Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology.

INTRODUCTION: Assessing the potential sources of bias and variability of the Centiloid (CL) scale is fundamental for its appropriate clinical application. METHODS: We included 533 participants from AMYloid imaging to Prevent Alzheimer's Disease (AMYPAD DPMS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts. Thirty-two CL pipelines were created using different combinations of reference region (RR), RR and target types, and quantification spaces. Generalized estimating equations stratified by amyloid positivity were used to assess the impact of the quantification pipeline, radiotracer, age, brain atrophy, and harmonization status on CL. RESULTS: RR selection and RR type impact CL the most, particularly in amyloid-negative individuals. The standard CL pipeline with the whole cerebellum as RR is robust against brain atrophy and differences in image resolution, with 95% confidence intervals below ± 3.95 CL for amyloid beta positivity cutoffs (CL < 24). DISCUSSION: The standard CL pipeline is recommended for most scenarios. Confidence intervals should be considered when operationalizing CL cutoffs in clinical and research settings. HIGHLIGHTS: We developed a framework for evaluating Centiloid (CL) variability to different factors. Reference region selection and delineation had the highest impact on CL values. Whole cerebellum (WCB) and whole cerebellum plus brainstem (WCB+BSTM) as reference regions yielded consistent results across tracers. The standard CL pipeline is robust against atrophy and image resolution variation. Estimated within- and between-pipeline variability (95% confidence interval) in absolute CL units.

Association of glial fibrillary acid protein, Alzheimer's disease pathology and cognitive decline.

Increasing evidence shows that neuroinflammation is a possible modulator of tau spread effects on cognitive impairment in Alzheimer's disease. In this context, plasma levels of the glial fibrillary acidic protein (GFAP) have been suggested to have a robust association with Alzheimer's disease pathophysiology. This study aims to assess the correlation between plasma GFAP and Alzheimer's disease pathology, and their synergistic effect on cognitive performance and decline. A cohort of 122 memory clinic subjects with amyloid and tau positron emission tomography, MRI scans, plasma GFAP, and Mini-Mental State Examination (MMSE) was included in the study. A subsample of 94 subjects had a follow-up MMSE score at least one year after baseline. Regional and voxel-based correlations between Alzheimer's disease biomarkers and plasma GFAP were assessed. Mediation analyses were performed to evaluate the effects of plasma GFAP on the association between amyloid and tau PET, and tau PET and cognitive impairment and decline. GFAP was associated with increased tau PET ligand uptake in the lateral temporal and inferior temporal lobes in a strong left-sided pattern independently of age, gender, education, amyloid, and APOE status (ß=0.001, p < 0.01). The annual rate of MMSE change was significantly and independently correlated with both GFAP (ß=0.006, p < 0.01) and global tau SUVR (ß=4.33, p < 0.01), but not with amyloid burden. Partial mediation effects of GFAP were found on the association between amyloid and tau pathology (13.7%), and between tau pathology and cognitive decline (17.4%), but not on global cognition at baseline. Neuroinflammation measured by circulating GFAP is independently associated with tau Alzheimer's disease pathology and with cognitive decline, suggesting neuroinflammation as a potential target for future disease-modifying trials targeting tau pathology. Peretti et al. show that a circulatory marker of neuroinflammation-glial fibrillary acidic protein-is associated with tau pathology in lateral temporal and frontal regions in patients with Alzheimer's disease, independent of amyloid load. Neuroinflammation appears to modulate the association between amyloid and tau biomarkers.

Sharing brain imaging data in the Open Science era: how and why?

The sharing of human neuroimaging data has great potential to accelerate the development of imaging biomarkers in neurological and psychiatric disorders; however, major obstacles remain in terms of how and why to share data in the Open Science context. In this Health Policy by the European Cluster for Imaging Biomarkers, we outline the current main opportunities and challenges based on the results of an online survey disseminated among senior scientists in the field. Although the scientific community fully recognises the importance of data sharing, technical, legal, and motivational aspects often prevent active adoption. Therefore, we provide practical advice on how to overcome the technical barriers. We also call for a harmonised application of the General Data Protection Regulation across EU countries. Finally, we suggest the development of a system that makes data count by recognising the generation and sharing of data as a highly valuable contribution to the community.

Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aß burden and decline in daily living activities in this population. Moreover, Aß-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS: Participants included 765 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.

A deep learning model for generating [18F]FDG PET Images from early-phase [18F]Florbetapir and [18F]Flutemetamol PET images.

INTRODUCTION: Amyloid-ß (Aß) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([18F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunction and disease progression and is complementary for AD diagnosis. Dual-scan acquisitions of amyloid PET allows the possibility to use early-phase amyloid-PET as a biomarker for neurodegeneration, proven to have a good correlation to [18F]FDG PET. The aim of this study was to evaluate the added value of synthesizing the later from the former through deep learning (DL), aiming at reducing the number of PET scans, radiation dose, and discomfort to patients. METHODS: A total of 166 subjects including cognitively unimpaired individuals (N = 72), subjects with mild cognitive impairment (N = 73) and dementia (N = 21) were included in this study. All underwent T1-weighted MRI, dual-phase amyloid PET scans using either Fluorine-18 Florbetapir ([18F]FBP) or Fluorine-18 Flutemetamol ([18F]FMM), and an [18F]FDG PET scan. Two transformer-based DL models called SwinUNETR were trained separately to synthesize the [18F]FDG from early phase [18F]FBP and [18F]FMM (eFBP/eFMM). A clinical similarity score (1: no similarity to 3: similar) was assessed to compare the imaging information obtained by synthesized [18F]FDG as well as eFBP/eFMM to actual [18F]FDG. Quantitative evaluations include region wise correlation and single-subject voxel-wise analyses in comparison with a reference [18F]FDG PET healthy control database. Dice coefficients were calculated to quantify the whole-brain spatial overlap between hypometabolic ([18F]FDG PET) and hypoperfused (eFBP/eFMM) binary maps at the single-subject level as well as between [18F]FDG PET and synthetic [18F]FDG PET hypometabolic binary maps. RESULTS: The clinical evaluation showed that, in comparison to eFBP/eFMM (average of clinical similarity score (CSS) = 1.53), the synthetic [18F]FDG images are quite similar to the actual [18F]FDG images (average of CSS = 2.7) in terms of preserving clinically relevant uptake patterns. The single-subject voxel-wise analyses showed that at the group level, the Dice scores improved by around 13% and 5% when using the DL approach for eFBP and eFMM, respectively. The correlation analysis results indicated a relatively strong correlation between eFBP/eFMM and [18F]FDG (eFBP: slope = 0.77, R2 = 0.61, P-value < 0.0001); eFMM: slope = 0.77, R2 = 0.61, P-value < 0.0001). This correlation improved for synthetic [18F]FDG (synthetic [18F]FDG generated from eFBP (slope = 1.00, R2 = 0.68, P-value < 0.0001), eFMM (slope = 0.93, R2 = 0.72, P-value < 0.0001)). CONCLUSION: We proposed a DL model for generating the [18F]FDG from eFBP/eFMM PET images. This method may be used as an alternative for multiple radiotracer scanning in research and clinical settings allowing to adopt the currently validated [18F]FDG PET normal reference databases for data analysis.

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.

Value-based motivational strategies combined with technology to encourage a lifestyle that helps to prevent dementia.

Lifestyles aimed at reducing dementia risk typically combine physical and cognitive training, nutritional adaptations, and, potentially, an augmentation in social interactions. Interventions at the population level are essential but should be complemented by individual efforts. For efficacy, lasting changes to an individual's lifestyle are needed, necessitating robust motivation and volition. Acting in accordance with one's values is assumed to be rewarding, leading to improved motivation and volition, and produces stable behaviour-outcome relationships. To this end, future preventive endeavours might first evaluate an individual's extant lifestyle, preferences, and values, including considerations of age-related changes to ensure these values remain a motivational source. Digital technology can support lifestyle goals and be targeted to support an individual's values. A digital platform could implement situation-specific, sensing-based feedback to alert users to a target situation (eg, opportunity for exercise) coupled with (smartphone-based) feedback on the extent of accomplished behavioural change to support individually set goals and facilitate their adjustment depending on whether these goals are achieved. This use of the motivational impetus of values, coupled with interpersonal techniques, such as motivational interviewing and SMART goal setting, in combination with sensor technology and just-in-time adaptive interventions, is assumed to hold high potential for dementia prevention.

