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Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults
- Kalantar, Katrina L;
- Neyton, Lucile;
- Abdelghany, Mazin;
- Mick, Eran;
- Jauregui, Alejandra;
- Caldera, Saharai;
- Serpa, Paula Hayakawa;
- Ghale, Rajani;
- Albright, Jack;
- Sarma, Aartik;
- Tsitsiklis, Alexandra;
- Leligdowicz, Aleksandra;
- Christenson, Stephanie A;
- Liu, Kathleen;
- Kangelaris, Kirsten N;
- Hendrickson, Carolyn;
- Sinha, Pratik;
- Gomez, Antonio;
- Neff, Norma;
- Pisco, Angela;
- Doernberg, Sarah B;
- Derisi, Joseph L;
- Matthay, Michael A;
- Calfee, Carolyn S;
- Langelier, Charles R
- et al.
Published Web Location
https://doi.org/10.1038/s41564-022-01237-2Abstract
We carried out integrated host and pathogen metagenomic RNA and DNA next generation sequencing (mNGS) of whole blood (n = 221) and plasma (n = 138) from critically ill patients following hospital admission. We assigned patients into sepsis groups on the basis of clinical and microbiological criteria. From whole-blood gene expression data, we distinguished patients with sepsis from patients with non-infectious systemic inflammatory conditions using a trained bagged support vector machine (bSVM) classifier (area under the receiver operating characteristic curve (AUC) = 0.81 in the training set; AUC = 0.82 in a held-out validation set). Plasma RNA also yielded a transcriptional signature of sepsis with several genes previously reported as sepsis biomarkers, and a bSVM sepsis diagnostic classifier (AUC = 0.97 training set; AUC = 0.77 validation set). Pathogen detection performance of plasma mNGS varied on the basis of pathogen and site of infection. To improve detection of virus, we developed a secondary transcriptomic classifier (AUC = 0.94 training set; AUC = 0.96 validation set). We combined host and microbial features to develop an integrated sepsis diagnostic model that identified 99% of microbiologically confirmed sepsis cases, and predicted sepsis in 74% of suspected and 89% of indeterminate sepsis cases. In summary, we suggest that integrating host transcriptional profiling and broad-range metagenomic pathogen detection from nucleic acid is a promising tool for sepsis diagnosis.
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