Global and cell type-specific immunological hallmarks of severe dengue progression identified via a systems immunology approach.

Severe dengue (SD) is a major cause of morbidity and mortality. To define dengue virus (DENV) target cells and immunological hallmarks of SD progression in children's blood, we integrated two single-cell approaches capturing cellular and viral elements: virus-inclusive single-cell RNA sequencing (viscRNA-Seq 2) and targeted proteomics with secretome analysis and functional assays. Beyond myeloid cells, in natural infection, B cells harbor replicating DENV capable of infecting permissive cells. Alterations in cell type abundance, gene and protein expression and secretion as well as cell-cell communications point towards increased immune cell migration and inflammation in SD progressors. Concurrently, antigen-presenting cells from SD progressors demonstrate intact uptake yet impaired interferon response and antigen processing and presentation signatures, which are partly modulated by DENV. Increased activation, regulation and exhaustion of effector responses and expansion of HLA-DR-expressing adaptive-like NK cells also characterize SD progressors. These findings reveal DENV target cells in human blood and provide insight into SD pathogenesis beyond antibody-mediated enhancement.

Magnitude and kinetics of the human immune cell response associated with severe dengue progression by single-cell proteomics.

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.

An 8-gene machine learning model improves clinical prediction of severe dengue progression.

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.

Heterogeneity of dengue transmission in an endemic area of Colombia.

Population based serological surveys are the gold-standard to quantify dengue (DENV) transmission. The purpose of this study was to estimate the age-specific seroprevalence and the force of infection of DENV in an endemic area of Colombia. Between July and October 2014, we conducted a household based cross-sectional survey among 1.037 individuals aged 2 to 40 years living in 40 randomly selected locations in urban Piedecuesta, Santander, Colombia. In addition, we also enrolled 246 indviduals living in rural "veredas". Participants were asked to answer a questionnaire that included demographic, socioeconomic and environmental questions and to provide a 5 ml blood sample. Sera were tested using the IgG indirect ELISA (Panbio) kit to determine past DENV infection. The overall DENV seroprevalence was 70% (95% CI = 67%-71%), but was significantly higher in urban (81%, 95% CI = 78%-83%) as compared to rural (21%, 95% CI = 17%-27%) locations. Age was a major predictor of seropositivity, consistent with endemic circulation of the virus. Using catalytic models we estimated that on average, 12% (95%CI = 11%-13%) of susceptible individuals living in the city are infected by DENV each year. Beyond age, the only predictor of seropositivity in urban locations was prior history of dengue diagnosed by a physician (aPR 1.15, 95% CI = 0.98-1.35). Among participants living in rural settings, those that reported traveling outside of their vereda were more likely to be seropositive (aPR 3.60, 95%CI = 1.54-8.42) as well as those who were born outside of Santander department (aPR = 2.77, 95%CI = 1.20-6.37). These results are consistent with long term endemic circulation of DENV in Piedecuesta, with large heterogeneities between urban and rural areas located just a few kilometers apart. Design of DENV control interventions, including vaccination, will need to consider this fine scale spatial heterogeneity.