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Clinical Trial
. 2018 Nov:37:392-400.
doi: 10.1016/j.ebiom.2018.10.037. Epub 2018 Oct 23.

Gut microbiota and plasma metabolites associated with diabetes in women with, or at high risk for, HIV infection

Affiliations
Clinical Trial

Gut microbiota and plasma metabolites associated with diabetes in women with, or at high risk for, HIV infection

Jee-Young Moon et al. EBioMedicine. 2018 Nov.

Abstract

Background: Gut microbiota alteration has been implicated in HIV infection and metabolic disorders. The relationship between gut microbiota and diabetes has rarely been studied in HIV-infected individuals, who have excess risk of metabolic disorders.

Methods: Our study during 2015-2016 enrolled predominantly African Americans and Hispanics in the Women's Interagency HIV Study. We studied 28 women with long-standing HIV infection under antiretroviral therapy and 20 HIV-uninfected, but at high risk of infection, women (16 HIV+ and 6 HIV- with diabetes). Fecal samples were analyzed by sequencing prokaryotic16S rRNA gene. Plasma metabolomics profiling was performed by liquid chromatography-tandem mass spectrometry.

Findings: No significant differences in bacterial α- or β-diversity were observed by diabetes or HIV serostatus (all P > .1). Relative abundances of four genera (Finegoldia, Anaerococcus, Sneathia, and Adlercreutzia) were lower in women with diabetes compared to those without diabetes (all P < .01). In women with diabetes, plasma levels of several metabolites in tryptophan catabolism (e,g., kynurenine/tryptophan ratio), branched-chain amino acid and proline metabolism pathways were higher, while glycerophospholipids were lower (all P < .05). Results were generally consistent between HIV-infected and HIV-uninfected women, and no significant modification effects by HIV serostatus were observed (all Pinteraction > 0.05). Anaerococcus, known to produce butyrate which is involved in anti-inflammation and glucose metabolism, showed an inverse correlation with kynurenine/tryptophan ratio (r = -0.38, P < .01).

Interpretation: Among women with or at high risk for HIV infection, diabetes is associated with gut microbiota and plasma metabolite alteration, including depletion of butyrate-producing bacterial population along with higher tryptophan catabolism. FUND: NHLBI (K01HL129892, R01HL140976) and FMF.

Keywords: Diabetes; Gut microbiota; HIV; Metabolite.

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Figures

Fig. 1
Fig. 1
Microbial composition and diversity by HIV serostatus and diabetes (a) Principal coordinates analysis of Bray-Curtis dissimilarity of microbiota by HIV serostatus and diabetes, (b) Alpha diversity of microbiota by HIV serostatus and diabetes. Observed richness is in the OTU level, and Chao 1 and Shannon index are in the genus level. A bar represents a median of the group.
Fig. 2
Fig. 2
Relative abundance of four bacterial genera by diabetes status. A bar represents the mean relative abundances and an error bar represents 1 standard error of relative abundances. The topmost P-value is the significance level of differential abundances between the women with diabetes and without diabetes, tested by a linear regression adjusting for age and HIV serostatus, and P-values in the second line are the significance levels of differential abundances between the women with diabetes and without diabetes, tested by linear regressions adjusting for age among HIV+ (left) and among HIV- (right).
Fig. 3
Fig. 3
Metabolic concentration levels by diabetes status. A bar represents the mean concentrations (ratio for kynurenine/tryptophan ratio) and an error bar represents 1 standard error of concentrations (ratio for kynurenine/tryptophan ratio). The topmost P-value is the significance level of differential concentrations between the women with diabetes and without diabetes [Mann-Whitney U test], and P-values in the second line are the significance levels of differential concentrations between the women with diabetes and without diabetes [Mann-Whitney U test], among HIV+ (left) and among HIV- (right). All P for interaction of diabetes status and HIV serostatus >.18 [linear regression].

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