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Midlife 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. Participants 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. Between 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 amyloid-β status or PACC score at 69–71 years of age. High and increasing blood pressure from early adulthood into midlife seems to be associated with increased WMHV and smaller brain volumes at 69–71 years of age. We found no evidence that blood pressure affected cognition or cerebral amyloid-β load at this age. Blood pressure monitoring and interventions might need to start around 40 years of age to maximise late-life brain health. Alzheimer's Research UK, Medical Research Council, Dementias Platform UK, Wellcome Trust, Brain Research UK, Wolfson Foundation, Weston Brain Institute, Avid Radiopharmaceuticals.

Previous studies have found that diabetes and its mechanistic factors (e.g., glycaemia) are associated with poorer cognitive and brain health. There is also growing evidence of sex differences in how diabetes manifests itself and impacts the brain. The mechanisms through which this association manifests itself are still poorly understood, but the possible role of inflammation has been proposed. This study aims to explore whether the relationship between mid-life glycaemia and brain volumes in later-life in women is mediated by systemic inflammation. The sample consisted of female participants from the National Survey of Health and Development (NSHD) who underwent neuroimaging as part of the Insight 46 sub-study. Path analysis models were then constructed between glycaemic markers (age 60−64) and brain health outcomes (age 69−71) with adjustments for social and metabolic confounders (age 60−64). Although fasting glucose was associated with higher GlycA levels (β = 0.05 [0.01, 0.10], p = 0.005), associations with CRP and IL-6 were weaker and not statistically significant (e.g., IL-6: β = 0.10 [−0.04, 0.30], p = 0.102). However, we did not find evidence that inflammatory markers were associated with brain volume outcomes (e.g., IL-6 and whole brain volume: β = −3.4 [−8.1, 1.3], p = 0.092; IL-6 and grey matter volume: β = −0.4 [−1.9, 1.0], p = 0.512). Consequently, indirect (mediated) effects via systemic inflammation were not observed. This suggests that alternative mechanisms beyond inflammation may contribute to the relationship between mid-life glycaemia and later-life brain health.

The human hippocampus comprises a number of interconnected histologically and functionally distinct subfields, which may be differentially influenced by cerebral pathology. Automated techniques are now available that estimate hippocampal subfield volumes using in vivo structural MRI data. To date, research investigating the influence of cerebral β-amyloid deposition-one of the earliest hypothesised changes in the pathophysiological continuum of Alzheimer's disease-on hippocampal subfield volumes in cognitively normal older individuals, has been limited. Using cross-sectional data from 408 cognitively normal individuals born in mainland Britain (age range at time of assessment = 69.2-71.9 years) who underwent cognitive assessment, 18F-Florbetapir PET and structural MRI on the same 3 Tesla PET/MR unit (spatial resolution 1.1 x 1.1 x 1.1. mm), we investigated the influences of β-amyloid status, age at scan, and global white matter hyperintensity volume on: CA1, CA2/3, CA4, dentate gyrus, presubiculum and subiculum volumes, adjusting for sex and total intracranial volume. Compared to β-amyloid negative participants (n = 334), β-amyloid positive participants (n = 74) had lower volume of the presubiculum (3.4% smaller, p = 0.012). Despite an age range at scanning of just 2.7 years, older age at time of scanning was associated with lower CA1 (p = 0.007), CA4 (p = 0.004), dentate gyrus (p = 0.002), and subiculum (p = 0.035) volumes. There was no evidence that white matter hyperintensity volume was associated with any subfield volumes. These data provide evidence of differential associations in cognitively normal older adults between hippocampal subfield volumes and β-amyloid deposition and, increasing age at time of scan. The relatively selective effect of lower presubiculum volume in the β-amyloid positive group potentially suggest that the presubiculum may be an area of early and relatively specific volume loss in the pathophysiological continuum of Alzheimer's disease. Future work using higher resolution imaging will be key to exploring these findings further.

•Novel data-driven approaches to quantifying amyloid burden from in-vivo PET imaging have been developed to address common sources of variability such as the dependence on the definition of a reference region.•We evaluated four novel data-driven amyloid metrics against the binding potential and Centiloid scale using consistent data and evaluation criteria.•Three metrics (Aβ load, Aβ index, CLNMF) showed strong association with the binding potential and Centiloid scale. The CLNMF and Aβ load could offer a more precise alternative to the more established Centiloid.•As the Aβ load, Aβ index and CLNMF rely on the decomposition of PET images in specific and non-specific binding components, our results are consistent with a multivariate pattern of amyloid deposition over time. Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation. All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL. Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.

•Novel methodology and software for MR-PET registration uncertainty analysis.•Registration software had the biggest effect on MR-PET registration precision, followed by reconstruction parameters (i.e., iterations, smoothing) and PET count level.•PVC can significantly improve the PET signal, but since it relies on precise MR-PET registration, it also increases PET signal variability and hence care should be taken when using it. Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.

