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IntroductionWhite matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.MethodsIndividual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.ResultsVRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p

IntroductionThe spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.MethodsIndividual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.ResultsWMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.DiscussionAggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Tau pathology is the main driver of neuronal dysfunction in 4-repeat tauopathies, including cortico-basal degeneration and progressive supranuclear palsy. Tau is assumed to spread prion-like across connected neurons, but the mechanisms of tau propagation are largely elusive in 4-repeat tauopathies, characterized not only by neuronal but also by astroglial and oligodendroglial tau accumulation. Here, we assess whether connectivity is associated with 4R-tau deposition patterns by combining resting-state fMRI connectomics with both 2nd generation 18F-PI-2620 tau-PET in 46 patients with clinically diagnosed 4-repeat tauopathies and post-mortem cell-type-specific regional tau assessments from two independent progressive supranuclear palsy patient samples (n = 97 and n = 96). We find that inter-regional connectivity is associated with higher inter-regional correlation of both tau-PET and post-mortem tau levels in 4-repeat tauopathies. In regional cell-type specific post-mortem tau assessments, this association is stronger for neuronal than for astroglial or oligodendroglial tau, suggesting that connectivity is primarily associated with neuronal tau accumulation. Using tau-PET we find further that patient-level tau patterns are associated with the connectivity of subcortical tau epicenters. Together, the current study provides combined in vivo tau-PET and histopathological evidence that brain connectivity is associated with tau deposition patterns in 4-repeat tauopathies.

Fibrillar tau gradually progresses in the brain during the course of Alzheimer’s disease (AD). However, the contribution of tau accumulation in a given brain region to decline in different cognitive domains and thus phenotypic heterogeneity in AD remains unclear. Here, we leveraged the functional connectome to link the locality of tau accumulation to domain-specific cognitive impairment.In the current study, we mapped regional tau-PET accumulation onto the normative functional connectome. Subsequently, we cross-validated in two samples of AD-patients the associations between the tau-connectivity profiles and cognitive domains (episodic memory, executive function, or language). Lastly, we tested the effect of local tau-PET accumulation on the domain-specific tau-lesion networks and cognition.We identified cognitive-domain-specific tau-lesion networks, where closer topological proximity of tau-PET locations to a network was predictive of worse impairment in that domain. Higher tau-PET was associated with decreased domain-specific network connectivity, and the decrease in connectivity was associated with lower domain-specific cognition.The tau locations’ connectivity profile explained domain-specific cognitive impairment, where disrupted connectivity may underlie the effect of tau on cognitive impairment.

Alzheimer's disease (AD) is associated with reduced temporo-parietal cerebral blood flow (CBF). However, a substantial variability in CBF across the clinical spectrum of AD has been reported, possibly due to differences in primary AD pathologies. Here, we assessed CBF (ASL-MRI), tau (AV1451-PET) and amyloid (AV45/FBB-PET) in 156 subjects across the AD continuum. Using mixed-effect regression analyses, we assessed the local associations between amyloid-PET, tau-PET and CBF in a hypothesis-driven way focusing on each pathology's predilection areas. The contribution of Apolipoprotein E (APOE) genotype, and MRI markers of small vessel disease (SVD) to alterations in CBF were assessed as well. Tau-PET was associated with lower CBF in the entorhinal cortex, independent of Aβ. Amyloid-PET was associated with lower CBF in temporo-parietal regions. No associations between MRI markers of SVD and CBF were observed. These results provide evidence that in addition to Aβ, pathologic tau is a major correlate of CBF in early Braak stages, independent of Aβ, APOE genotype and SVD markers.

Klotho-VS heterozygosity (KL-VShet) is associated with reduced risk of Alzheimer's disease (AD). However, whether KL-VShet is associated with lower levels of pathologic tau, i.e., the key AD pathology driving neurodegeneration and cognitive decline, is unknown. Here, we assessed the interaction between KL-VShet and levels of beta-amyloid, a key driver of tau pathology, on the levels of PET-assessed neurofibrillary tau in 551 controls and patients across the AD continuum. KL-VShet showed lower cross-sectional and longitudinal increase in tau-PET per unit increase in amyloid-PET when compared to that of non-carriers. This association of KL-VShet on tau-PET was stronger in Klotho mRNA-expressing brain regions mapped onto a gene expression atlas. KL-VShet was related to better memory functions in amyloid-positive participants and this association was mediated by lower tau-PET. Amyloid-PET levels did not differ between KL-VShet carriers versus non-carriers. Together, our findings provide evidence to suggest a protective role of KL-VShet against amyloid-related tau pathology and tau-related memory impairments in elderly humans at risk of AD dementia.

In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

Abstract 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.

Abstract 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 R 2) 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.

