Daniel Janowitz
,
Boris‐Stephan Rauchmann
,
Ingo Kilimann
,
Doreen Göerß
,
Matthias H. Munk
,
Stefan Hetzer
,
Peter Dechent
,
Michael Ewers
,
Klaus Scheffler
,
Anika Wuestefeld
,
Olof Strandberg
,
Danielle van Westen
,
Niklas Mattsson
,
Shorena Janelidze
,
Erik Stomrud
,
Sebastian Palmqvist
,
Annika Spottke
,
Christoph Laske
,
Stefan Teipel
,
Robert Perneczky
,
Katharina Büerger
,
Anja Schneider
,
Josef Priller
,
Oliver Peters
,
Alfredo Ramı́rez
,
Jens Wiltfang
,
Michael T. Heneka
,
Michael Wagner
,
Emrah Düzel
,
Frank Jessen
,
Oskar Hansson
,
David Berron
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/brain/awae118
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/brain/awae118
Memory clinic patients are a heterogeneous population representing various aetiologies of pathological ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer’s disease patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer’s type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer’s disease biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5) as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer’s disease biomarker levels, APOE ε4 carriership and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe, with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive Alzheimer’s disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of mild cognitive impairment conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, at both the subject and the group level, was excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for Alzheimer’s disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer’s disease.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/brain/awae118
- OA Status
- green
- Cited By
- 22
- References
- 71
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4395095623
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4395095623Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/brain/awae118Digital Object Identifier
- Title
-
A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settingsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-24Full publication date if available
- Authors
-
Hannah Baumeister, Jacob W. Vogel, Philip S. Insel, Luca Kleineidam, Steffen Wolfsgruber, Melina Stark, Helena M. Gellersen, Renat Yakupov, Matthias Schmid, Falk Lüsebrink, Frederic Brosseron, Gabriel Ziegler, Silka Dawn Freiesleben, Lukas Preis, Luisa‐Sophie Schneider, Eike Spruth, Slawek Altenstein, Andrea Lohse, Klaus Fließbach, Ina R. Vogt, Claudia Bartels, Björn H. Schott, Ayda Rostamzadeh, Wenzel Glanz, Enise I. Incesoy, Michaela Butryn, Daniel Janowitz, Boris‐Stephan Rauchmann, Ingo Kilimann, Doreen Göerß, Matthias H. Munk, Stefan Hetzer, Peter Dechent, Michael Ewers, Klaus Scheffler, Anika Wuestefeld, Olof Strandberg, Danielle van Westen, Niklas Mattsson, Shorena Janelidze, Erik Stomrud, Sebastian Palmqvist, Annika Spottke, Christoph Laske, Stefan Teipel, Robert Perneczky, Katharina Büerger, Anja Schneider, Josef Priller, Oliver Peters, Alfredo Ramı́rez, Jens Wiltfang, Michael T. Heneka, Michael Wagner, Emrah Düzel, Frank Jessen, Oskar Hansson, David BerronList of authors in order
- Landing page
-
https://doi.org/10.1093/brain/awae118Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.ncbi.nlm.nih.gov/pmc/articles/11224599Direct OA link when available
- Concepts
-
Atrophy, Temporal lobe, Dementia, Population, Cohort, Biomarker, Cognitive decline, Psychology, Episodic memory, Alzheimer's disease, Pathological, Medicine, Cognition, Internal medicine, Pathology, Neuroscience, Disease, Epilepsy, Biology, Environmental health, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
22Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 14, 2024: 7, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
71Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.clinical | 160 |
| abstract_inverted_index.compared | 119 |
| abstract_inverted_index.cortical | 210 |
| abstract_inverted_index.criteria | 93 |
| abstract_inverted_index.decline. | 185 |
| abstract_inverted_index.dementia | 108 |
| abstract_inverted_index.disease. | 395 |
| abstract_inverted_index.distinct | 46 |
| abstract_inverted_index.enrolled | 66 |
| abstract_inverted_index.episodic | 137 |
| abstract_inverted_index.finally, | 207 |
| abstract_inverted_index.followed | 201 |
| abstract_inverted_index.increase | 385 |
| abstract_inverted_index.manifest | 163 |
| abstract_inverted_index.negative | 287 |
| abstract_inverted_index.observed | 292 |
