Integrated omics endotyping of infants with respiratory syncytial virus bronchiolitis and risk of childhood asthma

Respiratory syncytial virus (RSV) bronchiolitis is not only the leading cause of hospitalization in U.S. infants, but also a major risk factor for asthma development. While emerging evidence suggests clinical heterogeneity within RSV bronchiolitis, little is known about its biologically-distinct endotypes. Here, we integrated clinical, virus, airway microbiome (species-level), transcriptome, and metabolome data of 221 infants hospitalized with RSV bronchiolitis in a multicentre prospective cohort study. We identified four biologically- and clinically-meaningful endotypes: A) clinicalclassicmicrobiomeM. nonliquefaciensinflammationIFN-intermediate, B) clinicalatopicmicrobiomeS. pneumoniae/M. catarrhalisinflammationIFN-high, C) clinicalseveremicrobiomemixedinflammationIFN-low, and D) clinicalnon-atopicmicrobiomeM.catarrhalisinflammationIL-6. Particularly, compared with endotype A infants, endotype B infants-who are characterized by a high proportion of IgE sensitization and rhinovirus coinfection, S. pneumoniae/M. catarrhalis codominance, and high IFN-α and -γ response-had a significantly higher risk for developing asthma (9% vs. 38%; OR, 6.00: 95%CI, 2.08-21.9; P = 0.002). Our findings provide an evidence base for the early identification of high-risk children during a critical period of airway development.

Importance of beta-lactam pharmacokinetics and pharmacodynamics on the recovery of microbial diversity in the airway of persons with cystic fibrosis

Cystic fibrosis (CF) is a chronic lung disease characterized by acute pulmonary exacerbations (PExs) that are frequently treated with antibiotics. The impact of antibiotics on airway microbial diversity remains a critical knowledge gap. We sought to define the association between beta-lactam pharmacokinetic (PK) and pharmacodynamic target attainment on richness and alpha diversity. Twenty-seven children <18 years of age with CF participated in the prospective study. Airway samples were collected at hospital admission for PEx, end of antibiotic treatment (Tr), and >1 month in follow-up (FU). Metagenomic sequencing was performed to determine richness, alpha diversity, and the presence of antibiotic resistance genes. Free plasma beta-lactam levels were measured, and PK modeling was performed to determine time above the minimum inhibitory concentration (fT>MIC). 52% of study subjects had sufficient fT>MIC for optimal bacterial killing. There were no significant differences in demographics or PEx characteristics, except for F508del homozygosity. No significant differences were noted in richness or alpha diversity at individual time points, and both groups experienced a decrease in richness and alpha diversity at Tr compared with PEx. However, alpha diversity remained decreased at FU compared with PEx in those with sufficient fT>MIC but increased in those with insufficient fT>MIC (Shannon -0.222 vs +0.452, p=0.031, and inverse Simpson -1.376 vs +1.388, p=0.032). Fluoroquinolone resistance was also more frequently detected in those with insufficient fT>MIC (log2 fold change (log2FC) 2.29, p=0.025). These findings suggest sufficient beta-lactam fT>MIC is associated with suppressed recovery of alpha diversity following the antibiotic exposure period.

Relationship of Soluble Interleukin-6 Receptors With Asthma: A Mendelian Randomization Study

Purpose: Emerging evidence suggests a potential role of interleukin-6 pathways—trans-signaling with soluble interleukin-6 receptors—in the asthma pathobiology. Despite the evidence for their associations with asthma, the causal role of soluble interleukin-6 receptors remains uncertain. We investigated the relations of soluble interleukin-6 receptors with asthma and its major phenotypes.

Methods: We conducted a two-sample Mendelian randomization study. As genetic instruments, we selected 33 independent cis-acting variants strongly associated with the level of plasma soluble interleukin-6 receptor in the INTERVAL study. To investigate the association of variants with asthma and its phenotypes, we used genome-wide association study data from the UK Biobank. We combined variant-specific causal estimates by the inverse-variance weighted method for each outcome.

Results: Genetically-instrumented soluble interleukin-6 receptor level was associated with a significantly higher risk of overall asthma (OR per one standard deviation increment in inverse-rank normalized soluble interleukin-6 receptor level, 1.02; 95%CI, 1.01–1.03; P = 0.004). Sensitivity analyses demonstrated consistent results and indicated no directional pleiotropy—e.g., MR-Egger (OR, 1.03; 95%CI, 1.01–1.05; P = 0.002; P_intercept =0.37). In the stratified analysis, the significant association persisted across asthma phenotypes—e.g., childhood asthma (OR, 1.05; 95%CI, 1.02–1.08; P < 0.001) and obese asthma (OR, 1.02; 95%CI 1.01–1.03; P = 0.007). Sensitivity analysis using 16 variants selected with different thresholds also demonstrated significant associations with overall asthma and its phenotypes.

