BACKGROUND:Respiratory syncytial virus (RSV) is a leading cause of hospitalization in infants, and those with RSV disease appear more likely to develop recurrent wheeze. We examined nasal airway gene expression and microbiome composition during primary RSV infection to test associations with illness severity and identify infants with recurrent wheeze. METHODS:Previously healthy infants with RSV infection were enrolled (December 2019-December 2023). Clinical and demographic data were collected, as were 2 anterior nasal swabs and a nasal wash for metagenome and transcriptome sequencing. Disease severity was measured by the improved Global Respiratory Severity Score (iGRSS). Participants were followed for approximately 1 year to identify recurrent wheeze. Multivariate regression models were developed to identify correlates and predictors of disease severity and recurrent wheeze, respectively. RESULTS:One hundred infants (90 hospitalized) were enrolled (mean ± SD age, 3.2 ± 2.3 months; 61% male). An overall 405 genes (false discovery rate, 0.10) were significantly and consistently associated with illness severity (iGRSS), implicating innate immune and interleukin signaling pathways. The abundance of nasal Dolosigranulum was inversely associated with iGRSS, while the abundance of Haemophilus was directly associated with iGRSS. Predictive models based on nasal gene expression during infection had the power to classify recurrent wheeze (in-sample area under the curve, 0.992; cross-validated area under the curve, 0.882), while metagenomic features did not improve predictive performance. CONCLUSIONS:We prospectively followed infants with primary RSV infection and identified associations among nasal gene expression, microbiome composition/function, and acute disease severity and recurrent wheeze. Host transcriptional profiles during infection were predictive of recurrent wheeze within the following year.

Congenital cytomegalovirus (cCMV) affects approximately 1 in 200 neonates and can lead to severe disease in the newborn period. Sensorineural hearing loss (SNHL) and developmental delays are the most common long-term sequelae. Prior to the implementation of a 1 year cCMV universal screening program in New York State (NYS), there was a state-mandated hearing-targeted cCMV screening program utilizing saliva-based PCR testing. All positive salivary cCMV PCR tests were confirmed by a urine PCR due to possible false-positive results from contamination of saliva by maternal breast milk containing CMV. This study aims to explore the performance characteristics of salivary cCMV PCR testing at URMC. A retrospective chart review of neonates who underwent saliva-based CMV PCR testing at URMC hospitals between March 1, 2019 and October 31, 2023 was completed. The primary outcomes were the false-positive rate and positive predictive value (PPV) of saliva-based CMV testing. The secondary outcome was the rate of SNHL among infants with confirmed cCMV infection through annual audiologic follow up. Out of 37 charts reviewed, 26 patients had both saliva and urine testing performed. Of the 26 neonates, 12 (46%) with positive salivary CMV PCR tests were confirmed positive by urine PCR testing; 14 of the 26 neonates (54%) had false positive salivary CMV PCR results. The PPV of saliva-based CMV testing was 46%. Of the 19 infants with a positive urine test during this period, 7 (36%) had moderate to profound hearing loss. Eight patients were lost to audiologic follow-up during the study period. The PPV of 46% confirms that while salivary testing may be a useful initial screening test due to the ease of sample collection, confirmation by urine PCR testing is necessary. Although hearing-targeted cCMV newborn screening is able to identify newborns with cCMV and early onset SNHL, it fails to identify those with cCMV who pass the hearing screen at birth but remain at high risk for hearing loss. Ongoing efforts to evaluate universal cCMV screening in NYS may decrease this limitation, potentially enabling a larger population of children to benefit from earlier intervention. Geoffrey A. Weinberg, MD, Inhalon Biopharma: Advisor/Consultant|Merck & Co: Honoraria Mary T. Caserta, MD, Merck: Grant/Research Support|Moderna: Grant/Research Support Jennifer L. Nayak, MD, Merck: Grant/Research Support|Moderna: Grant/Research Support|Pfizer, Inc.: Grant/Research Support|Sanofi: Grant/Research Support