| abstract_inverted_index.occurred | 238 |
| abstract_inverted_index.patients | 3 |
| abstract_inverted_index.patterns | 22, 325 |
| abstract_inverted_index.positive | 261 |
| abstract_inverted_index.profiles | 329 |
| abstract_inverted_index.proposed | 353 |
| abstract_inverted_index.regions. | 211 |
| abstract_inverted_index.reliable | 346 |
| abstract_inverted_index.repeated | 312 |
| abstract_inverted_index.standard | 73 |
| abstract_inverted_index.subtype- | 379 |
| abstract_inverted_index.subtypes | 117, 190 |
| abstract_inverted_index.temporal | 199, 204, 241, 246 |
| abstract_inverted_index.(SuStaIn) | 56 |
| abstract_inverted_index.Alzheimer | 130 |
| abstract_inverted_index.Cognitive | 131 |
| abstract_inverted_index.Composite | 132 |
| abstract_inverted_index.Inference | 55 |
| abstract_inverted_index.algorithm | 57 |
| abstract_inverted_index.baseline, | 213 |
| abstract_inverted_index.biomarker | 126, 225 |
| abstract_inverted_index.capturing | 360 |
| abstract_inverted_index.cognitive | 96, 102, 164, 172, 184, 233, 271, 306, 328 |
| abstract_inverted_index.described | 28 |
| abstract_inverted_index.divergent | 19 |
| abstract_inverted_index.examined. | 150 |
| abstract_inverted_index.executive | 140 |
| abstract_inverted_index.females). | 82 |
| abstract_inverted_index.fulfilled | 91 |
| abstract_inverted_index.increased | 301 |
| abstract_inverted_index.initially | 195, 237 |
| abstract_inverted_index.modelling | 310 |
| abstract_inverted_index.patients, | 32 |
| abstract_inverted_index.predicted | 159 |
| abstract_inverted_index.prevalent | 34 |
| abstract_inverted_index.promising | 357 |
| abstract_inverted_index.remaining | 209 |
| abstract_inverted_index.settings. | 374 |
| abstract_inverted_index.subtypes, | 48 |
| abstract_inverted_index.targeting | 392 |
| abstract_inverted_index.associated | 267, 327 |
| abstract_inverted_index.biomarkers | 264 |
| abstract_inverted_index.clinically | 36 |
| abstract_inverted_index.conversion | 174 |
| abstract_inverted_index.deviation, | 74 |
| abstract_inverted_index.diagnostic | 92 |
| abstract_inverted_index.excellent, | 344 |
| abstract_inverted_index.impairment | 103, 173, 307 |
| abstract_inverted_index.indicating | 345 |
| abstract_inverted_index.meaningful | 37 |
| abstract_inverted_index.population | 7 |
| abstract_inverted_index.previously | 27, 349 |
| abstract_inverted_index.structural | 60 |
| abstract_inverted_index.subjective | 95, 183 |
| abstract_inverted_index.unimpaired | 86, 178, 281 |
| abstract_inverted_index.BioFINDER-2 | 319 |
| abstract_inverted_index.Preclinical | 129 |
| abstract_inverted_index.aetiologies | 10 |
| abstract_inverted_index.carriership | 229 |
| abstract_inverted_index.cognitively | 85, 177 |
| abstract_inverted_index.conversion. | 308 |
| abstract_inverted_index.generalized | 270 |
| abstract_inverted_index.identified. | 192, 331 |
| abstract_inverted_index.impairment, | 165 |
| abstract_inverted_index.impairment. | 234, 272 |
| abstract_inverted_index.individuals | 259 |
| abstract_inverted_index.performance | 347 |
| abstract_inverted_index.progression | 21, 324 |
| abstract_inverted_index.statistical | 387 |
| abstract_inverted_index.Cross-cohort | 332 |
| abstract_inverted_index.Participants | 83 |
| abstract_inverted_index.functioning. | 141 |
| abstract_inverted_index.longitudinal | 288 |
| abstract_inverted_index.participants | 65, 179, 277, 294 |
| abstract_inverted_index.pathological | 12, 222 |
| abstract_inverted_index.representing | 8 |
| abstract_inverted_index.trajectories | 143, 161, 169 |
| abstract_inverted_index.Alzheimer’s | 30, 111, 124, 223, 262, 370, 394 |
| abstract_inverted_index.demographics, | 122 |
| abstract_inverted_index.heterogeneity | 361 |
| abstract_inverted_index.heterogeneous | 6 |
| abstract_inverted_index.participants, | 282 |
| abstract_inverted_index.implementation | 376 |
| abstract_inverted_index.spatiotemporal | 20 |
| abstract_inverted_index.stage-specific | 381 |
| abstract_inverted_index.pharmacological | 390 |
| abstract_inverted_index.generalizability, | 334 |
| abstract_inverted_index.Limbic-predominant | 186, 193, 273 |
| abstract_inverted_index.Hippocampal-sparing | 235 |
| abstract_inverted_index.hippocampal-sparing | 188, 298 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 6 |
| institutions_distinct_count | 58 |
| citation_normalized_percentile.value | 0.99007421 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |