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Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

BACKGROUND: We aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65 years using shared risk factors. METHODS: Data were obtained from 10 population-based cohorts (N = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrels C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer-Lemeshow goodness of fit test along calibration plots. RESULTS: Both the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65). CONCLUSIONS: The DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

INTRODUCTION: The LIfestyle for BRAin Health (LIBRA) index yields a dementia risk score based on modifiable lifestyle factors and is validated in Western samples. We investigated whether the association between LIBRA scores and incident dementia is moderated by geographical location or sociodemographic characteristics. METHODS: We combined data from 21 prospective cohorts across six continents (N = 31,680) and conducted cohort-specific Cox proportional hazard regression analyses in a two-step individual participant data meta-analysis. RESULTS: A one-standard-deviation increase in LIBRA score was associated with a 21% higher risk for dementia. The association was stronger for Asian cohorts compared to European cohorts, and for individuals aged ≤75 years (vs older), though only within the first 5 years of follow-up. No interactions with sex, education, or socioeconomic position were observed. DISCUSSION: Modifiable risk and protective factors appear relevant for dementia risk reduction across diverse geographical and sociodemographic groups. HIGHLIGHTS: A two-step individual participant data meta-analysis was conducted. This was done at a global scale using data from 21 ethno-regionally diverse cohorts. The association between a modifiable dementia risk score and dementia was examined. The association was modified by geographical region and age at baseline. Yet, modifiable dementia risk and protective factors appear relevant in all investigated groups and regions.

Abstract Background Patient data contain a wealth of information that could aid in understanding the onset and progression of disease. However, the task of modelling clinical data, which consist of multiple heterogeneous time series of different lengths, measured at different time intervals, is a complex one. A growing body of research has applied temporal pattern mining to this problem to identify common patterns in clinical attributes over time. However, the vast majority of these algorithms use techniques that are not ideally suited to clinical data. We present an efficient and scalable framework designed specifically for temporal pattern mining of real-world clinical data. Our framework combines temporal abstraction, an extended version of the efficient pattern-growth algorithm, TPMiner, the concepts of relative risk and the odds ratio to identify interesting and high-risk patterns and multiprocessing to improve computational efficiency. A complete set of cut-off values for discretisation and interpretation of the data is provided and is applicable to studies on ageing populations in general. We name this framework Clinical Temporal Pattern Mining or C-TPM. Results The framework is applied to data from two real-world studies of Alzheimer’s disease (AD). The patterns discovered were predictive of AD in survival analysis models with a Concordance index of up to 0.87 and contain clinically relevant variables. A visualisation module provides a clear picture of the discovered patterns for ease of interpretability. Conclusions The framework provides an effective and scalable method of modelling multivariate, longitudinal clinical data and can identify patterns in uncommon diseases and those that progress slowly over time. It is generalisable to clinical data from other medical domains as well as non-clinical data.

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

BACKGROUND: Dementia is a global public health priority. The World Health Organization adopted a Global Action Plan on Dementia, with dementia awareness a priority. This study examined the knowledge, attitudes, and self-confidence with skills required for providing dementia care among primary health care providers in Vietnam. METHODS: A cross-sectional study was conducted with 405 primary health care providers who worked at commune health stations and district health centers in eight provinces across Vietnam. RESULTS: The results showed that primary health care providers had poor knowledge and little confidence but more positive attitudes toward dementia care and management. CONCLUSIONS: The results suggest the training needs for building capacity amongst primary health care providers, which will be critical as Vietnams population ages.

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individuals regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Abstract Background Hospitalized older patients with cognitive impairment (CI) experience poor outcomes and high rates of hospital acquired complications (HACs). This study investigated the effectiveness of a multimodal hospital CI identification and education program. Method A prospective stepped-wedge, cross-sectional, continuous-recruitment, hybrid effectiveness-Implementation study was conducted in acute hospitals in four Australian states/territories. The intervention, the Dementia Care in Hospitals Program (DHCP) provided: clinical/ non-clinical hospital staff CI awareness support and education; CI screening for older patients and a bedside alert—the Cognitive Impairment Identifier (CII). The primary outcome was change in the rate of the combined risk of four HACs (urinary tract infection, pneumonia, new onset delirium, pressure injury). Results Participants were patients aged 65 years and over admitted for 24 h or more over a 12-month period between 2015–2017 (n = 16,789). Of the 11,309 (67.4%) screened, 4,277 (37.8%) had CI. HACs occurred in 27.4% of all screened patients and were three times more likely in patients with CI after controlling for age and sex (RR = 3.03; 95%CI:2.74–3.27). There was no significant change in HAC rate for patients with CI (RR = 1.084; 95%CI: 0.93; 1.26). In the intervention period the raw HAC rate for all screened patients was 27.0%, which when adjusted for age and sex suggested a small reduction overall. However, when adjusted for hospital site, this reduction in HAC risk not statistically significant (RR = 0.968; 95%CI:0.865–1.083). There was considerable interhospital variation in intervention implementation and outcomes which explains the final non-significant effect. Conclusion For patient with CI the implementation of the DCHP did not result in a reduction in HAC rates. Education for hospital staff regarding cognitive impairment screening, care support, carer engagement and bedside alerts, using the DCHP, can be feasibly implemented in acute hospitals. Reducing high frequency HACs in older hospital patients with CI, warrants further research. Trial Registration. The trial was registered retrospectively with the Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12615000905561 on 01/09/2015 with 92 patients (0.8% of total sample) recruited in the baseline and none in the intervention before registration submission.

Abstract Background We aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65 years using shared risk factors. Methods Data were obtained from 10 population-based cohorts (N = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrel’s C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer–Lemeshow goodness of fit test along calibration plots. Results Both the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65). Conclusions The DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures.

Compensation has been proposed as a mechanism to explain how individuals in very old age remain able to maintain normal cognitive functioning. Previous studies have provided evidence on the role of increasing functional connectivity as a compensatory mechanism for age-related white matter damage. However, we lack direct investigation into how these mechanisms contribute to the preservation of cognition in the very old population. We examined a cohort of near-centenarians and centenarians without dementia (aged 95-103 years, n=44). We constructed a structural disconnection matrix based on the disruption of white matter pathways caused by white matter hyperintensities (WMHs), aiming to explore the relationship between functional connections, cognitive preservation and white matter damage. Our results revealed that structural damage can reliably explain the variations of functional connections or cognitive maintenance. Notably, we found significant correlations between the weights in the functional connectivity model and the weights in the cognition model. We observed positive correlations between models for brain disconnections and cognitive function in near-centenarians and centenarians. The strongest effects were found between attention and somatomotor network (SMN) (r=0.397, p

INTRODUCTION: Sex differences in dementia risk, and risk factor (RF) associations with dementia, remain uncertain across diverse ethno-regional groups. METHODS: A total of 29,850 participants (58% women) from 21 cohorts across six continents were included in an individual participant data meta-analysis. Sex-specific hazard ratios (HRs), and women-to-men ratio of hazard ratios (RHRs) for associations between RFs and all-cause dementia were derived from mixed-effect Cox models. RESULTS: Incident dementia occurred in 2089 (66% women) participants over 4.6 years (median). Women had higher dementia risk (HR, 1.12 [1.02, 1.23]) than men, particularly in low- and lower-middle-income economies. Associations between longer education and former alcohol use with dementia risk (RHR, 1.01 [1.00, 1.03] per year, and 0.55 [0.38, 0.79], respectively) were stronger for men than women; otherwise, there were no discernible sex differences in other RFs. DISCUSSION: Dementia risk was higher in women than men, with possible variations by country-level income settings, but most RFs appear to work similarly in women and men.

IntroductionThere are limited data on prevalence of dementia in centenarians and near-centenarians (C/NC), its determinants, and whether the risk of dementia continues to rise beyond 100.MethodsParticipant-level data were obtained from 18 community-based studies (N = 4427) in 11 countries that included individuals ≥95 years. A harmonization protocol was applied to cognitive and functional impairments, and a meta-analysis was performed.ResultsThe mean age was 98.3 years (SD = 2.67); 79% were women. After adjusting for age, sex, and education, dementia prevalence was 53.2% in women and 45.5% in men, with risk continuing to increase with age. Education (OR 0.95;0.92-0.98) was protective, as was hypertension (odds ratio [OR] 0.51;0.35-0.74) in five studies. Dementia was not associated with diabetes, vision and hearing impairments, smoking, and body mass index (BMI).DiscussionAmong the exceptional old, dementia prevalence remains higher in the older participants. Education was protective against dementia, but other factors for dementia-free survival in C/NC remain to be understood.

