Atypical lymphocyte count correlates with the severity of dengue infection

Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing

Dengue fever, a neglected tropical arboviral disease, has emerged as a global health concern in the past decade. Necessitating a nuanced comprehension of the intricate dynamics of host-virus interactions influencing disease severity, we analysed transcriptomic patterns using bulk RNA-seq from 112 age- and gender-matched NS1 antigen-confirmed hospital-admitted dengue patients with varying severity. Severe cases exhibited reduced platelet count, increased lymphocytosis, and neutropenia, indicating a dysregulated immune response. Using bulk RNA-seq, our analysis revealed a minimal overlap between the differentially expressed gene and transcript isoform, with a distinct expression pattern across the disease severity. Severe patients showed enrichment in retained intron and nonsense-mediated decay transcript biotypes, suggesting altered splicing efficiency. Furthermore, an up-regulated programmed cell death, a haemolytic response, and an impaired interferon and antiviral response at the transcript level were observed. We also identified the potential involvement of the RBM39 gene among others in the innate immune response during dengue viral pathogenesis, warranting further investigation. These findings provide valuable insights into potential therapeutic targets, underscoring the importance of exploring transcriptomic landscapes between different disease sub-phenotypes in infectious diseases.

Immuno-Haematologic Aspects of Dengue Infection: Biologic Insights and Clinical Implications

Dengue infection is caused by the dengue virus (DENV) and is transmitted to humans by infected female Aedes aegypti and Aedes albopictus mosquitoes. There are nearly 100 million new dengue cases yearly in more than 120 countries, with a five-fold increase in incidence over the past four decades. While many patients experience a mild illness, a subset suffer from severe disease, which can be fatal. Dysregulated immune responses are central to the pathogenesis of dengue, and haematologic manifestations are a prominent feature of severe disease. While thrombocytopaenia and coagulopathy are major causes of bleeding in severe dengue, leucocyte abnormalities are emerging as important markers of prognosis. In this review, we provide our perspective on the clinical aspects and pathophysiology of haematologic manifestations in dengue. We also discuss the key gaps in our current practice and areas to be addressed by future research.

Hematological parameters: is there a difference between those released by the hematological analyzer and to the customer?

OBJECTIVE

This study aimed to compare the hematological parameters released by hematological analyzers with those released in customer reports.

METHODS

We conducted a descriptive study in the laboratories of a medium-sized municipality in the state of Minas Gerais registered in the National Register of Health Establishments. Interviews were conducted using a questionnaire to obtain information regarding the parameters released by the analyzers and those available in the customer's report.

RESULTS

Sixteen laboratories were evaluated, and none of them released all the parameters obtained from the hematological analyzers to customers. The red blood cell distribution width was released in 88% of the laboratories, atypical lymphocytes in 70%, mean platelet volume in 50%, platelet distribution width and platelet count in 20%. No laboratory released information on reticulocytes, fraction of immature reticulocytes and immature granulocytes, nucleated erythrocyte count, immature platelet fraction and reticulocyte hemoglobin, and large platelet rate.

CONCLUSION

All evaluated clinical analysis laboratories had at least one parameter that was not released in the customer's report despite being released by the hematological analyzers. The lack of knowledge on the part of professionals about the clinical importance of each parameter of the complete blood count results in a loss in patient assessment, and it is important to include these parameters in the complete blood count report.

Early transcriptomic host response signatures in the serum of dengue patients provides insights into clinical pathogenesis and disease severity

Dengue virus (DENV), known to cause viral infection, belongs to the family Flaviviridae, having four serotypes (DENV1-4) that spreads by the bite of the Aedes aegypti mosquito. India has been suffering from dengue outbreaks annually with widespread epidemics by prevalence of all the four DENV serotypes. The diverse spectrum of clinical manifestations in dengue infection, mild to severe forms, makes the need of timely diagnosis and prompt treatment an essence. The identification of a dengue host response signature in serum can increase the understanding of dengue pathogenesis since most dengue NS1 Ag tests have been developed and evaluated in serum samples. Here, to understand the same, we undertook a dual RNA-sequencing (RNA-Seq) based approach from the serum samples of dengue-infected patients. The results thus yield the early transcriptional signatures that discriminated the high viral reads patients from patients who had low dengue viral reads. We identified a significant upregulation of two sets of genes, key antiviral (IFIT3, RSAD2, SAT1) and vascular dysfunction (TNFS10, CXCL8) related genes in the high viral reads group. Deeper delving of this gene profile revealed a unique two-way response, where the antiviral genes can mediate the disease course to mild, contrarily the increased expression of the other gene set might act as pointers of severe disease course. Further, we explored the hematologic parameters from the complete blood count (CBC), which suggests that lymphocytes (low) and neutrophils (high) might serve as an early predictor of prognosis in dengue infection. Collectively, our findings give insights into the foundation for further investigation of the early host response using the RNA isolated from dengue patients' serum samples and opens the door for careful monitoring of the early clinical and transcriptome profiles for management of the dengue patients.

