Cognitive Impairment after Lacunar Stroke and the Risk of Recurrent Stroke and Death.

INTRODUCTION: Patients with poststroke cognitive impairment appear to be at higher risk of recurrent stroke and death. However, whether cognitive impairment after lacunar stroke is associated with recurrent stroke and death remains unclear. We assessed whether global or domain-specific cognitive impairment after lacunar stroke is associated with recurrent stroke and death. METHODS: We considered patients from the Secondary Prevention of Small Subcortical Strokes (SPS3) trial with a baseline cognitive exam administered in English by certified SPS3 personnel, 14-180 days after qualifying lacunar stroke. We considered a baseline score of ≤86 on the Cognitive Assessment Screening Instrument to indicate global cognitive impairment, <10 on the Clock Drawing on Command test to indicate executive function impairment, and domain-specific summary scores in the lowest quartile to indicate memory and nonmemory impairment. We used Cox proportional hazards models to estimate the association between poststroke cognitive impairment and subsequent risk of recurrent stroke and death. RESULTS: The study included 1,528 participants with a median enrollment time of 62 days after qualifying stroke. During a mean follow-up of 3.9 years, 11.4% of participants had recurrent stroke and 8.2% died. In the fully adjusted models, memory impairment was independently associated with an increased risk of recurrent stroke (hazard ratio, 1.48; 95% confidence interval [95% CI]: 1.04-2.09) and death (hazard ratio, 1.87; 95% CI: 1.25-2.79). Global impairment (hazard ratio, 1.66; 95% CI: 1.06-2.59) and nonmemory impairment (hazard ratio, 1.74; 95% CI: 1.14-2.67) were associated with an increased risk of death. DISCUSSION/CONCLUSION: After lacunar stroke, memory impairment was an independent predictor of recurrent stroke and death, while global and nonmemory impairment were associated with death. Cognitive screening in lacunar stroke may help identify populations at higher risk of recurrent stroke and death.

Comparison of Education and Episodic Memory as Modifiers of Brain Atrophy Effects on Cognitive Decline: Implications for Measuring Cognitive Reserve.

OBJECTIVE: This study compared the level of education and tests from multiple cognitive domains as proxies for cognitive reserve. METHOD: The participants were educationally, ethnically, and cognitively diverse older adults enrolled in a longitudinal aging study. We examined independent and interactive effects of education, baseline cognitive scores, and MRI measures of cortical gray matter change on longitudinal cognitive change. RESULTS: Baseline episodic memory was related to cognitive decline independent of brain and demographic variables and moderated (weakened) the impact of gray matter change. Education moderated (strengthened) the gray matter change effect. Non-memory cognitive measures did not incrementally explain cognitive decline or moderate gray matter change effects. CONCLUSIONS: Episodic memory showed strong construct validity as a measure of cognitive reserve. Education effects on cognitive decline were dependent upon the rate of atrophy, indicating education effectively measures cognitive reserve only when atrophy rate is low. Results indicate that episodic memory has clinical utility as a predictor of future cognitive decline and better represents the neural basis of cognitive reserve than other cognitive abilities or static proxies like education.

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

BACKGROUND: 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 trans-aortic constriction (TAC) in rats. We hypothesized that chronic activation of cardiac cholinergic neurons would also reduce TAC-induced derangement of cardiac electrical activity. METHODS: 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 weeks of TAC with or without 12 weeks of daily chemogenetic treatment. Action potential duration (APD60) and conduction velocity (CV) maps were analyzed for regional rate adaptation to dynamic pacing. RESULTS: At lower pacing rates, untreated TAC induced elevated LV epicardial APD60. Fitted APD60 steady state (APDss) was reduced in treated TAC hearts. At higher pacing rates, treatment heterogeneously reduced APD60 compared to untreated TAC hearts. Variance of conduction loss was reduced in treated hearts compared to untreated hearts during fast pacing. However, CV was markedly reduced in both treated and untreated TAC hearts throughout dynamic pacing. At 150msec pacing cycle length, APD60 v. diastolic interval (DI) dispersion was reduced in treated hearts compared to untreated hearts. CONCLUSIONS: Chronic activation of cardiac cholinergic neurons improved electrophysiological adaptation to increases in pacing rate during development of TAC-induced heart failure. This provides insight into the electrophysiological benefits of cholinergic stimulation as a treatment for heart failure patients.

Do nurse practitioner-led medical homes differ from physician-led medical homes?

BACKGROUND/PURPOSE: The patient-centered medical home (PCMH) is an enhanced model of primary care. This study examined to what extent nurse practitioner (NP)-led PCMHs differed from traditional physician-led PCMHs. METHODS: We tested for differences between 391 NP-led PCMHs and 11,479 physician-led PCMHs, as well as across two distinct clusters identified by the Two-Step cluster analysis procedure using a sample of 136 practices. FINDINGS: NP-led PCMHs were more likely to serve vulnerable populations in rural and underserved areas than physician-led PCMHs. NP-led PCMHs tended to be more responsive to population health needs in the areas during the recognition process, while physician-led PCMHs emphasized practice improvements through enhanced access to care and management of patient information data. DISCUSSION: The findings suggest possible differences in capabilities, priorities and needs of the population served across practices. This is an important guide as policymakers track the adoption of PCMHs.

Impact of menopausal hormone formulations on pituitary-ovarian regulatory feedback.

Changes in pituitary-ovarian hormones across the menopausal transition have multiple physiological consequences. However, little is known about how the major types of postmenopausal hormone therapy (HT) affect pituitary-ovarian hormonal relationships. This study evaluated these relationships in recently menopausal women (52.45 ± 2.49 yr of age) in the Kronos Early Estrogen Prevention Study (KEEPS) who were compliant to randomized, double-blinded treatment with oral conjugated equine estrogen (o-CEE; n = 109), transdermal 17ß-estradiol (t-E2; n = 107), or placebo (n = 146). Androstenedione, testosterone, 17ß-estradiol, estrone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were measured in serum before (baseline) and 48 mo after randomization to treatment. Descriptive summaries of hormone levels were performed, and multiple regression analyses were used to examine the effects of o-CEE, t-E2, and placebo on these hormone levels at 48 mo, adjusting for baseline levels. A network analysis examined the covariance of changes in hormone levels over the 48 mo within treatment groups. As expected, at 48 mo of treatment, hormone levels differed between women in the two active treatment groups compared with placebo, and network analysis indicated stronger relationships among hormone levels in the t-E2 and o-CEE groups compared with placebo. Associations among testosterone, 17ß-estradiol, FSH, and LH differed between the o-CEE group compared with t-E2 and placebo groups. Thus, two common HT regimens differentially alter pituitary-ovarian hormone levels, altering feedback cycles and interhormonal associations in recently menopausal women. These interactions provide the basis for future studies investigating the impact of hormonal modulation of aging, including cognitive decline in women.

Longitudinal Assessment of Self- and Informant-Subjective Cognitive Complaints in a Sample of Healthy Late-Middle Aged Adults Enriched with a Family History of Alzheimer's Disease.

OBJECTIVES: The purpose of this study was to investigate the longitudinal trajectory of self- and informant-subjective cognitive complaints (SCC), and to determine if SCC predict longitudinal changes in objective measures (OM) of cognitive function. METHODS: The study included healthy and cognitively normal late middle-aged adults enriched with a family history of AD who were evaluated at up to three visits over a 4-year period. At each visit (Visit 1-3), self- and informant-SCC and OM were evaluated. Linear mixed models were used to determine if the longitudinal rate of change of self- and informant-SCC were associated with demographic variables, depressive symptoms, family history (FH), and apolipoprotein epsilon 4 (APOE4) status. The same modeling approach was used to examine the effect of Visit 1 SCC on longitudinal cognitive change after controlling for the same variables. RESULTS: At Visit 1, more self-SCC were associated with fewer years of education and more depressive symptoms. SCC were also associated with poorer performance on cognitive measures, such that more self-SCC at Visit 1 were associated with poorer performance on memory and executive functioning measures at Visit 1, while more informant-SCC were associated with faster rate of longitudinal decline on a measure of episodic learning and memory. FH and APOE4 status were not associated with SCC. DISCUSSION: Self- and informant-SCC showed an association with OM, albeit over different time frames in our late middle-aged sample. Additional longitudinal follow-up will likely assist in further clarifying these relationships as our sample ages and more pronounced cognitive changes eventually emerge. (JINS, 2017, 23, 617-626).

