O'Brien, John Tiernan

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Abstract Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia, pathologically defined by the presence of Lewy bodies. Peripheral and central inflammation are increasingly recognized in DLB in clinical, post-mortem and animal studies. Finding clinically relevant biomarkers of inflammation in DLB will support the identification of novel pathways for disease-modifying therapies or use in clinical trials of immunomodulatory agents. Whilst there are cross-sectional studies of inflammation markers in DLB, there is limited evidence on the association between these markers and cognitive decline over time. Twenty participants with DLB underwent blood sampling for serum inflammatory markers, paired with PET imaging of the translocator protein (TSPO) and up to 4 years of longitudinal cognitive testing. Thirty participants with Alzheimer’s disease—comprising both Alzheimer’s dementia and/or mild cognitive impairment with biomarker evidence of amyloid pathology (AD/MCI+)—and 28 controls were also recruited for group comparisons. Data from 42 baseline cytokine immunoassays and TSPO PET were used as predictors of longitudinal cognitive scores in linear mixed-effects models. Partial least squares regression was used to test the association between peripheral and central inflammation. Using peripheral inflammatory markers as single predictors, we identified 14 associated with either a slower or faster rate of cognitive decline in DLB, whilst no single marker was predictive of decline in AD/MCI+. As many inflammatory markers were highly correlated, we used principal component analysis to identify a cytokine component associated with reduced cognitive decline in both DLB and AD/MCI+, that overlapped with the single markers identified in the previous analysis. A separate component was associated with cognitive decline in AD/MCI+ or DLB with Alzheimer’s dementia co-pathology (ascertained by amyloid PET). Widespread TSPO binding was associated with reduced cognitive decline in DLB, whilst a fronto-temporal pattern was associated with more rapid cognitive decline in both DLB and AD/MCI+. There were associations between peripheral cytokines and TSPO PET in AD/MCI+, but these were not significant in DLB. Overall, peripheral and central inflammation predicted cognitive decline in DLB. Specific patterns associated with both faster and slower rates of decline were identified. These profiles had both overlapping and contrasting associations when compared to AD/MCI+. Collectively, these data add to a body of evidence suggesting clinically relevant levels of inflammation in DLB. Future studies in larger, multi-site cohorts with multiple biomarker sampling points are required to understand the impact and dynamics of inflammation across all stages of the disease.

Abstract Dementia is associated with altered resting-state connectivity, measures of which could aid in its early detection and monitoring. High-density diffuse optical tomography (HD-DOT) is well suited to detect these alterations at scale due to its numerous practical advantages, but it has not yet been applied to dementia. In this study, we investigated resting-state functional connectivity across the prefrontal cortex in individuals with mild cognitive impairment (MCI, n = 22), Alzheimer’s disease (AD, n = 21), and in healthy controls (n = 22). A graph theoretical approach was taken to characterise both global and local patterns of prefrontal connectivity over a 5-minute resting period. We found that individuals with MCI exhibited denser and stronger networks with shorter path lengths, which normalised in AD, accompanied by a redistribution of network hubs that were less stable. These results perhaps reflect the recruitment of additional connections in the early stages of pathology to maintain short-term network stability, which is ultimately associated with less efficient and more fragmented network organisation in later stages. Following the demonstration of HD-DOT’s capacity to detect differences between healthy ageing and AD-type cognitive impairment, this work opens up new possibilities for the use of optical imaging in the study of this clinical population and HD-DOT’s potential for scalable clinical use.

