Human gut microbiota adaptation to high-altitude exposure: longitudinal analysis over acute and prolonged periods

Abstract

This study investigated the longitudinal effects of acute (7-day) and prolonged (3-month) high-altitude exposure on gut microbiota in healthy adult males, addressing the limited data available in human populations. A cohort of 406 healthy adult males was followed, and fecal samples were collected at three time points: baseline at 800 m (406 samples), 7 days after ascending to 4,500 m (406 samples), and 2 weeks post-return to 800 m following 3 months at high altitude (186 samples). High-throughput 16S ribosomal DNA sequencing was employed to analyze microbiota composition and diversity. Results revealed significant changes in alpha- and beta-diversity, with acute high-altitude exposure inducing more pronounced effects compared to prolonged exposure. Specifically, acute exposure increased opportunistic pathogens (Ruminococcus and Oscillibacter) but decreased beneficial short-chain fatty acid producers (Faecalibacterium and Bifidobacterium). Notably, these changes in microbiota persisted even after returning to low altitude, indicating long-term remodeling. Functional analyses revealed substantial changes in metabolic pathways, suggesting microbiota-driven adaptations to energy utilization under high-altitude hypoxic conditions. In summary, acute high-altitude exposure caused dramatic changes in gut microbiota, while prolonged exposure led to structural and functional reshaping. These findings enhance our understanding of how high-altitude environments reshape gut microbiota.

Importance: This study is the first to investigate the impact of high-altitude exposure on gut microbiota adaptation in a large-scale longitudinal cohort. It seeks to enhance understanding of how high-altitude environments reshape gut microbiota. Acute exposure to high altitude significantly affected both α-diversity and β-diversity of gut microbiota, with acute exposure causing more pronounced changes than prolonged adaptation, indicating temporary disruptions in microbial communities. Notable shifts in microbial abundance were observed, including increased levels of genera linked to hypoxic stress (e.g., Gemmiger, Ruminococcus, and Parabacteroides) and decreased levels of beneficial bacteria (e.g., Faecalibacterium, Roseburia, and Bifidobacterium), suggesting possible adverse health effects. Functional analysis indicated changes in metabolism-related pathways post-exposure, supporting the idea that high-altitude adaptations involve metabolic adjustments for energy management. These findings enhance understanding of high-altitude physiology, illustrating the role of gut microbiota in hypoxic health.

Keywords: 16S rDNA; dysbacteriosis; gut microbiota; high altitude; longitudinal effects.

Fig 1

Overview of the analysis pipeline. The fecal and baseline characteristics were collected and analyzed from populations at different altitudes. The fecal samples were subjected to the 16S rRNA gene sequencing followed by diversity analysis, bacterial composition analysis, linear differential analysis, and KEGG functional pathway.

Fig 2

Alpha-diversity index box plot. The community richness between G-I, G-II, and G-III is shown in A (observed species diversity index) and B (Chao1 index), and the species diversity of microbiota is shown in C (Shannon diversity) and D (Simpson diversity index). The horizontal axis represents the sample grouping, and the vertical axis represents the α-diversity index value of different groups.

Fig 3

Microbial community structure between three groups. (A) Unweighted UniFrac PCoA. (B) PCoA of weighted UniFrac. The percentage represents the contribution rate of the principal dimension to the sample difference.

Fig 4

Species classification and abundance analysis of three groups. (A) The phylum bar graph of the intestinal microbiota of each group. (B) Heatmap clustering analysis at the phylum classification level. Z-score normalization is now performed horizontally across the three groups for each phylum/genus, with group averages calculated prior to normalization. The use of color gradients clearly illustrates the different enrichment patterns (highest values are red, and lowest values are purple). (C) The genus bar graph of the intestinal microbiota of each group. (D) Heatmap clustering analysis at the genus classification level.

Fig 5

Significant difference analysis of gut microbiota of three groups. (A) Rank sum test analysis between groups (P < 0.05). (B and C) LEfSe analysis. The figure lists bacterial communities with LDA score (log 10 > 2) and P < 0.05. p, phylum; c, class; o, order; f, family; and g, genus. (D) Spearman correlation analysis of genera with significant differences among groups.

Fig 6

Microbiota functional analysis of three groups. (A) The enriched Kyoto Encyclopedia of Genes and Genomes database pathway of level 2. (B) The enriched KEGG pathway of level 3.

Fig 7

Spearman correlation analysis of genera with lifestyle factors. ⁺P < 0.05 and *P < 0.01.