A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings

Author:

Baumeister Hannah1ORCID,Vogel Jacob W2ORCID,Insel Philip S3ORCID,Kleineidam Luca45,Wolfsgruber Steffen45,Stark Melina5,Gellersen Helena M1,Yakupov Renat16ORCID,Schmid Matthias C47,Lüsebrink Falk1,Brosseron Frederic4,Ziegler Gabriel6,Freiesleben Silka D89,Preis Lukas9,Schneider Luisa-Sophie9,Spruth Eike J89,Altenstein Slawek89,Lohse Andrea9,Fliessbach Klaus45,Vogt Ina R4,Bartels Claudia10,Schott Björn H101112ORCID,Rostamzadeh Ayda13,Glanz Wenzel1,Incesoy Enise I1614,Butryn Michaela1,Janowitz Daniel15,Rauchmann Boris-Stephan161718,Kilimann Ingo1920,Goerss Doreen1920,Munk Matthias H2122,Hetzer Stefan23,Dechent Peter24,Ewers Michael1525ORCID,Scheffler Klaus26,Wuestefeld Anika2,Strandberg Olof2,van Westen Danielle2728ORCID,Mattsson-Carlgren Niklas22930ORCID,Janelidze Shorena2,Stomrud Erik231,Palmqvist Sebastian231ORCID,Spottke Annika432,Laske Christoph212233,Teipel Stefan1920ORCID,Perneczky Robert16253435,Buerger Katharina1525,Schneider Anja45,Priller Josef893637,Peters Oliver89,Ramirez Alfredo45383940ORCID,Wiltfang Jens101141,Heneka Michael T42,Wagner Michael45,Düzel Emrah1643ORCID,Jessen Frank41338,Hansson Oskar231ORCID,Berron David1243ORCID

Affiliation:

1. German Center for Neurodegenerative Diseases (DZNE) , 39120 Magdeburg , Germany

2. Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University , 222 42 Lund , Sweden

3. Department of Psychiatry and Behavioral Sciences, University of California, San Francisco , San Francisco, CA 94143 , USA

4. German Center for Neurodegenerative Diseases (DZNE) , 53127 Bonn , Germany

5. Department of Neurodegenerative Disease and Geriatric Psychiatry, University of Bonn Medical Center , 53127 Bonn , Germany

6. Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University , 39120 Magdeburg , Germany

7. Institute for Medical Biometry, University Hospital Bonn , 53127 Bonn , Germany

8. German Center for Neurodegenerative Diseases (DZNE) , 10117 Berlin , Germany

9. Department of Psychiatry and Neurosciences, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin , 10117 Berlin , Germany

10. Department of Psychiatry and Psychotherapy, University Medical Center Göttingen , 37075 Göttingen , Germany

11. German Center for Neurodegenerative Diseases (DZNE) , 37075 Göttingen , Germany

12. Leibniz Institute for Neurobiology , 39118 Magdeburg , Germany

13. Department of Psychiatry, Medical Faculty, University of Cologne , 50937 Cologne , Germany

14. Department of Psychiatry and Psychotherapy, Otto-von-Guericke University , 39120 Magdeburg , Germany

15. Institute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-Universität , 81377 Munich , Germany

16. Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität , 80336 Munich , Germany

17. Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield , Sheffield S10 2HQ , UK

18. Department of Neuroradiology, Ludwig-Maximilians-Universität , 81377 Munich , Germany

19. German Center for Neurodegenerative Diseases (DZNE) , 18147 Rostock , Germany

20. Department of Psychosomatic Medicine, Rostock University Medical Center , 18147 Rostock , Germany

21. German Center for Neurodegenerative Diseases (DZNE) , 72076 Tübingen , Germany

22. Department of Psychiatry and Psychotherapy, University of Tübingen , 72076 Tübingen , Germany

23. Berlin Center for Advanced Neuroimaging, Charité—Universitätsmedizin Berlin , 10117 Berlin , Germany

24. MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Göttingen , 37075 Göttingen , Germany

25. German Center for Neurodegenerative Diseases (DZNE) , 81377 Munich , Germany

26. Department for Biomedical Magnetic Resonance, University of Tübingen , 72076 Tübingen , Germany

27. Diagnostic Radiology, Institution of Clinical Sciences Lund, Lund University , 211 84 Lund , Sweden

28. Image and Function, Skåne University Hospital , 211 84 Lund , Sweden

29. Department of Neurology, Skåne University Hospital, Lund University , 211 84 Lund , Sweden

30. Wallenberg Center for Molecular Medicine, Lund University , 22184 Lund , Sweden

31. Memory Clinic, Skåne University Hospital , 205 02 Malmö , Sweden

32. Department of Neurology, University of Bonn , 53127 Bonn , Germany

33. Section for Dementia Research, Hertie Institute for Clinical Brain Research , 72076 Tübingen , Germany

34. Munich Cluster for Systems Neurology (SyNergy) , 81377 Munich , Germany

35. Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London , London SW7 2AZ , UK

36. Department of Psychiatry and Psychotherapy, Technical University of Munich , 81675 Munich , Germany

37. Centre for Clinical Brain Sciences, University of Edinburgh and UK DRI , Edinburgh EH16 4SB , UK

38. Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne , 50931 Cologne , Germany

39. Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne , 50931 Cologne , Germany

40. Department of Psychiatry & Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, The University of Texas at San Antonio , San Antonio, TX 78229 , USA

41. Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro , 3810-193 Aveiro , Portugal

42. Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg , 4362, Belvaux , Luxembourg

43. Center for Behavioral Brain Sciences (CBBS), Otto-von-Guericke University Magdeburg , 39106 Magdeburg , Germany

Abstract

Abstract 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.

Funder

German Center for Neurodegenerative Diseases

Publisher

Oxford University Press (OUP)

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