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The role of gut microbiota in humans is of great interest, and metagenomics provided the possibilities for extensively analysing bacterial diversity in health and disease. Here we explored the human gut microbiome samples across 19 countries, performing compositional, functional and integrative analysis. To complement these data and analyse the stability of the microbiome, we followed 86 healthy Swedish individuals over one year, with four sampling times and extensive clinical phenotyping. The integrative analysis of temporal microbiome changes shows the existence of two types of species with a tendency to vary in abundance with time, here called outflow and inflow species. Importantly, the former tends to be enriched in disease, while the latter is enriched in health. We suggest that the decrease of disease-associated outflow and the increase of health-associated inflow species with time may be a fundamental albeit previously unrecognized aspect of the homeostasis maintenance in a healthy microbiome.

Background In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Results Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. Conclusion We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed. Electronic supplementary material The online version of this article (10.1186/s40168-018-0479-3) contains supplementary material, which is available to authorized users.