Family history and TOMM40 '523 interactive associations with memory in middle-aged and Alzheimer's disease cohorts.

INTRODUCTION: Family history (FH) of Alzheimer's disease (AD) affects mitochondrial function and may modulate effects of translocase of the outer mitochondrial membrane 40 kDa (TOMM40) rs10524523 ('523) poly-T length on memory decline. METHODS: For 912 nonapolipoprotein ε4 middle-aged adults and 365 aged adults across the AD spectrum, linear mixed models gauged FH and TOMM40 '523 interactions on memory and global cognition between baseline and up to 10 years later. A cerebrospinal fluid mitochondrial function biomarker was also assessed. RESULTS: For FH negative participants, gene-dose preservation of memory and global cognition was seen for "very long" versus "short" carriers. For FH positive, an opposite gene-dose decline was seen for very long versus short carriers. Maternal FH was a stronger predictor in aged, but not middle-aged, participants. Similar gene-dose effects were seen for the mitochondrial biomarker aspartate aminotransferase. DISCUSSION: These results may clarify conflicting findings on TOMM40 poly-T length and AD-related decline.

Common Sense Model Factors Affecting African Americans' Willingness to Consult a Healthcare Provider Regarding Symptoms of Mild Cognitive Impairment.

OBJECTIVE: Although at increased risk for developing dementia compared with white patients, older African Americans are diagnosed later in the course of dementia. Using the common sense model (CSM) of illness perception, we sought to clarify processes promoting timely diagnosis of mild cognitive impairment (MCI) for African American patients. DESIGN, SETTING, PARTICIPANTS: In-person, cross-sectional survey data were obtained from 187 African American (mean age: 60.44 years). Data were collected at social and health-focused community events in three southern Wisconsin cities. MEASUREMENTS: The survey represented a compilation of published surveys querying CSM constructs focused on early detection of memory disorders, and willingness to discuss concerns about memory loss with healthcare providers. Derived CSM variables measuring perceived causes, consequences, and controllability of MCI were included in a structural equation model predicting the primary outcome: Willingness to discuss symptoms of MCI with a provider. RESULTS: Two CSM factors influenced willingness to discuss symptoms of MCI with providers: Anticipation of beneficial consequences and perception of low harm associated with an MCI diagnosis predicted participants' willingness to discuss concerns about cognitive changes. No association was found between perceived controllability and causes of MCI, and willingness to discuss symptoms with providers. CONCLUSIONS: These data suggest that allaying concerns about the deleterious effects of a diagnosis, and raising awareness of potential benefits, couldinfluence an African American patient's willingness to discuss symptoms of MCI with a provider. The findings offer guidance to designers of culturally congruent MCI education materials, and healthcare providers caring for older African Americans. .

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

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.

The mediational effects of FDG hypometabolism on the association between cerebrospinal fluid biomarkers and neurocognitive function.

Positive cerebrospinal fluid (CSF) biomarkers of tau and amyloid beta42 suggest possible active underlying Alzheimer's disease (AD) including neurometabolic dysfunction and neurodegeneration leading to eventual cognitive decline. But the temporal relationship between CSF, imaging markers of neural function, and cognition has not been described. Using a statistical mediation model, we examined relationships between cerebrospinal fluid (CSF) analytes (hyperphosphorylated tau (p-Tau(181p)), ß-amyloid peptides 1-42 (Aß(1-42)), total tau (t-Tau), and their ratios); change in cognitive function; and change in [18F]fluorodeoxyglucose (FDG) uptake using positron emission tomography (PET). We hypothesized that a) abnormal CSF protein values at baseline, result in cognitive declines by decreasing neuronal glucose metabolism across time, and b) the role of altered glucose metabolism in the assumed causal chain varies by brain region and the nature of CSF protein alteration. Data from 412 individuals participating in Alzheimer's Disease Neuroimaging (ADNI) cohort studies were included in analyses. At baseline, individuals were cognitively normal (N = 82), or impaired: 241 with mild cognitive impairment, and 89 with Alzheimer's disease. A parallel-process latent growth curve model was used to test mediational effects of changes in regional FDG-PET uptake over time in relation to baseline CSF biomarkers and changes in cognition, measured with the 13-item Alzheimer Disease's Assessment Scale-cognitive subscale (ADAS-Cog). Findings suggested a causal sequence of events; specifically, FDG hypometabolism acted as a mediator between antecedent CSF biomarker alterations and subsequent cognitive impairment. Higher baseline concentrations of t-Tau, and p-Tau(181p) were more predictive of decline in cerebral glucose metabolism than lower baseline concentrations of Aß(1-42). FDG-PET changes appeared to mediate t-Tau or t-Tau/Aß(1-42)-associated cognitive change across all brain regions examined. Significant direct effects of alterations in Aß(1-42) levels on hypometabolism were observed in a single brain region: middle/inferior temporal gyrus. Results support a temporal framework model in which reduced CSF amyloid-related biomarkers occur earlier in the pathogenic pathway, ultimately leading to detrimental cognitive effects. Also consistent with this temporal framework model, baseline markers of neurofibrillary degeneration predicted changes in brain glucose metabolism in turn causing longitudinal cognitive changes, suggesting that tau-related burden precedes neurometabolic dysfunction. While intriguing, the hypothesized mediational relationships require further validation.

