Clinical and immunological features of the combined course of pertussis and rhinovirus infection in children

The association of pertussis with various respiratory infections in children is the leading factor determining the complicated course and unfavorable outcome of the disease.Objective. To analyze clinical and immunological features of the combined course of pertussis and rhinovirus infection.Children characteristics and research methods. The authors observed 20 patients: 10 (50%) children were under the age of 1 year, 5 (25%) children of 1–3 years old, 3 (15%) children of 4–6 years, 2 (10%) children of 7 -14 years old.Results. The rhinovirus infection developed mainly at 1-2 weeks of illness in 18 (90%) children. Bronchitis developed in 11 (55%) children, pneumonia – in 4 (20%). Special attention was drawn to the low content of NK cells in 82.4% of patients when assessing the subpopulation composition of lymphocytes. The cytokine profile was characterized by a low level of interferon-gamma and interferon-alpha production – in 94.4 and 61.1% of patients, respectively.Conclusion. The combination of pertussis and rhinovirus infection in children contributes to the uneven course of the disease, the frequent development of bronchopulmonary complications.

Airway epithelial interferon response to SARS-CoV-2 is inferior to rhinovirus and heterologous rhinovirus infection suppresses SARS-CoV-2 replication

Introduction: Common alphacoronaviruses and human rhinoviruses (HRV) induce type I and III interferon (IFN) responses important to limiting viral replication in the airway epithelium. In contrast, highly pathogenic betacoronaviruses including SARS-CoV-2 may evade or antagonize RNA-induced IFN I/III responses. Methods: In airway epithelial cells (AECs) from children and older adults we compared IFN I/III responses to SARS-CoV-2 and HRV-16, and assessed whether pre-infection with HRV-16, or pretreatment with recombinant IFN-β or IFN-λ, modified SARS-CoV-2 replication. Bronchial AECs from children (ages 6-18 yrs.) and older adults (ages 60-75 yrs.) were differentiated ex vivo to generate organotypic cultures. In a biosafety level 3 (BSL-3) facility, cultures were infected with SARS-CoV-2 or HRV-16, and RNA and protein was harvested from cell lysates 96 hrs. following infection and supernatant was collected 48 and 96 hrs. following infection. In additional experiments cultures were pre-infected with HRV-16, or pre-treated with recombinant IFN-β1 or IFN-λ2 before SARS-CoV-2 infection. Results: Despite significant between-donor heterogeneity SARS-CoV-2 replicated 100 times more efficiently than HRV-16. IFNB1, INFL2, and CXCL10 gene expression and protein production following HRV-16 infection was significantly greater than following SARS-CoV-2. IFN gene expression and protein production were inversely correlated with SARS-CoV-2 replication. Treatment of cultures with recombinant IFNβ1 or IFNλ2, or pre-infection of cultures with HRV-16, markedly reduced SARS-CoV-2 replication. Discussion: In addition to marked between-donor heterogeneity in IFN responses and viral replication, SARS-CoV-2 elicits a less robust IFN response in primary AEC cultures than does rhinovirus, and heterologous rhinovirus infection, or treatment with recombinant IFN-β1 or IFN-λ2, markedly reduces SARS-CoV-2 replication.

1327. Human Rhinovirus Infection in Multiple Myeloma Patients: Effect on Morbidity and Mortality

Background Human Rhinovirus (hRV) causes mild, primarily upper respiratory tract symptoms in immunocompetent hosts. However, in immunocompromised patients, it often progresses to a lower respiratory tract infection. Multiple myeloma (MM) patients are immunocompromised due to inherent immunodeficiency and exposure to biologic and chemotherapeutic agents. The complications of hRV infection in MM patients are not well known. In this study, we aim to identify the morbidity and mortality associated with hRV in MM participants. Methods This was a retrospective study, using Arkansas Clinical Registry Database, which identified all MM patients diagnosed with hRV infection by nasopharyngeal multiplex polymerase chain reaction (PCR) in January-December 2019. Duplicates within 30 days were excluded. Patients were followed for 30 days after diagnosis. We assessed the need for hospitalization, intensive care unit (ICU) admission, oxygen administration, mechanical ventilation, and death. We collected their absolute neutrophil (ANC) and lymphocyte count (ALC) within three days of diagnosis and compared values using Mann-Whitney U test. Results We identified 217 MM patients with hRV. Ninety (41%) had prior autologous stem cell transplant, 148 (68%) had received chemotherapy within 30 days. Ninety (41%) had chest imaging, with 11 (12%) having infiltrates. Out of the 217, 69 (31.9%) were admitted, with a mean length of stay of 3 days. 13% of the admitted patients were transferred to the ICU. 65.5% of the admitted patients needed oxygen, and two required mechanical ventilation. The mean ANC and ALC for the admitted group was 3.88 cells/µL and 1.22 cells/µL respectively, compared to 3.57 cells/µL and 1.07 cells/µL in the outpatient group, p=0.6 and 1. Five participants died. Conclusion Human Rhinovirus infection in MM patients was associated with significant morbidity, including hospitalization, ICU care, supplemental oxygen requirement, and even mechanical ventilation in 2 patients. Death was observed within 30 days, although rarely. The mean ALC and ANC were not predictive of the severity of the disease. Recognizing hRV effects on morbidity and mortality could lead to earlier recognition and management of complications in MM patients. Disclosures All Authors: No reported disclosures

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders Expanding (T-REX) was created to identify changes in both very rare and common cells in diverse human immune monitoring settings. T-REX identified cells that were highly similar in phenotype and localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized reagents used to detect the rhinovirus-specific CD4+ cells, MHCII tetramers, were not used during unsupervised analysis and instead 'left out' to serve as a test of whether T-REX identified biologically significant cells. In the rhinovirus challenge study, T-REX identified virus-specific CD4+ T cells based on these cells being a distinct phenotype that expanded by ≥95% following infection. T-REX successfully identified hotspots containing virus-specific T cells using pairs of samples comparing Day 7 of infection to samples taken either prior to infection (Day 0) or after clearing the infection (Day 28). Mapping pairwise comparisons in samples according to both the direction and degree of change provided a framework to compare systems level immune changes during infectious disease or therapy response. This revealed that the magnitude and direction of systemic immune change in some COVID-19 patients was comparable to that of blast crisis acute myeloid leukemia patients undergoing induction chemotherapy and characterized the identity of the immune cells that changed the most. Other COVID-19 patients instead matched an immune trajectory like that of individuals with rhinovirus infection or melanoma patients receiving checkpoint inhibitor therapy. T-REX analysis of paired blood samples provides an approach to rapidly identify and characterize mechanistically significant cells and to place emerging diseases into a systems immunology context.