Machine Learning-Based Detection of Dengue from Blood Smear Images Utilizing Platelet and Lymphocyte Characteristics

Dengue fever, also known as break-bone fever, can be life-threatening. Caused by DENV, an RNA virus from the Flaviviridae family, dengue is currently a globally important public health problem. The clinical methods available for dengue diagnosis require skilled supervision. They are manual, time-consuming, labor-intensive, and not affordable to common people. This paper describes a method that can support clinicians during dengue diagnosis. It is proposed to automate the peripheral blood smear (PBS) examination using Artificial Intelligence (AI) to aid dengue diagnosis. Nowadays, AI, especially Machine Learning (ML), is increasingly being explored for successful analyses in the biomedical field. Digital pathology coupled with AI holds great potential in developing healthcare services. The automation system developed incorporates a blob detection method to detect platelets and thrombocytopenia from the PBS images. The results achieved are clinically acceptable. Moreover, an ML-based technique is proposed to detect dengue from the images of PBS based on the lymphocyte nucleus. Ten features are extracted, including six morphological and four Gray Level Spatial Dependance Matrix (GLSDM) features, out of the lymphocyte nucleus of normal and dengue cases. Features are then subjected to various popular supervised classifiers built using a ten-fold cross-validation policy for automated dengue detection. Among all the classifiers, the best performance was achieved by Support Vector Machine (SVM) and Decision Tree (DT), each with an accuracy of 93.62%. Furthermore, 1000 deep features extracted using pre-trained MobileNetV2 and 177 textural features extracted using Local binary pattern (LBP) from the lymphocyte nucleus are subjected to feature selection. The ReliefF selected 100 most significant features are then fed to the classifiers. The best performance was attained using an SVM classifier with 95.74% accuracy. With the obtained results, it is evident that this proposed approach can efficiently contribute as an adjuvant tool for diagnosing dengue from the digital microscopic images of PBS.

Shapley-Additive-Explanations-Based Factor Analysis for Dengue Severity Prediction using Machine Learning

Dengue is a viral disease that primarily affects tropical and subtropical regions and is especially prevalent in South-East Asia. This mosquito-borne disease sometimes triggers nationwide epidemics, which results in a large number of fatalities. The development of Dengue Haemorrhagic Fever (DHF) is where most cases occur, and a large portion of them are detected among children under the age of ten, with severe conditions often progressing to a critical state known as Dengue Shock Syndrome (DSS). In this study, we analysed two separate datasets from two different countries- Vietnam and Bangladesh, which we referred as VDengu and BDengue, respectively. For the VDengu dataset, as it was structured, supervised learning models were effective for predictive analysis, among which, the decision tree classifier XGBoost in particular produced the best outcome. Furthermore, Shapley Additive Explanation (SHAP) was used over the XGBoost model to assess the significance of individual attributes of the dataset. Among the significant attributes, we applied the SHAP dependence plot to identify the range for each attribute against the number of DHF or DSS cases. In parallel, the dataset from Bangladesh was unstructured; therefore, we applied an unsupervised learning technique, i.e., hierarchical clustering, to find clusters of vital blood components of the patients according to their complete blood count reports. The clusters were further analysed to find the attributes in the dataset that led to DSS or DHF.

Elevated TNF-α Induces Thrombophagocytosis by Mononuclear Cells in ex vivo Whole-Blood Co-Culture with Dengue Virus

Background

Infection with dengue virus (DENV) causes hematological complications in dengue diseases characterized by thrombocytopenia accompanied by macrophage activation syndrome and hemophagocytosis in fatal patients.

Methods

In this study, we investigate the undefined mechanisms underlying the progression of thrombocytopenia caused by thrombophagocytosis based on an ex vivo whole-blood co-culture model of DENV infection for mimicking the acute febrile phase of infection.

