Early circulating biomarker signatures of dengue-associated plasma leakage uncovered by proteomics
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Background
Plasma leakage, a defining feature of severe dengue, lacks early predictive biomarkers critical for timely clinical decision-making. We aimed to characterize early proteomic signatures of dengue-associated plasma leakage using two complementary high-throughput platforms.
Methods
Febrile-phase plasma samples were collected from 222 dengue patients (stratified by plasma leakage and prior dengue exposure), 50 febrile non-dengue controls, and 6 healthy individuals. Proteomic profiling of pooled plasma was performed using liquid chromatography–tandem mass spectrometry (LC-MS/MS) and SomaScan aptamer-based platforms. Differential expression, pathway enrichment, and protein–protein interaction analyses were conducted to identify leakage-associated signatures.
Findings
We identified 23 proteins differentially expressed and validated across both platforms, and 108 (LC-MS/MS) and 3181 (SomaScan) proteins identified as differentially expressed by at least one platform, in patients who subsequently developed plasma leakage. Prior dengue exposure shaped the molecular response with secondary infections exhibiting multi-system inflammatory responses with metabolic dysregulation and immune signalling pathways. Network analysis revealed greater protein connectivity and more complex interaction clusters involving multiple biological pathways compared to primary infections.
Interpretation
This proteomic screening identified candidate biomarkers that merit validation in other cohorts to assess generalisability. Such validated biomarkers could be useful in predicting plasma leakage and hence triaging patients for hospital admission in future.
Funding
National Health and Medical Research Council of Australia (1173666); University of Colombo, Sri Lanka (AP/3/2/2017/CG/25).
Research in context
Evidence before this study
Plasma leakage is a defining feature of severe dengue and the earliest objective indicator of clinical deterioration. Early identification of patients at risk of leakage could improve triage and reduce complications, particularly in resource-limited settings. However, most studies to date have used composite outcomes such as severe dengue or dengue haemorrhagic fever, which are subject to more inter-observer bias. Our prior systematic review found limited high-certainty evidence for plasma leakage-specific predictive biomarkers. In follow-up experimental work guided by the systematic review, we identified proteins—such as VCAM-1, IL-33R, and CCL11—independently associated with plasma leakage. However, a comprehensive, untargeted proteomic screen could identify more predictive proteins for plasma leakage. Most previous proteomic studies used a single platform, focused on general dengue severity rather than vascular-specific outcomes, and did not stratify by infection history—despite secondary infection being an established risk factor for adverse outcomes. The extreme dynamic range of the plasma proteome, spanning over ten orders of magnitude, necessitates complementary high-throughput approaches for robust biomarker discovery.
Added value of this study
This is the first study to use two complementary high-throughput proteomics platforms— mass spectrometry and aptamer-based analysis—to identify early host protein signatures predictive of dengue-associated plasma leakage. We analysed febrile-phase plasma from a well-characterised prospective cohort with predefined clinical endpoints and stratification by prior dengue exposure. We identified 23 proteins consistently differentially expressed across both platforms. These included novel markers of metabolic stress, endothelial dysfunction, and liver-derived proteins. Network and pathway analyses further revealed distinct regulatory architectures in primary versus secondary dengue infections and identified topologically central proteins with high translational relevance.
Implications of all the available evidence
This study reframes plasma leakage in dengue as a clinically actionable, multi-system process involving immune, metabolic, and endothelial disruption, with dominant hepatic involvement. The 23 cross-validated biomarkers offer a practical foundation for developing early risk stratification tools to guide triage and monitoring decisions during the febrile phase—when patients still appear clinically stable but are at risk of rapid deterioration.
