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. 2021 Apr 8:12:663950.
doi: 10.3389/fphys.2021.663950. eCollection 2021.

Influence of Intermittent Hypoxia/Hypercapnia on Atherosclerosis, Gut Microbiome, and Metabolome

Jin Xue  1 , Celeste Allaband  1   2   3 , Dan Zhou  1 , Orit Poulsen  1 , Cameron Martino  1   4   5 , Lingjing Jiang  6 , Anupriya Tripathi  1   7   8 , Emmanuel Elijah  8   9 , Pieter C Dorrestein  5   8   9 , Rob Knight  1   5   10 , Amir Zarrinpar  3   5   11   12 , Gabriel G Haddad  1   13   14
Affiliations

Influence of Intermittent Hypoxia/Hypercapnia on Atherosclerosis, Gut Microbiome, and Metabolome

Jin Xue et al. Front Physiol. .

Abstract

Obstructive sleep apnea (OSA), a common sleep disorder characterized by intermittent hypoxia and hypercapnia (IHC), increases atherosclerosis risk. However, the contribution of intermittent hypoxia (IH) or intermittent hypercapnia (IC) in promoting atherosclerosis remains unclear. Since gut microbiota and metabolites have been implicated in atherosclerosis, we examined whether IH or IC alters the microbiome and metabolome to induce a pro-atherosclerotic state. Apolipoprotein E deficient mice (ApoE-/- ), treated with IH or IC on a high-fat diet (HFD) for 10 weeks, were compared to Air controls. Atherosclerotic lesions were examined, gut microbiome was profiled using 16S rRNA gene amplicon sequencing and metabolome was assessed by untargeted mass spectrometry. In the aorta, IC-induced atherosclerosis was significantly greater than IH and Air controls (aorta, IC 11.1 ± 0.7% vs. IH 7.6 ± 0.4%, p < 0.05 vs. Air 8.1 ± 0.8%, p < 0.05). In the pulmonary artery (PA), however, IH, IC, and Air were significantly different from each other in atherosclerotic formation with the largest lesion observed under IH (PA, IH 40.9 ± 2.0% vs. IC 20.1 ± 2.6% vs. Air 12.2 ± 1.5%, p < 0.05). The most differentially abundant microbial families (p < 0.001) were Peptostreptococcaceae, Ruminococcaceae, and Erysipelotrichaceae. The most differentially abundant metabolites (p < 0.001) were tauro-β-muricholic acid, ursodeoxycholic acid, and lysophosphoethanolamine (18:0). We conclude that IH and IC (a) modulate atherosclerosis progression differently in distinct vascular beds with IC, unlike IH, facilitating atherosclerosis in both aorta and PA and (b) promote an atherosclerotic luminal gut environment that is more evident in IH than IC. We speculate that the resulting changes in the gut metabolome and microbiome interact differently with distinct vascular beds.

Keywords: atherosclerosis; intermittent hypoxia and hypercapnia; metabolome; microbiome; obstructive sleep apnea.

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Conflict of interest statement

AZ is a co-founder and equity holder of Tortuga Biosciences. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Atherosclerotic lesions in the (A) aortas, (B) aortic arches, and (C) pulmonary arteries of ApoE−/− mice after 10-week treatments. Mice were exposed to either Air, IH, or IC for 10 weeks. The en-face lesions were quantified as the percentage of lesion area in the total area of the blood vessel examined. Side panels: representative Sudan IV-stained images of aortic arch (B) and PA (C). In the aortas and aortic arches, n = 12 for Air, n = 11 for IH, and n = 11 for IC. In the pulmonary arteries, n = 11 for each Air, IH, and IC group. Data were presented as means ± SEM. Statistical significance (one-way ANOVA with Tukey’s multiple comparison test), *p < 0.05.
Figure 2
Figure 2
16S microbiome of ApoE−/− mice on HFD during chronic 10-week treatment. (A) Weighted UniFrac PCoA of the microbiome during four key time points, each time point calculated in isolation. Longitudinal relative abundance values for (B) family Peptostreptococcaceae; (C) family Ruminococcaceae; and (D) family Erysipelotrichaceae. PERMANOVA used for statistical comparisons at the population level. Linear mixed effect (LME) modeling used for statistical comparisons of individual families over time. The shaded areas in parts (B–D) represent standard error of the mean. Air/controls are black (n = 6), IH is blue (n = 12), and IC is red (n = 12). Statistical significance p < 0.05, *IC vs. Air, #IH vs. Air, and $IH vs. IC.
Figure 3
Figure 3
Untargeted LC-MS/MS metabolomics of ApoE−/− mice on HFD during chronic 10-week treatment. (A) Canberra PCoA of the metabolome during four key time points, each time point calculated in isolation. Longitudinal relative abundance values for (B) Tauro-β-muricholic acid (TβMCA; level 1 identification); (C) Ursodeoxycholic acid (UDCA; level 1 identification); and (D) lysophosphoethanolamine 1-stearoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine [LysoPE(18:0); level 3 identification]. PERMANOVA used for statistical comparisons at the population level. LME modeling used for statistical comparisons of individual metabolites over time. The shaded areas in parts (B–D) represent standard error of the mean. Air/controls are black (n = 6), IH is blue (n = 12), and IC is red (n = 12). Statistical significance p < 0.05, *IC vs. Air, #IH vs. Air, and $IH vs. IC.
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