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High blood pressure (BP) and cerebral amyloid angiopathy (CAA) are two common risk factors for intracranial hemorrhage, potentially leading to cognitive impairment. Less is known about the relationship between BP and CAA, the examination of which was the objective of this study. We analyzed data from 2510 participants in the National Alzheimer’s Coordinating Center (NACC) who had information on longitudinal BP measurements before death and on CAA from autopsy. Using the average of four systolic BPs (SBPs) prior to death, SBP was categorized into three groups: n = 435), 120–139 mmHg (n = 1335), and ≥140 mmHg (n = 740). CAA was diagnosed using immunohistochemistry in 1580 participants and categorized as mild (n = 759), moderate (n = 529), or severe (n = 292). When adjusted for age at death, sex, APOE genotype, Braak, CERAD, antihypertensive medication use, and microinfarcts, the odds ratios (95% CIs) for CAA associated with SBPs of 120–139 and ≥140 mmHg were 0.91 (0.74–1.12) and 1.00 (0.80–1.26), respectively. Findings from predictor effect plots show no variation in the probability of CAA between the three SBP categories. Microbleeds had no association with CAA, but among those with SBP ≥ 130 mmHg, the proportion of those with microbleeds was numerically greater in those with more severe CAA (p for trend, 0.084). In conclusion, we found no evidence of an association between SBP and CAA. Future studies need to develop non-invasive laboratory tests to diagnose CAA and prospectively examine this association and its implication on the pathophysiology and outcome of Alzheimer’s disease.

Background Poststroke cognitive impairment (PSCI) occurs in about 60% of patients with stroke in the first year after stroke. However, the question regarding risks of recurrent stroke and mortality in patients with PSCI remains controversial. The goal of this study was to conduct a meta‐analysis of published literature to estimate the risks of stroke recurrence and mortality associated with PSCI. Methods and Results Electronic databases were screened for eligible studies published from 1990 to 2023. The primary end points of this study were recurrent stroke and mortality. Pooled estimates were calculated as hazard ratios (HR) with 95% CIs. Meta‐regression analyses evaluated moderating effects of PSCI severity, study design, and study period on recurrent stroke and mortality. Pooled data from 27 studies comprised 39 412 patients with ischemic stroke. Nine studies evaluated the association between PSCI and risk of stroke recurrence that showed the hazard of recurrent stroke risk was significantly higher in patients with PSCI compared with those without it (HR, 1.59 [95% CI, 1.29–1.94]; I2=52.2%). Eighteen studies examined the impact of PSCI on mortality risk. The pooled hazard of mortality was significantly higher in the group with PSCI relative to the non‐PSCI group (HR, 2.07 [95% CI, 1.65 –2.59]; I2=89.3%). Meta‐regressions showed that the average effect of PSCI on mortality risk differed across study period and study design. Conclusions Based on this meta‐analysis PSCI was statistically significantly associated with increased risks of recurrent stroke and all‐cause mortality. Poststroke neurocognitive assessment may identify patients at a higher risk who may require more aggressive interventions for secondary prevention.

Traditional Rasch estimation of the item and student parameters via marginal maximum likelihood, joint maximum likelihood or conditional maximum likelihood, assume individuals in clustered settings are uncorrelated and items within a test that share a grouping structure are also uncorrelated. These assumptions are often violated, particularly in educational testing situations, in which students are grouped into classrooms and many test items share a common grouping structure, such as a content strand or a reading passage. Consequently, one possible approach is to explicitly recognize the clustered nature of the data and directly incorporate random effects to account for the various dependencies. This article demonstrates how the multilevel Rasch model can be estimated using the functions in R for mixed-effects models with crossed or partially crossed random effects. We demonstrate how to model the following hierarchical data structures: a) individuals clustered in similar settings (e.g., classrooms, schools), b) items nested within a particular group (such as a content strand or a reading passage), and c) how to estimate a teacher × content strand interaction.

