Biomarkers to distinguish bacterial from viral pediatric clinical pneumonia in a malaria endemic setting

Signature Proteins in Small Extracellular Vesicles of Granulocytes and CD4+ T-Cell Subpopulations Identified by Comparative Proteomic Analysis

Several studies have described the proteomic profile of different immune cell types, but only a few have also analysed the content of their delivered small extracellular vesicles (sEVs). The aim of the present study was to compare the protein signature of sEVs delivered from granulocytes (i.e., neutrophils and eosinophils) and CD4+ T cells (i.e., TH1, TH2, and TH17) to identify potential biomarkers of the inflammatory profile in chronic inflammatory diseases. Qualitative (DDA) and quantitative (DIA-SWATH) analyses of in vitro-produced sEVs revealed proteome variations depending on the cell source. The main differences were found between granulocyte- and TH cell-derived sEVs, with a higher abundance of antimicrobial proteins (e.g., LCN2, LTF, MPO) in granulocyte-derived sEVs and an enrichment of ribosomal proteins (RPL and RPS proteins) in TH-derived sEVs. Additionally, we found differentially abundant proteins between neutrophil and eosinophil sEVs (e.g., ILF2, LTF, LCN2) and between sEVs from different TH subsets (e.g., ISG15, ITGA4, ITGB2, or NAMPT). A "proof-of-concept" assay was also performed, with TH2 biomarkers ITGA4 and ITGB2 displaying a differential abundance in sEVs from T2high and T2low asthma patients. Thus, our findings highlight the potential use of these sEVs as a source of biomarkers for diseases where the different immune cell subsets studied participate, particularly chronic inflammatory pathologies such as asthma or chronic obstructive pulmonary disease (COPD).

Single-cell transcriptome analysis of the mouse lungs during the injury and recovery periods after lipopolysaccharide administration

OBJECTIVE

This study sought to investigate the cellular and molecular alterations during the injury and recovery periods of ALI and develop effective treatments for ALI.

METHODS

Pulmonary histology at 1, 3, 6, and 9 days after lipopolysaccharide administration mice were assessed. An unbiased single-cell RNA sequencing was performed in alveoli tissues from injury (day 3) and recovery (day 6) mice after lipopolysaccharide administration. The roles of Fpr2 and Dpp4 in ALI were assessed.

RESULTS

The most severe lung injury occurred on day 3, followed by recovery entirely on day 9 after lipopolysaccharide administration. The numbers of Il1a+ neutrophils, monocytes/macrophages, and Cd4+ and Cd8+ T cells significantly increased at day 3 after LPS administration; subsequently, the number of Il1a+ neutrophils greatly decreased, the numbers of monocytes/macrophages and Cd4+ and Cd8+ T cells continuously increased, and the number of resident alveolar macrophages significantly increased at day 6. The interactions between monocytes/macrophages and pneumocytes during the injury period were enhanced by the Cxcl10/Dpp4 pair, and inhibiting Dpp4 improved ALI significantly, while inhibiting Fpr2 did not.

CONCLUSIONS

Our results offer valuable insights into the cellular and molecular mechanisms underlying its progression and identify Dpp4 as an effective therapeutic target for ALI.

Cerebrospinal Fluid Neutrophil Gelatinase-Associated Lipocalin as a Novel Biomarker for Postneurosurgical Bacterial Meningitis: A Prospective Observational Cohort Study

BACKGROUND AND OBJECTIVES

Postneurosurgical bacterial meningitis (PNBM) was a significant clinical challenge, as early identification remains difficult. This study aimed to explore the potential of neutrophil gelatinase-associated lipocalin (NGAL) as a novel biomarker for the early diagnosis of PNBM in patients who have undergone neurosurgery.

METHODS

A total of 436 postneurosurgical adult patients were enrolled in this study. Clinical information, cerebrospinal fluid (CSF), and blood samples were collected. After the screening, the remaining 267 patients were divided into the PNBM and non-PNBM groups, and measured CSF and serum NGAL levels to determine the diagnostic utility of PNBM. Subsequently, patients with PNBM were categorized into gram-positive and gram-negative bacterial infection groups to assess the effectiveness of CSF NGAL in differentiating between these types of infections. We analyzed the changes in CSF NGAL expression before and after anti-infection treatment in PNBM. Finally, an additional 60 patients were included as an independent validation cohort to further validate the diagnostic performance of CSF NGAL.