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure.

OBJECTIVE: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. METHODS: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid ß1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. INTERPRETATION: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.

The Taxonomy of Subjective Cognitive Decline: Proposal and First Clinical Evidence from the Geneva Memory Clinic Cohort.

INTRODUCTION: Subjective cognitive decline (SCD) is characterized by subjective cognitive concerns without objective cognitive impairment and is considered a risk factor for cognitive decline and dementia. However, most SCD patients will not develop neurodegenerative disorders, yet they may suffer from minor psychiatric, neurological, or somatic comorbidities. The aim of the present study was to provide a taxonomy of the heterogeneous SCD entity and to conduct a preliminary validation using data from a memory clinic sample. METHODS: Participants were fifty-five SCD individuals consecutively recruited at the Geneva Memory Center. Based on clinical reports, they were classified into three clinically pre-defined subgroups: (i) those with psychological or psychiatric comorbidities (Psy), (ii) those with somatic comorbidities (SomCom), (iii) and those with no apparent cause (NAC). Baseline demographics, clinical, cognitive, and biomarker differences among the SCD subgroups were assessed. Longitudinal cognitive changes (average 3 years follow-up) were modeled using a linear mixed model. RESULTS: Out of the 55 SCD cases, 16 were SomCom, 18 Psy, and 21 NAC. 47% were female, mean age was 71 years. We observed higher frequency of APOE ε4 carriers in NAC (53%) compared to SomCom (14%) and Psy (0%, p = 0.023) and lower level of plasma Aß42 in NAC (6.8 ± 1.0) compared to SomCom (8.4 ± 1.1; p = 0.031). SomCom subjects were older (74 years) than Psy (67 years, p = 0.011), and had greater medial temporal lobe atrophy (1.0 ± 1.0) than Psy (0.2 ± 0.6) and NAC (0.4 ± 0.5, p = 0.005). SomCom has worse episodic memory performances (14.5 ± 3.5) than Psy (15.8 ± 0.4) and NAC (15.8 ± 0.7, p = 0.032). We observed a slightly steeper, yet not statistically significant, cognitive decline in NAC (ß = -0.48) compared to Psy (ß = -0.28) and SomCom (ß = -0.24). CONCLUSIONS: NAC features a higher proportion of APOE ε4 carriers, lower plasma Aß42 and a trend towards steeper cognitive decline than SomCom and Psy. Taken together, these findings suggest that NACs are at higher risk of cognitive decline due to AD. The proposed clinical taxonomy might be implemented in clinical practice to identify SCD at higher risk. However, such taxonomy should be tested on an independent cohort with a larger sample size.

Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients.

BACKGROUND: Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI). METHODS: Plasma (Aß42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity. RESULTS: Cognitive decline was significantly predicted in MCI by baseline plasma NfL (ß=-0.55), GFAP (ß=-0.36), hippocampal volume (ß = 0.44), centiloid (ß=-0.38), and tau-SUVR (ß=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity. CONCLUSIONS: Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

Alterations in gamma frequency oscillations correlate with cortical tau deposition in Alzheimer's disease.

We assessed the relationship of gamma oscillations with tau deposition in Alzheimer's disease (AD) and other cognitive diseases, as both are altered during the disease course and relate to neurodegeneration. We retrospectively analyzed data from 7 AD, tau positive patients and 9 tau negative patients, who underwent cerebral amyloid PET and tau PET, and EEG within 12 months. Relative gamma power was higher in tau positive (AD) patients than in tau negative patients (p < .05). In tau positive AD patients, tau burden was associated with a linear increase in gamma power (p < .05), while no association was present in the tau negative group nor with amyloid-ß burden in either group. Thus, increase in the gamma power might represent a novel biomarker for tau driven neurodegeneration.

The treatment of behavioural and psychological symptoms in dementia: pragmatic recommendations.