Abstract Background Respiratory syncytial virus (RSV) epidemics are a leading cause of hospitalization in infants. Those infants with severe illness appear more likely to develop recurrent wheeze. We aimed to test if airway gene expression and microbiome/metagenome composition in the nasal epithelium during primary RSV infection are associated with illness severity and can identify infants with recurrent wheeze.Table 1.Subject Characteristics Methods Healthy infants with PCR confirmed RSV were prospectively recruited from inpatient and outpatient locations over three seasons (Dec 2019 to Dec 2023). Clinical and demographic data, 2 anterior nasal swabs and a nasal wash were collected. Microbiome/metagenome analysis and transcriptome/RNA sequencing were performed on the nasal biospecimens. Disease severity was measured by the Global Respiratory Severity Score (GRSS) and retrained improved Global Respiratory Severity Score (iGRSS). Subjects were followed for 12 months to identify recurrent wheezing.Figure 1.Top 20 genes associated with iGRSS Results 100 (80 hospitalized) infants were enrolled. Two children were found to be ineligible leaving 98 for analysis. The average age was 3.2 (2.3 SD) months. 60 (61%) were male. A multivariate linear regression model was used to associate gene expression profiles with GRSS and iGRSS. After controlling false discovery rate (FDR) at 0.10 level, 283 genes were significantly associated with iGRSS (95 at 0.05). Gene expression changes involved both Innate Immune and Interleukin Signaling pathways. Metagenome analysis identified microbial species and the microbial metabolic state of the nares during acute infection. We found an abundance of Moraxella in the anterior nares was inversely associated with iGRSS while the abundance of Haemophilus was directly associated with iGRSS. We also identified 29 metabolic pathways associated with the iGRSS including coenzyme A biosynthesis I (procaryotic), mixed acid fermentation, Cavin-Benson-Bassham cycle and superpathways of branched chain amino acid biosynthesis.Figure 2.Bacterial Abundance vs. iGRSS Conclusion We enrolled a cohort of previously healthy infants with primary RSV infection and identified associations between host nasal gene expression, nasal microbiome/metagenome composition/activity and disease severity. We are currently testing for associations between these biomarkers and recurrent wheeze.Figure 3.Metabolic Pathways associated with iGRSS Disclosures Mary T. Caserta, MD, Merck: Grant/Research Support|Moderna: Grant/Research Support|Pfizer: Grant/Research Support Edward E. Walsh, MD, Enanta: Advisor/Consultant|Enanta: Honoraria|GSK: Advisor/Consultant|Janssen: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support

Respiratory Syncytial Virus (RSV) disease in newborns ranges from mild symptoms to severe disease requiring hospitalization. RSV is classified into two subtypes (RSVA and RSVB) based on antigenic and genetic differences. The role these genomic variations play in disease severity remains unknown. Genome sequences were obtained using next-generation RNA sequencing on archived frozen nasal swabs of young children (< 8 months-old) infected with RSV in Rochester, NY between 1977-1998. Samples were chosen from both children hospitalized with severe RSV disease (inpatient) and those presenting with mild symptoms (outpatient) during their first cold-season. Both A and B subtypes demonstrated significant differences in the phylogeny and primary-protein structure during this time period. We found a significant association between RSV phylogeny over this time period and disease severity. For both subtypes, the G-protein demonstrated the greatest amino acid substitutions, although the number of amino acid substitutions was higher in the RSVA subtype. We found a significant association between G-protein variation and disease severity for RSVA, but not RSVB. For both subtypes, variation in the M2-2 protein was significantly associated with disease severity. These results suggest that the genetic variability of RSV proteins may contribute to disease severity in humans. Importance Each cold-season Respiratory Syncytial Virus (RSV) infects thousands of children in the US. Some will display mild cold symptoms while others develop severe disease, sometimes resulting in lifelong lung problems or fatality. RSV initiates infection and replicates in the nasopharynx. Substitutions in the RSV genome can be found in clinically isolated nasal-swab samples of RSV infected children. Whether these genome variations contribute to severe disease is unknown. Here we found a statistically significant association between RSV phylogeny and disease severity. Furthermore, we found specific RSV proteins (G and M2-2) whose amino acid variation was statistically associated with severe disease, although which protein was associated depended on subtype. Taken together, our results suggest that RSV genotype contributed to disease severity over this time period.

