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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.

The neurodegenerative disorder Alzheimer's disease is characterised by the formation of β-amyloid plaques and neurofibrillary tangles in the brain parenchyma, which cause synapse and neuronal loss. This leads to clinical symptoms, such as progressive memory deficits. Clinically, these pathological changes can be detected in the cerebrospinal fluid and with brain imaging, although reliable blood tests for plaque and tangle pathologies remain to be developed. Plaques and tangles often co-exist with other brain pathologies, including aggregates of transactive response DNA-binding protein 43 and Lewy bodies, but the extent to which these contribute to the severity of Alzheimer's disease is currently unknown. In this ‘At a glance’ article and poster, we summarise the molecular biomarkers that are being developed to detect Alzheimer's disease and its related pathologies. We also highlight the biomarkers that are currently in clinical use and include a critical appraisal of the challenges associated with applying these biomarkers for diagnostic and prognostic purposes of Alzheimer's disease and related neurodegenerative disorders, also in their prodromal clinical phases.

IntroductionCerebral amyloid angiopathy (CAA) is associated with symptomatic intracerebral haemorrhage. Biomarkers of clinically silent bleeding events, such as cerebrospinal fluid (CSF) ferritin and iron, might provide novel measures of disease presence and severity.MethodsWe performed an exploratory study comparing CSF iron, ferritin, and other metal levels in patients with CAA, control subjects (CS) and patients with Alzheimer’s disease (AD). Ferritin was measured using a latex fixation test; metal analyses were performed using inductively coupled plasma mass spectrometry.ResultsCAA patients (n = 10) had higher levels of CSF iron than the AD (n = 20) and CS (n = 10) groups (medians 23.42, 15.48 and 17.71 μg/L, respectively, p = 0.0015); the difference between CAA and AD groups was significant in unadjusted and age-adjusted analyses. We observed a difference in CSF ferritin (medians 10.10, 7.77 and 8.01 ng/ml, for CAA, AD and CS groups, respectively, p = 0.01); the difference between the CAA and AD groups was significant in unadjusted, but not age-adjusted, analyses. We also observed differences between the CAA and AD groups in CSF nickel and cobalt (unadjusted analyses).ConclusionsIn this exploratory study, we provide preliminary evidence for a distinct CSF metallomic profile in patients with CAA. Replication and validation of these results in larger cohorts is needed.

Freeze-thaw instability may contribute to preanalytical variation in blood-based biomarker studies. We investigated the effects of up to four freeze-thaw cycles on single molecule array immunoassays of serum neurofilament light chain and plasma total tau, amyloid β 1–40 (Aß40), and Aβ 1–42 (Aβ42). Individuals who had peripheral venepuncture during investigation of suspected neurodegenerative disease were recruited. After standardized preprocessing, 200 μL of plasma and serum aliquots were stored at −80°C within 60 minutes. Aliquots underwent one to four freeze-thaw cycles. There was no significant difference across four freeze-thaw cycles for serum neurofilament light chain (n = 12), plasma total tau (n = 11), or plasma Aβ42 (n = 12). For plasma Aβ40 (n = 14), there were significant median reductions by ratios of .96 and .92 at the third and fourth cycles, respectively. Up to four freeze-thaw cycles do not influence single molecule array blood biomarkers of neurofilament light chain, total tau, or Aβ42, with at most minor reductions in Aβ40.

