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Predicting outcomes in patients with pneumonia is challenging as the disease is complex and influenced by various factors.
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Multiomic Analyses Identify New Pneumonia Biomarkers

Some nine sets of metagenomic and transcriptomic biomarkers outperformed existing clinical prediction models

BGI Genomics
Published:Sep 21, 2023
|2 min read
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Community-acquired pneumonia (CAP) is a major infectious disease worldwide and contributes to high mortality and massive economic burden. Hospital mortality among the severe CAP (SCAP) remains high, ranging from 25 percent to more than 50 percent.

Early identification of patients at high risk of death is essential for improving patient outcomes. However, predicting outcomes in patients with SCAP is challenging, as the disease is complex and influenced by various factors, including the types of pathogens causing the infection, the host immune response, and underlying medical conditions.

In this study published in eBioMedicine, a team led by Jinmin Ma, PhD, BGI Genomics Infection Department chief science officer, and Jieming Qu, MD, professor, Ruijin Hospital, conducted research on SCAP patients to explore the pulmonary microbiota and host responses of different outcomes since the genetic differences could be detected more easily in the most severe patients as opposed to mildly severe patients.

Methods and Findings

BGI Genomics researchers used metagenomic and transcriptomic analysis to identify a new set of biomarkers that can predict 30-day mortality in patients with SCAP. The study included 275 patients with SCAP from 18 hospitals in China.

Researchers performed DNA and RNA-based metagenomic next-generation sequencing of bronchoalveolar lavage ?uid (BALF), sputum, and blood samples from 275 SCAP patients with varied characteristics and outcomes to analyze the differences in the microbes and host responses between them.

The researchers identified nine sets of biomarkers, both metagenomic and transcriptomic, that were associated with 30-day mortality.

The biomarkers were validated in an independent cohort of patients with SCAP and were able to predict 30-day mortality with an accuracy of 85 percent. This is significantly higher than the accuracy of existing clinical prediction models, which typically have accuracies of around 70 percent.

Other key findings

The study revealed that 30-day mortality was independent of pathogen category, microbial diversity, or speci?c microbial taxa, while significant differences in host gene expression patterns were suggested to be responsible for different outcomes.

Clinical characteristics analysis showed that male sex with age over 55 years was a risk factor for poor prognosis, and speci?c enrichment of genes and signaling pathways were found in omics data.

Potential of Biomarkers Utilization

The new biomarkers could have the following potential benefits for patients with SCAP:

  • Improve the accuracy of predicting and reducing mortality, which could lead to better clinical decision-making.

  • Identify patients at high risk of death, who could then be targeted with more aggressive treatment.

  • Reduce the need for invasive procedures, such as lung biopsies, which are associated with risks.

  • Improve the allocation of healthcare resources by identifying patients who are most likely to benefit from intensive care.

  • Develop new therapeutic strategies by identifying biomarkers that are associated with poor outcomes.

- This press release was originally published on the BGI Genomics website