OBJECTIVE:The objective of this study was to determine if valganciclovir initiated after 1 month of age improves congenital cytomegalovirus-associated sensorineural hearing loss. STUDY DESIGN:We conducted a randomized, double-blind, placebo-controlled phase 2 trial of 6 weeks of oral valganciclovir at US (n = 12) and UK (n = 9) sites. Patients of ages 1 month through 3 years with baseline sensorineural hearing loss were enrolled. The primary outcome was change in total ear hearing between baseline and study month 6. Secondary outcome measures included change in best ear hearing and reduction in cytomegalovirus viral load in blood, saliva, and urine. RESULTS:Of 54 participants enrolled, 35 were documented to have congenital cytomegalovirus infection and were randomized (active group: 17; placebo group: 18). Mean age at enrollment was 17.8 ± 15.8 months (valganciclovir) vs 19.5 ± 13.1 months (placebo). Twenty (76.9%) of the 26 ears from subjects in the active treatment group did not have worsening of hearing, compared with 27 (96.4%) of 28 ears from subjects in the placebo group (P = .09). All other comparisons of total ear or best ear hearing outcomes were also not statistically significant. Saliva and urine viral loads decreased significantly in the valganciclovir group but did not correlate with change in hearing outcome. CONCLUSIONS:In this randomized controlled trial, initiation of antiviral therapy beyond the first month of age did not improve hearing outcomes in children with congenital cytomegalovirus-associated sensorineural hearing loss. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov identifier NCT01649869.

Guidance from the American Academy of Pediatrics (AAP) for the use of palivizumab prophylaxis against respiratory syncytial virus (RSV) was first published in a policy statement in 1998. AAP recommendations have been updated periodically to reflect the most recent literature regarding children at greatest risk of severe RSV disease. Since the last update in 2014, which refined prophylaxis guidance to focus on those children at greatest risk, data have become available regarding the seasonality of RSV circulation, the incidence and risk factors associated with bronchiolitis hospitalizations, and the potential effects of the implementation of prophylaxis recommendations on hospitalization rates of children with RSV infection. This technical report summarizes the literature review by the Committee on Infectious Diseases, supporting the reaffirmation of the 2014 AAP policy statement on palivizumab prophylaxis among infants and young children at increased risk of hospitalization for RSV infection. Review of publications since 2014 did not support a change in recommendations for palivizumab prophylaxis and continues to endorse the guidance provided in the 2021 Red Book.

Objective:To evaluate the demographic, maternal, and community-level predictors of pediatric respiratory syncytial virus (RSV) and influenza diagnosis among an urban population of children residing in Rochester, NY.Study design:A test-negative case-control design was used to investigate various non-clinical determinants of RSV and influenza diagnosis among 1,808 children aged 0-14 years who presented to the University of Rochester Medical Center (URMC) or an affiliated health clinic in Rochester, NY between 2012-2019. These children were all tested for RSV and influenza via polymerase-chain-reaction (PCR) method, including RSV and influenza diagnosis of all severity types. Test results were linked to medical records, birth certificates, questionnaires administered through the Statewide Perinatal Data System, and the US census by census tracts to obtain information on child, maternal, demographic, and socio-economic characteristics.Results:Overall the strongest predictor of RSV and influenza diagnosis was child's age, with every year increase in child's age, risk for RSV decreased (OR: 0.75; 95% CI: 0.71, 0.79) and risk for influenza increased (OR: 1.20; 95%: 1.16, 1.24). In addition to age, non-private insurance type was positively associated with influenza diagnosis. When considering the proportion of positive cases for RSV and influenza over all PCR tests by respiratory season, a spike in influenza cases was observed in 2018-2019.Conclusions:Age was a strong predictor of RSV and influenza diagnosis among this urban sample of children.

