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Women with signs and symptoms of ischemia, no obstructive coronary artery disease (CAD) and preserved left ventricular ejection fraction (EF) often have diastolic dysfunction and experience elevated rates of major adverse cardiac events (MACE), including heart failure (HF) hospitalization with preserved ejection fraction (HFpEF). We evaluated the predictive value of inflammatory biomarkers for long-term HF hospitalization and all-cause mortality in these women. We performed a cross-sectional analysis to investigate the relationships between inflammatory biomarkers [serum interleukin-6 (IL-6), C-reactive protein (hs-CRP) and serum amyloid A (SAA)] and median of 6 years follow-up for all-cause mortality and HF hospitalization among women with signs and symptoms of ischemia, non-obstructive CAD and preserved EF. Multivariable Cox regression analysis tested associations between biomarker levels and adverse outcomes. Among 390 women, mean age 56 ± 11 years, median follow up of 6 years, we observed that there is continuous association between IL-6 level and HF hospitalization (adjusted hazard ratio [AHR] 2.5 [1.2-5.0], p = 0.02). In addition, we found significant association between IL-6, SAA levels and all-cause mortality AHR (1.8 [1.1-3.0], p = 0.01) (1.5 [1.0-2.1], p = 0.04), respectively. In women with signs and symptoms of ischemia, non-obstructive CAD and preserved EF, elevated IL-6 predicted HF hospitalization and all-cause mortality, while SAA level was only associated with all-cause mortality. These results suggest that inflammation plays a role in the pathogenesis of development of HFpEF, as well all-cause mortality.

The COVID pandemic initially led to the unprecedented suspension of large numbers of clinical research studies and trials that required in-person study visits, highlighting the need to reevaluate how human participant research projects are conducted. During this time the University of Pittsburgh Clinical and Translational Science Institute (Pitt CTSI) embarked on a multi-year initiative to envision the Research Visit of the Future, which ultimately led to an academia–industry partnership that enables the scalable self-service model using a virtual clinical research platform for clinical studies at a major academic research institution. This model enables the flexible deployment of eConsent, Telehealth (audio/video) calls, synchronous and asynchronous data capture, integrated sensors and wearables, and patient engagement tools, all within a single participant-focused research platform. Academic investigators can configure their studies without custom coding across a wide range of study designs, including hybrid- and fully decentralized clinical trials. Here we present the journey to identifying the technology requirements to enrich data collection, structure of our partnership model, and considerations for crossing the digital divide to enable broader access to clinical research among diverse and under-represented communities.

Periodontal disease and dental caries are two oral conditions that have been associated with atherosclerotic cardiovascular disease (ASCVD). However, it is unclear if one of the key mechanisms involved in this association could be a shared genetic susceptibility. The goal of this study was to explore whether there is an intersection of genetic loci among individuals with comprehensive oral examinations and subclinical ASCVD screenings. We leveraged data from oral and medical examinations obtained from the Dental and Heart Strategies Concentrating on Risk Evaluation (Dental/Heart SCORE) projects. Genome-wide association studies (GWASs) were performed independently in 552 participants (aged 45–75 years). The decayed, missing, or filled teeth index (DMFT) and periodontal disease indices were used to reflect oral conditions; coronary artery calcium scores (CAC) and carotid intima media thickness (CIMT) were analyzed as subclinical ASCVD traits. Single nucleotide variant (SNV) associations with oral and ASCVD traits were found; however, there were only a few regions of suggestive genetic loci overlap between these conditions. The most robust associations found for each phenotype are as follows: DMFT with rs79198416 (near CDC73/KCNT2 ; p  = 7.57E-07), periodontal disease with rs73870587 ( DIPK2A , p  = 7.38E-08); CIMT with rs113152669 ( LRP1B p  = 4.07E-07), and CAC with rs76676138 ( CNTNAP2 ; p  = 2.47E-19). Although genetic associations were identified for each of the phenotypes of interest in the GWASs, there were no regions of shared genetic loci that significantly intersected across phenotypes. Thus, our results suggest that incorporation of environmental, behavioral, microbiome-related factors, and larger sample sizes, are warranted in future studies between oral and cardiovascular health.

