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Objectives: We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists' accuracy and confidence in detecting volume loss, and in differentiating Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone., Methods: Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52-81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, 'non-clinical image analysts') assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as 'normal' or 'abnormal' and if 'abnormal' as 'AD' or 'FTD'., Results: The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group's accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters' agreement (Cohen's κ) with the 'gold standard' was not significantly affected by the QReport; only the consultant group improved significantly (κ s 0.41➔0.55, p = 0.04*). Cronbach's alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from 'good' to 'excellent'., Conclusion: Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses., Key Points: • The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone. • Consultant neuroradiologists' assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports. • First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia.

Background: We classified non-demented European Prevention of Alzheimer's Dementia (EPAD) participants through the amyloid/tau/neurodegeneration (ATN) scheme and assessed their neuropsychological and imaging profiles., Materials and Methods: From 1500 EPAD participants, 312 were excluded. Cerebrospinal fluid cut-offs of 1000 pg/mL for amyloid beta (Aß)1-42 and 27 pg/mL for p-tau181 were validated using Gaussian mixture models. Given strong correlation of p-tau and t-tau (R 2  = 0.98, P < 0.001), neurodegeneration was defined by age-adjusted hippocampal volume. Multinomial regressions were used to test whether neuropsychological tests and regional brain volumes could distinguish ATN stages., Results: Age was 65 ± 7 years, with 58% females and 38% apolipoprotein E (APOE) ε4 carriers; 57.1% were A-T-N-, 32.5% were in the Alzheimer's disease (AD) continuum, and 10.4% suspected non-Alzheimer's pathology. Age and cerebrovascular burden progressed with biomarker positivity (P < 0.001). Cognitive dysfunction appeared with T+. Paradoxically higher regional gray matter volumes were observed in A+T-N- compared to A-T-N- (P < 0.001)., Discussion: In non-demented individuals along the AD continuum, p-tau drives cognitive dysfunction. Memory and language domains are affected in the earliest stages., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease., Methods: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status., Results: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R 2  = 0.95), fluorodeoxyglucose (R 2  = 0.93), and atrophy (R 2  = 0.95) in mutation carriers compared to non-carriers., Discussion: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions., (© 2021 the Alzheimer's Association.)

Background: In view of reported associations between high adiposity, particularly in midlife and late-life dementia risk, we aimed to determine associations between body mass index (BMI), and BMI changes across adulthood and brain structure and pathology at age 69-71 years., Methods: Four hundred sixty-five dementia-free participants from Insight 46, a sub-study of the British 1946 birth cohort, who had cross-sectional T1/FLAIR volumetric MRI, and florbetapir amyloid-PET imaging at age 69-71 years, were included in analyses. We quantified white matter hyperintensity volume (WMHV) using T1 and FLAIR 3D-MRI; β-amyloid (Aβ) positivity/negativity using a SUVR approach; and whole brain (WBV) and hippocampal volumes (HV) using 3D T1-MRI. We investigated the influence of BMI, and BMI changes at and between 36, 43, 53, 60-64, 69 and 71 years, on late-life WMHV, Aβ-status, WBV and mean HV. Analyses were repeated using overweight and obese status., Results: At no time-point was BMI, change in BMI or overweight/obese status associated with WMHV or WBV at age 69-71 years. Decreasing BMI in the 1-2 years before imaging was associated with an increased odds of being β-amyloid positive (OR 1.45, 95% confidence interval 1.09, 1.92). There were associations between being overweight and larger mean HV at ages 60-64 (β = 0.073 ml, 95% CI 0.009, 0.137), 69 (β = 0.076 ml, 95% CI 0.012, 0.140) and 71 years (β = 0.101 ml, 95% CI 0.037, 0.165). A similar, albeit weaker, trend was seen with obese status., Conclusions: Using WMHV, β-amyloid status and brain volumes as indicators of brain health, we do not find evidence to explain reported associations between midlife obesity and late-life dementia risk. Declining BMI in later life may reflect preclinical Alzheimer's disease.

The basis of visual short-term memory (VSTM) impairments in preclinical Alzheimer's disease (AD) remains unclear. Research suggests that eye movements may serve as indirect surrogates to investigate VSTM. Yet, investigations in preclinical populations are lacking. Fifty-two individuals from a familial Alzheimer's disease (FAD) cohort (9 symptomatic carriers, 17 presymptomatic carriers and 26 controls) completed the "Object-localisation" VSTM task while an eye-tracker recorded eye movements during the stimulus presentation. VSTM function and oculomotor performance were compared between groups and their association during encoding investigated. Compared to controls, symptomatic FAD carriers showed eye movement patterns suggestive of an ineffective encoding and presymptomatic FAD carriers within 6 years of their expected age at symptom onset, were more reliant on the stimuli fixation time to achieve accuracy in the localisation of the target. Consequently, for shorter fixation times on the stimuli, presymptomatic carriers were less accurate at localising the target than controls. By contrast, the only deficits detected on behavioural VSTM function was in symptomatic individuals. Our findings provide novel evidence that encoding processes may be vulnerable and weakened in presymptomatic FAD carriers, most prominently for spatial memory, suggesting a possible explanation for the subtle VSTM impairments observed in the preclinical stages of AD.

Objective: To assess associations between head injury (HI) with loss of consciousness (LOC), ageing and markers of later-life cerebral pathology; and to explore whether those effects may help explain subtle cognitive deficits in dementia-free individuals., Methods: Participants (n = 502, age = 69-71) from the 1946 British Birth Cohort underwent cognitive testing (subtests of Preclinical Alzheimer Cognitive Composite), 18 F-florbetapir Aβ-PET and MR imaging. Measures include Aβ-PET status, brain, hippocampal and white matter hyperintensity (WMH) volumes, normal appearing white matter (NAWM) microstructure, Alzheimer's disease (AD)-related cortical thickness, and serum neurofilament light chain (NFL). LOC HI metrics include HI occurring: (i) >15 years prior to the scan (ii) anytime up to age 71., Results: Compared to those with no evidence of an LOC HI, only those reporting an LOC HI>15 years prior (16%, n = 80) performed worse on cognitive tests at age 69-71, taking into account premorbid cognition, particularly on the digit-symbol substitution test (DSST). Smaller brain volume (BV) and adverse NAWM microstructural integrity explained 30% and 16% of the relationship between HI and DSST, respectively. We found no evidence that LOC HI was associated with Aβ load, hippocampal volume, WMH volume, AD-related cortical thickness or NFL (all p > 0.01)., Interpretation: Having a LOC HI aged 50's and younger was linked with lower later-life cognitive function at age ~70 than expected. This may reflect a damaging but small impact of HI; explained in part by smaller BV and different microstructure pathways but not via pathology related to AD (amyloid, hippocampal volume, AD cortical thickness) or ongoing neurodegeneration (serum NFL)., (© 2021 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Aim: Identify a global resting-state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regard to amyloid (A), tau (T), and neurodegeneration (N) biomarkers, and estimated years to symptom onset (EYO). Introduction: Cross-sectional measures were assessed in MC ( n  = 171) and mutation noncarrier (NC) ( n  = 70) participants. A functional connectivity (FC) matrix that encompassed multiple resting-state networks was computed for each participant. Methods: A global FC was compiled as a single index indicating FC strength. The gFC signature was modeled as a nonlinear function of EYO. The gFC was linearly associated with other biomarkers used for assessing the AT(N) framework, including cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging. Results: The gFC was reduced in MC compared with NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR >0 (demented) compared with either MC CDR 0 (cognitively normal) or NC participants. The gFC varied nonlinearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO = 0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ 1-42 , CSF p-tau, CSF t-tau, 18F-fluorodeoxyglucose, and hippocampal volume. Conclusions: The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.

