Dementia Risk Score Research Articles

Education as a moderator of middle-age cardiovascular risk factor-old-age cognition relationships: testing cognitive reserve hypothesis in epidemiological study.

Backgroundhigher educational attainment and less midlife cardiovascular risk factors are related to better old-age cognition. Whether education moderates the association between cardiovascular risk factors and late-life cognition is not known. We studied if higher education provides resilience against the deteriorative effects of higher middle-age body mass index (BMI) and a combination of midlife cardiovascular risk factors on old-age cognition.Methodsthe study population is the older Finnish Twin Cohort (n = 4,051, mean age [standard deviation, SD] = 45.5 years [6.5]). Cardiovascular risk factors and education were studied at baseline with questionnaires in 1975, 1981 and/or 1990 (participation rates of 89, 84 and 77%, respectively). Cognition was evaluated with telephone interviews (participation rate 67%, mean age [SD] =73.4 [2.9] years, mean follow-up [SD] = 27.8 [6.0] years) in 1999–2017. We studied the main and interactive effects of education and BMI/dementia risk score on late-life cognition with linear regression analysis. The study design was formulated before the pre-defined analyses.Resultsyears of education moderated the association between BMI with old-age cognition (among less educated persons, BMI-cognition association was stronger [B = −0.24 points per BMI unit, 95% CI −0.31, −0.18] than among more educated persons [B = −0.06 points per BMI unit, 95% CI −0.16, 0.03], Pinteraction < 0.01). There was a similar moderating effect of education on dementia risk score consisting of cardiovascular risk factors (P < 0.001).Conclusionsour results support the cognitive reserve hypothesis. Those with higher education may tolerate the deteriorative effects of midlife cardiovascular risk factors on old-age cognition better than those with lower education.

Dementia Risk Scores and Their Role in the Implementation of Risk Reduction Guidelines.

Dementia prevention is a global health priority. In 2019, the World Health Organisation published its first evidence-based guidelines on dementia risk reduction. We are now at the stage where we need effective tools and resources to assess dementia risk and implement these guidelines into policy and practice. In this paper we review dementia risk scores as a means to facilitate this process. Specifically, we (a) discuss the rationale for dementia risk assessment, (b) outline some conceptual and methodological issues to consider when reviewing risk scores, (c) evaluate some dementia risk scores that are currently in use, and (d) provide some comments about future directions. A dementia risk score is a weighted composite of risk factors that reflects the likelihood of an individual developing dementia. In general, dementia risks scores have a wide range of implementations and benefits including providing early identification of individuals at high risk, improving risk perception for patients and physicians, and helping health professionals recommend targeted interventions to improve lifestyle habits to decrease dementia risk. A number of risk scores for dementia have been published, and some are widely used in research and clinical trials e.g., CAIDE, ANU-ADRI, and LIBRA. However, there are some methodological concerns and limitations associated with the use of these risk scores and more research is needed to increase their effectiveness and applicability. Overall, we conclude that, while further refinement of risk scores is underway, there is adequate evidence to use these assessments to implement guidelines on dementia risk reduction.

A pragmatic dementia risk score for patients with mild cognitive impairment in a memory clinic population: Development and validation of a dementia risk score using routinely collected data.

IntroductionThis study aimed to develop and validate a 3‐year dementia risk score in individuals with mild cognitive impairment (MCI) based on variables collected in routine clinical care.MethodsThe prediction score was trained and developed using data from the National Alzheimer's Coordinating Center (NACC). Selection criteria included aged 55 years and older with MCI. Cox models were validated externally using two independent cohorts from the Prospective Registry of Persons with Memory Symptoms (PROMPT) registry and the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.ResultsOur Mild Cognitive Impairment to Dementia Risk (CIDER) score predicted dementia risk with c‐indices of 0.69 (95% confidence interval [CI] 0.66–0.72), 0.61 (95% CI 0.59–0.63), and 0.72 (95% CI 0.69–0.75), for the internally validated and the external validation PROMPT, and ADNI cohorts, respectively.DiscussionThe CIDER score could be used to inform clinicians and patients about the relative probabilities of developing dementia in patients with MCI.

Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients

Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice. To assess the ability of machine learning algorithms to predict dementia incidence within 2 years compared with existing models and determine the optimal analytic approach and number of variables required. This prognostic study used data from a prospective cohort of 15 307 participants without dementia at baseline to perform a secondary analysis of factors that could be used to predict dementia incidence. Participants attended National Alzheimer Coordinating Center memory clinics across the United States between 2005 and 2015. Analyses were conducted from March to May 2021. 258 variables spanning domains of dementia-related clinical measures and risk factors. The main outcome was incident all-cause dementia diagnosed within 2 years of baseline assessment. In a sample of 15 307 participants (mean [SD] age, 72.3 [9.8] years; 9129 [60%] women and 6178 [40%] men) without dementia at baseline, 1568 (10%) received a diagnosis of dementia within 2 years of their initial assessment. Compared with 2 existing models for dementia risk prediction (ie, Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score, and the Brief Dementia Screening Indicator), machine learning algorithms were superior in predicting incident all-cause dementia within 2 years. The gradient-boosted trees algorithm had a mean (SD) overall accuracy of 92% (1%), sensitivity of 0.45 (0.05), specificity of 0.97 (0.01), and area under the curve of 0.92 (0.01) using all 258 variables. Analysis of variable importance showed that only 6 variables were required for machine learning algorithms to achieve an accuracy of 91% and area under the curve of at least 0.89. Machine learning algorithms also identified up to 84% of participants who received an initial dementia diagnosis that was subsequently reversed to mild cognitive impairment or cognitively unimpaired, suggesting possible misdiagnosis. These findings suggest that machine learning algorithms could accurately predict incident dementia within 2 years in patients receiving care at memory clinics using only 6 variables. These findings could be used to inform the development and validation of decision-making aids in memory clinics.

Development and external validation of a novel dementia risk prediction score in the UK Biobank cohort

AbstractBackgroundGlobally, up to 40% of dementia cases may be prevented if several key risk factors, such as low education and obesity, are targeted. This has motivated interest into the development of risk scores that aim to quantify an individual’s risk of developing dementia within a given time frame. However, translation to a clinical setting has been hampered by either a lack of external validation, poor out‐of‐sample performance, or the integration of measures (e.g., MRI, cognitive testing) that are costly or time intensive to administer.This study aimed to develop a novel dementia risk score suitable for a primary care setting and compare its discrimination accuracy with other risk scores.Method208,108 UK Biobank (UKB) participants were examined, with cases of incident dementia (mean time to diagnosis ± SD = 5.91 years ± 2.02) identified through self‐report, hospital inpatient records and death certificates (n = 1,270, 0.6%). The dataset was randomly split into a training (80%) and test set (20%). Potential predictors (n = 30) included Apolipoprotein E4 (APOE4) status and cardiovascular, medical and lifestyle factors collected at baseline. Logistic LASSO regression was employed for variable selection and logistic regression was then used to derive beta coefficients for each predictor included in the UKB dementia risk score (UKB‐DRS). The area under the curve (i.e., AUC) was used to compare the discriminative ability of the UKB‐DRS to the CAIDE, ANU‐ADRI, Dementia Risk Score (i.e., DRS) and Framingham risk score, in both the test set and the Whitehall II study (WHIII, n = 2,974), which served as an external dataset.ResultThe UKB‐DRS consisted of age, sex, education, APOE4 status, a medical history of diabetes, stroke and depression and a family history of dementia. The UKB‐DRS demonstrated good discrimination accuracy in both the test set (AUC [95% ] = 0.79 [0.77, 0.82]) and external dataset (AUC [95% CI] = 0.83 [0.79,0.87]). Additionally, the UKB‐DRS outperformed all other risk scores (the DRS had the next best AUC [95% CI]: UKB = 0.77 [0.74, 0.8]; WHII = 0.77 [0.73, 0.81]).ConclusionThis study contributes a novel dementia risk score that may be used to guide primary prevention strategies.

