Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Nov 4:S0092-8674(24)01204-2.
doi: 10.1016/j.cell.2024.10.022. Online ahead of print.

Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations

Suguru Nishijima  1 , Evelina Stankevic  2 , Oliver Aasmets  3 , Thomas S B Schmidt  1 , Naoyoshi Nagata  4 , Marisa Isabell Keller  1 , Pamela Ferretti  1 , Helene Bæk Juel  2 , Anthony Fullam  1 , Shahriyar Mahdi Robbani  1 , Christian Schudoma  1 , Johanne Kragh Hansen  5 , Louise Aas Holm  6 , Mads Israelsen  5 , Robert Schierwagen  7 , Nikolaj Torp  5 , Anja Telzerow  1 , Rajna Hercog  1 , Stefanie Kandels  1 , Diënty H M Hazenbrink  1 , Manimozhiyan Arumugam  2 , Flemming Bendtsen  8 , Charlotte Brøns  9 , Cilius Esmann Fonvig  10 , Jens-Christian Holm  10 , Trine Nielsen  11 , Julie Steen Pedersen  8 , Maja Sofie Thiele  5 , Jonel Trebicka  12 , Elin Org  3 , Aleksander Krag  5 , Torben Hansen  2 , Michael Kuhn  13 , Peer Bork  14 ; GALAXY and MicrobLiver Consortia
Collaborators, Affiliations
Free article

Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations

Suguru Nishijima et al. Cell. .
Free article

Abstract

The microbiota in individual habitats differ in both relative composition and absolute abundance. While sequencing approaches determine the relative abundances of taxa and genes, they do not provide information on their absolute abundances. Here, we developed a machine-learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applying our prediction model to a large-scale metagenomic dataset (n = 34,539), we demonstrated that microbial load is the major determinant of gut microbiome variation and is associated with numerous host factors, including age, diet, and medication. We further found that for several diseases, changes in microbial load, rather than the disease condition itself, more strongly explained alterations in patients' gut microbiome. Adjusting for this effect substantially reduced the statistical significance of the majority of disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.

Keywords: absolute abundance; disease associations; gut microbiome; machine learning; microbial load; shotgun metagenomics.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests The authors declare no competing interests.

LinkOut - more resources