We previously reported in a cross-sectional analysis an adverse relationship between weight cycling and HDL-cholesterol but not angiographic obstructive coronary artery disease (CAD) among women undergoing coronary angiography for suspected ischemia in the NHLBI-sponsored Women's Ischemia Syndrome Evaluation (WISE). We now examine the relationship between weight cycling and prospective adverse cardiovascular outcome in this group. 795 women enrolled between 1996-2001 in the WISE undergoing coronary angiography for evaluation of suspected ischemia and followed for a median of 6.0 years (interquartile range = 3.4 years). Adverse outcome was defined as a composite of all-cause death, cardiovascular mortality, non-fatal myocardial infarction, non-fatal stroke, and hospitalization for heart failure. Weight cycling was defined as the intentional loss of at least 10 lbs. (4.5 kgs.) at least three times during the women's lifetime. Women (n = 224) who reported a history of weight cycling were younger; more often white and better educated compared those without this history. At baseline, women with a weight cycling history had lower HDL-C values, higher body mass index, larger waist circumferences and higher values for fasting blood sugar, but no difference in obstructive CAD prevalence or severity. There was an inverse relationship between weight cycling and adverse composite cardiovascular outcome, whereby fewer of women with a history of weight cycling experienced an adverse outcome as compared to non-cyclers (21% vs 29%, respectively, p = 0.03). Despite an adverse association with HDL-cholesterol in women undergoing coronary angiography for suspected ischemia, weight cycling was associated with a lower adverse outcome rate in women with suspected ischemia.

Background Some individuals escape the development of Alzheimer's disease (AD) amyloid and tau pathology suggesting resistance, and not all individuals with these pathologies develop cognitive impairment (CI), suggesting resilience. Social, physical, and cognitive activities may impact resistance and resilience, and this study explores their roles. Method This is a secondary analysis of existing data from the Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study. Multiple activities were collected via the CHAMPS Activities Questionnaire. We grouped them into five domains: social, cognitive, physical, leisure, and household/gardening Total weekly hours were calculated for each domain. We also created combined cognitive‐social activities and combined physical activities. Tau burden was measured using [18F]Flortaucipir (FTP) PET imaging, and amyloid using [11C] Pittsburgh Compound‐B (PiB) PET imaging (Table 1). Cognition was categorized clinically as either unimpaired cognition (CU) or impaired cognition (MCI/dementia). Resilience and resistance profiles were defined as follows: tau‐resilient: tau‐positive, CI‐negative; tau‐resistant: tau‐negative, CI‐negative and amyloid resistant). We used logistic regression to identify activity predictors of tau and amyloid resistance and resilience. Result The study included 152 participants, with demographic characteristics stratified by tau and amyloid status at baseline (Table 2). Throughout the period of follow‐up, greater cognitive activity was significantly associated with tau resilience, while leisure activity was inversely associated with tau resilience (Table 3) Among demographic and health factors, throughout the follow‐up, being White and having a history of cardiovascular disease significantly predicted tau resilience. Hypercholesterolemia was significantly and inversely associated with tau resistance. Increased leisure activity hours were significantly associated with amyloid resistance, while social activity showed an inverse association. Among demographic and health predictors, none were significant, though diabetes was associated with reduced amyloid resistance while education was positively associated (Table 3). Amyloid resilience could not be included due to model non‐convergence secondary to low power. Conclusion Cognitive activities and leisure activities may contribute to tau resilience and amyloid resistance respectively. Promoting a multifaceted approach to activity engagement and cardiovascular risk‐factor control may be key in mitigating the impact of tau and amyloid pathology on cognitive health.

