The usability and reliability of a smartphone application for monitoring future dementia risk in ageing UK adults.

BACKGROUND: The rising number of dementia diagnoses and imminent adoption of disease-modifying treatments necessitate innovative approaches to identify individuals at risk, monitor disease course and intervene non-pharmacologically earlier in the disease course. Digital assessments of dementia risk and cognitive function have the potential to outperform traditional in-person assessments in terms of their affordability, accuracy and longitudinal tracking abilities. However, their accessibility and reliability in older adults is unclear. AIMS: To evaluate the usability and reliability of a smartphone assessment of lifestyle and cognitive factors relevant to dementia risk in a group of UK-based older adults. METHOD: Cognitively healthy adults (n = 756) recruited through the Dementias Platform UK Great Minds volunteer register completed three assessments of cognitive function and dementia risk over a 3-month period and provided usability feedback on the Five Lives smartphone application (app). We evaluated cognitive test scores for age, gender and higher education effects, normality distributions, test-retest reliability and their relationship with participants' lifestyle dementia risk factors. RESULTS: Participants found the app 'easy to use', 'quick to complete' and 'enjoyable'. The cognitive tests showed normal or near-to-normal distributions, variable test-retest reliabilities and age-related effects. Only tests of verbal ability showed gender and education effects. The cognitive tests did not correlate with lifestyle dementia risk scores. CONCLUSIONS: The Five Lives assessment demonstrates high usability and reliability among older adults. These findings highlight the potential of digital assessments in dementia research and clinical practice, enabling improved accessibility and better monitoring of cognitive health on a larger scale than traditional in-person assessments.

LGI1-antibody encephalitis: how to approach this highly treatable dementia mimic in memory and mental health services.

Leucine-rich glioma-inactivated 1-antibody-encephalitis is a treatable and potentially reversible cause of cognitive and psychiatric presentations, and may mimic cognitive decline, rapidly progressive dementia and complex psychosis in older patients. This aetiology is of immediate relevance given the alternative treatment pathway required, compared with other conditions presenting with cognitive deficits.

Entorhinal-based path integration selectively predicts midlife risk of Alzheimer's disease.

INTRODUCTION: Entorhinal cortex (EC) is the first cortical region to exhibit neurodegeneration in Alzheimer's disease (AD), associated with EC grid cell dysfunction. Given the role of grid cells in path integration (PI)-based spatial behaviors, we predicted that PI impairment would represent the first behavioral change in adults at risk of AD. METHODS: We compared immersive virtual reality (VR) PI ability to other cognitive domains in 100 asymptomatic midlife adults stratified by hereditary and physiological AD risk factors. In some participants, behavioral data were compared to 7T magnetic resonance imaging (MRI) measures of brain structure and function. RESULTS: Midlife PI impairments predicted both hereditary and physiological AD risk, with no corresponding multi-risk impairment in episodic memory or other spatial behaviors. Impairments associated with altered functional MRI signal in the posterior-medial EC. DISCUSSION: Altered PI may represent the transition point from at-risk state to disease manifestation in AD, prior to impairment in other cognitive domains.

Artificial intelligence for dementia prevention.

INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possible interactions between them or with genetic risk, and causality, and how they can help in clinical trial recruitment and drug development. Artificial intelligence (AI) and machine learning (ML) may refine understanding. METHODS: ML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field. RESULTS: Risk-profiling tools may help identify high-risk populations for clinical trials; however, their performance needs improvement. New risk-profiling and trial-recruitment tools underpinned by ML models may be effective in reducing costs and improving future trials. ML can inform drug-repurposing efforts and prioritization of disease-modifying therapeutics. DISCUSSION: ML is not yet widely used but has considerable potential to enhance precision in dementia prevention. HIGHLIGHTS: Artificial intelligence (AI) is not widely used in the dementia prevention field. Risk-profiling tools are not used in clinical practice. Causal insights are needed to understand risk factors over the lifespan. AI will help personalize risk-management tools for dementia prevention. AI could target specific patient groups that will benefit most for clinical trials.

Personalised treatment for cognitive impairment in dementia: development and validation of an artificial intelligence model.

