Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Duvallet, Claire; Gibbons, Sean; Gurry, Thomas; Irizarry, Rafael; Alm, Eric
• Is Part Of: Nature communications. Volume 8:Issue 1(2017)
• Page Start: 1
• Page End: 10
• Publication Date: 2017-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-017-01973-8
• Languages: English
• ISSNs: 2041-1723

Abstract

Abstract Hundreds of clinical studies have demonstrated associations between the human microbiome and disease, yet fundamental questions remain on how we can generalize this knowledge. Results from individual studies can be inconsistent, and comparing published data is further complicated by a lack of standard processing and analysis methods. Here we introduce the MicrobiomeHD database, which includes 28 published case–control gut microbiome studies spanning ten diseases. We perform a cross-disease meta-analysis of these studies using standardized methods. We find consistent patterns characterizing disease-associated microbiome changes. Some diseases are associated with over 50 genera, while most show only 10–15 genus-level changes. Some diseases are marked by the presence of potentially pathogenic microbes, whereas others are characterized by a depletion of health-associated bacteria. Furthermore, we show that about half of genera associated with individual studies are bacteria that respond to more than one disease. Thus, many associations found in case–control studies are likely not disease-specific but rather part of a non-specific, shared response to health and disease. Reported associations between the human microbiome and disease are often inconsistent. Here, Duvallet et al. perform a meta-analysis of 28 gut microbiome studies spanning ten diseases, and find associations that are likely not disease-specific but potentially part of a shared response to disease.