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INTRODUCTION: Limited observational windows lead to conflicting results in studies examining educational differences in Alzheimer's disease and related dementias (ADRD) risk, due to observational window bias relative to onset of accelerated cognitive decline. This study tested a novel model to address observational window bias and tested for the presence and sources of disparities in accelerated cognitive declines due to ADRD. METHODS: The sample examined 167,314 cognitive assessments from 32,441 Health and Retirement Study participants. We implemented a parametric non‐linear nested longitudinal regression and reported multivariable‐adjusted nodal incidence ratios (aNIR). RESULTS: University degrees were associated with lower incidence (aNIR = 0.253, 95% confidence interval [CI] = [0.221 to 0.289], p < 0.001), while black participants had a higher incidence (aNIR = 1.995, [1.858 to 2.141], p < 0.001) of accelerated cognitive decline, adjusting for demographic, sociobehavioral, and medical risk factors. Sex‐stratified analyses identified diminished educational returns for women and increased incidence among minoritized women. DISCUSSION: Addressing observational window bias reveals large social inequalities in the onset of accelerated cognitive declines indicative of ADRD. Highlights: This study identifies observational window bias as a source of conflicting results among previous studies of educational achievement in Alzheimer's disease and related dementias (ADRD) disparities.The study locates preclinical accelerated cognitive decline, which is indicative of ADRD while occurring 10+ years prior to symptom onset, as a site to study ADRD disparities that mitigates observational window bias.A novel method, nested non‐linear regression, is developed to test for differences in the onset of accelerated cognitive decline.Educational and racial/ethnic disparities are demonstrated in the onset of accelerated cognitive decline, as are their intersecting differences with sex/gender. [ABSTRACT FROM AUTHOR]

INTRODUCTION: We aimed to investigate associations between common infections and neuroimaging markers of dementia risk (brain volume, hippocampal volume, white matter lesions) across three population‐based studies. METHODS: We tested associations between serology measures (pathogen serostatus, cumulative burden, continuous antibody responses) and outcomes using linear regression, including adjustments for total intracranial volume and scanner/clinic information (basic model), age, sex, ethnicity, education, socioeconomic position, alcohol, body mass index, and smoking (fully adjusted model). Interactions between serology measures and apolipoprotein E (APOE) genotype were tested. Findings were meta‐analyzed across cohorts (Nmain = 2632; NAPOE‐interaction = 1810). RESULTS: Seropositivity to John Cunningham virus associated with smaller brain volumes in basic models (β = −3.89 mL [−5.81, −1.97], Padjusted < 0.05); these were largely attenuated in fully adjusted models (β = −1.59 mL [−3.55, 0.36], P = 0.11). No other relationships were robust to multiple testing corrections and sensitivity analyses, but several suggestive associations were observed. DISCUSSION: We did not find clear evidence for relationships between common infections and markers of dementia risk. Some suggestive findings warrant testing for replication. [ABSTRACT FROM AUTHOR]

Background: We assess if, and at which ages during 30 years of adulthood, undertaking leisure time physical activity (LTPA) is associated with brain health at age 70, and to what extent brain health metrics explain the positive association between LTPA and later‐life cognition. Method: Participants from the British 1946 birth cohort prospectively reported LTPA five times between ages 36 and 69. Metrics were categorised into: not active (no participation/month); active (participated once or more/month); and summed. Participants underwent 18F‐florbetapir Aβ‐PET and MRI at age 70 (n = 468, 49% female). Regression analyses examined associations between LTPA metrics and later‐life brain health including Aβ‐PET, TIV‐adjusted brain, hippocampal and log‐transformed‐white matter hyperintensity (WMH) volume, adjusting for sex, scan age, childhood cognition, education, and childhood socioeconomic position. Effect modification by sex and APOE‐ε4 were examined. The relationship between cumulative LPTA and later‐life cognition (Addenbrooke's cognitive Examination (ACE‐III)) was assessed adjusting for brain health measures. Result: Participation in LTPA was associated with better brain health at age 70. For brain volume and WMH volume, the strongest associations were with LTPA at age 69 (Figure 1). Being active in one or more period across adulthood was linked to larger hippocampal volume (Figure 1); this relationship was modified by APOE‐ε4 (p<0.01), with a stronger effect shown in ε4 carriers (Figure 2). LTPA at age 43 was also associated with larger hippocampal volumes. There was no evidence of associations with amyloid status. The positive association between cumulative LTPA and better cognition was not attenuated by any of the brain health measures (Figure 3). Conclusion: We provide evidence that LTPA across adulthood is linked to brain health at age 70; being active throughout adulthood was associated with larger hippocampal volume, particularly in APOE ε4 carriers; and being active in later‐life was linked to less WMH and larger brain volume at age 70. However, these brain health metrics did not explain the relationship between LPTA and better cognitive scores, suggesting that these pathways may not underlie the inferred cognitive benefit at this age. Our findings warrant further research to shed light on the mechanisms of physical activity as a potential disease‐modifying intervention of brain health. [ABSTRACT FROM AUTHOR]

Background: Evidence for a role of common infections in neurodegenerative and cerebrovascular diseases is conflicting, and the extent to which pathogen exposure associates with subclinical imaging markers of these diseases is unclear. We aimed to investigate associations between a panel of serological measures characterising exposure to common pathogens – selected based on their relevance to public health – and brain volume, hippocampal volume, and white matter lesions in two population‐based cohorts in the UK. Method: Serology and imaging data were available for 1371 participants across two studies: the UK Biobank (N = 935, mean age(SD)[years] = 55.3(7.7) at serology; 63.8(7.7) at imaging) and the Medical Research Council National Survey of Health and Development [N = 436, mean age(SD) [years] = 63.3(1.1) years at serology; 70.7(0.7) years at imaging). Serology measures included a) serostatuses of 17 pathogens, b) total proportion of 17 pathogens exposed to, and c) total proportion of 11 neurotropic pathogens exposed to (Table 1). Associations between serology measures and outcomes (brain volume, hippocampal volume, and white matter lesion volume) were tested using linear regression. Regression models included adjustments for total intracranial volume and clinic information (basic models), and age, sex, ethnicity, education, socioeconomic position and lifestyle factors (Figure 1). Findings across cohorts were meta‐analysed using random‐effects models. The present study will be expanded to include an additional cohort (Southall and Brent Revisited,N≤1200) to add more precision for identifying associations. Result: Seropositivity to seven pathogens associated with an outcome in basic models, and four in fully‐adjusted models: seropositivity to JC virus was associated with smaller brain volumes, Epstein‐Barr virus with larger brain volumes, Merkel cell virus with larger hippocampal volumes and fewer white matter lesions, and C.trachomatis with fewer white matter lesions (Figure 2). Neurotropic pathogen burden scores associated with smaller hippocampal volumes in basic models, but no associations were seen for either pathogen burden score in fully‐adjusted models. Conclusion: We found some evidence of both positive and negative associations between common infections and imaging markers of subclinical cerebrovascular disease and neurodegeneration, with no evidence of relationships with pathogen burden. This work highlights key relationships for further investigation, which may reveal novel pathways associated with brain structure and cerebrovascular pathology. [ABSTRACT FROM AUTHOR]