Increased efforts in neuroscience seek to understand how macro-anatomical and physiological connectomes cooperatively work to generate cognitive behaviors. However, the structure-function coupling characteristics in normal aging individuals remain unclear. Here, we developed an index, the Coupling in Brain Structural connectome and Functional connectome (C-BSF) index, to quantify regional structure-function coupling in a large community-based cohort. C-BSF used diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) data from the Polyvascular Evaluation for Cognitive Impairment and Vascular Events study (PRECISE) cohort (2007 individuals, age: 61.15 ± 6.49 years) and the Sydney Memory and Ageing Study (MAS) cohort (254 individuals, age: 83.45 ± 4.33 years). We observed that structure-function coupling was the strongest in the visual network and the weakest in the ventral attention network. We also observed that the weaker structure-function coupling was associated with increased age and worse cognitive level of the participant. Meanwhile, the structure-function coupling in the visual network was associated with the visuospatial performance and partially mediated the connections between age and the visuospatial function. This work contributes to our understanding of the underlying brain mechanisms by which aging affects cognition and also help establish early diagnosis and treatment approaches for neurological diseases in the elderly.

AIM: To synthesize international findings on the alcohol-dementia relationship, including representation from low- and middle-income countries. METHODS: Individual participant data meta-analysis of 15 prospective epidemiological cohort studies from countries situated in six continents. Cox regression investigated the dementia risk associated with alcohol use in older adults aged over 60 years. Additional analyses assessed the alcohol-dementia relationship in the sample stratified by sex and by continent. Participants included 24 478 community dwelling individuals without a history of dementia at baseline and at least one follow-up dementia assessment. The main outcome measure was all-cause dementia as determined by clinical interview. RESULTS: At baseline, the mean age across studies was 71.8 (standard deviation = 7.5, range = 60-102 years), 14 260 (58.3%) were female and 13 269 (54.2%) were current drinkers. During 151 636 person-years of follow-up, there were 2124 incident cases of dementia (14.0 per 1000 person-years). When compared with abstainers, the risk for dementia was lower in occasional [hazard ratio (HR) = 0.78; 95% confidence interval (CI) = 0.68-0.89], light-moderate (HR = 0.78; 95% CI = 0.70-0.87) and moderate-heavy drinkers (HR = 0.62; 95% CI = 0.51-0.77). There was no evidence of differences between life-time abstainers and former drinkers in terms of dementia risk (HR = 0.98; 95% CI = 0.81-1.18). In dose-response analyses, moderate drinking up to 40 g/day was associated with a lower risk of dementia when compared with lif-time abstaining. Among current drinkers, there was no consistent evidence for differences in terms of dementia risk. Results were similar when the sample was stratified by sex. When analysed at the continent level, there was considerable heterogeneity in the alcohol-dementia relationship. CONCLUSIONS: Abstinence from alcohol appears to be associated with an increased risk for all-cause dementia. Among current drinkers, there appears to be no consistent evidence to suggest that the amount of alcohol consumed in later life is associated with dementia risk.

IntroductionThough consistent evidence suggests that physical activity may delay dementia onset, the duration and amount of activity required remains unclear.MethodsWe harmonized longitudinal data of 11,988 participants from 10 cohorts in eight countries to examine the dose-response relationship between late-life physical activity and incident dementia among older adults.ResultsUsing no physical activity as a reference, dementia risk decreased with duration of physical activity up to 3.1 to 6.0 hours/week (hazard ratio [HR] 0.88, 95% confidence interval [CI] 0.67 to 1.15 for 0.1 to 3.0 hours/week; HR 0.68, 95% CI 0.52 to 0.89 for 3.1 to 6.0 hours/week), but plateaued with higher duration. For the amount of physical activity, a similar pattern of dose-response curve was observed, with an inflection point of 9.1 to 18.0 metabolic equivalent value (MET)-hours/week (HR 0.92, 95% CI 0.70 to 1.22 for 0.1 to 9.0 MET-hours/week; HR 0.70, 95% CI 0.53 to 0.93 for 9.1 to 18.0 MET-hours/week).DiscussionThis cross-national analysis suggests that performing 3.1 to 6.0 hours of physical activity and expending 9.1 to 18.0/MET-hours of energy per week may reduce dementia risk.

