Deep sequencing of the gut microbiomes of 1,135 participants from a Dutch population-based cohort shows relations between the microbiome and 126 exogenous and intrinsic host factors, including 31 intrinsic factors, 12 diseases, 19 drug groups, 4 smoking categories, and 60 dietary factors. These factors collectively explain 18.7% of the variation seen in the inter-individual distance of microbial composition. We could associate 110 factors to 125 species and observed that fecal Chromogranin A (CgA), a protein secreted by enteroendocrine cells, was exclusively associated with 61 microbial species whose abundance collectively accounted for 53% of microbial composition. Low CgA levels were seen in individuals with a more diverse microbiome. These results are an important step towards better understanding of environment-diet-microbe-host interactions.

Background and aimsProton pump inhibitors (PPIs) are among the top 10 most widely used drugs in the world. PPI use has been associated with an increased risk of enteric infections, most notably Clostridium difficile. The gut microbiome plays an important role in enteric infections, by resisting or promoting colonisation by pathogens. In this study, we investigated the influence of PPI use on the gut microbiome.MethodsThe gut microbiome composition of 1815 individuals, spanning three cohorts, was assessed by tag sequencing of the 16S rRNA gene. The difference in microbiota composition in PPI users versus non-users was analysed separately in each cohort, followed by a meta-analysis.Results211 of the participants were using PPIs at the moment of stool sampling. PPI use is associated with a significant decrease in Shannon's diversity and with changes in 20% of the bacterial taxa (false discovery rate <0.05). Multiple oral bacteria were over-represented in the faecal microbiome of PPI-users, including the genus Rothia (p=9.8×10−38). In PPI users we observed a significant increase in bacteria: genera Enterococcus, Streptococcus, Staphylococcus and the potentially pathogenic species Escherichia coli.ConclusionsThe differences between PPI users and non-users observed in this study are consistently associated with changes towards a less healthy gut microbiome. These differences are in line with known changes that predispose to C. difficile infections and can potentially explain the increased risk of enteric infections in PPI users. On a population level, the effects of PPI are more prominent than the effects of antibiotics or other commonly used drugs.

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Further information on research design is available in the Life Sciences Reporting Summary linked to this article. Data availability The LifeLines-DEEP metagenomics sequencing data are available at the European Genome-phenome Archive (EGA), with access code EGAS00001001704. Genotype and phenotype data can be requested from the Lifelines Biobank https://www.lifelines.nl/ researcher/biobank-lifelines/application-process. Summary statistics for metabolic traits were downloaded from MAGIC, GIANT and DIAGRAM websites (see URLs).

The gut microbiome is affected by multiple factors, including genetics. In this study, we assessed the influence of host genetics on microbial species, pathways and gene ontology categories, on the basis of metagenomic sequencing in 1,514 subjects. In a genome-wide analysis, we identified associations of 9 loci with microbial taxonomies and 33 loci with microbial pathways and gene ontology terms at P < 5 × 10. Additionally, in a targeted analysis of regions involved in complex diseases, innate and adaptive immunity, or food preferences, 32 loci were identified at the suggestive level of P < 5 × 10. Most of our reported associations are new, including genome-wide significance for the C-type lectin molecules CLEC4F-CD207 at 2p13.3 and CLEC4A-FAM90A1 at 12p13. We also identified association of a functional LCT SNP with the Bifidobacterium genus (P = 3.45 × 10) and provide evidence of a gene-diet interaction in the regulation of Bifidobacterium abundance. Our results demonstrate the importance of understanding host-microbe interactions to gain better insight into human health.