Cardiovascular and dementia risk scores and their association with dementia‐related biomarkers in a memory clinic population

AbstractBackgroundRisk scores for dementia and cardiovascular disease (CVD) predict dementia development, but their link to underlying brain pathology remains unclear. This study explored the cross‐sectional associations between well‐validated CVD and dementia risk scores and dementia‐related cerebrospinal fluid (CSF) and imaging markers in memory clinic patients without dementia,MethodThe study population consisted of 207 patients with subjective cognitive impairment or mild cognitive impairment from the Karolinska University Hospital, Theme Aging, Memory Clinic, who had CSF (Aβ42, phosphorylated tau, total tau, neurofilament light chain NfL), visual MRI ratings (medial temporal lobe atrophy MTA, Fazekas for white matter lesions WML), and available clinical data to calculate risk scores. CVD risk score (FINRISK) was calculated for all patients; data for the CAIDE Dementia Risk Score (with and without APOE) were available for a subsample (N=88). The associations between risk scores and biomarkers were analyzed with linear regression (zero‐skewness log‐transformed CSF biomarkers as dependent variables) and ordinal regression (MTA and WML ratings as dependent variables). Risk scores were categorized into 3 similar‐sized groups (lower‐, intermediate‐, and higher‐risk groups; lower‐risk group used as reference),ResultHigher FINRISK score and CAIDE score (with APOE) were associated with lower levels of CSF Aβ42 (coefficients in the higher‐risk groups ‐0.05, p=0.02 for FINRISK and ‐0.08, p=0.04 for CAIDE). Higher CAIDE score (with APOE) was also associated with a lower CSF Aβ42/p‐tau ratio (coefficient ‐0.03, p=0.03 in the higher‐risk group). With respect to neuronal injury markers, a higher risk of CVD and dementia was associated with higher CSF NfL levels (coefficients in the higher‐risk groups 0.58, p&lt;0.001 for FINRISK; 0.38, p=0.001 for CAIDE; 0.34, p=0.005 for CAIDE with APOE). Furthermore, higher‐risk patients had more pronounced MTA (OR 2.3, 95% CI 1.2–4.5 for FINRISK; OR 3.0, 95% CI 1.2–7.4 for CAIDE), and WML (OR 2.4, 95% CI 1.2–4.5 for FINRISK),ConclusionHaving a higher risk of CVD or dementia was associated with several dementia‐related CSF and imaging markers. Follow‐up studies are needed to explore the utility of different risk scores in assessing risk of cognitive decline and disease progression in memory clinic patients.

Association of neighborhood‐level socioeconomic advantage with cognition and dementia risk factors in an Australian cohort

AbstractBackgroundResiding in areas of low socioeconomic advantage is associated with increased risk of dementia1 and associated brain pathology2,3. Given the long and insidious course of dementia pathologies, it is critical to establish the effect of ‘exposomic’ risk factors in midlife and to understand which groups of people are particularly vulnerable. Therefore, the objective of this study was to examine whether cognitive performance or dementia risk factors differed according to neighborhood‐level socioeconomic advantage in cognitively normal middle‐aged people.MethodsOur sample comprised 4798 participants from the Healthy Brain Project, an online cohort of community‐dwelling Australians aged 40‐70 years. Socioeconomic advantage was computed by matching participants’ residential address to the Australian Bureau of Statistics’ Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD), assigning each participant a decile score (10 being the most advantaged). Scores were related to dementia risk estimated using the CAIDE dementia risk score and cognitive performance measured with the Cogstate Brief Battery (CBB) in linear regression models.ResultsOf the 4798 participants (mean age±SD 56±7 years, 26% male), 2762 (58%) were classified as living within an area of high neighbourhood socioeconomic advantage (IRSAD scores ≥ 8th decile), 1296 resided in rural or regional areas (27%), and 984 identified as “non‐European” (21%). Each decile unit increase in neighborhood socioeconomic advantage was associated with a lower CAIDE dementia risk score (β±SE= ‐0.088±0.024, p &lt;0.001), following adjustments for race and rurality, and with better memory performance (β±SE= 0.084±0.024, p &lt;0.001), following adjustments for age, sex, race, education, and rurality. An interaction was observed with differences in memory performance between levels of neighborhood advantage (comparing scores above and below the 8th decile) being larger at older ages and in people with higher dementia risk scores (Figure 1). There was no association between neighborhood‐level advantage and attention.ConclusionsIn a middle‐aged Australian cohort, higher neighborhood‐level socioeconomic advantage was associated with superior memory and lower dementia risk scores. Efforts to lower dementia risk factors, particularly in relation to reducing the negative impacts of disadvantage, are needed to curtail the growing burden of dementia.

