Research Article

Altered Gut Microbiota and Shift in Bacteroidetes between Young Obese and Normal-Weight Korean Children: A Cross-Sectional Observational Study

Figure 3

Correlation plot showing Pearson’s correlation coefficient between blood biochemical markers related to insulin resistance and inflammation, major taxa, and dietary intake (a). Only statistically significant values are shown () (a). Positive correlations are displayed in blue, and negative correlations are displayed in red (a). Color intensity and the size of the circle are proportional to the correlation coefficients (a). Canonical correspondence analysis of gut microbial community composition at the phylum level with respect to BMI -score, blood biochemical markers including 25-OH vitamin D, neutrophil count, CRP, ferritin, and HOMA-IR (b), or dietary intake including calories, fat, Na, niacin, Zn, P, and vitamin B6 (c). The blue lines indicate the direction and magnitude of variables associated with bacterial community composition (b, c). Red dots represent different bacterial phyla, and black dots represent each patient (O—obese group; N—normal-weight group) (b, c). Axes 1 and 2 can explain 80.4% of the data variance in the correlation between the microbiota and blood biomarkers associated with inflammation and metabolic syndrome (b). Axes 1 and 2 can explain 83.5% of the data variance in the correlation between microbiota and dietary intake (c). Abbreviations: VitD—25-OH vitamin D; Ntcount—neutrophil count; CRP—high-sensitivity C-reactive protein; BMI_Z—body mass index -score; HOMA_IR—the homeostasis model assessment-estimated insulin resistance; Zn—zinc; TGs—triglycerides; VitB6—vitamin B6.
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