Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease.

Staging amyloid-beta (Aß) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aß pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aß ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aß-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aß therapies.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Longitudinal cerebrospinal fluid measurements show glial hypo- and hyperactivation in predementia Alzheimer's disease.

BACKGROUND: Brain innate immune activation is associated with Alzheimer's disease (AD), but degrees of activation may vary between disease stages. Thus, brain innate immune activation must be assessed in longitudinal clinical studies that include biomarker negative healthy controls and cases with established AD pathology. Here, we employ longitudinally sampled cerebrospinal fluid (CSF) core AD, immune activation and glial biomarkers to investigate early (predementia stage) innate immune activation levels and biomarker profiles. METHODS: We included non-demented cases from a longitudinal observational cohort study, with CSF samples available at baseline (n = 535) and follow-up (n = 213), between 1 and 6 years from baseline (mean 2.8 years). We measured Aß42/40 ratio, p-tau181, and total-tau to determine Ab (A+), tau-tangle pathology (T+), and neurodegeneration (N+), respectively. We classified individuals into these groups: A-/T-/N-, A+/T-/N-, A+/T+ or N+, or A-/T+ or N+. Using linear and mixed linear regression, we compared levels of CSF sTREM2, YKL-40, clusterin, fractalkine, MCP-1, IL-6, IL-1, IL-18, and IFN-γ both cross-sectionally and longitudinally between groups. A post hoc analysis was also performed to assess biomarker differences between cognitively healthy and impaired individuals in the A+/T+ or N+ group. RESULTS: Cross-sectionally, CSF sTREM2, YKL-40, clusterin and fractalkine were higher only in groups with tau pathology, independent of amyloidosis (p < 0.001, A+/T+ or N+ and A-/T+ or N+, compared to A-/T-/N-). No significant group differences were observed for the cytokines CSF MCP-1, IL-6, IL-10, IL18 or IFN-γ. Longitudinally, CSF YKL-40, fractalkine and IFN-γ were all significantly lower in stable A+/T-/N- cases (all p < 0.05). CSF sTREM2, YKL-40, clusterin, fractalkine (p < 0.001) and MCP-1 (p < 0.05) were all higher in T or N+, with or without amyloidosis at baseline, but remained stable over time. High CSF sTREM2 was associated with preserved cognitive function within the A+/T+ or N+ group, relative to the cognitively impaired with the same A/T/N biomarker profile (p < 0.01). CONCLUSIONS: Immune hypoactivation and reduced neuron-microglia communication are observed in isolated amyloidosis while activation and increased fractalkine accompanies tau pathology in predementia AD. Glial hypo- and hyperactivation through the predementia AD continuum suggests altered glial interaction with Ab and tau pathology, and may necessitate differential treatments, depending on the stage and patient-specific activation patterns.

Segmenting white matter hyperintensities on isotropic three-dimensional Fluid Attenuated Inversion Recovery magnetic resonance images: Assessing deep learning tools on a Norwegian imaging database.

An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer's disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models-one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed-were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining.

Medial Temporal Lobe Atrophy in Predementia Alzheimer's Disease: A Longitudinal Multi-Site Study Comparing Staging and A/T/N in a Clinical Research Cohort.

BACKGROUND: Atrophy of the medial temporal lobe (MTL) is a biological characteristic of Alzheimer's disease (AD) and can be measured by segmentation of magnetic resonance images (MRI). OBJECTIVE: To assess the clinical utility of automated volumetry in a cognitively well-defined and biomarker-classified multi-center longitudinal predementia cohort. METHODS: We used Automatic Segmentation of Hippocampal Subfields (ASHS) to determine MTL morphometry from MRI. We harmonized scanner effects using the recently developed longitudinal ComBat. Subjects were classified according to the A/T/N system, and as normal controls (NC), subjective cognitive decline (SCD), or mild cognitive impairment (MCI). Positive or negative values of A, T, and N were determined by cerebrospinal fluid measurements of the Aß42/40 ratio, phosphorylated and total tau. From 406 included subjects, longitudinal data was available for 206 subjects by stage, and 212 subjects by A/T/N. RESULTS: Compared to A-/T-/N- at baseline, the entorhinal cortex, anterior and posterior hippocampus were smaller in A+/T+orN+. Compared to NC A- at baseline, these subregions were also smaller in MCI A+. Longitudinally, SCD A+ and MCI A+, and A+/T-/N- and A+/T+orN+, had significantly greater atrophy compared to controls in both anterior and posterior hippocampus. In the entorhinal and parahippocampal cortices, longitudinal atrophy was observed only in MCI A+ compared to NC A-, and in A+/T-/N- and A+/T+orN+ compared to A-/T-/N-. CONCLUSION: We found MTL neurodegeneration largely consistent with existing models, suggesting that harmonized MRI volumetry may be used under conditions that are common in clinical multi-center cohorts.