The impact of built and social environmental characteristics on incidence and estimated risk of dementia

AbstractBackgroundDementia is a public health priority1 and the current study designed to investigate associations between built and social environmental characteristics and dementia incidence, and the estimated future risk of dementia. Further we investigated spatial variations in dementia risk and dementia incidence to identify unmet areas for policy intervention.MethodWe used 25,511 patients (aged 65 years and older) records in Adelaide between 2011‐2015. In addition to dementia incidence, we calculated a dementia risk score based on risk and protective factors for patients not diagnosed with dementia. The following built and social environment exposures were estimated for each statistical area level 1 (SA1)2: social fragmentation, nitrogen dioxide (NO2), public open spaces, walkability, socio‐economic status and the length of main roads. We performed multilevel regression analyses to allow for the hierarchical nature of the data and applied spatial cluster analysis to identify areas with high and low risk of dementia.ResultWe found that a one standard deviation (SD) increase in NO2 and walkability score was associated with 10% higher odds of any versus no dementia (95% confidence interval (CI): 1%, 21% for NO2 and 0%, 22% for walkability score). For estimated future risk of dementia, a 1‐SD increase in social fragmentation (mobility component) and NO2 was associated with a 1% increase in dementia risk (95% CI: 0, 1%). 1‐SD increases in public open space and socioeconomic status were associated with 3% (95% CI: 0.95, 0.98) and 1% decreases (95% CI: 0.98, 0.99) in dementia risk, respectively. There was spatial heterogeneity in the pattern of dementia incidence and dementia risk.ConclusionAssociations of neighbourhood NO2 level, walkability, public open space and social fragmentation with dementia incidence and estimated future risk of dementia were statistically significant, indicating the potential to reduce the risk through changes in built and social environments. Mapping the estimated future risk of dementia and diagnosed cases of dementia offers a novel approach to identifying areas of unmet need. 1. Towards a dementia plan: a WHO guide. Geneva: WHO; 2018. 2. Australian Statistical Geography Standard (ASGS): Volume 1 ‐ Main Structure and Greater Capital City Statistical Areas, 2016.

Maintain Your Brain trial: Early findings and lessons learned from adherence and compliance data

AbstractBackgroundTechnology and web‐based approaches potentially provide scalable population‐based interventions to reduce modifiable risk factors for dementia. Key issues in online interventions are recruitment and retention. To devise strategies to improve population reach We investigated which factors influence recruiting and maintaining participants in such an intervention, the in‐progress Maintain Your Brain trial.MethodInvitations were sent to people aged 55‐77 years from the 45 and Up study, a population‐based cohort study of one in ten people aged 45 years and older in New South Wales, Australia (n = 267,000). For MYB, participants were required to be eligible for at least one of four modules to be enrolled (physical activity, nutrition, brain training and mental wellbeing). All participants received modules based on their risks and were randomly allocated to either personalised coaching (intervention) or static information (control). Associations between participant characteristics (listed Table 1) and likelihood of completing set assessment tasks was assessed at two key stages – end of baseline and end of 12‐month follow‐up using stepwise (forward) regression.ResultsOf 96,418 people invited, 12,281 (13%) participants started baseline and completed a mean of 6.2 (SD 4.3) of ten assessments. Of these, 6,236 (6%) were enrolled in the trial. At 12‐months participants completed a mean of 5.0 of 8 assessments (SD = 3.8). Completion rate of the primary outcome (two tasks) was 62% (3,869). In the final regression model for baseline (Table1), overall associations were weak even though statistically significant, with only years of education not entered in the final model. The follow‐up model included retirement status, gender, baseline dementia risk and baseline wellbeing. However, this model (df1 = 1, df2 =6231; R2 = .01) accounted for even less variation than baseline model (R2 = .04).ConclusionOverall, regression models of participant characteristics accounted for a low amount of variation in task completion rates at both baseline and follow‐up. Participants were less likely to complete baseline tasks if they were older, male, not living with a spouse or alone and not retired or had lower dementia risk score and more psychological distress.

Occupational complexity and neuroimaging measures of structural MRI and PET‐amyloid in a randomized controlled trial: FINGER

