Characterizing Emerging Canine H3 Influenza Viruses.

The continual emergence of novel influenza A strains from non-human hosts requires constant vigilance and the need for ongoing research to identify strains that may pose a human public health risk. Since 1999, canine H3 influenza A viruses (CIVs) have caused many thousands or millions of respiratory infections in dogs in the United States. While no human infections with CIVs have been reported to date, these viruses could pose a zoonotic risk. In these studies, the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaboratively demonstrated that CIVs replicated in some primary human cells and transmitted effectively in mammalian models. While people born after 1970 had little or no pre-existing humoral immunity against CIVs, the viruses were sensitive to existing antivirals and we identified a panel of H3 cross-reactive human monoclonal antibodies (hmAbs) that could have prophylactic and/or therapeutic value. Our data predict these CIVs posed a low risk to humans. Importantly, we showed that the CEIRS network could work together to provide basic research information important for characterizing emerging influenza viruses, although there were valuable lessons learned.

A systems genomics approach uncovers molecular associates of RSV severity.

Respiratory syncytial virus (RSV) infection results in millions of hospitalizations and thousands of deaths each year. Variations in the adaptive and innate immune response appear to be associated with RSV severity. To investigate the host response to RSV infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. We implemented a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation, which enabled us to identify cellular pathways associated with RSV severity. In both airway and immune cells, we found an association between RSV severity and activation of pathways controlling Th17 and acute phase response signaling, as well as inhibition of B cell receptor signaling. Dysregulation of both the humoral and mucosal response to RSV may play a critical role in determining illness severity.

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection.

BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of infant respiratory disease. Infant airway microbiota has been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease susceptibility and severity, are unknown. METHODS: We carried out 16S rRNA microbiota profiling of infants in the first year of life from (1) a cross-sectional cohort of 89 RSV-infected infants sampled during illness and 102 matched healthy controls, and (2) a matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled before, during, and after infection. RESULTS: We identified 12 taxa significantly associated with RSV infection. All 12 taxa were differentially abundant during infection, with 8 associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs infected than of disease severity. CONCLUSIONS: Our findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and impact of RSV infection on microbiota composition.

Airway Gene Expression Correlates of Respiratory Syncytial Virus Disease Severity and Microbiome Composition in Infants.

BACKGROUND: Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. The causes and correlates of severe illness in the majority of infants are poorly defined. METHODS: We recruited a cohort of RSV-infected infants and simultaneously assayed the molecular status of their airways and the presence of airway microbiota. We used rigorous statistical approaches to identify gene expression patterns associated with disease severity and microbiota composition, separately and in combination. RESULTS: We measured comprehensive airway gene expression patterns in 106 infants with primary RSV infection. We identified an airway gene expression signature of severe illness dominated by excessive chemokine expression. We also found an association between Haemophilus influenzae, disease severity, and airway lymphocyte accumulation. Exploring the time of onset of clinical symptoms revealed acute activation of interferon signaling following RSV infection in infants with mild or moderate illness, which was absent in subjects with severe illness. CONCLUSIONS: Our data reveal that airway gene expression patterns distinguish mild/moderate from severe illness. Furthermore, our data identify biomarkers that may be therapeutic targets or useful for measuring efficacy of intervention responses.

Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants.

