Search

INTRODUCTION: Cerebral small vessel disease (SVD) is a common cause of stroke/vascular dementia with few effective treatments. Neuroinflammation and increased blood‐brain barrier (BBB) permeability may influence pathogenesis. In rodent models, minocycline reduced inflammation/BBB permeability. We determined whether minocycline had a similar effect in patients with SVD. METHODS: MINERVA was a single‐center, phase II, randomized, double‐blind, placebo‐controlled trial. Forty‐four participants with moderate‐to‐severe SVD took minocycline or placebo for 3 months. Co‐primary outcomes were microglial signal (determined using 11C‐PK11195 positron emission tomography) and BBB permeability (using dynamic contrast‐enhanced MRI). RESULTS: Forty‐four participants were recruited between September 2019 and June 2022. Minocycline had no effect on 11C‐PK11195 binding (relative risk [RR] 1.01, 95% confidence interval [CI] 0.98–1.04), or BBB permeability (RR 0.97, 95% CI 0.91–1.03). Serum inflammatory markers were not affected. DISCUSSION: 11C‐PK11195 binding and increased BBB permeability are present in SVD; minocycline did not reduce either process. Whether these pathophysiological mechanisms are disease‐causing remains unclear. INTERNATIONAL CLINICAL TRIALS REGISTRY PORTAL IDENTIFIER: ISRCTN15483452 Highlights: We found focal areas of increased microglial signal and increased blood‐brain barrier permeability in patients with small vessel disease.Minocycline treatment was not associated with a change in these processes measured using advanced neuroimaging.Blood‐brain barrier permeability was dynamic but MRI‐derived measurements correlated well with CSF/serum albumin ratio.Advanced neuroimaging is a feasible outcome measure for mechanistic clinical trials. [ABSTRACT FROM AUTHOR]

Background: The thalamus consists of multiple nuclei involved in processes such as sleep and cognition. Individuals with AD, mild cognitive impairment (MCI) and asymptomatic individuals with risk factors for early‐onset AD display a reduction in thalamic volumes (Lee et al., 2013; Zidan et al., 2019). The pulvinar, anteroventral, centromedian and mediodorsal nuclei are amongst the thalamic nuclei affected in AD and MCI (Bernstein et al., 2021). Our aim was to investigate thalamic nuclei volumes and their association with cognitive performance in middle‐aged, cognitively unimpaired individuals with respect to dementia family history (FHD). Method: 701 participants were recruited into the PREVENT‐Dementia study. 645 T1‐weighted 3T MRI scans underwent thalamic segmentation using Freesurfer 7.1.0. The 24 sub‐nuclei were grouped into 6 regions (Table 1); 1) Anterior, 2) Lateral, 3) Ventral, 4) Intralaminar, 5) Medial and 6) Posterior (Iglesias et al., 2018). Cognitive performance was evaluated using the COGNITO battery. Differences in volumes with respect to parental FHD and the effect on cognitive performance was analysed using robust linear regression, with age, sex, years of education and total intracranial volume as covariates and FDR correction for multiple comparisons. Result: Individuals with a FHD had significantly smaller volumes of the medial thalamus (pFDR = 0.037), particularly the mediodorsal medial (MDm, p = 0.016) and lateral (MDl, p = 0.016) nuclei (Figure 1). Individuals with a FHD performed significantly better on the delayed (p = 0.015) and descriptive recall (p = 0.03) tests. Larger volumes of the MDm (p = 0.003) and MDl (p = 0.036) were associated with a faster processing speed in those without FHD. Larger volumes of the MDl were also associated with greater recall in narrative and descriptive recall tests (p = 0.007 and p = 0.025, respectively) in those without FHD (Figure 2). Conclusion: Individuals without FHD have larger volumes of the MDm and MDl nuclei, which appear to exert a protective effect on cognitive performance, whilst having little effect in those with FHD. This could represent initial dysregulation in the disease process, which could be further evaluated with functional imaging or longitudinal follow up to assess for cognitive decline. [ABSTRACT FROM AUTHOR]

Background: There is growing evidence for early and extensive synaptic loss in frontotemporal lobar degeneration syndromes from in vivo and post‐mortem studies. We proposed that synaptic loss would affect behaviour, in relation to changes in functional connectivity. Method: We recruited 29 participants with progressive supranuclear palsy, 16 participants with amyloid‐negative corticobasal syndrome, 8 participants with behavioural variant frontotemporal dementia and 24 similarly‐aged healthy volunteers. All participants underwent resting‐state functional 3T MRI and positron emission tomography with [11C]UCB‐J, that binds synaptic vesicle 2A. We compared the connectivity metrics of nodal weighted degree and voxelwise regional homogeneity with [11C]UCB‐J non‐displaceable binding potential (BPND), in associative and commonality analyses. We then used independent component analysis to extract [11C]UCB‐J BPND signal variance across participants, followed by derivation of participant‐specific scores of functional spatial covariance with the [11C]UCB‐J components. We applied model selection to assess whether connectivity scores would improve prediction of and moderate the effect of synaptic loss on clinical severity. Result: Reduced [11C]UCB‐J BPND was associated with reduced connectivity, with synaptic density predicting both measures of connectivity over and above grey matter volume (Figure 1). The anatomical distribution of synaptic loss partially overlapped in PSP, bvFTD and CBS, but there were also disease‐specific effects (Figure 2). The effect of synaptic loss on functional connectivity was expressed local to the regions of severe synaptic loss, and in remote regions. Moreover, functional connectivity explained additional variance and moderated the relationship between synaptic density and clinical severity (Figure 3). Conclusion: In vivo synaptic loss is associated with reduced connectivity, and changes in behaviour, with implications for modelling disease pathogenesis and translational studies. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Degeneration of cortical cholinergic projections from the nucleus basalis of Meynert (NBM) is characteristic of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), whereas involvement of cholinergic projections from the pedunculopontine nucleus (PPN) to the thalamus is less clear. METHODS: We studied both cholinergic projection systems using a free water‐corrected diffusion tensor imaging (DTI) model in the following cases: 46 AD, 48 DLB, 35 mild cognitive impairment (MCI) with AD, 38 MCI with Lewy bodies, and 71 controls. RESULTS: Free water in the NBM‐cortical pathway was increased in both dementia and MCI groups compared to controls and associated with cognition. Free water along the PPN‐thalamus tract was increased only in DLB and related to visual hallucinations. Results were largely replicated in an independent cohort. DISCUSSION: While NBM‐cortical projections degenerate early in AD and DLB, the thalamic cholinergic input from the PPN appears to be more selectively affected in DLB and might associate with visual hallucinations. Highlights: Free water in the NBM‐cortical cholinergic pathways is increased in AD and DLB.NBM‐cortical pathway integrity is related to overall cognitive performance.Free water in the PPN‐thalamus cholinergic pathway is only increased in DLB, not AD.PPN‐thalamus pathway integrity might be related to visual hallucinations in DLB. [ABSTRACT FROM AUTHOR]

Background: It is now acknowledged that Alzheimer's Disease (AD) processes are present decades before the symptoms manifest, but whether lifestyle activities can protect against these early AD processes in mid‐life remains poorly understood. Furthermore, the impact of sex as a biological variable on associations between dementia risk, protective lifestyle activities and cognition is unknown. In this study, we aimed to replicate findings from our two recent studies (Deng et al., 2022; Heneghan et al., 2022) on the contribution of mid‐life modifiable activities to cognition in individuals with dementia risk, in a larger independent cohort (N = 461 vs N = 208 used previously). Second, we investigated associations between biological sex, dementia risk, protective lifestyle activities and cognitive performance. Method: Cognitively unimpaired middle‐aged participants (40‐59 years; N = 461) completed cognitive and clinical assessments cross‐sectionally. Risk factors (Apolipoprotein E [APOE] ε4 allele status, family history of dementia, and the Cardiovascular Risk Factors Aging and Dementia score [CAIDE]) were assessed and mid‐life activities were measured with the Lifetime of Experiences Questionnaire. Result: Replicating our key previous findings, we found that episodic and relational memory was (a) significantly negatively associated with the CAIDE risk score (Figure 1a), (b) positively associated with stimulating lifestyle activities (Figure 1b), and (c) that females performed significantly better than males in episodic and relational memory (Figure 2a). The key novel finding of this study was that APOE ε4 genotype modulated the association between sex, lifestyle and cognition. Only for APOE ε4+ females, not APOE ε4‐, higher occupational attainment was associated with better episodic and relational memory (Figure 2c, 2d). Conversely, only for APOE ε4+ males, not APOE ε4‐, higher occupational attainment was associated with worse episodic and relational memory (Figure 2c, 2d). Conclusion: These findings suggest that modifiable lifestyle activities offset cognitive decrements due to inherited AD risk in mid‐life and support the targeting of modifiable lifestyle activities for the prevention of AD. Furthermore, these findings suggest an urgent need for targeted research on female‐specific risk factors, to inform personalised strategies for AD prevention and the promotion of female brain health. [ABSTRACT FROM AUTHOR]

Background: Brain inflammation is an important pathogenic mechanism in many dementias, occurring early in the disease and being predictive of clinical decline. However, data on blood markers of inflammation across different dementia subtypes are limited. Here we assess inflammatory patterns of serum cytokines from patients with Alzheimer's disease (AD), Lewy‐body dementia (DLB), frontotemporal dementia (FTD), progressive supranuclear palsy (PSP), corticobasal syndrome (CBS) and motor neurone disease (MND). Method: Blood samples were obtained from 422 participants (29 controls, 46 patients with AD, 35 with mild cognitive impairment (MCI), 38 with DLB, 52 with behavioural variant FTD, 51 with primary progressive aphasia, 58 with PSP, 53 with CBS, 60 with MND. Serum assays for 41 inflammatory markers used the MesoScale Discovery V‐Plex‐Human Cytokine 36 plex panel plus five additional cytokine assays. A Principal Component Analysis (PCA) across all participants was used to identify leading multivariate components, or profiles, of inflammation. Analysis of variance and Bayesian pairwise t‐tests were performed on the resulting components to compare each patient cohort to controls. Result: Fifteen cytokines were undetectable in the majority (>50%) of participants and were thus excluded. The PCA of remaining 26 cytokines identified 3 components (explaining 18.3%, 8.5% and 6.4% variance, respectively). Component 1 was strongly represented by pro‐inflammatory cytokines (Figure 1, left). Kruskal–Wallis one‐way analyses of variance on the first component detected significant differences across the groups (χ2(8) = 24.3, p = 0.0021), and the Bayesian pairwise t‐tests identified significant differences between each patient cohort and controls, except for people with MCI (Figure 1, right). Component 2 did not differ between patients and controls. Component 3 split the cytokines into two subgroups, and was mainly loaded by patients with MCI, AD and MND (χ2(8) = 64.6, p<0.0001). Conclusion: This data‐driven approach identified similar profiles of pro‐inflammatory responses across multiple neurodegenerative dementia types. Further analyses will clarify differences between diagnoses, relationships of the pro‐inflammatory patterns with clinical severity and brain changes captured by neuroimaging (PET and MRI). [ABSTRACT FROM AUTHOR]