AbstractBackgroundHigher occupational complexity has been associated with better cognition in late life, but associations with brain changes remain unclear. We assessedwhether occupational complexity was associated with baseline brain structural MRI measures and PIB‐PET amyloid burden in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER).MethodFINGER is a two‐year, population‐based, multicenter, multidomain randomized controlled trial. Inclusion criteria included age 60‐77 years; Cardiovascular Risk Factors, Aging and Dementia Risk Score of at least 6; cognition at a mean level or slightly lower than expected for age. Participants (n=1260) were randomly assigned in a 1:1 ratio to a multidomain intervention group (diet, exercise, cognitive training, vascular risk management) or a group receiving general health advice. Primary outcome was change in cognition (Neuropsychological Test Battery). Occupational complexity with data, people, and substantive complexity were classified through the Dictionary of Occupational Titles. The MRI analyses included a subgroup of 126 participants from three different FINGER study sites and the PiB‐PET measures included 42 participants from one study site. MRI regional cortical thickness and volumes were measured using the Freesurfer image analysis suite (version 5.0.3). Linear, logistic, and ordinal logistic regression models were used to assess the association between occupational complexity and neuroimaging measures, adjusting for age, sex, education, intracranial volume, and study site. Neuroimaging assessments included hippocampal and total gray matter volume, Alzheimer´s disease signature thickness, visually rated medial temporal atrophy (MTA), and amyloid accumulation.ResultThere was no association between occupational complexity and brain cortical thickness, volume measures, or PiB‐PET measures.ConclusionNo association between occupational complexity and brain structure and amyloid burden was found in older adults at increased risk of dementia. These findings should be verified in larger cohorts.

The Impact of Built and Social Environmental Characteristics on Diagnosed and Estimated Future Risk of Dementia.

Dementia is a major global health challenge and the impact of built and social environments' characteristics on dementia risk have not yet been fully evaluated. To investigate associations between built and social environmental characteristics and diagnosed dementia cases and estimated dementia risk. We recruited 25,511 patients aged 65 and older from family physicians' practices. We calculated a dementia risk score based on risk and protective factors for patients not diagnosed with dementia. Our exposure variables were estimated for each statistical area level 1: social fragmentation, nitrogen dioxide, public open spaces, walkability, socio-economic status, and the length of main roads. We performed a multilevel mixed effect linear regression analysis to allow for the hierarchical nature of the data. We found that a one standard deviation (1-SD) increase in NO2 and walkability score was associated with 10% higher odds of any versus no dementia (95% CI: 1%, 21% for NO2 and 0%, 22% for walkability score). For estimated future risk of dementia, a 1-SD increase in social fragmentation and NO2 was associated with a 1% increase in dementia risk (95% CI: 0, 1%). 1-SD increases in public open space and socioeconomic status were associated with 3% (95% CI: 0.95, 0.98) and 1% decreases (95% CI: 0.98, 0.99) in dementia risk, respectively. There was spatial heterogeneity in the pattern of diagnosed dementia and the estimated future risk of dementia. Associations of neighborhood NO2 level, walkability, public open space, and social fragmentation with diagnosed dementia cases and estimated future risk of dementia were statistically significant, indicating the potential to reduce the risk through changes in built and social environments.

Development of the First WHO Guidelines for Risk Reduction of Cognitive Decline and Dementia: Lessons Learned and Future Directions.

The first WHO guidelines for risk reduction of cognitive decline and dementia marked an important milestone in the field of dementia prevention. In this paper, we discuss the evidence reviewed as part of the guidelines development and present the main themes emerged from its synthesis, to inform future research and policies on dementia risk reduction. The role of intervention effect-size; the mismatch between observational and intervention-based evidence; the heterogeneity of evidence among intervention trials; the importance of intervention duration; the role of timing of exposure to a certain risk factor and interventions; the relationship between intervention intensity and response; the link between individual risk factors and specific dementia pathologies; and the need for tailored interventions emerged as the main themes. The interaction and clustering of individual risk factors, including genetics, was identified as the overarching theme. The evidence collected indicates that multidomain approaches targeting simultaneously multiple risk factors and tailored at both individual and population level, are likely to be most effective and feasible in dementia risk reduction. The current status of multidomain intervention trials aimed to cognitive impairment/dementia prevention was also briefly reviewed. Primary results were presented focusing on methodological differences and the potential of design harmonization for improving evidence quality. Since multidomain intervention trials address a condition with slow clinical manifestation—like dementia—in a relatively short time frame, the need for surrogate outcomes was also discussed, with a specific focus on the potential utility of dementia risk scores. Finally, we considered how multidomain intervention could be most effectively implemented in a public health context and the implications world-wide for other non-communicable diseases targeting common risk factors, taking into account the limited evidence in low-middle income countries. In conclusion, the evidence from the first WHO guidelines for risk reduction of cognitive decline and dementia indicated that “one size does not fit all,” and multidomain approaches adaptable to different populations and individuals are likely to be the most effective. Harmonization in trial design, the use of appropriate outcome measures, and sustainability in large at-risk populations in the context of other chronic disorders also emerged as key elements.