Background Cognitive impairment (CI) in Alzheimer’s disease (AD) is driven, among others in the AT(V)N framework, by tau and amyloid pathology, but individual responses to these pathologies vary widely. Some individuals maintain cognitive function despite significant pathology (resilience), while others remain pathology‐free and cognitively intact (resistance). Emerging evidence suggests that health behavior factors, such as physical activity, cognitive engagement, and social interaction, along with demographic and clinical variables, may play a protective role. Our aim was to identify predictors of resistance and resilience. Method This study included 152 participants from the Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study with longitudinal imaging data and cognitive assessments. Tau burden was measured using [18F]Flortaucipir (FTP) and amyloid burden using [11C]Pittsburgh Compound‐B (PiB) PET imaging. Cognition was categorized clinically as unimpaired or impaired (MCI or dementia) cognition. Resistance and resilience profiles were developed by combining tau, amyloid, and CI status (e.g., tau‐resilient: tau‐positive, CI‐negative; tau‐resistant: tau‐negative, CI‐negative). Stepwise logistic regression with a p‐value cutoff of 0.2 was used to identify predictors of tau and amyloid resistance and resilience. Discrete‐time survival analysis (logistic regression) was used to examine transitions to MCI/dementia. Model performance was assessed using the Area Under the ROC Curve (AUC) for discrimination and calibration plots for the accuracy of predicted probabilities. Calibration plots were generated using local regression (loess) and evaluated for internal validity. Result The demographic, clinical and health behavior characteristics of participants stratified by cognition status at baseline visit are summarized in Table 1. White race, history of CVD, cognitive activity were positively associated with tau resilience, while leisure activity was inversely related. Hypercholesterolemia showed an inverse association with tau resistance. Social activity, leisure activity, household activity, and education were positively associated with amyloid resistance. Within every year of study follow‐up, amyloid positivity and tau‐positivity predicted higher odds of progression to MCI/dementia, while CVD history, White race and cognitive activity predicted reduced lower odds. (See Table 2 & Figure 1 for model discrimination/calibration). Conclusion Tau and amyloid status influence cognitive transitions, with health behavior factors, demographic and CVD history playing key roles in resistance and resilience.

Background Cognitive impairment (CI) in Alzheimer's disease (AD) is driven, among others in the AT(V)N framework, by tau and amyloid pathology, but individual responses to these pathologies vary widely. Some individuals maintain cognitive function despite significant pathology (resilience), while others remain pathology‐free and cognitively intact (resistance). Emerging evidence suggests that health behavior factors, such as physical activity, cognitive engagement, and social interaction, along with demographic and clinical variables, may play a protective role. Our aim was to identify predictors of resistance and resilience. Method This study included 152 participants from the Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study with longitudinal imaging data and cognitive assessments. Tau burden was measured using [18F]Flortaucipir (FTP) and amyloid burden using [11C]Pittsburgh Compound‐B (PiB) PET imaging. Cognition was categorized clinically as unimpaired or impaired (MCI or dementia) cognition. Resistance and resilience profiles were developed by combining tau, amyloid, and CI status (e.g., tau‐resilient: tau‐positive, CI‐negative; tau‐resistant: tau‐negative, CI‐negative). Stepwise logistic regression with a p‐value cutoff of 0.2 was used to identify predictors of tau and amyloid resistance and resilience. Discrete‐time survival analysis (logistic regression) was used to examine transitions to MCI/dementia. Model performance was assessed using the Area Under the ROC Curve (AUC) for discrimination and calibration plots for the accuracy of predicted probabilities. Calibration plots were generated using local regression (loess) and evaluated for internal validity. Result The demographic, clinical and health behavior characteristics of participants stratified by cognition status at baseline visit are summarized in Table 1. White race, history of CVD, cognitive activity were positively associated with tau resilience, while leisure activity was inversely related. Hypercholesterolemia showed an inverse association with tau resistance. Social activity, leisure activity, household activity, and education were positively associated with amyloid resistance. Within every year of study follow‐up, amyloid positivity and tau‐positivity predicted higher odds of progression to MCI/dementia, while CVD history, White race and cognitive activity predicted reduced lower odds. (See Table 2 & Figure 1 for model discrimination/calibration). Conclusion Tau and amyloid status influence cognitive transitions, with health behavior factors, demographic and CVD history playing key roles in resistance and resilience.