Results

In this model, complete blood count test showed a decrease in monocytes (p < 0.01), but not neutrophils nor other white blood cells, accompanied by a low thrombocyte count (p < 0.01) in DENV infection with a positive correlation (r = 0.636, p < 0.05). Furthermore, DENV exposure caused significant thrombophagocytosis in mononuclear cells (p < 0.05). Abnormal production of tumor necrosis factor (TNF)-α was highly associated with induction of thrombophagocytosis (r = 0.758, p < 0.01), decreased monocytes (r = −0.758, p < 0.01), and decreased thrombocyte (r = −0.728, p < 0.01). Neutralizing TNF-α considerably (p < 0.05) reversed such DENV-induced effects and was further validated by immunostaining-based flow cytometry analysis on mononuclear CD14 positive monocytes. Exogenous administration of TNF-α effectively caused thrombophagocytosis accompanied by decreased monocytes and thrombocytes, probably causing monocyte activation.

Conclusion

These results demonstrate the potential pathogenesis of thrombocytopenia caused by TNF-α-induced thrombophagocytosis in monocytes during DENV infection.

The immature platelet fraction, a predictive tool for early recovery from dengue-related thrombocytopenia: a prospective study

BACKGROUND

There is a paucity of predictive factors for early recovery from thrombocytopenia related to dengue. The immature platelet fraction (IPF%) is reflective of megakaryopoiesis and may correlate with recovery from dengue-related thrombocytopenia. Our objective was to assess the predictive value of IPF% on days 2 and 3 of illness for recovery from dengue-related thrombocytopenia.

METHODS

A prospective study was conducted among patients with dengue admitted to our institution (Nawaloka Hospital PLC) from December 2019 to October 2020. Dengue was diagnosed based on positive non-structural antigen 1 or IgM. IPF% data were extracted from the Sysmex-XN-1000 automated hematology analyzer. Clinical data were obtained from electronic medical records. Statistical analyses were performed using SPSS version 20.

RESULTS

We included 240 patients. An IPF% on day 2 of illness of >7.15% had a sensitivity of 80.0% and specificity of 70.4% for prediction of platelet recovery (defined as platelet count ≥60×109/L) on day 7 of illness. An IPF% of >7.25% on day 3 of illness had a sensitivity of 88.9% and specificity of 47.1% for predicting platelet recovery >60×109/L on day 8 of illness. The IPF% was significantly lower in patients with severe dengue. Platelet recovery was observed within 48 h after the peak IPF% was reached, regardless of severity.

CONCLUSION

We propose that IPF% values on days 2 and 3 of illness are a promising predictive tool for early recovery from dengue-related thrombocytopenia.

Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections

The dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequent infections from a different serotype. We developed a stochastic model of the adaptive immune response to dengue infections. We first delineated the mechanisms initiating and sustaining adaptive immune responses during primary infections. We then contrasted these immune responses during secondary infections of either a homotypic or heterotypic serotype to understand the role of pre-existing and reactivated immune pathways on disease severity. Comparison of non-symptomatic and severe cases from heterotypic infections demonstrated that overproduction of specific antibodies during primary infection induces an enhanced population of cross-reactive antibodies during secondary infection, ultimately leading to severe disease manifestations. In addition, the level of disease severity was found to correlate with immune response kinetics, which was dependent on beginning lymphocyte levels. Our results detail the contribution of specific lymphocytes and antibodies to immunity and memory recall that lead to either protective or pathological outcomes, allowing for the understanding and determination of mechanisms of protective immunity.

The atypical lymphocyte count: a novel predictive factor for severe thrombocytopenia related to dengue

BACKGROUND

Early identification of patients at risk of severe dengue disease (DD) is critical to guide its management. We evaluated whether the atypical lymphocyte count (ALC), generated from the Sysmex automated full blood count analyzer, is predictive of severe thrombocytopenia secondary to Dengue infection.

METHODS

We prospectively collected data on patients admitted with DD between December 2017 and October 2018. ALC data were extracted from the Sysmex XS500i analyzer from day 1 to day 7 of admission. Clinical data were obtained from patients' medical records.

RESULTS

We enrolled 256 patients with DD. A negative correlation between ALC on admission and platelet count on day 5 to day 7 (Spearmen's correlation; day 5:-0.485, day 6:-0.428 and day 7:-0.344) (p=0.001) was observed. Based on receiver operator characteristic curve analysis, we found that an ALC of >0.5x103/L had 90% sensitivity and 70% specificity for severe thrombocytopenia (platelet count <50x109/L) on day 5. The positive and negative predictive values were 74.4 and 91.2%, respectively (power 84.7).