Effects of Hormone Therapy on Cognition and Mood in Recently Postmenopausal Women: Findings from the Randomized, Controlled KEEPS-Cognitive and Affective Study.

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.

Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer's disease.

Progressive and insidious cognitive decline that interferes with daily life is the defining characteristic of Alzheimer's disease (AD). Epidemiological studies have found that the pathological process of AD begins years before a clinical diagnosis is made and can be highly variable within a given population. Characterizing cognitive decline in the preclinical phase of AD is critical for the development of early intervention strategies when disease-modifying therapies may be most effective. In the last decade, there has been an increased interest in the application of change-point models to longitudinal cognitive outcomes prior to and after diagnosis. Most of the proposed statistical methodology for describing decline relies upon distributional assumptions that may not hold. In this article, we introduce a quantile regression with a change-point model for longitudinal data of cognitive function in persons bound to develop AD. A change-point in our model reflects the transition from the cognitive decline due to normal aging to the accelerated decline due to disease progression. Quantile regression avoids common distributional assumptions on cognitive outcomes and allows the covariate effects and the change-point to vary for different quantiles of the response. We provided an approach for estimating the model parameters, including the change-point, and presented inferential procedures based on the asymptotic properties of the estimators. A simulation study showed that the estimation and inferential procedures perform reasonably well in finite samples. The practical use of our model was illustrated by an application to longitudinal episodic memory outcomes from two cohort studies of aging and AD.

Cerebral blood flow is diminished in asymptomatic middle-aged adults with maternal history of Alzheimer's disease.

Cerebral blood flow (CBF) provides an indication of the metabolic status of the cortex and may have utility in elucidating preclinical brain changes in persons at risk for Alzheimer's disease (AD) and related diseases. In this study, we investigated CBF in 327 well-characterized adults including patients with AD (n = 28), patients with amnestic mild cognitive impairment (aMCI, n = 23), older cognitively normal (OCN, n = 24) adults, and asymptomatic middle-aged adults (n = 252) with and without a family history (FH) of AD. Compared with the asymptomatic cohort, AD patients displayed significant hypoperfusion in the precuneus, posterior cingulate, lateral parietal cortex, and the hippocampal region. Patients with aMCI exhibited a similar but less marked pattern of hypoperfusion. Perfusion deficits within the OCN adults were primarily localized to the inferior parietal lobules. Asymptomatic participants with a maternal FH of AD showed hypoperfusion in hippocampal and parietofrontal regions compared with those without a FH of AD or those with only a paternal FH of AD. These observations persisted when gray matter volume was included as a voxel-wise covariate. Our findings suggest that having a mother with AD might confer a particular risk for AD-related cerebral hypoperfusion in midlife. In addition, they provide further support for the potential utility of arterial spin labeling for the measurement of AD-related neurometabolic dysfunction, particularly in situations where [18F]fluorodeoxyglucose imaging is infeasible or clinically contraindicated.

Imaging-based enrichment criteria using deep learning algorithms for efficient clinical trials in mild cognitive impairment.

