The recent Zika virus (ZIKV) outbreak demonstrates that cost-effective clinical diagnostics are urgently needed to detect and distinguish viral infections to improve patient care. Unlike dengue virus (DENV), ZIKV infections during pregnancy correlate with severe birth defects, including microcephaly and neurological disorders. Because ZIKV and DENV are related flaviviruses, their homologous proteins and nucleic acids can cause cross-reactions and false-positive results in molecular, antigenic, and serologic diagnostics. We report the characterization of monoclonal antibody pairs that have been translated into rapid immunochromatography tests to specifically detect the viral nonstructural 1 (NS1) protein antigen and distinguish the four DENV serotypes (DENV1-4) and ZIKV without cross-reaction. To complement visual test analysis and remove user subjectivity in reading test results, we used image processing and data analysis for data capture and test result quantification. Using a 30-μl serum sample, the sensitivity and specificity values of the DENV1-4 tests and the pan-DENV test, which detects all four dengue serotypes, ranged from 0.76 to 1.00. Sensitivity/specificity for the ZIKV rapid test was 0.81/0.86, respectively, using a 150-μl serum input. Serum ZIKV NS1 protein concentrations were about 10-fold lower than corresponding DENV NS1 concentrations in infected patients; moreover, ZIKV NS1 protein was not detected in polymerase chain reaction-positive patient urine samples. Our rapid immunochromatography approach and reagents have immediate application in differential clinical diagnosis of acute ZIKV and DENV cases, and the platform can be applied toward developing rapid antigen diagnostics for emerging viruses.

Background Each year 3–6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. Methods We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were “locked” prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. Results We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2–100) sensitivity and 79.7% (95% CI 75.5–83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7–25.6) and 99.0% (95% CI 97.7–100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3–94.1) sensitivity and 39.7% (95% CI 34.7–44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. Conclusions The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

Background Dengue virus (DENV) infections pose one of the largest global barriers to human health. The four serotypes (DENV 1-4) present different symptoms and influence immune response to subsequent DENV infections, rendering surveillance, risk assessments, and disease control particularly challenging. Early diagnosis and appropriate clinical management is critical and can be achieved by detecting DENV nonstructural protein 1 (NS1) in serum during the acute phase. However, few NS1-based tests have been developed that are capable of differentiating DENV serotypes and none are currently commercially available. Methodology/Principle findings We developed an enzyme-linked immunosorbent assay (ELISA) to distinguish DENV-1-4 NS1 using serotype-specific pairs of monoclonal antibodies. A total of 1,046 antibodies PLOS NEGLECTED TROPICAL DISEASES

These findings highlight the ongoing coexistence of both arboviruses, a distinct clinical profile of each condition in the study area that could be used by clinicians to generate a differential diagnosis, and the presence of underreporting, mostly among hospitalised cases.

aportó el diseño del estudio, el análisis y la interpretación de los datos, la redacción y la revisión crítica del manuscrito. Rosa Margarita Gélvez contribuyó en la recolección y obtención de los resultados, la interpretación de los datos y la redacción del manuscrito. Jairo Antonio Rodríguez brindó soporte en la interpretación de datos y en la redacción del manuscrito. Doris Salgado brindó soporte en la redacción del manuscrito. Beatriz Parra contribuyó en la interpretación de los datos y la redacción del manuscrito. Lyda Osorio aportó al análisis y la interpretación de los datos, y en la redacción del manuscrito. Irene Bosch contribuyó en el análisis y la interpretación de los datos, y en la redacción del manuscrito. ARTÍCULO ORIGINAL Biomédica 2013;33(Supl. Introducción. Las estrategias encaminadas a identificar tempranamente a los pacientes con dengue que pudieran evolucionar a la forma grave de la enfermedad, son escasas. Objetivo. Evaluar la utilidad de los niveles séricos de algunos mediadores de la respuesta inmunitaria como biomarcadores tempranos de dengue grave. Materiales y métodos. En un diseño de casos y controles anidado en una cohorte multicéntrica de la Red AEDES, se compararon los niveles de TNFα, ST2, TRAIL e IDO en muestras obtenidas durante la fase temprana de la enfermedad. Resultados. Los niveles de ST2, TRAIL y TNFα fueron significativamente mayores en los pacientes que evolucionaron a dengue grave, comparados con los pacientes no complicados (p<0,0001) [¿¿ Odds ratio (OR)=24,8, IC 95% =6,1-98,0; OR=18,0, IC 95% =4,6-69,1; OR=NC, IC 95% =NC, respectivamente??]. No se observaron diferencias en los niveles de IDO entre los pacientes con dengue grave y aquellos con dengue no grave (p=1,0; OR=1,0, IC 95% =0,2-6,1). Conclusiones. En las primeras 96 horas de la infección por el virus del dengue, las cuantificaciones de ST2, TRAIL y TNFα contribuyen a predecir complicaciones de la enfermedad.Palabras clave: dengue, permeabilidad capilar, inflamación, índice de gravedad de la enfermedad, citocinas, predicción, humanos. doi: http://dx.doi.org/10.7705/biomedica.v33i0.733Biomarkers for the prognosis of severe dengue Introduction: There are very few strategies for the early detection of the patients who might develop the severe form of the illness. Objective: To evaluate the utility of serum levels of some immune response mediators as early biomarkers for the severe dengue prognosis during the early phase of the illness. Materials and methods: Using a case-control design nested in a multicenter cohort from the AEDES network (a Colombian multicenter study), we compared TNFα, ST2, TRAIL and IDO levels in samples which were obtained during the early phase of the illness. Results: ST2, TRAIL and TNFα levels were higher in severe dengue patients compared with uncomplicated patients (p<0.0001), as follows: OR=24.8, CI95%= 6.1-98.0; OR=18.0, CI95%= 4.6-69.1; OR=NC, CI95%= NC, respectively. We did not find statistically significant differences between IDO levels in severe dengue and uncomplicated dengue (...