Development and validation of the dialysis dementia risk score: A retrospective, population-based, nested case-control study.

BackgroundDementia is prevalent and underdiagnosed in the dialysis population. We aimed to develop and validate a simple dialysis dementia scoring system to facilitate identification of individuals who are at high risk for dementia.MethodsWe applied a retrospective, nested case‐control study design using a national dialysis cohort derived from the National Health Insurance Research Database in Taiwan. Patients aged between 40 and 80 years were included and 2940 patients with incident dementia were matched to 29,248 non‐dementia controls. All subjects were randomly divided into the derivation and validation sets with a ratio of 4:1. Conditional logistic regression models were used to identify factors contributing to the risk score. The cutoff value of the risk score was determined by Youden's J statistic and the graphic method.ResultsThe dialysis dementia risk score (DDRS) finally included age and 10 comorbidities as risk predictors. The C‐statistic of the model was 0.71 (95% confidence interval [CI] 0.70–0.72). Calibration revealed a strong linear relationship between predicted and observed dementia risk (R 2 = 0.99). At a cutoff value of 50 points, the high‐risk patients had an approximately three‐fold increased risk of having dementia compared to those with low risk (odds ratio [OR] 3.03, 95% CI 2.78–3.31). The DDRS performance, including discrimination (C‐statistic 0.71, 95% CI 0.69–0.73) and calibration (p value of Hosmer−Lemeshow test for goodness of fit = 0.18), was acceptable during validation. The OR value (2.82, 95% CI 2.37–3.35) was similar to those in the derivation set.ConclusionThe DDRS system has the potential to serve as an easily accessible screening tool to determine the high‐risk groups who deserve subsequent neurological evaluation in daily clinical practice.

Association of Dementia Human Leukocyte Antigen (HLA) Profile with Human Herpes Viruses 3 and 7: An in-silico Investigation

Human leukocyte antigen (HLA), the most highly polymorphic region of the human genome, is increasingly recognized as an important genetic contributor to dementia risk and resilience. HLA is involved in protection against foreign antigens including human herpes viruses (HHV), which have been widely implicated in dementia. Here we used an in silico approach1 to determine binding affinities of glycoproteins from 9 human herpes virus (HHV) strains to 113 HLA alleles, and to examine the association of a previously identified HLA-dementia risk profile2 to those affinities. We found a highly significant correlation between high binding affinities of HLA alleles to HHV 3 and 7 and the dementia risk scores of those alleles, such that the higher the estimated binding affinity, the lower the dementia risk score. These findings suggest that protection conferred by HLA alleles may be related to their ability to bind and eliminate HHV3 and HHV7 and point to the possibility that protection against these viruses may reduce dementia incidence.

Prediction of Cognitive Decline Using Heart Rate Fragmentation Analysis: The Multi-Ethnic Study of Atherosclerosis.

Background: Heart rate fragmentation (HRF), a new non-invasive metric quantifying cardiac neuroautonomic function, is associated with increasing age and cardiovascular disease. Since these are risk factors for cognitive decline and dementia, in the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether disrupted cardiac neuroautonomic function, evidenced by increased HRF, would be associated with worse cognitive function assessed concurrently and at a later examination, and with greater cognitive decline.Methods: HRF was derived from the ECG channel of the polysomnographic recordings obtained in an ancillary study (n = 1,897) conducted in conjunction with MESA exam 5 (2010–2012). Cognitive function was assessed at exam 5 and 6.4 ± 0.5 years later at exam 6 (2016–2018) with tests of global cognitive performance (the Cognitive Abilities Screening Instrument, CASI), processing speed (Digit Symbol Coding, DSC) and working memory (Digit Span). Multivariable regression models were used to quantify the associations between HRF indices and cognitive scores.Results: The participants’ mean age was 68 ± 9 years (54% female). Higher HRF at baseline was independently associated with lower cognitive scores at both exams 5 and 6. Specifically, in cross-sectional analyses, a one-standard deviation (SD) (13.7%) increase in HRF was associated with a 0.51 (95% CI: 0.17–0.86) points reduction in CASI and a 1.12 (0.34–1.90) points reduction in DSC. Quantitatively similar effects were obtained in longitudinal analyses. A one-SD increase in HRF was associated with a 0.44 (0.03–0.86) and a 1.04 (0.28–1.81) points reduction in CASI and DSC from exams 5 to 6, respectively. HRF added predictive value to the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE-APOE-ε4) risk score and to models adjusted for serum concentration of NT-proBNP, an analyte associated with cognitive impairment and dementia.Conclusion: Increased HRF assessed during sleep was independently associated with diminished cognitive performance (concurrent and future) and with greater cognitive decline. These findings lend support to the links between cardiac neuroautonomic regulation and cognitive function. As a non-invasive, repeatable and inexpensive probe, HRF technology may be useful in monitoring cognitive status, predicting risk of dementia and assessing therapeutic interventions.