Abstract INTRODUCTION Past Alzheimer's disease and related dementias (ADRD) research has not considered ways to ensure the representation of diverse sexual and gender minorities. This study used concept mapping (CM) to identify strategies for engaging and recruiting LGBTQIA+ older adults living with memory loss and their caregivers into ADRD research. METHODS CM, involving brainstorming, thematic analysis, and rating of strategies, was conducted with 46 members from one national and three local community advisory boards. Data was analyzed using The Concept Systems Global MAX™ web platform. RESULTS One hundred twenty‐two solutions were identified from June through December 2022, and represented five key themes: aging focused, LGBTQIA+ specific, memory loss and caregiving support focused, physical advertisements, and other media. Promising strategies included partnering with LGBTQIA+ health centers, attending social groups for older adults, and increasing community representation in marketing. DISCUSSION Tailored strategies, building trust, and community involvement are essential for engaging LGBTQIA+ individuals living with memory loss or ADRD and their caregivers in ADRD‐focused research. Highlights Innovative ways to ensure the inclusion of LGBTQIA+ older adults in Alzheimer's disease and related dementias (ADRD) research can be bolstered through collaboration with key community stakeholders. Promising strategies for recruitment and engagement include partnering with LGBTQIA+ centers, attending social groups for older adults, and ensuring diverse representation in marketing. Tailored recruitment and engagement strategies are crucial for building trust with LGBTQIA+ populations to increase participation in ADRD research.

More than 50 million older people worldwide are suffering from dementia, and this number is estimated to increase to 150 million by 2050. Greater caregiver burdens and financial impacts on the healthcare system are expected as we wait for an effective treatment for dementia. Researchers are constantly exploring new therapies and screening approaches for the early detection of dementia. Artificial intelligence (AI) is widely applied in dementia research, including machine learning and deep learning methods for dementia diagnosis and progression detection. Computerized apps are also convenient tools for patients and caregivers to monitor cognitive function changes. Furthermore, social robots can potentially provide daily life support or guidance for the elderly who live alone. This review aims to provide an overview of AI applications in dementia research. We divided the applications into three categories according to different stages of cognitive impairment: (1) cognitive screening and training, (2) diagnosis and prognosis for dementia, and (3) dementia care and interventions. There are numerous studies on AI applications for dementia research. However, one challenge that remains is comparing the effectiveness of different AI methods in real clinical settings.

Abstract Efficient identification of cognitive decline and Alzheimer's disease (AD) risk in early stages of the AD disease continuum is a critical unmet need. Subjective cognitive decline is increasingly recognized as an early symptomatic stage of AD. Dyadic cognitive report, including subjective cognitive complaints (SCC) from a participant and an informant/study partner who knows the participant well, represents an accurate, reliable, and efficient source of data for assessing risk. However, the separate and combined contributions of self‐ and study partner report, and the dynamic relationship between the two, remains unclear. The Subjective Cognitive Decline Professional Interest Area within the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment convened a working group focused on dyadic patterns of subjective report. Group members identified aspects of dyadic‐report information important to the AD research field, gaps in knowledge, and recommendations. By reviewing existing data on this topic, we found evidence that dyadic measures are associated with objective measures of cognition and provide unique information in preclinical and prodromal AD about disease stage and progression and AD biomarker status. External factors including dyad (participant–study partner pair) relationship and sociocultural factors contribute to these associations. We recommend greater dyad report use in research settings to identify AD risk. Priority areas for future research include (1) elucidation of the contributions of demographic and sociocultural factors, dyad type, and dyad relationship to dyad report; (2) exploration of agreement and discordance between self‐ and study partner report across the AD syndromic and disease continuum; (3) identification of domains (e.g., memory, executive function, neuropsychiatric) that predict AD risk outcomes and differentiate cognitive impairment due to AD from other impairment; (4) development of best practices for study partner engagement; (5) exploration of study partner report as AD clinical trial endpoints; (6) continued development, validation, and optimization, of study partner report instruments tailored to the goals of the research and population.