Phenotype-informed polygenic risk scores are associated with worse outcome in individuals at risk of Alzheimer's disease.

Introduction: Patients with predementia Alzheimer's disease (AD) and at-risk subjects are targets for promising disease-modifying treatments, and improved polygenic risk scores (PRSs) could improve early-stage case selection. Methods: Phenotype-informed PRSs were developed by selecting AD-associated variants conditional on relevant inflammatory or cardiovascular traits. The primary outcome was longitudinal changes in measures of AD pathology, namely development of pathological amyloid deposition, medial temporal lobe atrophy, and cognitive decline in a prospective cohort study including 394 adults without AD dementia. Results: High-risk groups defined by phenotype-informed AD PRSs had significantly steeper volume decline in medial temporal cortices, and the high-risk group defined by the cardiovascular-informed AD PRS had significantly increased hazard ratio of pathological amyloid deposition, compared to low-risk groups. Discussion: AD PRSs informed by inflammatory disorders or cardiovascular risk factors and diseases are associated with development of AD pathology markers and may improve identification of subjects at risk for progression of AD.

Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns.

White matter hyperintensities (WMHs) are associated with vascular risk and Alzheimer's disease. In this study, we examined relations between WMH load and distribution, amyloid pathology and vascular risk in 339 controls and cases with either subjective (SCD) or mild cognitive impairment (MCI). Regional deep (DWMH) and periventricular (PWMH) WMH loads were determined using an automated algorithm. We stratified on Aß1-42 pathology (Aß+/-) and analyzed group differences, as well as associations with Framingham Risk Score for cardiovascular disease (FRS-CVD) and age. Occipital PWMH (p = 0.001) and occipital DWMH (p = 0.003) loads were increased in SCD-Aß+ compared with Aß- controls. In MCI-Aß+ compared with Aß- controls, there were differences in global WMH (p = 0.003), as well as occipital DWMH (p = 0.001) and temporal DWMH (p = 0.002) loads. FRS-CVD was associated with frontal PWMHs (p = 0.003) and frontal DWMHs (p = 0.005), after adjusting for age. There were associations between global and all regional WMH loads and age. In summary, posterior WMH loads were increased in SCD-Aß+ and MCI-Aß+ cases, whereas frontal WMHs were associated with vascular risk. The differences in WMH topography support the use of regional WMH load as an early-stage marker of etiology.

Author Correction: GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study.

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10-8). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10-6. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders.

Detecting At-Risk Alzheimer's Disease Cases.

While APOEɛ4 is the major genetic risk factor for Alzheimer's disease (AD), amyloid dysmetabolism is an initial or early event predicting clinical disease and is an important focus for secondary intervention trials. To improve identification of cases with increased AD risk, we evaluated recruitment procedures using pathological CSF concentrations of Aß42 (pAß) and APOEɛ4 as risk markers in a multi-center study in Norway. In total, 490 subjects aged 40-80 y were included after response to advertisements and media coverage or memory clinics referrals. Controls (n = 164) were classified as normal controls without first-degree relatives with dementia (NC), normal controls with first-degree relatives with dementia (NCFD), or controls scoring below norms on cognitive screening. Patients (n = 301) were classified as subjective cognitive decline or mild cognitive impairment. Subjects underwent a clinical and cognitive examination and MRI according to standardized protocols. Core biomarkers in CSF from 411 and APOE genotype from 445 subjects were obtained. Cases (both self-referrals (n = 180) and memory clinics referrals (n = 87)) had increased fractions of pAß and APOEɛ4 frequency compared to NC. Also, NCFD had higher APOEɛ4 frequencies without increased fraction of pAß compared to NC, and cases recruited from memory clinics had higher fractions of pAß and APOEɛ4 frequency than self-referred. This study shows that memory clinic referrals are pAß enriched, whereas self-referred and NCFD cases more frequently are pAß negative but at risk (APOEɛ4 positive), suitable for primary intervention.