Abstract Background Sex, education and race/ethnicity are all associated with risk of Alzheimer's disease dementia. Here, we assess the effects of self‐reported sex, educational attainment and race/ethnicity on amyloid‐positivity, and tau‐PET‐positivity in 12,048 (7,394 cognitively unimpaired [CU], 2,177 MCI, and 2,477 dementia) individuals from 42 cohorts worldwide. Method Logistic generalized estimating equations were used to estimate frequency of amyloid‐positivity (using cohort‐specific thresholds for amyloid‐PET [84%] or CSF) and tau‐PET‐positivity (cohort‐specific thresholds of 2SD above mean temporal uptake in amyloid‐negative controls). We assessed: i) sex and APOEε4 ( N = 10,098) associations, to complement earlier findings of a higher frequency of tau‐positivity in females, ii) effects of lower/higher education ( N = 10,970; cohort‐specific median‐split), and iii) effects of race/ethnicity (non‐Hispanic White [hereafter: White], N = 4880; Asian, N = 116; Black or African‐American [hereafter: Black], N = 353; Hispanic, N = 356, only from Northern‐American cohorts). Outcomes were frequency of amyloid‐positivity in CU individuals only, and tau‐PET‐positivity in both amyloid‐positive (AB+) CU and cognitively impaired (CI, i.e. MCI and dementia) individuals. Interaction effects on the relationship between age and amyloid/tau‐positivity were assessed and only retained in the models when significant. Result Female sex was associated with an APOEε4 ‐independent increased frequency of amyloid‐positivity (β=0.51[0.22], p = 0.02) in CU and increase of tau‐positivity in both AB+CU (β=0.27[0.08]) and AB+CI (β=0.37[0.08], both p <0.01). Remarkably, tau‐positivity frequencies of female APOEε4 non‐carriers were equivalent to male APOEε4 carriers in AB+CI (Figure 1). No significant sex* APOE interactions were observed. In CU, higher education was associated with lower amyloid‐positivity frequency (β=‐0.12[0.05], p = 0.02). In contrast, among AB+CU, there was an age*education interaction effect that indicated more pronounced age effects on tau‐positivity in individuals with higher education (age*education:β interaction =0.03[0.01], p <0.01). There were no education effects in AB+CI (Figure 2). In CU, an age*race/ethnicity interaction effect was observed across all non‐White groups compared to White (Hispanic:β interaction =‐0.05[0.01], p <0.01; Black:‐0.04[0.01], p <0.01; Asian:‐0.02[0.01], p = 0.04). This suggests that the impact of age on amyloid‐positivity was less pronounced in non‐White groups. Furthermore, in AB+CI, Hispanic ethnicity was related to higher tau‐positivity frequency than White (β=0.51[0.22], p = 0.02; Figure 3). Conclusion In this multi‐center initiative comprised of clinical and community‐based cohorts, we observed that self‐reported sex, educational attainment and race/ethnicity were related to positivity‐frequencies of Alzheimer's disease pathology.

Abstract Background The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution. In typical (memory‐predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicenters. However, atypical (non‐amnestic‐predominant) AD variants with heterogeneous tau patterns provide a key opportunity to assess the universality of connectivity as a scaffold for tau progression. Method We included tau‐PET data from 320 subjects with atypical AD, characterized by highly heterogeneous tau patterns ( n = 139 posterior cortical atrophy/PCA‐AD; n = 103 logopenic variant primary progressive aphasia/lvPPA‐AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS‐AD) from 14 sites, with a subset of patients ( n = 78) having longitudinal tau‐PET data. As an independent sample, we further included regional post‐mortem tau stainings from 93 atypical AD patients from two sites ( n = 19 PCA‐AD, n = 32 lvPPA‐AD, n = 23 bvAD, n = 19 CBS‐AD). Gaussian mixture modeling was used to harmonize different tau‐PET tracers by transforming tau‐PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether 1) brain regions with stronger functional connectivity showed greater covariance in cross‐sectional and longitudinal tau‐PET and post‐mortem tau pathology, and 2) functional connectivity of tau‐PET epicenters and tau‐PET accumulation epicenters was associated with cross‐sectional and longitudinal tau patterns. Result Tau‐PET epicenters—defined as the 5% brain regions with the highest tau load—aligned with clinical variants, e.g. a posterior pattern in PCA‐AD (“visual AD”) and left‐hemispheric temporal predominance in lvPPA‐AD (“language AD”) (Figure 1). More strongly functionally connected regions showed correlated concurrent tau‐PET levels, which was confirmed with post‐mortem data (Figure 2). Moreover, the connectivity profile of tau‐PET epicenters and accumulation epicenters corresponded to tau‐PET progression patterns (Figure 3). Conclusion Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicenters, across all AD clinical variants. Since tau proteinopathy is a key driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant‐specific endpoints in clinical trials.