RESULTS

Compared with the non-PNBM group, CSF NGAL was significantly higher in the PNBM group (305.1 [151.6-596.5] vs 58.5 [30.7-105.8] ng/mL; P < .0001). The area under the curve of CSF NGAL for diagnosing PNBM was 0.928 (95% CI: 0.897-0.960), at a threshold of 119.7 ng/mL. However, there was no significant difference in serum NGAL between the 2 groups (142.5 [105.0-248.6] vs 161.9 [126.6-246.6] ng/mL, P = .201). Furthermore, CSF NGAL levels were significantly higher in patients with gram-negative bacterial infections than those with gram-positive bacteria (P = .023). In addition, CSF NGAL levels decrease after treatment compared with the initial stage of infection (P < .0001). Finally, in this validation cohort, the threshold of 119.7 ng/mL CSF NGAL shows good diagnostic performance with a sensitivity and specificity of 90% and 80%, respectively.

CONCLUSION

CSF NGAL holds promise as a potential biomarker for the diagnosis, early drug selection, and efficacy monitoring of PNBM.

Circulating markers of neutrophil activation and lung injury in pediatric pneumonia in low-resource settings

Diagnostic biomarkers for childhood pneumonia could guide management and improve antibiotic stewardship in low-resource settings where chest x-ray (CXR) is not always available. In this cross-sectional study, we measured chitinase 3-like protein 1 (CHI3L1), surfactant protein D (SP-D), lipocalin-2 (LCN2), and tissue inhibitor of metalloproteinases-1 (TIMP-1) in Ugandan children under the age of five hospitalized with acute lower respiratory tract infection. We determined the association between biomarker levels and primary end-point pneumonia, indicated by CXR consolidation. We included 89 children (median age 11 months, 39% female). Primary endpoint pneumonia was present in 22 (25%). Clinical signs were similar in children with and without CXR consolidation. Broad-spectrum antibiotics (ceftriaxone) were administered in 83 (93%). Levels of CHI3L1, SP-D, LCN2 and TIMP-1 were higher in patients with primary end-point pneumonia compared to patients with normal CXR or other infiltrates. All markers were moderately accurate predictors of primary end-point pneumonia, with area under receiver operator characteristic curves of 0.66-0.70 (p<0.05 for all markers). The probability of CXR consolidation increased monotonically with the number of markers above cut-off. Among 28 patients (31%) in whom all four markers were below the cut-off, the likelihood ratio of CXR consolidation was 0.11 (95%CI 0.015 to 0.73). CHI3L1, SP-D, LCN2 and TIMP-1 were associated with CXR consolidation in children with clinical pneumonia in a low-resource setting. Combinations of quantitative biomarkers may be useful to safely withhold antibiotics in children with a low probability of bacterial infection.

Prognostic accuracy of biomarkers of immune and endothelial activation in Mozambican children hospitalized with pneumonia

Pneumonia is a leading cause of child mortality. However, currently we lack simple, objective, and accurate risk-stratification tools for pediatric pneumonia. Here we test the hypothesis that measuring biomarkers of immune and endothelial activation in children with pneumonia may facilitate the identification of those at risk of death. We recruited children <10 years old fulfilling WHO criteria for pneumonia and admitted to the Manhiça District Hospital (Mozambique) from 2010 to 2014. We measured plasma levels of IL-6, IL-8, Angpt-2, sTREM-1, sFlt-1, sTNFR1, PCT, and CRP at admission, and assessed their prognostic accuracy for in-hospital, 28-day, and 90-day mortality. Healthy community controls, within same age strata and location, were also assessed. All biomarkers were significantly elevated in 472 pneumonia cases versus 80 controls (p<0.001). IL-8, sFlt-1, and sTREM-1 were associated with in-hospital mortality (p<0.001) and showed the best discrimination with AUROCs of 0.877 (95% CI: 0.782 to 0.972), 0.832 (95% CI: 0.729 to 0.935) and 0.822 (95% CI: 0.735 to 0.908), respectively. Their performance was superior to CRP, PCT, oxygen saturation, and clinical severity scores. IL-8, sFlt-1, and sTREM-1 remained good predictors of 28-day and 90-day mortality. These findings suggest that measuring IL-8, sFlt-1, or sTREM-1 at hospital presentation can guide risk-stratification of children with pneumonia, which could enable prioritized care to improve survival and resource allocation.

Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms

Objectives

Hepatocellular carcinoma (HCC) is difficult to diagnose early and progresses rapidly, making it one of the most deadly malignancies worldwide. This study aimed to evaluate whether salivary glycopattern changes combined with machine learning algorithms could help in the accurate diagnosis of HCC.

Methods

Firstly, we detected the alteration of salivary glycopatterns by lectin microarrays in 118 saliva samples. Subsequently, we constructed diagnostic models for hepatic cirrhosis (HC) and HCC using three machine learning algorithms: Least Absolute Shrinkage and Selector Operation, Support Vector Machine (SVM), and Random Forest (RF). Finally, the performance of the diagnostic models was assessed in an independent validation cohort of 85 saliva samples by a series of evaluation metrics, including area under the receiver operator curve (AUC), accuracy, specificity, and sensitivity.

