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Researchers On the Verge of Identifying Biomarkers to Predict Dengue Disease Course

An international team of researchers believes they may be on the verge of identifying biomarkers that can be used to predict disease course in dengue fever, thereby enabling clinicians to triage patients at higher risk for severe forms of the mosquito-borne infection at an earlier stage.

An international team of researchers believes they may be on the verge of identifying biomarkers that can be used to predict disease course in dengue fever, thereby enabling clinicians to triage patients at higher risk for severe forms of the mosquito-borne infection at an earlier stage.

In a study published in the journal PLOS Neglected Tropic Diseases, the team of microbiologists, biologists, and infectious disease specialists from the US, Mexico, and Nicaragua used exploratory metabolomics to identify metabolites or small molecule biomarkers (SMBs) in serum specimens associated with distinct dengue virus (DENV) infection. At present, there are no standardized biomarkers or algorithms available for determining prognosis of severe dengue disease outcomes. This presents an acute clinical challenge in areas affected by the infection, of which there are up to 100 million reported cases each year worldwide, according to the US Centers for Disease Control and Prevention (CDC).

Of these reported cases, several hundred thousand develop dengue hemorrhagic fever, a more serious form of dengue. If the findings of the PLOS paper can be confirmed in future study, an early predictor of dengue hemorrhagic fever/dengue shock syndrome would enable clinicians to provide patients at higher risk for this form of the disease with the acute care needed to improve outcomes.

In addition, increased knowledge of the metabolic profile of dengue patients may also lead to greater understanding of the intracellular pathways instrumental in infection, replication, and pathogenesis.

“The ability to predict severe dengue disease outcomes using acute phase clinical specimens would be of enormous value to physicians and health care workers for appropriate triaging of patients for clinical management,” the authors write. “Advances in the field of metabolomics and analytic software provide new opportunities to identify host SMBs in acute phase clinical specimens that differentiate dengue disease outcomes.”

To assess the applicability of new diagnostic technologies in the setting of dengue fever, the authors of the PLOS paper performed exploratory metabolomic studies on retrospectively obtained serum samples from dengue patients in Nicaragua and Mexico. Hydrophilic interaction liquid chromatography mass spectrometry (MS) of the samples identified small molecule metabolites that were associated and statistically differentiated dengue fever, dengue hemorrhagic fever/dengue shock syndrome, and non-dengue diagnosis groups.

In the Nicaraguan samples, 191 metabolites differentiated dengue fever from non-dengue outcomes and 83 differentiated dengue hemorrhagic fever/dengue shock syndrome and dengue outcomes. In the Mexican samples, 306 metabolites differentiated dengue fever from non-dengue and 37 differentiated dengue hemorrhagic fever/dengue shock syndrome and dengue fever outcomes.

The authors confirmed the structural identities of 13 metabolites using tandem MS, and metabolomic analysis of serum samples from patients diagnosed with dengue fever who progressed to dengue hemorrhagic fever/dengue shock syndrome identified 65 metabolites that predicted outcomes. According to the authors, the differentiating metabolites also provide insights into metabolic pathways and pathogenic and immunologic mechanisms associated with dengue disease severity.

In their concluding remarks, the authors write, “Our studies confirm that DENV infection perturbs the human metabolome, [and] statistical analyses indicated that many metabolites and molecular features identified by MS had statistically significant differences in abundance in pairwise comparisons of the dengue fever, dengue hemorrhagic fever/dengue shock syndrome and non-dengue diagnosis groups. These results provide proof of concept that differential perturbation of the serum metabolome is associated with different dengue infections and disease outcomes and that changes in relative concentrations of certain metabolites are associated with dengue diagnosis groups.”

Brian P. Dunleavy is a medical writer and editor based in New York. His work has appeared in numerous healthcare-related publications. He is the former editor of Infectious Disease Special Edition.