Association of respiratory viruses with serum metabolome in infants with severe bronchiolitis

Respiratory Syncytial Virus Elicits Glycolytic Metabolism in Pediatric Upper and Lower Airways

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract viral infection in infants and causes around 60,000 in-hospital deaths annually. Emerging evidence suggests that RSV induces metabolic changes in host cells to support viral replication, presenting a potential target for therapeutic intervention. To investigate RSV-driven metabolic changes in situ, we combined positron emission tomography (PET), live-cell bioenergetics, and metabolomic profiling in the upper and lower airways of children. PET imaging revealed persistent, hyper-glycolytic regions in the lungs of RSV-infected children. Bioenergetic analysis of freshly collected nasopharyngeal aspirates from infants showed live upper respiratory cells (URCs) infected with RSV in situ exhibited significantly higher levels of glycolysis, glycolytic capacity, glycolytic reserves, and mitochondrial respiration than uninfected controls. Metabolomic analysis of nasopharyngeal fluids from these patients revealed distinct metabolic signatures, including increased citrate and malate, and decreases in taurine. In vitro infection of pediatric nasopharynx tissue-derived multicellular epithelial cultures (TEpiCs) and bronchial epithelial cells further confirmed RSV-induced increases in glycolysis. Together, these findings demonstrate that RSV infection induces hypermetabolism in both upper and lower primary airways in situ, supporting the potential of host-targeted metabolic interventions as a therapeutic strategy-particularly in vulnerable populations such as infants for whom vaccines are not currently available.

Respiratory Virus-Specific Nasopharyngeal Lipidome Signatures and Severity in Infants With Bronchiolitis: A Prospective Multicenter Study

BACKGROUND

In infant bronchiolitis, recent evidence indicates that respiratory viruses (eg, respiratory syncytial virus [RSV], rhinovirus [RV]) contribute to the heterogeneity of disease severity. Of the potential pathobiological molecules, lipids serve as signaling molecules in airway inflammation. However, little is known about the role of the airway lipidome in between-virus heterogeneity and disease severity.

METHODS

In this multicenter prospective study of 800 infants hospitalized for RSV or RV bronchiolitis, we analyzed nasopharyngeal lipidome data. We examined discriminatory lipids between RSV and RV infection and the association of the discriminatory lipids with bronchiolitis severity, defined by positive pressure ventilation (PPV) use.

RESULTS

We identified 30 discriminatory nasopharyngeal lipid species and 8 fatty acids between RSV and RV infection. In the multivariable models adjusting for patient-level confounders, 8 lipid species-for example, phosphatidylcholine (18:2/18:2) (adjusted odds ratio [aOR], 0.23 [95% confidence interval {CI}, .11-.44]; false discovery rate [FDR] = 0.0004) and dihydroceramide (16:0) (aOR, 2.17 [95% CI, 1.12-3.96]; FDR = 0.04)-were significantly associated with the risk of PPV use. Additionally, 6 fatty acids-for example, eicosapentaenoic acid (aOR, 0.27 [95% CI, .11-.57]; FDR = 0.01)-were also significantly associated with the risk of PPV use.

CONCLUSIONS

In infants hospitalized for bronchiolitis, the nasopharyngeal lipidome plays an important role in the pathophysiology of between-virus heterogeneity and disease severity.

Association of Nasopharyngeal and Serum Glutathione Metabolism with Bronchiolitis Severity and Asthma Risk: A Prospective Multicenter Cohort Study