Behavioural and psychological symptoms of dementia (BPSD) are a clinical challenge for the lack of a sound taxonomy, frequent presentation with comorbid BPSD, lack of specific pharmacologic interventions, poor base of methodologically sound evidence with randomized clinical trials, contamination from the treatment of behavioural disturbances of young and adult psychiatric conditions, and small efficacy window of psychotropic drugs. We present here a treatment workflow based on a concept-driven literature review based on the notions that (i) the aetiology of BPSD can be mainly neurobiological (so-called 'primary' symptoms) or mainly environmental and functional ('secondary' symptoms) and that this drives treatment; (ii) the clinical efficacy of psychotropic drugs is driven by their specific profile of receptor affinity; (iii) drug treatment should follow the rules of 'start low-go slow, prescribe and revise'. This article argues in support of the distinction between primary and secondary BPSD, as well as their characteristics, which until now have been just sketchily described in the literature. It also offers comprehensive and pragmatic clinician-oriented recommendations for the treatment of BPSD.

Neuroimaging-guided diagnosis of possible FTLD-FUS pathology: a case report.

BACKGROUND: This case report presents a patient with progressive memory loss and choreiform movements. CASE PRESENTATION: Neuropsychological tests indicated multi-domain amnestic mild cognitive impairment (aMCI), and neurological examination revealed asymmetrical involuntary hyperkinetic movements. Imaging studies showed severe left-sided atrophy and hypometabolism in the left frontal and temporoparietal cortex. [18F]Flortaucipir PET exhibited moderately increased tracer uptake in hypometabolic areas. The diagnosis initially considered Alzheimer's disease (AD), frontotemporal degeneration (FTD), and corticobasal degeneration (CBD), cerebral hemiatrophy syndrome, but imaging and cerebrospinal fluid analysis excluded AD and suggested fused-in-sarcoma-associated FTD (FTLD-FUS), a subtype of the behavioural variant of FTD. CONCLUSIONS: Our case highlights that despite the lack of specific FUS biomarkers the combination of clinical features and neuroimaging biomarkers can guide choosing the most likely differential diagnosis in a complex neurological case. Imaging in particular allowed an accurate measure of the topography and severity of neurodegeneration and the exclusion of AD-related pathology.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study.

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes.

OBJECTIVES: Mild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, including brain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up. METHODS: We included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data. RESULTS: The algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline. INTERPRETATION: aMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.

Predictors of Nursing Home Placement in a Cohort of European People with Alzheimer's Disease and Other Dementia Cases Enrolled in SCU-B or Non SCU-B Centers: The RECage Study.

Background: Nursing home placement (NHP) can be the final step of patients with Alzheimer's disease. Objective: We aimed to identify NHP predictors among 508 people with dementia with a 3-year follow-up. Methods: We analyzed data from the international observational RECage study, involving 508 people with especially Alzheimer's disease and comparing a cohort enrolled by five centers with a Special Care Unit for BPSD (behavioral and psychological symptoms of dementia) and another one enrolled by six centers lacking this facility. The tertiary objective of the study was to assess the possible role of the SCU-B in delaying NHP. We assessed the relationship of the baseline characteristics with NHP by means of univariate analysis followed by Cox's multivariate model. Results: Patients' mean age was 78.1 years, 54.9% were women. Diagnosis mean age was 75.4 (±8.32) years; the main diagnosis was Alzheimer's disease (296; 58.4%). During follow-up, 96 (18.9%) patients died and 153 (30.1%) were institutionalized without a statistically significant difference between the two cohorts (p = 0.9626). The mean NHP time was 902 (95% CI: 870-934). The multivariable analysis without death as a competing risk retained four independent predictors of NHP: age increase (hazard ratio (HR) = 1.023, 95% CI: 1.000-1.046), patient education level increase (HR = 1.062, 95% CI: 1.024-1.101), Neuropsychiatric Inventory total increase (HR = 1.018; 95% CI: 1.011-1.026), and total Mini-Mental State Examination as a favorable factor (HR = 0.948, 95% CI: 0.925-0.971). Gender (females versus males: HR = 1.265, 95% CI: 0.899-1.781) was included in the final Cox's model for adjusting the estimates for. Conclusions: Our data partially agree with the predictors of NHP in literature including the effect of high education level. No caregivers' factors were statistically significant. Clinical trial registration: NCT03507504.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings.

