SummaryBackgroundMidlife hypertension confers increased risk for cognitive impairment in late life. The sensitive period for risk exposure and extent that risk is mediated through amyloid or vascular-related mechanisms are poorly understood. We aimed to identify if, and when, blood pressure or change in blood pressure during adulthood were associated with late-life brain structure, pathology, and cognition.MethodsParticipants were from Insight 46, a neuroscience substudy of the ongoing longitudinal Medical Research Council National Survey of Health and Development, a birth cohort that initially comprised 5362 individuals born throughout mainland Britain in one week in 1946. Participants aged 69–71 years received T1 and FLAIR volumetric MRI, florbetapir amyloid-PET imaging, and cognitive assessment at University College London (London, UK); all participants were dementia-free. Blood pressure measurements had been collected at ages 36, 43, 53, 60–64, and 69 years. We also calculated blood pressure change variables between ages. Primary outcome measures were white matter hyperintensity volume (WMHV) quantified from multimodal MRI using an automated method, amyloid-β positivity or negativity using a standardised uptake value ratio approach, whole-brain and hippocampal volumes quantified from 3D-T1 MRI, and a composite cognitive score—the Preclinical Alzheimer Cognitive Composite (PACC). We investigated associations between blood pressure and blood pressure changes at and between 36, 43, 53, 60–64, and 69 years of age with WMHV using generalised linear models with a gamma distribution and log link function, amyloid-β status using logistic regression, whole-brain volume and hippocampal volumes using linear regression, and PACC score using linear regression, with adjustment for potential confounders.FindingsBetween May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. 465 participants (238 [51%] men; mean age 70·7 years [SD 0·7]; 83 [18%] amyloid-β-positive) were included in imaging analyses. Higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) at age 53 years and greater increases in SBP and DBP between 43 and 53 years were positively associated with WMHV at 69–71 years of age (increase in mean WMHV per 10 mm Hg greater SBP 7%, 95% CI 1–14, p=0·024; increase in mean WMHV per 10 mm Hg greater DBP 15%, 4–27, p=0·0057; increase in mean WMHV per one SD change in SBP 15%, 3–29, p=0·012; increase in mean WMHV per 1 SD change in DBP 15%, 3–30, p=0·017). Higher DBP at 43 years of age was associated with smaller whole-brain volume at 69–71 years of age (−6·9 mL per 10 mm Hg greater DBP, −11·9 to −1·9, p=0·0068), as were greater increases in DBP between 36 and 43 years of age (−6·5 mL per 1 SD change, −11·1 to −1·9, p=0·0054). Greater increases in SBP between 36 and 43 years of age were associated with smaller hippocampal volumes at 69–71 years of age (−0·03 mL per 1 SD change, −0·06 to −0·001, p=0·043). Neither absolute blood pressure nor change in blood pressure predicted amyloi...

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer’s disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer’s disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer’s disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer’s disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer’s disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer’s disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer’s disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer’s disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer’s disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer’s disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.

ObjectivesThe Rare Dementia Support (RDS) Impact study will be the first major study of the value of multicomponent support groups for people living with or supporting someone with a rare form of dementia. The multicentre study aims to evaluate the impact of multicomponent support offered and delivered to people living with a rare form of dementia, comprising the following five work packages (WPs): (a) longitudinal cohort interviews, (b) theoretical development, (c) developing measures, (d) novel interventions, and (e) economic analysis.MethodsThis is a mixed‐methods design, including a longitudinal cohort study (quantitative and qualitative) and a feasibility randomised control trial (RCT). A cohort of more than 1000 individuals will be invited to participate. The primary and secondary outcomes will be in part determined through a co‐design nominal groups technique prestudy involving caregivers to people living with a diagnosis of a rare dementia. Quantitative analyses of differences and predictors will be based on prespecified hypotheses. A variety of quantitative (eg, analysis of variance [ANOVA] and multiple linear regression techniques), qualitative (eg, thematic analysis [TA]), and innovative analytical methods will also be developed and applied by involving the arts as a research method.ResultsThe UCL Research Ethics Committee have approved this study. Data collection commenced in January 2020.ConclusionsThe study will capture information through a combination of longitudinal interviews, questionnaires and scales, and novel creative data collection methods. The notion of “impact” in the context of support for rare dementias will involve theoretical development, novel measures and methods of support interventions, and health economic analyses.

