Exploring associations of multimodal data with cognition in Alzheimer's disease

Poster No:

1610 

Submission Type:

Abstract Submission 

Authors:

René Lattmann1,2, Jose Bernal1, Inga Menze1, Judith Wesenberg2, Renat Yakupov1, Hartmut Schuetze2, Wenzel Glanz1, Enise Incesoy1,2, Michaela Burtyn1, Falk Lüsebrink1, Matthias Schmid3, Melina Stark3,4, Luca Kleineidam3,4, Annika Spottke3,5, Marie Coenjaerts3, Frederic Brosseron3, Klaus Fliessbach3,4, Anja Schneider3,4, Peter Dechent6, Klaus Scheffler7, Stefan Hetzer8, Alfredo Ramirez3,4, Christoph Laske9, Sebastian Sodenkamp9, Luisa-Sophie Schneider10, Daria Gref10, Eike Spruth11,12, Andrea Lohse12, Björn Schott13,14, Jens Wiltfang13,14, Ingo Kilimann15, Josef Priller16,17, Oliver Peters11,12, Michael Wagner3, Stefan Teipel15, Frank Jessen18,19, Anne Maass1,20, Emrah Düzel1,2, Gabriel Ziegler1,2

Institutions:

1German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany, 2Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany, 3German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 4Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Bonn, Germany, 5Department of Neurology, University Hospital Bonn, Bonn, Germany, 6MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University, Göttingen, Germany, 7Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany, 8Berlin Center for Advanced Neuroimaging, Charité – Universitätsmedizin Berlin, Berlin, Germany, 9German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany, 10Institute of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin, Berlin, Germany, 11German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany, 12Department of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin, Berlin, Germany, 13German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany, 14Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany, 15German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany, 16Department of Psychiatry, School of Medicine, TUM, Munich, Germany, 17University of Edinburgh and UK DRI, Edinburgh, United Kingdom, 18German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 19Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Disease (CECAD), University of Cologne, Cologne, Germany, 20Institute for Biology, Otto von Guericke University, Magdeburg, Germany

First Author:

René Lattmann  
German Center for Neurodegenerative Diseases (DZNE)|Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany|Magdeburg, Germany

Co-Author(s):