Since its 2013 emergence in the Americas, Chikungunya virus (CHIKV) has posed a serious threat to public health. Early and accurate diagnosis of the disease, though currently lacking in clinics, is integral to enable timely care and epidemiological response. We developed a dual detection system: a CHIKV antigen E1/E2-based enzyme-linked immunosorbent assay (ELISA) and a lateral flow test using high-affinity anti-CHIKV antibodies. The ELISA was validated with 100 PCR-tested acute Chikungunya fever samples from Honduras. The assay had an overall sensitivity and specificity of 51% and 96.67%, respectively, with accuracy reaching 95.45% sensitivity and 92.03% specificity at a cycle threshold (Ct) cutoff of 22. As the Ct value decreased from 35 to 22, the ELISA sensitivity increased. We then developed and validated two lateral flow tests using independent antibody pairs. The sensitivity and specificity reached 100% for both lateral flow tests using 39 samples from Colombia and Honduras at Ct cutoffs of 20 and 27, respectively. For both lateral flow tests, sensitivity decreased as the Ct increased after 27. Because CHIKV E1/E2 are exposed in the virion surfaces in serum during the acute infection phase, these sensitive and specific assays demonstrate opportunities for early detection of this emerging human pathogen.

Approximately 5 million dengue virus–infected patients progress to a potentially life-threatening severe dengue (SD) infection annually. To identify the immune features and temporal dynamics underlying SD progression, we performed deep immune profiling by mass cytometry of PBMCs collected longitudinally from SD progressors (SDp) and uncomplicated dengue (D) patients. While D is characterized by early activation of innate immune responses, in SDp there is rapid expansion and activation of IgG-secreting plasma cells and memory and regulatory T cells. Concurrently, SDp, particularly children, demonstrate increased proinflammatory NK cells, inadequate expansion of CD16 + monocytes, and high expression of the FcγR CD64 on myeloid cells, yet a signature of diminished antigen presentation. Syndrome-specific determinants include suppressed dendritic cell abundance in shock/hemorrhage versus enriched plasma cell expansion in organ impairment. This study reveals uncoordinated immune responses in SDp and provides insights into SD pathogenesis in humans with potential implications for prediction and treatment.

Since its 2013 emergence in the Americas, chikungunya virus (CHIKV) has posed a serious threat to public health. Early and accurate diagnosis of the disease, though currently lacking in clinics, is integral to enable timely care and epidemiological response. We developed a dual detection system: a CHIKV antigen E1/E2-based enzyme-linked immunosorbent assay (ELISA) and a lateral flow test using high-affinity anti-CHIKV antibodies. The ELISA was validated with 100 PCR-tested acute Chikungunya fever samples from Honduras. The assay had an overall sensitivity and specificity of 51% and 96.67%, respectively, with accuracy reaching 95.45% sensitivity and 92.03% specificity at a Ct cutoff of 22. As the Ct value increased from 22, ELISA sensitivity decreased. We then developed and validated two lateral flow tests using independent antibody pairs. The sensitivity and specificity reached 100% for both lateral flow tests using 39 samples from Colombia and Honduras at Ct cutoffs of 20 and 27, respectively. For both lateral flow tests, sensitivity decreased as the Ct increased after 27. Because CHIKV E1/E2 are exposed in the virion surfaces in serum during the acute infection phase, these sensitive and specific assays demonstrate opportunities for early detection of this emerging human pathogen.