Association between Longitudinal Cerebrospinal Fluid Alzheimer's Biomarkers and the Lifestyle for Brain Health (LIBRA) Index: Findings from the European Prevention of Alzheimer's Dementia Cohort Study (EPAD LCS).

BACKGROUND: In the absence of preventative pharmacological interventions for Alzheimer's Disease dementia, there is a growing interest in modifiable risk factors associated with AD. Such risk factors are thought to contribute up to 40% of the risk of dementia. The Lifestyle for Brain Health (LIBRA) index, a dementia risk score which focuses exclusively on modifiable factors, has been found to be associated with increased risk of dementia and cognitive decline. It is currently unclear how the LIBRA index relates to cerebrospinal fluid (CSF) biomarkers of Alzheimer's Disease. OBJECTIVES: To examine the association between LIBRA index scores and trajectories of phospho-tau 181 and total tau in the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study (EPAD LCS), and to examine whether these trajectories differ between participants with high and low CSF amyloid-beta 1-42 (Aß42). DESIGN: Analysis of CSF biomarker and LIBRA index scores from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study. SETTING: The European Prevention of Alzheimer's Dementia Longitudinal Cohort Study is a multi-centre, pan-European study. MEASUREMENTS: Cerebrospinal fluid samples were taken by lumbar puncture and analysed using electrochemiluminescence. LIBRA index scores were calculated from self-reported variables, questionnaires, and physiological measurements. RESULT: In the total sample (n = 1715; mean age = 66.0, 56.4% female), there were no significant associations between LIBRA scores (mean = 0.73 points) and rate of change in cerebrospinal fluid biomarkers. In participants with high Aß, reflecting less deposition in the brain, (n = 1134), LIBRA scores were significantly associated with the rate of change in total tau, where higher LIBRA scores (denoting higher dementia risk) were associated with increases in t-tau. There were no significant associations between LIBRA scores and change in cerebrospinal biomarkers in participants with low Aß. CONCLUSION: We found an association between modifiable risk factors and total tau accumulation in participants without dementia and without Aß accumulation. This suggests that increasing levels of total tau may be driven by factors other than Aß accumulation and highlights the need for developing and examining tau-targeting drugs in Alzheimer's Disease development.

The Scottish Brain Health Service Model: Rationale and Scientific Basis for a National Care Pathway of Brain Health Services in Scotland.

In order to address the oft-cited societal, economic, and health and social care impacts of neurodegenerative diseases, such as Alzheimer's disease, we must move decisively from reactive to proactive clinical practice and to embed evidence-based brain health education throughout society. Most disease processes can be at least partially prevented, slowed, or reversed. We have long neglected to intervene in neurodegenerative disease processes, largely due to a misconception that their predominant symptom - cognitive decline - is a normal, age-related process, but also due to a lack of multi-disciplinary collaboration. We now understand that there are modifiable risk factors for neurodegenerative diseases, that successful management of common comorbidities (such as diabetes and hypertension) can reduce the incidence of neurodegenerative disease, and that disease processes begin (and, crucially, can be detected, reduced, and delayed, prevented, or treated) decades earlier in life than had previously been appreciated. Brain Health Scotland, established by Scottish Government and working in partnership with Alzheimer Scotland, propose far-reaching public health and clinical practice approaches to reduce neurodegenerative disease incidence. Focusing here on Brain Health Scotland's clinical offerings, we present the Scottish Model for Brain Health Services. To our knowledge, the Scottish Model for Brain Health, built on foundations of personalised risk profiling, targeted risk reduction and prevention, early disease detection, equity of access, and harnessing comprehensive data to assist in clinical decision-making, marks the first example of a nationwide approach to overhauling clinical, societal, and political approaches to the prevention, assessment, and treatment of neurodegenerative disease.

Impact of clinical symptoms and diagnosis: the electronic Person-Specific Outcome Measure (ePSOM) development programme.