Background: Novel, validated imaging biomarkers for assessing disease severity and progression in dementia with Lewy Bodies (DLB) are needed as standard neuroimaging changes such as atrophy are not pronounced. Both multi‐modal MR and PET offer opportunities, for example cortical microstructure and dendritic imaging can be assessed using advanced MR diffusion weighted imaging (DWI) methods such as neurite orientation dispersion and density imaging (NODDI) and PET with UCB‐J can assess synaptic density. We applied these and other markers to people with DLB and controls. Method: In linked studies, people with probable DLB and similarly aged controls (n = 10‐30 per group depending on study) underwent multimodal 3T‐MRI (including structural, multi‐shell DWI and arterial spin labelling imaging) and PET imaging with AV1451 (for assessment of tau), PiB (for amyloid status) and [11C]UCB‐J PET/MR. For MR, T1‐MRI and DWI datasets were processed using FreeSurfer 7.2 and FSL 6.0.4 respectively with whole‐brain ODI derived from the Microstructure Diffusion Toolbox. The [11C]UCB‐J and [18F]AV1451 binding potentials (BPND) were assessed using a simplified reference tissue model (reference centrum semiovale for UCBJ and cerebellum for AV1451). Group differences in ODI, UCB‐J and AV1451 BPND were examined and correlated with structural changes and clinical and cognitive variables (ACE‐R score). Result: Compared to controls, people with DLB showed significantly thinner neocortex (T = ‐2.8, p = 0.01) in temporo‐parietal regions but more widespread reductions in cortical microstructure (ODI, T = ‐3.9, p < 0.001)(Figure 1). Within the DLB group, hippocampal ODI was positively correlated with cognitive performance (robust linear regression: p < 0.001)(Figure 2). Reduced synaptic density (UCB‐J BPND) was found for the DLB group in posterior regions (p<0.05, FWE corrected)(Figure 3), with a trend for greater reductions in those who were amyloid positive. ACE‐R scores significantly correlated with synaptic density (p<0.05, FWE corrected). There were no significant differences in AV1451 binding between DLB and controls. Conclusion: Extensive reductions in ODI and reduced synaptic density, both associated with cognitive impairment and occurring in regions without significant atrophy or tau deposition, suggests that NODDI and synaptic PET imaging are promising biomarkers for DLB which merit further investigation, including in longitudinal studies. [ABSTRACT FROM AUTHOR]

Background: The early degeneration of the cholinergic nucleus basalis of Meynert (NBM) and its cortical projections is a hallmark of both dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). In addition to the NBM, the other major cholinergic projection system originates in the pedunculopontine nucleus (PPN) and provides innervation to the thalamus. Given that visual hallucinations are a hallmark of DLB, but not AD, and have recently been attributed to thalamic degeneration, we tested whether the PPN projection system is differentially altered in DLB compared to AD. Methods: NBM‐cortical and PPN‐thalamus white matter pathways were tracked using diffusion‐weighted imaging data from 46 patients with AD, 48 with DLB, 35 with mild cognitive impairment (MCI) with AD, 38 with MCI with Lewy bodies, and 71 control participants. A free‐water corrected DTI model was estimated. Free water fraction along the cholinergic pathways was compared between groups controlling for age, sex, and free water fraction from a white matter control mask. Multiple linear regression was applied to test associations with cognitive function, core Lewy body symptoms with a focus on visual hallucinations, and changes in cognition using longitudinal follow‐up data. Results: Free water fraction in the NBM lateral pathway was increased in both dementia and MCI groups compared to controls and this was associated with performance on overall cognition and phonemic fluency tests as well as with longitudinal changes in cognition (Figure 1). Free water fraction along the PPN‐thalamus tract was increased only in DLB patients while it appeared relatively spared in AD and this increase in the Lewy body patients was related to the presence of visual hallucinations (Figure 2). These results were largely replicated in an independent validation cohort (34 AD, 34 DLB, 35 controls). Conclusion: Our cross‐validated findings show that the cholinergic input to the thalamus from the PPN is selectively affected in DLB and contributes to visual hallucinations. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is an important pathogenic mechanism in frontotemporal dementia (FTD) and related disorders. Postmortem and in vivo imaging studies have shown brain inflammation early in these conditions, and as proportionate to symptom severity and rate of progression. However, data on inflammation blood markers of inflammation and their relationship with central inflammation are limited. Here we assess inflammatory patterns of 41 serum cytokines from patients with FTD and related conditions, and their association with regional microglial activation (TSPO PET). Method: Blood samples were obtained from 29 healthy controls, and 214 patients with a clinical diagnosis of behavioural variant FTD (bvFTD = 52), primary progressive aphasia (PPA = 51), progressive supranuclear palsy (PSP = 58) and corticobasal syndrome (CBS = 53). Serum assays used the MesoScale Discovery V‐Plex‐Human Cytokine 36 plex panel plus five additional cytokine assays. A Principal Component Analysis (PCA) across all participants was used to reduce dimensionality of cytokine data. A sub‐group of patients (bvFTD = 10, PPA = 17, PSP = 17) underwent PET imaging with [11C]PK11195 PET, as index of microglial activation. Kruskal‐Wallis and pairwise t‐tests were performed on the resulting components to compare each patient cohort to controls. [11C]PK11195 non‐displaceable binding potential (BPND) was calculated in 83 regions of interest (ROIs) across the whole brain. Spearman correlations tested associations between cytokine components and regional [11C]PK11195 BPND. Result: Sixteen cytokines were undetectable in >50% of participants and thus excluded. The first component identified by the PCA on the remaining 25 cytokines (explaining 19.7%) was strongly loaded by pro‐inflammatory cytokines (Figure 1, left). Kruskal–Wallis one‐way analyses of variance on detected significant differences across the groups (χ2(4) = 11.0, p = 0.027), and the pairwise t‐tests identified significant differences between each patient cohort and controls (Figure 1, right). Spearman correlations identified regional positive associations between individual cytokine‐component scores and microglial activation in frontal and brainstem regions across the whole group (R≥0.25), and syndrome‐specific regional patterns (Figure 2). Conclusion: This data‐driven approach identified a pro‐inflammatory profile across FTD and related conditions, which is positively associated with higher levels of microglial activation in syndrome‐related key brain regions. Blood‐based tests could greatly increase the scalability and access to neuroinflammatory assessment in dementia and experimental medicine studies. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is an important pathogenic mechanism in frontotemporal dementia (FTD) and related disorders. Postmortem and in vivo imaging studies have shown brain inflammation early in these conditions, and as proportionate to symptom severity and rate of progression. However, data on inflammation blood markers of inflammation and their relationship with central inflammation are limited. Here we assess inflammatory patterns of 41 serum cytokines from patients with FTD and related conditions, and their association with regional microglial activation (TSPO PET). Method: Blood samples were obtained from 29 healthy controls, and 214 patients with a clinical diagnosis of behavioural variant FTD (bvFTD = 52), primary progressive aphasia (PPA = 51), progressive supranuclear palsy (PSP = 58) and corticobasal syndrome (CBS = 53). Serum assays used the MesoScale Discovery V‐Plex‐Human Cytokine 36 plex panel plus five additional cytokine assays. A Principal Component Analysis (PCA) across all participants was used to reduce dimensionality of cytokine data. A sub‐group of patients (bvFTD = 10, PPA = 17, PSP = 17) underwent PET imaging with [11C]PK11195 PET, as index of microglial activation. Kruskal‐Wallis and pairwise t‐tests were performed on the resulting components to compare each patient cohort to controls. [11C]PK11195 non‐displaceable binding potential (BPND) was calculated in 83 regions of interest (ROIs) across the whole brain. Spearman correlations tested associations between cytokine components and regional [11C]PK11195 BPND. Result: Sixteen cytokines were undetectable in >50% of participants and thus excluded. The first component identified by the PCA on the remaining 25 cytokines (explaining 19.7%) was strongly loaded by pro‐inflammatory cytokines (Figure 1, left). Kruskal–Wallis one‐way analyses of variance on detected significant differences across the groups (χ2(4) = 11.0, p = 0.027), and the pairwise t‐tests identified significant differences between each patient cohort and controls (Figure 1, right). Spearman correlations identified regional positive associations between individual cytokine‐component scores and microglial activation in frontal and brainstem regions across the whole group (R≥0.25), and syndrome‐specific regional patterns (Figure 2). Conclusion: This data‐driven approach identified a pro‐inflammatory profile across FTD and related conditions, which is positively associated with higher levels of microglial activation in syndrome‐related key brain regions. Blood‐based tests could greatly increase the scalability and access to neuroinflammatory assessment in dementia and experimental medicine studies. [ABSTRACT FROM AUTHOR]

Background: The entorhinal cortex (EC) is the first cortical brain region to exhibit neurodegeneration in Alzheimer's disease (AD). Given that the EC contains unique grid cells underpinning path integration, tests probing this aspect of navigation may have added value in detecting AD in its earliest preclinical stages. Building on our past work showing that a VR path integration task was highly sensitive and specific for prodromal AD (Howett et al., 2019 Brain), we tested the hypothesis that path integration may be affected in asymptomatic middle‐aged individuals at increased risk of AD. Method: 100 cognitively healthy adults (aged 43–66) from the PREVENT Dementia cohort performed an immersive VR path integration task in a simulated environment with distal boundary cues to generate allocentric spatial representations. We manipulated EC‐dependence by pseudo‐randomly removing supportive spatial cues from the virtual environment (Figure 1). Participants additionally performed a battery of cognitive tasks including the ACE‐R and COGNITO episodic memory. Linear mixed effects models and Tukey‐corrected post‐hoc contrasts were used to explore the contributions to task performance of parental family history, APOE‐e4 status, global amyloid PET uptake value (N = 46) and CAIDE lifestyle dementia risk score, adjusted for age, sex and education. Result: Individuals with a positive family history, APOE‐e4 allele or higher CAIDE dementia risk score showed a selective impairment in path integration only when supportive boundary cues were removed. Significant sex interactions indicated that the family history effect (t = 2.31, pTukey = 0.022, Figure 2) and APOE‐e4 effect (t = 3.18, pTukey = 0.023) was specific to males. The effect of CAIDE risk score was specific to individuals with a family history (t = 2.45, pTukey = 0.038) (Figure 3). Conversely, these AD risk factors showed no effect on performance for the other cognitive tasks. Global amyloid PET uptake values showed no association to any task performance. Conclusion: These results suggest that navigation tests based on EC grid cell function may identify the earliest cognitive changes in individuals at greater risk of AD. The additional moderation by sex indicates a future need to consider male/female differences when using family history or APOE status to inform detection of initial stages of AD. [ABSTRACT FROM AUTHOR]

Background: A hallmark of neurodegenerative disorders is synaptic dysfunction and degeneration. This makes the presynaptic protein synaptosomal‐associated protein 25 (SNAP‐25) and the Vesicle‐associated membrane protein 2 (VAMP‐2) targets of interest and importance. Previously, these proteins have only been measurable in cerebrospinal fluid (CSF) and are increased in Alzheimer's disease (AD) patients. Considering the advancement of blood‐based detection of phosphorylated tau (p‐tau), neurofilament light (NfL) and amyloid‐β (Aβ42/40), a measure of synaptic degeneration in blood would be important for disease prognosis and clinical trial outcome. In this study, we describe results from novel single molecular arrays (Simoa) for blood SNAP‐25 and VAMP‐2. Method: Prototype Simoa assays for N‐terminal SNAP‐25 and VAMP‐2 were developed as more sensitive versions of previously validated in‐house CSF assays with diluent suited for both plasma and CSF. We examined 110 participants (54 AD and 56 healthy controls) from the Swedish BioFINDER pilot study. The mean age of patients was 75.9 years (7.1 SD) and there was an even distribution of sex. We examined group differences by the Wilcoxon rank sum test and associations between these two blood biomarkers and Aβ‐PET, tau‐PET, MRI and MMSE were determined by linear regression, adjusting for age and sex. Result: SNAP‐25 was significantly increased in patients with AD (mean [SD], 0.81 pg/mL [0.27]; p < 0.001) as compared to controls (0.60 pg/mL [0.22]). SNAP‐25 distinguished AD patients from controls with an area under the curve of 0.74 (95% CI = 0.65‐0.83). SNAP‐25 showed association with Aβ PET (β = 0.10, p = 0.007) but not tau PET. SNAP‐25 associated with cortical thickness (β = ‐0.05, p = 0.009) and MMSE (β = ‐6.69, p = 0.001). No significant associations were found when analysing the AD group alone. VAMP‐2 showed no significant association with any of the mentioned parameters above. Conclusion: This novel ultra‐sensitive immunoassay demonstrates an increase of plasma SNAP‐25 in AD patients, and a significant relationship with cognition and cortical atrophy. Further studies will verify these changes in independent cohorts and explore the relationship between plasma SNAP‐25 and VAMP‐2 with synaptic vesicle glycoprotein 2A (SV2A) PET in a broad range of neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