OBJECTIVE: To develop a valid research tool to measure infant respiratory illness severity using parent-reported symptoms. STUDY DESIGN: Nose and throat swabs were collected monthly for 1 year and during respiratory illnesses for 2 years in a prospective study of term and preterm infants in the Prematurity, Respiratory Outcomes, Immune System and Microbiome study. Viral pathogens were detected using Taqman Array Cards. Parents recorded symptoms during respiratory illnesses using a Childhood Origins of Asthma (COAST) scorecard. The COAST score was validated using linear mixed effects regression modeling to evaluate associations with hospitalization and specific infections. A data-driven method was also used to compute symptom weights and derive a new score, the Infant Research Respiratory Infection Severity Score (IRRISS). Linear mixed effects regression modeling was repeated with the IRRISS illness data. RESULTS: From April 2013 to April 2017, 50 term, 40 late preterm, and 28 extremely low gestational age (<29 weeks of gestation) infants had 303 respiratory illness visits with viral testing and parent-reported symptoms. A range of illness severity was described with 39% of illness scores suggestive of severe disease. Both the COAST score and IRRISS were associated with respiratory syncytial virus infection and hospitalization. Gestational age and human rhinovirus infection were inversely associated with both scoring systems. The IRRISS and COAST scores were highly correlated (r = 0.93; P < .0001). CONCLUSIONS: Using parent-reported symptoms, we validated the COAST score as a measure of respiratory illness severity in infants. The new IRRISS score performed as well as the COAST score.

Virus-Specific Antibody, Viral Load, and Disease Severity in Respiratory Syncytial Virus Infection.

Background: Maternally derived serum antibody and viral load are thought to influence disease severity in primary respiratory syncytial virus (RSV) infection. As part of the AsPIRES study of RSV pathogenesis, we correlated various serum antibody concentrations and viral load with disease severity. Methods: Serum neutralizing antibody titers and levels of immunoglobulin G (IgG) to RSV fusion protein (F), attachment proteins of RSV group A and B, the CX3C region of G, and nasal viral load were measured in 139 full-term previously healthy infants with primary RSV infection and correlated with illness severity. Results: Univariate analysis showed no relationship between measures of serum antibody and severity. However, a multivariate model adjusting for age at the time of infection found a significant 0.56 decrease in severity score for each 2-fold increase in antibody concentration to RSV F. The benefit of antibody was greatest in infants ≤ 2 months of age. Additionally, estimated antibody titer at birth was correlated with age at infection, suggesting that higher antibody titers delay infection. Viral load did not differ by illness severity. Conclusion: Our data support the concept of maternal immunization with an RSV vaccine during pregnancy as a strategy for reducing the burden of RSV infection in full-term healthy infants exposed to RSV during their first winter.

Dissociation, cellular isolation, and initial molecular characterization of neonatal and pediatric human lung tissues.

Human lung morphogenesis begins by embryonic life and continues after birth into early childhood to form a complex organ with numerous morphologically and functionally distinct cell types. Pulmonary organogenesis involves dynamic changes in cell proliferation, differentiation, and migration of specialized cells derived from diverse embryonic lineages. Studying the molecular and cellular processes underlying formation of the fully functional lung requires isolating distinct pulmonary cell populations during development. We now report novel methods to isolate four major pulmonary cell populations from pediatric human lung simultaneously. Cells were dissociated by protease digestion of neonatal and pediatric lung and isolated on the basis of unique cell membrane protein expression patterns. Epithelial, endothelial, nonendothelial mesenchymal, and immune cells were enriched by fluorescence-activated cell sorting. Dead cells and erythrocytes were excluded by 7-aminoactinomycin D uptake and glycophorin-A (CD235a) expression, respectively. Leukocytes were identified by membrane CD45 (protein tyrosine phosphatase, receptor type C), endothelial cells by platelet endothelial cell adhesion molecule-1 (CD31) and vascular endothelial cadherin (CD144), and both were isolated. Thereafter, epithelial cell adhesion molecule (CD326)-expressing cells were isolated from the endothelial- and immune cell-depleted population to enrich epithelial cells. Cells lacking these membrane markers were collected as "nonendothelial mesenchymal" cells. Quantitative RT-PCR and RNA sequencing analyses of population specific transcriptomes demonstrate the purity of the subpopulations of isolated cells. The method efficiently isolates major human lung cell populations that we announce are now available through the National Heart, Lung, and Blood Institute Lung Molecular Atlas Program (LungMAP) for their further study.

Maximum Likelihood Estimation of Titer via a Power Family of Four-Parameter Logistic Model.