INTRODUCTION: Regulatory bodies recommend that outcome measures used in Alzheimer's disease (AD) clinical trials capture clinically meaningful changes for the trial participant. However, commonly used outcome measures do not reflect the individual's views on what matters to them individually. The aim of the electronic Person-Specific Outcome Measure (ePSOM) programme is to better understand what outcomes matter to patients in early Alzheimer's disease. METHODS: As part of the ePSOM programme, we designed and ran an online study to understand what matters to individuals when developing new treatments for AD. The ePSOM survey ran Aug 2019-Dec 2019 (UK) and collected primarily free text responses which were analysed using Natural Language Processing (NLP) techniques. In this paper, we focus our analyses on individuals who reported having a neurodegenerative disease diagnosis (primarily Mild Cognitive Impairment (MCI) or AD), reporting the most frequent and most important brain health priorities for this group. Due to a small sample size, the Diagnosis group was analysed as a whole. Finally, we compared the Diagnosis group to an age and gender matched control group using chi-squared tests to look for any differences between the Diagnosis and control groups' priorities. RESULTS: The survey was completed by 5808 respondents, of whom 167 (2.9%) (women n = 91, men n = 69, other n = 7) had received one of our pre-defined neurodegenerative disease diagnosis: most commonly MCI n = 52, 1.1% (mean age 69.42, SD = 10.8); or Alzheimer's disease n = 48, 1.0% (mean age 71.24, SD = 9.79). Several thematic clusters were significantly more important for the target diagnostic group, e.g.: Expressing opinions; and less important, e.g., Cognitive Games. CONCLUSION: We conclude there are a range of outcomes which individuals consider important and what potential new treatments should help maintain or improve, suggesting that outcomes that matter shift along the preclinical, prodromal and overt dementia continuum. This has important implications for the development of outcome measures in long term prevention studies that last several years where participants may pass through different stages of disease. In the final stage of our project, we will design an electronic outcomes app which will employ the methodology tested in the large-scale survey to capture what matters to individuals about their brain health at an individual level.

A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme.

BACKGROUND: It is important to use outcome measures for novel interventions in Alzheimer's disease (AD) that capture the research participants' views of effectiveness. The electronic Person-Specific Outcome Measure (ePSOM) development programme is underpinned by the need to identify and detect change in early disease manifestations and the possibilities of incorporating artificial intelligence in outcome measures. OBJECTIVES: The aim of the ePSOM programme is to better understand what outcomes matter to patients in the AD population with a focus on those at the pre-dementia stages of disease. Ultimately, we aim to develop an app with robust psychometric properties to be used as a patient reported outcome measure in AD clinical trials. DESIGN: We designed and ran a nationwide study (Aug 2019 - Nov 2019, UK), collecting primarily free text responses in five pre-defined domains. We collected self-reported clinical details and sociodemographic data to analyse responses by key variables whilst keeping the survey short (around 15 minutes). We used clustering and Natural Language Processing techniques to identify themes which matter most to individuals when developing new treatments for AD. RESULTS: The study was completed by 5,808 respondents, yielding over 80,000 free text answers. The analysis resulted in 184 themes of importance. An analysis focusing on key demographics to explore how priorities differed by age, gender and education revealed that there are significant differences in what groups consider important about their brain health. DISCUSSION: The ePSOM data has generated evidence on what matters to people when developing new treatments for AD that target secondary prevention and therein maintenance of brain health. These results will form the basis for an electronic outcome measure to be used in AD clinical research and clinical practice.

The European Prevention of Alzheimer's Dementia (EPAD) Longitudinal Cohort Study: Baseline Data Release V500.0.

BACKGROUND: The European Prevention of Alzheimer's Dementia (EPAD) Programme is a pan-European project whose objective is to deliver a platform, adaptive, Phase 2 proof of concept (PoC) trial for the secondary prevention of Alzheimer's dementia. A component of this platform is the Longitudinal Cohort Study (LCS) which acts as a readiness cohort for the PoC Trial as well as generating data for disease modelling work in the preclinical and prodromal phases of Alzheimer's dementia. OBJECTIVES: The first data wave has been collected, quality checked, released and now available for analysis to answer numerous research questions. Here we describe the results from key variables in the EPAD LCS with the objective of using these results to compliment analyses of these data in the future. DESIGN: EPAD LCS is a cohort study whose primary objective is as a readiness cohort for the EPAD PoC Trial. As such recruitment is not capped at any particular number but will continue to facilitate delivery of the EPAD PoC Trial. Research Participants are seen annually (with an additional 6 month visit in the first year). SETTING: The EPAD Trial Delivery Network comprises currently 21 centres across Europe. PARTICIPANTS: Research participants are included if they are over 50 years old and do not have a diagnosis of dementia. MEASUREMENTS: All research participants undergo multiple assessments to fully characterise the biology of Alzheimer's disease and relate this to risk factors (both fixed and modifiable) and biomarker expression of disease through brain imaging, fluid samples (CSF, blood, urine and saliva), cognitive performance, functional abilities and neuropsychiatric symptomatology. RESULTS: V500.0 represents the first 500 research participants baselined into EPAD LCS. The mean age was 66.4 (SD=6.7) and 47.8% were male. The data was split for presentation into 4 groups: [1] CDR=0 and Amyloid + (preclinical AD), [2] CDR=0 and Amyloid -, [3] CDR=0.5 and Amyloid + (prodromal AD) and [4] CDR=0.5 and Amyloid -. CONCLUSIONS: The EPAD LCS is achieving its primary objective of trial readiness and the structured approach to data release as manifest by this first data release of V500.0 will assist researchers to describe and compare their findings as well as in systematic reviews and meta-analyses. It is anticipated given current recruitment rates that V1500.0 data release will take place in Autumn 2019. V500.1 (when the 1 year follow up is completed on the V500.0 (sub)cohort will be in Autumn 2019 also.