Background: Brain Age Gap (BAG) represents the difference between an individual's predicted age, derived from machine learning models trained on neuroimaging data, and their chronological age. BAG has been associated with dementia and cognition in old age. Less is known relating BAG to dementia risk‐factors or cognitive performance in middle‐age. Method: Cognitively healthy, middle‐aged (40‐59 years) subjects from PREVENT‐Dementia had an array of neuropsychological, neuroimaging and genetic assessments. Brain Ages were predicted from T1‐weighted 3T MRI scans. Cognition was assessed using COGNITO. Multiple linear robust regression models tested hypotheses that: (i) BAG is positively associated with dementia risk‐factors; (ii) increased BAG is associated with worse cognition; (iii) longitudinal BAG change is positively associated with longitudinal cognitive deterioration. A range of machine learning algorithms with nested cross‐validation was used to assess whether BAG and cognition could predict each other. Result: 552 middle‐aged participants (median age 52.8 years) had all baseline assessments; 68 had amyloid PET data and 138 had longitudinal data. Median BAG was ‐2.0 years with a range from ‐21.2 to 18.4 years (Figure 1). BAG in middle‐age was associated with hypertension (p = 0.007) and alcohol intake (p = 0.008) but not APOE4 carrier status (p = 0.14) or amyloid centiloids (p = 0.53). BAG was not associated with cognitive performance either cross‐sectionally (p = 0.74) or longitudinally (p = 0.30), and there was no added predictive value between BAG and cognition. More education was associated with better cognition (p = 4.7×10−11) but not with BAG (p = 0.32). Conclusion: Even in midlife, substantial inter‐individual heterogeneity exists in the extent to which brains have aged. BAG in middle‐age is associated with modifiable dementia risk‐factors, suggesting that lifestyle risk‐factor modification needs to start at, or before, midlife to optimise brain health. BAG in middle‐age was not associated with risk‐factors for Alzheimer's disease (APOE4, amyloid deposition) or cognitive performance, despite there being a plausible and expected association between more education and better cognitive performance. These results are important for understanding brain‐age in middle‐aged populations who might be the target of future dementia‐preventing therapies. [ABSTRACT FROM AUTHOR]

Background: The Mediterranean diet (MedDiet) has been associated with better cardiometabolic and brain health. Research has suggested differences in these associations between men and women, with men typically reported to benefit more from higher MedDiet adherence. However there remains a lack of research in this area in non‐Mediterranean countries. This study aimed to explore cross‐sectional associations between MedDiet adherence in the PREVENT Dementia cohort (UK and Ireland), stratified by sex. Method: After deriving scores to quantify adherence to the MedDiet (MEDAS, MEDAS continuous and Pyramid), we used linear regression and linear mixed effects models to test for associations between the MedDiet scores, cardiometabolic health (blood pressure, BMI, glycemia, cholesterol, triglycerides) and brain health (white matter hyperintensity volume (WMHV), cortical thickness, hippocampal subfield volumes, cognition). Propensity scores were calculated to strengthen causality inferences from the data, and used as covariates along with total energy intake and Western diet scores. Result: We included 533 participants, mean age 51.25 (±5.40) years, majority women (60.0%). Higher MedDiet scores (MEDAS data presented) were associated with lower blood pressure (systolic ß: ‐1.16, p:0.009; diastolic ß: ‐1.00, p<0.001) and BMI (ß: ‐0.53, p<0.001). There were significant interactions between MedDiet and sex for diastolic blood pressure and hip‐to‐waist ratio. When stratified by sex, women had significant positive associations between MedDiet scores and blood pressure (systolic ß: ‐1.45, p: 0.006; diastolic ß: ‐1.29, p<0.001), BMI (ß: ‐0.51, p: 0.02) and glycemia (Pyramid only: ß: ‐0.11, p: 0.02), whereas men only had a significant association with BMI (ß: ‐0.45, p: 0.02) (Figure 1). There were no significant associations between dietary scores and any markers of brain health. An exploratory path analysis found a significant mediation between the Pyramid MedDiet score, pulse pressure and WMHV (Figure 2), which was only seen in women. Conclusion: There were significant associations between higher MedDiet scores and better cardiometabolic health, particularly for women. There were no direct associations with brain health outcomes, however a path analysis suggested a mediating effect of pulse pressure between the MedDiet and WMHV. Sex‐stratified nutritional guidelines to support better cardiometabolic health, may lead to better brain health and warrant further investigation. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease and related dementias (ADRD) are among the most feared conditions. Some level of fear can motivate healthy behaviors. However, intense fears can have the opposite effect, leading to avoidance behaviors such as withdrawal from cognitively or socially demanding activities. In this way, fears and avoidance behaviors have potential to influence modifiable ADRD risk. Here, we investigated if fear and avoidance are associated with cognitive, psychological and lifestyle factors in mid‐ and later life. Methods: Participants were middle‐aged (n = 188, 40‐59 years, mean = 51.4 ± 5, 52.7% female) and older adults (n = 746, 60‐90 years, mean = 65 ± 7.2, 61.5% female). Fears and avoidance behaviors were measured using Fear and Avoidance of Memory Loss scale. Linear regression examined the contribution of fear and avoidance to cognitive, psychological and lifestyle factors. Mid‐life factors included cognition (COGNITO), stress (Perceived Stress Scale), depressive symptoms (Center for Epidemiologic Studies Depression Scale), loneliness (UCLA Loneliness Scale) and lifestyle activities (Lifetime of Experiences Questionnaire). Later life factors included cognition (MoCA) and depression (Geriatric Depression Scale). Models were adjusted for age, gender, education, ADRD family history and anxiety. Results: Middle‐aged and older women reported higher fear compared to men (ps <.028). Older individuals with a family history of ADRD also reported higher fear (p <.001). Avoidance behaviors were significantly associated with worse cognitive performance in later life (β = ‐0.10, p =.020), but not in mid‐life. Greater avoidance in mid‐life was associated with higher stress (β =.83, p =.001), loneliness (β = 1.22, p <.001) and depressive symptoms (β = 1.09, p <.001), and lower engagement in lifestyle activities (β = ‐0.19, p =.02). Avoidance was also associated with depressive symptoms in later life (β =.28, p <.001). Conclusions: Avoidance behaviors were associated with lower engagement in healthy lifestyle activities in mid‐life, worse cognitive performance in later life, and reduced psychological well‐being in both mid‐ and later life. While causation cannot be determined, it is likely that these factors interact recursively over time. Thus, targeting avoidance early on may be beneficial for ADRD risk reduction. [ABSTRACT FROM AUTHOR]

Background: The long‐term consequences of mild traumatic brain injury (mTBI) are poorly understood. Prior studies have shown that a history of mTBI is associated with a 2 fold increase of dementia diagnosis. However, the precise mechanisms for increased dementia risk which could start in mid‐life remain unclear. TBI can cause varying degrees of damage to different regions of the brain, and as a result, may affect distinct subdomains of cognitive function in distinct ways. This study investigated cognitive performance and brain volume among individuals at risk of Alzheimer's Disease (AD) in mid‐life with a history of self‐reported mTBI. Method: 578 participants (118 no head injury, 116 single mTBI & 344 repeated mTBI) aged 40‐60 years participating in the PREVENT study, a large cohort study examining the risk of AD in mid‐life, underwent structural 3T MRI and neuropsychometric evaluation (ACE‐III and COGNITO) at baseline. Self‐reported, cross‐sectional data on head injury were collected through the Brain Injury Screening Questionnaire (BISQ). FSL (version 6.0.1) was used to calculate brain volume (correcting for head size). Comparisons between participants with no history of head injury and single or repeated mTBI were done using a one‐way ANOVA. Result: There was no statistically significant difference in total brain volume between participants with or without a history of mTBI (F(2,576) = 1.24, p = 0.29). There was also no significant difference between self‐reported mTBI and ACE‐III total scores F(2,579) = 0.0112, p = 0.99) or performance on memory (p = 0.87), language (p = 0.24), visuospatial abilities (p = 0.61) and attention (p = 0.14) in the COGNITO battery. Conclusion: We found no evidence that a history of mTBI (single or repeated) is associated with cognitive impairment in this cohort. Future longitudinal studies are necessary to further evaluate self‐reported mTBI and how the aging process might interact with cognitive outcome post‐injury. Future analysis of covariates such as lower socioeconomic status, gender, physical health and history of alcohol/drug use, that are known to impact cognitive performance and are related to greater rates of TBI, will be studied to determine the influence of a history of mTBI on dementia risk. [ABSTRACT FROM AUTHOR]

Background: Carriership of the apolipoprotein ε4 (APOE4) allele confers a heightened risk for the development of Alzheimer's disease (AD). Cerebral blood flow (CBF) is decreased in prodromal and established AD, however findings in the preclinical stage are mixed, with some studies reporting increases. CBF can be impacted by many factors including the haematocrit. We investigated in a cohort at risk of developing AD how haematological variables relate to CBF and if this relationship is differentially moderated by APOE4. Method: 375 participants from the PREVENT‐Dementia study underwent arterial spin labelling (ASL) and structural 3Tesla MRI. ASL data were analysed using BASIL/FSL and structural scans with SPM12. CBF maps were corrected for partial volume effects. A vascular territory mask with nine territories, the middle, proximal and distal branches of the anterior, middle and posterior cerebral arteries (ACA, MCA, PCA) was used for region‐of‐interest analysis and registered to the native ASL space. Regional gray matter (GM) CBF values were harmonised using COMBAT. Linear regression was used to examine differences between APOE4 carriers and non‐carriers controlling for age, sex and years of education. Associations between haematological properties and CBF were examined with Pearson's correlations. Differential relationships between CBF, haematocrit, and measures of red blood cell size and shape (distribution width (RDW) and mean corpuscular volume (MCV)) were investigated by including interaction terms of APOE4 and haematological variables in the models. Result: APOE4 carriers had significantly higher CBF in the proximal MCA (t = 2.54, p = 0.01). Across all subjects, RDW and MCV were not associated with GM CBF, though several significant interactions were observed between APOE4 and RDW in predicting CBF (Figure 1). Haematocrit was associated with GM CBF (ρ = ‐0.19, p < 0.01). No significant interactions were seen between APOE4 and haematocrit or MCV in predicting CBF. Conclusion: The variability of the size and shapes of erythrocytes was differentially associated with CBF between APOE4 carriers and non‐carriers suggesting a different response to morphological erythrocyte alterations. This could further relate to underlying factors such as inflammation, which is associated with a higher RDW. Such associations should be examined in further studies. [ABSTRACT FROM AUTHOR]

Background: The relationship between sleep and dementia risk is complex, with both longer and shorter sleep duration being associated with cognitive decline. The thalamus has an important role in regulating the sleep‐wake cycle and structural changes may be a good marker of sleep abnormalities. Our aim was to investigate the association between dementia risk, sleep and the volume of thalamic nuclei. Method: We analysed baseline data from PREVENT‐dementia, a multicentre, prospective cohort study of cognitively intact participants aged 40 to 59 years, who were stratified according to presence of the ApoE4 allele and parental family history of dementia (FH+). Sleep data was collected using the Pittsburgh Sleep Quality Index (PSQI) which measures subjective sleep quality, latency, duration, efficiency, disturbances, medication use and daytime dysfunction. T1‐weighted 3T MRI images were analysed using Freesurfer (version 7.1.0) to determine the volume of the thalamus and its subnuclei, controlling for total intracranial volume. The score on the centre for epidemiologic studies depression scale and the number of analgesic medications, were also used as covariates in the analysis to control for mood and pain. The data was analysed in R Studio using robust logistic regression. Result: Complete data was available for 594 participants. The total PSQI score was lower in FH+ subjects (p = 0.046) but was not associated with ApoE4 status. FH+ subjects had smaller volumes of mediodorsal medial (p = 0.03) and lateral (p = 0.03) nuclei, longer sleep duration (p = 0.02), and counterintuitively less sleep‐related daytime dysfunction (p = 0.01) compared to controls. In the FH+ group, larger pulvinar nucleus was associated with better sleep quality (r = ‐0.17, p = 0.002). In apoE4 non‐carriers, a larger thalamus (r = ‐0.12, p = 0.02) and larger centromedian nucleus (r = ‐0.13, p = 0.01) were both associated with a lower total PSQI score. They also had an association between larger pulvinar (r = ‐0.11, p = 0.04) and centromedian (r = ‐0.14, p = 0.007) nuclei and increased sleep efficiency. Conclusion: Middle‐aged subjects with a FH+ had longer sleep duration and smaller thalamic volumes which may represent early neurodegenerative changes. Furthermore, we found an association between larger thalamic nuclei and better sleep variables, especially in ApoE4 non‐carriers, indicating that the thalamus may be an important imaging correlate of sleep quality. [ABSTRACT FROM AUTHOR]