BackgroundAlthough women are known to have a relatively higher left ventricular ejection fraction (LVEF) compared with men, a sex-neutral LVEF threshold continues to be used for clinical management. We sought to investigate the relationship among high (>65%), normal (55%–65%) and low (<55%) LVEF and long-term all-cause mortality and major adverse cardiovascular events (MACEs) in women presenting with suspected myocardial ischaemia.MethodsA total of 734 women from the Women’s Ischemia Syndrome Evaluation (WISE) were analysed. LVEF was calculated by invasive left ventriculography. The relationship between baseline characteristics, LVEF and outcomes was evaluated. A multivariable Cox regression model was used to assess the association of LVEF with outcomes, after adjusting for known risk factors.ResultsLow LVEF was associated with higher rates of mortality and MACE compared with normal and high LVEF (p<0.0001). Normal LVEF was associated with higher mortality (p=0.047) and rate of myocardial infarctions (MIs) compared with high LVEF (p=0.03). Low LVEF remained a significant predictor of mortality compared with high LVEF (p=0.013) in a multivariable regression model and normal compared with high LVEF trended towards higher mortality (p=0.16).ConclusionAmong women with suspected ischaemia, women with LVEF above the defined normal threshold (>65%) had lower rates of all-cause mortality and non-fatal MI. Further investigation is needed to determine the optimal LVEF in women.Trial registration numberNCT00000554.

Sleep apnea and obesity are strongly associated, and both increase the risk for coronary artery disease. Several cross-sectional studies have reported discrepant results regarding the role obesity plays in the relation between sleep apnea and coronary artery calcium (CAC), a marker of subclinical coronary disease. The aim of the present study was to investigate the association between sleep apnea and the presence of CAC in a community cohort of middle-aged men and women without preexisting cardiovascular disease, stratified by body mass index (<30 vs ≥30 kg/m2). Participants underwent electron-beam computed tomography to measure CAC and underwent home sleep testing for sleep apnea. The presence of CAC was defined as an Agatston score >0. Sleep apnea was analyzed categorically using the apnea-hypopnea index. The sample was composed of primarily men (61%) and Caucasians (56%), with a mean age of 61 years. The prevalence of CAC was 76%. In participants with body mass indexes <30 kg/m2 (n = 139), apnea-hypopnea index ≥15 (vs <5) was associated with 2.7-fold odds of having CAC, but the effect only approached significance. Conversely, in participants with body mass indexes ≥30 kg/m2, sleep apnea was not independently associated with CAC. In conclusion, sleep apnea is independently associated with early atherosclerotic plaque burden in nonobese patients. •Greater sleep apnea severity is associated with CAC.•This association may exist primarily in nonobese subjects.•Treatment of sleep apnea may be important for attenuating atherosclerotic progression.

To further reduce the burden of cardiovascular disease (CVD) and expand prevention efforts, the American Heart Association (AHA) introduced in 2010 the concept of Ideal Cardiovascular Health (ICH), which includes 7 metrics (smoking status, body mass index, physical activity, diet, total cholesterol, blood pressure, and fasting plasma glucose). Limited data exist on the relation between ICH and long-term CVD risk. The Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study cohort was used to examine the relation between ICH and incident major adverse cardiovascular events (MACE: first occurrence of death, myocardial infarction, stroke, acute ischemic syndrome, or coronary revascularization). The 7 factors of the ICH were scored at study entry on a 0 to 2 scale, resulting in possible range of 0 to 14, with higher scores representing “better” health. Cox regression analyses were used to estimate hazard ratios (HR) of MACE, along with 95% confidence intervals. Over a median follow-up of 12 years, the study population (n = 1,863, 67% women, 42% Black race, mean age 59 years [range 45 to 75]) had 218 MACE. In unadjusted analysis, the ICH score (per 1 unit) was associated with an estimated 12% lower risk of MACE (HR [95% Confidence Interval]: 0.88 [0.82, 0.93]). Adjusting for demographics, education, and quality of life, ICH score was associated with a 10% lower risk of MACE (HR 0.90 [0.84, 0.96]). In a community-based sample of adults, the AHA ICH construct, which includes 7 modifiable CVD risk factors, appears to be a valid measure for predicting long-term risk of MACE.