Background: Cognitive decline in older age has significant health, economic and social consequences and there is evidence that financial adversity might play a role. Financial adversity, for many, is not an acute but a chronic stressor. However, little is known about the effect of persistence exposure to financial adversity across the lifecourse on cognitive ageing. Method: Using data from the 1946 British birth cohort (N = 2,759) with an embedded neuroimaging study (Insight46; N = 356‐468), we examined the prospective association between financial adversity (low household income, financial hardships; 26‐53 years) and cognitive performance (69 years) and decline (53‐69 years), as well as volumetric measures of brain health (69‐71 years) in older adulthood. Cognitive decline was modelled using latent growth curves, with derived intercepts and slopes used in subsequent regression analyses, adjusted for sex, childhood socioeconomic circumstances (SEC), baseline cognition and internalising symptoms, and educational attainment. Sex, childhood SEC and APOE‐ɛ4 genetic risk were further tested as moderators in regression models using interaction terms. This study has been pre‐registered (https://doi.org/10.17605/OSF.IO/6Y9NV). Result: Increased exposure to financial adversity showed dose‐response associations with slower verbal memory decline and lower processing speed and verbal memory at 69 years (Table 1). Each increased period of exposure to low household income or financial hardships was associated with a 0.11 and 0.08 standard deviation (SD) decrease in processing speed, and a 0.32 and 0.22 SD decrease in verbal memory at 69 years, respectively. Males persistently exposed to financial hardships showed slower processing speed decline but increased brain atrophy compared to females. Those whose fathers were in unskilled profession or unemployed in childhood, and who also persistently experienced low income themselves showed greater brain atrophy (Fig. 1). APOE‐ɛ4 carriers who persistently experienced financial adversity were also at greater risk for brain atrophy (Fig. 2). Conclusion: Persistent financial adversity is directly associated with cognitive performance and may be differentially associated with brain atrophy depending on demographic and genetic factors. Reducing the frequency of financial adversity over the lifecourse may improve cognitive performance and protect against genetic susceptibility to brain atrophy and subsequent dementia risk in the ageing population. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Background: Accelerated Long‐term Forgetting (ALF) is the phenomenon whereby material is retained normally over short intervals (minutes or hours) but forgotten abnormally rapidly over longer periods (days or weeks). ALF may be an early marker of cognitive decline, but little is known about its relationships with preclinical Alzheimer's disease pathology in older adults, and how memory selectivity may influence which material is forgotten. Method: Participants in 'Insight 46', a sub‐study of the MRC National Survey of Health and Development (British 1946 birth cohort), completed cognitive and neuroimaging assessments at two time‐points (baseline at age ∼70; follow‐up ∼2.4 years later). At follow‐up, we assessed Complex Figure Drawing (copy; immediate recall; 30‐minute recall; 7‐day recall). Complex Figure items were categorized as 'outline' or 'detail' (Fig1), to test the hypothesis that forgetting the outline of the structure would be more sensitive to the effect of brain pathologies. ALF scores were calculated as the proportion of material retained after 7 days, relative to 30 minutes. Rates of cerebral atrophy between baseline and follow‐up were quantified from T1‐weighted MRI using the Brain Boundary Shift Integral (BBSI). β‐amyloid status (positive/negative) was determined from 18F‐Florbetapir‐PET. Baseline serum neurofilament light (NfL) was quantified (Quanterix Simoa assay). Multivariable regression models were used to investigate the effects (mutually adjusted) of β‐amyloid status, BBSI and NfL on ALF in n = 316 clinically‐normal individuals (50% female; 22% β‐amyloid positive; 30% APOE‐ε4 carriers), and to explore interactions between these predictors, adjusting for potential confounders including prospectively‐collected childhood cognitive ability and education. Result: 'Outline' items were better retained than 'detail' (Fig1). β‐amyloid‐positive participants had poorer ALF scores for 'outline' (but not 'detail') items (Fig1C; Table 1). Unexpectedly, higher NfL was associated with scores for 'outline' items (Table 1). Greater rate of cerebral atrophy predicted poorer retention among participants with elevated β‐amyloid and higher NfL (Table 1; Fig2). Conclusion: These results provide evidence of associations between biomarkers of brain pathologies and ALF in 73‐year‐olds. Interactions between different biomarkers merit further exploration. ALF may be a sensitive outcome measure for therapeutic trials in preclinical AD. Better retention of 'outline' (vs. 'detail') items illustrates the strategic role of memory selectivity. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Sleep disturbance is associated with an increased risk of developing Alzheimer's disease, yet the relationship between sleep metrics and brain pathology remains poorly understood. Complementing 'traditional' metrics such as total sleep time (TST) and sleep efficiency (SE), the midpoint of sleep, interdaily stability and intradaily variability provide important insights into chronotype and circadian rest activity rhythms. Methods: We used data from dementia‐free participants from the Insight 46 neuroscience sub‐study of the MRC National Survey of Health and Development (NSHD, British 1946 Birth Cohort). Hippocampal, whole brain, and white matter hyperintensity volume (WMHV), and amyloid status (positive/negative) were derived from volumetric T1 and FLAIR MRI, and 18F‐florbetapir amyloid‐PET at age 73. TST, SE, midpoint of sleep, interdaily stability, and intradaily variability were calculated from 6 nights of wrist actigraphy (Philips Actiwatch) at the same time point. Normal appearing white matter (NAWM) microstructure was assessed by diffusion weighted imaging at age 70. Mean z‐scores for each participant's neurite density index (NDI) and orientation dispersion index (ODI) were generated relative to normal controls. The relationship between sleep and imaging metrics was examined using generalised additive models to allow a flexible functional form for the sleep metrics. Where there was no evidence of a nonlinear effect, results are presented from linear regression (continuous outcomes) or logistic regression (binary outcomes). All analyses were controlled for TST, SE, age, gender, socioeconomic status, intracranial volume, and interval from imaging to actigraphy, in addition to blood pressure age 53, and body mass index for WMHV analyses. Results: There was a significant nonlinear relationship between TST and both hippocampal and brain volume, with ∼ 7 hours sleep appearing optimal (Table 1, Figure 1). Increasing TST and decreasing SE were associated with decreased NDI. Unexpectedly, increased interdaily stability was associated with an increased risk of being amyloid positive (P = 0.003, Figure 2). Conclusion: Sleep and circadian measures at age 73 were associated with brain microstructure, macrostructure, and amyloid pathology. Efficient sleep of around 7 hours is associated with optimal brain health. Ongoing longitudinal follow‐up will help to explore causality. [ABSTRACT FROM AUTHOR]

Background: In older adults, exposure to area disadvantage is associated with poorer cognitive performance, smaller whole brain and hippocampal volumes and cardiovascular risk. However, there is little research on the timing, accumulation and change in exposure to area disadvantage. This study aimed to investigate whether exposure to area disadvantage across the life course is associated with cognition and neurodegenerative pathology in late adulthood. Method: Data from the MRC National Survey of Heath and Development (British 1946 birth cohort; analytical sample: n = 1,762) and a neuroimaging sub‐study (Insight 46; analytical sample: n = 447) were used. Area disadvantage was defined as the percentage of employed individuals in semi‐skilled or unskilled occupations. In the full cohort we assessed the relationship of area disadvantage at 26, 53 and 60‐64 years, cumulative area disadvantage and area disadvantage change score with cognitive performance at 69. In Insight 46 we examined associations between area disadvantage and neuroimaging outcomes (69‐71 years): whole brain, hippocampal, and ventricular volumes, amyloid status, and white matter hyperintensity volume (WMHV). All analyses were adjusted for socio‐economic and lifestyle confounders, with the neuroimaging analyses also adjusted for age at scan and total intracranial volume. Result: Negative associations were found between exposure to area disadvantage at all ages and cognitive performance, with stronger effects at 53 and 60‐64 (Table 1). These effect sizes remained similar when adjusted for sex, father's social class and childhood emotional symptoms, but were attenuated when further adjusted for educational attainment and childhood cognition. A negative association was found between cumulative exposure to area disadvantage and cognitive performance (Table 1), and no effect was found from change in area disadvantage. WMHV was the only neurological outcome found to be associated with area disadvantage variables (Table 2). Conclusion: Living in a disadvantaged area across the life course is associated with poorer cognitive performance at age 69, most of this affect is accounted for by childhood cognition and educational attainment. Living in a disadvantaged area across the life course is also associated with higher WMHV, suggesting presumed cerebrovascular disease, a dementia risk factor. Further research is required to understand the mechanism driving this association. [ABSTRACT FROM AUTHOR]

