Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer's disease.

Background: The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer's disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking. Methods: BioFINDER-2 participants with memory impairment, abnormal amyloid-ß status and tau-PET were included. Forty-one EOAD individuals aged ≤65 years and, as comparison, late-onset AD (LOAD, ≥70 years, n=154) and Aß-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results: AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found. Conclusions: We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables.

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study.

OBJECTIVE: We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS: Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS: Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION: Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024.

Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment.

Importance: An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression. Objective: To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia. Design, Setting, and Participants: This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-ß (Aß) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study. Exposures: Tau PET, Aß PET, and MRI. Main Outcomes and Measures: Positive results on tau PET (temporal meta-region of interest), Aß PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics. Results: In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aß PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia. Conclusions and Relevance: In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.

Structural and functional connectivity associations with anterior cingulate sulcal variability.

Sulcation of the anterior cingulate may be defined by presence of a paracingulate sulcus, a tertiary sulcus developing during the third gestational trimester with implications on cognitive function and disease. In this cross-sectional study we examine task-free resting state functional connectivity and diffusion-weighted tract segmentation data from a cohort of healthy adults (< 60-year-old, n = 129), exploring the impact of ipsilateral paracingulate sulcal presence on structural and functional connectivity. Presence of a left paracingulate sulcus was associated with reduced fractional anisotropy in the left cingulum bundle and the left peri-genual and dorsal bundle segments, suggesting reduced structural organisational coherence in these tracts. This association was not observed in the offsite temporal cingulum bundle segment. Left paracingulate sulcal presence was associated with increased left peri-genual radial diffusivity and tract volume possibly suggesting increased U-fibre density in this region. Greater network dispersity was identified in individuals with an absent left paracingulate sulcus by presence of a significant, predominantly intraregional, frontal component of resting state functional connectivity which was not present in individuals with a present left paracingulate sulcus. Seed-based functional connectivity in pre-defined networks was not associated with paracingulate sulcal presence. These results identify a novel association between sulcation and structural connectivity in a healthy adult population with implications for conditions where this variation is of interest. Presence of a left paracingulate sulcus appears to alter local structural and functional connectivity, possibly as a result of the presence of a local network reliant on short association fibres.

A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings.

Memory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease (AD) patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± SD age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (CU; n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (SCD; n = 342), mild cognitive impairment (MCI; n = 118), or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid AD biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5), as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test if baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and MCI conversion rates of CU and SCD participants. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy first affected the medial temporal lobes, followed by further temporal and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological AD biomarker levels, APOE ε4 carriership, and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive AD biomarkers and was associated with more generalised cognitive impairment. Limbic-predominant atrophy, in all and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of MCI conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, both on the subject and group level, were excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for AD in applied settings. The implementation of atrophy subtype- and stage-specific end-points may increase the statistical power of pharmacological trials targeting early AD.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions. METHODS: A cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: (1) clinical data only, including demographics, cognitive tests and APOE ε4 status, (2) clinical data plus hippocampal volume, (3) clinical data plus all regional MRI gray matter volumes (N = 68) extracted using FreeSurfer software, (4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. A double cross-validation scheme, with five test folds and for each of those ten validation folds, was used. External evaluation was performed on part of the ADNI dataset, including 108 patients. Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant. RESULTS: In the BioFINDER cohort, 109 patients (33%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC) = 0.85 and four-year cognitive decline was R2 = 0.14. The performance was improved for both outcomes when adding hippocampal volume (AUC = 0.86, R2 = 0.16). Adding FreeSurfer brain regions improved prediction of four-year cognitive decline but not progression to AD (AUC = 0.83, R2 = 0.17), while the DL model worsened the performance for both outcomes (AUC = 0.84, R2 = 0.08). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. In the external evaluation cohort from ADNI, 23 patients (21%) progressed to AD dementia. The results for predicted progression to AD dementia were similar to the results for the BioFINDER test data, while the performance for the cognitive decline was deteriorated. CONCLUSIONS: The DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.

Diffusion weighted magnetic resonance spectroscopy revealed neuronal specific microstructural alterations in Alzheimer's disease.

