Figure 4: Receiver operating characteristic (ROC) analysis of potential biomarkers and numeric correlation between clinical phenotype and identified significant metabolites. | Scientific Reports

Figure 4: Receiver operating characteristic (ROC) analysis of potential biomarkers and numeric correlation between clinical phenotype and identified significant metabolites.

From: Integrated metabolomics and metagenomics analysis of plasma and urine identified microbial metabolites associated with coronary heart disease

Figure 4

(a) ROC analysis and boxplots of 7 identified plasma potential biomarkers and 2 identified urine potential biomarkers with AUC larger than 0.80 in validation datasets. (b) Spearman correlation analysis was performed between 18 plasma identified potential biomarkers and clinical indicators. Red, positive correlation; blue, negative correlation. + , adjusted p.value < 0.05; *, adjusted p.value < 0.01. Red panel indicated increased metabolites in CHD patients while green panel suggested decreased metabolites in CHD patients. Paraxanthine did not show significant correlations with any of the 15 numerical phenotypes (adjusted p.value > 0.05, Spearman’s), creatine kinase MB (CKMB), aspartate transaminase (AST) and creatinine (CREA) did not show significant correlations with any of 18 plasma identified potential biomarkers, both of which were not shown. albumin (ALB), alanine aminotransferase (ALT), total protein (TP), hydroxybutyrate dehydrogenase (HBDH), triglyceride (TRIG), low-density lipoprotein (LDLC), cholesterol (CHOL), high-density lipoprotein (HDLC), apolipoprotein (b) (APOB), apolipoprotein (a) (APOA), lipoprotein (a) (LPA). (c) Spearman correlation analysis was performed between 4 urine identified potential biomarkers and clinical indicators. CKMB, ALB, ALT, TRIG and LPA did not show significant correlations with any of 4 urine identified potential biomarkers were not shown.

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