Background: We investigated imaging biomarkers of Aβ and neurodegeneration in relation to tau‐PET Braak stage in a preclinical birth cohort. Method: Cognitively normal individuals enrolled in Insight 46, the neuroimaging sub‐study of the MRC National Survey of Health and Development (1946 British birth cohort), were scanned on combined PET/MR with [18F]florbetapir Aβ‐PET at age ∼70 years and again at ∼73 years. A sub‐sample enriched for Aβ (Aβ+; Centiloid> = 13, hole cerebellum reference) is currently being assessed with [18F]MK‐6240 tau‐PET at age ∼76 years. For this interim analysis, tau‐PET images (90‐110 minutes post‐injection) were co‐registered with T1‐weighted MRI. Anatomical areas were parcellated on the T1 to form Braak regions. Standard uptake value ratios (SUVRs) were calculated using an inferior cerebellar grey reference without partial volume correction. Tau‐PET positivity (Tau+) was defined using Gaussian mixture modelling in each region. Participants were assigned to Tau‐, Braak I‐II, III‐IV or V‐VI groups based on the most advanced Tau+ region. Group differences in baseline Aβ (Centiloids), Aβ accumulation (Centiloids/year) and hippocampal atrophy rate (%/year) were investigated with Mann‐Whitney U tests. Result: Analysis included 80 individuals with tau‐PET data (Table 1), 45% of the sample were Aβ+ by age 73. Three individuals did not conform to the Braak stage hierarchy (orange triangles, Figure 1). No Aβ‐ individuals were Tau+ beyond Braak I. Figure 2 shows baseline Aβ, Aβ accumulation and hippocampal atrophy rates for Braak stage groups for participants who had data at all timepoints (N = 78). Tau+ individuals (in any Braak region) had significantly higher baseline Aβ than Tau‐ individuals. Rate of annual Aβ accumulation was higher for Braak III‐IV and Braak V‐VI compared to Tau‐ individuals. Hippocampal atrophy rate was elevated for Braak V‐VI compared to Tau‐, and Braak III‐IV was borderline significant. Conclusion: In this preliminary analysis, tau‐PET positivity beyond Braak I was restricted to individuals who were Aβ+ three years prior. Participants with elevated tau aged 76 had increased Aβ at age 70. Increased rates of hippocampal atrophy were occurring at least three years prior to tau scanning in individuals with advanced tau pathology. These findings will be updated as more data is acquired. [ABSTRACT FROM AUTHOR]

Background: White matter hyperintensity volume (WMHV) is a presumed marker of cerebrovascular disease associated with ageing, Alzheimer's disease (AD) and vascular dementia. Higher baseline WMHV is associated with increased brain atrophy rate, with disproportionate effects in the hippocampus – a region affected early in AD. Understanding the relationships between longitudinal change in WMHV and hippocampal atrophy, while accounting for AD and cardiovascular risk factors, will increase our understanding of the multifactorial disease processes occurring during the early stages of AD. Method: Rate of change in WMHV was calculated using Bayesian Model Selection (BaMoS) and total hippocampal atrophy rate was calculated using the Boundary Shift Integral (BSI), measured concurrently between two time‐points. Participants with major neurological disorders were excluded. Linear regression was used to test whether rates of WMHV change predicted rates of hippocampal atrophy while adjusting for total intracranial volume (TIV), sex and age. Further models adjusted for baseline PET amyloid‐β (Aβ) standard uptake value ratio (SUVR), ApoE‐e4 carrier status, and Framingham heart study cardiovascular risk (FHS‐CVS) aged 69, and tested for interactions with rate of WMHV change. Result: 308 individuals with high‐resolution isotropic MRI data at two time‐points were analysed in this study (Table 1). For every 1ml/year increase in WMHV there was an associated 0.013ml/year decrease in total hippocampal volume (Table 2, Model 1). This association remained when adjusting for Aβ SUVR (Table 2, Model 2), ApoE‐e4 status (Table 2, Model 3), and FHS‐CVS (Table 2, Model 4). A separate semi‐partial correlation analysis showed 4.6% of variance in rate of hippocampal atrophy was uniquely explained by rate of WMHV change when accounting for TIV, sex and age. There were no significant interactions between rate of WMHV change and Aβ, ApoE‐e4 or FHS‐CVS in relation to hippocampal atrophy rate. Conclusion: Increases in WMHV were significantly associated with progressive hippocampal atrophy accounting for head size, age and sex. These associations were not materially changed when adjusting for amyloid deposition, ApoE‐e4 or cardiovascular risk factors. These results suggest systemic processes that contribute to WMH development also contribute to hippocampal atrophy. Further work is required to determine the processes that drive this relationship. [ABSTRACT FROM AUTHOR]

