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.

[Stress test in the elderly. Clinical, hemodynamic, metabolic and electrocardiographic variables]

PURPOSE

To identify in the elderly adaptations imposed by exercise in both sexes.

METHODS

1528 stress tests were performed on subjects divided in: group I (GI) (90%) between 65 to 75 years old, and group II (GII) more than 75 years old. Protocols applied were Bruce (72%), and modified Naughton (28%). Clinical, hemodynamic and electrocardiographic variables were estimated as recommended by the World Health Organization, and the metabolic variables in the adapted Naughton protocols by the American College of Sports Medicine standards.

RESULTS

Analysis of GI and GII, respectively disclosed: 1) stress electrocardiogram (ECG): normal, 36 and 35%; ST depression, 20 and 22%; ST elevation, 6 and 1%; ventricular ectopic beats, 11 and 14%; supra ventricular ectopic beats, 5 and 6%; 2) metabolic and hemodynamic variables: the double-product: 26636 (+/-1539) and 23133 (+/-3218) mmHg X bpm (p < 0.0001). Maximum oxygen uptake measured in METS: GI, men, 7.7 (+/-1.9), women 5.4 (+/-0.8) (p < 0.0001); GII, NS, curve of systolic blood pressure: GI, men, 8.4 +/- (0.5), women, 10.6 (+/-1.8) mmHg/Met (p = 0.03); GII- NS. Difference of diastolic blood pressure and heart rate during exercise were similar between the two groups; 3) chest pain was the main clinical variable.

CONCLUSION

The more frequent indication for stress testing to evaluate chest pain in GI, did not correspond to a predominance of this symptom in this group, during exercise; in GI, in contrast to what is seen in the young, the curve of systolic blood pressure was greater in women; despite the greater prevalence of coronary artery disease in aged subjects, it was not observed significative differences between the two groups, to ischaemic ST depression.