Background: Cerebral microbleeds (CMB) are predictive of increased risk of dementia and stroke. Although commonly regarded as vascular markers, CMB can also stem from non‐vascular aetiologies like head injuries or traumatic brain injury (TBI), although these are often overlooked. Therefore, this study examines CMB in relation to TBI, and their differential causes (i.e., risk factors) and consequences (i.e., clinical outcomes). Method: In 605 healthy middle‐aged adults (aged 40‐59), CMB were rated on 3T susceptibility weighted imaging (SWI) MRI. TBI was assessed using the Brain Injury Screening Questionnaire (BISQ). TBI+ was defined as at least one blow to the head resulting in loss of consciousness (36.0%; n = 217). Memory was assessed using the COGNITO battery. Interaction analyses examined TBI*CMB interactions on hypertension, gait, and memory. Dominance analysis examined the relative contribution of TBI and vascular risk factors on predicting gait disturbances and memory. All models adjusted for sex, age, education, and study site. Result: TBI was related to higher CMB count (t = 2.06, p =.039), and were more common in males (48.3%) than females (28.0%) (Χ2 = 28.91, p<.001). Number of TBI events related to poorer memory (t = ‐2.62, p =.009) and gait disturbances (t = 3.54, p<.001). Interaction analyses demonstrated that hypertension (t = ‐2.26, p =.024), memory (t = 2.70, p =.007) and gait (t = ‐2.29, p =.023) were less closely related to CMB in individuals with greater number of TBI events, relative to those with fewer TBIs. Regionally, these interactions were significant for lobar CMB, but not deep subcortical CMB. Within the TBI+ group, dominance analysis demonstrated that number of TBI events outperformed vascular risk factors in predicting gait disturbances (Contribution to R2: TBI = 52.9%, vascular risk = 32.6%) and memory (TBI = 28.7%, vascular risk = 1.2%). Conclusion: CMB appeared to differ aetiologically and clinically in those with and without TBI. In individuals with TBI, TBI itself was the dominant driver of clinical deficits. When compared to CMB of presumed vascular origins cross‐sectionally, TBI‐related CMB may appear to be less detrimental. However, longitudinal analysis is required to determine how TBI‐related CMB differ in clinical trajectory and downstream pathologies. This study highlights the importance of differentiating between CMB of vascular origins vs. TBI in both research and clinically to aid prognosis and treatment decisions. [ABSTRACT FROM AUTHOR]

Background: It is well acknowledged that Alzheimer's Disease (AD) neuropathology start decades before clinical manifestations, but the brain mechanism of sporadic AD in midlife remains unclear. Resting‐state functional connectivity (FC) is increasingly used to understand early brain changes in Alzheimer's disease (AD) (Sperling, 2011; van den Heuvel & Sporns, 2019). We asked whether risk for late‐life dementia impacts functional connectivity in cognitively healthy middle‐aged individuals. Method: Functional Magnetic Resonance Imaging and detailed neuropsychological assessments were obtained for 585 (207/378 female/male) cognitively healthy individuals, aged 40‐59 years (mean = 50.9), from the PREVENT‐Dementia study. Dementia risk was calculated with the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score. A novel connectome‐based predictive method called NBS‐Predict was used to investigate the association between FC and CAIDE score and its role in cognition. Result: FC significantly predicted CAIDE scores across the whole cohort (r = 0.207, p < 0.001). FC within and between the cingulo‐opercular network (CON) and sensorimotor network (SMN), as well as between CON and fronto‐parietal network (FPN), and between SMN with default mode network (DMN), and FPN contributed the most (Figure 1). Furthermore, we found that, in the high dementia risk group (CAIDE > 6) only, FC, mainly in DMN‐SMN and DMN‐CON (Figure 2), significantly predicted multisensory processing cognitive score (r = 0.114, p<0.05). Conclusion: Our results show that FC can be used to detect early brain changes associated with risk of future dementia in cognitively healthy individuals. This method has implications of the early detection of dementia in preclinical populations. [ABSTRACT FROM AUTHOR]

Background: Blood‐based biomarkers of Alzheimer's disease (AD) may help to rule AD in, with particular promise at the mild cognitive impairment (MCI) stage when potential disease‐modifying treatments may be most effective. However, AD is not the only common cause of cognitive impairment: Lewy body disease and other non‐AD pathologies are common and under‐recognised. Reliance on AD‐specific biomarkers alone may therefore contribute to missed diagnosis of non‐AD aetiologies. We aimed to examine the utility of emerging AD plasma biomarkers in identifying disease‐specific MCI due to AD (MCI‐AD), MCI with Lewy bodies (MCI‐LB) and in disease‐general MCI. We also aimed to compare these with alternative disease‐general biomarkers of neurodegeneration, and examined any change over time. Method: In a longitudinal study, plasma samples were collected for 172 participants (31 healthy controls, 48 MCI‐AD, 28 possible MCI‐LB and 65 probable MCI‐LB) at baseline, and a subset (n = 55) who provided repeated samples after ≥1 year. Samples were analysed with Simoa assays for Alzheimer's disease (Aβ42, Aβ40, ptau‐181) and neurodegeneration (GFAP and NfL) biomarkers. MCI cases were differentially classified as MCI‐AD or MCI‐LB by an expert panel of old age psychiatrists, based on current consensus diagnostic criteria, and including Lewy body disease‐specific imaging biomarkers. Age‐adjusted mixed effects models assessed any longitudinal changes over time in each biomarker, and associations with severity of cognitive impairment as assessed by the Addenbrooke's Cognitive Examination – Revised. Result: GFAP performed comparably to AD‐specific biomarkers in identifying any‐cause MCI (GFAP AUC = 0.75; ptau‐181 = 0.73), while maintaining good accuracy in identifying MCI‐AD specifically. AD biomarkers did not reliably distinguish MCI‐AD from MCI‐LB. Severity of cognitive impairment in any‐cause MCI and MCI‐AD was most strongly correlated with the disease‐nonspecific neurodegenerative biomarker NfL (r = 0.48, p = 0.005; cf. GFAP r = 0.23, p = 0.121), which progressively increased over time. Conclusion: Given the high prevalence of unrecognised non‐AD pathologies at autopsy (>1/3 cases in UK brain banks), blood biomarkers of neurodegeneration may be a useful alternative to AD‐specific biomarkers in screening for neurodegenerative disease in MCI. As AD biomarkers do not reliably differentiate MCI‐AD from MCI‐LB, there is a need for disease‐specific biomarkers of synucleinopathies. [ABSTRACT FROM AUTHOR]

Background: Carriership of the apolipoprotein ε4 (APOE4) allele confers a heightened risk for the development of Alzheimer's disease (AD). Cerebral blood flow (CBF) is decreased in prodromal and established AD, however findings in the preclinical stage are mixed, with some studies reporting increases. CBF can be impacted by many factors including the haematocrit. We investigated in a cohort at risk of developing AD how haematological variables relate to CBF and if this relationship is differentially moderated by APOE4. Method: 375 participants from the PREVENT‐Dementia study underwent arterial spin labelling (ASL) and structural 3Tesla MRI. ASL data were analysed using BASIL/FSL and structural scans with SPM12. CBF maps were corrected for partial volume effects. A vascular territory mask with nine territories, the middle, proximal and distal branches of the anterior, middle and posterior cerebral arteries (ACA, MCA, PCA) was used for region‐of‐interest analysis and registered to the native ASL space. Regional gray matter (GM) CBF values were harmonised using COMBAT. Linear regression was used to examine differences between APOE4 carriers and non‐carriers controlling for age, sex and years of education. Associations between haematological properties and CBF were examined with Pearson's correlations. Differential relationships between CBF, haematocrit, and measures of red blood cell size and shape (distribution width (RDW) and mean corpuscular volume (MCV)) were investigated by including interaction terms of APOE4 and haematological variables in the models. Result: APOE4 carriers had significantly higher CBF in the proximal MCA (t = 2.54, p = 0.01). Across all subjects, RDW and MCV were not associated with GM CBF, though several significant interactions were observed between APOE4 and RDW in predicting CBF (Figure 1). Haematocrit was associated with GM CBF (ρ = ‐0.19, p < 0.01). No significant interactions were seen between APOE4 and haematocrit or MCV in predicting CBF. Conclusion: The variability of the size and shapes of erythrocytes was differentially associated with CBF between APOE4 carriers and non‐carriers suggesting a different response to morphological erythrocyte alterations. This could further relate to underlying factors such as inflammation, which is associated with a higher RDW. Such associations should be examined in further studies. [ABSTRACT FROM AUTHOR]

Background: The relationship between sleep and dementia risk is complex, with both longer and shorter sleep duration being associated with cognitive decline. The thalamus has an important role in regulating the sleep‐wake cycle and structural changes may be a good marker of sleep abnormalities. Our aim was to investigate the association between dementia risk, sleep and the volume of thalamic nuclei. Method: We analysed baseline data from PREVENT‐dementia, a multicentre, prospective cohort study of cognitively intact participants aged 40 to 59 years, who were stratified according to presence of the ApoE4 allele and parental family history of dementia (FH+). Sleep data was collected using the Pittsburgh Sleep Quality Index (PSQI) which measures subjective sleep quality, latency, duration, efficiency, disturbances, medication use and daytime dysfunction. T1‐weighted 3T MRI images were analysed using Freesurfer (version 7.1.0) to determine the volume of the thalamus and its subnuclei, controlling for total intracranial volume. The score on the centre for epidemiologic studies depression scale and the number of analgesic medications, were also used as covariates in the analysis to control for mood and pain. The data was analysed in R Studio using robust logistic regression. Result: Complete data was available for 594 participants. The total PSQI score was lower in FH+ subjects (p = 0.046) but was not associated with ApoE4 status. FH+ subjects had smaller volumes of mediodorsal medial (p = 0.03) and lateral (p = 0.03) nuclei, longer sleep duration (p = 0.02), and counterintuitively less sleep‐related daytime dysfunction (p = 0.01) compared to controls. In the FH+ group, larger pulvinar nucleus was associated with better sleep quality (r = ‐0.17, p = 0.002). In apoE4 non‐carriers, a larger thalamus (r = ‐0.12, p = 0.02) and larger centromedian nucleus (r = ‐0.13, p = 0.01) were both associated with a lower total PSQI score. They also had an association between larger pulvinar (r = ‐0.11, p = 0.04) and centromedian (r = ‐0.14, p = 0.007) nuclei and increased sleep efficiency. Conclusion: Middle‐aged subjects with a FH+ had longer sleep duration and smaller thalamic volumes which may represent early neurodegenerative changes. Furthermore, we found an association between larger thalamic nuclei and better sleep variables, especially in ApoE4 non‐carriers, indicating that the thalamus may be an important imaging correlate of sleep quality. [ABSTRACT FROM AUTHOR]

Background: Cerebral microbleeds (CMB) are predictive of increased risk of dementia and stroke. Although commonly regarded as vascular markers, CMB can also stem from non‐vascular aetiologies like head injuries or traumatic brain injury (TBI), although these are often overlooked. Therefore, this study examines CMB in relation to TBI, and their differential causes (i.e., risk factors) and consequences (i.e., clinical outcomes). Method: In 605 healthy middle‐aged adults (aged 40‐59), CMB were rated on 3T susceptibility weighted imaging (SWI) MRI. TBI was assessed using the Brain Injury Screening Questionnaire (BISQ). TBI+ was defined as at least one blow to the head resulting in loss of consciousness (36.0%; n = 217). Memory was assessed using the COGNITO battery. Interaction analyses examined TBI*CMB interactions on hypertension, gait, and memory. Dominance analysis examined the relative contribution of TBI and vascular risk factors on predicting gait disturbances and memory. All models adjusted for sex, age, education, and study site. Result: TBI was related to higher CMB count (t = 2.06, p =.039), and were more common in males (48.3%) than females (28.0%) (Χ2 = 28.91, p<.001). Number of TBI events related to poorer memory (t = ‐2.62, p =.009) and gait disturbances (t = 3.54, p<.001). Interaction analyses demonstrated that hypertension (t = ‐2.26, p =.024), memory (t = 2.70, p =.007) and gait (t = ‐2.29, p =.023) were less closely related to CMB in individuals with greater number of TBI events, relative to those with fewer TBIs. Regionally, these interactions were significant for lobar CMB, but not deep subcortical CMB. Within the TBI+ group, dominance analysis demonstrated that number of TBI events outperformed vascular risk factors in predicting gait disturbances (Contribution to R2: TBI = 52.9%, vascular risk = 32.6%) and memory (TBI = 28.7%, vascular risk = 1.2%). Conclusion: CMB appeared to differ aetiologically and clinically in those with and without TBI. In individuals with TBI, TBI itself was the dominant driver of clinical deficits. When compared to CMB of presumed vascular origins cross‐sectionally, TBI‐related CMB may appear to be less detrimental. However, longitudinal analysis is required to determine how TBI‐related CMB differ in clinical trajectory and downstream pathologies. This study highlights the importance of differentiating between CMB of vascular origins vs. TBI in both research and clinically to aid prognosis and treatment decisions. [ABSTRACT FROM AUTHOR]