Associations of the Lifestyle for Brain Health Index With Structural Brain Changes and Cognition: Results From the Maastricht Study.

Background and ObjectivesObservational research has shown that a substantial proportion of all dementia cases worldwide are attributable to modifiable risk factors. Dementia risk scores might be useful to identify high-risk individuals and monitor treatment adherence. The objective of this study was to investigate whether a dementia risk score, the Lifestyle for Brain Health (LIBRA) index, is associated with MRI markers and cognitive functioning/impairment in the general population.MethodsCross-sectional data were used from the observational population-based cohort of The Maastricht Study. The weighted compound score of LIBRA (including 12 dementia risk and protective factors, e.g., hypertension, physical inactivity) was calculated, with higher scores indicating higher dementia risk. Standardized volumes of white matter, gray matter, and CSF (as proxy for general brain atrophy), white matter hyperintensities, and presence of cerebral small vessel disease were derived from 3T MRI. Cognitive functioning was tested in 3 domains: memory, information processing speed, and executive function and attention. Values ≤1.5 SDs below the average were defined as cognitive impairment. Multiple regression analyses and structural equation modeling were used, adjusted for age, sex, education, intracranial volume, and type 2 diabetes.ResultsParticipants (n = 4,164; mean age 59 years; 49.7% men) with higher LIBRA scores (mean 1.19, range −2.7 to 9.2), denoting higher dementia risk, had higher volumes of white matter hyperintensities (β = 0.051, p = 0.002) and lower scores on information processing speed (β = −0.067, p = 0.001) and executive function and attention (β = −0.065, p = 0.004). Only in men, associations between LIBRA score and volumes of gray matter (β = −0.093, p < 0.001) and CSF (β = 0.104, p < 0.001) and memory (β = −0.054, p = 0.026) were found. White matter hyperintensities and CSF volume partly mediated the association between LIBRA score and cognition.DiscussionHigher health- and lifestyle-based dementia risk is associated with markers of general brain atrophy, cerebrovascular pathology, and worse cognition, suggesting that LIBRA meaningfully summarizes individual lifestyle-related brain health. Improving LIBRA factors on an individual level might improve population brain health. Sex differences in lifestyle-related pathology and cognition need to be further explored.Classification of EvidenceThis study provides Class II evidence that higher LIBRA scores are significantly associated with lower scores in some cognitive domains and a higher risk of cognitive impairment.

A Modified CAIDE Risk Score as a Screening Tool for Cognitive Impairment in Older Adults.

Although an efficacious dementia-risk score system, Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) was derived using midlife risk factors in a population with low educational attainment that does not reflect today's US population, and requires laboratory biomarkers, which are not always available. Develop and validate a modified CAIDE (mCAIDE) system and test its ability to predict presence, severity, and etiology of cognitive impairment in older adults. Population consisted of 449 participants in dementia research (N = 230; community sample; 67.9±10.0 years old, 29.6%male, 13.7±4.1 years education) or receiving dementia clinical services (N = 219; clinical sample; 74.3±9.8 years old, 50.2%male, 15.5±2.6 years education). The mCAIDE, which includes self-reported and performance-based rather than blood-derived measures, was developed in the community sample and tested in the independent clinical sample. Validity against Framingham, Hachinski, and CAIDE risk scores was assessed. Higher mCAIDE quartiles were associated with lower performance on global and domain-specific cognitive tests. Each one-point increase in mCAIDE increased the odds of mild cognitive impairment (MCI) by up to 65%, those of AD by 69%, and those for non-AD dementia by > 85%, with highest scores in cases with vascular etiologies. Being in the highest mCAIDE risk group improved ability to discriminate dementia from MCI and controls and MCI from controls, with a cut-off of ≥7 points offering the highest sensitivity, specificity, and positive and negative predictive values. mCAIDE is a robust indicator of cognitive impairment in community-dwelling seniors, which can discriminate well between dementia severity including MCI versus controls. The mCAIDE may be a valuable tool for case ascertainment in research studies, helping flag primary care patients for cognitive testing, and identify those in need of lifestyle interventions for symptomatic control.