Background Cerebrospinal fluid (CSF) biomarkers are increasingly being used to support a diagnosis of Alzheimer’s disease (AD). Their clinical utility for differentiating AD from non-AD neurodegenerative dementias, such as dementia with Lewy bodies (DLB) or frontotemporal dementia (FTD), is less well established. We aimed to determine the diagnostic utility of an extended panel of CSF biomarkers to differentiate AD from a range of other neurodegenerative dementias. Methods We used immunoassays to measure conventional CSF markers of amyloid and tau pathology (amyloid beta (Aβ)1–42, total tau (T-tau), and phosphorylated tau (P-tau)) as well as amyloid processing (AβX-38, AβX-40, AβX-42, soluble amyloid precursor protein (sAPP)α, and sAPPβ), large fibre axonal degeneration (neurofilament light chain (NFL)), and neuroinflammation (YKL-40) in 245 patients with a variety of dementias and 30 controls. Patients fulfilled consensus criteria for AD ( n  = 156), DLB ( n  = 20), behavioural variant frontotemporal dementia (bvFTD; n  = 45), progressive non-fluent aphasia (PNFA; n  = 17), and semantic dementia (SD; n  = 7); approximately 10% were pathology/genetically confirmed ( n  = 26). Global tests based on generalised least squares regression were used to determine differences between groups. Non-parametric receiver operating characteristic (ROC) curves and area under the curve (AUC) analyses were used to quantify how well each biomarker discriminated AD from each of the other diagnostic groups (or combinations of groups). CSF cut-points for the major biomarkers found to have diagnostic utility were validated using an independent cohort which included causes of AD ( n  = 104), DLB ( n  = 5), bvFTD ( n  = 12), PNFA ( n  = 3), SD ( n  = 9), and controls ( n  = 10). Results There were significant global differences in Aβ1–42, T-tau, T-tau/Aβ1–42 ratio, P-tau-181, NFL, AβX-42, AβX-42/X-40 ratio, APPα, and APPβ between groups. At a fixed sensitivity of 85%, AβX-42/X-40 could differentiate AD from controls, bvFTD, and SD with specificities of 93%, 85%, and 100%, respectively; for T-tau/Aβ1–42 these specificities were 83%, 70%, and 86%. AβX-42/X-40 had similar or higher specificity than Aβ1–42. No biomarker or ratio could differentiate AD from DLB or PNFA with specificity > 50%. Similar sensitivities and specificities were found in the independent validation cohort for differentiating AD and other dementias and in a pathology/genetically confirmed sub-cohort. Conclusions CSF AβX-42/X-40 and T-tau/Aβ1–42 ratios have utility in distinguishing AD from controls, bvFTD, and SD. None of the biomarkers tested had good specificity at distinguishing AD from DLB or PNFA.

Objective Identifying and recruiting people with early pre-symptomatic Alzheimer’s disease to neuroimaging research studies is increasingly important. The extent to which results of these studies can be generalised depends on the recruitment and representativeness of the participants involved. We now report the recruitment and participation patterns from a neuroscience sub-study of the MRC National Survey of Health and Development, “Insight 46”. This study aimed to recruit 500 participants for extensive clinical and neuropsychological testing, and neuroimaging. We investigate how sociodemographic factors, health conditions and health-related behaviours predict participation at different levels of recruitment. Results We met our target recruitment (n = 502). Higher educational attainment and non-manual socio-economic position (SEP) were consistent predictors of recruitment. Health-related variables were also predictive at every level of recruitment; in particular higher cognition, not smoking and better self-rating health. Sex and APOE-e4 status were not predictors of participation at any level. Whilst recruitment targets were met, individuals with lower SEP, lower cognition, and more health problems are under-represented in Insight 46. Understanding the factors that influence recruitment are important when interpreting results; for Insight 46 it is likely that health-related outcomes and life course risks will under-estimate those seen in the general population.

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.

Introduction Blood‐based assays to measure brain amyloid beta (Aβ) deposition are an attractive alternative to the cerebrospinal fluid (CSF)–based assays currently used in clinical settings. In this study, we examined different blood‐based assays to measure Aβ and how they compare among centers and assays. Methods Aliquots from 81 plasma samples were distributed to 10 participating centers. Seven immunological assays and four mass‐spectrometric methods were used to measure plasma Aβ concentrations. Results Correlations were weak for Aβ42 while Aβ40 correlations were stronger. The ratio Aβ42/Aβ40 did not improve the correlations and showed weak correlations. Discussion The poor correlations for Aβ42 in plasma might have several potential explanations, such as the high levels of plasma proteins (compared to CSF), sensitivity to pre‐analytical sample handling and specificity, and cross‐reactivity of different antibodies. Different methods might also measure different pools of plasma Aβ42. We, however, hypothesize that greater correlations might be seen in future studies because many of the methods have been refined during completion of this study.