Background: First‐degree relatives of people with dementia (FH+) are at increased risk of developing Alzheimer's disease (AD). Identifying preclinical brain changes would facilitate both early quantifiable longitudinal disease monitoring and interventional trials. However, the literature of imaging changes in FH+ remains highly controversial. We aim to investigate "estimated years to onset of dementia" (EYOD) as a surrogate marker of preclinical progression and assessed whether FH+ approaching the parental age of dementia onset would express more severe patterns of longitudinal brain changes. Method: 89 FH+ persons underwent serial 3T‐MRI with T1‐MPRAGE, DWI and ASL (mean interval: 2 years). The longitudinal Freesurfer pipeline was used to segment hippocampal subfields and early‐AD regions. Partial‐volume corrected ASL data and DWI data were processed with FSL‐BASIL4 and DTI‐TK5. Small vessel disease was indexed with white matter hyperintensities (WMHs) (Figure 1). We applied linear mixed effects models to predict MRI changes relative to EYOD, accounting for age, gender, education and time from baseline. Secondary analyses examined the interaction of APOE‐ε4+ on proximity‐related brain changes. Result: A shorter EYOD was associated with progressive decrease in FA, increase in MD/RD and atrophy of the fusiform gyrus over time (Figure 2). Interaction analyses revealed that APOE‐ε4+ carriers showed significant longitudinal atrophy of the hippocampal subfields with shorter EYOD. In contrast, cortical perfusion increased before plateauing ∼10 years before estimated onset. There were no associations of EYOD with mean cortical thickness or WMHs (See Figure 3 for a summary of main findings). Conclusion: Our findings represent the first extensive characterisation of longitudinal brain changes associated with proximity to dementia in FH+. Individuals who are approaching their parental age of dementia onset may be showing incipient brain abnormalities, particularly amongst APOE‐ε4 carriers. The specificity our findings in early‐AD regions also confer support to biological validity of EYOD as a stage marker of preclinical progression. Further ongoing clinical follow‐up of our sample would provide critical validation of these findings. [ABSTRACT FROM AUTHOR]

Background: Subclinical brain changes in Alzheimer's disease (AD) are detectable many years before symptom onset. While cerebral small vessel disease (SVD) has been well‐established as a key pathology in AD, whether genetic predisposition to AD influences markers of SVD in midlife remains unclear. In this study, we compare the longitudinal change in SVD burden between cognitively healthy middle‐aged adults with and without genetic predisposition to AD, and their effect on cognitive decline. Method: 151 cognitively‐normal participants (age 52.0 ± 5.5; PREVENT‐Dementia study) underwent 3T MRI and cognitive assessment at baseline and two‐year follow‐up. Genetic predisposition to AD was assessed by family history of parental dementia (FH) and APOE4 carriership. White matter hyperintensity (WMH) volumes were segmented and manually corrected on FLAIR MRI and cerebral microbleeds (CMB) on susceptibility‐weighted imaging (Figure 1). WMH volume was adjusted for total intracranial volume and inverse‐normal transformed. SVD progression was compared between groups using ANCOVA and linear mixed modelling in R controlling for sex, age, and education. Result: Cross‐sectionally, WMH and CMB did not differ by FH or APOE4 status. However, longitudinal data showed greater WMH progression in FH+ subjects (t=3.94, p<.001) and APOE4+ (t=2.09, p=.038) (Figure 2). The effect of FH on WMH progression was stronger for periventricular WMH (t=3.65, p<.001; deep WMH: t=2.13, p=.035), while APOE4+ subjects displayed greater progression of deep (t=3.30, p=.001), but not periventricular WMH (t=1.17, p=.243). CMB progression did not differ by FH or APOE4 status. Significant three‐way interaction indicated that longitudinal decline in processing speed was associated with global and deep WMH progression in FH+ but not FH‐ subjects (global: t=2.05, p=.042; deep: t=2.90, p=.004; periventricular: t=0.87, p=.384) (Figure 3), while no effect was observed regarding APOE4 carriership. Conclusion: Cognitively‐healthy individuals with a genetic predisposition to AD displayed greater WMH progression in midlife. WMH progression was associated with longitudinal decline in processing speed in those with FH of parental dementia, but not in those without FH. Taken together, findings suggest that WMH progression is evident decades before dementia might occur, and may be of clinical relevance in predicting cognitive decline particularly in individuals at increased inherited risk of AD. [ABSTRACT FROM AUTHOR]

Background: The epigenetic mechanism of DNA methylation has been implicated in the pathophysiology of neurodegenerative disorders such as Lewy body dementia (LBD). DNA methylation profiling may help to identify novel treatment targets and early disease markers. We hypothesized that DNA methylation alterations are detectable in blood due the influence of genetic and environmental factors as well as immune system changes associated with LBD. Method: Genome‐wide DNA methylation profiling was carried out using reduced representation bisulfite sequencing in blood samples from 89 LBD patients and 67 controls. Fifty five LBD patients had amyloid PET imaging. Data processing was performed using FastQC, TrimGalore, Bismark and MethylKit. DNA methylation alterations at specific CpG sites as well as at promoter, CpG island and CpG shore regions were compared between LBD cases and controls. A log odds logistic regression was used to identify differential DNA methylation after adjusting for age, sex and smoking status. The false discovery rate (FDR) was used for correction for multiple testing. We also tested the diagnostic classification performance of the differentially methylated regions using receiver operating characteristic (ROC) curve analysis and examined the potential of DNA methylation as a predictor of amyloid PET positivity in LBD. Result: Two single CpG sites at TNFRSF1B and EMC6 and three CpG shore regions at ABCG5, ETAA1 and TENM4 reached genome‐wide significance in the differential DNA methylation analysis comparing LBD cases and controls. The combined panel of the top three differentially methylated CpG shores reached an area under the curve (AUC) of 0.91 for the diagnosis of LBD compared to controls (sensitivity 0.89, specificity 0.85). DNA methylation at TENM4 was associated with amyloid PET positivity in LBD with an AUC of 0.84 (sensitivity 0.99, specificity 0.55). Conclusion: Our data suggest that DNA methylation alterations in blood are observed in a cohort of LBD patients compared to controls. Our findings need to be replicated in larger cohorts and tested for specificity in LBD in order to explore their future potential as diagnostic markers and/or targets for novel therapeutics. [ABSTRACT FROM AUTHOR]

Background: Dementia with Lewy bodies (DLB), Parkinson's disease (PD) and Parkinson's disease dementia (PDD) are termed Lewy body diseases (LBDs). These neurodegenerative diseases are classified by the accumulation of alpha‐synuclein in neurons, forming Lewy bodies (LB). Whilst pathologically similar, symptomatic staging is different. Previous genome wide association studies (GWAS) have identified classic Alzheimer's disease (AD) and PD loci as risk loci in DLB. Therefore, we have used polygenic risk score (PRS) analysis to investigate the contribution of AD and PD variants in the LBDs. Method: DNA was extracted from bulk brain tissue from 481 individuals (162 controls, 95 DLB, 156 PDD and 68 PD) and genotyped on the Illumina global screening array. After a strict quality control and imputation pipeline, PRSs for multiple relevant traits using reference GWAS summary statistics were calculated using PRSice2. Result: Study groups have been sourced consisting of cases with PD, PDD and DLB based on LB deposition and clinical symptom staging. All groups, including controls are stratified for age and concomitant AD pathology. Assessing multiple PRSs for association with pathological development and clinical outcomes we have identified the contribution of genetic risk from related neurodegenerative and neuropsychiatric disorders in our cohort of PD, PDD and DLB samples. Conclusion: We have collated a well powered study cohort to interrogate the genetic basis of the Lewy body dementias and the relative contribution of AD and PD risk loci in the LBDs. We are currently generating methylation quantitative trait loci (mQTLs) for this dataset using previously generated matched DNA methylation data in the brain. [ABSTRACT FROM AUTHOR]

Background: The epigenetic mechanism of DNA methylation has been implicated in the pathophysiology of neurodegenerative disorders such as Lewy body dementia (LBD). DNA methylation profiling may help to identify novel treatment targets and early disease markers. We hypothesized that DNA methylation alterations are detectable in blood due the influence of genetic and environmental factors as well as immune system changes associated with LBD. Method: Genome‐wide DNA methylation profiling was carried out using reduced representation bisulfite sequencing in blood samples from 89 LBD patients and 67 controls. Fifty five LBD patients had amyloid PET imaging. Data processing was performed using FastQC, TrimGalore, Bismark and MethylKit. DNA methylation alterations at specific CpG sites as well as at promoter, CpG island and CpG shore regions were compared between LBD cases and controls. A log odds logistic regression was used to identify differential DNA methylation after adjusting for age, sex and smoking status. The false discovery rate (FDR) was used for correction for multiple testing. We also tested the diagnostic classification performance of the differentially methylated regions using receiver operating characteristic (ROC) curve analysis and examined the potential of DNA methylation as a predictor of amyloid PET positivity in LBD. Result: Two single CpG sites at TNFRSF1B and EMC6 and three CpG shore regions at ABCG5, ETAA1 and TENM4 reached genome‐wide significance in the differential DNA methylation analysis comparing LBD cases and controls. The combined panel of the top three differentially methylated CpG shores reached an area under the curve (AUC) of 0.91 for the diagnosis of LBD compared to controls (sensitivity 0.89, specificity 0.85). DNA methylation at TENM4 was associated with amyloid PET positivity in LBD with an AUC of 0.84 (sensitivity 0.99, specificity 0.55). Conclusion: Our data suggest that DNA methylation alterations in blood are observed in a cohort of LBD patients compared to controls. Our findings need to be replicated in larger cohorts and tested for specificity in LBD in order to explore their future potential as diagnostic markers and/or targets for novel therapeutics. [ABSTRACT FROM AUTHOR]

Background: Dementia with Lewy bodies (DLB), Parkinson's disease (PD) and Parkinson's disease dementia (PDD) are termed Lewy body diseases (LBDs). These neurodegenerative diseases are classified by the accumulation of alpha‐synuclein in neurons, forming Lewy bodies (LB). Whilst pathologically similar, symptomatic staging is different. Previous genome wide association studies (GWAS) have identified classic Alzheimer's disease (AD) and PD loci as risk loci in DLB. Therefore, we have used polygenic risk score (PRS) analysis to investigate the contribution of AD and PD variants in the LBDs. Method: DNA was extracted from bulk brain tissue from 481 individuals (162 controls, 95 DLB, 156 PDD and 68 PD) and genotyped on the Illumina global screening array. After a strict quality control and imputation pipeline, PRSs for multiple relevant traits using reference GWAS summary statistics were calculated using PRSice2. Result: Study groups have been sourced consisting of cases with PD, PDD and DLB based on LB deposition and clinical symptom staging. All groups, including controls are stratified for age and concomitant AD pathology. Assessing multiple PRSs for association with pathological development and clinical outcomes we have identified the contribution of genetic risk from related neurodegenerative and neuropsychiatric disorders in our cohort of PD, PDD and DLB samples. Conclusion: We have collated a well powered study cohort to interrogate the genetic basis of the Lewy body dementias and the relative contribution of AD and PD risk loci in the LBDs. We are currently generating methylation quantitative trait loci (mQTLs) for this dataset using previously generated matched DNA methylation data in the brain. [ABSTRACT FROM AUTHOR]

