Statin utilization and cardiovascular outcomes in a real-world primary prevention cohort of older adults.

Background: Statins are a cost-effective therapy for prevention of atherosclerotic cardiovascular disease (ASCVD). Guidelines on statins for primary prevention are unclear for older adults (>75 years). Objective: Investigate statin utility in older adults without ASCVD events, by risk stratifying in a large healthcare network. Methods: We included 8,114 older adults, without CAD, PVD or ischemic stroke. Statin utilization based on ACC/AHA 10-year ASCVD risk calculation, was evaluated in intermediate (7.5%-19.9%) and high-risk patients (≥ 20%); and categorized using low and 'moderate or high' intensity statins with a follow up period of ∼7 years. Cox regression models were used to calculate hazard ratios for incident ASCVD and mortality across risk categories stratified by statin utilization. Data was adjusted for competing risk using Elixhauser Comorbidity Index. Results: Compared with those on moderate or high intensity statins, high-risk older patients not on any statin had a significantly increased risk of MI [HR 1.51 (1.17-1.95); p<0.01], stroke [HR 1.47 (1.14-1.90); p<0.01] and all-cause mortality [HR 1.37 (1.19-1.58); p<0.001] in models adjusted for Elixhauser Comorbidity Index. When comparing the no statin group versus the moderate or high intensity statin group in the intermediate risk cohort, although a trend for increased risk was seen, it did not meet statistical significance thresholds for MI, stroke or all-cause mortality. Conclusion: Lack of statin use was associated with increased cardiovascular events and mortality in high-risk older adults. Given the benefits appreciated, statin use may need to be strongly considered for primary ASCVD prevention among high-risk older adults. Future studies will assess the risk-benefit ratio of statin intervention in older adults.

Apolipoprotein E and Alzheimer's disease pathology in African American older adults.

The apolipoprotein-E4 (APOE*4) and apolipoprotein-E2 (APOE*2) alleles are more common in African American versus non-Hispanic white populations, but relationships of both alleles with Alzheimer's disease (AD) pathology among African American individuals are unclear. We measured APOE allele and ß-amyloid (Aß) and tau using blood samples and positron emission tomography (PET) images, respectively. Individual regression models tested associations of each APOE allele with Aß or tau PET overall, stratified by racialized group, and with a racialized group interaction. We included 358 older adults (42% African American) with Aß PET, 134 (29% African American) of whom had tau PET. APOE*4 was associated with higher Aß in non-Hispanic white (P < 0.0001), but not African American (P = 0.64) participants; racialized group modified the association between APOE*4 and Aß (P < 0.0001). There were no other racialized group differences. These results suggest that the association of APOE*4 and Aß differs between African American and non-Hispanic white populations. Other drivers of AD pathology in African American populations should be identified as potential therapeutic targets.

The Evolve to Next-Gen ACT Network: An evolving open-access, real-world data resource primed for real-world evidence research across the Clinical and Translational Science Award Consortium.

The ACT Network was funded by NIH to provide investigators from across the Clinical and Translational Science Award (CTSA) Consortium the ability to directly query national federated electronic health record (EHR) data for cohort discovery and feasibility assessment of multi-site studies. NIH refunded the program for expanded research application to become "Evolve to Next-Gen ACT" (ENACT). In parallel, the US Food and Drug Administration has been evaluating the use of real-world data (RWD), including EHR data, as sources of real-world evidence (RWE) for its regulatory decisions involving drug and biological products. Using insights from implementation science, six lessons learned from ACT for developing and sustaining RWD/RWE infrastructures and networks across the CTSA Consortium are presented in order to inform ENACT's development from the outset. Lessons include intentional institutional relationship management, end-user engagement, beta-testing, and customer-driven adaptation. The ENACT team is also conducting customer discovery interviews with CTSA hub and investigators using Innovation-Corps@NCATS (I-Corps™) methodology for biomedical entrepreneurs to uncover unmet RWD needs. Possible ENACT value proposition hypotheses are presented by stage of research. Developing evidence about methods for sustaining academically derived data infrastructures and support can advance the science of translation and support our nation's RWD/RWE research capacity.

Cardiovascular Disease and Alzheimer's Disease: The Heart-Brain Axis.

Cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in aging adults across the United States. Prior studies indicate that the presence of atherosclerosis, the pathogenic basis of CVD, is linked with dementias. Alzheimer's disease (AD) and AD-related dementias are a major public health challenge in the United States. Recent studies indicate that ≈3.7 million Americans ≥65 years of age had clinical AD in 2017, with projected increases to 9.3 million by 2060. Treatment options for AD remain limited. Development of disease-modifying therapies are challenging due, in part, to the long preclinical window of AD. The preclinical incubation period of AD starts in midlife, providing a critical window for identification and optimization of AD risk factors. Studies link AD with CVD risk factors such as hypertension, inflammation, and dyslipidemia. Both AD and CVD are progressive diseases with decades-long development periods. CVD can clinically manifest several years earlier than AD, making CVD and its risk factors a potential predictor of future AD. The current review focuses on the state of literature on molecular and metabolic pathways modulating the heart-brain axis underlying the potential association of midlife CVD risk factors and their effect on AD and related dementias. Further, we explore potential CVD/dementia preventive strategies during the window of opportunity in midlife and the future of research in the field in the multiomics and novel biomarker use era.

Left ventricular ejection fraction and long-term outcomes in women presenting with signs and symptoms of ischaemia.

BACKGROUND: Although 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. METHODS: A 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. RESULTS: Low 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). CONCLUSION: Among 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 NUMBER: NCT00000554.

Fitness attenuates long-term cardiovascular outcomes in women with ischemic heart disease and metabolic syndrome.

Background: The prevalence of metabolic syndrome continues to increase steadily while fitness remains relatively low. The contribution of fitness on longer-term cardiovascular outcomes and mortality in individuals with cardiovascular disease and metabolic syndrome remains unknown. Design: Women's Ischemia Syndrome Evaluation (WISE) prospective cohort (enrolled 1996-2001) of women undergoing invasive coronary angiography with signs/symptoms of ischemic heart disease. Methods: Investigated the association of fitness, defined as >7METs measured by self-reported Duke Activity Status Index (DASI), and both metabolic syndrome (ATPIII criteria) and dysmetabolism (ATPIII criteria and/or treated diabetes) with long-term cardiovascular outcomes and all-cause mortality risk. Results: Among the 492 women followed for a median of 8.6 years (range 0-11 years), 19.5% were fit-metabolically healthy (reference), 14.4% fit-metabolic syndrome, 29.9% unfit-metabolically healthy, and 36.2% unfit-metabolic syndrome. Compared to reference, MACE risk was 1.52-fold higher in fit-metabolic syndrome women (HR 1.52, 95% CI 1.03-2.26) and 2.42-fold higher in unfit-metabolic syndrome women (HR 2.42, 95% CI 1.30-4.48). Compared to reference, mortality risk was 1.96-fold higher in fit-dysmetabolism (HR 1.96, 95% CI 1.29-3.00) and 3-fold higher in unfit-dysmetabolism women (HR 3.0, 95% CI 1.66-5.43). Conclusions: In a high risk cohort of women with signs/symptoms of ischemic heart disease, unfit-metabolically healthy and fit-metabolically unhealthy women were at higher risk of long-term MACE and mortality compared to fit-metabolically healthy women; and women who were unfit and metabolically unhealthy were at the highest risk. Our study demonstrates that metabolic health and fitness play an important role in long term outcomes that warrants further investigation. Registration: https://www.clinicaltrials.gov/ct2/show/NCT00000554 (NCT00000554).

Leveraging CTSA hubs for rapid, large-scale, high-impact research: A case study during a global public health emergency.

As the COVID-19 pandemic took hold in the USA in early 2020, it became clear that knowledge of the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among asymptomatic individuals could inform public health policy decisions and provide insight into the impact of the infection on vulnerable populations. Two Clinical and Translational Science Award (CTSA) Hubs and the National Institutes of Health (NIH) set forth to conduct a national seroprevalence survey to assess the infection's rate of spread. This partnership was able to quickly design and launch the project by leveraging established research capacities, prior experiences in large-scale, multisite studies and a highly skilled workforce of CTSA hubs and unique experimental capabilities at the NIH to conduct a diverse prospective, longitudinal observational cohort of 11,382 participants who provided biospecimens and participant-reported health and behavior data. The study was completed in 16 months and benefitted from transdisciplinary teamwork, information technology innovations, multimodal communication strategies, and scientific partnership for rigor in design and analytic methods. The lessons learned by the rapid implementation and dissemination of this national study is valuable in guiding future multisite projects as well as preparation for other public health emergencies and pandemics.

Associations between cumulative social risk, psychosocial risk, and ideal cardiovascular health: Insights from the HeartSCORE study.