For many laboratory assays, the readouts are presence or absence of a particular function, and the binary outcomes are correlated. The research interest is often focused on the estimation of titers, at which 50% positivity occurs. The classical approach by Reed and Muench (RM) assumes linear dose-response relationship around the potential titer, and uses only information from two points around the potential titer, which is inefficient in both precision and accuracy. While the model-based methods such as four-parameter logistic regression (4PL) use all the data, they do not consider the correlation among binary outcomes from same identities, which may lead to estimates with overstated precision. We propose estimating titers from two different anchors: independent responses from same identities or exchangeable responses from same identities. Marginal distributions of responses are linked to covariates of dilution factors by the 4PL model for independent responses and by a power family of the 4PL models for exchangeable responses. The maximum-likelihood procedure is used to get estimates of parameters and titers. The superiority of proposed methods over the classical approach is demonstrated both in simulation studies and in analysis of real data from hemagglutination assays.

Association of Dynamic Changes in the CD4 T-Cell Transcriptome With Disease Severity During Primary Respiratory Syncytial Virus Infection in Young Infants.

Background: Nearly all children are infected with respiratory syncytial virus (RSV) within the first 2 years of life, with a minority developing severe disease (1%-3% hospitalized). We hypothesized that an assessment of the adaptive immune system, using CD4+ T-lymphocyte transcriptomics, would identify gene expression correlates of disease severity. Methods: Infants infected with RSV representing extremes of clinical severity were studied. Mild illness (n = 23) was defined as a respiratory rate (RR) < 55 and room air oxygen saturation (SaO2) ≥ 97%, and severe illness (n = 23) was defined as RR ≥ 65 and SaO2 ≤ 92%. RNA from fresh, sort-purified CD4+ T cells was assessed by RNA sequencing. Results: Gestational age, age at illness onset, exposure to environmental tobacco smoke, bacterial colonization, and breastfeeding were associated (adjusted P < .05) with disease severity. RNA sequencing analysis reliably measured approximately 60% of the genome. Severity of RSV illness had the greatest effect size upon CD4 T-cell gene expression. Pathway analysis identified correlates of severity, including JAK/STAT, prolactin, and interleukin 9 signaling. We also identified genes and pathways associated with timing of symptoms and RSV group (A/B). Conclusions: These data suggest fundamental changes in adaptive immune cell phenotypes may be associated with RSV clinical severity.

Development of a Global Respiratory Severity Score for Respiratory Syncytial Virus Infection in Infants.

Background: Respiratory syncytial virus (RSV) infection in infants has recognizable clinical signs and symptoms. However, quantification of disease severity is difficult, and published scores remain problematic. Thus, as part of a RSV pathogenesis study, we developed a global respiratory severity score (GRSS) as a research tool for evaluating infants with primary RSV infection. Methods: Previously healthy infants <10 months of age with RSV infections representing the spectrum of disease severity were prospectively evaluated. Clinical signs and symptoms were collected at 3 time points from hospitalized infants and those seen in ambulatory settings. Data were also extracted from office, emergency department, and hospital records. An unbiased data-driven approach using factor analysis was used to develop a GRSS. Results: A total of 139 infants (84 hospitalized and 55 nonhospitalized) were enrolled. Using hospitalization status as the output variable, 9 clinical variables were identified and weighted to produce a composite GRSS. The GRSS had an area under the receiver operator curve of 0.961. Construct validity was demonstrated via a significant correlation with length of stay (r = 0.586, P < .0001). Conclusions: Using routine clinical variables, we developed a severity score for infants with RSV infection that should be useful as an end point for investigation of disease pathogenesis and as an outcome measure for therapeutic interventions.

Viral Respiratory Infections in Preterm Infants during and after Hospitalization.