The mild cognitive impairment (MCI) stage of Alzheimer's disease (AD) may be optimal for clinical trials to test potential treatments for preventing or delaying decline to dementia. However, MCI is heterogeneous in that not all cases progress to dementia within the time frame of a trial and some may not have underlying AD pathology. Identifying those MCIs who are most likely to decline during a trial and thus most likely to benefit from treatment will improve trial efficiency and power to detect treatment effects. To this end, using multimodal, imaging-derived, inclusion criteria may be especially beneficial. Here, we present a novel multimodal imaging marker that predicts future cognitive and neural decline from [F-18]fluorodeoxyglucose positron emission tomography (PET), amyloid florbetapir PET, and structural magnetic resonance imaging, based on a new deep learning algorithm (randomized denoising autoencoder marker, rDAm). Using ADNI2 MCI data, we show that using rDAm as a trial enrichment criterion reduces the required sample estimates by at least five times compared with the no-enrichment regime and leads to smaller trials with high statistical power, compared with existing methods.

Midlife measurements of white matter microstructure predict subsequent regional white matter atrophy in healthy adults.

OBJECTIVES: Although age-related brain changes are becoming better understood, midlife patterns of change are still in need of characterization, and longitudinal studies are lacking. The aim of this study was to determine if baseline fractional anisotropy (FA), obtained from diffusion tensor imaging (DTI) predicts volume change over a 4-year interval. EXPERIMENTAL DESIGN: Forty-four cognitively healthy middle-age adults underwent baseline DTI and longitudinal T1-weighted magnetic resonance imaging. Tensor-based morphometry methods were used to evaluate volume change over time. FA values were extracted from regions of interest that included the cingulum, entorhinal white matter, and the genu and splenium of the corpus callosum. Baseline FA was used as a predictor variable, whereas gray and white matter atrophy rates as indexed by Tensor-based morphometry were the dependent variables. PRINCIPAL OBSERVATIONS: Over a 4-year period, participants showed significant contraction of white matter, especially in frontal, temporal, and cerebellar regions (P < 0.05, corrected for multiple comparisons). Baseline FA in entorhinal white matter, genu, and splenium was associated with longitudinal rates of atrophy in regions that included the superior longitudinal fasciculus, anterior corona radiata, temporal stem, and white matter of the inferior temporal gyrus (P < 0.001, uncorrected for multiple comparisons). CONCLUSIONS: Brain change with aging is characterized by extensive shrinkage of white matter. Baseline white matter microstructure as indexed by DTI was associated with some of the observed regional volume loss. The findings suggest that both white matter volume loss and microstructural alterations should be considered more prominently in models of aging and neurodegenerative diseases.

Amyloid burden, neuronal function, and cognitive decline in middle-aged adults at risk for Alzheimer's disease.

The relative influence of amyloid burden, neuronal structure and function, and prior cognitive performance on prospective memory decline among asymptomatic late middle-aged individuals at risk for Alzheimer's disease (AD) is currently unknown. We investigated this using longitudinal cognitive data from 122 middle-aged adults (21 "Decliners" and 101 "Stables") enrolled in the Wisconsin Registry for Alzheimer's Prevention who underwent multimodality neuroimaging [11C-Pittsburgh Compound B (PiB), 18F-fluorodeoxyglucose (FDG), and structural/functional magnetic resonance imaging (fMRI)] 5.7 ± 1.4 years (range = 2.9-8.9) after their baseline cognitive assessment. Covariate-adjusted regression analyses revealed that the only imaging measure that significantly distinguished Decliners from Stables (p = .027) was a Neuronal Function composite derived from FDG and fMRI. In contrast, several cognitive measures, especially those that tap episodic memory, significantly distinguished the groups (p's<.05). Complementary receiver operating characteristic curve analyses identified the Brief Visuospatial Memory Test-Revised (BVMT-R) Total (.82 ± .05, p < .001), the BVMT-R Delayed Recall (.73 ± .06, p = .001), and the Reading subtest from the Wide-Range Achievement Test-III (.72 ± .06, p = .002) as the top three measures that best discriminated the groups. These findings suggest that early memory test performance might serve a more clinically pivotal role in forecasting future cognitive course than is currently presumed.

Using concept mapping to identify recruitment and engagement strategies for inclusion of LGBTQIA+ populations in Alzheimer's disease and related dementia research.

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.

Cardiometabolic outcomes in Kronos Early Estrogen Prevention Study continuation: 14-year follow-up of a hormone therapy trial.

