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Fig. 2 | Cardiovascular Diabetology

Fig. 2

From: Machine learning of plasma metabolome identifies biomarker panels for metabolic syndrome: findings from the China Suboptimal Health Cohort

Fig. 2

Identification of metabolic biomarkers and disturbed pathways related to metabolic syndrome. A Volcano plot of candidate metabolic biomarkers. B Orthogonal projection to latent structure-discriminant analysis (OPLS-DS) score plots. C Disturbed metabolic pathways in MetS individuals. D Correlation coefficient matrix between 13 potential metabolic biomarkers and 14 cardiometabolic risk factors. Statistically significant correlations between two metabolites are shown, while the insignificant correlation coefficients are blank in the boxes. The positive correlations are represented by blue color, while negative correlations are represented by red color; WC, waist circumference; HC, hip circumference; WHR, Waist-to-hip ratio; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TC, total cholesterol; TG, triglycerides; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; BUN, blood urea nitrogen; Cr, creatinine. P < 0.05 is considered statistically significant. The detailed correlation coefficients and P values were shown in Additional file 4

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