In Alzheimer's disease, reconfiguration and deterioration of tissue microstructure occur before substantial degeneration become evident. We explored the diffusion properties of both water, a ubiquitous marker measured by diffusion MRI, and N-acetyl-aspartate, a neuronal metabolite probed by diffusion-weighted magnetic resonance spectroscopy, for investigating cortical microstructural changes downstream of Alzheimer's disease pathology. To this aim, 50 participants from the Swedish BioFINDER-2 study were scanned on both 7 and 3 T MRI systems. We found that in cognitively impaired participants with evidence of both abnormal amyloid-beta (CSF amyloid-beta42/40) and tau accumulation (tau-PET), the N-acetyl-aspartate diffusion rate was significantly lower than in cognitively unimpaired participants (P < 0.05). This supports the hypothesis that intraneuronal tau accumulation hinders diffusion in the neuronal cytosol. Conversely, water diffusivity was higher in cognitively impaired participants (P < 0.001) and was positively associated with the concentration of myo-inositol, a preferentially astrocytic metabolite (P < 0.001), suggesting that water diffusion is sensitive to alterations in the extracellular space and in glia. In conclusion, measuring the diffusion properties of both water and N-acetyl-aspartate provides rich information on the cortical microstructure in Alzheimer's disease, and can be used to develop new sensitive and specific markers to microstructural changes occurring during the disease course.

Structural and functional connectivity associations with anterior cingulate sulcal variability.

Background: Sulcation of the anterior cingulate may be defined by presence of a paracingulate sulcus, a tertiary sulcus developing during the third gestational trimester with implications on cognitive function and disease. Methods: In this retrospective analysis we examine task-free resting state functional connectivity and diffusion-weighted tract segmentation data from a cohort of healthy adults (< 60-year-old, n = 129), exploring the impact of ipsilateral paracingulate sulcal presence on structural and functional connectivity. Results: Presence of a left paracingulate sulcus was associated with reduced fractional anisotropy in the left cingulum (P = 0.02) bundle and the peri-genual (P = 0.002) and dorsal (P = 0.03) but not the temporal cingulum bundle segments. Left paracingulate sulcal presence was associated with increased left peri-genual radial diffusivity (P = 0.003) and tract volume (P = 0.012). A significant, predominantly intraregional frontal component of altered resting state functional connectivity was identified in individuals possessing a left PCS (P = 0.01). Seed-based functional connectivity in pre-defined networks was not associated with paracingulate sulcal presence. Conclusion: These results identify a novel association between neurodevelopmentally derived sulcation and altered structural connectivity in a healthy adult population with implications for conditions where this variation is of interest. Furthermore, they provide evidence of a link between the structural and functional connectivity of the brain in the presence of a paracingulate sulcus which may be mediated by a highly connected local functional network reliant on short association fibres.

Plasma Biomarker Strategy for Selecting Patients With Alzheimer Disease for Antiamyloid Immunotherapies.

Importance: Antiamyloid immunotherapies against Alzheimer disease (AD) are emerging. Scalable, cost-effective tools will be needed to identify amyloid ß (Aß)-positive patients without an advanced stage of tau pathology who are most likely to benefit from these therapies. Blood-based biomarkers might reduce the need to use cerebrospinal fluid (CSF) or positron emission tomography (PET) for this. Objective: To evaluate plasma biomarkers for identifying Aß positivity and stage of tau accumulation. Design, Setting, and Participants: The cohort study (BioFINDER-2) was a prospective memory-clinic and population-based study. Participants with cognitive concerns were recruited from 2017 to 2022 and divided into a training set (80% of the data) and test set (20%). Exposure: Baseline values for plasma phosphorylated tau 181 (p-tau181), p-tau217, p-tau231, N-terminal tau, glial fibrillary acidic protein, and neurofilament light chain. Main Outcomes and Measures: Performance to classify participants by Aß status (defined by Aß-PET or CSF Aß42/40) and tau status (tau PET). Number of hypothetically saved PET scans in a plasma biomarker-guided workflow. Results: Of a total 912 participants, there were 499 males (54.7%) and 413 females (45.3%), and the mean (SD) age was 71.1 (8.49) years. Among the biomarkers, plasma p-tau217 was most strongly associated with Aß positivity (test-set area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI, 0.90-0.97). A 2-cut-point procedure was evaluated, where only participants with ambiguous plasma p-tau217 values (17.1% of the participants in the test set) underwent CSF or PET to assign definitive Aß status. This procedure had an overall sensitivity of 0.94 (95% CI, 0.90-0.98) and a specificity of 0.86 (95% CI, 0.77-0.95). Next, plasma biomarkers were used to differentiate low-intermediate vs high tau-PET load among Aß-positive participants. Plasma p-tau217 again performed best, with the test AUC = 0.92 (95% CI, 0.86-0.97), without significant improvement when adding any of the other plasma biomarkers. At a false-negative rate less than 10%, the use of plasma p-tau217 could avoid 56.9% of tau-PET scans needed to identify high tau PET among Aß-positive participants. The results were validated in an independent cohort (n = 118). Conclusions and Relevance: This study found that algorithms using plasma p-tau217 can accurately identify most Aß-positive individuals, including those likely to have a high tau load who would require confirmatory tau-PET imaging. Plasma p-tau217 measurements may substantially reduce the number of invasive and costly confirmatory tests required to identify individuals who would likely benefit from antiamyloid therapies.

