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

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.

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Publication Details

Journal
Cell
Published
2024-11-13
DOI
https://doi.org/10.1016/j.cell.2024.10.022
Citations
78
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
18.00

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article

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

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78 citations
Cell
Gut microbiota and health
18.00
article

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

Stefanie Kandels‐Lewis, Oliver Aasmets, Suguru Nishijima, Anja Telzerow, Elin Org, Evelina Stankevič, Jens‐Christian Holm, Julie Steen Pedersen, Trine Nielsen, Jonel Trebicka, Anthony Fullam, Robert Schierwagen, Louise Aas Holm, Mads Israelsen, Helene Bæk Juel, Aleksander Krag, Cristina Legido‐Quigley, Hans Olav Melberg, Rajna Hercog, Manimozhiyan Arumugam, Christian Schudoma, Flemming Bendtsen, Shahriyar Mahdi Robbani, Nikolaj Torp, M.A. Karsdal, Maja Thiele, Thomas Schmidt, Peer Bork, Naoyoshi Nagata, Pamela Ferretti, Michael Kuhn, Charlotte Brøns, Matthias Mann, Ema Anastasiadou, Cilius Esmann Fonvig, Torben Hansen, M. Keller, Hans Israelsen, Jelle Matthijnssens, Dienty Hendrina Maria Johanna Hazenbrink
article en
78 citations

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.

CellVol. 188(1)
University of Copenhagen (DK), Steno Diabetes Centers (DK), University of Ulster (GB), Tokyo Medical University (JP), University of Southern Denmark (DK), Max Delbrück Center (DE), University of Münster (DE), University of Würzburg (DE), Novo Nordisk Foundation (DK), Odense University Hospital (DK), Hvidovre Hospital (DK), Copenhagen University Hospital (DK), European Foundation for the Study of Chronic Liver Failure (ES), European Molecular Biology Laboratory (DE), Holbæk Sygehus (DK), European Molecular Biology Laboratory (DE), Corewell Health Zeeland Hospital (US), University of Tartu (EE)
Hjerteforeningen, Uehara Memorial Foundation, Japan Agency for Medical Research and Development, Innovationsfonden, Steno Diabetes Center Copenhagen, European Commission, Deutsche Forschungsgemeinschaft, Eesti Teadusagentuur, EMBO, Ministry of Health, Labour and Welfare, Novo Nordisk, Region Sjælland, Novo Nordisk Fonden, Estonian Research Competency Council, Horizon 2020
Zero hunger
Openalex Percentile: Top 0%
Gut microbiota and health
18.00
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