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Improving Cardiovascular Risk Prediction–Biomarkers and Beyond; Implications for Astronaut Selection and Monitoring During Prolonged Spaceflight

Principal Investigator:
James de Lemos, M.D.

University of Texas Southwestern Medical Center

Strategies for predicting catastrophic cardiovascular events remain largely focused on statistical models that combine traditional atherosclerosis risk factors such as smoking, diabetes, blood pressure and lipids. However, the majority of cardiovascular events occur among individuals classified into low or intermediate risk categories using these models. It is imperative to improve upon these models to optimize cardiovascular risk prediction for the astronaut core, to ensure selection of astronaut candidates who will be able to complete training and exploration missions with extremely low risk of interval cardiovascular events.

Numerous studies have evaluated novel risk markers in an attempt to improve cardiovascular risk prediction, with several promising imaging and blood-based biomarkers identified. Most of these studies have investigated the incremental predictive value of a single biomarker added to a traditional risk factor model, with a few reporting combinations of biomarkers. Moreover, few studies have evaluated strategies for risk prediction that cross testing modalities. Such a multi-modality approach has the potential to markedly improve cardiovascular risk prediction among potential and existing astronauts, and would have direct relevance to the general population.

Dr. de Lemos and colleagues will enhance cardiovascular risk prediction by developing novel strategies that combine risk prediction tests that cross testing modalities. These modalities will include traditional risk factor and fitness assessments, as well as cardiovascular imaging studies, novel protein biomarkers, and genetics. Models will be developed that optimize global cardiovascular disease risk prediction over two time windows:
(1) 10-20 years, representing the full career of the astronaut; and
(2) 2-5 years, representing the planning and operational phase of a manned mission to Mars.

NASA Taskbook Entry

Technical Summary

The project will develop a consortium of biomarker and aerospace medicine leaders, with expertise in multiple different testing modalities, and with access to robust existing databases, to identify and validate novel strategies to enhance global CVD risk prediction. Data will be collated from multiple large population-based cohort studies that contain overlapping data elements, including information on novel biomarkers, imaging studies, genetics, and risk factors. Because the focus of the study is on low-risk individuals, the number of cardiovascular events within individual cohort studies is low, and thus combining data from multiple cohort studies will be required to provide adequate statistical power to develop the multivariable risk prediction algorithms.

Risk prediction models will be developed that sequentially evaluate novel testing modalities on top of standard risk factors, including coronary calcium (a measure of the extent of coronary atherosclerosis), multiple blood based protein biomarkers that reflect inflammation, cardiac injury and cardiac stress, as well as imaging-based assessments of cardiac function. Finally, we will work directly with NASA researchers in the Human Research Program to explore the feasibility of transforming the Longitudinal Study of Astronaut Health into a prospective state-of-the art cohort study of the astronaut core.

(1) Risk prediction strategies that cross testing modalities and include a hierarchy of blood-based and imaging biomarkers will improve prediction of 10-year global cardiovascular event rates in middle aged men and women.
(2) Distinct risk markers will identify individuals at increased risk for short-term global CVD events. Markers of existing subclinical disease, including imaging-based measures of atherosclerosis and cardiac structure and function, and biomarkers of subclinical myocardial injury and neurohormonal activation will enhance short-term risk prediction.

Specific Aims:
(1) Establish a consortium of biomarker and aerospace medicine experts to provide recommendations regarding biomarker screening in the astronaut population, and to conduct collaborative research focused on the specific risk prediction needs of the astronaut population. This is an infrastructure aim that will support the scientific aims and also provide ongoing advice to NASA.
(2) Develop a multi-modality risk prediction tool for 10 year global CVD events that combines imaging and novel blood-based biomarkers.
(3) Develop a risk prediction tool for short-term (3 year) global CVD events.
(4) Work with NASA researchers in the Human Research Program to explore the feasibility of transforming the Longitudinal Study of Astronaut Health (LSAH) into a prospective state-of-the art cohort study of the astronaut corps. This is an exploratory aim to assess the feasibility of enhancing the LSAH to make it a state-of-the art program for study of the effects of training and spaceflight on disease phenotypes.

After completion of these aims, we will have created a consortium of the very best biomarker experts in the world, which will provide specific recommendations to NASA flight surgeons regarding pre-flight assessment of cardiovascular risk in astronauts. By combining data from multiple well defined non-astronaut populations, we will establish the utility of novel biomarkers for predicting long term (10 yr) and short term (2-5 yr) risk in an “astronaut like” demographic; this effort will allow mission managers to weigh precisely the relative risk of mission threatening cardiovascular events in the context of other non-medical mission concerns. Finally, we will work with NASA to plan the transformation of the LSAH into a state-of-the art cohort study.

Earth Applications

The outcome of this research program will directly inform decisions regarding astronaut selection and clearance for long-duration manned space flight. The research program will also have multiple earth based applications relevant to public health. Identifying optimal combinations of biomarkers to improve cardiovascular risk assessment is one of the “holy grails” of preventive cardiology, as the majority of CV events continue to occur in individuals NOT previously considered high risk. Because the absolute number of “low risk” individuals is so large, it is impractical to treat every person with aggressive medical therapy, not just for cost and compliance issues, but because of the possibility of side-effects of even the safest medicines. Therefore refinement of the algorithms to reclassify patients into higher risk categories is essential for optimization of medical management and reduction of morbidity and mortality from cardiovascular disease.