OBJECTIVE: This study aimed to determine long-term cardiometabolic effects of hormone therapies initiated within 3 years of onset of menopause after a 14-year follow-up study of participants of the Kronos Early Estrogen Prevention Study (KEEPS). METHODS: KEEPS was a multisite clinical trial that recruited recently menopausal women with good cardiovascular health for randomization to oral conjugated equine estrogens (Premarin, 0.45 mg/d) or transdermal 17ß-estradiol (Climara, 50 µg/d) both with micronized progesterone (Prometrium, 200 mg/d) for 12 d/mo, or placebo pills and patch for 4 years. KEEPS continuation recontacted KEEPS participants 14 years after randomization and 10 years after the completion of the 4-year clinical trial to attend in-person clinic visits. RESULTS: Participants of KEEPS continuation (n = 299 of the 727 KEEPS participants; 41%) had an average age of 67 years (range, 58-73 y). Measurements of systolic and diastolic blood pressures, waist-to-hip ratio, fasting levels of glucose, insulin, lipid profiles, and homeostasis model assessment of insulin resistance were not different among the treatment groups at either KEEPS baseline or at KEEPS continuation visits, or for change between these two visits. The frequency of self-reported diabetes ( P = 0.007) and use of diabetes medications was higher in the placebo than the oral conjugated equine estrogens ( P = 0.045) or transdermal 17ß-estradiol ( P = 0.02) groups, but these differences were not supported by the laboratory measurements of glycemia or insulin resistance. CONCLUSIONS: There was no evidence of cardiovascular and/or metabolic benefits or adverse effects associated with 4 years use of oral or transdermal forms of hormone therapy by recently menopausal women with good cardiovascular health after 10 years.

Expression analysis of BACH1 with clinical variables using the US breast cancer patient cohort.

Background: Studies on functional roles of BACH1 reveal that BACH1 promotes cancer metastasis and regulates metabolic networks for metastatic processes. However, little is known about BACH1 protein expression in breast tumors and its relevance to clinical variables as a biomarker for patients with breast tumors. Methods: Using a tissue microarray (TMA) of breast tumor tissues isolated from a patient cohort (N = 130) expression of BACH1 and its target gene MCT1 (encoded by SLC16A1) were monitored by immunohistochemistry (IHC) assays and scored for further analyses. We examined the association between scores of BACH1 (Allredscoretotal) or MCT1 (Hscoretotal3×2×1x) with clinical variables including: breast cancer subtypes, tissue types, tumor size, patient's racial/ethnic background, and age group. Groups were compared using the Mann-Whitney U test (or the non-parametric Kruskal-Wallis test when appropriate) for numerical data. A proportional odds ordinal logistic model was used to examine multiple covariates. Associations between variables were evaluated with the Spearman's correlation coefficient. Results: BACH1 and MCT1 expression were detected in 90.76% (N = 118/130) and 92.30% (N = 120/130) of patients by IHC, respectively, in our study. After dichotomizing tumor size (small: 3-25 in diameter vs. big: 27-85 mm in diameter), BACH1 expression scores were significantly higher (p = 0.015) in the bigger tumor group (mean [SD]; 4.20 [1.796]) compared with the smaller tumor group (3.920 [1.693]). Of interest, we also observed significantly higher BACH1 scores (p = 0.004) in tumors from Black women (3.971 [1.514]; N = 69) compared with those of White women (3.02 [1.942]; N = 49). Consistent with mRNA expression analysis, BACH1 expression is most abundant in the basal-like tumors among all subtypes, specifically in Black women, whereas MCT1 expression scores are considerably higher in the basal-like tumors regardless of race. In addition, there was a positive association between BACH1 and MCT1 IHC scores in tumors from Black women, although a weak association between them in tumors from White women. In general, we did not detect associations between MCT1 IHC scores and race, tumor size, tissue types, or patient's age. Conclusions: We found strong associations of BACH1 expression with tumor size and the basal-like subtype, respectively. Importantly, BACH1 expresses significantly higher in tumors from Black women than White women, as well as in the basal-like subtype of breast tumors from Black women. Our study suggests that BACH1 expression could serve as a potential race-associated biomarker indicating poor prognosis.

Applications of artificial intelligence in dementia 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.