Combined Connectomics, MAPT Gene Expression, and Amyloid Deposition to Explain Regional Tau Deposition in Alzheimer Disease.

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, 18 F-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.

Interactions between vascular burden and amyloid-ß pathology on trajectories of tau accumulation.

Cerebrovascular pathology often co-exists with Alzheimer's disease pathology and can contribute to Alzheimer's disease-related clinical progression. However, the degree to which vascular burden contributes to Alzheimer's disease pathological progression is still unclear. This study aimed to investigate interactions between vascular burden and amyloid-ß pathology on both baseline tau tangle load and longitudinal tau accumulation. We included 1229 participants from the Swedish BioFINDER-2 Study, including cognitively unimpaired and impaired participants with and without biomarker-confirmed amyloid-ß pathology. All underwent baseline tau-PET (18F-RO948), and a subset (n = 677) underwent longitudinal tau-PET after 2.5 ± 1.0 years. Tau-PET uptake was computed for a temporal meta-region-of-interest. We focused on four main vascular imaging features and risk factors: microbleeds; white matter lesion volume; stroke-related events (infarcts, lacunes and haemorrhages); and the Framingham Heart Study Cardiovascular Disease risk score. To validate our in vivo results, we examined 1610 autopsy cases from an Arizona-based neuropathology cohort on three main vascular pathological features: cerebral amyloid angiopathy; white matter rarefaction; and infarcts. For the in vivo cohort, primary analyses included age-, sex- and APOE ɛ4-corrected linear mixed models between tau-PET (outcome) and interactions between time, amyloid-ß and each vascular feature (predictors). For the neuropathology cohort, age-, sex- and APOE ɛ4-corrected linear models between tau tangle density (outcome) and an interaction between plaque density and each vascular feature (predictors) were performed. In cognitively unimpaired individuals, we observed a significant interaction between microbleeds and amyloid-ß pathology on greater baseline tau load (ß = 0.68, P < 0.001) and longitudinal tau accumulation (ß = 0.11, P < 0.001). For white matter lesion volume, we did not observe a significant independent interaction effect with amyloid-ß on tau after accounting for microbleeds. In cognitively unimpaired individuals, we further found that stroke-related events showed a significant negative interaction with amyloid-ß on longitudinal tau (ß = -0.08, P < 0.001). In cognitively impaired individuals, there were no significant interaction effects between cerebrovascular and amyloid-ß pathology at all. In the neuropathology dataset, the in vivo observed interaction effects between cerebral amyloid angiopathy and plaque density (ß = 0.38, P < 0.001) and between infarcts and plaque density (ß = -0.11, P = 0.005) on tau tangle density were replicated. To conclude, we demonstrated that cerebrovascular pathology-in the presence of amyloid-ß pathology-modifies tau accumulation in early stages of Alzheimer's disease. More specifically, the co-occurrence of microbleeds and amyloid-ß pathology was associated with greater accumulation of tau aggregates during early disease stages. This opens the possibility that interventions targeting microbleeds may attenuate the rate of tau accumulation in Alzheimer's disease.

