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Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).

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Background: Studies examining racial and ethnic disparities in-hospital mortality for patients hospitalized with COVID-19 had mixed results. Findings from patients within academic medical centers (AMCs) are lacking, but important given the role of AMCs in improving health equity.

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