This statement updates the recommendations of the American Academy of Pediatrics for the routine use of influenza vaccine and antiviral medications in the prevention and treatment of influenza in children during the 2022-2023 influenza season. A detailed review of the evidence supporting these recommendations is published in the accompanying technical report (http://www.pediatrics.org/cgi/doi/10.1542/ peds.2022-059275). The American Academy of Pediatrics recommends annual influenza vaccination of all children without medical contraindications starting at 6 months of age. Influenza vaccination is an important strategy for protecting children and the broader community, as well as reducing the overall burden of respiratory illnesses when other viruses, including severe acute respiratory syndrome-coronavirus 2, are cocirculating. Any licensed influenza vaccine appropriate for age and health status can be administered, ideally as soon as possible in the season, without preference for one product or formulation over another. Antiviral treatment of influenza with any US Food and Drug Administration-approved, age-appropriate influenza antiviral medication is recommended for children with suspected or confirmed influenza who are hospitalized, have severe or progressive disease, or have underlying conditions that increase their risk of complications of influenza, regardless of duration of illness. Antiviral treatment should be initiated as soon as possible. Antiviral treatment may be considered in the outpatient setting for symptomatic children with suspected or confirmed influenza disease who are not at high risk for influenza complications, if treatment can be initiated within 48 hours of illness onset, and for children with suspected or confirmed influenza disease whose siblings or household contacts either are younger than 6 months or have a high-risk condition that predisposes them to complications of influenza. Antiviral chemoprophylaxis is recommended for the prevention of influenza virus infection as an adjunct to vaccination in certain individuals, especially exposed children who are at high risk for influenza complications but have not yet been immunized or who lack a sufficient immune response.

BACKGROUND:Febrile infants are at risk for invasive bacterial infections (IBIs) (i.e., bacteremia and bacterial meningitis), which, when undiagnosed, may have devastating consequences. Current IBI predictive models rely on serum biomarkers, which may not provide timely results and may be difficult to obtain in low-resource settings.OBJECTIVE:The aim of this study was to derive a clinical-based IBI predictive model for febrile infants.DESIGNS, SETTING, AND PARTICIPANTS:This is a cross-sectional study of infants brought to two pediatric emergency departments from January 2011 to December 2018. Inclusion criteria were age 0-90 days, temperature ≥38°C, and documented gestational age, fever duration, and illness duration.MAIN OUTCOME AND MEASURES:To detect IBIs, we used regression and ensemble machine learning models and evidence-based predictors (i.e., sex, age, chronic medical condition, gestational age, appearance, maximum temperature, fever duration, illness duration, cough status, and urinary tract inflammation). We up-weighted infants with IBIs 8-fold and used 10-fold cross-validation to avoid overfitting. We calculated the area under the receiver operating characteristic curve (AUC), prioritizing a high sensitivity to identify the optimal cut-point to estimate sensitivity and specificity.RESULTS:Of 2311 febrile infants, 39 had an IBI (1.7%); the median age was 54 days (interquartile range: 35-71). The AUC was 0.819 (95% confidence interval: 0.762, 0.868). The predictive model achieved a sensitivity of 0.974 (0.800, 1.00) and a specificity of 0.530 (0.484, 0.575). Findings suggest that a clinical-based model can detect IBIs in febrile infants, performing similarly to serum biomarker-based models. This model may improve health equity by enabling clinicians to estimate IBI risk in any setting. Future studies should prospectively validate findings across multiple sites and investigate performance by age.

BACKGROUND AND OBJECTIVE For febrile infants, predictive models to detect bacterial infections are available, but clinical adoption remains limited by implementation barriers. There is a need for predictive models using widely available predictors. Thus, we previously derived 2 novel predictive models (machine learning and regression) by using demographic and clinical factors, plus urine studies. The objective of this study is to refine and externally validate the predictive models. METHODS This is a cross-sectional study of infants initially evaluated at one pediatric emergency department from January 2011 to December 2018. Inclusion criteria were age 0 to 90 days, temperature ≥38°C, documented gestational age, and insurance type. To reduce potential biases, we derived models again by using derivation data without insurance status and tested the ability of the refined models to detect bacterial infections (ie, urinary tract infection, bacteremia, and meningitis) in the separate validation sample, calculating areas-under-the-receiver operating characteristic curve, sensitivities, and specificities. RESULTS Of 1419 febrile infants (median age 53 days, interquartile range = 32-69), 99 (7%) had a bacterial infection. Areas-under-the-receiver operating characteristic curve of machine learning and regression models were 0.92 (95% confidence interval [CI] 0.89-0.94) and 0.90 (0.86-0.93) compared with 0.95 (0.91-0.98) and 0.96 (0.94-0.98) in the derivation study. Sensitivities and specificities of machine learning and regression models were 98.0% (94.7%-100%) and 54.2% (51.5%-56.9%) and 96.0% (91.5%-99.1%) and 50.0% (47.4%-52.7%). CONCLUSIONS Compared with the derivation study, the machine learning and regression models performed similarly. Findings suggest a clinical-based model can estimate bacterial infection risk. Future studies should prospectively test the models and investigate strategies to optimize clinical adoption.