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

BackgroundSocial health in the context of dementia has recently gained interest. The development of a social health conceptual framework at the individual and social environmental levels, has revealed a critical need for a further exploration of social health markers that can be used in the development of dementia intervention and to construct social health measures.ObjectiveTo identify social health markers in the context of dementia.MethodThis international qualitative study included six countries: Australia, Germany, Indonesia, Italy, Poland, and the Netherlands. Using purposive sampling, three to five cases per country were recruited to the study, with each case consisting of a person living with dementia, a primary informal caregiver, an active network member, and a health care professional involved in the care of the person with dementia. In-depth interviews, using an agreed topic guide, and content analysis were conducted to identify known and new social health markers. The codes were then categorized against our conceptual framework of social health.ResultsSixty-seven participants were interviewed. We identified various social health markers, ranging from those that are commonly used in epidemiological studies such as loneliness to novel markers of social health at the individual and the social environmental level. Examples of novel individual-level markers were efforts to comply with social norms and making own choices in, for example, keeping contact or refusing support. At a social environmental level, examples of novel markers were proximity (physical distance) and the function of the social network of helping the person maintaining dignity.ConclusionsThe current study identified both well-known and novel social health markers in the context of dementia, mapped to the social health framework we developed. Future research should focus on translating these markers into validated measures and on developing social health focused interventions for persons with dementia.

Introduction Promising evidence is emerging for the procognitive, anti-inflammatory and neuroprotective properties of dietary flavonoids, particularly anthocyanins that provide red, purple and blue plant pigments.Methods and analysis The ‘Food for Thought’ study is a multicentre, 6-month randomised, parallel 3-arm clinical trial. Its primary aim is to investigate whether anthocyanin consumption, either through diet or supplementation, can prevent memory loss progression and improve inflammatory and cardiovascular health in older adults at risk for dementia. Eligible participants will include those aged 60–85 years with a diagnosis of amnestic mild cognitive impairment or with a self-referral of memory concerns and scoring ≤13 on the Memory Index Score within the Telephone Montreal Cognitive Assessment screening test. Participants will be randomised to one of three arms: High anthocyanin (‘purple foods’) diet (aiming for a target of 250 mg anthocyanins/day); freeze-dried product derived from blackcurrants (250 mg anthocyanins/day); or control (coloured maltose powder). The primary outcome is auditory anterograde memory functioning assessed by the Buschke and Grober Free and Cued Selective Reminding Test-Immediate Recall. Secondary outcomes are additional cognitive functions including processing speed, working memory, aspects of executive functioning (attentional shifting and word generativity) and premorbid estimate as well as subjective memory problems and self-reported depression symptoms. Additional secondary outcomes are blood pressure, inflammatory biomarkers, brain-derived neurotrophic factor, fatty acid profile, apolipoprotein E and polyphenol metabolites, gut microbiota composition and function and vascular and microvascular endothelial function tests. Repeated measures analysis of variance and/or mixed linear modelling will evaluate changes over time, with the inclusion of covariates.Ethics and dissemination Ethics approval has been obtained from the Greater Western Human Research Ethics Committee (2021/ETH12083). A Consumer Advisory Group was established to guide and review the protocol and dissemination strategy. The results of this trial are intended to be published in a peer-reviewed journal.Trial sponsor National Health and Medical Research Centre Dementia Collaborative Research Centre.Start date of clinical trial: 02 September 2022.Expected end date: 11 October 2024.Trial registration number ACTRN12622000065796.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

Background: The SKT is a short cognitive performance test designed to assess impairments in memory and cognitive abilities such as attention and speed of information processing. In 2019, new regression-based norms for the English version of the SKT were calculated. This study has two aims: to establish valid cut-offs for distinguishing between no cognitive impairment, mild cognitive impairment (MCI), and dementia (1) and to cross-validate the new norms for detecting MCI and dementia in a community sample of older adults with clinical diagnoses (2). Methods: The validation sample included 143 older adults (mean age = 87.7, SD = 3.55) from the Sydney Memory and Aging Study (MAS Study). Participants were classified as having normal cognition, MCI, or dementia solely based on a consensus diagnosis; in addition, three tests (SKT, Mini-Mental State Examination (MMSE), and Addenbrooke’s Cognitive Examination III (ACE-III)) to measure cognitive impairment were applied. Sensitivity and specificity for all three tests, as well as bivariate correlations, were calculated. Results: The sensitivity of the SKT for the differentiation of cognitive impairment (MCI or dementia) from normal cognition was 80.6%. The convergence between the SKT and the consensus diagnoses was 70.3% for all three diagnostic groups. All correlations between the three tests and the consensus diagnosis were significant (p < 0.01). Conclusions: In sum, it can be stated that the SKT is a valid tool for detecting early stages of cognitive impairment, performing very well in discriminating between no cognitive impairment and cognitive impairment (MCI or dementia).

