Related Experiment Video
Updated: Jul 23, 2025
Simplified Whole Body Plethysmography to Characterize Lung Function During Respiratory Melioidosis
Published on: February 24, 2023
IL-1R2-based biomarker models predict melioidosis mortality independent of clinical data
Taniya Kaewarpai1, Shelton W Wright2, Thatcha Yimthin1
1Department of Microbiology and Immunology, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Introduction:
Melioidosis is an often-fatal tropical infectious disease caused by the Gram-negative bacillus Burkholderia pseudomallei, but few studies have identified promising biomarker candidates to predict outcome.
Methods:
In 78 prospectively enrolled patients hospitalized with melioidosis, six candidate protein biomarkers, identified from the literature, were measured in plasma at enrollment. A multi-biomarker model was developed using least absolute shrinkage and selection operator (LASSO) regression, and mortality discrimination was compared to a clinical variable model by receiver operating characteristic curve analysis. Mortality prediction was confirmed in an external validation set of 191 prospectively enrolled patients hospitalized with melioidosis.
Results:
LASSO regression selected IL-1R2 and soluble triggering receptor on myeloid cells 1 (sTREM-1) for inclusion in the candidate biomarker model. The areas under the receiver operating characteristic curve (AUC) for mortality discrimination for the IL-1R2 + sTREM-1 model (AUC 0.81, 95% CI 0.72-0.91) as well as for an IL-1R2-only model (AUC 0.78, 95% CI 0.68-0.88) were higher than for a model based on a modified Sequential Organ Failure Assessment (SOFA) score (AUC 0.69, 95% CI 0.56-0.81, p < 0.01, p = 0.03, respectively). In the external validation set, the IL-1R2 + sTREM-1 model (AUC 0.86, 95% CI 0.81-0.92) had superior 28-day mortality discrimination compared to a modified SOFA model (AUC 0.80, 95% CI 0.74-0.86, p < 0.01) and was similar to a model containing IL-1R2 alone (AUC 0.82, 95% CI 0.76-0.88, p = 0.33).
Conclusion:
Biomarker models containing IL-1R2 had improved 28-day mortality prediction compared to clinical variable models in melioidosis and may be targets for future, rapid test development.
Insights
This study identified Interleukin-1 receptor 2 (IL-1R2) and soluble triggering receptor on myeloid cells 1 (sTREM-1) as promising biomarkers for predicting melioidosis mortality. These protein biomarkers improve outcome prediction compared to traditional clinical scores.
Area of Science:
- Infectious Diseases
- Biomarker Discovery
- Clinical Diagnostics
Background:
- Melioidosis, a tropical infectious disease caused by *Burkholderia pseudomallei*, has a high mortality rate.
- Effective prediction of melioidosis outcomes is crucial for timely intervention.
- Limited studies have identified reliable biomarkers for predicting melioidosis prognosis.
Purpose of the Study:
- To identify and validate protein biomarkers for predicting 28-day mortality in patients hospitalized with melioidosis.
- To develop and assess a multi-biomarker model for improved mortality prediction.
- To compare the performance of biomarker models against established clinical scoring systems.
Main Methods:
- Six candidate protein biomarkers were measured in plasma from 78 prospectively enrolled melioidosis patients.
- Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to develop a multi-biomarker model.
- Receiver Operating Characteristic (ROC) curve analysis compared the discriminatory ability of biomarker models and a modified Sequential Organ Failure Assessment (SOFA) score.
- The model's performance was validated in an independent cohort of 191 patients.
Main Results:
- LASSO regression selected IL-1R2 and sTREM-1 for the optimal biomarker model.
- The IL-1R2 + sTREM-1 model demonstrated superior 28-day mortality prediction (AUC 0.81) compared to the modified SOFA score (AUC 0.69) in the initial cohort.
- In external validation, the IL-1R2 + sTREM-1 model (AUC 0.86) also outperformed the modified SOFA score (AUC 0.80).
- An IL-1R2-only model also showed strong predictive performance.
Conclusions:
- Biomarker models incorporating IL-1R2 significantly improved 28-day mortality prediction in melioidosis compared to clinical models.
- IL-1R2 and sTREM-1 are promising candidates for developing rapid diagnostic tests for melioidosis prognosis.
- Further research into these biomarkers could lead to improved patient management and outcomes.