During this pandemic, the impact of health disparities on mortality due to COVID-19 has been high among our concerns about this illness.1–4 Unfortunately, disparities related to respiratory infections are not limited to COVID-19. There are decades of research revealing that morbidity and mortality are strongly influenced by the social determinants of health (SDOH).Respiratory syncytial virus (RSV) is the leading cause of lower respiratory infection (LRI) in infants and a major cause of hospitalization in the first 2 years of life.5–7 In this issue of Pediatrics, Fitzpatrick et al8 report on the impact of sociodemographic and psychosocial factors on the risk for RSV hospitalization in children <3 years of age in Ontario, Canada. The authors used linked sociodemographic and health administrative data sets covering the period from 2012 to 2018 to identify factors associated with hospitalization. Their findings reveal the increased risk of hospitalization associated with maternal characteristics consistent with social vulnerability, including younger age, involvement with the criminal justice system, and mental health problems or addiction. The use of low-income drug benefits, a measure of socioeconomic status, was also associated with RSV hospitalization, as was an area level measure of income showing an increased risk of hospitalization with the lowest two quartiles of income.In their study, Fitzpatrick et al8 reinforce the important, enduring, and widespread influence of SDOH on our youngest patients. These data add to the existing literature by identifying associations between hospitalization for respiratory disease in infants and specific sociodemographic factors as well as including findings from Ontario, Canada. Unfortunately, these data also confirm reports that stretch back for several decades linking SDOH with respiratory disease in infants. McConnochie et al9 used census and hospital discharge data from New York state to investigate variations in hospitalization rates for LRI in infants from 1985 to 1991. LRI hospitalization rates were significantly associated with the unemployment rate of an area in the full state analysis. When limited to Monroe County, New York, the LRI hospitalization rate increased notably from the suburban to the inner-city zip codes with a corresponding increase in measures of poverty.The association between hospitalization for acute respiratory infections and bronchiolitis in infants with sociodemographic characteristics associated with deprivation, such as measures of overcrowding, home ownership, and unemployment, has also been shown in studies conducted from the early 1990s to 2015 in England and New Zealand.10–12 Despite the long-standing recognition of these associations, Fitzpatrick et al8 identify specific psychosocial and sociodemographic factors that impact infant hospitalization rates for acute respiratory infections and highlight the intractable nature of the SDOH effect on health and health care use.Hospitalization is often used as a proxy measure for RSV disease severity because of the variable nature of the respiratory symptoms over time, leading to the difficulty in determining illness severity. Although the use of pulse oximetry provides an objective measure of oxygenation, several other clinical factors are often used to determine the need for hospitalization. Maternal psychosocial characteristics and prenatal health care usage patterns have been associated with rehospitalization in an infant Medicaid population, confirming that social factors impact health care providers’ decisions on hospitalization.13 The report by Fitzpatrick et al8 does not allow a determination to be made between the need for hospitalization due to RSV disease severity and the concern for the family’s ability to care for a child with symptomatic RSV disease, regardless of severity. This distinction is important when contemplating ways to decrease hospitalization due to RSV infection in infants.In a recent publication, researchers examined child, family, and health care risk factors for RSV hospitalization in infants and toddlers in the first 3 years of life in Scotland.14 Population-attributable fractions for each significant risk factor were calculated. A reduction in hospitalization of 34% was predicted by eliminating the risk from older siblings in the home. This factor was associated with the largest impact on hospitalization, with the presence of chronic conditions (6.5%), maternal smoking (5.9%), and delayed vaccinations (2.5%) all substantially less. Fitzpatrick et al8 also reported population-attributable fractions for RSV hospitalization. They confirmed that interventions aimed at decreasing the risk of RSV disease in young infants and infants with older siblings could prevent a large percentage of hospitalizations (45.5% and 41.6%, respectively). A 7% decrease in RSV hospitalizations was predicted by removing the risk associated with living in lower income neighborhoods. Attributable risks due to maternal mental health problems and or addiction and involvement with the criminal justice system were statistically significant but impacted <1% of admissions. These data reinforce the importance of infant and family characteristics in determining RSV hospitalization, specifically young age during the RSV season and the presence of older siblings.We know that RSV LRI is a major reason for hospital admission in the first year of life. Additionally, a large majority of infants admitted to the hospital because of RSV LRI are previously healthy term infants. Fitzpatrick et al8 reveal that the largest population level impact for reducing infant hospitalizations due to RSV would be to protect the youngest infants and those with siblings at home.Thankfully, research into the prevention of RSV disease continues to move forward. Efforts aimed at protecting the neonate and young infant by passive immunization via maternal vaccination or with enhanced, long half-life monoclonal antibodies that could be given to all newborns in their first RSV season have been recently described.15,16 Programs under development for immunizing older infants and siblings also show promise.17Do these advances point to a way forward? Although disparities in vaccination rates have been identified on the bases of measures of social vulnerability, national vaccination coverage rates in the United States for children remain high and stable.18 Additionally, various interventions aimed at reducing gaps in vaccination coverage based on race and income levels have shown substantial promise.19–21 Widespread vaccination was the greatest public health advance of the last century. We are looking forward to an even better future in which successful vaccine and preventive strategies targeted against RSV are widely disseminated with equal access for all our children.