OBJECTIVE: To determine the burden of viral respiratory infections in preterm infants both during and subsequent to neonatal intensive care unit (NICU) hospitalization and to compare this with term infants living in the community. STUDY DESIGN: From March 2013 through March 2015, we enrolled 189 newborns (96 term and 93 preterm) into a prospective, longitudinal study obtaining nose/throat swabs within 7 days of birth, weekly while hospitalized and then monthly to 4 months after hospital discharge. Taqman array cards were used to identify 16 viral respiratory pathogens by real-time polymerase chain reaction. Demographic, clinical, and laboratory data were gathered from electronic medical records, and parent interview while hospitalized with interval histories collected at monthly visits. The hospital course of all preterm infants who underwent late-onset sepsis evaluations was reviewed. RESULTS: Over 119 weeks, we collected 618 nose/throat swabs from at risk preterm infants in our level IV regional NICU. Only 4 infants had viral respiratory infections, all less than 28 weeks gestation at birth. Two infants were symptomatic with the infections recognized by the clinical team. The daily risk of acquiring a respiratory viral infection in preterm infants in the NICU was significantly lower than in the full term cohort living in the community. Once discharged from the hospital, viral respiratory infections were common in all infants. CONCLUSIONS: Viral respiratory infections are infrequent in a NICU with strict infection prevention strategies and do not appear to cause unrecognized illness. Both preterm and term infants living in the community quickly acquire respiratory viral infections.

Directed selection of influenza virus produces antigenic variants that match circulating human virus isolates and escape from vaccine-mediated immune protection.

Influenza vaccination does not provide 100% protection from infection, partly due to antigenic drift of the haemagglutinin (HA) protein. Low serum antibody titres increase the risk of infection. To determine whether there were additional correlates of risk, we examined the relationship between human serum immunity and antigenic variation in seasonal H3N2 influenza viruses. Seasonal H3N2 vaccine strains grown in the presence of heterogeneous human or mono-specific ferret antisera selected variants with mutations in the HA antigenic sites. Surprisingly, circulating strains infecting human subjects in the same seasons displayed mutations in the same positions, although only in one case did the change correspond to the same amino acid. Serum antibody titres were lower against both the in vitro selected and clinical isolates compared with the vaccine strains, suggesting that the mutations are relevant to vaccine failure. Antibody titres were also significantly lower in sera from infected subjects than in non-infected subjects, suggesting relatively poor responses to vaccination in the infected subjects. Collectively, the data suggest that risk from influenza infection is a result of poor response to vaccination, as well as encounter with drifted seasonal influenza virus antigenic variants. The results also show that directed selection under human immune pressure could reveal antigenic variants relevant to real-world drifted viruses, helping in annual vaccine re-formulation.

An improved method for estimating antibody titers in microneutralization assay using green fluorescent protein.

Viruses that express reporter genes upon infection have been recently used to evaluate neutralizing antibody responses, where a lack of reporter expression indicates specific virus inhibition. The traditional model-based methods using standard outcome of percent neutralization could be applied to the data from the assays to estimate antibody titers. However, the data produced are sometimes irregular, which can yield meaningless outcomes of percent neutralization that do not fit the typical curves for immunoassays, making automated or semi-high throughput antibody titer estimation unreliable. We developed a type of new outcomes model, which is biologically meaningful and fits typical immunoassay curves well. Our simulation study indicates that the new response approach outperforms the traditional response approach regardless of the data variability. The proposed new response approach can be used in similar assays for other disease models.

Developmentally determined reduction in CD31 during gestation is associated with CD8+ T cell effector differentiation in preterm infants.

Homeostatic T cell proliferation is more robust during human fetal development. In order to understand the relative effect of normal fetal homeostasis and perinatal exposures on CD8+ T cell behavior in PT infants, we characterized umbilical cord blood CD8+ T cells from infants born between 23-42weeks gestation. Subjects were recruited as part of the NHLBI-sponsored Prematurity and Respiratory Outcomes Program. Cord blood from PT infants had fewer naïve CD8+ T cells and lower regulatory CD31 expression on both naïve and effector, independent of prenatal exposures. CD8+ T cell in vitro effector function was greater at younger gestational ages, an effect that was exaggerated in infants with prior inflammatory exposures. These results suggest that CD8+ T cells earlier in gestation have loss of regulatory co-receptor CD31 and greater effector differentiation, which may place PT neonates at unique risk for CD8+ T cell-mediated inflammation and impaired T cell memory formation.