Background Increased CSF levels of a number of synaptic markers have been reported in Alzheimer’s disease (AD), but little is known about their concentrations in frontotemporal dementia (FTD). We investigated this in three synaptic proteins, neurogranin, SNAP-25, and synaptotagmin-1. Methods CSF samples were analysed from 66 patients with a disorder in the FTD spectrum and 19 healthy controls. Patients were stratified by their tau to Aβ 42 ratio: those with a ratio of > 1 considered as having likely AD pathology, i.e. an atypical form of AD (‘AD biomarker’ group [ n  = 18]), and < 1 as likely FTD pathology (‘FTD biomarker’ group [ n  = 48]). A subgroup analysis compared those in the FTD group with likely tau ( n  = 7) and TDP-43 ( n  = 18) pathology. Concentrations of neurogranin were measured using two different ELISAs (Ng22 and Ng36), and concentrations of two SNAP-25 fragments (SNAP-25tot and SNAP-25aa40) and synaptotagmin-1 were measured via mass spectrometry. Results The AD biomarker group had significantly higher concentrations of all synaptic proteins compared to controls except for synaptotagmin-1 where there was only a trend to increased levels—Ng22, AD mean 232.2 (standard deviation 138.9) pg/ml, controls 137.6 (95.9); Ng36, 225.5 (148.8) pg/ml, 130.0 (80.9); SNAP-25tot, 71.4 (27.9) pM, 53.5 (11.7); SNAP-25aa40, 14.0 (6.3), 7.9 (2.3) pM; and synaptotagmin-1, 287.7 (156.0) pM, 238.3 (71.4). All synaptic measures were significantly higher in the atypical AD group than the FTD biomarker group except for Ng36 where there was only a trend to increased levels—Ng22, 114.0 (117.5); Ng36, 171.1 (75.2); SNAP-25tot, 49.2 (16.7); SNAP-25aa40, 8.2 (3.4); and synaptotagmin-1, 197.1 (78.9). No markers were higher in the FTD biomarker group than controls. No significant differences were seen in the subgroup analysis, but there was a trend to increased levels in those with likely tau pathology. Conclusions No CSF synaptic proteins have been shown to be abnormal in those with likely FTD pathologically. Higher CSF synaptic protein concentrations of neurogranin, SNAP-25, and synaptotagmin-1 appear to be related to AD pathology.

[...]the development of certified reference materials allowing for standardisation of measurements across assays for the same p-tau moiety is awaited and would facilitate assay performance comparison. 4 Some gaps remain for the translation of these findings into clinical practice. Other proposed ways of improving accuracy of p-tau217 include the use of ratios (eg, the ratio of p-tau217 to Aβ42) or by calculating the percentage of p-tau217. 7 For clinicians, sensitivity and specificity have less of a direct effect on decision making with individual patients than the negative and positive predictive values of testing, which change according to prevalence. 8 Clinicians should integrate information from these biomarkers with a thorough clinical assessment that takes into account their assessment of the pre-test probability of Alzheimer's disease. A global clinician survey indicated that confidence in clinically implementing Alzheimer's disease blood biomarkers would be improved by the provision of educational materials supporting understanding of what the test results mean (for both clinicians and patients, in terms of test performance, validation, and interpretation) and how test results will influence treatment decisions, and by more data on their performance in real-world populations. 9 To fully assess diagnostic accuracy, studies are required based on prospectively collected cohorts, incorporating high ethnic diversity 10 and individuals with multimorbidity, and using predetermined cut-points.