Objective: To investigate the inherent clinical risks associated with the presence of cerebral microhemorrhages (CMHs) or cerebral microbleeds and characterize individuals at high risk for developing hemorrhagic amyloid-related imaging abnormality (ARIA-H), we longitudinally evaluated families with dominantly inherited Alzheimer disease (DIAD)., Methods: Mutation carriers (n = 310) and noncarriers (n = 201) underwent neuroimaging, including gradient echo MRI sequences to detect CMHs, and neuropsychological and clinical assessments. Cross-sectional and longitudinal analyses evaluated relationships between CMHs and neuroimaging and clinical markers of disease., Results: Three percent of noncarriers and 8% of carriers developed CMHs primarily located in lobar areas. Carriers with CMHs were older, had higher diastolic blood pressure and Hachinski ischemic scores, and more clinical, cognitive, and motor impairments than those without CMHs. APOE ε4 status was not associated with the prevalence or incidence of CMHs. Prevalent or incident CMHs predicted faster change in Clinical Dementia Rating although not composite cognitive measure, cortical thickness, hippocampal volume, or white matter lesions. Critically, the presence of 2 or more CMHs was associated with a significant risk for development of additional CMHs over time (8.95 ± 10.04 per year)., Conclusion: Our study highlights factors associated with the development of CMHs in individuals with DIAD. CMHs are a part of the underlying disease process in DIAD and are significantly associated with dementia. This highlights that in participants in treatment trials exposed to drugs, which carry the risk of ARIA-H as a complication, it may be challenging to separate natural incidence of CMHs from drug-related CMHs., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Alzheimer's disease has a preclinical stage when cerebral amyloid-β deposition occurs before symptoms emerge, and when amyloid-β-targeted therapies may have maximum benefits. Existing amyloid-β status measurement techniques, including amyloid PET and CSF testing, are difficult to deploy at scale, so blood biomarkers are increasingly considered for screening. We compared three different blood-based techniques-liquid chromatography-mass spectrometry measures of plasma amyloid-β, and single molecule array (Simoa) measures of plasma amyloid-β and phospho-tau181-to detect cortical 18F-florbetapir amyloid PET positivity (defined as a standardized uptake value ratio of >0.61 between a predefined cortical region of interest and eroded subcortical white matter) in dementia-free members of Insight 46, a substudy of the population-based British 1946 birth cohort. We used logistic regression models with blood biomarkers as predictors of amyloid PET status, with or without age, sex and APOE ε4 carrier status as covariates. We generated receiver operating characteristics curves and quantified areas under the curves to compare the concordance of the different blood tests with amyloid PET. We determined blood test cut-off points using Youden's index, then estimated numbers needed to screen to obtain 100 amyloid PET-positive individuals. Of the 502 individuals assessed, 441 dementia-free individuals with complete data were included; 82 (18.6%) were amyloid PET-positive. The area under the curve for amyloid PET status using a base model comprising age, sex and APOE ε4 carrier status was 0.695 (95% confidence interval: 0.628-0.762). The two best-performing Simoa plasma biomarkers were amyloid-β42/40 (0.620; 0.548-0.691) and phospho-tau181 (0.707; 0.646-0.768), but neither outperformed the base model. Mass spectrometry plasma measures performed significantly better than any other measure (amyloid-β1-42/1-40: 0.817; 0.770-0.864 and amyloid-β composite: 0.820; 0.775-0.866). At a cut-off point of 0.095, mass spectrometry measures of amyloid-β1-42/1-40 detected amyloid PET positivity with 86.6% sensitivity and 71.9% specificity. Without screening, to obtain 100 PET-positive individuals from a population with similar amyloid PET positivity prevalence to Insight 46, 543 PET scans would need to be performed. Screening using age, sex and APOE ε4 status would require 940 individuals, of whom 266 would proceed to scan. Using mass spectrometry amyloid-β1-42/1-40 alone would reduce these numbers to 623 individuals and 243 individuals, respectively. Across a theoretical range of amyloid PET positivity prevalence of 10-50%, mass spectrometry measures of amyloid-β1-42/1-40 would consistently reduce the numbers proceeding to scans, with greater cost savings demonstrated at lower prevalence., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

The aerial hunting behaviours of birds are strongly influenced by flight morphology and ecology, but little is known of how this relates to the behavioural algorithms guiding flight. Here, we used GPS loggers to record the attack trajectories of captive-bred gyrfalcons ( Falco rusticolus ) during their maiden flights against robotic aerial targets, which we compared with existing flight data from peregrine falcons ( Falco peregrinus ). The attack trajectories of both species were well modelled by a proportional navigation (PN) guidance law, which commands turning in proportion to the angular rate of the line-of-sight to target, at a guidance gain N However, naive gyrfalcons operate at significantly lower values of N than peregrine falcons, producing slower turning and a longer path to intercept. Gyrfalcons are less manoeuvrable than peregrine falcons, but physical constraint is insufficient to explain the lower values of N we found, which may reflect either the inexperience of the individual birds or ecological adaptation at the species level. For example, low values of N promote the tail-chasing behaviour that is typical of wild gyrfalcons and which apparently serves to tire their prey in a prolonged high-speed pursuit. Likewise, during close pursuit of typical fast evasive prey, PN will be less prone to being thrown off by erratic target manoeuvres at low guidance gain. The fact that low-gain PN successfully models the maiden attack flights of gyrfalcons suggests that this behavioural algorithm is embedded in a guidance pathway ancestral to the clade containing gyrfalcons and peregrine falcons, though perhaps with much deeper evolutionary origins., Competing Interests: Competing interestsC.H.B., K.E.C. and G.K.T. declare no competing interests. N.C.F. is CEO of Wingbeat Ltd, which supplied and piloted the Roprey in this study., (© 2021. Published by The Company of Biologists Ltd.)