BackgroundA substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness. MethodWe defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1-10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness severity score (GRSS). Using AIC-based model selection, we built a sparse linear correlate of GRSS based on 41 genes (NGSS1). We also built an alternate model based upon 13 genes associated with severe infection acutely but displaying stable expression over time (NGSS2). ResultsNGSS1 is strongly correlated with the disease severity, demonstrating a naïve correlation (ρ) of ρ=0.935 and cross-validated correlation of 0.813. As a binary classifier (mild versus severe), NGSS1 correctly classifies disease severity in 89.6% of the subjects following cross-validation. NGSS2 has slightly less, but comparable, accuracy with a cross-validated correlation of 0.741 and classification accuracy of 84.0%. ConclusionAirway gene expression patterns, obtained following a minimally-invasive procedure, have potential utility for development of clinically useful biomarkers that correlate with disease severity in primary RSV infection.

Vaccines are safe and effective in protecting individuals and populations against infectious diseases. New vaccines are evaluated by a long-standing, rigorous, and transparent process by the US Food and Drug Administration and the Centers for Disease Control and Prevention (CDC). All available safety and efficacy data are reviewed before authorization or approval of policy recommendations.

Objective To develop a novel predictive model using primarily clinical history factors and compare performance to the widely used Rochester Low Risk (RLR) model. Study design In this cross-sectional study, we identified infants brought to one pediatric emergency department from January 2014 to December 2016. We included infants age 0-90 days, with temperature >= 38 degrees C, and documented gestational age and illness duration. The primary outcome was bacterial infection. We used 10 predictors to develop regression and ensemble machine learning models, which we trained and tested using 10-fold cross-validation. We compared areas under the curve (AUCs), sensitivities, and specificities of the RLR, regression, and ensemble models. Results Of 877 infants, 67 had a bacterial infection (7.6%). The AUCs of the RLR, regression, and ensemble models were 0.776 (95% CI 0.746, 0.807), 0.945 (0.913, 0.977), and 0.956 (0.935, 0.975), respectively. Using a bacterial infection risk threshold of .01, the sensitivity and specificity of the regression model was 94.6% (87.4%, 100%) and 74.5% (62.4%, 85.4%), compared with 95.5% (87.5%, 99.1%) and 59.6% (56.2%, 63.0%) using the RLR model. Conclusions Compared with the RLR model, sensitivities of the novel predictive models were similar whereas AUCs and specificities were significantly greater. If externally validated, these models, by producing an individualized bacterial infection risk estimate, may offer a targeted approach to young febrile infants that is noninvasive and inexpensive.

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.

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.