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.

Introduction Lower network segregation is associated with accelerated cognitive decline in Alzheimer's disease (AD), yet it is unclear whether less segregated brain networks facilitate connectivity‐mediated tau spreading. Methods We combined resting state functional magnetic resonance imaging (fMRI) with longitudinal tau positron emission tomography (PET) in 42 betamyloid‐negative controls and 81 amyloid beta positive individuals across the AD spectrum. Network segregation was determined using resting‐state fMRI–assessed connectivity among 400 cortical regions belonging to seven networks. Results AD subjects with higher network segregation exhibited slower brain‐wide tau accumulation relative to their baseline entorhinal tau PET burden (typical onset site of tau pathology). Second, by identifying patient‐specific tau epicenters with highest baseline tau PET we found that stronger epicenter segregation was associated with a slower rate of tau accumulation in the rest of the brain in relation to baseline epicenter tau burden. Discussion Our results indicate that tau spreading is facilitated by a more diffusely organized connectome, suggesting that brain network topology modulates tau spreading in AD. Highlights Higher brain network segregation is associated with attenuated tau pathology accumulation in Alzheimer's disease (AD). A patient‐tailored approach allows for the more precise localization of tau epicenters. The functional segregation of subject‐specific tau epicenters predicts the rate of future tau accumulation.

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.

The neocortex is the most complex part of the mammalian brain and as such it has undergone tremendous expansion during evolution, especially in primates. The majority of neocortical neurons originate from distinct neural stem and progenitor cells (NPCs) located in the ventricular and subventricular zone (SVZ). Previous studies revealed that the SVZ thickness as well as the abundance and distribution of NPCs, especially that of basal radial glia (bRG), differ markedly between the lissencephalic rodent and gyrencephalic primate neocortex. The northern tree shrew (Tupaia belangeri) is a rat-sized mammal with a high brain to body mass ratio, which stands phylogenetically mid-way between rodents and primates. Our study provides – for the first time – detailed data on the presence, abundance and distribution of bRG and other distinct NPCs in the developing neocortex of the northern tree shrew (Tupaia belangeri). We show that the developing tree shrew neocortex is characterized by an expanded SVZ, a high abundance of Pax6+ NPCs in the SVZ, and a relatively high percentage of bRG at peak of upper-layer neurogenesis. We further demonstrate that key features of tree shrew neocortex development, e.g., the presence, abundance and distribution of distinct NPCs, are closer related to those of gyrencephalic primates than to those of ferret and lissencephalic rodents. Together, our study provides novel insight into the evolution of bRG and other distinct NPCs in the neocortex development of Euarchontoglires and introduces the tree shrew as a potential novel model organism in the area of human brain development and developmental disorders.

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.

BackgroundMicroglial activation occurs early in Alzheimer’s disease (AD) and previous studies reported both detrimental and protective effects of microglia on AD progression. Therefore, it is critical to investigate at which AD stages microglial activation could be protective or detrimental to evaluate microglia as a treatment target. To address this, we used CSF sTREM2 (i.e. Triggering receptor expressed on myeloid cells 2) to investigate disease stage-dependent drivers of microglial activation and to determine downstream consequences on AD biomarker progression.MethodsWe included 402 cognitively normal and mild cognitively impaired patients with CSF sTREM2 assessments. To assess AD severity, we included measures of earliest beta-amyloid (i.e. Aβ) in CSF (i.e. Aβ1-42) and late-stage fibrillary Aβ pathology (i.e. amyloid-PET centiloid), as well as p-tau181 and FDG-PET for assessing downstream changes in tau and cerebral glucose metabolism. To determine disease stage, we stratified participants according to earliest Aβ abnormalities (i.e. Aβ CSF+/PET−; early Aβ-accumulators, n=70) or fully developed fibrillary Aβ pathology (i.e. Aβ CSF+/PET+; late Aβ-accumulators, n=201) plus 131 healthy controls (i.e. Aβ CSF−/PET−).ResultsIn early Aβ-accumulators, higher centiloid was associated with cross-sectional/longitudinal sTREM2 and p-tau increases, suggesting reactive microglial and p-tau increases in response to earliest Aβ fibrillization. Further, higher sTREM2 mediated the association between centiloid and cross-sectional/longitudinal p-tau increases and higher sTREM2 was associated with FDG-PET hypermetabolism in line with previous findings of increased glucose consumption of activated microglia. In late Aβ-accumulators, we found no association between centiloid and sTREM2 but a cross-sectional association between higher sTREM2, higher p-tau and glucose hypometabolism, suggesting that sTREM2 parallels tau and neurodegeneration rather than Aβ once fully developed Aβ pathology is present.ConclusionsOur findings suggest that sTREM2-related microglial activation occurs in response to earliest Aβ fibrillization, manifests in inflammatory glucose hypermetabolism and may facilitate subsequent p-tau increases in earliest AD, while previous reports of protective sTREM2 effects may occur in later AD stages.

Temporalis muscle (TM) atrophy has emerged as a potential biomarker for muscle wasting. However, its diagnostic utility as a monitoring tool in intensive care remains uncertain. Hence, the objective of this study was to evaluate the diagnostic value of sequential ultrasound- and computed tomography (CT)-based measurements of TM thickness (TMT). With a prospective observational design, we included 40 patients without preexisting sarcopenia admitted to a neurointensive care unit. TMT measurements, performed upon admission and serially every 3–4 days, were correlated with rectus femoris muscle thickness (RFT) ultrasound measurements. Interrater reliability was assessed by Bland Altmann plots and intraclass correlation coefficient (ICC). Analysis of variance was performed in subgroups to evaluate differences in the standard error of measurement (SEM). RFT decline was paralleled by ultrasound- as well as CT-based TMT measurements (TMT to RFT: r = 0.746, p < 0.001; CT-based TMT to ultrasound-based RFT: r = 0.609, p < 0.001). ICC was 0.80 [95% CI 0.74, 0.84] for ultrasound-based assessment and 0.90 [95% CI 0.88, 0.92] for CT-based TMT measurements. Analysis of variance for BMI, Heckmatt score, fluid balance, and agitation showed no evidence of measurement errors in these subgroups. This study demonstrates the clinical feasibility and utility of ultrasound- and CT-based TMT measurements for the assessment of muscle wasting.

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