ObjectiveTo investigate predictors of performance on a range of cognitive measures including the Preclinical Alzheimer Cognitive Composite (PACC) and test for associations between cognition and dementia biomarkers in Insight 46, a substudy of the Medical Research Council National Survey of Health and Development.MethodsA total of 502 individuals born in the same week in 1946 underwent cognitive assessment at age 69–71 years, including an adapted version of the PACC and a test of nonverbal reasoning. Performance was characterized with respect to sex, childhood cognitive ability, education, and socioeconomic position (SEP). In a subsample of 406 cognitively normal participants, associations were investigated between cognition and β-amyloid (Aβ) positivity (determined from Aβ-PET imaging), whole brain volumes, white matter hyperintensity volumes (WMHV), and APOE ε4.ResultsChildhood cognitive ability was strongly associated with cognitive scores including the PACC more than 60 years later, and there were independent effects of education and SEP. Sex differences were observed on every PACC subtest. In cognitively normal participants, Aβ positivity and WMHV were independently associated with lower PACC scores, and Aβ positivity was associated with poorer nonverbal reasoning. Aβ positivity and WMHV were not associated with sex, childhood cognitive ability, education, or SEP. Normative data for 339 cognitively normal Aβ-negative participants are provided.ConclusionsThis study adds to emerging evidence that subtle cognitive differences associated with Aβ deposition are detectable in older adults, at an age when dementia prevalence is very low. The independent associations of childhood cognitive ability, education, and SEP with cognitive performance at age 70 have implications for interpretation of cognitive data in later life.

Introduction This work aims to characterize the sequence in which cognitive deficits appear in two dementia syndromes. Methods Event‐based modeling estimated fine‐grained sequences of cognitive decline in clinically‐diagnosed posterior cortical atrophy (PCA) ( ) and typical Alzheimer's disease (tAD) ( ) at the UCL Dementia Research Centre. Our neuropsychological battery assessed memory, vision, arithmetic, and general cognition. We adapted the event‐based model to handle highly non‐Gaussian data such as cognitive test scores where ceiling/floor effects are common. Results Experiments revealed differences and similarities in the fine‐grained ordering of cognitive decline in PCA (vision first) and tAD (memory first). Simulation experiments reveal that our new model equals or exceeds performance of the classic event‐based model, especially for highly non‐Gaussian data. Discussion Our model recovered realistic, phenotypical progression signatures that may be applied in dementia clinical trials for enrichment, and as a data‐driven composite cognitive end‐point.

Current models of progression in neurodegenerative diseases use neuroimaging measures that are averaged across pre-defined regions of interest (ROIs). Such models are unable to recover fine details of atrophy patterns; they tend to impose an assumption of strong spatial correlation within each ROI and no correlation among ROIs. Such assumptions may be violated by the influence of underlying brain network connectivity on pathology propagationa strong hypothesis e.g. in Alzheimer's Disease. Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from shortterm longitudinal data sets. DIVE clusters vertex-wise (i.e. point-wise) biomarker measurements on the cortical surface that have similar temporal dynamics across a patient population, and concurrently estimates an average trajectory of vertex measurements in each cluster. DIVE uniquely outputs a parcellation of the cortex into areas with common progression patterns, leading to a new signature for individual diseases. DIVE further estimates the disease stage and progression speed for every visit of every subject, potentially enhancing stratification for clinical trials or management. On simulated data, DIVE can recover ground truth clusters and their underlying trajectory, provided the average trajectories are sufficiently different between clusters. We demonstrate DIVE on data from two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Dementia Research Centre (DRC), UK. The DRC cohort contains patients with Posterior Cortical Atrophy (PCA) as well as typical Alzheimer's disease (tAD). DIVE finds similar spatial patterns of atrophy arXiv:1901.03553v1 [cs.CV] 11 Jan 2019 for tAD subjects in the two independent datasets (ADNI and DRC), and further reveals distinct patterns of pathology in different diseases (tAD vs PCA) and for distinct types of biomarker datacortical thickness from Magnetic Resonance Imaging (MRI) vs amyloid load from Positron Emission Tomography (PET). We demonstrate that DIVE stages have potential clinical relevance, despite being based only on imaging data, by showing that the stages correlate with cognitive test scores. Finally, DIVE can be used to estimate a fine-grained spatial distribution of pathology in the brain using any kind of voxelwise or vertexwise measures including Jacobian compression maps, fractional anisotropy (FA) maps from diffusion tensor imaging (DTI) or other PET measures.DIVE availability: DIVE source code, written in Python3, is available at https://github.com/mrazvan22/dive and can be easily applied on any registered voxelwise images or images processed with the Freesurfer software. ADNI data can be downloaded from the Laboratory of NeuroImaging at the University of Southern California.