Background: Despite the considerable overlap with atypical parkinsonism, a systematic characterization of the movement disorders associated with frontotemporal lobar degeneration (FTLD) is lacking., Objective: The aim of this study is to provide a detailed description of the phenomenology and neuropathologic correlations of movement disorders in FTLD., Methods: In this cohort study, movement disorder clinical data were retrospectively collected from medical records of consecutive patients with a postmortem diagnosis of FTLD from the Queen Square Brain Bank between January 2010 and December 2018. At postmortem, neurodegenerative pathologies were systematically evaluated following consensus criteria. Degeneration of the substantia nigra was assessed as a marker of presynaptic dopaminergic parkinsonism using semiquantitative methods., Results: A total of 55 patients (35 men [64%]) were included with median (interquartile range) age at diagnosis of 58.8 (52.6-63.9) years and a disease duration of 9.6 (6.2-12.9) years. Movement disorders were present in 19 (35%) patients without differences among disease subtypes. The most common syndromes were parkinsonism (9 patients [16%]), usually as an additional late feature, and corticobasal syndrome (CBS, 7 patients [13%]), commonly as a presenting feature. Substantia nigra degeneration was present in 37 (67%) patients although it did not show a good clinical correlation with movement disorders. Those with Pick's disease showed milder substantia nigra degeneration and better response to levodopa., Conclusions: Movement disorders can present in all FTLD subtypes, more commonly as a late additional feature (parkinsonism) or as a presenting symptom (CBS). The underlying pathophysiology is complex and likely to involve structures outside the presynaptic striatonigral system. © 2020 International Parkinson and Movement Disorder Society., (© 2020 International Parkinson and Movement Disorder Society.)

Dementia is arguably the most pressing public health challenge of our age. Since dementia does not have a cure, identifying risk factors that can be controlled has become paramount to reduce the personal, societal and economic burden of dementia. The relationship between exposure to air pollution and effects on cognitive function, cognitive decline and dementia has stimulated increasing scientific interest in the past few years. This review of the literature critically examines the available epidemiological evidence of associations between exposure to ambient air pollutants, cognitive performance, acceleration of cognitive decline, risk of developing dementia, neuroimaging and neurological biomarker studies, following Bradford Hill guidelines for causality. The evidence reviewed has been consistent in reporting associations between chronic exposure to air pollution and reduced global cognition, as well as impairment in specific cognitive domains including visuo-spatial abilities. Cognitive decline and dementia incidence have also been consistently associated with exposure to air pollution. The neuro-imaging studies reviewed report associations between exposure to air pollution and white matter volume reduction. Other reported effects include reduction in gray matter, larger ventricular volume, and smaller corpus callosum. Findings relating to ischemic (white matter hyperintensities/silent cerebral infarcts) and hemorrhagic (cerebral microbleeds) markers of cerebral small vessel disease have been heterogeneous, as have observations on hippocampal volume and air pollution. The few studies available on neuro-inflammation tend to report associations with exposure to air pollution. Several effect modifiers have been suggested in the literature, but more replication studies are required. Traditional confounding factors have been controlled or adjusted for in most of the reviewed studies. Additional confounding factors have also been considered, but the inclusion of these has varied among the different studies. Despite all the efforts to adjust for confounding factors, residual confounding cannot be completely ruled out, especially since the factors affecting cognition and dementia are not yet fully understood. The available evidence meets many of the Bradford Hill guidelines for causality. The reported associations between a range of air pollutants and effects on cognitive function in older people, including the acceleration of cognitive decline and the induction of dementia, are likely to be causal in nature. However, the diversity of study designs, air pollutants and endpoints examined precludes the attribution of these adverse effects to a single class of pollutant and makes meta-analysis inappropriate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

We investigated whether subtle visuomotor deficits were detectable in familial and sporadic preclinical Alzheimer's disease. A circle-tracing task-with direct and indirect visual feedback, and dual-task subtraction-was completed by 31 individuals at 50% risk of familial Alzheimer's disease (19 presymptomatic mutation carriers; 12 non-carriers) and 390 cognitively normal older adults (members of the British 1946 Birth Cohort, all born during the same week; age range at assessment = 69-71 years), who also underwent β-amyloid-PET/MRI to derive amyloid status (positive/negative), whole-brain volume and white matter hyperintensity volume. We compared preclinical Alzheimer's groups against controls cross-sectionally (mutation carriers versus non-carriers; amyloid-positive versus amyloid-negative) on speed and accuracy of circle-tracing and subtraction. Mutation carriers (mean 7 years before expected onset) and amyloid-positive older adults traced disproportionately less accurately than controls when visual feedback was indirect, and were slower at dual-task subtraction. In the older adults, the same pattern of associations was found when considering amyloid burden as a continuous variable (Standardized Uptake Value Ratio). The effect of amyloid was independent of white matter hyperintensity and brain volumes, which themselves were associated with different aspects of performance: greater white matter hyperintensity volume was also associated with disproportionately poorer tracing accuracy when visual feedback was indirect, whereas larger brain volume was associated with faster tracing and faster subtraction. Mutation carriers also showed evidence of poorer tracing accuracy when visual feedback was direct. This study provides the first evidence of visuomotor integration deficits common to familial and sporadic preclinical Alzheimer's disease, which may precede the onset of clinical symptoms by several years., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Mutations in presenilin 1 (PSEN1) or presenilin 2 (PSEN2), the catalytic subunit of γ-secretase, cause familial Alzheimer's disease (fAD). We hypothesized that mutations in PSEN1 reduce Notch signaling and alter neurogenesis. Expression data from developmental and adult neurogenesis show relative enrichment of Notch and γ-secretase expression in stem cells, whereas expression of APP and β-secretase is enriched in neurons. We observe premature neurogenesis in fAD iPSCs harboring PSEN1 mutations using two orthogonal systems: cortical differentiation in 2D and cerebral organoid generation in 3D. This is partly driven by reduced Notch signaling. We extend these studies to adult hippocampal neurogenesis in mutation-confirmed postmortem tissue. fAD cases show mutation-specific effects and a trend toward reduced abundance of newborn neurons, supporting a premature aging phenotype. Altogether, these results support altered neurogenesis as a result of fAD mutations and suggest that neural stem cell biology is affected in aging and disease., Competing Interests: Declaration of Interests H.Z. has served at scientific advisory boards for Denali, Roche Diagnostics, Wave, Samumed, Siemens Healthineers, Pinteon Therapeutics, and CogRx; has given lectures in symposia sponsored by Fujirebio, Alzecure, and Biogen; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program. The other authors have no conflicts of interest to declare., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Given considerable variation in diagnostic and therapeutic practice, there is a need for national guidance on the use of neuroimaging, fluid biomarkers, cognitive testing, follow-up and diagnostic terminology in mild cognitive impairment (MCI). MCI is a heterogenous clinical syndrome reflecting a change in cognitive function and deficits on neuropsychological testing but relatively intact activities of daily living. MCI is a risk state for further cognitive and functional decline with 5-15% of people developing dementia per year. However, ~50% remain stable at 5 years and in a minority, symptoms resolve over time. There is considerable debate about whether MCI is a useful clinical diagnosis, or whether the use of the term prevents proper inquiry (by history, examination and investigations) into underlying causes of cognitive symptoms, which can include prodromal neurodegenerative disease, other physical or psychiatric illness, or combinations thereof. Cognitive testing, neuroimaging and fluid biomarkers can improve the sensitivity and specificity of aetiological diagnosis, with growing evidence that these may also help guide prognosis. Diagnostic criteria allow for a diagnosis of Alzheimer's disease to be made where MCI is accompanied by appropriate biomarker changes, but in practice, such biomarkers are not available in routine clinical practice in the UK. This would change if disease-modifying therapies became available and required a definitive diagnosis but would present major challenges to the National Health Service and similar health systems. Significantly increased investment would be required in training, infrastructure and provision of fluid biomarkers and neuroimaging. Statistical techniques combining markers may provide greater sensitivity and specificity than any single disease marker but their practical usefulness will depend on large-scale studies to ensure ecological validity and that multiple measures, e.g. both cognitive tests and biomarkers, are widely available for clinical use. To perform such large studies, we must increase research participation amongst those with MCI., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Techniques for clinical genetic testing in dementia disorders have advanced rapidly but remain to be more widely implemented in practice. A positive genetic test offers a precise molecular diagnosis, can help members of an affected family to determine personal risk, provides a basis for reproductive choices and can offer options for clinical trials. The likelihood of identifying a specific genetic cause of dementia depends on the clinical condition, the age at onset and family history. Attempts to match phenotypes to single genes are mostly inadvisable owing to clinical overlap between the dementias, genetic heterogeneity, pleiotropy and concurrent mutations. Currently, the appropriate genetic test in most cases of dementia is a next-generation sequencing gene panel, though some conditions necessitate specific types of test such as repeat expansion testing. Whole-exome and whole-genome sequencing are becoming financially feasible but raise or exacerbate complex issues such as variants of uncertain significance, secondary findings and the potential for re-analysis in light of new information. However, the capacity for data analysis and counselling is already restricting the provision of genetic testing. Patients and their relatives need to be given reliable information to enable them to make informed choices about tests, treatments and data sharing; the ability of patients with dementia to make decisions must be considered when providing this information.