Abstract Background Individuals living in socioeconomically disadvantaged areas are disproportionately affected by dementia. However, the pathway leading from neighbourhood deprivation to cognitive symptoms is not well understood. To test our hypothesis that this relationship is associated with cerebral small vessel disease (SVD), we examined (1) whether neighbourhood deprivation related to midlife SVD burden and cognition, and (2) whether these links can be explained by modifiable lifestyle risk factors. Method In this multi‐centre cross‐sectional study, 514 cognitively healthy midlife participants aged 40‐59 years (median 52 years, 64.6% female) underwent clinical assessment and 3T MRI. Postcode data were used to obtain national indices of neighbourhood deprivation. To quantify SVD, we assessed white matter hyperintensities (WMH), perivascular spaces, cerebral microbleeds, and lacunes. Cognition was assessed using the Computerized Assessment of Information Processing (COGNITO) battery. Lifestyle risk factors were evaluated based on clinical data. Using multivariate statistics like structural equation modelling (SEM) and canonical correlation analysis (CCA), we examined associations between these constructs both globally and at the item‐level (i.e., distinction between domains of cognition/deprivation), to shed light on specific domains that could inform targeted prevention strategies. Result Neighbourhood deprivation related to greater prevalence of lifestyle risk factors ( r = 0.36, p < .001), greater SVD burden (b=0.18, p = .01; Figure 1), and greater cognitive impairment ( r = 0.36, p < .001), independent of educational attainment, sex, and age. These links with neighbourhood deprivation were largely driven by lifestyle factors relating to vascular health (sleep, physical activity, obesity, hypertension) (Figure 2), and cognitive deficits consistent with SVD (processing speed, visuospatial) (Figure 3). Residents of deprived neighbourhoods displayed greater prevalence of lifestyle risk factors, except alcohol consumption. Lower cognitive scores were most closely associated with deprivation domains of Crime and Living Environment (Figure 3). The DEPRIVATION→SVD path was mediated by lifestyle risk factors (z=2.57, p = .010), and the DEPRIVATION→COGNITION path was mediated by SVD (z=‐2.14, p = .032) (global SVD & hypertensive subtype, but not CAA‐SVD). Conclusion The pathway linking neighbourhood disadvantage to cognitive impairment at midlife is influenced by vascular risk factors and cerebrovascular burden. Tailored strategies could promote resilience against dementia by promoting health behaviours aligned with the community's unique needs.

Abstract Background Dementia with Lewy Bodies (DLB) is often misdiagnosed or conflated with Alzheimer’s Disease (AD) due to overlapping clinical presentations and neuropathological features. The presence of AD‐like features correlates with accelerated cognitive decline and a worse overall prognosis. Compared to AD, studies suggest that amyloid uptake in DLB may spare the occipital lobe. This project aims to investigate whether amyloid PET could be leveraged to differentiate between AD and DLB patients, with the goal of improving diagnostic accuracy and supporting patient stratification and safety in anti‐amyloid trials. Method This study involves collaboration across six centres (University of Geneva, BioFINDER, AMPLE, AMYPAD PNHS, MCSA, GEHC), each contributing amyloid PET imaging data from patients diagnosed with DLB based on clinical or neuropathological assessments. Moreover, each center provided an additional subset of AD and healthy controls, then matched to DLB samples based on age/sex/APOE genotype/education for comparison. A sub analysis will be performed on patients with evidence of both DLB and AD markers. Given the relatively small sample size, key aspect of the methodological approach is to reduce technical sources of variability. The processing workflow includes rigorous quality control, formatting, normalisation to MNI space, harmonisation (differential smoothing), and MRI‐based segmentation. Result The dataset currently includes amyloid PET scans (acquired using [ 11 C]PiB, [ 18 F]Flutemetamol or [ 18 F]Florbetapir) and MRI scans from ∼130 DLB patients, along with ∼150 AD patients and ∼150 controls. In addition, 99 patients positive for the CSF α‐Synuclein Seeding Amplification Assay were included. Patient data were anonymized, and a harmonised database was created, including demographic characteristics, clinical history, and results from neuropsychological assessments. Conclusion The creation of a standardized, multi‐centre amyloid PET dataset for DLB will enable the study of amyloid PET patterns at the global, regional and voxel level, in comparison with uptake in AD patients and controls. This dataset will serve as a valuable resource for investigating the neuropathological underpinnings of DLB, improving diagnostic accuracy, and potentially guiding patient stratification in anti‐amyloid trials. Efforts to integrate [ 18 F]Florbetaben and additional data are ongoing.