Conclusion: Genetically-instrumented soluble interleukin-6 receptor level was causally associated with modestly but significantly higher risks of asthma and its phenotypes. Our observations support further investigations into identifying specific endotypes in which interleukin-6 pathways may play major roles.

Inflammation in children with cystic fibrosis: contribution of bacterial production of long-chain fatty acids

BACKGROUND

Cystic fibrosis (CF) affects >70,000 people worldwide, yet the microbiologic trigger for pulmonary exacerbations (PExs) remains unknown. The objective of this study was to identify changes in bacterial metabolic pathways associated with clinical status.

METHODS

Respiratory samples were collected at hospital admission for PEx, end of intravenous (IV) antibiotic treatment, and follow-up from 27 hospitalized children with CF. Bacterial DNA was extracted and shotgun DNA sequencing was performed. MetaPhlAn2 and HUMAnN2 were used to evaluate bacterial taxonomic and pathway relative abundance, while DESeq2 was used to evaluate differential abundance based on clinical status.

RESULTS

The mean age of study participants was 10 years; 85% received combination IV antibiotic therapy (beta-lactam plus a second agent). Long-chain fatty acid (LCFA) biosynthesis pathways were upregulated in follow-up samples compared to end of treatment: gondoate (p = 0.012), oleate (p = 0.048), palmitoleate (p = 0.043), and pathways of fatty acid elongation (p = 0.012). Achromobacter xylosoxidans and Escherichia sp. were also more prevalent in follow-up compared to PEx (p < 0.001).

CONCLUSIONS

LCFAs may be associated with persistent infection of opportunistic pathogens. Future studies should more closely investigate the role of LCFA production by lung bacteria in the transition from baseline wellness to PEx in persons with CF.

IMPACT

Increased levels of LCFAs are found after IV antibiotic treatment in persons with CF. LCFAs have previously been associated with increased lung inflammation in asthma. This is the first report of LCFAs in the airway of persons with CF. This research provides support that bacterial production of LCFAs may be a contributor to inflammation in persons with CF. Future studies should evaluate LCFAs as predictors of future PExs.

Integrated-omics endotyping of infants with rhinovirus bronchiolitis and risk of childhood asthma

BACKGROUND

Young children with rhinovirus (RV) infection-particularly bronchiolitis-are at high risk for developing childhood asthma. Emerging evidence suggests clinical heterogeneity within RV bronchiolitis. However, little is known about these biologically distinct subgroups (endotypes) and their relations with asthma risk.

OBJECTIVE

We aimed to identify RV bronchiolitis endotypes and examine their longitudinal relations with asthma risk.

METHODS

As part of a multicenter prospective cohort study of infants (age <12 months) hospitalized for bronchiolitis, we integrated clinical, RV species (RV-A, RV-B, and RV-C), nasopharyngeal microbiome (16S rRNA gene sequencing), cytokine, and metabolome (liquid chromatography tandem mass spectrometry) data collected at hospitalization. We then applied network and clustering approaches to identify bronchiolitis endotypes. We also examined their longitudinal association with risks of developing recurrent wheeze by age 3 years and asthma by age 5 years.

RESULTS

Of 122 infants hospitalized for RV bronchiolitis (median age, 4 months), we identified 4 distinct endotypes-mainly characterized by RV species, microbiome, and type 2 cytokine (T2) response: endotype A, virus^RV-Cmicrobiome^mixedT2^low; endotype B, virus^RV-Amicrobiome^HaemophilusT2^low; endotype C, virus^RSV/RVmicrobiome^{Streptococcus}T2^low; and endotype D, virus^RV-Cmicrobiome^MoraxellaT2^high. Compared with endotype A infants, endotype D infants had a significantly higher rate of recurrent wheeze (33% vs 64%; hazard ratio, 2.23; 95% CI, 1.00-4.96; P = .049) and a higher risk for developing asthma (28% vs 59%; odds ratio, 3.74: 95% CI, 1.21-12.6; P = .03).

CONCLUSIONS

Integrated-omics analysis identified biologically meaningful RV bronchiolitis endotypes in infants, such as one characterized by RV-C infection, Moraxella-dominant microbiota, and high T2 cytokine response, at higher risk for developing recurrent wheeze and asthma. This study should facilitate further research toward validating our inferences.

Serum soluble receptor for advanced glycation end-products (sRAGE) in infants with bronchiolitis: Associations with acute severity and recurrent wheeze

BACKGROUND

Although bronchiolitis contributes to substantial acute (e.g., intensive care use) and chronic (e.g., recurrent wheeze and infections) morbidities in young children, the pathobiology remains uncertain. We examined relations of serum soluble receptor for advanced glycation end-products (sRAGE) with acute and chronic morbidities of bronchiolitis and whether the effect of serum sRAGE on development of recurrent wheeze is mediated through acute severity.