Background: The primary goal of large global studies investigating Alzheimer's Disease (AD) is to make meaningful and robust conclusions on cognitive outcomes. However, this is challenging due to the heterogeneous cognitive test batteries used across studies. Here, we use four international cohorts to derive robust and sensitive cross‐cohort cognitive composites. Methods: Using longitudinal neuropsychological data from four international cohorts1 (NIMROD,n=90,fu=2+‐1.34years; ADNI,n=2168,fu=3.13+‐3.03years; NUS,n=186,fu=3.44+‐1.47years; BACS,n=188,fu=4.22+‐3.27years) we generated two AD‐related cognitive composites. For cognitively normal (CN) individuals at baseline we generated a Cross‐Cohort Preclinical Alzheimer's Cognitive Composite (CC‐PACC). For individuals with MCI at baseline we generated a Cross‐Cohort Prodromal Alzheimer's Cognitive Composite (CC‐ProACC). We harmonised neuropsychological data across cohorts using k‐nearest neighbour's imputation resulting in a complete set of 139 item level cognitive variables (Figure 1). Using PCA on real and imputed values across all cohorts we derived single scores for memory, executive function and general cognition. We combined these values into either the CC‐PACC or the CC‐ProACC following established methodology[1]. To show AD‐related change in cognition we used linear mixed effects models to test the interaction of cortical amyloid status and time from baseline. We investigate cohort effects testing the 3‐way interaction of cohort, cortical amyloid status and time. For the ADNI preclinical cohort, we contrasted AD‐related change in the CC‐PACC against established measures (PACC[1]). Results: Annual change in the CC‐ProACC from baseline was significantly different for individuals who were amyloid positive vs. amyloid negative (F(1,2598)=97,β= ‐0.22,P<0.0001) (Figure 2a), no significant differences were observed between prodromal‐AD cohorts (ADNI‐NIMROD‐NUS) (F(2,2590)=2.33,P=0.1). Annual change in the CC‐PACC from baseline was significantly different for individuals who were amyloid positive vs. amyloid negative (F(1,1827)=37.4,β=‐0.14,P<0.0001) (Figure 2b), no significant differences were observed between preclinical‐AD cohorts (ADNI‐BACS) (F(1,1823)=1.56,P=0.21). For the preclinical ADNI cohort we show the CC‐PACC was 1.9‐times more sensitive than the PACC for measuring AD‐related cognitive decline (Figure 3). Conclusions: Our approach unifies and consolidates neuropsychological data from four global cohorts by deriving robust cross‐cohort preclinical (CC‐PACC) and prodromal (CC‐ProACC) AD cognitive composites. We demonstrate that the CC‐PACC outperforms the gold standard measure of preclinical‐AD cognitive decline (PACC), with twice the sensitivity for cognitive decline. 1COHORT, (n)number of individuals, (fu)mean duration of follow‐up+‐std. Reference: [1] Insel(2019),Neurology. [ABSTRACT FROM AUTHOR]

Background: The primary goal of large global studies investigating Alzheimer's Disease (AD) is to make meaningful and robust conclusions on cognitive outcomes. However, this is challenging due to the heterogeneous cognitive test batteries used across studies. Here, we use four international cohorts to derive robust and sensitive cross‐cohort cognitive composites. Methods: Using longitudinal neuropsychological data from four international cohorts1 (NIMROD,n=90,fu=2+‐1.34years; ADNI,n=2168,fu=3.13+‐3.03years; NUS,n=186,fu=3.44+‐1.47years; BACS,n=188,fu=4.22+‐3.27years) we generated two AD‐related cognitive composites. For cognitively normal (CN) individuals at baseline we generated a Cross‐Cohort Preclinical Alzheimer's Cognitive Composite (CC‐PACC). For individuals with MCI at baseline we generated a Cross‐Cohort Prodromal Alzheimer's Cognitive Composite (CC‐ProACC). We harmonised neuropsychological data across cohorts using k‐nearest neighbour's imputation resulting in a complete set of 139 item level cognitive variables (Figure 1). Using PCA on real and imputed values across all cohorts we derived single scores for memory, executive function and general cognition. We combined these values into either the CC‐PACC or the CC‐ProACC following established methodology[1]. To show AD‐related change in cognition we used linear mixed effects models to test the interaction of cortical amyloid status and time from baseline. We investigate cohort effects testing the 3‐way interaction of cohort, cortical amyloid status and time. For the ADNI preclinical cohort, we contrasted AD‐related change in the CC‐PACC against established measures (PACC[1]). Results: Annual change in the CC‐ProACC from baseline was significantly different for individuals who were amyloid positive vs. amyloid negative (F(1,2598)=97,β= ‐0.22,P<0.0001) (Figure 2a), no significant differences were observed between prodromal‐AD cohorts (ADNI‐NIMROD‐NUS) (F(2,2590)=2.33,P=0.1). Annual change in the CC‐PACC from baseline was significantly different for individuals who were amyloid positive vs. amyloid negative (F(1,1827)=37.4,β=‐0.14,P<0.0001) (Figure 2b), no significant differences were observed between preclinical‐AD cohorts (ADNI‐BACS) (F(1,1823)=1.56,P=0.21). For the preclinical ADNI cohort we show the CC‐PACC was 1.9‐times more sensitive than the PACC for measuring AD‐related cognitive decline (Figure 3). Conclusions: Our approach unifies and consolidates neuropsychological data from four global cohorts by deriving robust cross‐cohort preclinical (CC‐PACC) and prodromal (CC‐ProACC) AD cognitive composites. We demonstrate that the CC‐PACC outperforms the gold standard measure of preclinical‐AD cognitive decline (PACC), with twice the sensitivity for cognitive decline. 1COHORT, (n)number of individuals, (fu)mean duration of follow‐up+‐std. Reference: [1] Insel(2019),Neurology. [ABSTRACT FROM AUTHOR]

Introduction: Cerebral small vessel disease (CSVD) is associated with late‐onset Alzheimer's disease (LOAD) and might contribute to the relationship between apolipoprotein E ε4 (APOE ε4) and LOAD, in older people. However, it is unclear whether CSVD begins in middle age in individuals genetically predisposed to LOAD. Methods: We assessed the relationship between radiological markers of CSVD, white matter hyperintensities and microbleeds, and genetic predisposition to LOAD in a cross‐sectional analysis of cognitively normal subjects aged 40–59 years recruited from the PREVENT Dementia study. Results: Microbleed prevalence was 14.5%, and mean ± standard deviation white matter hyperintensity percentage of total brain volume was 0.41 ± 0.28%. There was no significant association between APOE ε4 carrier status or history of parental dementia and white matter hyperintensity volume (P =.713,.912 respectively) or microbleeds (P =.082,.562 respectively) on multiple regression. Discussion: Genetic predisposition to LOAD, through APOE genotype or AD family history, is not associated with CSVD in middle age. Highlights: Cerebral small vessel disease was assessed in middle‐aged subjects.Cerebral microbleed prevalence was 14.5%.Cerebral small vessel disease was not associated with APOE or parental history of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: Post‐mortem clinical studies and animal models described severe synaptic loss as an early feature of neurodegenerative disease, including frontotemporal dementia. Recently, PET radiotracers that bind to synaptic vesicle glycoprotein 2A have been developed and proven to enable in vivo quantification of synaptic loss in people with neurodegenerative diseases. This study used [11C]UCB‐J PET to quantify synaptic loss in people with behavioural variant frontotemporal dementia (bvFTD). Method: We recruited 10 people with a clinical diagnosis of bvFTD and 24 age‐ and sex‐matched healthy controls. Participants underwent dynamic [11C]UCB‐J PET‐MR, and a neuropsychological assessment, including the Addenbrooke's cognitive examination (ACE‐R) as a global measure of cognitive performance, and the INECO frontal screening. Synaptic density was estimated using [11C]UCB‐J non‐displaceable binding potential (BPND) at voxel level and in whole‐brain regions of interest. General linear models were used to compare [11C]UCB‐J binding voxel‐wise between groups, and correlate synaptic density with cognitive performance in bvFTD cohort. These analyses were also performed using regional [11C]UCB‐J binding potentials, with and without partial‐volume correction. Regional correlations were performed with both frequentist and Bayesian approaches. Result: People with bvFTD showed severe synaptic loss compared to controls at individual level and as a group. [11C]UCB‐J binding was significantly reduced bilaterally in medial and dorsolateral frontal regions, inferior frontal gyri, anterior and posterior cingulate gyrus, insula cortex and medial temporal lobe (5.1 ≤ t ≤ 9.3, p < 0.05 FWE at voxel level, Figure 1A). Results from ROI‐based analyses mirrored the voxel‐wise results, with and without partial‐volume correction. Synaptic loss in the left frontal and cingulate regions significantly correlated with cognitive impairments as assessed with ACE‐R and INECO (r > 0.8, p<0.001 at voxel level, p<0.05 FWE at cluster level, Figure 1B). Correlations were confirmed by regional‐based analyses, with both frequentist and Bayesian approaches (Figure 1C). Conclusion: Different analytic approaches converged showing a significant and widespread frontotemporal loss of synapses in symptomatic bvFTD, in proportion to disease severity. [11C]UCB‐J PET could therefore be a useful supporting tool for translational studies and experimental medicines strategies for new disease‐modifying treatments in this condition. [ABSTRACT FROM AUTHOR]

Introduction Although biomarker studies of late-onset Alzheimer's disease suggest pathology to be present decades before diagnosis, little is known about cognitive performance at this stage. Methods A sample of 210 adults (aged 40–59) of whom 103 have a parent diagnosed with dementia (family history subgroup) underwent computerized cognitive testing. Apolipoprotein E (apoE) status was determined, and 193 subjects had magnetic resonance imaging. Distance from dementia onset was estimated in relation to age of parental diagnosis, and Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Scores were calculated. Results Lower hippocampal volumes ( P = .04) were associated with poorer spatial location recall and higher Dementia Risk Scores with poorer visual recognition ( P = .0005), and lower brain and hippocampal volume ( P < .0001, P = .04, respectively). Family history subgroup participants closer to dementia onset had lower scores on visual working memory ( P = .05), whereas those with an APOE ε4 allele performed better on form perception ( P = .005). Discussion Middle-aged adults at risk of dementia show evidence of poorer cognitive performance, principally in visuospatial functions. [ABSTRACT FROM AUTHOR]

Background: Neuropsychiatric symptoms (NPS) in Lewy body diseases, including dementia with Lewy bodies (DLB) and Parkinson's disease (PD) dementia, occur frequently and at an early stage in disease progression. Such symptoms are significantly associated with quality of life, caregiver burden and functional limitations. Limited evidence exists, however, outlining the relationship between NPS and cognitive decline. Methods: Data from 217 participants were derived from three cohort studies. Patients diagnosed with either MCI with Lewy bodies (MCI‐LB, n = 67), PD‐MCI (n = 56) or Alzheimer's disease (MCI‐AD, n = 39) and a group of healthy older adults (n = 55) completed comprehensive neuropsychological and neuropsychiatric assessment and were followed up longitudinally for a median of three years. NPS identified at baseline by the Neuropsychiatric Inventory (NPI) were included as predictors in linear regressions and linear mixed effects models to assess the relationship between NPS and performance on a range of cognitive tests both at baseline and longitudinally. Results: At baseline, NPS were most prevalent and severe among the MCI‐LB group (49% with NPI score >4 in at least one symptom) and least prevalent in controls (7% with NPI score >4). Total NPI score was not related to baseline cognitive function in any domain in any group. Greater baseline total NPI score was associated with steeper rates of decline among PD‐MCI patients on a measure of processing speed (p =.01). Among healthy adults, only sleep disturbance was associated with steeper rates of decline on global cognition (p =.005). None of the patient groups showed any association between individual NPS and decline on a measure of global cognitive function. Conclusions: The lack of a significant relationship found between NPS and either global cognitive function or decline in global cognition seen among MCI patients suggests that at this prodromal stage of disease, NPS appear to be of limited clinical impact and indicates that the mechanisms of cognitive and neuropsychiatric symptoms may differ in early Lewy body disease. Future work will investigate these mechanisms using multimodal imaging data from this cohort. [ABSTRACT FROM AUTHOR]