BACKGROUND: Donepezil, galantamine, rivastigmine and memantine are potentially effective interventions for cognitive impairment in dementia, but the use of these drugs has not been personalised to individual patients yet. We examined whether artificial intelligence-based recommendations can identify the best treatment using routinely collected patient-level information. METHODS: Six thousand eight hundred four patients aged 59-102 years with a diagnosis of dementia from two National Health Service (NHS) Foundation Trusts in the UK were used for model training/internal validation and external validation, respectively. A personalised prescription model based on the Recurrent Neural Network machine learning architecture was developed to predict the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores post-drug initiation. The drug that resulted in the smallest decline in cognitive scores between prescription and the next visit was selected as the treatment of choice. Change of cognitive scores up to 2 years after treatment initiation was compared for model evaluation. RESULTS: Overall, 1343 patients with MMSE scores were identified for internal validation and 285 [21.22%] took the drug recommended. After 2 years, the reduction of mean [standard deviation] MMSE score in this group was significantly smaller than the remaining 1058 [78.78%] patients (0.60 [0.26] vs 2.80 [0.28]; P = 0.02). In the external validation cohort (N = 1772), 222 [12.53%] patients took the drug recommended and reported a smaller MMSE reduction compared to the 1550 [87.47%] patients who did not (1.01 [0.49] vs 4.23 [0.60]; P = 0.01). A similar performance gap was seen when testing the model on patients prescribed with AChEIs only. CONCLUSIONS: It was possible to identify the most effective drug for the real-world treatment of cognitive impairment in dementia at an individual patient level. Routine care patients whose prescribed medications were the best fit according to the model had better cognitive performance after 2 years.

Neurology and neuropsychiatry of COVID-19: a systematic review and meta-analysis of the early literature reveals frequent CNS manifestations and key emerging narratives.

There is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations.We searched MEDLINE, Embase, PsycINFO and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series. Studies reporting prevalences of neurological or neuropsychiatric symptoms were synthesised into meta-analyses to estimate pooled prevalence.13 292 records were screened by at least two authors to identify 215 included studies, of which there were 37 cohort studies, 15 case-control studies, 80 cross-sectional studies and 83 case series from 30 countries. 147 studies were included in the meta-analysis. The symptoms with the highest prevalence were anosmia (43.1% (95% CI 35.2% to 51.3%), n=15 975, 63 studies), weakness (40.0% (95% CI 27.9% to 53.5%), n=221, 3 studies), fatigue (37.8% (95% CI 31.6% to 44.4%), n=21 101, 67 studies), dysgeusia (37.2% (95% CI 29.8% to 45.3%), n=13 686, 52 studies), myalgia (25.1% (95% CI 19.8% to 31.3%), n=66 268, 76 studies), depression (23.0% (95% CI 11.8% to 40.2%), n=43 128, 10 studies), headache (20.7% (95% CI 16.1% to 26.1%), n=64 613, 84 studies), anxiety (15.9% (5.6% to 37.7%), n=42 566, 9 studies) and altered mental status (8.2% (95% CI 4.4% to 14.8%), n=49 326, 19 studies). Heterogeneity for most clinical manifestations was high.Neurological and neuropsychiatric symptoms of COVID-19 in the pandemic's early phase are varied and common. The neurological and psychiatric academic communities should develop systems to facilitate high-quality methodologies, including more rapid examination of the longitudinal course of neuropsychiatric complications of newly emerging diseases and their relationship to neuroimaging and inflammatory biomarkers.

Real-world effectiveness, its predictors and onset of action of cholinesterase inhibitors and memantine in dementia: retrospective health record study.

BACKGROUND: The efficacy of acetylcholinesterase inhibitors and memantine in the symptomatic treatment of Alzheimer's disease is well-established. Randomised trials have shown them to be associated with a reduction in the rate of cognitive decline. AIMS: To investigate the real-world effectiveness of acetylcholinesterase inhibitors and memantine for dementia-causing diseases in the largest UK observational secondary care service data-set to date. METHOD: We extracted mentions of relevant medications and cognitive testing (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores) from de-identified patient records from two National Health Service (NHS) trusts. The 10-year changes in cognitive performance were modelled using a combination of generalised additive and linear mixed-effects modelling. RESULTS: The initial decline in MMSE and MoCA scores occurs approximately 2 years before medication is initiated. Medication prescription stabilises cognitive performance for the ensuing 2-5 months. The effect is boosted in more cognitively impaired cases at the point of medication prescription and attenuated in those taking antipsychotics. Importantly, patients who are switched between agents at least once do not experience any beneficial cognitive effect from pharmacological treatment. CONCLUSIONS: This study presents one of the largest real-world examination of the efficacy of acetylcholinesterase inhibitors and memantine for symptomatic treatment of dementia. We found evidence that 68% of individuals respond to treatment with a period of cognitive stabilisation before continuing their decline at the pre-treatment rate.