Next-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there are few reports about their use in clinical practice. Which patients would most profit from testing, and information on the likelihood of discovery of a causal variant in a clinical syndrome, are conspicuously absent from the literature, mostly for a lack of large-scale studies. We applied a validated NGS dementia panel to 3241 patients with dementia and healthy aged controls; 13,152 variants were classified by likelihood of pathogenicity. We identified 354 deleterious variants (DV, 12.6% of patients); 39 were novel DVs. Age at clinical onset, clinical syndrome and family history each strongly predict the likelihood of finding a DV, but healthcare setting and gender did not. DVs were frequently found in genes not usually associated with the clinical syndrome. Patients recruited from primary referral centres were compared with those seen at higher-level research centres and a national clinical neurogenetic laboratory; rates of discovery were comparable, making selection bias unlikely and the results generalisable to clinical practice. We estimated penetrance of DVs using large-scale online genomic population databases and found 71 with evidence of reduced penetrance. Two DVs in the same patient were found more frequently than expected. These data should provide a basis for more informed counselling and clinical decision making.

In the phase 3 EPOCH trial (Clinicaltrials.gov; NCT01739348), treatment with the BACE inhibitor verubecestat failed to improve cognition in patients with mild-to-moderate Alzheimer's disease, but was associated with reduced hippocampal volume after 78 weeks as assessed by MRI. The aims of the present exploratory analyses were to: (i) characterize the effect of verubecestat on brain volume by evaluating the time course of volumetric MRI changes for a variety of brain regions; and (ii) understand the mechanism through which verubecestat might cause hippocampal (and other brain region) volume loss by assessing its relationship to measures of amyloid, neurodegeneration, and cognition. Participants were aged 55-85 years with probable Alzheimer's disease dementia and a Mini Mental State Examination score ≥15 and ≤26. MRIs were obtained at baseline and at Weeks 13, 26, 52 and 78 of treatment. MRIs were segmented using Freesurfer and analysed using a tensor-based morphometry method. PET amyloid data were obtained with 18F-flutemetamol (Vizamyl®) at baseline and Week 78. Standardized uptake value ratios were generated with subcortical white matter as a reference region. Neurofilament light chain in the CSF was assessed as a biomarker of neurodegeneration. Compared with placebo, verubecestat showed increased MRI brain volume loss at Week 13 with no evidence of additional loss through Week 78. The verubecestat-related volumetric MRI loss occurred predominantly in amyloid-rich brain regions. Correlations between amyloid burden at baseline and verubecestat-related volumetric MRI reductions were not significant (r = 0.05 to 0.26, P-values > 0.27). There were no significant differences between verubecestat and placebo in changes from baseline in CSF levels of neurofilament light chain at Week 78 (increases of 7.2 and 14.6 pg/ml for verubecestat versus 19.7 pg/ml for placebo, P-values ≥ 0.1). There was a moderate correlation between volumetric MRI changes and cognitive decline in all groups including placebo at Week 78 (e.g. r = -0.45 to -0.55, P < 0.001 for whole brain), but the correlations were smaller at Week 13 and significant only for the verubecestat groups (e.g. r = -0.15 and -0.11, P < 0.04 for whole brain). Our results suggest that the verubecestat-associated MRI brain volume loss is not due to generalized, progressive neurodegeneration, but may be mediated by specific effects on BACE-related amyloid processes., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: To explore the value of olfactory identification deficits as a predictor of cerebral β-amyloid status and other markers of brain health in cognitively normal adults aged ~ 70 years., Methods: Cross-sectional observational cohort study. 389 largely healthy and cognitively normal older adults were recruited from the MRC National Survey of Health and Development (1946 British Birth cohort) and investigated for olfactory identification deficits, as measured by the University of Pennsylvania Smell Identification Test. Outcome measures were imaging markers of brain health derived from 3 T MRI scanning (cortical thickness, entorhinal cortex thickness, white matter hyperintensity volumes); 18 F florbetapir amyloid-PET scanning; and cognitive testing results. Participants were assessed at a single centre between March 2015 and January 2018., Results: Mean (± SD) age was 70.6 (± 0.7) years, 50.8% were female. 64.5% had hyposmia and 2.6% anosmia. Olfaction showed no association with β-amyloid status, hippocampal volume, entorhinal cortex thickness, AD signature cortical thickness, white matter hyperintensity volume, or cognition., Conclusion and Relevance: In the early 70s, olfactory function is not a reliable predictor of a range of imaging and cognitive measures of preclinical AD. Olfactory identification deficits are not likely to be a useful means of identifying asymptomatic amyloidosis. Further studies are required to assess if change in olfaction may be a proximity marker for the development of cognitive impairment.

Familial Alzheimer's disease (fAD) mutations alter amyloid precursor protein (APP) cleavage by γ-secretase, increasing the proportion of longer amyloidogenic amyloid-β (Aβ) peptides. Using five control induced pluripotent stem cell (iPSC) lines and seven iPSC lines generated from fAD patients, we investigated the effects of mutations on the Aβ secretome in human neurons generated in 2D and 3D. We also analysed matched CSF, post-mortem brain tissue, and iPSCs from the same participant with the APP V717I mutation. All fAD mutation lines demonstrated an increased Aβ42:40 ratio relative to controls, yet displayed varied signatures for Aβ43, Aβ38, and short Aβ fragments. We propose four qualitatively distinct mechanisms behind raised Aβ42:40. (1) APP V717I mutations alter γ-secretase cleavage site preference. Whereas, distinct presenilin 1 (PSEN1) mutations lead to either (2) reduced γ-secretase activity, (3) altered protein stability or (4) reduced PSEN1 maturation, all culminating in reduced γ-secretase carboxypeptidase-like activity. These data support Aβ mechanistic tenets in a human physiological model and substantiate iPSC-neurons for modelling fAD.

Background: Understanding the earliest manifestations of Alzheimer's disease (AD) is key to realising disease-modifying treatments. Advances in neuroimaging and fluid biomarkers have improved our ability to identify AD pathology in vivo. The critical next step is improved detection and staging of early cognitive change. We studied an asymptomatic familial Alzheimer's disease (FAD) cohort to characterise preclinical cognitive change., Methods: Data included 35 asymptomatic participants at 50% risk of carrying a pathogenic FAD mutation. Participants completed a multi-domain neuropsychology battery. After accounting for sex, age and education, we used event-based modelling to estimate the sequence of cognitive decline in presymptomatic FAD, and uncertainty in the sequence. We assigned individuals to their most likely model stage of cumulative cognitive decline, given their data. Linear regression of estimated years to symptom onset against model stage was used to estimate the timing of preclinical cognitive decline., Results: Cognitive change in mutation carriers was first detected in measures of accelerated long-term forgetting, up to 10 years before estimated symptom onset. Measures of subjective cognitive decline also revealed early abnormalities. Our data-driven model demonstrated subtle cognitive impairment across multiple cognitive domains in clinically normal individuals on the AD continuum., Conclusions: Data-driven modelling of neuropsychological test scores has potential to differentiate cognitive decline from cognitive stability and to estimate a fine-grained sequence of decline across cognitive domains and functions, in the preclinical phase of Alzheimer's disease. This can improve the design of future presymptomatic trials by informing enrichment strategies and guiding the selection of outcome measures.

An increasing proportion of cognitive difficulties are recognized to have a functional cause, the chief clinical indicator of which is internal inconsistency. When these symptoms are impairing or distressing, and not better explained by other disorders, this can be conceptualized as a cognitive variant of functional neurological disorder, termed functional cognitive disorder (FCD). FCD is likely very common in clinical practice but may be under-diagnosed. Clinicians in many settings make liberal use of the descriptive term mild cognitive impairment (MCI) for those with cognitive difficulties not impairing enough to qualify as dementia. However, MCI is an aetiology-neutral description, which therefore includes patients with a wide range of underlying causes. Consequently, a proportion of MCI cases are due to non-neurodegenerative processes, including FCD. Indeed, significant numbers of patients diagnosed with MCI do not 'convert' to dementia. The lack of diagnostic specificity for MCI 'non-progressors' is a weakness inherent in framing MCI primarily within a deterministic neurodegenerative pathway. It is recognized that depression, anxiety and behavioural changes can represent a prodrome to neurodegeneration; empirical data are required to explore whether the same might hold for subsets of individuals with FCD. Clinicians and researchers can improve study efficacy and patient outcomes by viewing MCI as a descriptive term with a wide differential diagnosis, including potentially reversible components such as FCD. We present a preliminary definition of functional neurological disorder-cognitive subtype, explain its position in relation to other cognitive diagnoses and emerging biomarkers, highlight clinical features that can lead to positive diagnosis (as opposed to a diagnosis of exclusion), and red flags that should prompt consideration of alternative diagnoses. In the research setting, positive identifiers of FCD will enhance our recognition of individuals who are not in a neurodegenerative prodrome, while greater use of this diagnosis in clinical practice will facilitate personalized interventions., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: There is increasing interest in improving understanding of the timing and nature of early neurodegeneration in Alzheimer's disease (AD) and developing methods to measure this in vivo. Autosomal dominant familial Alzheimer's disease (FAD) provides the opportunity for investigation of presymptomatic change. We assessed early microstructural breakdown of cortical grey matter in FAD with diffusion-weighted MRI., Methods: Diffusion-weighted and T1-weighed MRI were acquired in 38 FAD mutation carriers (17 symptomatic, 21 presymptomatic) and 39 controls. Mean diffusivity (MD) was calculated for six cortical regions previously identified as being particularly vulnerable to FAD-related neurodegeneration. Linear regression compared MD between symptomatic and presymptomatic carriers and controls, adjusting for age and sex. Spearman coefficients assessed associations between cortical MD and cortical thickness. Spearman coefficients also assessed associations between cortical MD and estimated years to/from onset (EYO). Across mutation carriers, linear regression assessed associations between MD and EYO, adjusting for cortical thickness., Results: Compared with controls, cortical MD was higher in symptomatic mutation carriers (mean ± SD CDR = 0.88 ± 0.39) for all six regions (p < 0.001). In late presymptomatic carriers (within 8.1 years of predicted symptom onset), MD was higher in the precuneus (p = 0.04) and inferior parietal cortex (p = 0.003) compared with controls. Across all presymptomatic carriers, MD in the precuneus correlated with EYO (p = 0.04). Across all mutation carriers, there was strong evidence (p < 0.001) of association between MD and cortical thickness in all regions except entorhinal cortex. After adjusting for cortical thickness, there remained an association (p < 0.05) in mutation carriers between MD and EYO in all regions except entorhinal cortex., Conclusions: Cortical MD measurement detects microstructural breakdown in presymptomatic FAD and correlates with proximity to symptom onset independently of cortical thickness. Cortical MD may thus be a feasible biomarker of early AD-related neurodegeneration, offering additional/complementary information to conventional MRI measures.

The commonest causes of dementia are Alzheimer's disease and vascular cognitive impairment. Although these conditions have been viewed as distinct entities, there is increasing evidence that neurodegenerative and vascular pathologies interact or overlap to cause cognitive decline, and that at least in some cases individuals at risk of cognitive decline exhibit abnormal cardiovascular physiology long before emergence of disease. However, the mechanisms linking haemodynamic disturbances with cognitive impairment and the various pathologies that cause dementia are poorly understood. A sub-sample of 502 participants from the Medical Research Council National Survey of Health and Development (NSHD) have participated in the first visit of a neuroscience sub-study referred to as Insight 46, where clinical, cognitive, imaging, and lifestyle data have been collected for the purpose of elucidating the pathological changes preceding dementia. This paper outlines the cardiovascular phenotyping performed in the follow-up visit of Insight 46, with the study participants now aged 74. In addition to standard cardiovascular assessments such as blood pressure measurements, echocardiography, and electrocardiography (ECG), functional Near Infrared Spectroscopy (fNIRS) has been included to provide an assessment of cerebrovascular function. A detailed description of the fNIRS protocol along with preliminary results from pilot data is presented. The combination of lifestyle data, brain structure/function, cognitive performance, and cardiovascular health obtained not only from Insight 46, but also from the whole NSHD provides an exciting opportunity to advance our understanding of the cardiovascular mechanisms underlying dementia and cognitive decline, and identify novel targets for intervention., Competing Interests: Conflicts of Interest Nish Chaturvedi serves on a Data Safety and Monitoring Board for a clinical trial of a glucose lowering agent, funded by AstraZeneca. No other authors have competing interests.

Neuronal intranuclear inclusion disease (NIID) is a clinically heterogeneous neurodegenerative condition characterized by pathological intranuclear eosinophilic inclusions. A CGG repeat expansion in NOTCH2NLC was recently identified to be associated with NIID in patients of Japanese descent. We screened pathologically confirmed European NIID, cases of neurodegenerative disease with intranuclear inclusions and applied in silico-based screening using whole-genome sequencing data from 20 536 participants in the 100 000 Genomes Project. We identified a single European case harbouring the pathogenic repeat expansion with a distinct haplotype structure. Thus, we propose new diagnostic criteria as European NIID represents a distinct disease entity from East Asian cases., (© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Objective: To use survival modeling to estimate disease duration in autosomal dominant familial Alzheimer disease (ADAD) and ascertain whether factors influencing age at onset also affect survival., Methods: Symptomatic mutation carriers (201 presenilin 1 [ PSEN1 ] and 55 amyloid precursor protein [ APP ]) from ADAD families referred to the Dementia Research Centre, between 1987 and 2019, were included. Survival was assessed with respect to age at onset, year of birth, APOE ε4 status, cognitive presentation, and sex using multilevel mixed-effects Weibull survival models. The contribution of mutation and family to variance in age at onset and duration was also assessed., Results: Estimated mean survival was 11.6 (10.4-12.9) years and was similar for APP and PSEN1 mutations. Sixty-seven percent of the variance in age at onset was explained by mutation and 72% by mutation and family together. In contrast, only 6% of the variance in disease duration was explained by mutation specificity and 18% by family membership. Irrespective of gene, survival appeared longer for successive generations and in individuals with atypical presentations. Older age at onset was associated with longer duration within PSEN1 and shorter duration within APP mutation carriers. No differences in survival time were found between sexes or between mutations located before or beyond codon 200 within PSEN1 ., Conclusions: Survival is influenced by mutation to a much lesser extent than age at onset. Survival time has increased over time and is longer in atypical presentations. These insights may inform the interpretation of disease-modifying therapy trials in ADAD., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Introduction: We investigated whether life-course factors and neuroimaging biomarkers of Alzheimer's disease pathology predict reaction time (RT) performance in older adults., Methods: Insight 46 study participants, all born in the same week in 1946 (n = 501; ages at assessment = 69 to 71 years), completed a 2-choice RT task and amyloid beta (Aβ) positron emission tomography and MR imaging. We tested for associations between task outcomes (RT; error rate; intra-individual variability in RT) and life-course predictors including childhood cognitive ability and education. In a subsample of 406 cognitively normal participants, we investigated associations between task outcomes and biomarkers including Aβ-positivity., Results: Cognitively normal Aβ-positive participants had 10% more variable RTs than Aβ-negative participants, despite having similar mean RTs. Childhood cognitive ability and education independently predicted task performance., Discussion: This study provides novel evidence that Aβ pathology is associated with poorer consistency of RT in cognitively normal older adults, at an age when dementia prevalence is still very low., Competing Interests: Kirsty Lu reports no disclosures. Jennifer M. Nicholas reports no disclosures. Sarah‐Naomi James reports no disclosures. Thomas D. Parker is supported by a Wellcome Trust Clinical Research Fellowship (200109/Z/15/Z). Christopher A. Lane reports no disclosures. Ashvini Keshavan is supported by a Clinical Research Fellowship funded by the Wolfson Foundation. Sarah E. Keuss reports no disclosures. Sarah M. Buchanan reports no disclosures. Heidi Murray‐Smith reports no disclosures. David M. Cash is supported by an Alzheimer's Society Project Grant (AS‐PG‐205). Carole H. Sudre is supported by an Alzheimer's Society Junior Fellowship (AS‐JF‐17‐011). Ian B. Malone reports no disclosures. William Coath reports no disclosures. Andrew Wong reports no disclosures. Susie M.D. Henley reports no disclosures. Nick C. Fox is supported by the UCL/UCLH NIHR Biomedical Research Centre and the UK Dementia Research Institute at UCL. Marcus Richards reports no disclosures. Jonathan M. Schott is supported by the UCL/UCLH NIHR Biomedical Research Centre, UCL Hospitals Biomedical Research Centre, and Leonard Wolfson Experimental Neurology Centre and acknowledges the EPSRC (EP/J020990/1) and European Union's Horizon 2020 research and innovation programme (Grant 666992). Sebastian J. Crutch is supported by an Alzheimer's Research UK Senior Research Fellowship (ARUK‐SRF2013‐8)., (© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of the Alzheimer's Association.)

Genetic and acquired disorders of white matter comprise a diverse group of conditions, with often overlapping clinical and radiological findings. Patients present with a variable combination of cognitive impairment, ataxia, spasticity or movement disorders, among others. There are many genetic causes, and the route to diagnosis involves comprehensive clinical assessment, radiological expertise, metabolic investigations and finally genetic studies. It is essential not to miss the treatable acquired causes. In this review, we present a practical approach to investigating patients with acquired and genetic disorders of white matter, based on the experience of a large international referral centre. We present a guide for clinicians, including pitfalls of testing, clinical pearls and where to seek advice., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer's disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer's disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T 1 -weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset -9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer's disease, which is alike sporadic Alzheimer's disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer's disease., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

Introduction: Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear., Methods: We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18 F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness., Results: Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region., Discussion: WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms., (© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of the Alzheimer's Association.)

Introduction: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge., Methods: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated., Results: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R 2 = 24%) and memory (R 2 = 25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%-75%., Discussion: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD., (© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

Development of tau-based therapies for Alzheimer's disease requires an understanding of the timing of disease-related changes in tau. We quantified the phosphorylation state at multiple sites of the tau protein in cerebrospinal fluid markers across four decades of disease progression in dominantly inherited Alzheimer's disease. We identified a pattern of tau staging where site-specific phosphorylation changes occur at different periods of disease progression and follow distinct trajectories over time. These tau phosphorylation state changes are uniquely associated with structural, metabolic, neurodegenerative and clinical markers of disease, and some (p-tau217 and p-tau181) begin with the initial increases in aggregate amyloid-β as early as two decades before the development of aggregated tau pathology. Others (p-tau205 and t-tau) increase with atrophy and hypometabolism closer to symptom onset. These findings provide insights into the pathways linking tau, amyloid-β and neurodegeneration, and may facilitate clinical trials of tau-based treatments.

Importance: Midlife vascular risk burden is associated with late-life dementia. Less is known about if and how risk exposure in early adulthood influences late-life brain health., Objective: To determine the associations between vascular risk in early adulthood, midlife, and late life with late-life brain structure and pathology using measures of white matter-hyperintensity volume, β-amyloid load, and whole-brain and hippocampal volumes., Design, Setting, and Participants: This prospective longitudinal cohort study, Insight 46, is part of the Medical Research Council National Survey of Health and Development, which commenced in 1946. Participants had vascular risk factors evaluated at ages 36 years (early adulthood), 53 years (midlife), and 69 years (early late life). Participants were assessed with multimodal magnetic resonance imaging and florbetapir-amyloid positron emission tomography scans between May 2015 and January 2018 at University College London. Participants with at least 1 available imaging measure, vascular risk measurements at 1 or more points, and no dementia were included in analyses., Exposures: Office-based Framingham Heart study-cardiovascular risk scores (FHS-CVS) were derived at ages 36, 53, and 69 years using systolic blood pressure, antihypertensive medication usage, smoking, diabetic status, and body mass index. Analysis models adjusted for age at imaging, sex, APOE genotype, socioeconomic position, and, where appropriate, total intracranial volume., Main Outcomes and Measures: White matter-hyperintensity volume was generated from T1/fluid-attenuated inversion recovery scans using an automated technique and whole-brain volume and hippocampal volume were generated from automated in-house pipelines; β-amyloid status was determined using a gray matter/eroded subcortical white matter standardized uptake value ratio threshold of 0.61., Results: A total of 502 participants were assessed as part of Insight 46, and 463 participants (236 male [51.0%]) with at least 1 available imaging measure (mean [SD] age at imaging, 70.7 [0.7] years; 83 β-amyloid positive [18.2%]) who fulfilled eligibility criteria were included. Among them, FHS-CVS increased with age (36 years: median [interquartile range], 2.7% [1.5%-3.6%]; 53 years: 10.9% [6.7%-15.6%]; 69 years: 24.3% [14.9%-34.9%]). At all points, these scores were associated with smaller whole-brain volumes (36 years: β coefficient per 1% increase, -3.6 [95% CI, -7.0 to -0.3]; 53 years: -0.8 [95% CI, -1.5 to -0.08]; 69 years: -0.6 [95% CI, -1.1 to -0.2]) and higher white matter-hyperintensity volume (exponentiated coefficient: 36 years, 1.09 [95% CI, 1.01-1.18]; 53 years, 1.02 [95% CI, 1.00-1.04]; 69 years, 1.01 [95% CI, 1.00-1.02]), with largest effect sizes at age 36 years. At no point were FHS-CVS results associated with β-amyloid status., Conclusions and Relevance: Higher vascular risk is associated with smaller whole-brain volume and greater white matter-hyperintensity volume at age 69 to 71 years, with the strongest association seen with early adulthood vascular risk. There was no evidence that higher vascular risk influences amyloid deposition, at least up to age 71 years. Reducing vascular risk with appropriate interventions should be considered from early adulthood to maximize late-life brain health.

Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72., Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried., Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even more by family membership (66%, 56-75, for age at onset; 74%, 65-82, for age at death). In the GRN group, only 2% (0-10) of the variability of age at onset and 9% (3-21) of that of age of death was explained by the specific mutation, whereas 14% (9-22) of the variability of age at onset and 20% (12-30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11-26) of the variability of age at onset and 19% (12-29) of that of age at death., Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates., Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Hearing impairment may be a modifiable risk factor for dementia. However, it is unclear how hearing associates with pathologies relevant to dementia in preclinical populations., Methods: Data from 368 cognitively healthy individuals born during 1 week in 1946 (age range 69.2-71.9 years), who underwent structural MRI, 18 F-florbetapir positron emission tomography, pure tone audiometry and cognitive testing as part of a neuroscience substudy the MRC National Survey of Health and Development were analysed. The aim of the analysis was to investigate whether pure tone audiometry performance predicted a range of cognitive and imaging outcomes relevant to dementia in older adults., Results: There was some evidence that poorer pure tone audiometry performance was associated with lower primary auditory cortex thickness, but no evidence that it predicted in vivo β-amyloid deposition, white matter hyperintensity volume, hippocampal volume or Alzheimer's disease-pattern cortical thickness. A negative association between pure tone audiometry and mini-mental state examination score was observed, but this was no longer evident after excluding a test item assessing repetition of a single phrase., Conclusion: Pure tone audiometry performance did not predict concurrent β-amyloid deposition, small vessel disease or Alzheimer's disease-pattern neurodegeneration, and had limited impact on cognitive function, in healthy adults aged approximately 70 years., Competing Interests: Competing interests: NCF’s research group has received payment for consultancy or for conducting studies from Biogen, Eli Lilly Research Laboratories, GE Healthcare, and Roche. NCF receives no personal compensation for the activities mentioned above. JMS has received research funding from Avid Radiopharmaceuticals (a wholly owned subsidiary of Eli Lilly), has consulted for Roche Pharmaceuticals, Biogen, Merck and Eli Lilly, given educational lectures sponsored by GE Healthcare, Eli Lilly and Biogen, and serves on a Data Safety Monitoring Committee for Axon Neuroscience SE., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (n ADRC  = 381; n DIAN  = 145), preclinical (n ADRC  = 153; n DIAN  = 76), and cognitively impaired (n ADRC  = 54; n DIAN  = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11 C-Pittsburgh compound B or 18 F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: There is limited data on cerebrospinal fluid (CSF) biomarkers in sporadic amyloid-β (Aβ) cerebral amyloid angiopathy (CAA)., Objective: To determine the profile of biomarkers relevant to neurodegenerative disease in the CSF of patients with CAA., Methods: We performed a detailed comparison of CSF markers, comparing patients with CAA, Alzheimer's disease (AD), and control (CS) participants, recruited from the Biomarkers and Outcomes in CAA (BOCAA) study, and a Specialist Cognitive Disorders Service., Results: We included 10 CAA, 20 AD, and 10 CS participants (mean age 68.6, 62.5, and 62.2 years, respectively). In unadjusted analyses, CAA patients had a distinctive CSF biomarker profile, with significantly lower (p < 0.01) median concentrations of Aβ38, Aβ40, Aβ42, sAβPPα, and sAβPPβ. CAA patients had higher levels of neurofilament light (NFL) than the CS group (p < 0.01), but there were no significant differences in CSF total tau, phospho-tau, soluble TREM2 (sTREM2), or neurogranin concentrations. AD patients had higher total tau, phospho-tau and neurogranin than CS and CAA groups. In age-adjusted analyses, differences for the CAA group remained for Aβ38, Aβ40, Aβ42, and sAβPPβ. Comparing CAA patients with amyloid-PET positive (n = 5) and negative (n = 5) scans, PET positive individuals had lower (p < 0.05) concentrations of CSF Aβ42, and higher total tau, phospho-tau, NFL, and neurogranin concentrations, consistent with an "AD-like" profile., Conclusion: CAA has a characteristic biomarker profile, suggestive of a global, rather than selective, accumulation of amyloid species; we also provide evidence of different phenotypes according to amyloid-PET positivity. Further replication and validation of these preliminary findings in larger cohorts is needed.