The oncogenic expression or mutation of tumor suppressors drives metabolic alteration, causing cancer cells to utilize diverse nutrients. Lactate is a known substrate for cancer cells, yet the regulatory mechanisms of lactate catabolism are limited. Here, we show that a heme-binding transcription factor, BACH1, negatively regulates lactate catabolic pathways in triple-negative breast cancer (TNBC) cells. BACH1 suppresses the transcriptional expression of monocarboxylate transporter 1 (MCT1) and lactate dehydrogenase B, inhibiting lactate-mediated mitochondrial metabolism. In our studies, the depletion of BACH1 either genetically or pharmacologically increased the lactate use of TNBC cells, increasing their sensitivity to MCT1 inhibition. Thus, small inhibitory molecules (SR13800 and AZD3965) blocking MCT1 better suppressed the growth of BACH1-depleted TNBC cells than did the controls. Particularly, hemin treatment degrading BACH1 proteins induced lactate catabolism in TNBC cells, generating synthetic lethality with MCT1 inhibition. Our data indicates that targeting BACH1 generates metabolic vulnerability and increases sensitivity to lactate transporter inhibition, suggesting a potential novel combination therapy for cancer patients with TNBC.

Abstract There is a growing interest in understanding how amyloid β (Aβ) accumulation in preclinical Alzheimer's disease relates to brain morphometric measures and cognition. Existing investigations in this area have been primarily conducted in older cognitively normal (CN) individuals. Therefore, not much is known about the associations between Aβ burden, cortical thickness, and cognition in midlife. We examined this question in 109, CN, late to middle‐aged adults (mean age = 60.72 ± 5.65 years) from the Wisconsin Registry for Alzheimer's Prevention. They underwent Pittsburgh Compound B (PiB) and anatomical magnetic resonance (MR) imaging, and a comprehensive cognitive examination. Blinded visual rating of the PiB scans was used to classify the participants as Aβ+ or Aβ−. Cortical thickness measurements were derived from the MR images. The Aβ+ group exhibited significant thinning of the entorhinal cortex and accelerated age‐associated thinning of the parahippocampal gyrus compared with the Aβ− group. The Aβ+ group also had numerically lower, but nonsignificant, test scores on all cognitive measures, and significantly faster age‐associated cognitive decline on measures of Speed & Flexibility, Verbal Ability, and Visuospatial Ability. Our findings suggest that early Aβ aggregation is associated with deleterious changes in brain structure and cognitive function, even in midlife, and that the temporal lag between Aβ deposition and the inception of neurodegenerative/cognitive changes might be narrower than currently thought.

Introduction: Little is still known about the effects of risk factors for Alzheimer's disease (AD) on white matter microstructure in cognitively healthy adults. The purpose of this cross-sectional study was to assess the effect of two well-known risk factors for AD, parental family history and APOE4 genotype. Methods: This study included 343 participants from the Wisconsin Registry for Alzheimer's Prevention, who underwent diffusion tensor imaging (DTI). A region of interest analysis was performed on fractional anisotropy maps, in addition to mean, radial, and axial diffusivity maps, aligned to a common template space using a diffeomorphic, tensor-based registration method. The analysis focused on brain regions known to be affected in AD including the corpus callosum, superior longitudinal fasciculus, fornix, cingulum, and uncinate fasciculus. Analyses assessed the impact of APOE4, parental family history of AD, age, and sex on white matter microstructure in late middle-aged participants (aged 47–76 years). Results: Both APOE4 and parental family history were associated with microstructural white matter differences. Participants with parental family history of AD had higher FA in the genu of the corpus callosum and the superior longitudinal fasciculus. We observed an interaction between family history and APOE4, where participants who were family history positive but APOE4 negative had lower axial diffusivity in the uncinate fasciculus, and participants who were both family history positive and APOE4 positive had higher axial diffusivity in this region. We also observed an interaction between APOE4 and age, whereby older participants (≥65 years of age) who were APOE4 carriers, had higher MD in the superior longitudinal fasciculus and in the portion of the cingulum bundle running adjacent to the cingulate cortex, compared to non-carriers. Older participants who were APOE4 carriers also showed higher radial diffusivity in the genu compared to non-carriers. Across all participants, age had an effect on FA, MD, and axial and radial diffusivities. Sex differences were observed in FA and radial diffusivity. Conclusion: APOE4 genotype, parental family history of AD, age, and sex are all associated with microstructural white matter differences in late middle-aged adults. In participants at risk for AD, alterations in diffusion characteristics—both expected and unexpected—may represent cellular changes occurring at the earliest disease stages, but further work is needed. Higher mean, radial, and axial diffusivities were observed in participants who are more likely to be experiencing later stage preclinical pathology, including participants who were both older and carried APOE4, or who were positive for both APOE4 and parental family history of AD.

