Fig. 6: Validation of markers for ACS.
From: Microbiome and metabolome features of the cardiometabolic disease spectrum
a–c, For the gut microbial and plasma metabolome features common to both MetaCardis and Israeli cohorts, a Spearman correlation analysis (a) was conducted between the effect sizes (Cliff’s delta) for HC versus ACS comparison in each study after recalculating Cliff’s deltas in the Israeli population. Next, ROC curves depicting the classifier performance (AUROC) of five-fold cross-validated O-PLS-DA models based on the overlapped set of ACS biomarkers in three settings are shown for MetaCardis as the training population (b) and Israeli cohort as the test population (c). Model 1 included nine clinical ACS risk variables—that is, age, sex, BMI, systolic blood pressure, diastolic blood pressure, glycated hemoglobin (factored as >5.7, 5.7–6.4 and <6.4 mmol l−1), smoking status, fasting total cholesterol and HDL cholesterol (mmol l−1). Model 2 included ACS-specific biomarkers identified in our study that were also found in ref. 25 (118 variables), whereas model 3 involved all variables considered for model 1 and model 2 (that is, 127 variables). Two-sided MWU was used for assessing the significance of group-wise comparisons using HC (n = 275) and ACS (n = 112) in MetaCardis population and HC (n = 473) versus ACS (n = 156) in the Israeli population. Multiple testing corrections were done using the Benjamini–Hochberg method, and FDR ≤ 0.1 was considered significant.
