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Associations between the gut microbiota and host responses to high altitude - PubMed

  • ️Mon Jan 01 2018

Randomized Controlled Trial

. 2018 Dec 1;315(6):G1003-G1015.

doi: 10.1152/ajpgi.00253.2018. Epub 2018 Sep 13.

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Randomized Controlled Trial

Associations between the gut microbiota and host responses to high altitude

J Philip Karl et al. Am J Physiol Gastrointest Liver Physiol. 2018.

Abstract

Hypobaric hypoxia and dietary protein and fat intakes have been independently associated with an altered gastrointestinal (GI) environment and gut microbiota, but little is known regarding host-gut microbiota interactions at high altitude (HA) and the impact of diet macronutrient composition. This study aimed to determine the effect of dietary protein:fat ratio manipulation on the gut microbiota and GI barrier function during weight loss at high altitude (HA) and to identify associations between the gut microbiota and host responses to HA. Following sea-level (SL) testing, 17 healthy males were transported to HA (4,300 m) and randomly assigned to consume provided standard protein (SP; 1.1 g·kg-1·day-1, 39% fat) or higher protein (HP; 2.1 g·kg-1·day-1, 23% fat) carbohydrate-matched hypocaloric diets for 22 days. Fecal microbiota composition and metabolites, GI barrier function, GI symptoms, and acute mountain sickness (AMS) severity were measured. Macronutrient intake did not impact fecal microbiota composition, had only transient effects on microbiota metabolites, and had no effect on increases in small intestinal permeability, GI symptoms, and inflammation observed at HA. AMS severity was also unaffected by diet but in exploratory analyses was associated with higher SL-relative abundance of Prevotella, a known driver of interindividual variability in human gut microbiota composition, and greater microbiota diversity after AMS onset. Findings suggest that the gut microbiota may contribute to variability in host responses to HA independent of the dietary protein:fat ratio but should be considered preliminary and hypothesis generating due to the small sample size and exploratory nature of analyses associating the fecal microbiota and host responses to HA. NEW & NOTEWORTHY This study is the first to examine interactions among diet, the gut microbiota, and host responses to weight loss at high altitude (HA). Observed associations among the gut microbiota, weight loss at HA, and acute mountain sickness provide evidence that the microbiota may contribute to variability in host responses to HA. In contrast, dietary protein:fat ratio had only minimal, transient effects on gut microbiota composition and bacterial metabolites which were likely not of clinical consequence.

Keywords: gut barrier; hypoxia; macronutrient; microbiome; weight loss.

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Figures

Fig. 1.
Fig. 1.

Changes in gastrointestinal (GI) symptomology, GI function, and inflammation at high altitude (HA; 4,300 m) are largely independent of dietary protein:fat ratio. GI quality of life (GIQLI; lower scores indicate worse symptoms; A) and fasting serum IL-6 (B), plasma LPS binding protein (LBP; C), and serum glucagon-like peptide (GLP)-2 (D) concentrations. Data are analyzed by marginal models controlling for age, body mass index, and baseline value. B and C: data were log10-transformed for analysis. HP, higher protein diet group; SL, sea level; SP, standard-protein diet group. HP, n = 9; SP, n = 8. Values are means ± SE. Time points not sharing a superscript letter are significantly different within a diet group (P ≤ 0.05). #Significantly different from SL (P < 0.05). *Significantly different from SP (P  = 0.02). †Significantly different from HA days 0 and 21 (P ≤ 0.01).

Fig. 2.
Fig. 2.

Changes in fecal microbiota composition during weight loss at high altitude (HA 4,300 m) are largely independent of dietary protein:fat ratio. A: α-diversity [Shannon diversity and observed operational taxonomic units (OTUs)] analyzed by marginal models controlling for age, body mass index, and baseline diversity (i.e., SL1). B: principle coordinates (PCo) analysis of Bray-Curtis dissimilarities. Individual data points represent the entire fecal microbiota community of a single individual at one point in time. Samples closer together are more similar than samples farther apart. C: log2-fold change in relative abundance from SL in HP relative to SP for taxa demonstrating significant diet-by-time interactions (false discovery rate <0.20). *Change from SL significantly different in HP vs. SP (P ≤ 0.02). D: log2-fold change in relative abundance from SL in genera demonstrating a significant main effect of time (false discovery rate <0.20). #Significant change from SL (P ≤ 0.005). HA, high altitude; HP, higher protein diet group; SL, sea level; SP, standard protein diet group; Uncl, unassigned genus level taxonomy. HP, n = 9; SP, n = 8.

Fig. 3.
Fig. 3.

Acute mountain sickness (AMS) severity is associated with gastrointestinal (GI) symptoms, and changes in fecal microbiota composition. Lake Louise scores (A), serum cortisol (B), GI symptomology (C), lactulose:mannitol ratio (L:M; D), and α-diversity (E) by AMS severity group (no/mild vs. moderate/severe). A–D: data are means ± SE and analyzed by marginal models or mixed models controlling for diet group, age, body mass index, and baseline value. *Different from no/mild AMS (P < 0.05). F: principle coordinates analysis of Bray-Curtis dissimilarities. Individual data points represent the entire fecal microbiota community of a single individual at one point in time. Samples closer together are more similar than samples farther apart. G: log2-fold change in relative abundance from SL to HA2 in taxa demonstrating significant AMS group-by-time interactions (false discovery rate <0.20). #Significant within group difference from SL. HA, high altitude; SL, sea level; Uncl, unassigned genus level taxonomy. No/mild AMS, n = 6; moderate/severe AMS, n = 11.

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