ABSTRACT INTRODUCTION Neighborhood deprivation increases dementia risk, although mechanisms remain unclear. We tested a framework in which modifiable risk factors and cerebral small vessel disease (SVD) mediate the link between neighborhood deprivation and cognition. METHODS In 585 cognitively healthy midlife adults (ages 40–59), neighborhood deprivation was derived from postcodes, cognition was assessed using the COGNITO, lifestyle risk factors were measured using clinical assessments, and SVD (white matter hyperintensities, lacunes, microbleeds, perivascular spaces) was assessed on 3T magnetic resonance imaging. Multivariate analyses examined association pathways among these variables. RESULTS Neighborhood deprivation was associated with poorer cognition ( r = 0.36, p < 0.001), greater prevalence of modifiable risk factors ( r = 0.36, p < 0.001), and greater SVD burden ( β = 0.18, p = 0.008). Serial mediation showed that the effects of deprivation on cognition were indirect, possibly operating via lifestyle risk and SVD, explaining 20% of the total effect, whereas SVD alone explained 28%. DISCUSSION Neighborhood disadvantage relates to poorer cognition, possibly mediated through vascular risk factors and cerebrovascular disease. Highlights Neighborhood deprivation linked to poorer cognition in healthy midlife adults Deprivation linked to small vessel disease (SVD) and modifiable risk factors (chiefly cardiovascular risk) Association between deprivation and cognition mediated by modifiable risk and SVD Mediation was exclusive to hypertensive SVD, but not cerebral amyloid angiopathy (CAA)‐related SVD

Abstract The link between regional tau load and clinical manifestation of Alzheimer’s disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD (‘visual AD’) and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD (‘language AD’). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.

Abstract Dementia with Lewy bodies (DLB), a progressive neurodegenerative disease with heterogeneous clinical presentations, greatly impacts patients, caregivers, and society. Despite its frequency, diagnosing and treating DLB remains challenging. Advances in in vivo biomarker assays reflecting underlying pathology are improving disease identification, diagnostic accuracy, and therapeutic development for biologically targeted, disease‐modifying agents. Consequently, definitions of Alzheimer's disease and Parkinson's disease (PD) have shifted to focus on pathological changes occurring before clinical features, with proposed frameworks for detecting pathological amyloid and tau, neurodegeneration, and other markers (National Institute on Aging‐Alzheimer's Association) and alpha‐synucleinopathy and dopaminergic degeneration (Neuronal α‐synuclein Disease Integrated Staging System, SynNeurGe). The biological frameworks, particularly those related to alpha‐synuclein (α‐synuclein), have sparked debate about unifying DLB and PD under a single pathobiologic disease. This paper discusses the implications of these biological frameworks for the DLB community, addressing topics regarding multiple pathologies and neurochemical systems, clinical heterogeneity, and functional impairment, and exploring the potential impact on clinical trials and care. Highlights DLB is a progressive neurodegenerative disease with varied clinical presentations. Diagnosing and treating DLB remains challenging despite its frequency. Biological frameworks are reshaping Alzheimer's and Parkinson's definitions. In vivo biomarkers are improving DLB identification and diagnostic accuracy. Debate exists regarding unifying DLB and Parkinson's under one pathobiology.