Stability of clinically relevant depression symptoms in old-age across 11 cohorts: a multi-state study.

AIMS: To study the temporal dynamics of depression symptom episodes in old-age and the related influence of risk factors. METHODS: Data from 41 362 old adults (54.61% women; mean age = 75.30, SD = 6.20) from the Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project were used. Depressive symptoms were followed over an 18-year period. A multi-state model, comprising three statuses (no depression, new clinically relevant episode of symptoms and episode persistence), was fitted. Multinomial regression was used to study the role of risk factors in status transition. RESULTS: Almost 85% of participants showed no depression, but prevalence became lower over time (B = -0.25, P < 0.001). New episode point prevalence was over 5.30% with a significant probability of moving to persistence status (transition probability = 0.27). Episode persistence became evident in 9.86% of episode status transitions, with increasing rate over time (B = 0.54, P < 0.01). Loneliness was proven to be the strongest predictor of episode emergence (OR = 17.76) and persistence (OR = 5.93). CONCLUSIONS: The course of depression tends to become chronic and unremitting in old-age. This study may help to plan interventions to tackle symptom escalation and risk factor influence.

Five-decade trajectories in body mass index in relation to dementia death: follow-up of 33,083 male Harvard University alumni.

BACKGROUND: In prospective cohort studies, obesity has been linked with a lower risk of subsequent dementia. Reverse causality, whereby neurodegeneration preceding overt dementia symptoms may lower weight, is a possible explanation of these findings. To explore further the weight-dementia association we followed people from early adulthood, an age at which neurodegeneration has typically yet to begin. METHODS: In all, 33,083 male participants in the Harvard Alumni Health Study underwent a medical examination as undergraduates (typically aged 18 years) during which height, weight, resting pulse rate, blood pressure, physical activity, and smoking status were assessed. Subsamples provided height and weight in 1962/6 (mean age 50.7 years), 1977 (58.6), 1988 (67.5), and 1993 (71.1). Dementia deaths were extracted from death certificates (mean follow-up 53.1 years). We used latent class mixed models to create body mass index (BMI) trajectories; for comparison, we also constructed models with cardiovascular disease (CVD) death. RESULTS: We found no association between early life BMI and subsequent dementia (age-adjusted HR 0.94, 95% CI 0.85, 1.04). We identified two latent class groups based on different BMI trajectories-"early decliners" whose BMI began to decline around age 50 years and "late decliners" whose BMI declined about two decades later. The former experienced a raised risk of dementia-related death compared to the latter (multivariable-adjusted HR 1.57, 95% CI 1.14, 2.17). Expected associations were identified between CVD risk factors and CVD death. CONCLUSIONS: In a population likely to be free of dementia neuropathology at BMI measurement, we found no association between BMI at baseline and subsequent dementia-related death. Earlier decline in BMI was, however, associated with dementia, which suggests that findings associating BMI with dementia risk may be influenced by reverse causality.

Clinic variation in glycaemic control for children with Type 1 diabetes in England and Wales: a population-based, multilevel analysis.

AIM: To understand the scope for improving children's glycaemic outcomes by reducing variation between clinics and examine the role of insulin regimen and clinic characteristics. METHODS: Cross-sectional analysis of 2012-2013 National Paediatric Diabetes Audit data from 21 773 children aged < 19 years with Type 1 diabetes cared for at 176 clinics organized into 11 regional diabetes networks in England and Wales. Variation in HbA1c was explored by multilevel models with a random effect for clinic. The impact of clinic context was quantified by computing the per cent of total variation in HbA1c which occurs between clinics (intraclass correlation coefficient; ICC). RESULTS: Overall, 69 of the 176 diabetes clinics (39%) had a glycaemic performance that differed significantly from the national average after adjusting for patient case-mix with respect to age, gender, diabetes duration, deprivation and ethnicity. However, differences between clinics accounted for 4.7% of the total variation in HbA1c . Inclusion of within-clinic HbA1c standard deviation led to a substantial reduction in ICC to 2.4%. Insulin regimen, clinic volume and diabetes networks had a small or moderate impact on ICC. CONCLUSIONS: Differences between diabetes clinics accounted for only a small portion of the total variation in glycaemic control because most of the variation was within clinics. This implies that national glycaemic improvements might best be achieved not only by targeting poor centres but also by shifting the whole distribution of clinics to higher levels of quality.

Decline in Memory, Visuospatial Ability, and Crystalized Cognitive Abilities in Older Adults: Normative Aging or Terminal Decline?