Results

We identified alterations in the expression levels of salivary glycopatterns in patients with HC and HCC. The results revealed that the glycopatterns recognized by 22 lectins showed significant differences in the saliva of HC and HCC patients and healthy volunteers. In addition, after Boruta feature selection, the best predictive performance was obtained with the RF algorithm for the construction of models for HC and HCC. The AUCs of the RF-HC model and RF-HCC model in the validation cohort were 0.857 (95% confidence interval [CI]: 0.780–0.935) and 0.886 (95% CI: 0.814–0.957), respectively.

Conclusions

Detecting alterations in salivary protein glycopatterns with lectin microarrays combined with machine learning algorithms could be an effective strategy for diagnosing HCC in the future.

Host respiratory transcriptome signature associated with poor outcome in children with influenza-Staphylococcus aureus pneumonia

Respiratory coinfection of influenza with Staphylococcus aureus often causes severe disease; methicillin resistant S. aureus (MRSA) coinfection is frequently fatal. Understanding disease pathogenesis may inform therapies. We aimed to identify host and pathogen transcriptomic (mRNA) signatures from the respiratory compartment of patients with influenza-S. aureus coinfection (ISAC) critical illness that predict worse outcomes. mRNA extracted from endotracheal aspirates was evaluated for S. aureus and host transcriptomic biosignatures. Influenza-MRSA outcomes were worse, but of 190 S. aureus virulence-associated genes, 6 were differentially expressed between MRSA- versus methicillin-susceptible S. aureus coinfected patients and none discriminated outcome. Host gene expression in ISAC patients was compared to influenza infection alone. Patients with poor clinical outcomes (death or prolonged multi-organ dysfunction) had relatively reduced expression of interferons and down-regulation of interferon gamma-induced immune cell chemoattractants CXCL10 and CXCL11. In influenza-S. aureus respiratory coinfection, airway host but not pathogen gene expression profiles predicted worse clinical outcomes.

Childhood Pneumonia Diagnostics in Sub-Saharan Africa: A Systematic Review

BACKGROUND

The prompt and accurate aetiological diagnosis of childhood pneumonia remains a challenge, especially in sub-Saharan Africa (SSA) because of limited resources for disease management.

OBJECTIVE

To review existing diagnostics for childhood pneumonia and potential modalities available to differentiate between bacterial and viral aetiologies in SSA.

METHODS

Online databases were searched for relevant articles published between January 2010 and December 2020 regarding childhood pneumonia diagnosis, conducted in SSA in children less than 18 years of age. The 2020 PRISMA checklist was utilized in appraising the selected studies and the QUADAS-2 tool was employed to assess the risk of bias in each of the studies selected.

RESULTS

A total of 1542 study titles and abstracts were screened following which 45 studies (39 on childhood pneumonia diagnostics and 6 on discriminating between bacterial and viral childhood pneumonia) were selected for review. Microbiological investigations (79.7%) constituted the most utilized index tests with blood-related specimen (32.8%) being the most utilized specimen. The most performed index diagnostic modality was polymerase chain reaction (PCR) (53.1%). The commonest reference gold standard technique was based on clinical diagnosis of the disease (46.2%). Only six studies in SSA attempted at using serum biomarkers, either singly or in combination to distinguish between aetiologies with use of combined biomarkers showing promise.

CONCLUSION

Microbiological investigations are the most employed diagnostic methods for childhood pneumonia in SSA. More studies are required to evaluate the potential use of serum biomarkers; either singly or in combination with the goal of discriminating bacterial and viral childhood pneumonia.

Is Serum Endocan Level an Indicator of the Severity of Childhood Community-Acquired Pneumonia?

Objective We aimed to investigate the relationship between serum endocan, procalcitonin (PCT), C-reactive protein (CRP), white blood cell count (WBC), neutrophil/lymphocyte ratios (NLR), and the severity of the disease in childhood community-acquired pneumonia (CAP) cases.

Methods This cross-sectional designed study included 30 pneumonia cases and 30 severe pneumonia cases aged between 3 months and 18 years who were hospitalized and treated in our hospital with the diagnosis of CAP. We also included 30 healthy controls in the same age range. Pearson's correlation and receiver operating characteristic (ROC) curve analyzes were performed.

Results PCT, endocan, NLR, and CRP levels were found to be significantly higher in patients with severe pneumonia. Sensitivity and specificity values in detecting pneumonia were 72.5 and 93% for PCT, 78.4 and 83.3% for CRP, 78.4 and 76.7% for endocan, and 64.7 and 63.3% for NLR. However, the area under the curve in ROC analysis were 0.821, 0.840, 0.842, and 0.670 for PCT, CRP, endocan, and NLR respectively.

Conclusion Endocan may be a marker of the diagnosis of pneumonia and not clinical severity, but studies are needed in large patient populations.