Background: We investigated imaging biomarkers of Aß and neurodegeneration in relation to tau‐PET Braak stage in a preclinical birth cohort. Method: Cognitively normal individuals enrolled in Insight 46, the neuroimaging sub‐study of the MRC National Survey of Health and Development (1946 British birth cohort), were scanned on combined PET/MR with [18F]florbetapir Aß‐PET at age ∼70 years and again at ∼73 years. A sub‐sample enriched for Aß (Aß+; Centiloid> = 13, hole cerebellum reference) is currently being assessed with [18F]MK‐6240 tau‐PET at age ∼76 years. For this interim analysis, tau‐PET images (90‐110 minutes post‐injection) were co‐registered with T1‐weighted MRI. Anatomical areas were parcellated on the T1 to form Braak regions. Standard uptake value ratios (SUVRs) were calculated using an inferior cerebellar grey reference without partial volume correction. Tau‐PET positivity (Tau+) was defined using Gaussian mixture modelling in each region. Participants were assigned to Tau‐, Braak I‐II, III‐IV or V‐VI groups based on the most advanced Tau+ region. Group differences in baseline Aß (Centiloids), Aß accumulation (Centiloids/year) and hippocampal atrophy rate (%/year) were investigated with Mann‐Whitney U tests. Result: Analysis included 80 individuals with tau‐PET data (Table 1), 45% of the sample were Aß+ by age 73. Three individuals did not conform to the Braak stage hierarchy (orange triangles, Figure 1). No Aß‐ individuals were Tau+ beyond Braak I. Figure 2 shows baseline Aß, Aß accumulation and hippocampal atrophy rates for Braak stage groups for participants who had data at all timepoints (N = 78). Tau+ individuals (in any Braak region) had significantly higher baseline Aß than Tau‐ individuals. Rate of annual Aß accumulation was higher for Braak III‐IV and Braak V‐VI compared to Tau‐ individuals. Hippocampal atrophy rate was elevated for Braak V‐VI compared to Tau‐, and Braak III‐IV was borderline significant. Conclusion: In this preliminary analysis, tau‐PET positivity beyond Braak I was restricted to individuals who were Aß+ three years prior. Participants with elevated tau aged 76 had increased Aß at age 70. Increased rates of hippocampal atrophy were occurring at least three years prior to tau scanning in individuals with advanced tau pathology. These findings will be updated as more data is acquired. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Subjective Cognitive Decline (SCD) may represent the onset of cognitive decline before impairment on standard cognitive tests occurs (Jessen et al., 2014). Previous cross‐sectional studies were shown to have limited ability to capture objective differences in cognitive performance between groups with and without SCD (Cacciamani et al., 2017). Understanding the interplay between changes in subjective memory ratings and objective cognitive function over time may have utility in identifying people at risk of dementia. Method: 370 cognitively normal (CN) individuals with complete cognitive data (Table 1 for characteristics) from Insight 46, a longitudinal neuroscience sub‐study of the MRC National Survey for Health and Development (the British 1946 Birth Cohort), underwent cognitive, clinical, and physical assessments, and neuroimaging (combined MRI/18F‐Florbetapir‐PET). SCD was measured using MyCog (Rami et al., 2014) a validated tool, from the SCD‐Questionnaire, where higher scores indicate greater subjective complaints. Linear regression models were used to test whether longitudinal cognitive change as measured using the Preclinical Alzheimer Cognitive Composite (PACC) and a visual short‐term memory binding task were influenced by baseline MyCog and whether there are parallel associations between rates of change in MyCog and longitudinal cognitive change. Covariates were sex, age at baseline visit, childhood cognitive ability, educational attainment, and adult socioeconomic position. Result: Baseline MyCog scores did not predict rates of change in PACC or visual short‐term memory binding outcome measures (Table 2). Rates of MyCog change alone did not predict rate of change in PACC, localisation error, total correct number of trials or proportion of misbinding errors (Table 3). However, we observed an interaction effect with baseline amyloid‐b status, whereby greater rates of subjective memory concerns predicted faster rates of decline in the proportion of misbinding errors in amyloid‐b positive participants only (Table 3; Figure 1). Conclusion: These findings suggest that higher amyloid‐b burden in CN individuals with subjective memory complaints is associated with faster rates of decline in visual working memory. Corroborating previous reports that feature binding tasks can objectify subtle cognitive deficits found in SCD (Koppara et al., 2015) and serve as a promising tool for identifying people at risk of dementia. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, adolescent carers in the UK may have experienced psychological distress owing to increased caring burden and loss of a break from their caring role. This study investigated longitudinal association between adolescents' caring status and mental health outcomes from 2018/2019 to February–March 2021. The participants (n = 3,927) answered mental health questions in both the Millennium Cohort Study sweep 7 survey (age 17 years in 2018/2019) and at least one of three waves of the COVID-19 survey from May 2020 to February–March 2021. Caring status at the age of 17 years was assessed using a single question regarding whether the participant regularly looked after anyone who needed care, without being paid. Outcome measures were psychological symptoms, measured using the Kessler Distress Scale, and mental well-being, measured using the Warwick-Edinburgh Mental Well-being Scale. Compared with 3,616 noncarers, 311 (7.9%) adolescent carers reported significantly higher Kessler Distress Scale and lower Warwick-Edinburgh Mental Well-being Scale scores during the pandemic. These associations were largely explained by psychosocial risk factors. Worse outcomes were associated with poor sleep quality, attempted suicide at baseline, low social support, and a strong feeling of loneliness during the pandemic. These factors were significantly more likely to be observed among adolescent carers than noncarers. UK adolescent carers exhibited worsened mental health outcomes one year after the first national lockdown. This increased distress may be attributable to psychosocial risk factors during the pre–COVID-19 and current COVID-19 periods, and they require psychosocial support. [ABSTRACT FROM AUTHOR]

Despite growing concerns in the UK about social isolation, there remains a lack of data on the extent and time trends of social isolation from longitudinal, population-based studies. There is also little research that assesses the multiple domains of social isolation across the lifecourse and between generations in a holistic way accounting for different contexts. By applying a multi-context, multi-domain framework of social isolation to 5 successive British birth cohorts, we provide conceptual and empirical understanding of social isolation trajectories across the lifecourse and identify potential generational and sex differences in trends. Where data were available, comparable social isolation indicators were generated to enable lifecourse trajectories and cross-generational trends to be explored. Information on isolation was available across the following relational contexts: household i.e., living alone; partnership, family and friends outside the household; education and employment networks; and community engagement. Trajectories were modelled stratified by sex using a multilevel growth curve framework. Data were analysed from 73,847 individuals (48.5% female), in 5 successive cohorts born in 1946 (N = 5,362), 1958 (N = 16,742), 1970 (N = 16,950), 1989-90 (N = 15,562), and 2000–01 (N = 19,231). Exploring a range of social isolation indicators across several contexts provided a nuanced picture of social isolation across the lifecourse and between generations in the UK, with no consistent pattern of increased or decreased isolation over time. For example, more people are living alone, less women are out of education and employment in midlife, more people are volunteering, but fewer people regularly engage in religious activity. It therefore highlights the need to focus on a range of social isolation indicators across contexts to understand how people compensate for specific types of isolation, and to understand structural differences in social configurations in the UK, which may not only define the timing and sequencing of life transitions but also social isolation. • First document of lifecourse social isolation across multiple British generations. • No consistent pattern of increased or decreased isolation over time. • More people living alone, less women out of education and employment in midlife. • More people volunteering, but fewer people regularly engaging in religious activity. • Support for a multi-context, multi-domain approach to studying social isolation. [ABSTRACT FROM AUTHOR]

There is an urgent need for interventions that can prevent or delay cognitive decline and dementia. Decades of epidemiological research have identified potential pharmacological strategies for risk factor modification to prevent these serious conditions, but clinical trials have failed to confirm the potential efficacy for such interventions. Our multidisciplinary international group reviewed seven high‐potential intervention strategies in an attempt to identify potential reasons for the mismatch between the observational and trial results. In considering our findings, we offer constructive recommendations for the next steps. Overall, we observed some differences in the observational evidence base for the seven strategies, but several common methodological themes that emerged. These themes included the appropriateness of trial populations and intervention strategies, including the timing of interventions and other aspects of trials methodology. To inform the design of future clinical trials, we provide recommendations for the next steps in finding strategies for effective dementia risk reduction. [ABSTRACT FROM AUTHOR]

Background: We aim to assess how the timing of being physically active in adulthood is associated with later‐life cognitive function; and estimate to what extent these effects are explained by pathways including earlier life influences, cardiovascular and mental health. Method: Data from participants (n = 1417, 53% female) in the British 1946 birth cohort were included. Physical activity was assessed across adulthood at ages 36, 43, 53, 60 and 69 by interviews and categorised into: 0)Not active; 1)Moderately active (participated in physical activity 1‐4 times per month); 2) Most active (participated 5+ times per month). Responses were additionally binarized and summed to create a cumulative exposure of adulthood physical activity. Cognition at age 69 was assessed by the Addenbrooke's Cognitive Examination (ACE‐III)). Regression analyses examined associations between physical activity measures and later‐life cognition, adjusting for childhood cognition; childhood socioeconomic position (SEP); education; cardiovascular health (Framingham risk score at age 69); emotional symptoms (general health questionnaire at age 69); and APOE‐e4 status. A structural equation modelling analysis further tested the life course models of sensitive period and accumulation for describing how physical activity was best related to later‐life cognition. Result: Compared to those not active, those who were moderately and most physically active, at every age, had higher ACE‐III scores at age 69 (Figure 1). Being physically active across different periods was associated with better cognitive state, in a dose‐response manner (Figure 1). Adjusting for childhood cognition, childhood SEP and education largely attenuated these effects but results mainly remained significant at the 5% level; adjustment for cardiovascular risk, mental health and APOE‐e4 status did not attenuate associations (Figure 1). An accumulation model of physical activity was the best fit (Table 1). Conclusion: We provide evidence from two complementary analyses that maintaining physical activity across different periods of adulthood is related to better later‐life cognitive state in a dose response manner, even after adjustment for variables that predict physical activity and later‐life cognition, such as childhood cognition, education and SEP. These relationships were independent of cardiovascular and mental health and APOE‐E4 status. [ABSTRACT FROM AUTHOR]