Background: Limited studies have assessed the effects of psychosocial risk factors on achievement of ideal cardiovascular health (CVH). Methods: Using the Heart Strategies Concentrating on Risk Evaluation (HeartSCORE) cohort, we examined the cross-sectional associations of cumulative social risk (CSR) and three psychosocial factors (depression, stress, perceived discrimination) with ideal CVH. CSR was calculated by assigning one point for each of: low family income, low education level, minority race (Black), and single-living status. Ideal CVH was calculated by assigning one point for ideal levels of each factor in American Heart Association's Life's Simple 7. Ideal CVH was dichotomized into fewer versus higher by combining participants achieving <3 versus ≥3 factors. Logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of having fewer ideal CVH factors. Psychosocial factors were assessed as mediators of the association between CSR and ideal CVH. Results: We included 2000 participants (mean age 59.1 [7.5] years, 34.6% male, 42.7% Black, and 29.1% with low income), among whom 60.6% had <3 ideal CVH factors. The odds of having fewer ideal CVH factors increased significantly with increasing CSR scores from 1 to 2, to ≥3 compared to individuals with CSR score of zero, after adjusting for age and sex (OR [95% CIs]: 1.77 [1.41 - 2.22]; 2.09 [1.62 - 2.69] 2.67 [1.97 - 3.62], respectively). Taking the components of ideal CVH separately, higher CSR was directly associated with odds of being in 'non-ideal' category for six of the seven factors, but was inversely associated with probability of being in 'non-ideal' category for cholesterol. The association was modestly attenuated after adjusting for depression, stress, and perceived discrimination (corresponding OR [95% CI]: 1.69 [1.34 - 2.12], 1.96 [1.51 - 2.55], 2.34 [1.71 - 3.20]). The psychosocial factors appeared to mediate between 10% and 20% of relationship between CSR and ideal CVH. Conclusions: Increased CSR was associated with lower probability of achieving ideal CVH factors. A modest amount of the effect of CSR on ideal CVH appeared to be mediated by depression, stress and perceived discrimination. Public health strategies aimed at improving ideal cardiovascular health may benefit from including interventions targeting social and psychosocial risk factors.

Body weight and physical fitness in women with ischaemic heart disease: does physical fitness contribute to our understanding of the obesity paradox in women?

AIMS: Body mass index (BMI) defined obesity is paradoxically associated with lower all-cause mortality in patients with known cardiovascular disease. This study aims to determine the role of physical fitness in the obesity paradox in women with ischaemic heart disease (IHD). METHODS AND RESULTS: Women undergoing invasive coronary angiography with signs/symptoms of IHD in the Women's Ischemia Syndrome Evaluation (WISE) prospective cohort (enrolled 1997-2001) were analysed. This study investigated the longer-term risk of major adverse cardiovascular events (MACE) and all-cause mortality associated with BMI and physical fitness measured by Duke Activity Status Index (DASI). Overweight was defined as BMl ≥25 to 30 kg/m2, obese as BMI ≥30 kg/m2, unfit as DASI scores <25, equivalent to ≤7 metabolic equivalents. Among 899 women, 18.6% were normal BMI-fit, 11.4% overweight-fit, 10.4% obese-fit, 15.3% normal BMI-unfit, 23.8% overweight-unfit, and 30.4% obese-unfit. In adjusted models compared to normal BMI-fit, normal BMI-unfit women had higher MACE risk [hazard ratio (HR) 1.65, 95% confidence interval (CI) 1.17-2.32; P = 0.004]; whereas obese-fit and overweight-fit women had lower risk of mortality (HR 0.60, 95% CI 0.40-0.89; P = 0.012 and HR 0.62, 95% CI 0.41-0.92; P = 0.018, respectively). CONCLUSION: To address the paradox of body weight and outcomes in women, we report for the first time that among women with signs/symptoms of IHD overweight-fit and obese-fit were at lower risk of long-term all-cause mortality; whereas normal BMI-unfit were at higher risk of MACE. Physical fitness may contribute to the obesity paradox in women, warranting future studies to better understand associations between body weight, body composition, and physical fitness to improve cardiovascular outcomes in women.

Genetic Analyses of Enamel Hypoplasia in Multiethnic Cohorts.