RocHealthData.org: Development and usage of a publicly available, geographic source of social determinants of health data.

Access to local, population specific, and timely data is vital in understanding factors that impact population health. The impact of place (neighborhood, census tract, and city) is particularly important in understanding the Social Determinants of Health. The University of Rochester Medical Center's Clinical and Translational Science Institute created the web-based tool RocHealthData.org to provide access to thousands of geographically displayed publicly available health-related datasets. The site has also hosted a variety of locally curated datasets (eg., COVID-19 vaccination rates and community-derived health indicators), helping set community priorities and impacting outcomes. Usage statistics (available through Google Analytics) show returning visitors with a lower bounce rate (leaving a site after a single page access) and spent longer at the site than new visitors. Of the currently registered 1033 users, 51.7% were from within our host university, 20.1% were from another educational institution, and 28.2% identified as community members. Our assessments indicate that these data are useful and valued across a variety of domains. Continuing site improvement depends on new sources of locally relevant data, as well as increased usage of data beyond our local region.

Investigating Ethical Tradeoffs in Crisis Standards of Care through Simulation of Ventilator Allocation Protocols.

Introduction: Arguments over the appropriate Crisis Standards of Care (CSC) for public health emergencies often assume that there is a tradeoff between saving the most lives, saving the most life-years, and preventing racial disparities. However, these assumptions have rarely been explored empirically. To quantitatively characterize possible ethical tradeoffs, we aimed to simulate the implementation of five proposed CSC protocols for rationing ventilators in the context of the COVID-19 pandemic. Methods: A Monte Carlo simulation was used to estimate the number of lives saved and life-years saved by implementing clinical acuity-, comorbidity- and age-based CSC protocols under different shortage conditions. This model was populated with patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. To estimate lives and life-years saved by each protocol, we determined survival to discharge and estimated remaining life expectancy for each admission. Results: The simulation demonstrated stronger performance for age- and comorbidity-sensitive protocols. For a capacity of 1 bed per 2 patients, ranking by age bands saves approximately 28.7 lives and 3408 life-years per thousand patients, while ranking by Sequential Organ Failure Assessment (SOFA) bands saved the fewest lives (13.2) and life-years (416). For all protocols, we observed a positive correlation between lives saved and life-years saved. For all protocols except lottery and the banded SOFA, significant disparities in lives saved and life-years saved were noted between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. Conclusion: While there is significant variance in the number of lives saved and life-years saved, we did not find a tradeoff between saving the most lives and saving the most life-years. Moreover, concerns about racial discrimination in triage protocols require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

Ventilation during COVID-19 in a school for students with intellectual and developmental disabilities (IDD).

BACKGROUND: This study examined the correlation of classroom ventilation (air exchanges per hour (ACH)) and exposure to CO2 ≥1,000 ppm with the incidence of SARS-CoV-2 over a 20-month period in a specialized school for students with intellectual and developmental disabilities (IDD). These students were at a higher risk of respiratory infection from SARS-CoV-2 due to challenges in tolerating mitigation measures (e.g. masking). One in-school measure proposed to help mitigate the risk of SARS-CoV-2 infection in schools is increased ventilation. METHODS: We established a community-engaged research partnership between the University of Rochester and the Mary Cariola Center school for students with IDD. Ambient CO2 levels were measured in 100 school rooms, and air changes per hour (ACH) were calculated. The number of SARS-CoV-2 cases for each room was collected over 20 months. RESULTS: 97% of rooms had an estimated ACH ≤4.0, with 7% having CO2 levels ≥2,000 ppm for up to 3 hours per school day. A statistically significant correlation was found between the time that a room had CO2 levels ≥1,000 ppm and SARS-CoV-2 PCR tests normalized to room occupancy, accounting for 43% of the variance. No statistically significant correlation was found for room ACH and per-room SARS-CoV-2 cases. Rooms with ventilation systems using MERV-13 filters had lower SARS-CoV-2-positive PCR counts. These findings led to ongoing efforts to upgrade the ventilation systems in this community-engaged research project. CONCLUSIONS: There was a statistically significant correlation between the total time of room CO2 concentrations ≥1,000 and SARS-CoV-2 cases in an IDD school. Merv-13 filters appear to decrease the incidence of SARS-CoV-2 infection. This research partnership identified areas for improving in-school ventilation.

