Long-term instability of the intestinal microbiome is associated with metabolic liver disease, low microbiota diversity, diabetes mellitus and impaired exocrine pancreatic function

Abstract

Objective: The intestinal microbiome affects the prevalence and pathophysiology of a variety of diseases ranging from inflammation to cancer. A reduced taxonomic or functional diversity of the microbiome was often observed in association with poorer health outcomes or disease in general. Conversely, factors or manifest diseases that determine the long-term stability or instability of the microbiome are largely unknown. We aimed to identify disease-relevant phenotypes associated with faecal microbiota (in-)stability.

Design: A total of 2564 paired faecal samples from 1282 participants of the population-based Study of Health in Pomerania (SHIP) were collected at a 5-year (median) interval and microbiota profiles determined by 16S rRNA gene sequencing. The changes in faecal microbiota over time were associated with highly standardised and comprehensive phenotypic data to determine factors related to microbiota (in-)stability.

Results: The overall microbiome landscape remained remarkably stable over time. The greatest microbiome instability was associated with factors contributing to metabolic syndrome such as fatty liver disease and diabetes mellitus. These, in turn, were associated with an increase in facultative pathogens such as Enterobacteriaceae or Escherichia/Shigella. Greatest stability of the microbiome was determined by higher initial alpha diversity, female sex, high household income and preserved exocrine pancreatic function. Participants who newly developed fatty liver disease or diabetes during the 5-year follow-up already displayed significant microbiota changes at study entry when the diseases were absent.

Conclusion: This study identifies distinct components of metabolic liver disease to be associated with instability of the intestinal microbiome, increased abundance of facultative pathogens and thus greater susceptibility toward dysbiosis-associated diseases.

Keywords: E. coli; colonic microflora; diabetes mellitus; fatty liver; pancreas.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1

Scheme of study design. Paired microbiota profiles from Study of Health in Pomerania (SHIP)-2 and SHIP-3 participants (n=1282 at each time point) and corresponding SHIP-2 phenotype data were included into the analysis.

Figure 2

Stability of the faecal microbiome from Study of Health in Pomerania (SHIP)-2 to SHIP-3. (A) Stacked bar plots show the average faecal microbiota composition at SHIP-2 and SHIP-3. (B) Principal coordinate analysis (PCoA) of 2564 faecal microbiota samples obtained from 1282 individuals at SHIP-2 (orange dots) and SHIP-3 (blue dots). (C) Boxplots display the PCo1–PCo5 scores comparing SHIP-2 (orange boxes) to SHIP-3 (blue boxes) samples. Numbers in brackets below denote the percentage of variation explained by the respective PCo. The overall faecal microbiome landscape was quite stable from SHIP-2 to SHIP-3 with small but significant shifts along PCo1, PCo3 and PCo5. (D) Shown are the percentage changes in abundance of the 18 taxa with a significant increase (red) or decrease (blue) in abundance over time. All taxa are ordered according their mean abundance at SHIP-2 from top (most abundant) to bottom (least abundant). (E) Analysis of the taxon presence distribution from SHIP-2 to SHIP-3. Shown are the ORs and their respective 95% CIs at SHIP-3 compared with SHIP-2 as baseline of all 16 taxa with significant changes in their presence profiles. An OR over 1 indicates an increased likelihood for the respective taxon to be present in a SHIP-3 sample if it was not present in the same subject at SHIP-2, whereas an OR below 1 implies the loss of the respective taxon in SHIP-3 samples compared with SHIP-2. All taxa are ordered according to the percentage of samples with presence of the respective taxon at SHIP-2 from top (high presence) to bottom (low presence). (F) Comparison of alpha diversity between SHIP-2 and SHIP-3. Species richness (N0) was slightly reduced at follow-up, whereas no change was observed in Simpson diversity number (N2) or Shannon diversity index (H). Whiskers are drawn up to 1.5 times the IQR (outliers not shown). *Indicates significant difference. c, class; f, family; o, order; p, phylum.

Figure 3

Sankey plot displays the proportions of predicted metagenomic pathways with significantly (q

Figure 4

Contribution of phenotypic factors to faecal microbiome changes. Shown are the correlations between different phenotypic factors at SHIP-2 and global changes in the faecal microbiome from SHIP-2 to SHIP-3. Large positive associations indicate greater variation or instability in the faecal microbiome if the respective factor is distinctly elevated (continuous variables) or positive (binary variables). On the other hand, large negative associations suggest stability of the faecal microbiome. *Indicates significant associations (q

Figure 5

Associations between incident metabolic and cardiovascular diseases at SHIP-3 and faecal microbiota changes in the affected individuals at SHIP-2 (before the respective disease was present). (A) Individuals with incident fatty liver disease and diabetes mellitus at SHIP-3 already displayed gut microbiota changes at SHIP-2 prior to their diagnosis. (B) Associations of incident fatty liver disease with microbial taxa at SHIP-2 and SHIP-3. (C) Significant metabolite associations of incident fatty liver disease cases at SHIP-2 (left). The heatmap (right) indicates the association of the different disease-associated genera with the respective metabolites. (D) Associations of incident diabetes mellitus at SHIP-3 with microbial taxa at SHIP-2 and SHIP-3. (E) Significant metabolite associations of incident diabetes mellitus cases at SHIP-2 (left). The heatmap (right) indicates the association of the different disease-associated genera with the respective metabolites. Significant results are highlighted by a black frame. Unclassified taxa at genus level: (f): family, (o): order. DMA, dimethylarginine; H1, hexose; PC, phosphatidylcholine; SHIP, Study of Health in Pomerania; SM (OH), hydroxylated sphingomyelin.