Metabolite Panel for Identifying COVID-19
To generate a plasma metabolite panel for differentiating COVID-19 patients from healthy individuals, variables with p < 0.05 between healthy controls and COVIDP19 patients after adjustment for age, sex and BMI were sieved out to form a starting pool. From this pool, a starting variable with lowest p value was added to Set 1, and remaining variables from the starting pool significantly correlated (p < 0.05) with this starting variable were added together to form Set 1. The process then was repeated in an iterative process using starting variable with the second lowest p value, and so on, finally generating a total of ten established sets. Representative metabolite from each established set was chosen based on (1) smallest p value and (2) reported biological function through a PubMed search. The selection process finally created a panel of ten plasma metabolites, and its performance was evaluated in a logistic regression model with leave-one-out (LOO) cross-validation, which distinguished between COVID-19 patients and healthy controls with an area under curve (AUC) = 0.955.