Background: Dementia with Lewy bodies (DLB) is the second most common form of dementia. Current symptomatic treatment with medications remains inadequate. Deep brain stimulation of the nucleus basalis of Meynert (NBM DBS) has been proposed as a potential new treatment option in dementias. Objective: To assess the safety and tolerability of low frequency (20 Hz) NBM DBS in DLB patients and explore its potential effects on both clinical symptoms and functional connectivity in underlying cognitive networks. Methods: We conducted an exploratory randomised, double-blind, crossover trial of NBM DBS in six DLB patients recruited from two UK neuroscience centres. Patients were aged between 50 and 80 years, had mild-moderate dementia symptoms and were living with a carer-informant. Patients underwent image guided stereotactic implantation of bilateral DBS electrodes with the deepest contacts positioned in the Ch4i subsector of NBM. Patients were subsequently assigned to receive either active or sham stimulation for six weeks, followed by a two week washout period, then the opposite condition for six weeks. Safety and tolerability of both the surgery and stimulation were systematically evaluated throughout. Exploratory outcomes included the difference in scores on standardised measurements of cognitive, psychiatric and motor symptoms between the active and sham stimulation conditions, as well as differences in functional connectivity in discrete cognitive networks on resting state fMRI. Results: Surgery and stimulation were well tolerated by all six patients (five male, mean age 71.33 years). One serious adverse event occurred: one patient developed antibiotic-associated colitis, prolonging his hospital stay by two weeks. No consistent improvements were observed in exploratory clinical outcome measures, but the severity of neuropsychiatric symptoms reduced with NBM DBS in 3/5 patients. Active stimulation was associated with functional connectivity changes in both the default mode network and the frontoparietal network. Conclusion: Low frequency NBM DBS can be safely conducted in DLB patients. This should encourage further exploration of the possible effects of stimulation on neuropsychiatric symptoms and corresponding changes in functional connectivity in cognitive networks.

Background Retinal thickness can be measured non-invasively with optical coherence tomography (OCT) and may offer compelling potential as a biomarker for Alzheimer’s disease (AD). Retinal thinning is hypothesized to be a result of retrograde atrophy and/or parallel neurodegenerative processes. Changes in the visual pathway are of particular interest in posterior cortical atrophy (PCA), the most common atypical AD phenotype predominantly affecting the parietal-occipital cortices. We therefore evaluated retinal thickness as non-invasive biomarker of neurodegeneration in well-characterized participants with posterior cortical atrophy (PCA) and typical Alzheimer’s disease (tAD). Methods Retinal thickness measures were acquired from 48 patient participants ( N = 25 PCA; N = 23 tAD) fulfilling consensus diagnostic criteria and 70 age-matched controls. Participants were recruited between 2014 and 2016. All participants underwent optical coherence tomography (OCT) imaging, including measurement of peripapillary retinal nerve fiber layer (pRNFL) thickness and total macular thickness (mRT). Participants did not show evidence of any significant ophthalmological conditions. Subgroup analyses were performed in participants with available MRI and CSF measures, providing evidence of neurodegeneration and underlying AD pathology respectively. Results There was no evidence of overall between-group differences in pRNFL thickness (mean PCA 98.7 ± 12.2; tAD 99.9 ± 8.7; controls 99.6 ± 10.0 μm, one-way analysis of variance (ANOVA) p = 0.92) or total mRT (mean PCA 266.9 ± 16.3; tAD 267.8 ± 13.6; controls 269.3 ± 13.6 μm, one-way ANOVA p = 0.75). Similarly, subgroup analysis with MRI biomarkers (PCA = 18, tAD = 17, controls = 31) showing neurodegeneration, and CSF biomarkers (PCA = 18, tAD = 14, controls = 13) supporting underlying AD pathology did not provide evidence of overall between-group differences in pRNFL or mRT measures (all p > 0.3). Conclusions Retinal thickness did not discriminate tAD and PCA from controls or from one another despite unequivocal differences on standard clinical, neuro-imaging and CSF measures. Findings from this well-characterized sample, including cases with PCA, do not support the hypothesis that retinal neurodegeneration, measured using conventional OCT, is a useful biomarker for AD or PCA.