Abstract Background Forward with Dementia is a co-designed campaign to improve communication of dementia diagnosis and post-diagnostic support. Methods Webinars, a website, social and traditional media, and promotions through project partners were used to disseminate campaign messages to health and social care professionals (primary audience) and people with dementia and carers (secondary audience). The campaign ran between October 2021 and June 2022, with 3-months follow-up. The RE-AIM framework was used for process evaluation. Measurements included surveys and interviews, a log of activities (e.g. webinars, social media posts) and engagements (e.g. attendees, reactions to posts), and Google Analytics. Results There were 29,053 interactions with campaign activities. More than three-quarters of professionals (n = 63/81) thought webinars were very or extremely helpful. Professionals and people with dementia and carers reported that the website provided appropriate content, an approachable tone, and was easy to use. Following campaign engagement, professionals planned to (n = 77/80) or had modified (n = 29/44) how they communicated the diagnosis and/or provided post-diagnostic information and referrals. Qualitative data suggested that the campaign may have led to benefits for some people with dementia and carers. Conclusions Forward with Dementia was successful in terms of reach, appropriateness, adoption and maintenance for professionals, however flow-through impacts on people with dementia are not clear. Targeted campaigns can potentially change health professionals’ communication and support around chronic diseases such as dementia.

Abstract INTRODUCTION White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions. METHODS We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population‐based cohorts of non‐demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains. RESULTS Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing. CONCLUSION The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.

Introduction: Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive change after stroke are unclear. We aimed to measure changes in the trajectory of cognitive function following a first stroke, controlling for pre-stroke cognitive performance using diverse population-based studies from the Cohort Studies of Memory in an International Consortium (COSMIC). Methods: Fourteen longitudinal cohorts from 11 countries from Asia, Africa, North America, South America, Europe, and Australia contributed data. Cognitive domain scores were formed by selecting the most common test administered amongst studies in each domain (memory, processing speed, language, and executive function) and the scores standardised; global cognition was the standardised average of the 4 domains and the primary outcome. One-stage IPD meta- analysis with linear mixed model and regression discontinuity design was used to model the change in cognitive function. Time-dependent incident stroke, age, time in study, and time since stroke were included in the basic model. In the full model we adjusted for sex, education, ethno- racial group, study period and potential confounders significant in the basic model at p

Abstract INTRODUCTION Long‐term improvements in physical inactivity and other behavioral risk factors are integral to dementia risk reduction; however, sustained behavior change is challenging. Apathy, depression, and fatigue may impact engagement in health behaviors, but their presentation overlaps. This study investigates whether these symptoms are differentially associated with multiple health behaviors. METHODS In 1037 community‐dwelling older adults without dementia (aged 70–90, 55% women), regression analyses examined apathy, depression, and fatigue as predictors of health behaviors (physical activity, diet, alcohol, smoking) and a behavioral risk index. RESULTS Apathy was associated with reduced physical activity and alcohol use, and one or multiple behavioral risk factors. No or inconsistent relations were found between depression or fatigue and health behaviors. DISCUSSION Apathy is relevant to multiple health behaviors and should be considered when designing health promotion for older adults, including interventions for dementia risk reduction. Findings highlight the importance of distinguishing apathy from comorbid symptoms. Highlights Novel theory‐based perspective on behavioural risk factors for dementia. Higher apathy predicted less physical activity and alcohol use, and increased odds of lifestyle risk factors. Depressive symptoms were not associated with any health behavior. Apathy may be a determinant of multiple health behaviors in older adults, distinct from depression and fatigue. Considering apathy in precision prevention of dementia appears warranted.