Abstract Background In Alzheimer’s disease (AD), fibrillar tau initially occurs locally and progresses preferentially between closely connected regions. However, the underlying sources of regional vulnerability to tau pathology remain unclear. Previous brain-autopsy findings suggest that the myelin levels—which differ substantially between white matter tracts in the brain—are a key modulating factor of region-specific susceptibility to tau deposition. Here, we investigated whether myelination differences between fiber tracts of the human connectome are predictive of the interregional spreading of tau pathology in AD. Methods We included two independently recruited samples consisting of amyloid-PET-positive asymptomatic and symptomatic elderly individuals, in whom tau-PET was obtained at baseline (ADNI: n = 275; BioFINDER-1: n = 102) and longitudinally in a subset (ADNI: n = 123, mean FU = 1.53 [0.69–3.95] years; BioFINDER-1: n = 39, mean FU = 1.87 [1.21–2.78] years). We constructed MRI templates of the myelin water fraction (MWF) in 200 gray matter ROIs and connecting fiber tracts obtained from adult cognitively normal participants. Using the same 200 ROI brain-parcellation atlas, we obtained tau-PET ROI values from each individual in ADNI and BioFINDER-1. In a spatial regression analysis, we first tested the association between cortical myelin and group-average tau-PET signal in the amyloid-positive and control groups. Secondly, employing a previously established approach of modeling tau-PET spreading based on functional connectivity between ROIs, we estimated in a linear regression analysis, whether the level of fiber-tract myelin modulates the association between functional connectivity and longitudinal tau-PET spreading (i.e., covariance) between ROIs. Results We found that higher myelinated cortical regions show lower tau-PET uptake (ADNI: rho = − 0.267, p

The single nucleotide polymorphism (SNP) rs744373 in the bridging integrator-1 gene (BIN1) is a risk factor for Alzheimer's disease (AD). In the brain, BIN1 is involved in endocytosis and sustaining cytoskeleton integrity. Post-mortem and in vitro studies suggest that BIN1-associated AD risk is mediated by increased tau pathology but whether rs744373 is associated with increased tau pathology in vivo is unknown. Here we find in 89 older individuals without dementia, that BIN1 rs744373 risk-allele carriers show higher AV1451 tau-PET across brain regions corresponding to Braak stages II-VI. In contrast, the BIN1 rs744373 SNP was not associated with AV45 amyloid-PET uptake. Furthermore, the rs744373 risk-allele was associated with worse memory performance, mediated by increased global tau levels. Together, our findings suggest that the BIN1 rs744373 SNP is associated with increased tau but not beta-amyloid pathology, suggesting that alterations in BIN1 may contribute to memory deficits via increased tau pathology.

Individuals with young onset sporadic Alzheimer’s disease show faster pathological and clinical progression. Here the authors report that earlier symptom onset in Alzheimer’s disease is associated with higher tau pathology in globally connected brain hubs, accelerated connectivity-mediated tau spreading and faster cognitive decline.

Tau pathology drives neuronal dysfunction in 4- repeat tauopathies. Here, the authors combine tau-PET, resting-state fMRI and histopathology data, to show that brain connectivity is associated with tau deposition patterns in 4-repeat tauopathies.

Introduction: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as “unusual”, but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. Methods: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. Results: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. Discussion: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Abstract Background To systematically examine the clinical utility of tau-PET and Braak-staging as prognostic markers of future cognitive decline in older adults with and without cognitive impairment. Methods In this longitudinal study, we included 396 cognitively normal to dementia subjects with 18F-Florbetapir/18F-Florbetaben-amyloid-PET, 18F-Flortaucipir-tau-PET and ~ 2-year cognitive follow-up. Annual change rates in global cognition (i.e., MMSE, ADAS13) and episodic memory were calculated via linear-mixed models. We determined global amyloid-PET (Centiloid) plus global and Braak-stage-specific tau-PET SUVRs, which were stratified as positive(+)/negative(−) at pre-established cut-offs, classifying subjects as Braak0/BraakI+/BraakI–IV+/BraakI–VI+/Braakatypical+. In bootstrapped linear regression, we assessed the predictive accuracy of global tau-PET SUVRs vs. Centiloid on subsequent cognitive decline. To test for independent tau vs. amyloid effects, analyses were further controlled for the contrary PET-tracer. Using ANCOVAs, we tested whether more advanced Braak-stage predicted accelerated future cognitive decline. All models were controlled for age, sex, education, diagnosis, and baseline cognition. Lastly, we determined Braak-stage-specific conversion risk to mild cognitive impairment (MCI) or dementia. Results Baseline global tau-PET SUVRs explained more variance (partial R 2) in future cognitive decline than Centiloid across all cognitive tests (Cohen’s d ~ 2, all tests p

The KL-VS haplotype of the Klotho gene has been associated with reduced risk of Alzheimer’s disease and dementia. Here the authors show an association between the KL-VS haplotype and amyloid-dependent tau accumulation using PET data.

