Published June 4, 2025
| Version v1
Journal article
Open
Fecal metabolite profiling identifies critically ill patients with increased 30-day mortality
Creators
-
de Porto, Alexander P.1
- Dylla, Nicholas P.1
- Stutz, Matthew1
-
Lin, Huaiying1
- Khalid, Maryam1
-
Mullowney, Michael W.1
-
Little, Jessica1
-
Rose, Amber1
-
Moran, David1
- McMillin, Mary1
-
Burgo, Victoria1
-
Smith, Rita1
- Woodson, Che1
-
Metcalfe, Carolyn1
-
Ramaswamy, Ramanujam1
-
Lehmann, Christopher1
- Odenwald, Matthew1
- Bandealy, Nadeem1
-
Zhao, Jack1
-
Kim, Marie1
- Adler, Emerald1
-
Sundararajan, Anitha1
- Sidebottom, Ashley1
-
Kress, John P.1
- Wolfe, Krysta S.1
-
Pamer, Eric G.1
-
Patel, Bhakti K.1
- 1. University of Chicago
Description
Critically ill patients admitted to the medical intensive care unit (MICU) have reduced intestinal microbiota diversity and altered microbiome-associated metabolite concentrations. Metabolites produced by the gut microbiota have been associated with survival of patients receiving complex medical treatments and thus might represent a treatable trait to improve clinical outcomes. We prospectively collected fecal specimens, defined microbiome compositions by shotgun metagenomic sequencing, and quantified microbiota-derived fecal metabolites by mass spectrometry from 196 critically ill patients admitted to the MICU for non–COVID-19 respiratory failure or shock to correlate microbiota features and metabolites with 30-day mortality. Microbiota compositions of the first fecal sample after MICU admission did not independently associate with 30-day mortality. We developed a metabolic dysbiosis score (MDS) that uses fecal concentrations of 13 microbiota-derived metabolites, which predicted 30-day mortality independent of known confounders. The MDS complements existing tools to identify patients at high risk of mortality by incorporating potentially modifiable, microbiome-related, independent contributors to host resilience.
Data availability
Metabolomics data is available at https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=24a010b7e6a34ac88cd45b3848c88cc0. Metagenomics sequencing data is available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1134172. The code used in this paper is available at https://zenodo.org/records/14968628. All other data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.Files
sciadv.adt1466.pdf
Files
(2.3 MB)
| Name | Size | Download all |
|---|---|---|
|
Article md5:634df3c9527a79ca9417599fb28fe881 |
1.8 MB | Preview Download |
|
Supplementary Materials md5:9c315be79d38aaf853e58bcd6683404e |
541.0 kB | Preview Download |
Additional details
Identifiers
- DOI
- 10.1126/sciadv.adt1466
- Other
- oai:uchicago.tind.io:15462
Funding
- National Institutes of Health
- UL1 TR000430
- National Heart, Lung, and Blood Institute
- K23 HL148387
- Unknown funder
- Niels Stensen Fellowship
- University of Chicago