Objectives Participant retention is a significant challenge in ageing and dementia research. This analysis investigated (a) factors associated with retention in Insight 46, a neuroscience sub-study of the 1946 British birth cohort, and (b) clinical and cognitive changes over 2.5 years of follow-up. Results Of 502 participants assessed at baseline (mean[SD] age: 70.5[0.7] years), 442 returned for follow-up (mean[SD] interval: 2.5[0.3] years), representing a retention rate of 88%. Being β-amyloid positive (measures using positron emission tomography), female sex, and older age at baseline associated with lower odds of retention, while completion of neuroimaging and better cognitive performance at baseline– particularly on memory testing– related to higher odds of retention. By the time of follow-up, 14 participants were deceased, 12 of whom were female. Over follow-up, improvements were noted in certain cognitive tests (face-name test, logical memory delayed recall) with declines seen in others (mini-mental state examination, digit-symbol substitution test). Increases in self- and informant-reported cognitive complaints, cognitive disorder diagnoses, and motor abnormalities were also observed, alongside declines in blood pressure. These results have implications for the interpretation and generalisability of Insight 46 data and may be relevant to the planning of other longitudinal studies in this field.

To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates. MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into \"progressors\" (MCI-P) if diagnosed with AD within 36 months or \"stable\" (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated. Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P. These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD.

INTRODUCTION We assessed the concordance of cerebrospinal fluid (CSF) amyloid beta (Aβ) and tau measured on the fully automated Lumipulse platform with pre‐symptomatic Alzheimer's disease (AD) pathology on amyloid positron emission tomography (PET). METHODS In 72 individuals from the Insight 46 study, CSF Aβ40, Aβ42, total tau (t‐tau), and phosphorylated tau at site 181 (p‐tau181) were measured using Lumipulse, INNOTEST, and Meso Scale Discovery (MSD) assays and inter‐platform Pearson correlations derived. Lumipulse Aβ42 measures were adjusted to incorporate standardization to certified reference materials. Logistic regressions and receiver operating characteristics analysis generated CSF cut‐points optimizing concordance with 18F‐florbetapir amyloid PET status (n = 63). RESULTS Measurements of CSF Aβ, p‐tau181, and their ratios correlated well across platforms (r 0.84 to 0.94, P < .0001); those of t‐tau and t‐tau/Aβ42 correlated moderately (r 0.57 to 0.79, P < .0001). The best concordance with amyloid PET (100% sensitivity and 94% specificity) was afforded by cut‐points of 0.075 for Lumipulse Aβ42/Aβ40, 0.087 for MSD Aβ42/Aβ40 and 17.3 for Lumipulse Aβ42/p‐tau181. DISCUSSION The Lumipulse platform provides comparable sensitivity and specificity to established CSF immunoassays in identifying pre‐symptomatic AD pathology.

Background Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46—the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer’s disease (AD). Methods Following quality control, levels of 1019 metabolites—detected with liquid chromatography-mass spectrometry—were available for 1740 participants at age 60–64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69–71). Regression analyses tested relationships between metabolite measures—modules and hub metabolites—and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant ( p FDR  < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated ( p FDR  < 0.05) with an imaging outcome ( N  = 1638). Results In the fully adjusted model, three lipid modules were associated with a brain volume measure ( p FDR  < 0.05): one enriched in sphingolipids (hippocampal volume: ß  = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß  =  − 0.072, 95%CI = [− 0.12, − 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß  =  − 0.066, 95% CI = [− 0.11, − 0.020]). Twenty-two hub metabolites were associated ( p FDR  < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. Conclusions Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.

Background PET imaging of glucose metabolism has revealed presymptomatic abnormalities in genetic FTD but has not been explored in MAPT P301L mutation carriers. This study aimed to explore the patterns of presymptomatic hypometabolism and atrophy in MAPT P301L mutation carriers. Methods Eighteen asymptomatic members from five families with a P301L MAPT mutation were recruited to the study, six mutation carriers, and twelve mutation-negative controls. All participants underwent standard behavioural and cognitive assessment as well as [ 18 F]FDG-PET and 3D T1-weighted MRI brain scans. Regional standardised uptake value ratios (SUVR) for the PET scan and volumes calculated from an automated segmentation for the MRI were obtained and compared between the mutation carrier and control groups. Results The mean (standard deviation) estimated years from symptom onset was 12.5 (3.6) in the mutation carrier group with a range of 7 to 18 years. No differences in cognition were seen between the groups, and all mutation carriers had a global CDR plus NACC FTLD of 0. Significant reduction in [ 18 F] FDG uptake in the anterior cingulate was seen in mutation carriers (mean 1.25 [standard deviation 0.07]) compared to controls (1.36 [0.09]). A similar significant reduction was also seen in grey matter volume in the anterior cingulate in mutation carriers (0.60% [0.06%]) compared to controls (0.68% [0.08%]). No other group differences were seen in other regions. Conclusions Anterior cingulate hypometabolism and atrophy are both apparent presymptomatically in a cohort of P301L MAPT mutation carriers. Such a specific marker may prove to be helpful in stratification of presymptomatic mutation carriers in future trials.