METHODS

A multi-center, multi-year, prospective cohort study of infants hospitalized for bronchiolitis was analyzed. We measured serum sRAGE level at acute hospitalization and examined its association with intensive care use (use of mechanical ventilation and/or admission to intensive care unit) and development of recurrent wheeze by age 3 years. We performed causal mediation analysis to estimate indirect (mediation) and direct effects of sRAGE on recurrent wheeze.

RESULTS

In 886 infants with bronchiolitis, median age was 2.9 months. Overall, 15% underwent intensive care and 32% developed recurrent wheeze by age 3 years. In the multivariable model adjusting for 11 confounders, higher presenting sRAGE level was associated with significantly lower risk of intensive care use (OR for each one-log increment, 0.39; 95%CI 0.16-0.91; P=0.03) and significantly lower rate of recurrent wheeze (HR 0.58; 95%CI 0.36-0.94; P=0.03). In mediation analysis, the direct effect was significant (HR 0.60; 95%CI 0.37-0.97; P=0.04) while the indirect effect was not (P=0.30).

CONCLUSIONS

Serum sRAGE levels were inversely associated with acute and chronic morbidities of bronchiolitis. Effect of sRAGE on development of recurrent wheeze is potentially driven through pathways other than acute severity of bronchiolitis.

Development of Persistent Respiratory Morbidity in Previously Healthy Children After Acute Respiratory Failure

OBJECTIVES

Acute respiratory failure is a common reason for admission to PICUs. Short- and long-term effects on pulmonary health in previously healthy children after acute respiratory failure requiring mechanical ventilation are unknown. The aim was to determine if clinical course or characteristics of mechanical ventilation predict persistent respiratory morbidity at follow-up.

DESIGN

Prospective cohort study with follow-up questionnaires at 6 and 12 months.

SETTING

Ten U.S. PICUs.

PATIENTS

Two-hundred fifty-five children were included in analysis after exclusion for underlying chronic disease or incomplete data. One-hundred fifty-eight and 130 children had follow-up data at 6 and 12 months, respectively.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Pulmonary dysfunction at discharge a priori defined as one of: mechanical ventilation, supplemental oxygen, bronchodilators or steroids at 28 days or discharge. Persistent respiratory morbidity a priori defined as a respiratory PedsQL, a pediatric quality of life measure, greater than or equal to 5 or asthma diagnosis, bronchodilator or inhaled steroids, or unscheduled clinical evaluation for respiratory symptoms. Multivariate backward stepwise regression using Akaike information criterion minimization determined independent predictors of these outcomes. Pulmonary dysfunction at discharge was present in 34% of patients. Positive bacterial respiratory culture predicted pulmonary dysfunction at discharge (odds ratio, 4.38; 95% CI, 1.66-11.56). At 6- and 12-month follow-up 42% and 44% of responders, respectively, had persistent respiratory morbidity. Pulmonary dysfunction at discharge was associated with persistent respiratory morbidity at 6 months, and persistent respiratory morbidity at 6 months was strongly predictive of 12-month persistent respiratory morbidity (odds ratio, 18.58; 95% CI, 6.68-52.67). Positive bacterial respiratory culture remained predictive of persistent respiratory morbidity in patients at both follow-up points.

CONCLUSIONS

Persistent respiratory morbidity develops in up to potentially 44% of previously healthy children less than or equal to 24 months old at follow-up after acute respiratory failure requiring mechanical ventilation. This is the first study, to our knowledge, to suggest a prevalence of persistent respiratory morbidity and the association between positive bacterial respiratory culture and pulmonary morbidity in a population of only previously healthy children with acute respiratory failure.

Airway microbial diversity is decreased in young children with cystic fibrosis compared to healthy controls but improved with CFTR modulation

BACKGROUND

Culture-independent next generation sequencing has identified diverse microbial communities within the cystic fibrosis (CF) airway. The study objective was to test for differences in the upper airway microbiome of children with CF and healthy controls and age-related differences in children with CF.

METHODS

Oropharyngeal swabs and clinical data were obtained from 25 children with CF and 50 healthy controls aged ≤6 years. Bacterial DNA was amplified and sequenced for the V4 region of 16S rRNA marker-gene. Alpha diversity was measured using operational taxonomic units (OTUs), Shannon diversity, and the inverse Simpson's index. Beta diversity was measured using Morisita-Horn and Bray-Curtis and Jaccard distances. General linear models were used for comparison of alpha diversity measures between groups to account for differences in demographics and exposures. Mixed effects general linear models were used for longitudinal comparisons 1) between children with CF of different ages and 2) between children with CF receiving CF transmembrane conductance regulator (CFTR) modulators, children with CF not receiving CFTR modulators, and healthy controls to adjust for repeated measures per subject.