Background: The Lewy body diseases, Dementia with Lewy bodies (DLB), Parkinson's disease (PD) and Parkinson's disease dementia (PDD) are all neurodegenerative diseases classified by the accumulation of alpha‐synuclein in neurons, forming Lewy bodies (LB). We hypothesise that these LBs cause epigenetic changes within neurons and surrounding cells and that these changes can be used to distinguish the different diseases from one another. Method: Bulk tissue from the cingulate gyrus and prefrontal cortex was analyzed on the Illumina Infinium Methylation EPIC array generating a quantitative measure of DNA methylation for over 850,000 CpG sites (n=∼100/disease group). Linear regression and pathway analyses were then used to identify loci that are significantly different or specific to each disease. Result: Study groups have been sourced consisting of cases with PD, PDD and DLB based on LB deposition and clinical symptom staging. Age‐matched control cases have been selected that have similar levels of concomitant AD pathology to the disease groups. We have identified significant changes in methylation associated with both phenotype and neuropathology alongside the cellular pathways these changes correspond with. Conclusion: We have collated a well powered study cohort to interrogate the epigenetic basis of neuropathological progression and clinical staging of LB disease, controlling for levels of concomitant AD pathology. We have completed DNA methylation analysis for two disease relevant brain regions and identified both phenotype neuropathology associated changes within these regions. Processing of samples for fluorescence activated nuclei sorting (FANS) and laser capture microdissection (LCM) has begun (n=15/group) to assess the cell type specificity of the methylation changes and the effect of Lewy bodies on neuronal methylation respectively. [ABSTRACT FROM AUTHOR]

Background: Sex differences exist in the prevalence, prognosis, and clinical manifestation of cerebral small vessel disease (SVD) and dementia. Given the role of SVD in cognitive impairment – both directly and through accelerating neurodegenerative pathology – understanding sex differences in SVD risk factors could inform targeted intervention strategies. In this longitudinal study, we examined sex differences in the effects of age and hypertension on SVD at midlife. Method: 185 cognitively‐healthy midlife adults underwent 3T MRI at baseline and two‐year follow‐up. SVD markers were white matter hyperintensities (WMH) volume, enlarged perivascular spaces, microbleeds, lacunes, and global SVD burden (composite score of all four SVD markers). Piecewise linear regression analysis estimated change‐points in age, beyond which WMH accelerates. To examine sex as a moderator of age and hypertension on SVD cross‐sectionally, interaction analysis was conducted in general linear models, adjusting for age and education. To assess interactions on longitudinal SVD progression, linear mixed effects models were fitted, adjusting for the same covariates and random intercept of subjects. Result: Males were twice as likely to have hypertension compared to females (males:53.8%, females:26.4%, X2=7.97, p=.005). Interaction analysis demonstrated that the effect of hypertension on SVD was amplified in females, compared to males, both cross‐sectionally (WMH: t=2.42, p=.017) and longitudinally (WMH progression: t=3.37, p<.001; new microbleeds: t=2.57, p=.011) (Fig 1). Findings remained consistent when additionally controlling for antihypertensive medication. In terms of age, piecewise linear regression estimated a WMH change‐point at age 50.2 (SE=3.2) in the whole sample, 50.6 years (SE=3.8) in males, but was undetectable in females (Fig 2). Sex*age interaction demonstrated that the effect of age on global SVD burden was amplified in males compared to females (t=‐2.43, p=.016) (Fig 3). Sex*age*hypertension interaction showed that hypertension intensified the effect of age on global SVD burden in males but not females (t=‐2.67, p=.008), for whom hypertension was a stronger predictor than age. Conclusion: Older men (especially those with hypertension) and women with hypertension (regardless of age) were at greatest risk of SVD. Our findings highlight the importance of hypertension management as early as midlife in relation to SVD, but suggest that this may be especially effective for women. [ABSTRACT FROM AUTHOR]

Background: Frontotemporal dementia is clinically and neuropathologically heterogeneous, but atrophy, neuroinflammation, and executive dysfunction occur in each of the principal variants. Across the clinical spectrum of frontotemporal dementia, we assessed the predictive value of in vivo neuroimaging measures of grey‐matter volume (from structural MRI) and microglial activation (from [11C]PK11195 PET) on the rate of future executive decline. We hypothesised a detrimental effect of inflammation and atrophy severity on executive dysfunction progression. Method: Thirty patients with frontotemporal dementia underwent a baseline multi‐modal imaging assessment, including [11C]PK11195 PET to index microglial activation and structural MRI for atrophy, as part of the Neuroimaging of Inflammation in Memory and Related Other Disorders (NIMROD) study. Cognitive impairments were assessed at baseline and serially for up to 5 years with the revised Addenbrooke's Cognitive Examination (ACE‐R). Regional grey‐matter volumes and [11C]PK11195 binding potentials were averaged in four regions of interest: left and right frontal and temporal lobes. Linear mixed models were applied to the longitudinal ACE‐R attention/executive sub‐score. Regional CSF‐corrected PET values and TIV‐corrected grey‐matter volumes were included in linear mixed models as predictors, with age and education as covariates. Specifically, negative associations of atrophy and inflammation with annual rate of executive decline were tested. Result: Patients showed a mean 3.3‐point loss per year on the ACE‐R attention/executive sub‐score (p<0.001, Figure 1). Faster decline in ACE‐R was associated with reduced baseline grey‐matter volume of the left frontal lobe (beta=1.000, SE=0.285, p=0.000789, p‐FDR= 0.00316; Figure 2) and increased inflammation in frontal regions bilaterally (Left: beta=‐0.722, SE=0.251, p=0.00528, p‐FDR=0.0105, Figure 2; Right: Estimate=‐0.623, SE=0.256, p=0.0175, p‐FDR=0.0233). These associations remain significant when including both left frontal grey‐matter volume and [11C]PK11195 binding as predictors in the same model, and after controlling for baseline attention/executive scores. In these regions, grey‐matter volumes and inflammation levels were negatively correlated (left: r=‐0.414, p<0.001; right: r=‐0.374, p<0.001). Conclusion: Imaging markers for atrophy and microglial activation provide useful and independent information to evaluate and stratify patients with frontotemporal dementia. This may improve cohort selection in clinical trials and highlights the potential for immunomodulatory treatment strategies in frontotemporal dementia. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is implicated in the pathogenesis of neurodegenerative disorders including dementia with Lewy bodies (DLB), but its relationship with disease progression, including cognitive decline, is less well understood. We investigated the predictive value of microglial activation, assessed in vivo using positron emission tomography (PET) imaging with [11C]PK11195, on the rate of annual cognitive decline in patients with DLB. We hypothesised a detrimental effect of inflammation on cognition over time. Method: Nineteen patients with DLB underwent baseline assessment, including [11C]PK11195 PET and cognitive tests from the Neuroimaging of Inflammation in Memory and Related Other Disorders (NIMROD) study. Cognitive performance was then assessed at an average of 1.1‐year intervals (standard deviation (SD) ± 0.03 years) up to 3.4 years (average ± SD = 3.20 ± 0.16) using the revised Addenbrooke's Cognitive Examination (ACE‐R) and Cambridge Neuropsychological Test Automated Battery (CANTAB). Regional [11C]PK11195 binding potential values were included in a principal component analysis (PCA). Linear mixed effects models were applied to the longitudinal ACE‐R scores. Individual component scores were included in analysis of interaction with time to test for associations between [11C]PK11195 uptake at baseline and longitudinal cognitive performance scores. Age and sex were included as covariates in the models. Result: Patients showed a mean 8.8‐point loss per year on the ACE‐R total score (p<0.001) (Figure 1, left panel). The PCA identified five components, explaining >80% of variance. Annual rate of change in the ACE‐R total score (estimate=‐2.90, p=0.0226) (Figure 1, right panel), memory (estimate=‐1.14, p=0.004) and attention/executive function (estimate=‐0.80, p=0.022) sub‐scores was negatively associated with increased microglial activation in component #4, which was mainly loaded onto the hippocampus, amygdala and pallidum but also parahippocampal cortex and the pre‐subgenual frontal area. Conclusion: Higher levels of neuroinflammation in medial temporal regions and pallidum predict faster cognitive decline in patients with DLB, particularly in the domains of memory and attention/executive function. Our results encourage the application of [11C]PK11195 PET in DLB to inform prognosis, and to improve patient stratification for clinical trials. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the impact of an acute assessment unit (AAU) on length of hospital stay (LOS), emergency department (ED) waiting times, direct discharge rate, unplanned readmission rate and all-cause hospital mortality of general medical patients.Design and Setting: Retrospective comparison of data for general medical patients admitted to a tertiary teaching hospital in Adelaide, South Australia, before and after the establishment of an AAU (reference years, 2003 [before] and 2006 [after]).Main Outcome Measures: Mean LOS, ED waiting times and all-cause hospital mortality during calendar years 2003 (pre-establishment) and 2006 (post-establishment).Results: Following the establishment of an AAU, the mean LOS shortened (from 6.8 days in 2003 to 5.7 days in 2006; P < 0.001) despite a 50.5% increase in the number of admissions (from 2652 to 3992). The number of admitted patients waiting in the ED more than 8 hours for a hospital bed decreased (from 28.7% to 17.9%; P < 0.001), as did the number waiting more than 12 hours (from 20.2% to 10.4%; P < 0.001). The rates of unplanned readmission within 7 and 28 days did not change. The all-cause hospital mortality for general medical admissions was 4.6% in 2003 v 3.7% in 2006 (P = 0.056).Conclusion: The establishment of an AAU within the general medical service coincided with decreases in both LOS and ED waiting times, despite a 50% increase in admissions. This structural reform in the process of acute medical care may have contributed to the improvement in these key health care performance indices without compromising the quality of patient care. [ABSTRACT FROM AUTHOR]

The article focuses on a study that determined the impact of an acute assessment unit (AAU) on patient treatment and hospital operations. Data in the study were gathered from records acquired from general medical patients admitted in a tertiary teaching hospital in Adelaide, South Australia before and after the establishment of an AAU, covering the years 2003 and 2006. Results revealed that despite a 50% increase in admissions, length of hospital stay (LOS) and emergency department (ED), waiting times decreased.

Background: Progressive Supranuclear Palsy (PSP) is associated with tau pathology and neurodegeneration, particularly in basal ganglia, diencephalon, and brainstem. Recently, neuroinflammation has been recognized as another key aspect in the pathophysiology of PSP. Understanding whether these three pathological features predict the clinical progression is crucial to develop new prognostic measures. Here, we studied how baseline assessments of in vivo tau pathology (measured by [18F]AV‐1451 PET), neuroinflammation ([11C]PK11195 PET), and atrophy (structural MRI) predicted longitudinal clinical changes in n=17 patients with PSP‐Richardson's syndrome. Method: All patients underwent a baseline multi‐modal assessment with [18F]AV‐1451 PET, [11C]PK11195 PET, and structural MRI. They were clinically assessed up to 4 years, with the PSP rating scale. Regional PET binding potentials and grey‐matter volumes across all brain regions were summarised by method‐specific Principal Component Analyses (PCAs). A linear mixed model was applied to the longitudinal PSP rating scale scores to estimate the rate of annual decline in each participant. We regressed the individuals' estimated rate of clinical progression on neuroimaging components, to identify the prognostic value of PET and MRI markers in different clusters of regions, with age and time between scan and the first clinical assessment as covariates. Result: PCAs identified four components for each ligand, reflecting the relative expression of tau pathology or neuroinflammation in distinct groups of brain regions, and seven components of grey‐matter volumes. Patients showed an average increase of 6.15 points (p<0.0001) per year on the PSP rating scale. PCA‐derived components reflecting tau burden (r=0.639, p=0.010) and neuroinflammation (r=0.596, p=0.019) in PSP‐related subcortical areas were linked to the annual rate of change of disease severity. These pathology markers components were associated with atrophy of the same regions (tau: r=‐0.626, p=0.007; neuroinflammation: r=‐0.584, p=0.014) but atrophy did not correlate with clinical progression (r=‐0.474, p=0.074). Conclusion: In vivo PET markers of both tau pathology and neuroinflammation in subcortical regions predicted clinical progression in PSP patients. Our results encourage the application of [18F]AV‐1451 and [11C]PK11195 PET in PSP as stratification measures that inform prognosis, to develop new targeting disease‐modifying therapies and empower clinical trials. [ABSTRACT FROM AUTHOR]

