Fig. 2 | Scientific Reports

Fig. 2

From: Associations between weight gain, integrase inhibitors antiretroviral agents, and gut microbiome in people living with HIV: a cross-sectional study

Fig. 2

Exploring the relationship between weight gain, microbiome, treatments and host characteristics: Sex, Age, and BMI. (A) Multiple linear regressions were performed to determine the association between weight gain, microbiome (beta-diversity: Pco1 & Pco2), drugs (DTG, BIC, Other) Sex, BMI category (normal, overweight, obese), Age category (old > median, young ≤ median; median = 51 years old). A volcano plot visualizes all predictors based on their adjusted p-value (-log10) and coefficients. Significant threshold is adjusted p-value < 0.05. (B) Significant results from volcano plot are further illustrated in the violin plot (weight gain in different treatments) and density plots. Pco1 & Pco2 in Bray–Curtis distance were used to represent the variability of microbiome. Difference between male & female in only Pco1 are presented in density plots. (C) Principal coordinate analyses of all samples (n = 121) based on Bray–Curtis distance metrics (Pco1 & Pco2) showing different clusters of bacteria regardless of treatment groups. Male and female samples are different in shape while color gradients represent the continuous data of log2 ratios of Akkermansia/Prevotella, Firmicutes/Bacteroidota, Bacteroides/Prevotella respectively. Spearman’s correlation (Rs) heatmap between host’s characteristics (BMI, CD4 + T-cell count, age, weight gain), bacterial diversities (Pco1, Pco2, alpha diversity indices: Phylo.diver, InvSimpson, Observed ASV, Shannon) and diversity associated-bacterial ratios.

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