Characterization of Vascular Disease Risk in Postmenopausal Women and Its Association with Cognitive Performance

Objectives: While 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. Methods: A 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. Results: The 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. Conclusion: Among 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

The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations.

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

Positive Affect Predicts Cerebral Glucose Metabolism in Late Middle-aged Adults.

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

Measurement and control of bias in patient reported outcomes using multidimensional item response theory

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

Cholinergic stimulation improves electrophysiological rate adaptation during pressure overload-induced heart failure in rats.

Left ventricular (LV) electrical maladaptation to increased heart rate in failing myocardium contributes to morbidity and mortality. Recently, cardiac cholinergic neuron activation reduced loss of contractile function resulting from chronic transverse-ascending aortic constriction (TAC) in rats. We hypothesized that chronic activation of cardiac cholinergic neurons would also reduce TAC-induced derangement of cardiac electrical activity. We investigated electrophysiological rate adaptation in TAC rat hearts with and without daily chemogenetic activation of hypothalamic oxytocin neurons for downstream cardiac cholinergic neuron stimulation. Sprague-Dawley rat hearts were excised, perfused, and optically mapped under dynamic pacing after 16 wk of TAC with or without 12 wk of daily chemogenetic treatment. Action potential duration at 60% repolarization (APD ) and conduction velocity (CV) maps were analyzed for regional rate adaptation to dynamic pacing. At lower pacing rates, untreated TAC induced elevated LV epicardial APD . Fitted APD steady state (APD ) was reduced in treated TAC hearts. At higher pacing rates, treatment heterogeneously reduced APD , compared with untreated TAC hearts. Variance of conduction loss was reduced in treated hearts compared with untreated hearts during fast pacing. However, CV was markedly reduced in both treated and untreated TAC hearts throughout dynamic pacing. At 150 ms pacing cycle length, APD versus diastolic interval dispersion was reduced in treated hearts compared with untreated hearts. Chronic activation of cardiac cholinergic neurons improved electrophysiological adaptation to increases in pacing rate during the development of TAC-induced heart failure. This provides insight into the electrophysiological benefits of cholinergic stimulation as a treatment for patients with heart failure. 60 60 60 ss 60 6