Cell-Free DNA as Biomarker for Sepsis by Integration of Microbial and Host Information.
BACKGROUND: Cell-free DNA (cfDNA) is emerging as a biomarker for sepsis. Previous studies have been focused mainly on identifying blood infections or simply quantifying cfDNA. We propose that by characterizing multifaceted unexplored components, cfDNA could be more informative for assessing this com...
| Publicado en: | Clinical Chemistry Vol. 68; no. 9; pp. 1184 - 1196 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Oxford University Press / USA
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159050693&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159050693 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00099147 10CS jtl: Clinical Chemistry issn: 00099147 maglogo: N pubinfo: dt: Sep2022 vid: 68 iid: 9 pid: 622 pub: Oxford University Press / USA artinfo: ui: 159050693 10.1093/clinchem/hvac097 159050693 ppf: 1184 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Cell-Free DNA as Biomarker for Sepsis by Integration of Microbial and Host Information. aug: au: Qiuyu Jing Chi Hung Czarina Leung Wu, Angela Ruohao affil: Division of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, China sug: ab: BACKGROUND: Cell-free DNA (cfDNA) is emerging as a biomarker for sepsis. Previous studies have been focused mainly on identifying blood infections or simply quantifying cfDNA. We propose that by characterizing multifaceted unexplored components, cfDNA could be more informative for assessing this complex syndrome. METHODS: We explored multiple aspects of cfDNA in septic and nonseptic intensive care unit (ICU) patients by metagenomic sequencing, with longitudinal measurement and integrative assessment of plasma cfDNA quantity, human cfDNA fragmentation patterns, infecting pathogens, and overall microbial composition. RESULTS: Septic patients had significantly increased cfDNA quantity and altered human cfDNA fragmentation pattern. Moreover, human cfDNA fragments appeared to comprise information about cellular oxidative stress and could indicate disease severity. Metagenomic sequencing was more sensitive than blood culture in detecting bacterial infections and allowed for simultaneous detection of viral pathogens. We found differences in microbial composition between septic and nonseptic patients and between survivors and nonsurvivors by 28-day mortality, both on the first day of ICU admission and across the study period. By integrating all the information into a machine learning model, we achieved improved performance in identifying sepsis and prediction of clinical outcome for ICU patients with areas under the curve of 0.992 (95% CI 0.969-1.000) and 0.802 (95% CI 0.605-0.999), respectively. CONCLUSIONS: We were able to diagnose sepsis and predict mortality as soon as the first day of ICU admission by integrating multifaceted cfDNA information obtained in a single metagenomic assay; this approach could provide important advantages for clinical management and for improving outcomes in ICU patients. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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