Enamel hypoplasia causes reduction in the thickness of affected enamel and is one of the most common dental anomalies. This defect is caused by environmental and/or genetic factors that interfere with tooth formation, emphasizing the importance of investigating enamel hypoplasia on an epidemiological and genetic level. A genome-wide association of enamel hypoplasia was performed in multiple cohorts, overall comprising 7,159 individuals ranging in age from 7-82 years. Mixed-models were used to test for genetic association while simultaneously accounting for relatedness and genetic population structure. Meta-analysis was then performed. More than 5 million single-nucleotide polymorphisms were tested in individual cohorts. Analyses of the individual cohorts and meta-analysis identified association signals close to genome-wide significance (P < 510-8), and many suggestive association signals (510-8 < P < 510-6) near genes with plausible roles in tooth/enamel development. The strongest association signal (P = 1.5710-9) was observed near BMP2K in one of the individual cohorts. Additional suggestive signals were observed near genes with plausible roles in tooth development in the meta-analysis, such as SLC4A4 which can influence enamel hypoplasia. Additional human genetic studies are needed to replicate these results and functional studies in model systems are needed to validate our findings.

Depression Symptom Patterns as Predictors of Metabolic Syndrome and Cardiac Events in Symptomatic Women with Suspected Myocardial Ischemia: The Women's Ischemia Syndrome Evaluation (WISE and WISE-CVD) Projects.

Background: Ischemic heart disease (IHD) risk in women includes biomedical, behavioral, and psychosocial contributors. The purpose of this study was to build upon previous research suggesting that in women, somatic symptoms (SS) of depression may be important to the development of IHD risk factors and major adverse cardiovascular events (MACE). Based on previous findings, we hypothesized that: (1) SS would be associated with robust biomedical predictors of heart disease and functional capacity, while cognitive symptoms (CS) of depression would not, and (2) SS would independently predict adverse health outcomes while CS would not. Methods: We examined the relationships between symptoms of depression (SS/CS), metabolic syndrome (MetS), inflammatory markers (IM), coronary artery disease (CAD) severity, and functional capacity in two independent cohorts of women with suspected IHD. In the Women's Ischemia Syndrome Evaluation (WISE), we also examined these variables as predictors of all-cause mortality (ACM) + MACE over a median 9.3-year follow-up. The WISE sample included 641 women with suspected ischemia with or without obstructive CAD. The WISE-Coronary Vascular Dysfunction (WISE-CVD) sample consisted of 359 women with suspected ischemia and no obstructive CAD. All study measures were collected uniformly at baseline. Depressive symptoms were measured via the Beck Depression Inventory. MetS was assessed according to Adult Treatment Panel III (ATP-III) criteria. Results: In both studies, SS was associated with MetS (Cohen's d = 0.18, 0.26, P < 0.05, respectively), while CS was not. Within WISE, using Cox Proportional Hazard Regression, SS (Hazard ratio [HR] = 1.08, 95% confidence interval [CI] = 1.01-1.15; HR = 1.07, 95% CI = 1.00-1.13) and MetS (HR = 1.89, 95% CI = 1.16-3.08; HR = 1.74, 95% CI=1.07-2.84) were independent predictors of ACM + MACE after controlling for demographics, IM, and CAD severity, while CS was not. Conclusions: In two independent samples of women undergoing coronary angiography due to suspected ischemia, SS but not CS of depression were associated with MetS, and both SS and MetS independently predicted ACM and MACE. These results add to previous studies suggesting that SS of depression may warrant specific attention in women with elevated cardiovascular disease (CVD) risk. Future research evaluating the biobehavioral basis of the relationship between depression, MetS, and CVD is needed.

An atomic approach to the design and implementation of a research data warehouse.

OBJECTIVE: As a long-standing Clinical and Translational Science Awards (CTSA) Program hub, the University of Pittsburgh and the University of Pittsburgh Medical Center (UPMC) developed and implemented a modern research data warehouse (RDW) to efficiently provision electronic patient data for clinical and translational research. MATERIALS AND METHODS: We designed and implemented an RDW named Neptune to serve the specific needs of our CTSA. Neptune uses an atomic design where data are stored at a high level of granularity as represented in source systems. Neptune contains robust patient identity management tailored for research; integrates patient data from multiple sources, including electronic health records (EHRs), health plans, and research studies; and includes knowledge for mapping to standard terminologies. RESULTS: Neptune contains data for more than 5 million patients longitudinally organized as Health Insurance Portability and Accountability Act (HIPAA) Limited Data with dates and includes structured EHR data, clinical documents, health insurance claims, and research data. Neptune is used as a source for patient data for hundreds of institutional review board-approved research projects by local investigators and for national projects. DISCUSSION: The design of Neptune was heavily influenced by the large size of UPMC, the varied data sources, and the rich partnership between the University and the healthcare system. It includes several unique aspects, including the physical warehouse straddling the University and UPMC networks and management under an HIPAA Business Associates Agreement. CONCLUSION: We describe the design and implementation of an RDW at a large academic healthcare system that uses a distinctive atomic design where data are stored at a high level of granularity.