RESULTS

Children with CF were more likely to have received antibiotics in the prior year than healthy controls (92% vs 24%, p < 0.001). Controlling age, race, ethnicity, length of breastfeeding, and having siblings, children with CF had a lower richness than healthy controls: OTUs 62.1 vs 83, p = 0.022; and trended toward lower diversity: Shannon 2.09 vs 2.35, p = 0.057; inverse Simpson 5.7 vs 6.92, p = 0.118. Staphylococcus, three Rothia OTUs, and two Streptococcus OTUs were more abundant in CF children versus healthy controls (all p < 0.05). Bray-Curtis and Jaccard distances, which reflect overall microbial community composition, were also significantly different (both p = 0.001). In longitudinally collected samples from children with CF, Morisita-Horn trended toward more similarity in those aged 0-2 years compared to those aged 3-6 years (p = 0.070). In children >2 years of age, there was a significant trend in increasing alpha diversity measures between children with CF not receiving CFTR modulators, children with CF receiving CFTR modulators, and healthy controls: OTUs 63.7 vs 74.7 vs 97.6, p < 0.001; Shannon 2.11 vs 2.34 vs 2.56, p < 0.001; inverse Simpson 5.78 vs 7.23 vs 7.96, p < 0.001.

CONCLUSIONS

Children with CF have lower bacterial diversity and different composition of organisms compared with healthy controls. This appears to start in early childhood, is possibly related to the use of antibiotics, and may be partially corrected with the use of CFTR modulators.

Longitudinal Associations of the Cystic Fibrosis Airway Microbiome and Volatile Metabolites: A Case Study

The identification of 16S rDNA biomarkers from respiratory samples to describe the continuum of clinical disease states within persons having cystic fibrosis (CF) has remained elusive. We sought to combine 16S, metagenomics, and metabolomics data to describe multiple transitions between clinical disease states in 14 samples collected over a 12-month period in a single person with CF. We hypothesized that each clinical disease state would have a unique combination of bacterial genera and volatile metabolites as a potential signature that could be utilized as a biomarker of clinical disease state. Taxonomy identified by 16S sequencing corroborated clinical culture results, with the majority of the 109 PCR amplicons belonging to the bacteria grown in clinical cultures (Escherichia coli and Staphylococcus aureus). While alpha diversity measures fluctuated across disease states, no significant trends were present. Principle coordinates analysis showed that treatment samples trended toward a different community composition than baseline and exacerbation samples. This was driven by the phylum Bacteroidetes (less abundant in treatment, log₂ fold difference -3.29, p = 0.015) and the genus Stenotrophomonas (more abundant in treatment, log₂ fold difference 6.26, p = 0.003). Across all sputum samples, 466 distinct volatile metabolites were identified with total intensity varying across clinical disease state. Baseline and exacerbation samples were rather uniform in chemical composition and similar to one another, while treatment samples were highly variable and differed from the other two disease states. When utilizing a combination of the microbiome and metabolome data, we observed associations between samples dominated Staphylococcus and Escherichia and higher relative abundances of alcohols, while samples dominated by Achromobacter correlated with a metabolomics shift toward more oxidized volatiles. However, the microbiome and metabolome data were not tightly correlated; examining both the metagenomics and metabolomics allows for more context to examine changes across clinical disease states. In our study, combining the sputum microbiome and metabolome data revealed stability in the sputum composition through the first exacerbation and treatment episode, and into the second exacerbation. However, the second treatment ushered in a prolonged period of instability, which after three additional exacerbations and treatments culminated in a new lung microbiome and metabolome.

Platelets and platelet extracellular vesicles in hemostasis and sepsis

Platelets, cell fragments traditionally thought of as important only for hemostasis, substantially and dynamically contribute to the immune system's response to infection. In addition, there is increasing evidence that externally active platelet entities, including platelet granules and platelet extracellular vesicles (PEVs), play a role not only in hemostasis, but also in inflammatory actions previously ascribed to platelets themselves. Given the functions of platelets and PEVs during inflammation and infection, their role in sepsis is being investigated. Sepsis is a condition marked by the dysregulation of the body's normal activation of the immune system in response to a pathogen. The mechanisms for controlling infection locally become detrimental to the host if they are applied systemically. Similar to cells traditionally ascribed to the immune system, including neutrophils, lymphocytes, and macrophages, platelets are instrumental in helping a host clear an infection, but are also implicated in the uncontrolled amplification of the immune response that leads to sepsis. Clearly, the function of platelets is more complicated than its simple structure and primary role in hemostasis initially suggest. This review provides an overview of platelet and platelet extracellular vesicle structure and function, highlighting the complex role platelets and PEVs play in the body in the context of infection and sepsis.