Diffusion MRI tracks cortical microstructural changes during the early stages of Alzheimer's disease.

There is increased interest in developing markers reflecting microstructural changes that could serve as outcome measures in clinical trials. This is especially important after unexpected results in trials evaluating disease-modifying therapies targeting amyloid-ß (Aß), where morphological metrics from MRI showed increased volume loss despite promising clinical treatment effects. In this study, changes over time in cortical mean diffusivity, derived using diffusion tensor imaging, were investigated in a large cohort (n = 424) of non-demented participants from the Swedish BioFINDER study. Participants were stratified following the Aß/tau (AT) framework. The results revealed a widespread increase in mean diffusivity over time, including both temporal and parietal cortical regions, in Aß-positive but still tau-negative individuals. These increases were steeper in Aß-positive and tau-positive individuals and robust to the inclusion of cortical thickness in the model. A steeper increase in mean diffusivity was also associated with both changes over time in fluid markers reflecting astrocytic activity (i.e. plasma level of glial fibrillary acidic protein and CSF levels of YKL-40) and worsening of cognitive performance (all P < 0.01). By tracking cortical microstructural changes over time and possibly reflecting variations related to the astrocytic response, cortical mean diffusivity emerges as a promising marker for tracking treatments-induced microstructural changes in clinical trials.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

Background: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions. Methods: A cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: 1) clinical data only, including demographics, cognitive tests and APOE e4 status, 2) clinical data plus hippocampal volume, 3) clinical data plus all regional MRI gray matter volumes (N=68) extracted using FreeSurfer software, 4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. Models were developed on 80% of subjects (N=267) and tested on the remaining 20% (N=65). Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant. Results: In the test set, 21 patients (32.3%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC)=0.87 and four-year cognitive decline was R2=0.17. The performance was significantly improved for both outcomes when adding hippocampal volume (AUC=0.91, R2=0.26, p-values <0.05) or FreeSurfer brain regions (AUC=0.90, R2=0.27, p-values <0.05). Conversely, the DL model did not show any significant difference from the clinical data model (AUC=0.86, R2=0.13). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. Conclusions: The DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.

CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer's disease.

Aggregated insoluble tau is one of two defining features of Alzheimer's disease. Because clinical symptoms are strongly correlated with tau aggregates, drug development and clinical diagnosis need cost-effective and accessible specific fluid biomarkers of tau aggregates; however, recent studies suggest that the fluid biomarkers currently available cannot specifically track tau aggregates. We show that the microtubule-binding region (MTBR) of tau containing the residue 243 (MTBR-tau243) is a new cerebrospinal fluid (CSF) biomarker specific for insoluble tau aggregates and compared it to multiple other phosphorylated tau measures (p-tau181, p-tau205, p-tau217 and p-tau231) in two independent cohorts (BioFINDER-2, n = 448; and Knight Alzheimer Disease Research Center, n = 219). MTBR-tau243 was most strongly associated with tau-positron emission tomography (PET) and cognition, whereas showing the lowest association with amyloid-PET. In combination with p-tau205, MTBR-tau243 explained most of the total variance in tau-PET burden (0.58 ≤ R2 ≤ 0.75) and the performance in predicting cognitive measures (0.34 ≤ R2 ≤ 0.48) approached that of tau-PET (0.44 ≤ R2 ≤ 0.52). MTBR-tau243 levels longitudinally increased with insoluble tau aggregates, unlike CSF p-tau species. CSF MTBR-tau243 is a specific biomarker of tau aggregate pathology, which may be utilized in interventional trials and in the diagnosis of patients. Based on these findings, we propose to revise the A/T/(N) criteria to include MTBR-tau243 as representing insoluble tau aggregates ('T').

Associations of CSF PDGFRß With Aging, Blood-Brain Barrier Damage, Neuroinflammation, and Alzheimer Disease Pathologic Changes.