Fostering diversity and a culture of inclusion in clinical research by training and hiring community members as clinical research assistants.

The University of Pittsburgh (Pitt) Clinical and Translational Science Institute (CTSI) and the nonprofit Bidwell Training Center co-developed a new program for translational workforce diversification and development to foster diversity and inclusion in clinical research. The STricklAnd Research Training (START) program provides students in the Medical Assistant program at Bidwell a career path in clinical research. We created a 12-hour didactic package that covers responsible conduct of human subjects research and good clinical practice as an add-on to existing vocational curriculums. Students have the option of completing a clinical research-related externship at Pitt, which includes mentoring, shadowing, and protocol-specific training on a study team whose intention is to hire them as a clinical research assistant. Those who accept a position at Pitt receive continued mentorship, education, and professional development through Pitt CTSI. In the first three cohorts, two of which had access to research externships at Pitt, 92% of students successfully completed the instruction in clinical research. We plan to expand START to new venues to train and hire local community members from diverse backgrounds who can bring their lived experience to research programs.

Assessing the application of human-centered design to translational research.

INTRODUCTION: Human-centered design (HCD) training offers the potential to improve both team processes and products. However, the use of HCD to improve the quality of team science is a relatively recent application, and its benefits and challenges have not been rigorously evaluated. We conducted a qualitative study with health sciences researchers trained in HCD methods. We aimed to determine how researchers applied HCD methods and perceived the benefits and barriers to using HCD on research teams. METHODS: We conducted 1-hour, semi-structured interviews with trainees from three training cohorts. Interviews focused on perceptions of the training, subsequent uses of HCD, barriers and facilitators, and perceptions of the utility of HCD to science teams. Data analysis was conducted using Braun and Clarke's process for thematic analysis. RESULTS: We interviewed nine faculty and nine staff trained in HCD methods and identified four themes encompassing HCD use, benefits, challenges, and tensions between HCD approaches and academic culture. CONCLUSIONS: Trainees found HCD relevant to research teams for stakeholder engagement, research design, project planning, meeting facilitation, and team management. They also described benefits of HCD in five distinct areas: creativity, egalitarianism, structure, efficiency, and visibility. Our data suggest that HCD has the potential to help researchers work more inclusively and collaboratively on interdisciplinary teams and generate more innovative and impactful science. The application of HCD methods is not without challenges; however, we believe these challenges can be overcome with institutional investment.

Undiagnosed SARS-CoV-2 seropositivity during the first 6 months of the COVID-19 pandemic in the United States.

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates in the United States and elsewhere. To address this, we analyzed seropositivity in 9089 adults in the United States who had not been diagnosed previously with COVID-19. Individuals with characteristics that reflected the U.S. population (n = 27,716) were selected by quota sampling from 462,949 volunteers. Enrolled participants (n = 11,382) provided medical, geographic, demographic, and socioeconomic information and dried blood samples. Survey questions coincident with the Behavioral Risk Factor Surveillance System survey, a large probability-based national survey, were used to adjust for selection bias. Most blood samples (88.7%) were collected between 10 May and 31 July 2020 and were processed using ELISA to measure seropositivity (IgG and IgM antibodies against SARS-CoV-2 spike protein and the spike protein receptor binding domain). The overall weighted undiagnosed seropositivity estimate was 4.6% (95% CI, 2.6 to 6.5%), with race, age, sex, ethnicity, and urban/rural subgroup estimates ranging from 1.1% to 14.2%. The highest seropositivity estimates were in African American participants; younger, female, and Hispanic participants; and residents of urban centers. These data indicate that there were 4.8 undiagnosed SARS-CoV-2 infections for every diagnosed case of COVID-19, and an estimated 16.8 million infections were undiagnosed by mid-July 2020 in the United States.

Development of a Coronavirus Disease 2019 (COVID-19) Application Ontology for the Accrual to Clinical Trials (ACT) network.

Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that are critical to COVID-19 research. The ontology contains over 50 000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for severe acute respiratory syndrome coronavirus 2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of 9 academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community on GitHub at https://github.com/shyamvis/ACT-COVID-Ontology, will be useful for harmonizing EHRs for COVID-19 research beyond the ACT network.

Development of a COVID-19 Application Ontology for the ACT Network.

Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that that are critical to COVID-19 research. The ontology contains over 50,000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for SARS-CoV-2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of nine academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community on GitHub at https://github.com/shyamvis/ACT-COVID-Ontology, will be useful for harmonizing EHRs for COVID-19 research beyond the ACT network.