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aß42/Aß40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Low-Dose Radiation Therapy Impacts Microglial Inflammatory Response without Modulating Amyloid Load in Female TgF344-AD Rats.

Background: Low-dose radiation therapy (LD-RT) has demonstrated in preclinical and clinical studies interesting properties in the perspective of targeting Alzheimer's disease (AD), including anti-amyloid and anti-inflammatory effects. Nevertheless, studies were highly heterogenous with respect to total doses, fractionation protocols, sex, age at the time of treatment and delay post treatment. Recently, we demonstrated that LD-RT reduced amyloid peptides and inflammatory markers in 9-month-old TgF344-AD (TgAD) males. Objective: As multiple studies demonstrated a sex effect in AD, we wanted to validate that LD-RT benefits are also observed in TgAD females analyzed at the same age. Methods: Females were bilaterally treated with 2 Gy×5 daily fractions, 2 Gy×5 weekly fractions, or 10 fractions of 1 Gy delivered twice a week. The effect of each treatment on amyloid load and inflammation was evaluated using immunohistology and biochemistry. Results: A daily treatment did not affect amyloid and reduced only microglial-mediated inflammation markers, the opposite of the results obtained in our previous male study. Moreover, altered fractionations (2 Gy×5 weekly fractions or 10 fractions of 1 Gy delivered twice a week) did not influence the amyloid load or neuroinflammatory response in females. Conclusions: A daily treatment consequently appears to be the most efficient for AD. This study also shows that the anti-amyloid and anti-inflammatory response to LD-RT are, at least partly, two distinct mechanisms. It also emphasizes the necessity to assess the sex impact when evaluating responses in ongoing pilot clinical trials testing LD-RT against AD.

Cognitive, psychological, and physiological effects of a web-based mindfulness intervention in older adults during the COVID-19 pandemic: an open study.

BACKGROUND: The development of effective strategies to maintain good mental health of older adults is a public health priority. Mindfulness-based interventions have the potential to improve psychological well-being and cognitive functions of older adults, but little is known about the effect of such interventions when delivered through internet. During the COVID-19 pandemic we evaluated short- and long-term cognitive, psychological, and physiological effects of a mindfulness-based intervention (MBI) delivered via web-based videoconference in healthy older adults. METHODS: Fifty older adults participated in an 8-week MBI, which comprised structured 2-h weekly group sessions. A comprehensive evaluation encompassing cognitive (verbal memory, attention and processing speed, executive functions) and psychological assessments (depression and anxiety symptoms, mindfulness, worries, emotion regulation strategies, well-being, interoceptive awareness and sleep) was conducted. Additionally, electroencephalography (EEG) data were recorded before and after the MBI and at the 6-month follow-up (T6). Data were analyzed using an intention-to-treat approach, using linear mixed models adjusted for age. The effect size for time was computed as omega squared. RESULTS: We observed significant improvements from pre-MBI to post-MBI and at the T6 across several measures. These improvements were notable in the areas of verbal memory (California Verbal Learning Test, p ≤ .007), attention and executive functions (Trail Making Test A and BA, p < .050), interoceptive awareness (Multidimensional Assessment of Interoceptive Awareness, p = .0002 for self-regulation and p < .05 for noticing, body listening, and trusting dimensions), and rumination (Heidelberg Form for Emotion Regulation Strategies, p = .018). These changes were associated with low to medium effect size. Moreover, we observed significant changes in EEG patterns, with a decrease in alpha1 (p = .004) and an increase in alpha2 (p < .0001) from pre-MBI to T6. Notably, improvements in TMTBA and rumination were correlated with the decrease in alpha1 (p < .050), while improvements in TMTA were linked to the increase in alpha2 (p = .025). CONCLUSIONS: The results of our study show that a web-based MBI in older adults leads to improvements in cognitive and psychological measures, with associated modulations in specific brain rhythms. While these findings are promising, further controlled studies are required to validate these preliminary results. TRIAL REGISTRATION: The trial has been registered with the United States National Library of Medicine at the National Institutes of Health Registry of Clinical Trials under the code NCT05941143 on July 12, 2023.