Background: It is now well‐established that pathological brain alterations in Alzheimer's disease (AD) patients start occurring decades before symptom onset. The earliest detectable neuroimaging finding during the disease's preclinical stage is amyloid plaque deposition. During the disease's prodromal period, hippocampal atrophy is observed. However, it has been suggested that individual hippocampal subfields might demonstrate atrophy at an earlier stage. Our goal in the present study was to investigate the volume of individual hippocampal subfields along with their rate of volumetric change in cognitively normal middle‐aged subjects at high risk of AD using multi‐modal MRI. Method: PREVENT‐Dementia study participants were recruited based on their dementia family history (FH). The participants' age ranged between 40 and 59 years old and they were scanned at two time‐points (visit 1: 183 participants; visit 2: 155 participants). Hippocampal subfields were segmented using Freesurfer and information from a T1‐weighted MPRAGE scan (TR=2.3s /TE=2.98ms ,voxel size=1mm3) and a high‐resolution T2 coronal hippocampal acquisition (TR=9s/TE=94ms, voxel size=0.4x0.4x4.0mm3). The volume of the subiculum, CA1, CA2‐3, dentate gyrus & CA4, molecular layer, hippocampal fissure, hippocampal tail and the whole hippocampus were quantified and normalised to total brain volume. The volume of each subfield along with its rate of volumetric change were compared between FH positive and negative subjects and APOE ε4 carriers and non‐carriers using linear regression with age, sex and years of education as covariates. Result: APOE ε4 carriers had a significantly decreased molecular layer volume (figure 1) compared to controls at both study time‐points (visit 1: p < 0.01; visit2: p = 0.02). There were no other differences in the examined subfields, whole hippocampal volume and the rate of volumetric change between the groups. Conclusion: The molecular layer encompasses the stratum radiatum lacunosum and moleculare which is one of the earliest regions to be influenced in AD and has demonstrated high efficiency in separating amyloid positive and negative subjects. Our results suggest that the molecular layer could be amongst the first hippocampal subfields to demonstrate an atrophic pattern in mid‐aged APOE ε4 carriers, in the absence of whole hippocampal, CA1 or subiculum atrophy. [ABSTRACT FROM AUTHOR]

Background: First‐degree relatives of people with dementia (FH+) are at increased risk of developing Alzheimer's disease (AD). Identifying preclinical brain changes would facilitate both early quantifiable longitudinal disease monitoring and interventional trials. However, the literature of imaging changes in FH+ remains highly controversial. We aim to investigate "estimated years to onset of dementia" (EYOD) as a surrogate marker of preclinical progression and assessed whether FH+ approaching the onset of dementia would express more severe patterns of longitudinal brain changes. Method: 89 FH+ persons underwent serial 3T‐MRI with T1‐MPRAGE, DWI and ASL (mean interval: 2 years). The longitudinal Freesurfer pipeline was used to segment hippocampal subfields and early‐AD regions. Partial‐volume corrected ASL data and DWI data were processed with FSL‐BASIL4 and DTI‐TK5. Small vessel disease was indexed with white matter hyperintensities (WMHs) (Figure 1). We applied linear mixed effects models with random intercepts to predict MRI changes relative to baseline EYOD, accounting for baseline age, gender, education and time from baseline. Secondary analyses examined the interaction of APOE‐ε4+ on proximity‐related brain changes. Result: A shorter EYOD was associated with progressive decrease in FA, increase in MD/RD and atrophy of the fusiform gyrus over time (Figure 2). Interaction analyses revealed that APOE‐ε4+ carriers showed significant longitudinal atrophy of the hippocampal subfields with shorter EYOD. In contrast, cortical perfusion increased before plateauing ∼10 years before estimated onset. There were no associations of EYOD with mean cortical thickness or WMHs (See Figure 3 for a summary of main findings). Conclusion: Our findings represent an extensive characterisation of longitudinal brain changes associated with proximity to dementia in FH+. Individuals who are approaching their parental age of dementia onset may be showing incipient brain abnormalities, particularly amongst APOE‐ε4 carriers. The involvement of early‐AD regions also confer support to the biological validity of EYOD as a stage marker of preclinical progression. Further clinical follow‐up of our sample would provide critical validation of these findings. [ABSTRACT FROM AUTHOR]

Background: Lewy body dementia (LBD) includes dementia with Lewy bodies and Parkinson's disease dementia, which shared a common pathological core feature of cognitive fluctuations. However, the clinical identification of fluctuations is still controversial. With Electroencephalogram (EEG) and Magnetoencephalography (MEG), it becomes possible to observe the neural correlates of fluctuations with a high temporal resolution in LBD. In this multimodel imaging and computational modelling of dementia with lewy bodies (MILOS) study, we combined EEG/MEG to explore the electro‐magnetic biomarkers of fluctuations in LBD. We hypothesized that LBD would show an increased variation in EEG/MEG compared with controls, indicating a potential underlying mechanism for fluctuations in LBD. Method: Nine patients with LBD (mean age=72) and twelve healthy controls (mean age=67) were recruited and an animal/non‐animal object recognition task was conducted. 64‐channel EEG and 306‐channel MEG (including gradiometer (GRM) and magnetometer (MAG)) were simultaneously recorded during this task. Subsequently participants had MRI with T1‐weighted images for EEG/MEG source coregistration. Forward models for EEG/MEG were 3‐Shell Sphere and Single Shell respectively and minimum norm Least‐Squares as the inversion method. The variations of source post‐stimulus in object recognition was assessed. We used standardized clinical batteries to test cognitive functions and overall scalp sensors for EEG/MEG sensor‐level analyses. Result: HC had shorter reaction time and higher accuracy rate than LBD in object recognition. The variations of reaction time across trials in object recognition was significantly higher in LBD than HC. LBD had weaker overall EEG amplitudes and stronger MEG variations across trials for post stimulus than HC. Phase lock value (PLV) indicated different EEG synchronization patterns between groups with higher theta and lower beta synchronization in LBD than HC. The MEG variations across trials in LBD were involved with theta, alpha and beta bands. The MEG variations were negatively correlated with MMSE, ACER, ACE‐III but positively correlated with UPDRS scores. Source variations in LBD involved a network of parietal areas, including postcentral gyrus and superial parietal areas. Conclusion: Our study revealed the possible biomarkers of fluctuations in LBD by using EEG/MEG. It highlighted the importance of electrophysiological correlates of fluctuations in understanding the etiology of LBD. [ABSTRACT FROM AUTHOR]

Background: Visual hallucinations (VH) are a common symptom in Lewy body dementias (LBD), which comprise dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD). Previous studies investigated functional brain network alteration associated with VH in different diseases. However, there is a lack of studies on VH in LBD, and a clear picture of the affected pathways is still missing. In this study, we used electroencephalography (EEG) to detect the weakened cortical connections and the functionally disconnected cortical regions in LBD with VH. Method: Resting state eyes closed EEG signals (128 channels) were recorded from 45 LBD participants: 18 without VH (eight DLB) and 27 with VH (13 DLB). EEG time series were filtered (bandpass: 8‐13 Hz), and cleaned from artefacts. Magnetic resonance imaging (MRI) recordings were individually obtained with magnetisation prepared rapid gradient echo (MPRAGE) sequence, and source estimation was performed with sLORETA technique (Destrieux atlas). Connectivity was measured with weighted phase lag index (WPLI), and assessed with Network Based Statistics (NBS), including the MMSE score as covariate. Node strengths of the subnetworks detected with NBS was computed. The visual hallucination score was collected through the NPI questionnaire. Result: The NBS revealed two subnetworks affected in VH, both comprising regions belonging to the visual ventral pathway (p<0.05, t>3.8). The first one (Figure 1) comprised connections between the right temporal lobe and the prefrontal cortex, which showed reduced strength. In the second one (Figure 2), contra‐lateral connectivity between occipital and right infra‐temporal lobe was significantly weakened. Conclusion: We propose a topography of the subnetworks affected in LBD with VH. The first and second subnetworks comprise regions involved respectively in the top‐down and bottom‐up visual perception streams. Our results resonate with the literature related to the pathology of LBD and VH. We found indeed that both affected subnetworks comprise the right inferior temporal lobe, which has been previously found to show a great burden of Lewy bodies in patients with VH. Our results support EEG as a suitable biomarker for assessing the severity of the pathology, and providing useful insights into the disease. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is part of the pathophysiology of Alzheimer's disease (AD), in addition to amyloid‐β plaques and tau neurofibrillary tangles. PET markers of microglial activation have indicated inflammation of temporo‐parietal regions, in proportion to disease severity. Here we test the prognostic value of [11C]PK11195 PET on longitudinal clinical decline in AD, alone and in combination with MRI and tau ([18F]AV‐1451) PET imaging. Method: Twenty‐six patients with Alzheimer's dementia or amyloid‐positive Mild Cognitive Impairment, and 29 controls underwent multi‐modal assessment with [11C]PK11195 PET, [18F]AV‐1451 PET, structural MRI, and annual cognitively assessment with the Revised Addenbrooke's Cognitive Examination. Regional PET binding potentials and grey‐matter volumes from fifteen bilateral temporo‐parietal region were summarised by method‐specific Principal Component Analyses (PCAs). The rate of longitudinal cognitive decline was estimated using a Latent Growth Curve Model. The predictive value of PET and MRI on cognitive decline was tested with modality‐specific regression models, and a multi‐modality regression model. Result: PCA on each PET ligand consistently identified one component in anterior temporal regions, and another in posterior temporo‐parietal regions, while for MRI, a single component was identified across all regions. Worse annual rate of cognitive decline correlated with higher [11C]PK11195 in the anterior temporal component (r = −0.47, p = 0.002), and in posterior temporo‐parietal regions (r = −0.39, p = 0.012). An optimal multi‐modality model was identified by stepwise regression and Bayesian selection, that included the anterior [11C]PK11195 component and both [18F]AV‐1451 components as predictors of cognitive decline (R2 = 0.418; p = 0.001), but not their interaction and not the baseline MRI. Conclusion: These results suggest that in addition to tau pathology, microglial activation in the anterior temporal lobe plays a key role in predicting future cognitive decline in patients with AD. The results support therapeutic strategies targeting tau and microglial activation as disease‐modifying therapy against AD. [ABSTRACT FROM AUTHOR]

Background: The Lewy body diseases, Dementia with Lewy bodies (DLB), Parkinson's disease (PD) and Parkinson's disease dementia (PDD) are all neurodegenerative diseases classified by the accumulation of alpha‐synuclein in neurons, forming Lewy bodies (LB). We hypothesise that these LBs cause epigenetic changes within neurons and surrounding cells and that these changes can be used to distinguish the different LB diseases from one another. Method: Bulk tissue from the cingulate gyrus and prefrontal cortex will be as analysed for DNA methylation levels using the Illumina Infinium Methylation EPIC array to generate quantitative methylation data for over 850,000 CpG sites across the genome (n=∼100/disease group). Linear regression and pathway analyses will be used to identify loci that are significantly different or specific to each disease. Following this we will validate loci and determine their cellular specificity using a subset of samples (15 DLB, 15 PDD, 15 PD only, 15 controls) using fluorescence activated cell sorting (FACS). In each sample we will isolate various different cellular populations, including neurons, microglia, oligodendrocytes and astrocytes before profiling these using the EPIC array. Result: Study groups have been sourced consisting of cases with PD, PDD and DLB based on LB deposition and clinical symptom staging. Control cases have been selected for matched age and levels of concomitant AD pathology. Cases for FACS (n=15/group) have been selected to allow where possible a high base RIN, pH and minimal post‐mortem interval. Conclusion: We are collating a well powered study cohort to interrogate the epigenetic basis of neuropathological progression and clinical staging of LB disease, controlling for levels of concomitant AD pathology. Follow up FACS sorting and analysis will allow for the cell specific methylation changes occurring in each of the LB diseases. [ABSTRACT FROM AUTHOR]