Sepsis Immunometabolism: From Defining Sepsis to Understanding How Energy Production Affects Immune Response

OBJECTIVES

This review will examine current definitions and trends in sepsis management as well pathophysiologic mechanisms in animal and ex vivo studies that correlate decreased energy production with deranged inflammatory response during the septic process.

DATA SOURCES

The latest articles in the literature that focus on the role of immunometabolism and associated mechanisms in sepsis were selected.

STUDY SELECTION

The most relevant, original articles were included in the review.

DATA EXTRACTION

All pertinent data for sepsis definitions as well as changes in immunometabolic pathways during the septic process was reviewed and assessed for inclusion in this article.

DATA SYNTHESIS

Sepsis is a major cause of multiple organ dysfunction. It is the principal cause of death resulting from infection and one of the most expensive conditions treated in the United States. Despite current efforts to accurately define sepsis, novel treatments and highly trained providers, mortality rates for sepsis remain high, prompting a need for further investigation of underlying immunometabolic mechanisms to identify potential treatment targets. The definition of sepsis has shifted and changed in the past few decades due to poorly defined criteria, as well as unclear guidelines for providers with regards to management of severe sepsis and septic shock. The early identification of patients with a systemic inflammatory response that will progress to septic shock is critical since recent traditional therapeutic approaches, such as early goal-directed therapy, IV immunoglobulin, and anti-tumor necrosis factor-α antibodies have failed.

CONCLUSIONS

There are no effective anti-sepsis drug therapies due to complex inflammatory and metabolic interactions. Further studies regarding the interface between innate immunity and metabolism should be investigated to effectively address septic patient mortality rates.

Cholesterol efflux alterations in adolescent obesity: role of adipose-derived extracellular vesical microRNAs

BACKGROUND

Macrophage cholesterol efflux capacity has been identified as a predictor for cardiovascular disease. We assessed the relationship between adipocyte-derived extracellular vesicle microRNAs and macrophage cholesterol efflux capacity.

METHODS

We assessed an adolescent cohort (n = 93, Age, median (IQR) = 17 (3) year, Female = 71, Male = 22) throughout the BMI continuum (BMI = 45.2 (13.2) kg/m²) for: (1) cholesterol efflux capacity and lipoprotein profiles; (2) adipocyte-derived extracellular vesicle microRNAs in serum; (3) the role of visceral adipose tissue extracellular vesicle in regulation of cholesterol efflux and cholesterol efflux gene expression in THP-1 macrophages in vitro.

RESULTS

Efflux capacity was significantly associated with HDL (r = 0.30, p = 0.01) and LDL (r = 0.33, p = 0.005) particle size. Multivariate-analysis identified six microRNAs associated (p < 0.05) with cholesterol efflux capacity: miR-3129-5p (Beta = 0.695), miR-20b (0.430), miR9-5p (0.111), miR-320d (- 0.190), miR301a-5p (0.042), miR-155-5p (0.004). In response to increasing concentrations (1 μg/mL vs. 3 μg/mL) of VAT extracellular vesicle, cholesterol efflux (66% ± 10% vs. 49% ± 2%; p < 0.01) and expression of ABCA1 (FC = 1.9 ± 0.8 vs 0.5 ± 0.2; p < 0.001), CD36 (0.7 ± 0.4 vs. 2.1 ± 0.8, p = 0.02), CYP27A1 (1.4 ± 0.4 vs. 0.9 ± 0.5; p < 0.05), and LXRA (1.8 ± 1.1 vs. 0.5 ± 0.2; p < 0.05) was altered in THP-1 cells in vitro.

CONCLUSION

Adipocyte-derived extracellular vesicle microRNAs may, in part, be involved macrophage cholesterol efflux regulation.