Background: The immune response in Alzheimer's disease (AD) involves activation of microglia which may remove amyloid-β (Aβ). However, overproduction of inflammatory compounds may exacerbate neural damage in AD. AD pathology accumulates years before diagnosis, yet the extent to which neuroinflammation is involved in the earliest disease stages is unknown.Objective: To determine whether neuroinflammation exacerbates neural damage in preclinical AD.Methods: We utilized cerebrospinal fluid (CSF) and magnetic resonance imaging collected in 192 asymptomatic late-middle-aged adults (mean age = 60.98 years). Neuroinflammatory markers chitinase-3-like protein 1 (YKL-40) and monocyte chemoattractant protein-1 (MCP-1) in CSF were utilized as markers of neuroinflammation. Neural cell damage was assessed using CSF neurofilament light chain protein (NFL), CSF total tau (T-Tau), and neural microstructure assessed with diffusion tensor imaging (DTI). With regard to AD pathology, CSF Aβ42 and tau phosphorylated at threonine 181 (P-Tau181) were used as markers of amyloid and tau pathology, respectively. We hypothesized that higher YKL-40 and MCP-1 in the presence of AD pathology would be associated with higher NFL, T-Tau, and altered microstructure on DTI.Results: Neuroinflammation was associated with markers of neural damage. Higher CSF YKL-40 was associated with both higher CSF NFL and T-Tau. Inflammation interacted with AD pathology, such that greater MCP-1 and lower Aβ42 was associated with altered microstructure in bilateral frontal and right temporal lobe and that greater MCP-1 and greater P-Tau181 was associated with altered microstructure in precuneus.Conclusion: Inflammation may play a role in neural damage in preclinical AD. [ABSTRACT FROM AUTHOR]

Abstract Introduction Ensuring adequate and equitable distribution of resources to support persons living with dementia relies on understanding the burden and distribution of dementia in a population. Our goal was to develop an approach to estimate dementia prevalence at the local level in the United States using publicly available data. Methods Our approach combines publicly available data on dementia prevalence and demographic data from the US Census to estimate dementia prevalence. We illustrate this approach by estimating dementia prevalence in persons aged 65 and older in Philadelphia, PA; Chicago, IL; and Atlanta, GA. Results Overall, we estimate the prevalence of dementia among those 65 and older to be 11.9% in Philadelphia, 11.8% Chicago, and 12.3% in Atlanta. Estimates across Philadelphia localities vary from 9.3% to 15.9%. Discussion Our approach provides a cost‐effective method to generate estimates of dementia prevalence at the local level. HIGHLIGHTS Brain health needs assessments require understanding of local dementia prevalence. Our approach can be used to estimate dementia prevalence in individual communities. This information can inform decisions about distribution of resources.

Abstract Background Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent’s tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. Methods We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. Results A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. Conclusions A comprehensive evaluation of the psychometric quality and soundness of PRO assessment measures should incorporate the study of ERS as a potential nuisance dimension affecting the accuracy and validity of scores and the impact of PRO data in clinical research and decision making.

Abstract Background Subjective memory complaints (SMCs) represent an individual's perception of subtle changes in memory in the absence of objective impairment in memory. However, it is not fully known whether persons with SMCs harbor brain alterations related to Alzheimer's disease (AD) or whether they indeed demonstrate poorer cognitive performance. Methods The participants were 261 middle‐age adults (mean age 54.30 years) enrolled in the Wisconsin Registry for Alzheimer's Prevention, a registry of cognitively normal adults at risk of AD. They answered a question pertaining to subjective memory, completed a comprehensive neuropsychological examination, and subsequently underwent a volumetric magnetic resonance imaging scan. Cortical thickness measurements were derived from 10 a priori regions of interest involved in AD. Analyses of covariance were conducted to investigate the group differences in cortical thickness and neuropsychological measures. Results Compared with individuals without SMCs, those with SMCs had significant cortical thinning in the entorhinal, fusiform, posterior cingulate, and inferior parietal cortices and significantly reduced amygdala volume. Similarly, those with SMCs had significantly lower test scores on measures of Immediate Memory, Verbal Learning & Memory, and Verbal Ability. Additional adjustment for depressive symptoms (which differed between the groups) attenuated only the findings for the entorhinal cortex (P = .061) and Verbal Ability (P = .076). Conclusion At‐risk, cognitively healthy individuals with SMCs exhibit cortical thinning in brain regions affected by AD and poorer performance on objective memory tests. These findings suggest that, in some individuals, SMCs might represent the earliest stages of AD.