Background: Fixel‐based analysis (FBA) of diffusion MRI allows analysis of brain white matter (WM) tracts with greater specificity than voxel‐based approaches, including measures of microstructural fibre density (FD), macrostructural fibre cross section (FC), and representations of crossing fibres. We use FBA to explore early WM changes associated with amyloid‐β (Aβ) prior to manifestations of Alzheimer’s disease. We additionally explored global WM changes associated with increased cardiovascular risk. Method: We performed FBA on 233 participants in the Insight 46 birth cohort study, all of whom have been followed prospectively since birth in a single week in 1946, including cardiovascular risk assessment using the Framingham Risk Score (FRS). At age 69‐71 participants underwent cognitive assessment and combined 18F‐florbetapir PET‐MRI scans on a single scanner. Aβ positive status was defined using a Gaussian mixed model as a standardised uptake value ratio over 0.6103. Using Aβ positive (n=40) and negative (n=193) participants with no major brain disorders and excellent scan quality, we assessed FD and FC, as well as the combined FD and FC (FDC) metric across all white matter fixels. Subsequently we performed a tract‐of‐interest analysis of associations between Aβ and FDC in 13 selected white matter tracts, 7 defined a priori based on Alzheimer’s disease mechanisms, and 6 based on results of the global analysis. Result: Aβ positivity was associated with changes in microstructural and macrostructural changes (FD, FC and FDC), throughout the right corticospinal tract inferior to the internal capsule, and microstructurally in the right inferior longitudinal fasciculus. Similar left sided corticospinal changes were seen in FC and FDC only. Increased FRS was associated with FD changes in the right superior longitudinal fasciculus. Tract‐of‐interest analyses showed no significant associations between FDC and Aβ after false discovery correction using the Benjamini‐Hochberg method. Conclusion: We show Aβ associated changes in fixel‐based metrics in the corticospinal tracts, predominantly affecting the right hemisphere. These preliminary results raise the possibility of these fibres being predisposed to damage, perhaps in a length dependent manner, though longitudinal analysis based on further phases of Insight 46 may prove more powerful to detect change at this very early stage. [ABSTRACT FROM AUTHOR]

Background: In Alzheimer's disease, early amyloid‐β and tau deposition may have differential downstream effects on synaptic function and neuronal loss in a stage‐dependent manner. Amyloid‐related synaptic changes are thought to precede tau accumulation, which starts in the medial temporal lobe before propagating and leading to neurodegeneration. We explored whether microstructural MRI measures can detect these different sequential cortical changes. Method: Seventy‐nine healthy, asymptomatic individuals, recruited from the Insight 46 study of the British 1946 birth cohort underwent combined PET/MR with [18F]florbetapir Aβ‐PET at ∼73yrs, and [18F]MK‐6240 tau‐PET at ∼76yrs. Standard uptake value ratios were calculated using a whole cerebellar reference for florbetapir and an inferior cerebellar reference for MK‐6240. Multi‐shell diffusion MRI was acquired; neurite orientation dispersion and density imaging was used to quantify neurite density (NDI) and orientation dispersion (ODI, a proxy measure of dendritic morphology/complexity), with DTI measuring mean diffusivity (MD), a less specific measure of degenerative change. PET and microstructural MRI biomarkers were assessed in a neocortical composite ROI and across Braak stages. Result: Thirty‐six participants were amyloid positive, 18 of whom were tau positive (eight Braak stage 1‐2, four Braak 3‐4, six Braak 5‐6). Across all participants, in the neocortical composite, significant differences between amyloid positive and amyloid negative individuals were found in both tau PET (p = 0.0092) and ODI (p = 0.030) but not for other measures. Within the amyloid positive group, in the cortical composite, significant differences in MD (p = 0.0093) but not ODI were seen when comparing those who were tau positive and negative. In the amyloid positive group, there was an association between tau PET and MD in the MTL (Braak 1‐2) (r = 0.34, p = 0.040) and Braak 3‐4 (r = 0.37, p = 0.025), with an association between tau and ODI (r = 0.48, p = 0.0031) in Braak 3‐4 only. After adjusting for volume, only the association between tau PET and ODI in Braak 3‐4 remained (p = 0.038). Conclusion: Our results are consistent with amyloid deposition causing dendritic/changes (as assessed by ODI) with consequent synaptic dysfunction. Later tau propogation is then associated with frank neuronal breakdown (as measured by MD). dMRI cortical imaging biomarkers have the potential to provide proxy measures of underlying AD stage/pathology prior to symptom onset. [ABSTRACT FROM AUTHOR]

Background: Earlier menopause age associates with poorer cognitive performance post‐menopause, but links with dementia risk are mixed and the potential mechanisms underlying such associations are unclear. Few studies have examined the relationship between menopause age and later‐life brain health. Method: Our study included 126 women from Insight 46, the neuroscience sub‐study of the 1946 British birth cohort, which included combined amyloid PET and MRI scanning at mean age 70.7 years (standard deviation = 0.66). Age at natural menopause was self‐reported, during midlife, as years since birth at the time of period cessation; women who reported surgical menopause were excluded (n = 63). We tested for interactions of menopause age with APOE‐ε4 status and used multivariable regression analyses to test associations of menopause age with later‐life total brain volume (TBV) and hippocampal volume. A generalised linear model with log‐linked gamma distribution tested associations with white matter hyperintensity volume (WMHV). Models were cumulatively adjusted for total intracranial volume and age at scan (model 0/M0), hormone therapy (HT) use (M1:M0+HT) and for prospective early‐life and sociodemographic (M2:M1+childhood cognition, education, adult socioeconomic position), reproductive (M3:M2+menarche age, parity), and health‐related (M4:M3+smoking, BMI and blood pressure at age 36 years, APOE‐ε4 status) covariables. Result: The association of menopause age with WMHV was modified by APOE‐ε4 status (p = 0.024); each 1‐year increase in menopause age associated with a 7.4% decrease in WMHV for ε4 carriers (n = 35) and a 2.4% WMHV increase for non‐carriers (n = 90). Menopause age did not associate with hippocampal volume, but there was a positive association with TBV (Table 1) which remained significant until we accounted for health‐related factors in model 4 (Figure 1). In post‐hoc analysis, adjustment for blood pressure at age 36 attenuated the association by 11.24%, explaining more of the attenuation than other model 4 covariables. Conclusion: We find evidence for links between age at natural menopause and later‐life neuroimaging measures. Later menopause associated with greater brain volume, partly explained by midlife blood pressure. Interactive effects of APOE‐ε4 status on associations with WMHV, an indicator of brain pathology, warrant further investigation. [ABSTRACT FROM AUTHOR]