Changes in microbiome diversity following beta-lactam antibiotic treatment are associated with therapeutic versus subtherapeutic antibiotic exposure in cystic fibrosis

In persons with cystic fibrosis (CF), decreased airway microbial diversity is associated with lower lung function. Conflicting data exist on the impact of short-term antibiotics for treatment of acute pulmonary exacerbations. However, whether differences in antibiotic exposure impacts airway microbiome changes has not been studied. We hypothesized that subtherapeutic beta-lactam antibiotic exposure, determined by the pharmacokinetics and pharmacodynamics (PK/PD) after intravenous (IV) antibiotic administration, would be associated with different patterns of changes in CF airway microbial diversity. Eligible children were enrolled when well; study assessments were performed around the time of pulmonary exacerbation. Plasma drug concentrations and bacterial minimum inhibitory concentrations (MICs) were used to determine therapeutic versus subtherapeutic beta-lactam antibiotic exposure. Respiratory samples were collected from children, and extracted bacterial DNA was amplified for the V4 region of the 16S rRNA gene. Twenty children experienced 31 APEs during the study; 45% (n = 14) of antibiotic courses were deemed therapeutic. Those in the therapeutic group had more significant decreases in alpha diversity at end of treatment and post-recovery compared to baseline than those in the subtherapeutic group. Therapeutic and subtherapeutic beta-lactam use is associated with different patterns of changes in CF airway microbial diversity following antibiotic administration.

Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

IMPORTANCE

While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.

OBJECTIVES

To examine the performance of machine learning approaches to predict clinical outcomes and disposition in children in the ED and to compare their performance with conventional triage approaches.

DESIGN, SETTING, AND PARTICIPANTS

Prognostic study of ED data from the National Hospital Ambulatory Medical Care Survey from January 1, 2007, through December 31, 2015. A nationally representative sample of 52 037 children aged 18 years or younger who presented to the ED were included. Data analysis was performed in August 2018.

MAIN OUTCOMES AND MEASURES

The outcomes were critical care (admission to an intensive care unit and/or in-hospital death) and hospitalization (direct hospital admission or transfer). In the training set (70% random sample), using routinely available triage data as predictors (eg, demographic characteristics and vital signs), we derived 4 machine learning-based models: lasso regression, random forest, gradient-boosted decision tree, and deep neural network. In the test set (the remaining 30% of the sample), we measured the models' prediction performance by computing C statistics, prospective prediction results, and decision curves. These machine learning models were built for each outcome and compared with the reference model using the conventional triage classification information.

RESULTS

Of 52 037 eligible ED visits by children (median [interquartile range] age, 6 [2-14] years; 24 929 [48.0%] female), 163 (0.3%) had the critical care outcome and 2352 (4.5%) had the hospitalization outcome. For the critical care prediction, all machine learning approaches had higher discriminative ability compared with the reference model, although the difference was not statistically significant (eg, C statistics of 0.85 [95% CI, 0.78-0.92] for the deep neural network vs 0.78 [95% CI, 0.71-0.85] for the reference; P = .16), and lower number of undertriaged critically ill children in the conventional triage levels 3 to 5 (urgent to nonurgent). For the hospitalization prediction, all machine learning approaches had significantly higher discrimination ability (eg, C statistic, 0.80 [95% CI, 0.78-0.81] for the deep neural network vs 0.73 [95% CI, 0.71-0.75] for the reference; P < .001) and fewer overtriaged children who did not require inpatient management in the conventional triage levels 1 to 3 (immediate to urgent). The decision curve analysis demonstrated a greater net benefit of machine learning models over ranges of clinical thresholds.

CONCLUSIONS AND RELEVANCE

Machine learning-based triage had better discrimination ability to predict clinical outcomes and disposition, with reduction in undertriaging critically ill children and overtriaging children who are less ill.

Pediatric asthma comprises different phenotypic clusters with unique nasal microbiotas

BACKGROUND

Pediatric asthma is the most common chronic childhood disease in the USA, currently affecting ~ 7 million children. This heterogeneous syndrome is thought to encompass various disease phenotypes of clinically observable characteristics, which can be statistically identified by applying clustering approaches to patient clinical information. Extensive evidence has shown that the airway microbiome impacts both clinical heterogeneity and pathogenesis in pediatric asthma. Yet, so far, airway microbiotas have been consistently neglected in the study of asthma phenotypes. Here, we couple extensive clinical information with 16S rRNA high-throughput sequencing to characterize the microbiota of the nasal cavity in 163 children and adolescents clustered into different asthma phenotypes.

RESULTS

Our clustering analyses identified three statistically distinct phenotypes of pediatric asthma. Four core OTUs of the pathogenic genera Moraxella, Staphylococcus, Streptococcus, and Haemophilus were present in at least 95% of the studied nasal microbiotas. Phyla (Proteobacteria, Actinobacteria, and Bacteroidetes) and genera (Moraxella, Corynebacterium, Dolosigranulum, and Prevotella) abundances, community composition, and structure varied significantly (0.05 < P ≤ 0.0001) across asthma phenotypes and one of the clinical variables (preterm birth). Similarly, microbial networks of co-occurrence of bacterial genera revealed different bacterial associations across asthma phenotypes.

CONCLUSIONS

This study shows that children and adolescents with different clinical characteristics of asthma also show different nasal bacterial profiles, which is indicative of different phenotypes of the disease. Our work also shows how clinical and microbial information could be integrated to validate and refine asthma classification systems and develop biomarkers of disease.