The Dementias Platform UK (DPUK) Data Portal.

The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

Anxiety in older adults often goes undiagnosed.

Anxiety disorder in the elderly is twice as common as dementia and four to six times more common than major depression. Anxiety is associated with poorer quality of life, significant distress and contributes to the onset of disability. Mortality risks are also increased, through physical causes, especially cardiovascular disease, and suicide. Diagnosing anxiety disorders in older adults remains a challenge because of the significant overlap in symptoms between physical disorders (shortness of breath; abdominal and chest pain; palpitations) and depression (disturbed sleep; poor attention, concentration and memory; restlessness). Good history taking is crucial in elucidating whether the complaint is of new onset or a recurrence of a previous disorder. The presence of comorbid depression should be clarified. If present, its temporal relationship with the anxiety symptoms will indicate whether there is an independent anxiety disorder. A medication review is warranted, as a number of drugs may be causative (calcium channel blockers, alpha- and beta-blockers, digoxin, L-thyroxine, bronchodilators, steroids, theophylline, antihistamines) or may cause anxiety in withdrawal (e.g. benzodiazepines). Substance and alcohol abuse should be excluded, as withdrawal from either may cause anxiety. A new or exacerbated physical illness may be related to anxiety. Medical investigations will help clarify the extent to which a particular somatic symptom is the result of anxiety.

Nightmares and suicide: predicting risk in depression.

BACKGROUND: There is growing evidence of an association of a number of subjective and objective sleep parameters (especially nightmares) and elevated suicidal risk in different clinical populations as well as in the general populations. SUBJECTS AND METHODS: This is a cross-sectional naturalistic study of 52 inpatients (28 females and 24 males, aged from 24 to 75 years) meeting criteria for a current depressive episode within Recurrent Depressive Disorder (RDD) or Bipolar Disorder (BD) according to ICD-10. All patients were evaluated with the Hamilton Depression Rating Scale (HDRS), followed by a direct interview about their dreams' content and emotional charge, as well as about suicidal thoughts and plans or previous attempts. RESULTS: Patients with RDD suffered significantly more frequently from nightmares than those with BD, p<0.05. Within the RDD group, experiencing nightmares was associated with significantly higher scores on the HDRS suicide risk item (2.36 vs 1.00), higher frequency of suicide attempts (35% vs 6%), and lower likelihood for lack of detectable suicide risk (21% vs 81%), p<0.05. These differences were not explained by significant difference in the severity of depressive symptoms (28.00 vs 24.75, p=0.16). We were unable to detect such differences in the bipolar subgroup. No gender influences on the association of nightmares and suicidal risk were observed. CONCLUSIONS: Depressed patients suffering from nightmares showed significantly higher suicide risk. Depression appeared to be a stronger risk factor for suicidal behavior when accompanied with nightmares. This was only valid for unipolar depression, while the results concerning bipolar depression were inconclusive.

Dementia risk and thalamic nuclei volumetry in healthy midlife adults: the PREVENT Dementia study.