Background: Depression and anxiety are well recognised as risk factors for dementia and poorer cognitive outcomes. However, considerably less is known about the relationship between quality of life and cognitive function over time. Quality of life is not simply the absence of mental health problems, but instead is a related but distinct construct. In particular, it is unclear whether poorer quality of life precedes cognitive decline, or vice versa or whether there is a bidirectional relationship. This is of import because understanding directionality allows us to start to plan interventions around dementia risk reduction. The aim of this study was to test bidirectionality between quality of life and memory in a large, nationally representative sample of people aged 50+ without cognitive impairment. Method: Data were used from the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort comprising 12,099 people over the age of 50 and their partners. Repeated measures of quality of life and memory (immediate and delayed) were available nine times over a 17‐year period. Cross‐lagged models were fitted to test for bidirectionality between quality of life and memory function. Result: The fully adjusted model revealed that higher quality of life was significantly associated with higher subsequent immediate memory scores at all time‐points, and with higher subsequent delayed memory scores at all except the final time‐point. There was no consistent evidence that memory was significantly associated with subsequent quality of life. Conclusion: These results extend previous research by providing evidence for the temporal association between quality of life and memory in a population‐based sample of people aged 50+. Specifically, results suggest that quality of life is consistently associated with later memory function over nearly two decades, though the study did not provide evidence that the association operates in the opposite direction. The lack of consistent evidence for a relationship between cognitive function and subsequent quality of life may be due to the exclusion of people with cognitive impairment and adjustment for depressive symptoms. Better quality of life may act as a protective factor in retaining memory function from middle to later adulthood. [ABSTRACT FROM AUTHOR]

Background: Social health (SH) markers, including marital status, contact frequency, network size, and social support, have been linked with increased cognitive capability. However, the underlying mechanisms remain poorly understood. We aim to investigate whether depression symptoms and inflammatory biomarkers mediate associations between SH and cognitive outcomes. Method: We used data from waves 1‐9 of the English Longitudinal Study of Ageing, involving 7,136 participants aged 50 or older at baseline. First, we examined associations between SH (wave 1) and depression and inflammatory biomarkers (C‐reactive protein (CRP) and fibrinogen) (wave 2) using linear regression models. Second, we tested associations between a) SH and b) depression and inflammation with subsequent standardised verbal fluency and memory in wave 3 and change between waves 3‐9, indexed using slopes derived from multilevel models. We adjusted for age, sex, socio‐economic position, cardiovascular disease, basic and instrumental activities of daily living, health behaviours, and baseline depression symptoms and cognition. We will also conduct causal mediation analysis. Result: All SH markers, except contact frequency, were associated with lower subsequent depression, but not inflammatory biomarkers. Greater contact frequency (e.g. once‐twice a week vs 6 people vs none: β = 0.007SD/year [0.001, 0.012]), less negative (β = 0.001SD/year [0.001, 0.002]) and more positive support (β = 0.001SD/year [0.000, 0.001]) were linked with slower memory decline, and more positive support predicted slower verbal fluency decline (β = 0.001SD/year [0.000, 0.001]). Depression symptoms were associated with lower memory and verbal fluency, and faster memory decline (β = ‐0.001SD/year [‐0.001, ‐0.000]) and verbal fluency (β = ‐0.001SD/year [‐0.001, ‐0.000]). CRP was associated with lower verbal fluency (β = ‐0.02 [‐0.04, 0.00]), whereas fibrinogen was linked with faster memory decline (β = ‐0.001SD/year [‐0.003, ‐0.000]). Conclusion: Depression symptoms and SH showed associations with subsequent cognitive capability and change. SH was linked with lower depression, but not inflammatory biomarkers. Findings highlight the potential for depression to underpin associations between SH and cognition, a pathway which we will test using causal mediation analysis. We will also examine whether findings replicate in the Swedish National Study of Aging and Care in Kungsholmen. [ABSTRACT FROM AUTHOR]

Background: Primary care psychological therapy services can be effective in reducing symptoms of depression and anxiety in people living with dementia (PLWD) and are recommended in national guidelines (e.g., NICE, UK). However, it is currently unknown which factors are associated with better psychological therapy outcomes in PLWD. Method: National linked healthcare records (IAPT, HES, MHSD, HES‐ONS mortality data) were used to identify 1,522 PLWD who attended psychological therapy services across England. Associations between various factors (dementia‐specific and non‐dementia specific) and therapy outcomes on widely used anxiety (GAD7) and depression (PHQ9) measures (reliable improvement, recovery, deterioration, dropout) were explored. Result: People with FTD were more likely to experience a deterioration in depression or anxiety symptoms compared to people with vascular dementia (OR = 2.98, 95%CI[1.08,8.22], p =.03) and people with Alzheimer's disease (OR = 2.95, 95%CI[1.15,7.55], p =.03). Age at dementia diagnosis did not predict any therapy outcomes after controlling for sociodemographic and clinical factors. Greater depression severity (recovery: OR =.95, 95%CI[.92,.98], p<.001; deterioration: OR = 1.73, 95%CI[1.04,2.90], p =.04), lower anxiety severity (improvement: OR = 1.06, 95%CI[1.03,1.09], p<.001; deterioration: OR =.89, 95%CI[.84,.94], p<.001; dropout: OR = 1.06, 95%CI[1.02,1.11], p =.01), lower work and social functioning (improvement: OR =.98, 95%CI[.96,.99], p =.002; recovery: OR =.98, 95%CI[.96.99], p =.002; dropout: OR = 1.03, 95%CI[1.01,1.05], p =.01), psychotropic medication use (improvement: OR =.62, 95%CI[.46,.84], p =.002; recovery: OR =.67, 95%CI[.51,.90], p =.01; deterioration: OR = 1.73, 95%CI[1.04,2.90], p =.04), being working age (improvement: OR = 2.11, 95%ci[1.10, 4.04], p =.02; recovery: OR = 2.03, 95%CI[1.10,3.73], p =.02), and fewer therapy sessions (improvement: OR = 1.10, 95%CI[1.06,1.14], p<.001; recovery: OR = 1.12, 95%CI[1.09,1.16], p<.001) were all associated with worse psychological therapy outcomes in PLWD. Conclusion: Predictors of psychological therapy outcomes in PLWD were largely in line with those identified for a general population above and beyond dementia‐specific factors. Additional support and adaptations, such as more therapy sessions and regular clinical reviews, may be required to improve therapy outcomes in PLWD, particularly in those who are younger and have more severe depression. [ABSTRACT FROM AUTHOR]

Background: Word‐finding difficulties are a common early feature of Alzheimer's disease (AD) and may be detectable during the preclinical stage. However, the relationship between changes in naming ability and accumulation of β‐amyloid pathology is not fully understood, and questions remain about the role of factors such as sex and education. Method: Participants in Insight 46, a sub‐study of the British 1946 birth cohort, completed baseline cognitive assessments and neuroimaging (combined MRI/18F‐Florbetapir‐PET) at age 69‐71. Follow‐up assessments are currently underway (mean interval 28.9 months, SD 2.1) and include an audio‐recorded version of the 30‐item Graded Naming Test (GNT), which was not administered at baseline. Preliminary interim analyses have been conducted based on 211 cognitively‐normal individuals with complete neuroimaging data (see Table 1 for characteristics). A multivariable regression model was used to investigate predictors of picture naming accuracy, where the outcome was GNT score (max. 30) and predictors were sex, age at follow‐up assessment, β‐amyloid status at baseline (positive / negative), APOE genotype (ε4 carrier/non‐carrier), and prospectively‐collected measures of childhood cognitive ability, education and socioeconomic position (based on occupation). Due to the negatively‐skewed distribution of GNT scores, bootstrapping was used to produce bias‐corrected and accelerated 95% confidence intervals from 2,000 replications. Results will be updated to include the full sample before the conference. We also plan to include data on naming latency extracted from the audio‐recordings, which may be a more sensitive measure of early changes than naming accuracy. Result: Higher childhood cognitive ability predicted higher GNT scores over 60 years later (Table 2, Figure 1). Men scored 0.9 points higher than women on average. Amyloid‐positive participants scored 1.2 points lower than amyloid‐negative participants on average. These effects were all significant at the 5% level and were mutually independent. Conclusion: Subtle changes in naming accuracy associated with β‐amyloid pathology are detectable in cognitively‐normal individuals as early as age 72. Performance is additionally influenced by sex and general cognitive ability, so these factors should be accounted for where possible in future studies and clinical trials that seek to detect and track the emergence of naming deficits. [ABSTRACT FROM AUTHOR]