Association between coronary artery calcification and cognitive function in a Chinese community-based population.

BackgroundCoronary atherosclerosis and cognitive impairment are both age-related diseases, with similar risk factors. Coronary artery calcium (CAC), a marker of coronary atherosclerosis, may play a role in early detection of individuals prone to cognitive decline. This study aimed to investigate the relationship between CAC and cognitive function, and the capability of CAC to identify participants with a high risk of dementia in a Chinese community-based population.MethodsA total of 1332 participants, aged 40−80 years and free of dementia from a community located in Beijing were included. All participants completed neurocognitive questionnaires and noncontrast CT examinations. Cognitive performance tests (including verbal memory, semantic fluency, executive function, and global cognitive function tests), the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CIDE) risk score, and the CAC score (CACS) were evaluated by questionnaires and CT. A CAIDE score ≥ 10 was considered to indicate a high risk of dementia in late-life. Participants were divided into three groups according to CACS (0, 1−399, ≥ 400).ResultsAfter adjusting for risk factors, CACS was significantly associated with verbal memory (r = −0.083, P = 0.003) and global cognitive function (r = −0.070, P = 0.012). The prevalence of a high risk of dementia in the subgroups of CACS = 0, 1−399, and ≥ 400 was 4.67%, 13.66%, and 24.79%, respectively (P < 0.001). Individuals with CACS ≥ 400 had a higher risk of CAIDE score ≥ 10 [OR = 2.30 (1.56, 4.56), P = 0.014] than those with CACS = 0. The receiver-operating characteristic curves showed that the capability of CACS to identify participants with a high risk of dementia was moderate (AUC = 0.70, 95% CI: 0.67−0.72,P < 0.001). ConclusionsCAC, a marker of subclinical atherosclerosis, was significantly associated with cognitive performance in verbal memory and global cognitive function. CAC had a moderate capability to identify participants with a high risk of dementia, independent of age, education, and other risk factors.

Prevention of dementia using mobile phone applications (PRODEMOS): protocol for an international randomised controlled trial

IntroductionProfiles of high risk for future dementia are well understood and are likely to concern mostly those in low-income and middle-income countries and people at greater disadvantage in high-income countries....

Change in CAIDE Dementia Risk Score and Neuroimaging Biomarkers During a 2-Year Multidomain Lifestyle Randomized Controlled Trial: Results of a Post-Hoc Subgroup Analysis.

The CAIDE (Cardiovascular Risk Factors, Aging and Dementia) Risk Score is a validated tool estimating dementia risk. It was previously associated with imaging biomarkers. However, associations between dementia risk scores (including CAIDE) and dementia-related biomarkers have not been studied in the context of an intervention. This study investigated associations between change in CAIDE score and change in neuroimaging biomarkers (brain magnetic resonance imaging [MRI] and Pittsburgh Compound B-positron emission tomography [PiB-PET] measures) during the 2-year Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (post-hoc analyses). FINGER targeted at-risk older adults, aged 60–77 years, from the general population. Participants were randomized to either multidomain intervention (diet, exercise, cognitive training, and vascular risk management) or control group (general health advice). Neuroimaging (MRI and PiB-PET) data from baseline and 2-year visits were used. A toal of 112 participants had repeated brain MRI measures (hippocampal, total gray matter, and white matter lesion volumes, and Alzheimer’s disease signature cortical thickness). Repeated PiB-PET scans were available for 39 participants. Reduction in CAIDE score (indicating lower dementia risk) during the intervention was associated with less decline in hippocampus volume in the intervention group, but not the control group (Randomization group × CAIDE change interaction β coefficient = −0.40, p = .02). Associations for other neuroimaging measures were not significant. The intervention may have benefits on hippocampal volume in individuals who succeed in improving their overall risk level as indicated by a reduction in CAIDE score. This exploratory finding requires further testing and validation in larger studies.