In Alzheimer’s disease (AD), younger symptom onset is associated with accelerated disease progression and tau spreading, yet the mechanisms underlying faster disease manifestation are unknown. To address this, we combined resting-state fMRI and longitudinal tau-PET in two independent samples of controls and biomarker-confirmed AD patients (ADNI/BioFINDER, n = 240/57). Consistent across both samples, we found that younger symptomatic AD patients showed stronger tau-PET in globally connected fronto-parietal hubs, i.e., regions that are critical for maintaining cognition in AD. Stronger tau-PET in hubs predicted faster subsequent tau accumulation, suggesting that tau in globally connected regions facilitates connectivity-mediated tau spreading. Further, stronger tau-PET in hubs mediated the association between younger age and faster tau accumulation in symptomatic AD patients, which predicted faster cognitive decline. These independently validated findings suggest that younger AD symptom onset is associated with stronger tau pathology in brain hubs, and accelerated tau spreading throughout connected brain regions and cognitive decline.

Alzheimer’s disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and co-exist in most­ memory clinic patients. White matter damage as assessed by diffusion MRI is a key feature in both Alzheimer’s and cerebral small vessel disease. However, disease-specific biomarkers of white matter alterations are missing. Recent advances in diffusion MRI operating on the fixel level (fiber population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows to derive measures of both white matter microstructure, measured by fiber density, and macrostructure, measured by fiber-bundle cross-section. Here, we evaluated the capacity of these state-of-the-art fixel metrics to disentangle the effects of cerebral small vessel disease and Alzheimer’s disease on white matter integrity. We included three independent samples (total n = 387) covering genetically defined cerebral small vessel disease and age-matched controls, the full spectrum of biomarker-confirmed Alzheimer’s disease including amyloid- and tau-PET negative controls and a validation sample with presumed mixed pathology. In this cross-sectional analysis, we performed group comparisons between patients and controls and assessed associations between fixel metrics within main white matter tracts and imaging hallmarks of cerebral small vessel disease (white matter hyperintensity volume, lacune and cerebral microbleed count) and Alzheimer’s disease (amyloid- and tau-PET), age and a measure of neurodegeneration (brain volume). Our results showed that i) fiber density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks, ii) fiber-bundle cross-section was mainly associated with brain volume, and iii) both fiber density and fiber-bundle cross-section were reduced in the presence of amyloid, but not further exacerbated by abnormal tau deposition. Fixel metrics were only weakly associated with amyloid- and tau-PET. Taken together, our results in three independent samples suggest that fiber density captures the effect of cerebral small vessel disease, while fiber-bundle cross-section is largely determined by neurodegeneration. The ability of fixel-based imaging markers to capture distinct effects on white matter integrity can propel future applications in the context of precision medicine.

Microglial activation occurs early in Alzheimer's disease (AD) and previous studies reported both detrimental and protective effects of microglia on AD progression. Here, we used CSF sTREM2 to investigate disease stage‐dependent drivers of microglial activation and to determine downstream consequences on AD progression. We included 402 patients with measures of earliest beta‐amyloid (CSF Aβ1‐42) and late‐stage fibrillary Aβ pathology (amyloid‐PET centiloid), as well as sTREM2, p‐tau181, and FDG‐PET. To determine disease stage, we stratified participants into early Aβ‐accumulators (Aβ CSF+/PET−; n = 70) or late Aβ‐accumulators (Aβ CSF+/PET+; n = 201) plus 131 controls. In early Aβ‐accumulators, higher centiloid was associated with cross‐sectional/longitudinal sTREM2 and p‐tau181 increases. Further, higher sTREM2 mediated the association between centiloid and cross‐sectional/longitudinal p‐tau181 increases and higher sTREM2 was associated with FDG‐PET hypermetabolism. In late Aβ‐accumulators, we found no association between centiloid and sTREM2 but a cross‐sectional association between higher sTREM2, higher p‐tau181 and glucose hypometabolism. Our findings suggest that a TREM2‐related microglial response follows earliest Aβ fibrillization, manifests in inflammatory glucose hypermetabolism and may facilitate subsequent p‐tau181 increases in earliest AD.

Background Tau-PET is a prognostic marker for cognitive decline in Alzheimer’s disease, and the heterogeneity of tau-PET patterns matches cognitive symptom heterogeneity. Thus, tau-PET may allow precision-medicine prediction of individual tau-related cognitive trajectories, which can be important for determining patient-specific cognitive endpoints in clinical trials. Here, we aimed to examine whether tau-PET in cognitive-domain-specific brain regions, identified via fMRI meta-analyses, allows the prediction of domain-specific cognitive decline. Further, we aimed to determine whether tau-PET-informed personalized cognitive composites capture patient-specific cognitive trajectories more sensitively than conventional cognitive measures. Methods We included Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants classified as controls (i.e., amyloid-negative, cognitively normal, n = 121) or Alzheimer’s disease-spectrum (i.e., amyloid-positive, cognitively normal to dementia, n = 140), plus 111 AVID-1451-A05 participants for independent validation (controls/Alzheimer’s disease-spectrum=46/65). All participants underwent baseline 18F-flortaucipir tau-PET, amyloid-PET, and longitudinal cognitive testing to assess annual cognitive changes (i.e., episodic memory, language, executive functioning, visuospatial). Cognitive changes were calculated using linear mixed models. Independent meta-analytical task-fMRI activation maps for each included cognitive domain were obtained from the Neurosynth database and applied to tau-PET to determine tau-PET signal in cognitive-domain-specific brain regions. In bootstrapped linear regression, we assessed the strength of the relationship (i.e., partial R2) between cognitive-domain-specific tau-PET vs. global or temporal-lobe tau-PET and cognitive changes. Further, we used tau-PET-based prediction of domain-specific decline to compose personalized cognitive composites that were tailored to capture patient-specific cognitive decline. Results In both amyloid-positive cohorts (ADNI [age = 75.99±7.69] and A05 [age = 74.03±9.03]), cognitive-domain-specific tau-PET outperformed global and temporal-lobe tau-PET for predicting future cognitive decline in episodic memory, language, executive functioning, and visuospatial abilities. Further, a tau-PET-informed personalized cognitive composite across cognitive domains enhanced the sensitivity to assess cognitive decline in amyloid-positive subjects, yielding lower sample sizes required for detecting simulated intervention effects compared to conventional cognitive endpoints (i.e., memory composite, global cognitive composite). However, the latter effect was less strong in A05 compared to the ADNI cohort. Conclusion Combining tau-PET with task-fMRI-derived maps of major cognitive domains facilitates the prediction of domain-specific cognitive decline. This approach may help to increase the sensitivity to detect Alzheimer’s disease-related cognitive decline and to determine personalized cognitive endpoints in clinical trials.