Abnormalities in task‐fMRI activation are related to disease progression towards Alzheimer’s disease
Authors: Lattmann René , Vockert Niklas , Wesenberg Judith , Yakupov Renat , Suksangkharn Yanin , Schütze Hartmut , Schmid Matthias , Dechent Peter , Fliessbach Klaus , Janowitz Daniel , Ewers Michael , Heneka Michael T. , Hetzer Stefan , Peters Oliver , Perneczky Robert , Priller Josef , Scheffler Klaus , Schneider Anja , Spottke Annika , Buerger Katharina , Laske Christoph , Roy‐Kluth Nina , Teipel Stefan , Wiltfang Jens , Wolfsgruber Steffen , Schott Björn H. , Wagner Michael , Jessen Frank , Maass Anne , Ziegler Gabriel , Düzel Emrah 
Published: January 2025

Background

Differences in task‐fMRI activation have recently been found to be related to neuropathological hallmarks of AD. However, the evolution of fMRI‐based activation throughout AD disease progression and its relationship with other biomarkers remains elusive. Applying a disease progression model (DPM) to a multicentric cohort with up to four annual task‐fMRI visits, we hope to provide a deeper insight into these relationships.

Method

We estimated AD disease stages using a multivariate Gaussian Process (GP) DPM including CSF‐Aβ42/40 ratio, CSF‐p‐tau181, hippocampal and entorhinal volume, ADAS13‐Cog sum and PACC5 scores. Disease stages from 493 participants with longitudinal task‐fMRI measurements from DELCODE (165 healthy controls (CN), 214 participants with SCD, 82 with MCI, 32 with suspected AD) were obtained. We derived subsequent memory and novelty contrasts from a visual memory encoding task using general linear modeling (GLM). Contrasts from all available follow‐ups were then submitted to voxel‐based group‐level GLM analyses. Activations from resulting disease‐stage‐related clusters were (1) used to estimate cluster‐level trajectory curves over disease stages using smoothing splines and (2) submitted to linear‐mixed effects models to test longitudinal changes over follow‐ups.

Result

Our DPM‐derived disease stages were associated with clinical groups, fMRI performance and white matter lesions (Figure 1C‐F). Generally, in both contrasts, activation increases were observed in task‐negative clusters while activation decreases were observed in task‐positive clusters (Figure 2C‐F). We did not find indications for inverted u‐shaped associations between disease stage and activation in whole brain voxel‐wise cross‐sectional analyses. However, smoothing splines revealed non‐linear monotonically increasing biomarker abnormality for task‐negative areas, showing earliest changes towards the beginning of disease progression. After a plateau, fMRI activation increases in abnormality conjointly with volume changes. For task‐positive areas, we observed linear relationships with disease stages (Figure 3). Activation changes over follow‐ups were not associated with disease stages.

Conclusion

Biomarker abnormality timing in our DPM reflected hypothetical AD progression. Changes in task‐fMRI activation and deactivation were both associated with progression towards AD. Smoothing spline fits indicated abnormality changes in task‐fMRI activation to begin in the earliest phases of the disease. Findings can be discussed as differential pathophysiological processes such as complex reorganization and neural noise.