Single-Cell Transcriptomic Profiling Identifies Molecular Phenotypes of Newborn Human Lung Cells.

While animal model studies have extensively defined the mechanisms controlling cell diversity in the developing mammalian lung, there exists a significant knowledge gap with regards to late-stage human lung development. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. Transcriptomic profiling at the single-cell level created a cellular atlas of newborn human lungs. Frozen single-cell isolates obtained from two newborn human lungs from the LungMAP Human Tissue Core Biorepository, were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Transcriptional interrogation of 5500 newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, immune cells and their gene signatures. Computational integration of data from newborn human cells and with 32,000 cells from postnatal days 1 through 10 mouse lungs generated by the LungMAP Cincinnati Research Center facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the newborn human and mouse cellular transcriptomes also demonstrated cell type-specific differences in maturation states of newborn human lung cells. Specifically, newborn human lung matrix fibroblasts could be separated into those representative of younger cells (n = 393), or older cells (n = 158). Cells with each molecular profile were spatially resolved within newborn human lung tissue. This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of maturity.

Modeling of influenza-specific CD8+ T cells during the primary response indicates that the spleen is a major source of effectors.

The biological parameters that determine the distribution of virus-specific CD8(+) T cells during influenza infection are not all directly measurable by experimental techniques but can be inferred through mathematical modeling. Mechanistic and semimechanistic ordinary differential equations were developed to describe the expansion, trafficking, and disappearance of activated virus-specific CD8(+) T cells in lymph nodes, spleens, and lungs of mice during primary influenza A infection. An intensive sampling of virus-specific CD8(+) T cells from these three compartments was used to inform the models. Rigorous statistical fitting of the models to the experimental data allowed estimation of important biological parameters. Although the draining lymph node is the first tissue in which Ag-specific CD8(+) T cells are detected, it was found that the spleen contributes the greatest number of effector CD8(+) T cells to the lung, with rates of expansion and migration that exceeded those of the draining lymph node. In addition, models that were based on the number and kinetics of professional APCs fit the data better than those based on viral load, suggesting that the immune response is limited by Ag presentation rather than the amount of virus. Modeling also suggests that loss of effector T cells from the lung is significant and time dependent, increasing toward the end of the acute response. Together, these efforts provide a better understanding of the primary CD8(+) T cell response to influenza infection, changing the view that the spleen plays a minor role in the primary immune response.

Statistical estimation & inference of cell counts from ELISPOT limiting dilution assays.

The ELISPOT assay is often used for cell count determination in immunological studies. Automated methods are needed to estimate cell concentrations from spot counts obtained from the assay. Three major distributions are assumed for observational cell counts. For each assumed distribution, individual least squares (LS)/ maximum likelihood and/or individual robust least squares (RLS) are applied for parameter estimation. Distributions of study endpoints (derived variables), defined as percentages of antigen-specific memory cell per total immunoglobulin G (IgG), are investigated to provide a basis for hypothesis testing. We show, under some weak conditions, that the distribution of endpoint estimates across subjects is approximately the same within a group. Thus, the t -test or the Wilcoxon Rank Sum test can be applied to detect group differences. These methods are compared through simulations and application to real data.