BACKGROUND AND OBJECTIVES: Injured pericytes in the neurovascular unit release platelet-derived growth factor ß (PDGFRß) into the CSF. However, it is not clear how pericyte injury contributes to Alzheimer disease (AD)-related changes and blood-brain barrier (BBB) damage. We aimed to test whether CSF PDGFRß was associated with different AD-associated and age-associated pathologic changes leading to dementia. METHODS: PDGFRß was measured in the CSF of 771 participants with cognitively unimpaired (CU, n = 408), mild cognitive impairment (MCI, n = 175), and dementia (n = 188) from the Swedish BioFINDER-2 cohort. We then checked association with ß-amyloid (Aß)-PET and tau-PET standardized uptake value ratio, APOE ε4 genotype and MRI measurements of cortical thickness, white matter lesions (WMLs), and cerebral blood flow. We also analyzed the role of CSF PDGFRß in the relationship between aging, BBB dysfunction (measured by CSF/plasma albumin ratio, QAlb), and neuroinflammation (i.e., CSF levels of YKL-40 and glial fibrillary acidic protein [GFAP], preferentially expressed in reactive astrocytes). RESULTS: The cohort had a mean age of 67 years (CU = 62.8, MCI = 69.9, dementia = 70.4), and 50.1% were male (CU = 46.6%, MCI = 53.7%, dementia = 54.3%). Higher CSF PDGFRß concentrations were related to higher age (b = 19.1, ß = 0.5, 95% CI 16-22.2, p < 0.001), increased CSF neuroinflammatory markers of glial activation YKL-40 (b = 3.4, ß = 0.5, 95% CI 2.8-3.9, p < 0.001), GFAP (b = 27.4, ß = 0.4, 95% CI 20.9-33.9, p < 0.001), and worse BBB integrity measured by QAlb (b = 37.4, ß = 0.2, 95% CI 24.9-49.9, p < 0.001). Age was also associated with worse BBB integrity, and this was partly mediated by PDGFRß and neuroinflammatory markers (16%-33% of total effect). However, PDGFRß showed no associations with APOE ε4 genotype, PET imaging of Aß and tau pathology, or MRI measures of brain atrophy and WMLs (p > 0.05). DISCUSSION: In summary, pericyte damage, reflected by CSF PDGFRß, may be involved in age-related BBB disruption together with neuroinflammation, but is not related to Alzheimer-related pathologic changes.

Comparison of Group-Level and Individualized Brain Regions for Measuring Change in Longitudinal Tau Positron Emission Tomography in Alzheimer Disease.

Importance: Longitudinal tau positron emission tomography (PET) is a relevant outcome in clinical trials evaluating disease-modifying therapies in Alzheimer disease (AD). A key unanswered question is whether the use of participant-specific (individualized) regions of interest (ROIs) is superior to conventional approaches where the same ROI (group-level) is used for each participant. Objective: To compare group- and participant-level ROIs in participants at different stages of the AD clinical continuum in terms of annual percentage change in tau-PET standardized uptake value ratio (SUVR) and sample size requirements. Design, Setting, and Participants: This was a longitudinal cohort study with consecutive participant enrollment between September 18, 2017, and November 15, 2021. Included in the analysis were participants with mild cognitive impairment and AD dementia from the prospective and longitudinal Swedish Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably 2 (BioFINDER-2) study; in addition, a validation sample (the AVID 05e, Expedition-3, Alzheimer's Disease Neuroimaging Initiative [ADNI], and BioFINDER-1 study cohorts) was also included. Exposures: Tau PET (BioFINDER-2, [18F]RO948; validation sample, [18F]flortaucipir), 7 group-level (5 data-driven stages, meta-temporal, whole brain), and 5 individualized ROIs. Main Outcomes and Measures: Annual percentage change in tau-PET SUVR across ROIs. Sample size requirements in simulated clinical trials using tau PET as an outcome were also calculated. Results: A total of 215 participants (mean [SD] age, 71.4 (7.5) years; 111 male [51.6%]) from the BioFINDER-2 study were included in this analysis: 97 amyloid-ß (Aß)-positive cognitively unimpaired (CU) individuals, 77 with Aß-positive mild cognitive impairment (MCI), and 41 with AD dementia. In the validation sample were 137 Aß-positive CU participants, 144 with Aß-positive MCI, and 125 with AD dementia. Mean (SD) follow-up time was 1.8 (0.3) years. Using group-level ROIs, the largest annual percentage increase in tau-PET SUVR in Aß-positive CU individuals was seen in a composite ROI combining the entorhinal cortex, hippocampus, and amygdala (4.29%; 95% CI, 3.42%-5.16%). In individuals with Aß-positive MCI, the greatest change was seen in the temporal cortical regions (5.82%; 95% CI, 4.67%-6.97%), whereas in those with AD dementia, the greatest change was seen in the parietal regions (5.22%; 95% CI, 3.95%-6.49%). Significantly higher estimates of annual percentage change were found using several of the participant-specific ROIs. Importantly, the simplest participant-specific approach, where change in tau PET was calculated in an ROI that best matched the participant's data-driven disease stage, performed best in all 3 subgroups. For the power analysis, sample size reductions for the participant-specific ROIs ranged from 15.94% (95% CI, 8.14%-23.74%) to 72.10% (95% CI, 67.10%-77.20%) compared with the best-performing group-level ROIs. Findings were replicated using [18F]flortaucipir. Conclusions and Relevance: Finding suggest that certain individualized ROIs carry an advantage over group-level ROIs for assessing longitudinal tau changes and increase the power to detect treatment effects in AD clinical trials using longitudinal tau PET as an outcome.

