In:
Nature Microbiology, Springer Science and Business Media LLC, Vol. 7, No. 11 ( 2022-10-20), p. 1805-1816
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
2058-5276
DOI:
10.1038/s41564-022-01237-2
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2845610-5
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