Background: Accelerated Forgetting (AF) is the phenomenon whereby material is retained normally over short intervals (minutes or hours) but forgotten abnormally rapidly over longer periods (days or weeks). AF has been observed in presymptomatic carriers of mutations causing familial Alzheimer's disease (AD) (doi:10.1016/S1474‐4422(17)30434‐9). To our knowledge, no studies have investigated whether AF is sensitive to preclinical AD pathology in cognitively‐normal older adults. Method: Participants in the Insight 46 study, a sub‐study of the British 1946 birth cohort, completed baseline cognitive and neuroimaging assessments at age 69‐71. For the follow‐up visits (∼29 months later), we complemented the clinic visit assessments of Complex Figure Drawing and the Face‐Name test (FNAME‐12) with a 7‐day delay version administered by telephone (Figure 1). AF scores were calculated as the percentage of material retained after 7 days, relative to retention after 30 minutes. Cerebral atrophy between baseline and follow‐up was quantified from T1‐weighted MRI using the Brain Boundary Shift Integral (BBSI). β‐amyloid status at baseline (positive / negative) was determined from 18F‐Florbetapir‐PET. As follow‐up assessments are still underway, preliminary interim analyses have been conducted based on 195 cognitively‐normal individuals with complete neuroimaging data (see Table 1 for characteristics). Multivariable regression models were used to investigate the effects of β‐amyloid status and BBSI on AF, and to explore interactions between these two predictors, adjusting for potential confounders including prospectively‐collected measures of childhood cognitive ability and education. Result: Despite no statistically‐significant differences after a 30‐minute delay, β‐amyloid‐positive participants retained a lower percentage of Complex Figure material over 7 days (71.8% vs. 80.7%, p=0.010) and a trend to a lower percentage of FNAME‐12 material (69.4% vs. 77.2%, p = 0.083) (Table 2, Figure 2). Higher education predicted better retention of the Complex Figure. Among β‐amyloid‐positive participants only, greater cerebral atrophy predicted poorer retention of the Complex Figure (Table 2, Figure 3). Conclusion: These results provide novel evidence of AF in cognitively‐normal β‐amyloid‐positive 72‐year‐olds. AF may be a sensitive outcome measure for therapeutic trials in preclinical AD, as it may reveal subtle memory decline at an earlier stage than traditional assessments. The interaction between β‐amyloid pathology and cerebral atrophy merits longitudinal investigation. [ABSTRACT FROM AUTHOR]

Background: Accelerated Forgetting (AF) is the phenomenon whereby material is retained normally over short intervals (minutes or hours) but forgotten abnormally rapidly over longer periods (days or weeks). AF has been observed in presymptomatic carriers of mutations causing familial Alzheimer's disease (AD) (doi:10.1016/S1474‐4422(17)30434‐9). To our knowledge, no studies have investigated whether AF is sensitive to preclinical AD pathology in cognitively‐normal older adults. Method: Participants in the Insight 46 study, a sub‐study of the British 1946 birth cohort, completed baseline cognitive and neuroimaging assessments at age 69‐71. For the follow‐up visits (∼29 months later), we complemented the clinic visit assessments of Complex Figure Drawing and the Face‐Name test (FNAME‐12) with a 7‐day delay version administered by telephone (Figure 1). AF scores were calculated as the percentage of material retained after 7 days, relative to retention after 30 minutes. Cerebral atrophy between baseline and follow‐up was quantified from T1‐weighted MRI using the Brain Boundary Shift Integral (BBSI). β‐amyloid status at baseline (positive / negative) was determined from 18F‐Florbetapir‐PET. As follow‐up assessments are still underway, preliminary interim analyses have been conducted based on 195 cognitively‐normal individuals with complete neuroimaging data (see Table 1 for characteristics). Multivariable regression models were used to investigate the effects of β‐amyloid status and BBSI on AF, and to explore interactions between these two predictors, adjusting for potential confounders including prospectively‐collected measures of childhood cognitive ability and education. Result: Despite no statistically‐significant differences after a 30‐minute delay, β‐amyloid‐positive participants retained a lower percentage of Complex Figure material over 7 days (71.8% vs. 80.7%, p=0.010) and a trend to a lower percentage of FNAME‐12 material (69.4% vs. 77.2%, p = 0.083) (Table 2, Figure 2). Higher education predicted better retention of the Complex Figure. Among β‐amyloid‐positive participants only, greater cerebral atrophy predicted poorer retention of the Complex Figure (Table 2, Figure 3). Conclusion: These results provide novel evidence of AF in cognitively‐normal β‐amyloid‐positive 72‐year‐olds. AF may be a sensitive outcome measure for therapeutic trials in preclinical AD, as it may reveal subtle memory decline at an earlier stage than traditional assessments. The interaction between β‐amyloid pathology and cerebral atrophy merits longitudinal investigation. [ABSTRACT FROM AUTHOR]

Background: Word‐finding difficulties are a common early feature of Alzheimer's disease (AD) and may be detectable during the preclinical stage. However, the relationship between changes in naming ability and accumulation of β‐amyloid pathology is not fully understood, and questions remain about the role of factors such as sex and education. Method: Participants in Insight 46, a sub‐study of the British 1946 birth cohort, completed baseline cognitive assessments and neuroimaging (combined MRI/18F‐Florbetapir‐PET) at age 69‐71. Follow‐up assessments are currently underway (mean interval 28.9 months, SD 2.1) and include an audio‐recorded version of the 30‐item Graded Naming Test (GNT), which was not administered at baseline. Preliminary interim analyses have been conducted based on 211 cognitively‐normal individuals with complete neuroimaging data (see Table 1 for characteristics). A multivariable regression model was used to investigate predictors of picture naming accuracy, where the outcome was GNT score (max. 30) and predictors were sex, age at follow‐up assessment, β‐amyloid status at baseline (positive / negative), APOE genotype (ε4 carrier/non‐carrier), and prospectively‐collected measures of childhood cognitive ability, education and socioeconomic position (based on occupation). Due to the negatively‐skewed distribution of GNT scores, bootstrapping was used to produce bias‐corrected and accelerated 95% confidence intervals from 2,000 replications. Results will be updated to include the full sample before the conference. We also plan to include data on naming latency extracted from the audio‐recordings, which may be a more sensitive measure of early changes than naming accuracy. Result: Higher childhood cognitive ability predicted higher GNT scores over 60 years later (Table 2, Figure 1). Men scored 0.9 points higher than women on average. Amyloid‐positive participants scored 1.2 points lower than amyloid‐negative participants on average. These effects were all significant at the 5% level and were mutually independent. Conclusion: Subtle changes in naming accuracy associated with β‐amyloid pathology are detectable in cognitively‐normal individuals as early as age 72. Performance is additionally influenced by sex and general cognitive ability, so these factors should be accounted for where possible in future studies and clinical trials that seek to detect and track the emergence of naming deficits. [ABSTRACT FROM AUTHOR]