Age-related and amyloid-beta-independent tau deposition and its downstream effects.

Amyloid-ß (Aß) is hypothesized to facilitate the spread of tau pathology beyond the medial temporal lobe. However, there is evidence that, independently of Aß, age-related tau pathology might be present outside of the medial temporal lobe. We therefore aimed to study age-related Aß-independent tau deposition outside the medial temporal lobe in two large cohorts and to investigate potential downstream effects of this on cognition and structural measures. We included 545 cognitively unimpaired adults (40-92 years) from the BioFINDER-2 study (in vivo) and 639 (64-108 years) from the Rush Alzheimer's Disease Center cohorts (ex vivo). 18F-RO948- and 18F-flutemetamol-PET standardized uptake value ratios were calculated for regional tau and global/regional Aß in vivo. Immunohistochemistry was used to estimate Aß load and tangle density ex vivo. In vivo medial temporal lobe volumes (subiculum, cornu ammonis 1) and cortical thickness (entorhinal cortex, Brodmann area 35) were obtained using Automated Segmentation for Hippocampal Subfields packages. Thickness of early and late neocortical Alzheimer's disease regions was determined using FreeSurfer. Global cognition and episodic memory were estimated to quantify cognitive functioning. In vivo age-related tau deposition was observed in the medial temporal lobe and in frontal and parietal cortical regions, which was statistically significant when adjusting for Aß. This was also observed in individuals with low Aß load. Tau deposition was negatively associated with cortical volumes and thickness in temporal and parietal regions independently of Aß. The associations between age and cortical volume or thickness were partially mediated via tau in regions with early Alzheimer's disease pathology, i.e. early tau and/or Aß pathology (subiculum/Brodmann area 35/precuneus/posterior cingulate). Finally, the associations between age and cognition were partially mediated via tau in Brodmann area 35, even when including Aß-PET as covariate. Results were validated in the ex vivo cohort showing age-related and Aß-independent increases in tau aggregates in and outside the medial temporal lobe. Ex vivo age-cognition associations were mediated by medial and inferior temporal tau tangle density, while correcting for Aß density. Taken together, our study provides support for primary age-related tauopathy even outside the medial temporal lobe in vivo and ex vivo, with downstream effects on structure and cognition. These results have implications for our understanding of the spreading of tau outside the medial temporal lobe, also in the context of Alzheimer's disease. Moreover, this study suggests the potential utility of tau-targeting treatments in primary age-related tauopathy, likely already in preclinical stages in individuals with low Aß pathology.

Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis.

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-ß-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stßinteraction = -0.062, P = 0.032), higher education level (Stßinteraction = -0.072, P = 0.011) and higher intracranial volume (Stßinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

Discriminative accuracy of the A/T/N scheme to identify cognitive impairment due to Alzheimer's disease.

Introduction: The optimal combination of amyloid-ß/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear. Methods: We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non-AD neurodegenerative diseases in the TRIAD, BioFINDER-1 and BioFINDER-2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC). Results: For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90-0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non-AD neurodegenerative diseases (AUC range; A biomarker: 0.84-1; T biomarker: 0.83-1). Discussion: In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy.