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.
Background
Alzheimer’s Disease is more common in women than men. Menopause timing and type have been linked with cognition post‐menopause, but associations with dementia risk are unclear. Within the ...MRC National Survey of Health and Development (NSHD), childhood cognition predicts later‐life cognition and has largely explained menopause‐cognition associations post‐menopause. We now explore to what extent childhood cognition explains menopause‐cognition associations in later‐life and whether residual associations emerge.
Method
Prospective questionnaires at ages 43‐54 provided menopause age (years since birth until period cessation) and type (surgical/natural). Addenbrooke’s Cognitive Examination (ACE‐III) gave a measure of cognitive state at age 69 (maximum n=913). Cognitive domains were investigated using ACE‐III sub‐domains and cognitive tasks in a neuroimaging sub‐study (age 69‐71; maximum n=246) assessing memory, executive function, attention, visuospatial function, processing speed and non‐verbal reasoning. All cognitive outcomes were standardised. Multivariable regression analyses adjusted for relevant affective, early cognitive, sociodemographic, hormonal, health and genetic covariables, with multiple imputation of missing values using chained equations.
Results
Menopause associated with the following cognitive outcomes: total ACE‐III, ACE‐III verbal fluency, ACE‐III memory, ACE‐III visuospatial function, pre‐clinical Alzheimer’s cognitive composite, response inhibition, and intra‐individual variability in reaction times. Later menopause associated with better performance, while surgical menopause associated with worse performance. After accounting for childhood cognition, associations remained between menopause age and total ACE‐III (β=.012; 95% CI .001, .023), ACE‐III visuospatial function (β=.012; 95% CI .000, .023) and response inhibition (β=.034; 95% CI .008, .061), and between menopause type and response inhibition (β=‐.368; 95% CI ‐.665, ‐.070). With full adjustments, associations persisted between menopause age and ACE‐III memory (β=.011; 95% CI .000, .023). Intra‐individual variability in reaction times also remained associated with menopause age (β=‐.049; 95% CI ‐.079, ‐.019) and type (β=.413; 95% CI .076, .750).
Conclusion
In later‐life, associations emerge between menopause and cognitive domains implicated in dementia (memory, processing speed, attention). Later menopause associates with better performance and surgical menopause with worse. Associations are not fully explained by known predictors of later‐life cognition including childhood cognition and other lifetime covariables accounted for. Further exploration of the link between menopause and dementia risk in women is warranted.
Abstract
Background
Many studies of memory in older adults report a sex difference, usually with female participants scoring slightly better than males. These sex differences may be partially due to ...the content of the tests, with some content being more memorable to males or females (https://doi.org/10.1093/ARCLIN/ACAC102). We investigated whether male and female older adults show differences on the Face‐Name Associative Memory Exam (FNAME‐12, designed to detect subtle Alzheimer’s disease‐related memory impairment). Specifically, do they show a bias towards remembering the stimuli that match their own sex?
Method
Participants (n = 432, see
Table 1
) in ‘Insight 46’, a sub‐study of the MRC National Survey of Health and Development (British 1946 birth cohort), completed FNAME‐12 (version A) at age ∼73 years. Stimuli comprise six male and six female faces (presented in alternating order), with names and occupations. Recall is tested four times after various delay intervals. Four total scores were calculated across all recall trials: female names; female occupations; male names; male occupations. We fitted multivariable regression models using Generalised Estimating Equations to investigate effects of item type (name/occupation), item gender (male/female) and participant sex (male/female), and interactions between these variables, controlling for age, education, socioeconomic position and prospectively‐collected childhood cognitive ability.
Result
Women outperformed men (coefficient averaged across the four conditions = 2.2 points 95% CIs 1.3, 3.1, p<0.001) (
Fig1; Fig2
). This difference was exaggerated for female stimuli (interaction coefficient = 2.0 1.4, 2.6, p<0.001), and female stimuli occupations (3‐way interaction coefficient = 0.8 ‐0.0, 1.6 p = 0.050) i.e. women scored better than men even on male names, whereas men were particularly disadvantaged at recalling information associated with female stimuli, especially their occupations (
Fig2
).
Conclusion
We found evidence of a gender bias on FNAME‐12 among male participants, where their recall was worse for female stimuli compared to male stimuli, which may partially explain their poorer performance on this test. Such biases should be considered when interpreting sex differences on memory tests. Further analyses before the conference will investigate longitudinal FNAME‐12 performance over ∼2.4 years, to explore whether this memory bias remains constant, or whether it may be a marker of memory decline (potentially reflecting increased reliance on the relatability of test content).
•Older age at menopause is associated with better cognition at around 70 years of age.•Visual processing, associative learning, and memory showed the strongest effects.•Life course covariables ...explained most, but not all, associations.
Associations between age at menopause and cognition post-menopause are examined to determine whether relationships are stronger for certain cognitive domains.
Women from the Medical Research Council National Survey of Health and Development and its neuroscience sub-study, Insight 46, were included if they had known age at menopause (self-reported via questionnaire) and complete cognitive outcome data at age 69 (n = 746) or at Insight 46 wave I (n = 197). Multivariable linear regression analyses adjusting for life course confounders were run; interactions with menopause type (natural/surgical) and APOE-ε4 status were examined; and the potential contribution of hormone therapy was assessed.
Cognitive measures were standardized Addenbrooke's Cognitive Examination - third edition total and sub-domain scores at age 69 (whole cohort) and Preclinical Alzheimer's Cognitive Composite total and sub-test scores at age ~70 (Insight 46).
Older age at menopause was associated with better performance across all outcomes, most strongly for the Addenbrooke's Cognitive Examination memory and visuospatial function sub-domains, and the Preclinical Alzheimer's Cognitive Composite digit-symbol substitution test and face-name associative memory examination sub-tests. Adjusting for early-life factors attenuated all effect estimates, driven by childhood cognition, and accounting for menopause type revealed negative confounding for some outcomes. No significant interactions with menopause type or APOE-ε4 status were detected. Further adjustment for hormone therapy did not meaningfully alter the estimated effects.
Older age at menopause is associated with better later-life cognitive performance, particularly for visual processing and associative learning and memory domains. Childhood cognition was an important contributor.
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.
Eye-tracking technology is an innovative tool that holds promise for enhancing dementia screening. In this work, we introduce a novel way of extracting salient features directly from the raw ...eye-tracking data of a mixed sample of dementia patients during a novel instruction-less cognitive test. Our approach is based on self-supervised representation learning where, by training initially a deep neural network to solve a pretext task using well-defined available labels (e.g. recognising distinct cognitive activities in healthy individuals), the network encodes high-level semantic information which is useful for solving other problems of interest (e.g. dementia classification). Inspired by previous work in explainable AI, we use the Layer-wise Relevance Propagation (LRP) technique to describe our network's decisions in differentiating between the distinct cognitive activities. The extent to which eye-tracking features of dementia patients deviate from healthy behaviour is then explored, followed by a comparison between self-supervised and handcrafted representations on discriminating between participants with and without dementia. Our findings not only reveal novel self-supervised learning features that are more sensitive than handcrafted features in detecting performance differences between participants with and without dementia across a variety of tasks, but also validate that instruction-less eye-tracking tests can detect oculomotor biomarkers of dementia-related cognitive dysfunction. This work highlights the contribution of self-supervised representation learning techniques in biomedical applications where the small number of patients, the non-homogenous presentations of the disease and the complexity of the setting can be a challenge using state-of-the-art feature extraction methods.
OBJECTIVETo investigate predictors of performance on a range of cognitive measures including the Preclinical Alzheimer Cognitive Composite (PACC) and test for associations between cognition and ...dementia biomarkers in Insight 46, a substudy of the Medical Research Council National Survey of Health and Development.
METHODSA total of 502 individuals born in the same week in 1946 underwent cognitive assessment at age 69–71 years, including an adapted version of the PACC and a test of nonverbal reasoning. Performance was characterized with respect to sex, childhood cognitive ability, education, and socioeconomic position (SEP). In a subsample of 406 cognitively normal participants, associations were investigated between cognition and β-amyloid (Aβ) positivity (determined from Aβ-PET imaging), whole brain volumes, white matter hyperintensity volumes (WMHV), and APOE ε4.
RESULTSChildhood cognitive ability was strongly associated with cognitive scores including the PACC more than 60 years later, and there were independent effects of education and SEP. Sex differences were observed on every PACC subtest. In cognitively normal participants, Aβ positivity and WMHV were independently associated with lower PACC scores, and Aβ positivity was associated with poorer nonverbal reasoning. Aβ positivity and WMHV were not associated with sex, childhood cognitive ability, education, or SEP. Normative data for 339 cognitively normal Aβ-negative participants are provided.
CONCLUSIONSThis study adds to emerging evidence that subtle cognitive differences associated with Aβ deposition are detectable in older adults, at an age when dementia prevalence is very low. The independent associations of childhood cognitive ability, education, and SEP with cognitive performance at age 70 have implications for interpretation of cognitive data in later life.
Abstract
Background
Autosomal dominant familial Alzheimer’s disease (ADAD), caused by APP, PSEN1 and PSEN2 mutations, is clinically and pathologically similar to sporadic AD, with both typically ...presenting with memory impairment. However as in sporadic AD, atypical phenotypes and neuropathological heterogeneity occur, including variable vascular Aβ deposition as cerebral amyloid angiopathy (CAA). Investigating relationships between clinical, genetic and neuropathological heterogeneity in ADAD may provide insights into pathophysiological pathways relevant to AD in general.
Methods
256 symptomatic individuals from ADAD families seen at our Centre were included in a survival analysis, with detailed clinical phenotype data available for 138 (101 PSEN1, 37 APP). 33 of these individuals underwent brain donation (24 PSEN1, 9 APP), all demonstrating end‐stage AD pathology. Frontal and occipital cortex sections were stained immunohistochemically for Aβ and vessel counts used to determine the proportion of cortical and leptomeningeal blood vessels affected by CAA.
Results
Age at onset was, on average, seven years younger for PSEN1 than APP mutations and was influenced by mutation much more than survival was. Atypical (non‐amnestic) cognitive presentations with initial behavioral, language, dyscalculic or dysexecutive symptoms, and atypical clinical features (pyramidal, extrapyramidal and cerebellar signs) were more common in PSEN1 than APP cases, particularly those with post‐codon 200 mutations. Atypical cognitive presentations were associated with longer survival. There was some indication that APOE4 carriers had longer survival and that this effect may be restricted to PSEN1. In the post‐mortem cohort, atypical cognitive presentations occurred in 15%. Additional neurological features comprised myoclonus (45%), seizures (21%), pyramidal signs (21%) and extrapyramidal signs (15%), one individual had cerebellar signs. Increased frontal cortical and leptomeningeal CAA occurred in individuals with pyramidal and extrapyramidal signs, and in PSEN1 post‐codon 200 compared to pre‐codon 200 mutations. Atypical cognitive presentations were associated with increased frontal cortical CAA.
Conclusions
Phenotypic heterogeneity in ADAD is influenced by causative gene and mutation type, and atypical clinical presentations are associated with increased CAA. Exploring mechanisms by which certain mutations drive Aβ deposition towards the vasculature, and how these may be impacted by other genetic factors and by therapies targeting Aβ, is an important direction for future research.
Background
Cardiovascular and cerebrovascular pathology may accelerate brain aging and cognitive decline. Structural cerebrovascular imaging biomarkers, such as white matter hyperintensities, reflect ...mostly irreversible accumulated damage. In contrast, cerebral blood flow (CBF), measured with arterial spin labelling (ASL) perfusion MRI, is a potential early haemodynamic biomarker of cognitive impairment. However, our understanding of physiological CBF variability and its relation with cognition is limited.
Method
We included 245 cognitively unimpaired participants from the Insight 46 birth cohort study, who underwent 3D T1‐weighted and pseudo‐continuous ASL‐MRI (labelling duration = 1800ms; post‐labelling delay = 1800ms) on a 3T Siemens Biograph mMR PET‐MRI scanner. Cognitive assessment included tests for logical memory (Wechsler Memory Scale‐Revised), associative memory (Face‐Name Associative Memory Exam), attention and processing speed (Digit‐symbol substitution and response inhibition test), non‐verbal reasoning (Matrix test), executive functioning (Choice Reaction Time), visuomotor integration (circle‐tracing task), and two composite scores (Mini‐Mental State Examination (MMSE) and the Preclinical Alzheimer Cognitive Composite).
Result
Sample characteristics are reported in Table 1. Associations were found between GM sCoV and MMSE (Male/Female ß = 0.74/‐0.75, p = 0.028, Figure 1), and GM sCoV and Logical Memory (Male/Female ß = 1.05/‐0.25, p = 0.005, Figure 2), but not between CBF and any cognitive scores (p>0.05).
Conclusion
In a cognitively unimpaired population, cognitive performance was associated with GM sCoV but not with other CBF parameters. However, in males, the relationship was opposite to what we expected. Further work should investigate to what extent this indicates macrovascular change occurs before perfusion alterations and could relate to future cognitive decline, and how they differ between sex.
Background
Cardiovascular and cerebrovascular pathology may accelerate brain aging and cognitive decline. Structural cerebrovascular imaging biomarkers, such as white matter hyperintensities, reflect ...mostly irreversible accumulated damage. In contrast, cerebral blood flow (CBF), measured with arterial spin labelling (ASL) perfusion MRI, is a potential early haemodynamic biomarker of cognitive impairment. However, our understanding of physiological CBF variability and its relation with cognition is limited.
Method
We included 245 cognitively unimpaired participants from the Insight 46 birth cohort study, who underwent 3D T1‐weighted and pseudo‐continuous ASL‐MRI (labelling duration = 1800ms; post‐labelling delay = 1800ms) on a 3T Siemens Biograph mMR PET‐MRI scanner. Cognitive assessment included tests for logical memory (Wechsler Memory Scale‐Revised), associative memory (Face‐Name Associative Memory Exam), attention and processing speed (Digit‐symbol substitution and response inhibition test), non‐verbal reasoning (Matrix test), executive functioning (Choice Reaction Time), visuomotor integration (circle‐tracing task), and two composite scores (Mini‐Mental State Examination (MMSE) and the Preclinical Alzheimer Cognitive Composite).
Result
Sample characteristics are reported in Table 1. Associations were found between GM sCoV and MMSE (Male/Female ß = 0.74/‐0.75, p = 0.028, Figure 1), and GM sCoV and Logical Memory (Male/Female ß = 1.05/‐0.25, p = 0.005, Figure 2), but not between CBF and any cognitive scores (p>0.05).
Conclusion
In a cognitively unimpaired population, cognitive performance was associated with GM sCoV but not with other CBF parameters. However, in males, the relationship was opposite to what we expected. Further work should investigate to what extent this indicates macrovascular change occurs before perfusion alterations and could relate to future cognitive decline, and how they differ between sex.
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