Background: We examined cross‐sectional associations between plasma phospho‐tau181 (p‐tau181) and amyloid PET, MRI and cognitive outcomes in Insight 46, a sub‐study of the British 1946 birth cohort. Method: At age 69‐71, participants underwent blood sampling, neurocognitive assessment, and 3T‐MRI with simultaneous 18F‐florbetapir‐PET (yielding amyloid status binarized at grey matter:eroded white matter SUVR 0.6104). Plasma p‐tau181 was measured by a homebrew Simoa immunoassay. ROC analyses were performed for amyloid status incorporating p‐tau181 into a model combining age, sex and APOE ε4 carrier status (APOE ε4). Linear regression examined associations between p‐tau181 (predictor) and (A): cognitive measures (preclinical AD cognitive composite (PACC), digit‐symbol substitution (DSS), delayed logical memory (LMD), and 12‐item‐face‐name association memory (FNAME‐12)), adjusting for age, sex, APOE ε4, childhood cognition, socioeconomic position and education; and (B): imaging biomarkers of neurodegeneration (whole brain, ventricular and hippocampal volumes (WBV,VV,HV) and AD‐signature cortical thickness (CTh)) and vascular disease (white matter hyperintensity volume (WMHV)), adjusting for age, sex, APOE ε4, amyloid status and total intracranial volume as appropriate. Result: After excluding those with prior neurological diagnoses, mild cognitive impairment or dementia, 444 individuals had complete plasma p‐tau181 data (Table 1); 410 had high‐quality amyloid PET data. An amyloid status ROC model using plasma p‐tau181 alone had an AUC of 0.720,95%CI[0.657,0.783]. This was not significantly different from the prediction of a base model incorporating age, sex and APOE ε4 (0.692[0.622,0.761]), but adding plasma p‐tau181 to the base model improved it significantly (0.787[0.737,0.837],2p<0.001: figure 1). The numbers needed to pre‐screen for a pre‐symptomatic Alzheimer's trial could be reduced by about 27% by using the latter compared to the base model (table 2). Higher p‐tau181 was associated with lower FNAME‐12 (z‐score‐change for 10% p‐tau181 rise: ‐0.020,95%CI[‐0.033,‐0.007],p=0.003) and lower PACC (‐0.013[‐0.022,‐0.005],p=0.002). Only the latter association was significantly attenuated by further adjustment for amyloid status. Higher p‐tau181 was associated with higher VV (ratio‐change for 10% p‐tau181 rise: 1.010, 95%CI[1.003,1.017],p=0.007) and lower CTh (0.999[0.998,1.000],p=0.007). DSS, LMD, HV, WBV and WMHV had no significant associations with p‐tau181. Conclusion: In cognitively normal individuals, plasma p‐tau181 may contribute toward pre‐screening for amyloid PET positivity, and is associated with cognitive performance and imaging biomarkers of neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: Insight 46 is a longitudinal neuroscience sub‐study of the MRC National Survey of Health and Development (the British 1946 Birth Cohort). In March 2020, the COVID‐19 pandemic, and the introduction of lockdown measures across the UK, demanded a transition from traditional face‐to‐face data collection methods to teleconference‐based testing, to ensure the safety of our vulnerable cohort and the ongoing collection of longitudinal data. We present our approach to adapting and expanding our existing telephone assessment procedures to include as many tests as possible from our standard neuropsychology battery. Methods: Participants with a computer or tablet with a webcam, microphone, and screen dimensions greater than 9 inches were offered a Microsoft Teams videoconference assessment; those without were offered a telephone visit to ensure maximum data collection. Videoconference and telephone batteries were created under copyright agreements. Item‐by‐item responses were collected digitally, and audio‐recording software was used to capture verbal responses where appropriate. Pre‐visit packs containing assessment materials in sealed envelopes (to prevent advance sight of materials) were sent ahead of each assessment. Due to specific equipment or software requirements, computerised assessments could not be performed (see Table 1). Result: 65% of the remaining eligible participants completed a remote assessment (see table 2). Despite offering one‐to‐one videoconferencing training, a major reason for drop‐out was concerns about technology, in addition to hearing difficulties and other health considerations. During administration, challenges included ensuring a standardised research environment and overcoming technological issues. Detailed scripts and protocols were implemented to guarantee uniform administrations, as well as detailed recording of unexpected events such as distractions and technology failures. Conclusion: Our methods allowed for the continuation of longitudinal data collection, demonstrating the feasibility of teleneuropsychology in elderly populations. Positive feedback demonstrated participants' acceptance of telehealth approaches and their appreciation of the value of continuing research. Future implementation of these methods could increase retention in populations previously prevented by physical barriers. However, careful consideration must be given to the validity and reliability of remote administration, and the differences between telephone and videoconferencing methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Importance: Associations between affective symptoms and mortality have been evaluated, but studies have not examined timing or cumulative exposure to affective symptoms over the life course.Objectives: To examine how lifetime accumulation and timing of affective symptoms are associated with mortality and identify potential explanatory factors.Design, Setting, and Participants: Data were obtained from the MRC National Survey of Health and Development (1946 British birth cohort), a socially stratified, population-based sample originally consisting of 5362 singleton births in England, Wales, and Scotland during March 1946. The cohort has been followed up 24 times, most recently in 2014-2015. Eligible participants included those flagged for mortality with affective symptom data available at a minimum of 3 time points (n = 3001). Data analysis was conducted from July 2016 to January 2019.Exposures: Affective symptoms were assessed at ages 13 to 15 years (teacher-rated questionnaire), 36 years (Present State Examination clinical semistructured interview), 43 years (Psychiatric Symptom Frequency questionnaire), and 53 years (General Health Questionnaire-28). Case-level affective symptoms were determined by those scoring in the top 16th percentile (ie, suggestive of a clinical diagnosis).Main Outcomes and Measures: Mortality data were obtained from the UK National Health Service Central Register from age 53 to 68 years.Results: Of 3001 study members (1509 [50.3%] female, 1492 [49.7%] male), 235 individuals (7.8%) died over a 15-year follow-up. After adjustment for sex, those who experienced case-level affective symptoms 1, 2, and 3 to 4 times had 76%, 87%, and 134% higher rates of premature mortality, respectively, compared with those who never experienced case-level symptoms. Case-level symptoms in adolescence only (ages 13-15 years) were associated with a 94% increased rate of mortality, which was unexplained after full adjustment for covariates (hazard ratio, 1.73; 95% CI, 1.10-2.72). Associations between participants with case-level symptoms multiple (2-4) times and mortality were predominately explained by adult health indicators and behaviors. For example, associations for those with case-level symptoms 3 to 4 times were most strongly attenuated by number of health conditions (32.1%), anxiolytic use (28.4%), lung function (24.6%), physical activity (23.9%), smoking (24.6%), antidepressant use (20.1%), diet (16.4%), pulse rate (12.7%), and adult social class (11.2%).Conclusions and Relevance: Lifetime accumulation of affective symptoms may be associated with an increased rate of mortality, with explanatory pathways dependent on the duration and timing of symptoms. Future research into causal pathways and potential points of intervention should consider affective symptom history. [ABSTRACT FROM AUTHOR]