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.

Objective: To 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., Methods: A 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 ., Results: Childhood 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., Conclusions: This 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., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Importance: The amyloid/tau/neurodegeneration (A/T/N) framework uses cerebrospinal fluid (CSF) levels of total tau (tTau) as a marker of neurodegeneration and CSF levels of phosphorylated tau 181 (pTau181) as a marker of tau tangles. However, it is unclear whether CSF levels of tTau and pTau181 have similar or different trajectories over the course of Alzheimer disease., Objectives: To examine the rates of change in CSF levels of tTau and pTau181 across the Alzheimer disease course and how the rates of change are associated with brain atrophy as measured by magnetic resonance imaging., Design, Setting, and Participants: This cohort study was set in tertiary research clinics. Each participant was a member of a pedigree with a known mutation for dominantly inherited Alzheimer disease. Participants were divided into 3 groups on the basis of the presence of a mutation and their Clinical Dementia Rating score. Data analysis was performed in June 2019., Main Outcomes and Measures: Rates of change of CSF tTau and pTau181 levels and their association with the rate of change of brain volume., Results: Data from 465 participants (283 mutation carriers and 182 noncarriers) were analyzed. The mean (SD) age of the cohort was 37.8 (11.3) years, and 262 (56.3%) were women. The mean (SD) follow-up duration was 2.7 (1.5) years. Two or more longitudinal CSF and magnetic resonance imaging assessments were available for 160 and 247 participants, respectively. Sixty-five percent of mutation carriers (183) did not have symptoms at baseline (Clinical Dementia Rating score, 0). For mutation carriers, the annual rates of change for CSF tTau and pTau181 became significantly different from 0 approximately 10 years before the estimated year of onset (mean [SE] rates of change, 5.5 [2.8] for tTau [P = .05] and 0.7 [0.3] for pTau 181 [P = .04]) and 15 years before onset (mean [SE] rates of change, 5.4 [3.9] for tTau [P = .17] and 1.1 [0.5] for pTau181 [P = .03]), respectively. The rate of change of pTau181 was positive and increased at the early stages of the disease, showing a positive rate of change starting at 15 estimated years before onset until 5 estimated years before onset (mean [SE], 0.4 [0.3]), followed by a positive but decreasing rate of change at year 0 (mean [SE], 0.1 [0.3]) and then negative rates of change at 5 years (mean [SE], -0.3 [0.4]) and 10 years (mean [SE], -0.6 [0.6]) after symptom onset. In individuals without symptoms (Clinical Dementia Rating score, 0), the rates of change of CSF tTau and pTau181 were negatively associated with brain atrophy (high rates of change in CSF measures were associated with low rates of change in brain volume in asymptomatic stages). After symptom onset (Clinical Dementia Rating score, >0), an increased rate of brain atrophy was not associated with rates of change of levels of both CSF tTau and pTau181., Conclusions and Relevance: These findings suggest that CSF tTau and pTau181 may have different associations with brain atrophy across the disease time course. These results have implications for understanding the dynamics of disease pathobiology and interpreting neuronal injury biomarker concentrations in response to Alzheimer disease progression and disease-modifying therapies.

Background: 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., Methods: 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., Results: 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., Conclusion: 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., Competing Interests: NCF’s research group has received payment for consultancy or for conducting studies from Biogen, Eli Lilly Research Laboratories, GE Healthcare, and Roche. NCF receives no personal compensation for the activities mentioned above. JMS has received research funding from Avid Radiopharmaceuticals (a wholly owned subsidiary of Eli Lilly), has consulted for Roche Pharmaceuticals, Biogen, Merck and Eli Lilly, given educational lectures sponsored by GE Healthcare, Eli Lilly and Biogen, and serves on a Data Safety Monitoring Committee for Axon Neuroscience SE. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge compares the performance of algorithms at predicting the future evolution of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Participants are then required to make forecasts of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog 13), and total volume of the ventricles - which are then compared with future measurements. Strong points of the challenge are that the test data did not exist at the time of forecasting (it was acquired afterwards), and that it focuses on the challenging problem of cohort selection for clinical trials by identifying fast progressors. The submission phase of TADPOLE was open until 15 November 2017; since then data has been acquired until April 2019 from 219 subjects with 223 clinical visits and 150 Magnetic Resonance Imaging (MRI) scans, which was used for the evaluation of the participants' predictions. Thirty-three teams participated with a total of 92 submissions. No single submission was best at predicting all three outcomes. For diagnosis prediction, the best forecast (team Frog), which was based on gradient boosting, obtained a multiclass area under the receiver-operating curve (MAUC) of 0.931, while for ventricle prediction the best forecast (team EMC1 ), which was based on disease progression modelling and spline regression, obtained mean absolute error of 0.41% of total intracranial volume (ICV). For ADAS-Cog 13, no forecast was considerably better than the benchmark mixed effects model ( BenchmarkME ), provided to participants before the submission deadline. Further analysis can help understand which input features and algorithms are most suitable for Alzheimer's disease prediction and for aiding patient stratification in clinical trials. The submission system remains open via the website: https://tadpole.grand-challenge.org/.

Background: 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., Methods: 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., Findings: 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., Interpretation: 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., Funding: Alzheimer's Research UK, Medical Research Council, Dementias Platform UK, Wellcome Trust, Brain Research UK, Wolfson Foundation, Weston Brain Institute, Avid Radiopharmaceuticals., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Alzheimer disease (AD) is one of several neurodegenerative diseases characterized by dysregulation, misfolding and accumulation of specific proteins in the CNS. The stable isotope labelling kinetics (SILK) technique is based on generating amino acids labelled with naturally occurring stable (that is, nonradioactive) isotopes of carbon and/or nitrogen. These labelled amino acids can then be incorporated into proteins, enabling rates of protein production and clearance to be determined in vivo and in vitro without the use of radioactive or chemical labels. Over the past decade, SILK studies have been used to determine the turnover of key pathogenic proteins amyloid-β (Aβ), tau and superoxide dismutase 1 (SOD1) in the cerebrospinal fluid of healthy individuals, patients with AD and those with other neurodegenerative diseases. These studies led to the identification of several factors that alter the production and/or clearance of these proteins, including age, sleep and disease-causing genetic mutations. SILK studies have also been used to measure Aβ turnover in blood and within brain tissue. SILK studies offer the potential to elucidate the mechanisms underlying various neurodegenerative disease mechanisms, including neuroinflammation and synaptic dysfunction, and to demonstrate target engagement of novel disease-modifying therapies.