Abstract Background FDG-PET hypermetabolism can be observed in mild cognitive impairment (MCI), but the link to primary pathologies of Alzheimer’s diseases (AD) including amyloid and tau is unclear. Methods Using voxel-based regression, we assessed local interactions between amyloid- and tau-PET on spatially matched FDG-PET in 72 MCI patients. Control groups included cerebrospinal fluid biomarker characterized cognitively normal (CN, n = 70) and AD dementia subjects (n = 95). Results In MCI, significant amyloid-PET by tau-PET interactions were found in frontal, lateral temporal, and posterior parietal regions, where higher local tau-PET was associated with higher spatially corresponding FDG-PET at low levels of local amyloid-PET. FDG-PET in brain regions with a significant local amyloid- by tau-PET interaction was higher compared to that in CN and AD dementia and associated with lower episodic memory. Conclusion Higher tau-PET in the presence of low amyloid-PET is associated with abnormally increased glucose metabolism that is accompanied by episodic memory impairment.

Tau accumulation is associated with disease progression in Alzheimer’s disease. Here the authors use resting state fMRI and tau-PET to demonstrate that baseline connectivity in Alzheimer's disease is associated with tau spreading.

The BIN1 SNP rs744373 is associated with higher CSF tau and phosphorylated tau levels. Here the authors show, using PET imaging, that this SNP is associated with tau accumulation in the brain as well as impaired memory in older individuals without dementia.

Objective: We aimed to test whether region‐specific factors, including spatial expression patterns of the tau‐encoding gene MAPT and regional levels of amyloid positron emission tomography (PET), enhance connectivity‐based modeling of the spatial variability in tau‐PET deposition in the Alzheimer disease (AD) spectrum. Methods: We included 685 participants (395 amyloid‐positive participants within AD spectrum and 290 amyloid‐negative controls) with tau‐PET and amyloid‐PET from 3 studies (Alzheimer's Disease Neuroimaging Initiative, 18F‐AV‐1451‐A05, and BioFINDER‐1). Resting‐state functional magnetic resonance imaging was obtained in healthy controls (n = 1,000) from the Human Connectome Project, and MAPT gene expression from the Allen Human Brain Atlas. Based on a brain‐parcellation atlas superimposed onto all modalities, we obtained region of interest (ROI)‐to‐ROI functional connectivity, ROI‐level PET values, and MAPT gene expression. In stepwise regression analyses, we tested connectivity, MAPT gene expression, and amyloid‐PET as predictors of group‐averaged and individual tau‐PET ROI values in amyloid‐positive participants. Results: Connectivity alone explained 21.8 to 39.2% (range across 3 studies) of the variance in tau‐PET ROI values averaged across amyloid‐positive participants. Stepwise addition of MAPT gene expression and amyloid‐PET increased the proportion of explained variance to 30.2 to 46.0% and 45.0 to 49.9%, respectively. Similarly, for the prediction of patient‐level tau‐PET ROI values, combining all 3 predictors significantly improved the variability explained (mean adjusted R2 range across studies = 0.118–0.148, 0.156–0.196, and 0.251–0.333 for connectivity alone, connectivity plus MAPT expression, and all 3 modalities combined, respectively). Interpretation: Across 3 study samples, combining the functional connectome and molecular properties substantially enhanced the explanatory power compared to single modalities, providing a valuable tool to explain regional susceptibility to tau deposition in AD. ANN NEUROL 2024;95:274–287 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: Polygenic variation accounts for a substantial portion of the risk of Alzheimer's disease (AD), but its effect on the rate of fibrillar‐tau accumulation as a key driver of dementia symptoms is unclear. Methods: We combined the to‐date largest number of genetic risk variants of AD (n = 85 lead single‐nucleotide polymorphisms [SNPs]) from recent genome‐wide association studies (GWAS) to generate a polygenic score (PGS). We assessed longitudinal tau‐positron emission tomography (PET), amyloid‐PET, and cognition in 231 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Using the PGS, together with global amyloid‐PET, we predicted the rate of tau‐PET increases in Braak‐stage regions‐of‐interest and cognitive decline. We also assessed PGS‐risk enrichment effects on the required sample size in clinical trials targeting tau pathology. Results: We found that a higher PGS was associated with higher rates of tau‐PET accumulation, in particular at elevated amyloid‐PET levels. The tau‐PET increases mediated the association between PGS and faster cognitive decline. Risk enrichment through high PGS afforded sample size savings by 34%. Interpretation: Our results demonstrate that the PGS predicts faster tau progression and thus cognitive decline, showing utility to enhance statistical power in clinical trials. ANN NEUROL 2023;93:819–829 [ABSTRACT FROM AUTHOR]