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BackgroundWhite matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer’s disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.MethodsWe used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).ResultsAcross tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice’s coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.ConclusionTo conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

Brain endothelial cells (BECs) have unique roles in controlling cerebral blood flow (CBF) and as a cornerstone of the blood-brain barrier (BBB). Graph: Figure 1 The BRENDA network will define mechanisms linking risk genes for cerebral small vessel disease and stroke to brain endothelial cell dysfunction and brain injury, applying cutting edge technology to novel disease models, including human inducible pluripotent stem cell-based models of the blood-brain barrier and neurovascular unit (Aim 1); test whether genetic predisposition synergizes with hypertension to augment brain endothelial cell dysfunction and brain injury (Aim 2, "two-hit" model); and determine whether brain endothelial cell heterogeneity underlies differences in brain injury across regions (Aim 3). Genome-wide association studies[8] implicate BEC dysfunction in disease initiation and propagation.[5] For instance, common variants of I FOXF2 i are associated with small vessel stroke and white matter lesions (WMLs). [Extracted from the article]

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]

Introduction: It is uncertain whether subjective cognitive decline (SCD) in individuals who seek medical help serves the identification of the initial symptomatic stage 2 of the Alzheimer's disease (AD) continuum. Methods: Cross‐sectional and longitudinal data from the multicenter, memory clinic–based DELCODE study. Results: The SCD group showed slightly worse cognition as well as more subtle functional and behavioral symptoms than the control group (CO). SCD–A+ cases (39.3% of all SCD) showed greater hippocampal atrophy, lower cognitive and functional performance, and more behavioral symptoms than CO–A+. Amyloid concentration in the CSF had a greater effect on longitudinal cognitive decline in SCD than in the CO group. Discussion: Our data suggests that SCD serves the identification of stage 2 of the AD continuum and that stage 2, operationalized as SCD‐A+, is associated with subtle, but extended impact of AD pathology in terms of neurodegeneration, symptoms and clinical progression. [ABSTRACT FROM AUTHOR]

Alzheimer's disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and coexist 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 (fibre population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows derivation of measures of both white matter microstructure, measured by fibre density, and macrostructure, measured by fibre-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) fibre density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks; (ii) fibre-bundle cross-section was mainly associated with brain volume; and (iii) both fibre density and fibre-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 fibre density captures the effect of cerebral small vessel disease, while fibre-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. [ABSTRACT FROM AUTHOR]

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. 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. [ABSTRACT FROM AUTHOR]

Cerebral amyloid angiopathy (CAA) is an age-related condition and a major cause of intracerebral hemorrhage and cognitive decline that shows close links with Alzheimer's disease (AD). CAA is characterized by the aggregation of amyloid-β (Aβ) peptides and formation of Aβ deposits in the brain vasculature resulting in a disruption of the angioarchitecture. Capillaries are a critical site of Aβ pathology in CAA type 1 and become dysfunctional during disease progression. Here, applying an advanced protocol for the isolation of parenchymal microvessels from post-mortem brain tissue combined with liquid chromatography tandem mass spectrometry (LC–MS/MS), we determined the proteomes of CAA type 1 cases (n = 12) including a patient with hereditary cerebral hemorrhage with amyloidosis-Dutch type (HCHWA-D), and of AD cases without microvascular amyloid pathology (n = 13) in comparison to neurologically healthy controls (n = 12). ELISA measurements revealed microvascular Aβ1-40 levels to be exclusively enriched in CAA samples (mean: > 3000-fold compared to controls). The proteomic profile of CAA type 1 was characterized by massive enrichment of multiple predominantly secreted proteins and showed significant overlap with the recently reported brain microvascular proteome of patients with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary cerebral small vessel disease (SVD) characterized by the aggregation of the Notch3 extracellular domain. We found this overlap to be largely attributable to the accumulation of high-temperature requirement protein A1 (HTRA1), a serine protease with an established role in the brain vasculature, and several of its substrates. Notably, this signature was not present in AD cases. We further show that HTRA1 co-localizes with Aβ deposits in brain capillaries from CAA type 1 patients indicating a pathologic recruitment process. Together, these findings suggest a central role of HTRA1-dependent protein homeostasis in the CAA microvasculature and a molecular connection between multiple types of brain microvascular disease. [ABSTRACT FROM AUTHOR]

Introduction: The BIN1 rs744373 single nucleotide polymorphism (SNP) is a key genetic risk locus for Alzheimer’s disease (AD) associated with tau pathology. Because tau typically accumulates in response to amyloid beta (Aβ), we tested whether BIN1 rs744373 accelerates Aβ-related tau accumulation. Methods: We included two samples (Alzheimer’s Disease Neuroimaging Initiative [ADNI], n = 153; Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably [BioFINDER], n = 63) with longitudinal 18F-Flortaucipir positron emission tomography (PET), Aβ biomarkers, and longitudinal cognitive assessments. We assessed whether BIN1 rs744373 was associated with faster tau-PET accumulation at a given level of Aβ and whether faster BIN1 rs744373-associated tau-PET accumulation mediated cognitive decline. Results: BIN1 rs744373 risk-allele carriers showed faster global tau-PET accumulation (ADNI/BioFINDER, P < .001/P < .001). We found significant Aβ by rs744373 interactions on global tau-PET change (ADNI: β/standard error [SE] = 0.42/0.14, P = 0.002; BioFINDER: β/SE = –0.35/0.15, P = .021), BIN1 risk-allele carriers showed accelerated tau-PET accumulation at higher Aβ levels. In ADNI, rs744373 effects on cognitive decline were mediated by faster global tau-PET accumulation (β/SE = 0.20/0.07, P = .005). Discussion: BIN1-associated AD risk is potentially driven by accelerated tau accumulation in the face of Aβ. [ABSTRACT FROM AUTHOR]

Objectives: It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts.Methods: Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined.Results: The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures.Conclusions: Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity. [ABSTRACT FROM AUTHOR]

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 R2) in future cognitive decline than Centiloid across all cognitive tests (Cohen's d ~ 2, all tests p < 0.001) and diagnostic groups. Associations between tau-PET and cognitive decline remained consistent when controlling for Centiloid, while associations between amyloid-PET and cognitive decline were non-significant when controlling for tau-PET. More advanced Braak-stage was associated with gradually worsening future cognitive decline, independent of Centiloid or diagnostic group (p < 0.001), and elevated conversion risk to MCI/dementia. Conclusion: Tau-PET and Braak-staging are highly predictive markers of future cognitive decline and may be promising single-modality estimates for prognostication of patient-specific progression risk in clinical settings. [ABSTRACT FROM AUTHOR]

In Alzheimer's disease (AD), Aβ deposits form slowly, several decades before further pathological events trigger neurodegeneration and dementia. However, a substantial proportion of affected individuals remains non-demented despite AD pathology, raising questions about the underlying factors that determine the transition to clinical disease. Here, we emphasize the critical function of resilience and resistance factors, which we extend beyond the concept of cognitive reserve to include the glial, immune, and vascular system. We review the evidence and use the metaphor of "tipping points" to illustrate how gradually forming AD neuropathology in the preclinical stage can transition to dementia once adaptive functions of the glial, immune, and vascular system are lost and self-reinforcing pathological cascades are unleashed. Thus, we propose an expanded framework for pathomechanistic research that focuses on tipping points and non-neuronal resilience mechanisms, which may represent previously untapped therapeutic targets in preclinical AD. [ABSTRACT FROM AUTHOR]