CONCLUSIONS

We propose that ALC on admission may be a novel negative predictive factor for severe thrombocytopenia on day 5 to day 7 of DD. Further studies are required to validate our findings and evaluate whether ALC is predictive of other complications of DD.

The contributory role of lymphocyte subsets, pathophysiology of lymphopenia and its implication as prognostic and therapeutic opportunity in COVID-19

The incidence of the novel coronavirus disease (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has brought daunting complications for people as well as physicians around the world. An ever-increasing number of studies investigating the characteristics of the disease, day by day, is shedding light on a new feature of the virus with the hope that eventually these efforts lead to the proper treatment. SARS-CoV-2 activates antiviral immune responses, but in addition may overproduce pro-inflammatory cytokines, causing uncontrolled inflammatory responses in patients with severe COVID-19. This condition may lead to lymphopenia and lymphocyte dysfunction, which in turn, predispose patients to further infections, septic shock, and severe multiple organ dysfunction. Therefore, accurate knowledge in this issue is important to guide clinical management of the disease and the development of new therapeutic strategies in patients with COVID-19. In this review, we provide a piece of valuable information about the alteration of each subtype of lymphocytes and important prognostic factors associated with these cells. Moreover, through discussing the lymphopenia pathophysiology and debating some of the most recent lymphocyte- or lymphopenia-related treatment strategies in COVID-19 patients, we tried to brightening the foreseeable future for COVID-19 patients, especially those with severe disease.

Admission ultrasonography as a predictive tool for thrombocytopenia and disease severity in dengue infection

BACKGROUND

Ultrasound (US) is an investigation available in many acute care settings. Thrombocytopenia is a well-described complication of dengue infection and has been shown to correlate with disease severity. The purpose of this study was to assess the utility of admission ultrasonography in predicting thrombocytopenia and disease severity in patients infected with dengue virus.

METHODS

Data were collected prospectively on 176 patients (male, n=86; female, n=90) admitted to the Nawaloka Hospital, Sri Lanka with dengue infection between December 2016 and August 2018. All patients had an US scan on admission and disease severity was determined using the World Health Organization 2009 classification.

RESULTS

There were 106 (60.2%) cases of dengue with/without warning signs and 70 (39.8%) cases of severe dengue. Patients with an abnormal US on admission were more likely to have severe dengue. Gallbladder wall thickening was the most common US abnormality. Abnormal US findings significantly correlated with more pronounced thrombocytopenia from day 2 of admission.

CONCLUSIONS

An abnormal US scan on admission can aid in identification of patients at risk of developing severe dengue and can be used as a novel clinical tool to identify patients at risk of severe thrombocytopenia.

Early hematological indicators of severe COVID-19 disease in hospitalized patients: Data from a South Asian population

Introduction

Outbreak of corona virus disease in 2019 (COVID‐19) has resulted in significant morbidity and mortality worldwide. Our aim is to document hematological parameters of patients with COVID‐19 during initial stage of diagnosis and to identify early hematological indicators of severe infection.

Materials and methods

This retrospective study was conducted at Shifa International Hospital, Pakistan from April to November 2020. Patients hospitalized with COVID‐19, diagnosed on RT‐PCR and had a complete blood count (CBC) done within 48 hours of diagnosis were included. Data was analyzed using IBM^® SPSS Statistics.

Results

A total of 425 patients were included in this study out of whom 272(64%) were males. The mean age was 55.61 ± 17.84 years. 95 patients (22.4%) had normal blood counts within 48 hours of COVID‐19 diagnosis. Cytopenias were seen in 193(45.4%) patients. There were 75(17.6%) mortalities during the study period. Chi‐square test showed that thrombocytopenia, lymphopenia and neutrophilic leucocytosis were significantly associated with mortality (P = .037, P < .001, P < .001 respectively) and need for ventilator (P = .009, P < .001, P < .001, respectively). Neutrophilia was also associated with development of Acute Respiratory Distress Syndrome (P < .001). On ROC analysis, Neutrophil‐to‐Lymphocyte Ratio yielded an area under the curve (AUC) of 0.693 and 0.660 for the outcomes mortality and need for ventilator, respectively. For a subset of 288 patients who had D‐dimer levels checked within 48 hours of COVID‐19 diagnosis, the AUC for mortality and ventilator need was 0.708 and 0.671, respectively.

Conclusion

Hematological indices are vital indicators in the prognosis and risk stratification of COVID‐19 during initial stages of disease.