A reduction in the volume of the thalamus and its nuclei has been reported in Alzheimer's disease, mild cognitive impairment and asymptomatic individuals with risk factors for early-onset Alzheimer's disease. Some studies have reported thalamic atrophy to occur prior to hippocampal atrophy, suggesting thalamic pathology may be an early sign of cognitive decline. We aimed to investigate volumetric differences in thalamic nuclei in middle-aged, cognitively unimpaired people with respect to dementia family history and apolipoprotein ε4 allele carriership and the relationship with cognition. Seven hundred participants aged 40-59 years were recruited into the PREVENT Dementia study. Individuals were stratified according to dementia risk (approximately half with and without parental dementia history). The subnuclei of the thalamus of 645 participants were segmented on T1-weighted 3 T MRI scans using FreeSurfer 7.1.0. Thalamic nuclei were grouped into six regions: (i) anterior, (ii) lateral, (iii) ventral, (iv) intralaminar, (v) medial and (vi) posterior. Cognitive performance was evaluated using the computerized assessment of the information-processing battery. Robust linear regression was used to analyse differences in thalamic nuclei volumes and their association with cognitive performance, with age, sex, total intracranial volume and years of education as covariates and false discovery rate correction for multiple comparisons. We did not find significant volumetric differences in the thalamus or its subregions, which survived false discovery rate correction, with respect to first-degree family history of dementia or apolipoprotein ε4 allele status. Greater age was associated with smaller volumes of thalamic subregions, except for the medial thalamus, but only in those without a dementia family history. A larger volume of the mediodorsal medial nucleus (Pfalse discovery rate = 0.019) was associated with a faster processing speed in those without a dementia family history. Larger volumes of the thalamus (P = 0.016) and posterior thalamus (Pfalse discovery rate = 0.022) were associated with significantly worse performance in the immediate recall test in apolipoprotein ε4 allele carriers. We did not find significant volumetric differences in thalamic subregions in relation to dementia risk but did identify an interaction between dementia family history and age. Larger medial thalamic nuclei may exert a protective effect on cognitive performance in individuals without a dementia family history but have little effect on those with a dementia family history. Larger volumes of posterior thalamic nuclei were associated with worse recall in apolipoprotein ε4 carriers. Our results could represent initial dysregulation in the disease process; further study is needed with functional imaging and longitudinal analysis.

Protocol for a double-blind placebo-controlled randomised controlled trial assessing the impact of oral semaglutide in amyloid positivity (ISAP) in community dwelling UK adults.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), currently marketed for type 2 diabetes and obesity, may offer novel mechanisms to delay or prevent neurotoxicity associated with Alzheimer's disease (AD). The impact of semaglutide in amyloid positivity (ISAP) trial is investigating whether the GLP-1 RA semaglutide reduces accumulation in the brain of cortical tau protein and neuroinflammation in individuals with preclinical/prodromal AD. METHODS AND ANALYSIS: ISAP is an investigator-led, randomised, double-blind, superiority trial of oral semaglutide compared with placebo. Up to 88 individuals aged ≥55 years with brain amyloid positivity as assessed by positron emission tomography (PET) or cerebrospinal fluid, and no or mild cognitive impairment, will be randomised. People with the low-affinity binding variant of the rs6971 allele of the Translocator Protein 18 kDa (TSPO) gene, which can interfere with interpreting TSPO PET scans (a measure of neuroinflammation), will be excluded.At baseline, participants undergo tau, TSPO PET and MRI scanning, and provide data on physical activity and cognition. Eligible individuals are randomised in a 1:1 ratio to once-daily oral semaglutide or placebo, starting at 3 mg and up-titrating to 14 mg over 8 weeks. They will attend safety visits and provide blood samples to measure AD biomarkers at weeks 4, 8, 26 and 39. All cognitive assessments are repeated at week 26. The last study visit will be at week 52, when all baseline measurements will be repeated. The primary end point is the 1-year change in tau PET signal. ETHICS AND DISSEMINATION: The study was approved by the West Midlands-Edgbaston Research Ethics Committee (22/WM/0013). The results of the study will be disseminated through scientific presentations and peer-reviewed publications. TRIAL REGISTRATION NUMBER: ISRCTN71283871.

Comprehensive allostatic load risk index is associated with increased frontal and left parietal white matter hyperintensities in mid-life cognitively healthy adults.

To date, there is a considerable heterogeneity of methods to score Allostatic Load (AL). Here we propose a comprehensive algorithm (ALCS) that integrates commonly used approaches to generate AL risk categories and assess associations to brain structure deterioration. In a cohort of cognitively normal mid-life adults (n = 620, age 51.3 ± 5.48 years), we developed a comprehensive composite for AL scoring incorporating gender and age differences, high quartile approach, clinical reference values, and current medications, to then generate AL risk categories. Compared to the empirical approach (ALES), ALCS showed better model fit criteria and a strong association with age and sex. ALSC categories were regressed against brain and white matter hyperintensity (WMH) volumes. Higher AL risk categories were associated with increased total, periventricular, frontal, and left parietal WMH volumes, also showing better fit compared to ALES. When cardiovascular biomarkers were removed from the ALSC algorithm, only left-frontal WMHV remained associated with AL, revealing a strong vascular burden influencing the index. Our results agree with previous evidence and suggest that sustained stress exposure enhances brain deterioration in mid-life adults. Showing better fit than ALES, our comprehensive algorithm can provide a more accurate AL estimation to explore how stress exposure enhances age-related health decline.