Some cognitively healthy individuals develop brain amyloid accumulation, suggestive of incipient Alzheimer's disease (AD), but the effect of amyloid on other potentially informative imaging modalities, such as Diffusion Tensor Imaging (DTI), in characterizing brain changes in preclinical AD requires further exploration. In this study, a sample (N = 139, mean age 60.6, range 46 to 71) from the Wisconsin Registry for Alzheimer's Prevention (WRAP), a cohort enriched for AD risk factors, was recruited for a multimodal imaging investigation that included DTI and [C-11]Pittsburgh Compound B (PiB) positron emission tomography (PET). Participants were grouped as amyloid positive (Aβ+), amyloid indeterminate (Aβi), or amyloid negative (Aβ−) based on the amount and pattern of amyloid deposition. Regional voxel-wise analyses of four DTI metrics, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), and radial diffusivity (Dr), were performed based on amyloid grouping. Three regions of interest (ROIs), the cingulum adjacent to the corpus callosum, hippocampal cingulum, and lateral fornix, were selected based on their involvement in the early stages of AD. Voxel-wise analysis revealed higher FA among Aβ+ compared to Aβ− in all three ROIs and in Aβi compared to Aβ− in the cingulum adjacent to the corpus callosum. Follow-up exploratory whole-brain analyses were consistent with the ROI findings, revealing multiple regions where higher FA was associated with greater amyloid. Lower fronto-lateral gray matter MD was associated with higher amyloid burden. Further investigation showed a negative correlation between MD and PiB signal, suggesting that Aβ accumulation impairs diffusion. Interestingly, these findings in a largely presymptomatic sample are in contradistinction to relationships reported in the literature in symptomatic disease stages of Mild Cognitive Impairment and AD, which usually show higher MD and lower FA. Together with analyses showing that cognitive function in these participants is not associated with any of the four DTI metrics, the present results suggest an early relationship between PiB and DTI, which may be a meaningful indicator of the initiating or compensatory mechanisms of AD prior to cognitive decline.

BACKGROUND:Menopausal hormone therapy (MHT) reportedly increases the risk of cognitive decline in women over age 65 y. It is unknown whether similar risks exist for recently postmenopausal women, and whether MHT affects mood in younger women. The ancillary Cognitive and Affective Study (KEEPS-Cog) of the Kronos Early Estrogen Prevention Study (KEEPS) examined the effects of up to 4 y of MHT on cognition and mood in recently postmenopausal women. METHODS AND FINDINGS:KEEPS, a randomized, double-blinded, placebo-controlled clinical trial, was conducted at nine US academic centers. Of the 727 women enrolled in KEEPS, 693 (95.3%) participated in the ancillary KEEPS-Cog, with 220 women randomized to receive 4 y of 0.45 mg/d oral conjugated equine estrogens (o-CEE) plus 200 mg/d micronized progesterone (m-P) for the first 12 d of each month, 211 women randomized to receive 50 μg/d transdermal estradiol (t-E2) plus 200 mg/d m-P for the first 12 d of each month, and 262 women randomized to receive placebo pills and patches. Primary outcomes included the Modified Mini-Mental State examination; four cognitive factors: verbal learning/memory, auditory attention/working memory, visual attention/executive function, and speeded language/mental flexibility; and a mood measure, the Profile of Mood States (POMS). MHT effects were analyzed using linear mixed-effects (LME) models, which make full use of all available data from each participant, including those with missing data. Data from those with and without full data were compared to assess for potential biases resulting from missing observations. For statistically significant results, we calculated effect sizes (ESs) to evaluate the magnitude of changes. On average, participants were 52.6 y old, and 1.4 y past their last menstrual period. By month 48, 169 (24.4%) and 158 (22.8%) of the 693 women who consented for ancillary KEEPS-Cog were lost to follow-up for cognitive assessment (3MS and cognitive factors) and mood evaluations (POMS), respectively. However, because LME models make full use all available data, including data from women with missing data, 95.5% of participants were included in the final analysis (n = 662 in cognitive analyses, and n = 661 in mood analyses). To be included in analyses, women must have provided baseline data, and data from at least one post-baseline visit. The mean length of follow-up was 2.85 y (standard deviation [SD] = 0.49) for cognitive outcomes and 2.76 (SD = 0.57) for mood outcomes. No treatment-related benefits were found on cognitive outcomes. For mood, model estimates indicated that women treated with o-CEE showed improvements in depression and anxiety symptoms over the 48 mo of treatment, compared to women on placebo. The model estimate for the depression subscale was -5.36 × 10(-2) (95% CI, -8.27 × 10(-2) to -2.44 × 10(-2); ES = 0.49, p < 0.001) and for the anxiety subscale was -3.01 × 10(-2) (95% CI, -5.09 × 10(-2) to -9.34 × 10(-3); ES = 0.26, p < 0.001). Mood outcomes for women randomized to t-E2 were similar to those for women on placebo. Importantly, the KEEPS-Cog results cannot be extrapolated to treatment longer than 4 y. CONCLUSIONS:The KEEPS-Cog findings suggest that for recently postmenopausal women, MHT did not alter cognition as hypothesized. However, beneficial mood effects with small to medium ESs were noted with 4 y of o-CEE, but not with 4 y of t-E2. The generalizability of these findings is limited to recently postmenopausal women with low cardiovascular risk profiles. TRIAL REGISTRATION:ClinicalTrials.gov NCT00154180 and NCT00623311.

