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Nasal microbiota is a potential diagnostic biomarker of sepsis
Last reviewed: 02.07.2025
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The nasal microbiota of intensive care unit (ICU) patients effectively distinguishes sepsis from non-septic cases and is superior to gut microbiota analysis in predicting sepsis, according to a new study published in Microbiology Spectrum.
"These findings have implications for the development of diagnostic strategies and progress in the treatment of critical illness," said corresponding author of the study, Professor Jiaolong He, MD, PhD, of the Microbiome Medical Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
"In the past, we've focused more on the gut microbiota of patients with sepsis, but it's also worth looking at the respiratory microbiota."
Sepsis is a severe disease with a high mortality rate ranging from 29.9% to 57.5%. Despite the establishment of the third international consensus definition of sepsis and septic shock (Sepsis-3) in 2016, many aspects of sepsis still require further study to improve its diagnosis.
The evolution of diagnostic criteria from Sepsis-1 to Sepsis-3 demonstrates the need for continued research. In addition, diagnostic criteria for sepsis have moved from focusing solely on the inflammatory response to also including organ failure caused by infection.
Although significant progress has been made in the diagnosis of sepsis, biological markers with high sensitivity and specificity have not been identified. In addition, low culture positivity rates and few culturable organisms limit the diagnosis of clinical sepsis. Therefore, identifying a new, effective, and reliable biomarker for sepsis was the goal of the researchers.
In the new study, the researchers recruited 157 subjects (89 with sepsis) of both sexes at the Affiliated Hospital of Southern Medical University. They collected nasal swabs and fecal samples from septic and non-septic patients in the ICU and the respiratory and critical care department.
The scientists extracted and sequenced DNA using Illumina technology. Bioinformatics, statistical analysis, and machine learning methods were used to differentiate between septic and non-septic patients.
He and colleagues found that the nasal microbiota of septic patients had significantly lower overall community richness (P=0.002) and distinct composition (P=0.001) compared with non-septic patients. Corynebacterium, Staphylococcus, Acinetobacter, and Pseudomonas were identified as enriched genera in the nasal microbiota of septic patients.
"Going forward, we suggest the potential for further studies, perhaps using animal models or larger patient cohorts, to further our understanding of the role of the microbiota in sepsis beyond the antibiotic effect," He said.