Jose Bernal  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Inga Menze  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Judith Wesenberg  
Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany
Renat Yakupov  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Hartmut Schuetze  
Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany
Wenzel Glanz  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Enise Incesoy  
German Center for Neurodegenerative Diseases (DZNE)|Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany|Magdeburg, Germany
Michaela Burtyn  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Falk Lüsebrink  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Matthias Schmid  
German Center for Neurodegenerative Diseases (DZNE)
Bonn, Germany
Melina Stark  
German Center for Neurodegenerative Diseases (DZNE)|Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Luca Kleineidam  
German Center for Neurodegenerative Diseases (DZNE)|Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Annika Spottke  
German Center for Neurodegenerative Diseases (DZNE)|Department of Neurology, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Marie Coenjaerts  
German Center for Neurodegenerative Diseases (DZNE)
Bonn, Germany
Frederic Brosseron  
German Center for Neurodegenerative Diseases (DZNE)
Bonn, Germany
Klaus Fliessbach  
German Center for Neurodegenerative Diseases (DZNE)|Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Anja Schneider  
German Center for Neurodegenerative Diseases (DZNE)|Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Peter Dechent  
MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University
Göttingen, Germany
Klaus Scheffler  
Department for Biomedical Magnetic Resonance, University of Tübingen
Tübingen, Germany
Stefan Hetzer  
Berlin Center for Advanced Neuroimaging, Charité – Universitätsmedizin Berlin
Berlin, Germany
Alfredo Ramirez  
German Center for Neurodegenerative Diseases (DZNE)|Department for Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn
Bonn, Germany|Bonn, Germany
Christoph Laske  
German Center for Neurodegenerative Diseases (DZNE)
Tübingen, Germany
Sebastian Sodenkamp  
German Center for Neurodegenerative Diseases (DZNE)
Tübingen, Germany
Luisa-Sophie Schneider  
Institute of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin
Berlin, Germany
Daria Gref  
Institute of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin
Berlin, Germany
Eike Spruth  
German Center for Neurodegenerative Diseases (DZNE)|Department of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin
Berlin, Germany|Berlin, Germany
Andrea Lohse  
Department of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin
Berlin, Germany
Björn Schott  
German Center for Neurodegenerative Diseases (DZNE)|Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen
Göttingen, Germany|Göttingen, Germany
Jens Wiltfang  
German Center for Neurodegenerative Diseases (DZNE)|Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen
Göttingen, Germany|Göttingen, Germany
Ingo Kilimann  
German Center for Neurodegenerative Diseases (DZNE)
Rostock, Germany
Josef Priller  
Department of Psychiatry, School of Medicine, TUM|University of Edinburgh and UK DRI
Munich, Germany|Edinburgh, United Kingdom
Oliver Peters  
German Center for Neurodegenerative Diseases (DZNE)|Department of Psychiatry and Psychotherapy, Charité – University Medical Center Berlin
Berlin, Germany|Berlin, Germany
Michael Wagner  
German Center for Neurodegenerative Diseases (DZNE)
Bonn, Germany
Stefan Teipel  
German Center for Neurodegenerative Diseases (DZNE)
Rostock, Germany
Frank Jessen  
German Center for Neurodegenerative Diseases (DZNE)|Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Disease (CECAD), University of Cologne
Bonn, Germany|Cologne, Germany
Anne Maass  
German Center for Neurodegenerative Diseases (DZNE)|Institute for Biology, Otto von Guericke University
Magdeburg, Germany|Magdeburg, Germany
Emrah Düzel  
German Center for Neurodegenerative Diseases (DZNE)|Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany|Magdeburg, Germany
Gabriel Ziegler  
German Center for Neurodegenerative Diseases (DZNE)|Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University
Magdeburg, Germany|Magdeburg, Germany

Introduction:

Previously, we have shown that synaptic dysfunction as measured by functional magnetic resonance imaging (fMRI) is an early process being affected along the AD cascade (Lattmann-Grefe et al., 2024) and associated with cognition. Additionally, it was shown that vascular burden in the form of white matter hyperintensities (WMH) and perivascular spaces (PVS) contribute to the cognitive deterioration in AD. However, the exact relationship between structure, function, and vascular burden remains to be elucidated. Here, we used multimodal data and latent variable modelling in a sample covering the full clinical risk spectrum of AD to assess relationships between morphometry, task-fMRI, and vascular burden. We hypothesized that vascular co-pathology would moderate the association between structure, function, and cognition in AD.

Methods:

N = 419 participants were drawn from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE; Jessen et al., 2018) study (nHealthy = 122, nSCD = 169, nMCI = 61, nAD=18, nAD relatives = 49). The cross-sectional multimodal data comprised task-fMRI data of a modified version of an incidental memory encoding paradigm (Düzel et al., 2011; Soch et al., 2021) modulated gray matter images, segmented WMH and freesurfer-based segmented basal ganglia PVS maps. Preprocessing pipelines from previous studies were used for morphometry (Nemali et al., 2023), fMRI (Lattmann-Grefe et al., 2024), WMH and PVS (Menze et al., 2024). We used partial least squares (PLS) to estimate latent variables of fMRI-GMV association. Further, principal component analysis (PCA) was used to estimate a latent variable of vascular burden by concatenating WMH and basal ganglia PVS maps. AD progression was measured by the position on a latent disease time axis using disease progression modelling from a previous study (Lattmann-Grefe et al., 2024). We used correlation and Analyses of Covariance to test for the relationship between latent variables and cognition, AD progression, and AD biomarker groups corrected for age, sex, and education post-hoc. Multiple linear regression was used to test multimodal contributions of structure and function on cognition and whether this was moderated by vascular burden in the latent space.