Acute liver failure and death predictors in patients with dengue-induced severe hepatitis

BACKGROUND

Liver injury in patients with dengue infection is common. Most patients have mild and transient hepatitis. Acute liver failure (ALF) in dengue infection is rare but results in an extremely poor prognosis.

AIM

To identify prognostic predictors of ALF and death in patients with dengue-induced severe hepatitis (DISH).

METHODS

We retrospectively reviewed 2311 serologically confirmed adolescent and adult dengue patients who were hospitalized during a 12-year study period (between 2007 and 2019) at the university hospital of King Chulalongkorn Memorial Hospital, Bangkok, Thailand. Patients with DISH [n = 134 (5.80%)], defined as a baseline transaminase > 10 times the normal reference cut-off level, and DISH with subsequent ALF as defined by the American Association for the Study of the Liver Diseases 2011 criteria [n = 17 (0.74%)], were included. Predictors of ALF and in-hospital death were identified using logistic regression analysis.

RESULTS

Of the 151 dengue-infected patients with severe liver injury or ALF, 51% were female, with a mean age of 27.9 ± 14.5 years. Capillary leakage syndrome (CLS) occurred in 68.2% (n = 103) of DISH and 100% of ALF patients. The mortality rate was low in DISH patients (0.8%) but was remarkably high if ALF developed (58.8%). In univariate analysis, age, sex, hematocrit, white blood count, atypical lymphocyte count, platelet count, international normalized ratio (INR), bilirubin, serum glutamate-oxaloacetate transaminase, serum glutamate-pyruvate transaminase, alkaline phosphatase, albumin, creatinine, Model for End-Stage Liver Disease (MELD) score, presence of liver comorbidity and presence of CLS were identified as potential prognostic parameters for ALF or death. In multivariate analysis, the MELD score remained the only predictor of ALF with an adjusted odds ratio (aOR) of 1.3 [95% confidence interval (CI): 1.1-1.5; P = < 0.001]. An initial MELD score ≥ 15 was associated with ALF from DISH with an area under the receiver operating characteristic (AUROC) of 0.91, 88.2% sensitivity and 87.3% specificity. Regarding mortality prediction, the deterioration of liver function to ALF was the most significant factor related to death in DISH patients (aOR 108.5, 95%CI: 5.5-2145.4, P = 0.002). Other independent factors associated with death included baseline INR (aOR 10.4, 95%CI: 2.6-40.5, P = 0.001). An INR ≥ 1.5 predicted death from DISH with an AUROC of 0.83 (81.8% sensitivity and 86.8% specificity).

CONCLUSION

The MELD score is the best predictor of ALF in DISH patients, a complication from dengue that is associated with high mortality. The presence of ALF and the baseline INR level are independent markers of death in DISH patients.

Triple positivity for nonstructural antigen 1, immunoglobulin M and immunoglobulin G is predictive of severe thrombocytopaenia related to dengue infection

BACKGROUND

The early identification of patients at risk of severe dengue infection (DI) is critical to guide clinical management. Non-structural antigen 1 (NS-1), immunoglobulin M (IgM) and immunoglobulin G (IgG) are used routinely for the diagnosis of DI.

OBJECTIVES

We sought to evaluate whether positivity for NS-1, IgM and IgG individually or together is predictive of severe complications of DI.

METHODS & MATERIALS

A prospective study was conducted among patients with DI admitted to our institution between 2014 and 2019. DI was diagnosed based on a positive NS1 or IgM. IgG was also tested on all the patients. Clinical data was obtained from electronic medical records at NH. Statistical analyses were performed using SPSS version 20.

RESULTS

We collected data on 3504 patients. Patients who were positive for NS1, IgM and IgG (triple positive: TP) were more likely to develop severe DI (63.8 %) in comparison to those who were only NS1 positive (single positive: SP) (3.0 %) and patients with positive NS1 and IgM (double positive: DP) (7.5 %). [p = 0.001]. Regression analysis confirmed that TP status on admission was predictive of severe complications. (p < 0.01). Receiver operator characteristic curve (ROC) analysis showed (AUC: 84.8; sensitivity = 90.7 and specificity = 83.2) that TP status on admission is predictive of thrombocytopenia on day 5. The predictive power of TP status was superior to that of NS1 and IgG positivity.

CONCLUSIONS

We propose that TP status on admission is a novel predictive factor for severe DI. Further studies are required to explore the biological basis for this finding.