Testing assumptions about cardiovascular health in underrepresented groups

Testing assumptions about cardiovascular health in underrepresented groups

Meet a research team at Yale School of Medicine using the All of Us dataset to better understand associations and disparities in cardiovascular health.
June 22, 2022
Changing how we think about underrepresentation in biomedical research
Changing how we think about underrepresentation in biomedical research
Source: All of Us Research Program

Julián Acosta, MDJulián Acosta, MDPostdoctoral Research Fellow, Neurology
Yale School of Medicine

Guido Falcone, MD, ScD, MPHGuido Falcone, MD, ScD, MPHAssistant Professor of Neurology; Director of Clinical Research in Neurocritical Care
Yale School of Medicine

Audrey LeasureAudrey LeasureMD/MHS Student
Yale School of Medicine

Project details

A research team at the Yale University School of Medicine has turned to the All of Us dataset to pressure test existing theories about risk factors and prevalence in cardiovascular disease (CVD). By assessing whether certain skin conditions can increase the risk of developing CVD, evaluating CVD burden in racial and ethnic minorities, and exploring stroke disparities amongst non-racial minorities, the team is exploring how biological factors and social determinants work together to impact cardiovascular outcomes.

The Yale team was initially attracted to the All of Us research platform and Researcher Workbench because of its open access structure, diverse dataset, and fresh approach to defining underrepresented communities in biomedical research. Three of the several cross-sectional studies they conducted using All of Us data were published in 2021.

Stroke Disparities Among Nonracial Minorities in the All of Us Research Program
Stroke. 18 June 2021.

The researchers sought to describe stroke disparities in nonracial minority groups based on self-reported qualifiers of diversity (age, disability, income). They found that these minority groups had a higher stroke burden than individuals not in these groups, pointing to the importance of greater inclusion and retention of nonracial minorities in stroke research.

Cardiovascular Health Disparities in Racial and Other Underrepresented Groups: Initial Results From the All of Us Research Program
Journal of the American Heart Association.
25 August 2021.

The researchers combined survey response data and electronic health record data to estimate the CVD prevalence in underrepresented groups defined by race, ethnicity, age, disability, sexual orientation and gender identity, income, and education. They confirmed that, among participants enrolled in All of Us, underrepresented groups have a disproportionately high burden of CVD.

Association of Lichen Planus with Cardiovascular Disease: A Combined Analysis of the UK Biobank and All of Us Study
Journal of American Academy of Dermatology. 21 September 2021.

The researchers explored the relationship between CVD and lichen planus, an inflammatory skin disease, to test mounting evidence that the latter can drive the former. They concluded that the association between lichen planus and CVD was most noticeable in younger patients and that more research was needed to further define the causes of that association.

“The addition of genetic data into the All of Us dataset will help better define how socioeconomic, geographic, and lifestyle variables interact with genes and allow us to study the impact of that interaction on cardiovascular outcomes.”

– Dr. Julián Acosta

Long-term Vision

Dr. Acosta, Dr. Falcone, and Audrey Leasure intend to continue studying the impact of CVD on populations that have been traditionally underrepresented in biomedical research (UBR). They are particularly interested in working to expand the academic community’s understanding of these populations. As their own perspectives on what constitutes a UBR community evolve through exposure to the All of Us dataset, the team sees an opportunity to share that perspective with others — from colleagues to journal editors — to begin redefining the common, but limiting view of health disparities as measures of race and ethnicity alone.

Upcoming plans include bringing together a multi-disciplinary team of researchers from across Yale —including the Yale Center for Aging Research (Y-Age) and the neurosurgery department—to examine the consequences of disability and frailty on neurological and cardiovascular outcomes in hospital intensive care units (ICUs). The team also plans on exploring the new genomic data, available through the Controlled Tier, and medication data to examine causal associations with CVD.

For students, it’s a free resource. You can access it anywhere without any special computing powers, which makes it a great tool for us.

– Audrey Leasure

Key benefits of All of Us data and resources

The computational capacity and ease of access make the All of Us platform a particularly valuable tool for early career investigators, like Audrey, who are carrying out discovery research without the same funding or resources available to more established researchers.

The team credits the ease of use of the Researcher Workbench’s custom tools (such as the shared workspaces, notebooks and Dataset Builder) with their ability to effectively parse and analyze the expansive dataset.

All of Us is setting the stage for how we think about and define minorities. The concept is still percolating in different stages of academia, but All of Us has embraced the idea of underrepresented groups that are defined by factors other than race and ethnicity.”

– Dr. Falcone

Dr. Acosta, in particular, has also used and learned from many of the support services provided by the Workbench User Support Hub, including the Community Support Forum, the Help Desk, and training resources like Featured Workspaces.

The diversity and variation of the All of Us dataset are some of the main features that have kept the Yale team coming back to the Researcher Workbench. All of Us is opening doors to new lines of inquiry by enabling them to explore health disparities in new ways, making new associations through the integrated dataset, and redefining the measures of underrepresentation in research.