Investigating the brain's neurochemical profile at midlife in relation to dementia risk factors.

Changes in the brain's physiology in Alzheimer's disease are thought to occur early in the disease's trajectory. In this study our aim was to investigate the brain's neurochemical profile in a midlife cohort in relation to risk factors for future dementia using single voxel proton magnetic resonance spectroscopy. Participants in the multi-site PREVENT-Dementia study (age range 40-59 year old) underwent 3T magnetic resonance spectroscopy with the spectroscopy voxel placed in the posterior cingulate/precuneus region. Using LCModel, we quantified the absolute concentrations of myo-inositol, total N-acetylaspartate, total creatine, choline, glutathione and glutamate-glutamine for 406 participants (mean age 51.1; 65.3% female). Underlying partial volume effects were accounted for by applying a correction for the presence of cerebrospinal fluid in the magnetic resonance spectroscopy voxel. We investigated how metabolite concentrations related to apolipoprotein ɛ4 genotype, dementia family history, a risk score (Cardiovascular Risk Factors, Aging and Incidence of Dementia -CAIDE) for future dementia including non-modifiable and potentially-modifiable factors and dietary patterns (adherence to Mediterranean diet). Dementia family history was associated with decreased total N-acetylaspartate and no differences were found between apolipoprotein ɛ4 carriers and non-carriers. A higher Cardiovascular Risk Factors, Aging, and Incidence of Dementia score related to higher myo-inositol, choline, total creatine and glutamate-glutamine, an effect which was mainly driven by older age and a higher body mass index. Greater adherence to the Mediterranean diet was associated with lower choline, myo-inositol and total creatine; these effects did not survive correction for multiple comparisons. The observed associations suggest that at midlife the brain demonstrates subtle neurochemical changes in relation to both inherited and potentially modifiable risk factors for future dementia.

APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure.

The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.

Feasibility and usability of remote monitoring in Alzheimer's disease.

Introduction: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants. Methods: For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews. Results: Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible. Conclusions: This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

The PREVENT dementia programme: baseline demographic, lifestyle, imaging and cognitive data from a midlife cohort study investigating risk factors for dementia.

PREVENT is a multi-centre prospective cohort study in the UK and Ireland that aims to examine midlife risk factors for dementia and identify and describe the earliest indices of disease development. The PREVENT dementia programme is one of the original epidemiological initiatives targeting midlife as a critical window for intervention in neurodegenerative conditions. This paper provides an overview of the study protocol and presents the first summary results from the initial baseline data to describe the cohort. Participants in the PREVENT cohort provide demographic data, biological samples (blood, saliva, urine and optional cerebrospinal fluid), lifestyle and psychological questionnaires, undergo a comprehensive cognitive test battery and are imaged using multi-modal 3-T MRI scanning, with both structural and functional sequences. The PREVENT cohort governance structure is described, which includes a steering committee, a scientific advisory board and core patient and public involvement groups. A number of sub-studies that supplement the main PREVENT cohort are also described. The PREVENT cohort baseline data include 700 participants recruited between 2014 and 2020 across five sites in the UK and Ireland (Cambridge, Dublin, Edinburgh, London and Oxford). At baseline, participants had a mean age of 51.2 years (range 40-59, SD ± 5.47), with the majority female (n = 433, 61.9%). There was a near equal distribution of participants with and without a parental history of dementia (51.4% versus 48.6%) and a relatively high prevalence of APOEɛ4 carriers (n = 264, 38.0%). Participants were highly educated (16.7 ± 3.44 years of education), were mainly of European Ancestry (n = 672, 95.9%) and were cognitively healthy as measured by the Addenbrookes Cognitive Examination-III (total score 95.6 ± 4.06). Mean white matter hyperintensity volume at recruitment was 2.26 ± 2.77 ml (median = 1.39 ml), with hippocampal volume being 8.15 ± 0.79 ml. There was good representation of known dementia risk factors in the cohort. The PREVENT cohort offers a novel data set to explore midlife risk factors and early signs of neurodegenerative disease. Data are available open access at no cost via the Alzheimer's Disease Data Initiative platform and Dementia Platforms UK platform pending approval of the data access request from the PREVENT steering group committee.

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury.

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.

Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach.

INTRODUCTION: The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data. METHODS: 927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database. RESULTS: Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal. DISCUSSION: Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.