Antibiotic multidrug resistance in the cystic fibrosis airway microbiome is associated with decreased diversity

Background

Cystic fibrosis (CF) is associated with significant morbidity and early mortality due to recurrent acute and chronic lung infections. The chronic use of multiple antibiotics increases the possibility of multidrug resistance (MDR). Antibiotic susceptibility determined by culture-based techniques may not fully represent the resistance profile. The study objective was to detect additional antibiotic resistance using molecular methods and relate the presence of MDR to airway microbiome diversity and pulmonary function.

Methods

Bacterial DNA was extracted from sputum samples and amplified for the V4 region of the 16S rRNA gene. An qPCR array was used to detect antibiotic resistance genes. Clinical culture results and pulmonary function were also noted for each encounter.

Results

Six study participants contributed samples from 19 encounters. Those samples with MDR (n = 7) had significantly lower diversity measured by inverse Simpson's index than those without (n = 12) (2.193 ± 0.427 vs 6.023 ± 1.564, p = 0.035). Differential abundance showed that samples with MDR had more Streptococcus (p = 0.002) and Alcaligenaceae_unclassified (p = 0.002). Pulmonary function was also decreased when MDR was present (FEV₁, 51 ± 22.9 vs 77 ± 26.7, p = 0.054; FVC, 64.5 ± 22.7 vs 91.6 ± 27.7, p = 0.047).

Conclusions

The presence of MDR within the CF airway microbiome was associated with decreased microbial diversity, the presence of Alcaligenes, and decreased pulmonary function.

Microbial diversity within the airway microbiome in chronic pediatric lung diseases

The study of the airway microbiome in children is an area of emerging research, especially in relation to the role microbial diversity may play in acute and chronic inflammation. Three such pediatric airway diseases include cystic fibrosis, asthma, and chronic lung disease of prematurity. In cystic fibrosis, the presence of Pseudomonas spp. is associated with decreased microbial diversity. Decreasing microbial diversity is also associated with poor lung function. In asthma, early viral infections appear to drive changes in bacterial diversity which may be associated with asthma risk. Premature infants with Ureaplasma spp. are at higher risk for chronic lung disease due to inflammation. Microbiome changes due to prematurity also appear to affect the inflammatory response to viral infections post-natally. Importantly, microbial diversity can be measured using metataxonomic (e.g., 16S rRNA sequencing) and metagenomic (e.g., shotgun sequencing) approaches. A metagenomics approach may be preferable as it can provide further granularity of the sample composition, identifying the bacterial species or strain, information on additional microbial components, including fungal and viral components, information about functional genomics of the microbiome, and information about antimicrobial resistance mutations. Future studies of pediatric airway diseases incorporating these techniques may provide evidence for new treatment approaches for these vulnerable patient populations.

Benchmark Evaluation of True Single Molecular Sequencing to Determine Cystic Fibrosis Airway Microbiome Diversity

Cystic fibrosis (CF) is an autosomal recessive disease associated with recurrent lung infections that can lead to morbidity and mortality. The impact of antibiotics for treatment of acute pulmonary exacerbations on the CF airway microbiome remains unclear with prior studies giving conflicting results and being limited by their use of 16S ribosomal RNA sequencing. Our primary objective was to validate the use of true single molecular sequencing (tSMS) and PathoScope in the analysis of the CF airway microbiome. Three control samples were created with differing amounts of Burkholderia cepacia, Pseudomonas aeruginosa, and Prevotella melaninogenica, three common bacteria found in cystic fibrosis lungs. Paired sputa were also obtained from three study participants with CF before and >6 days after initiation of antibiotics. Antibiotic resistant B. cepacia and P. aeruginosa were identified in concurrently obtained respiratory cultures. Direct sequencing was performed using tSMS, and filtered reads were aligned to reference genomes from NCBI using PathoScope and Kraken and unique clade-specific marker genes using MetaPhlAn. A total of 180–518 K of 6–12 million filtered reads were aligned for each sample. Detection of known pathogens in control samples was most successful using PathoScope. In the CF sputa, alpha diversity measures varied based on the alignment method used, but similar trends were found between pre- and post-antibiotic samples. PathoScope outperformed Kraken and MetaPhlAn in our validation study of artificial bacterial community controls and also has advantages over Kraken and MetaPhlAn of being able to determine bacterial strains and the presence of fungal organisms. PathoScope can be confidently used when evaluating metagenomic data to determine CF airway microbiome diversity.