Results:

For a reference, the successful memory encoding contrast averaged across the whole sample is shown in Figure 1A (Blue: deactivations, Red: activations). Figure 1B shows weight maps for the latent structure-function association from PLS. Expectedly, the scores show a strong correlation (r = .42, 95% CI [.33, .50], p < .001). Better cognitive performance in the fMRI task was associated with higher scores in structure (r = .20, 95% CI [.11, .30], p < .001) and function (r = .34, 95% CI [.25, .42], p < .001). Correcting for covariates, further disease progression is associated with lower scores in structure (r = -.15, 95% CI [-.25, -.06], p = .00127) and function (r = -.21, 95% CI [-.30, .11], p < .001). Vascular burden (Figure 1C) was related to AD progression (r = .16, 95% CI [.07, .26], p < .001) and cognition (r = -.16, 95% CI [-.20, -.008], p = .034). Finally, multiple regression analyses (F(9,395) = 23.23, R2(adj) = .3312, p < .001) revealed that latent scores of structure (t = 2.155, p = .0318), function (t = 2.359, p = .0188), and vascular burden (t = -2.298, p = .0221) exert additive effects on cognition. All interaction effects between latent scores were non-significant.
Supporting Image: Fig1.jpg
 

Conclusions:

In line with previous studies, we found that the structure-function relationships are associated with AD progression and cognition. Vascular burden provides an additional load on structural integrity giving rise to cognitive problems. This has implications for brain maintenance research in AD.

Disorders of the Nervous System:

Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI)
Multivariate Approaches 1

Keywords:

FUNCTIONAL MRI
Machine Learning
Memory
Modeling
Morphometrics
Multivariate
STRUCTURAL MRI
White Matter

1|2Indicates the priority used for review

Abstract Information

By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.

I accept

The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:

I do not want to participate in the reproducibility challenge.

Please indicate below if your study was a "resting state" or "task-activation” study.

Task-activation

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was this research conducted in the United States?

No

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Functional MRI
Structural MRI
Neuropsychological testing

For human MRI, what field strength scanner do you use?

3.0T

Which processing packages did you use for your study?

SPM
Free Surfer

Provide references using APA citation style.

Düzel, E. (2011). Functional phenotyping of successful aging in long-term memory: Preserved performance in the absence of neural compensation. Hippocampus, 21(8), 803–814. https://doi.org/10.1002/hipo.20834

Jessen, F. (2018). Design and first baseline data of the DZNE multicenter observational study on predementia Alzheimer’s disease (DELCODE). Alzheimer’s Research & Therapy, 10(1), 15. https://doi.org/10.1186/s13195-017-0314-2

Lattmann-Grefe, R. (2024). Dysfunction of the episodic memory network in the Alzheimer’s disease cascade (S. 2024.10.25.620237). bioRxiv. https://doi.org/10.1101/2024.10.25.620237

Menze, I. (2024). Perivascular space enlargement accelerates in ageing and Alzheimer’s disease pathology: Evidence from a three-year longitudinal multicentre study. Alzheimer’s Research & Therapy, 16(1), 242. https://doi.org/10.1186/s13195-024-01603-8

Nemali, A. (2023). Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer’s disease—A systematic model evaluation. Medical Image Analysis, 90, 102913. https://doi.org/10.1016/j.media.2023.102913

Soch, J. (2021). A comprehensive score reflecting memory-related fMRI activations and deactivations as potential biomarker for neurocognitive aging. Human Brain Mapping, 42(14), 4478–4496. https://doi.org/10.1002/hbm.25559

UNESCO Institute of Statistics and World Bank Waiver Form

I attest that I currently live, work, or study in a country on the UNESCO Institute of Statistics and World Bank List of Low and Middle Income Countries list provided.

No