ObjectivesWhile global measures of cardiovascular (CV) risk are used to guide prevention and treatment decisions, these estimates fail to account for the considerable interindividual variability in pre-clinical risk status. This study investigated heterogeneity in CV risk factor profiles and its association with demographic, genetic, and cognitive variables.MethodsA latent profile analysis was applied to data from 727 recently postmenopausal women enrolled in the Kronos Early Estrogen Prevention Study (KEEPS). Women were cognitively healthy, within three years of their last menstrual period, and free of current or past CV disease. Education level, apolipoprotein E ε4 allele (APOE4), ethnicity, and age were modeled as predictors of latent class membership. The association between class membership, characterizing CV risk profiles, and performance on five cognitive factors was examined. A supervised random forest algorithm with a 10-fold cross-validation estimator was used to test accuracy of CV risk classification.ResultsThe best-fitting model generated two distinct phenotypic classes of CV risk 62% of women were "low-risk" and 38% "high-risk". Women classified as low-risk outperformed high-risk women on language and mental flexibility tasks (p = 0.008) and a global measure of cognition (p = 0.029). Women with a college degree or above were more likely to be in the low-risk class (OR = 1.595, p = 0.044). Older age and a Hispanic ethnicity increased the probability of being at high-risk (OR = 1.140, p = 0.002; OR = 2.622, p = 0.012; respectively). The prevalence rate of APOE-ε4 was higher in the high-risk class compared with rates in the low-risk class.ConclusionAmong recently menopausal women, significant heterogeneity in CV risk is associated with education level, age, ethnicity, and genetic indicators. The model-based latent classes were also associated with cognitive function. These differences may point to phenotypes for CV disease risk. Evaluating the evolution of phenotypes could in turn clarify preclinical disease, and screening and preventive strategies. ClinicalTrials.gov NCT00154180.

Positive affect is associated with a number of health benefits; however, few studies have examined the relationship between positive affect and cerebral glucose metabolism, a key energy source for neuronal function and a possible index of brain health. We sought to determine if positive affect was associated with cerebral glucose metabolism in late middle-aged adults (n = 133). Participants completed the positive affect subscale of the Center for Epidemiological Studies Depression Scale at two time points over a two-year period and underwent 18F-fluorodeoxyglucose-positron emission tomography scanning. After controlling for age, sex, perceived health status, depressive symptoms, anti-depressant use, family history of Alzheimer's disease, APOE ε4 status and interval between visits, positive affect was associated with greater cerebral glucose metabolism across para-/limbic, frontal, temporal and parietal regions. Our findings provide evidence that positive affect in late midlife is associated with greater brain health in regions involved in affective processing and also known to be susceptible to early neuropathological processes. The current findings may have implications for interventions aimed at increasing positive affect to attenuate early neuropathological changes in at-risk individuals., (Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.)