RSV vs. rhinovirus bronchiolitis: difference in nasal airway microRNA profiles and NFκB signaling

BackgroundAlthough rhinovirus infection is associated with increased risks of acute and chronic respiratory outcomes during childhood compared with respiratory syncytial virus (RSV), the underlying mechanisms remain unclear. We aimed to determine the differences in nasal airway microRNA profiles and their downstream effects between infants with rhinovirus and RSV bronchiolitis.MethodsAs part of a multicenter cohort study of infants hospitalized for bronchiolitis, we examined nasal samples obtained from 16 infants with rhinovirus and 16 infants with RSV. We tested nasal airway samples using microarrays to profile global microRNA expression and determine the predicted regulation of targeted transcripts. We also measured gene expression and cytokines for NFκB pathway components.ResultsBetween the virus groups, 386 microRNAs were differentially expressed (false discovery rate (FDR)<0.05). In infants with rhinovirus, the NFκB pathway was highly ranked as a predicted target for these differentially expressed microRNAs compared with RSV. Pathway analysis using measured mRNA expression data validated that rhinovirus infection had upregulation of NFκB family (RelA and NFκB2) and downregulation of inhibitor κB family. Infants with rhinovirus had higher levels of NFκB-induced type-2 cytokines (IL-10 and IL-13; FDR<0.01).ConclusionIn infants with bronchiolitis, rhinovirus and RSV infections had different nasal airway microRNA profiles associated with NFκB signaling.

Conditional reprogramming of pediatric airway epithelial cells: A new human model to investigate early-life respiratory disorders

BACKGROUND

Airway epithelial cells (AEC) are quite difficult to access in newborns and infants. It is critically important to develop robust life-extended models to conduct translational studies in this age group. We propose the use of a recently described cell culture technology (conditionally reprogrammed cells-CRC) to generate continuous primary cell cultures from nasal and bronchial AEC of young children.

METHODS

We collected nasal and/or bronchial AEC from a total of 23 subjects of different ages including newborns/infants/toddlers (0-2 years; N = 9), school-age children (4-11 years; N = 6), and a group of adolescent/adult donors (N = 8). For CRC generation, we used conditioned medium from mitotically inactivated 3T3 fibroblasts and Rho-associated kinase (ROCK) inhibitor (Y-27632). Antiviral immune responses were studied using 25 key antiviral genes and protein production of type III epithelial interferon (IFN λ1) after double-stranded (ds) RNA exposure.

RESULTS

CRC derived from primary AEC of neonates/infants and young children exhibited: (i) augmented proliferative capacity and life extension, (ii) preserved airway epithelial phenotype after multiple passages, (iii) robust immune responses characterized by the expression of innate antiviral genes and parallel nasal/bronchial production of IFN λ1 after exposure to dsRNA, and (iv) induction of airway epithelial inflammatory and remodeling responses to dsRNA (eg, CXCL8 and MMP9).

CONCLUSION

Conditional reprogramming of AEC from young children is a feasible and powerful translational approach to investigate early-life airway epithelial immune responses in humans.

Improved Risk Stratification in Pediatric Septic Shock Using Both Protein and mRNA Biomarkers. PERSEVERE-XP

RATIONALE

We previously derived and validated the Pediatric Sepsis Biomarker Risk Model (PERSEVERE) to estimate baseline mortality risk in children with septic shock. The PERSEVERE biomarkers are serum proteins selected from among the proteins directly related to 80 mortality risk assessment genes. The initial approach to selecting the PERSEVERE biomarkers left 68 genes unconsidered.

OBJECTIVES

To determine if the 68 previously unconsidered genes can improve upon the performance of PERSEVERE and to provide biological information regarding the pathophysiology of septic shock.

METHODS

We reduced the number of variables by determining the biological linkage of the 68 previously unconsidered genes. The genes identified through variable reduction were combined with the PERSEVERE-based mortality probability to derive a risk stratification model for 28-day mortality using classification and regression tree methodology (n = 307). The derived tree, PERSEVERE-XP, was then tested in a separate cohort (n = 77).

MEASUREMENTS AND MAIN RESULTS

Variable reduction revealed a network consisting of 18 mortality risk assessment genes related to tumor protein 53 (TP53). In the derivation cohort, PERSEVERE-XP had an area under the receiver operating characteristic curve (AUC) of 0.90 (95% confidence interval, 0.85-0.95) for differentiating between survivors and nonsurvivors. In the test cohort, the AUC was 0.96 (95% confidence interval, 0.91-1.0). The AUC of PERSEVERE-XP was superior to that of PERSEVERE.

CONCLUSIONS

PERSEVERE-XP combines protein and mRNA biomarkers to provide mortality risk stratification with possible clinical utility. PERSEVERE-XP significantly improves on PERSEVERE and suggests a role for TP53-related cellular division, repair, and metabolism in the pathophysiology of septic shock.