The aim of this study is to explore the pattern of change in multiple measures of cognitive abilities in a sample of oldest-old adults, comparing two different time metrics (chronological age and time to death) and therefore examining both underlying conceptual assumptions (age-related change and terminal decline). Moreover, the association with individual characteristics as sex, education, and dementia diagnosis was also examined. Measures of cognitive status (Mini-Mental State Examination and the Swedish Clock Test) and tests of crystallized (knowledge and synonyms), memory (verbal memory, nonverbal long-term memory, recognition and correspondence, and short-term memory), and visuospatial ability were included. The sample consisted of 671 older Swedish adult participants of the OCTO Twin Study. Linear mixed models with random coefficients were used to analyse change patterns and BIC indexes were used to compare models. Results showed that the time to death model was the best option in analyses of change in all the cognitive measures considered (except for the Information Test). A significant cognitive decline over time was found for all variables. Individuals diagnosed with dementia had lower scores at the study entrance and a faster decline. More educated individuals performed better in all the measures of cognition at study entry than those with poorer education, but no differences were found in the rate of change. Differences were found in age, sex, or time to death at baseline across the different measures. These results support the terminal decline hypothesis when compared to models assuming that cognitive changes are driven by normative aging processes.

Longitudinal associations between late-life depression dimensions and cognitive functioning: a cross-domain latent growth curve analysis.

BACKGROUND: Cognitive impairment and depression often co-occur in older adults, but it is not clear whether depression is a risk factor for cognitive decline, a psychological reaction to cognitive decline, or whether changes in depressive symptoms correlate with changes in cognitive performance over time. The co-morbid manifestation of depression and cognitive impairment may reflect either a causal effect or a common cause, depending on the specific symptoms experienced and the cognitive functions affected. METHOD: The study sample comprised 1506 community-dwelling older adults aged ⩾65 years from the Longitudinal Aging Study Amsterdam (LASA). We conducted cross-domain latent growth curve analyses to examine longitudinal associations between late-life depression dimensions (i.e. depressed affect, positive affect, and somatic symptoms) and specific domains of cognitive functioning (i.e. processing speed, inductive reasoning, immediate recall, and delayed recall). RESULTS: Poorer delayed recall performance at baseline predicted a steeper increase in depressed affect over time. Steeper decline in processing speed correlated with a steeper increase in somatic symptoms of depression over time. CONCLUSIONS: Our findings suggest a prospective association between memory function and depressed affect, whereby older adults may experience an increase in depressed affect in reaction to poor memory function. Somatic symptoms of depression increased concurrently with declining processing speed, which may reflect common neurodegenerative processes. Our findings do not support the hypothesis that depression symptoms may be a risk factor for cognitive decline in the general population. These findings have potential implications for the treatment of late-life depression and for the prognosis of cognitive outcomes.

Modification of genetic influences on adiposity between 36 and 63 years of age by physical activity and smoking in the 1946 British Birth Cohort Study.

BACKGROUND: Previous studies reporting on the interaction between physical activity and genetic susceptibility on obesity have been cross-sectional and have not considered the potential influences of other lifestyle behaviours. The aim of this study was to examine modification of genetic influences on changes across age in adiposity during mid-adulthood by physical activity and smoking. METHODS: The sample comprised 2444 participants who were genotyped for 11 obesity variants and had body mass index (BMI), waist circumference-to-height ratio (WHtR), physical activity and smoking measures at 36, 43, 53 and 60-64 years of age. A genetic risk score (GRS) comprising the sum of risk alleles was computed. Structural equation models investigated modification of the longitudinal GRS associations by physical activity (active versus inactive) and smoking (non-smoker versus smoker), using a latent linear spline to summarise BMI or WHtR (multiplied by 100) at the age of 36 years and their subsequent rates of change over age. RESULTS: Physical activity at the age of 36 years attenuated the GRS associations with BMI and WHtR at the same age (P-interaction 0.009 and 0.004, respectively). Further, physical activity at the age of 53 years attenuated the GRS association with rate of change in BMI between 53 and 63 years of age (by 0.012 kg m(-2) per year (95% confidence interval (CI): 0.001, 0.024), P-interaction 0.004). Conversely, smoking at the age of 43 years showed a trend towards augmenting the GRS association with rate of change in WHtR between 43 and 63 years of age (by 0.012 (95% CI: 0.001, 0.026), P-interaction 0.07). Estimated GRS effect sizes were lowest at all ages in the healthiest group (e.g., active non-smokers). CONCLUSIONS: Healthy lifestyle behaviours appeared to attenuate the genetic influence on changes across age in BMI and central adiposity during mid-adulthood. An active lifestyle and not smoking may have additive effects on reducing the genetic susceptibility to obesity in adults.