Infants hospitalized for bronchiolitis are at high risk for asthma. Glutathione-related metabolites may antagonize oxidative stress, which induces airway injuries in respiratory infection and subsequent airway remodeling. However, little is known about the relationship of glutathione-related metabolites with bronchiolitis severity and the risk of asthma. In a multicenter prospective observational cohort study of infants hospitalized for bronchiolitis, we measured nasopharyngeal and serum glutathione-related metabolites by using liquid chromatography−tandem mass spectrometry. We then examined their association with bronchiolitis severity (defined by positive pressure ventilation (PPV) use). We also identified severity-related glutathione-related metabolite signatures and examined their association with asthma at age 6 years. In 1013 infants, we identified 12 nasopharyngeal and 10 serum glutathione-related metabolites. In the multivariable models, lower relative abundances of seven metabolites, e.g., substrates of glutathione, including cysteine (adjOR 0.21, 95%CI 0.06−0.76), glycine (adjOR 0.25, 95%CI 0.07−0.85), and glutamate (adjOR 0.25, 95%CI 0.07−0.88), were significantly associated with PPV use (all FDR < 0.05). These associations were consistent with serum glutathione-related metabolites. The nasopharyngeal glutathione-related metabolite signature was also associated with a significantly higher risk of asthma (adjOR 0.90, 95%CI 0.82−0.99, p = 0.04). In infants hospitalized for bronchiolitis, glutathione-related metabolites were associated with bronchiolitis severity and asthma risk.

Nasopharyngeal metatranscriptome profiles of infants with bronchiolitis and risk of childhood asthma: a multicentre prospective study

BACKGROUND

Bronchiolitis is not only the leading cause of hospitalisation in US infants but also a major risk factor for asthma development. Growing evidence supports clinical heterogeneity within bronchiolitis. Our objectives were to identify metatranscriptome profiles of infant bronchiolitis, and to examine their relationship with the host transcriptome and subsequent asthma development.

METHODS

As part of a multicentre prospective cohort study of infants (age <1 year) hospitalised for bronchiolitis, we integrated virus and nasopharyngeal metatranscriptome (species-level taxonomy and function) data measured at hospitalisation. We applied network-based clustering approaches to identify metatranscriptome profiles. We then examined their association with the host transcriptome at hospitalisation and risk for developing asthma.

RESULTS

We identified five metatranscriptome profiles of bronchiolitis (n=244): profile A: virusRSVmicrobiomecommensals; profile B: virusRSV/RV-Amicrobiome H.influenzae ; profile C: virusRSVmicrobiome S.pneumoniae ; profile D: virusRSVmicrobiome M.nonliquefaciens ; and profile E: virusRSV/RV-Cmicrobiome M.catarrhalis . Compared with profile A, profile B infants were characterised by a high proportion of eczema, Haemophilus influenzae abundance and enriched virulence related to antibiotic resistance. These profile B infants also had upregulated T-helper 17 and downregulated type I interferon pathways (false discovery rate (FDR) <0.005), and significantly higher risk for developing asthma (17.9% versus 38.9%; adjusted OR 2.81, 95% CI 1.11-7.26). Likewise, profile C infants were characterised by a high proportion of parental asthma, Streptococcus pneumoniae dominance, and enriched glycerolipid and glycerophospholipid metabolism of the microbiome. These profile C infants had an upregulated RAGE signalling pathway (FDR <0.005) and higher risk of asthma (17.9% versus 35.6%; adjusted OR 2.49, 95% CI 1.10-5.87).

CONCLUSIONS

Metatranscriptome and clustering analysis identified biologically distinct metatranscriptome profiles that have differential risks of asthma.

Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts

BACKGROUND

Bronchiolitis is the leading cause of infants hospitalization in the U.S. and Europe. Additionally, bronchiolitis is a major risk factor for the development of childhood asthma. Growing evidence suggests heterogeneity within bronchiolitis. We sought to identify distinct, reproducible bronchiolitis subgroups (profiles) and to develop a decision rule accurately predicting the profile at the highest risk for developing asthma.

METHODS

In three multicenter prospective cohorts of infants (age < 12 months) hospitalized for bronchiolitis in the U.S. and Finland (combined n = 3081) in 2007-2014, we identified clinically distinct bronchiolitis profiles by using latent class analysis. We examined the association of the profiles with the risk for developing asthma by age 6-7 years. By performing recursive partitioning analyses, we developed a decision rule predicting the profile at highest risk for asthma, and measured its predictive performance in two separate cohorts.

FINDINGS

We identified four bronchiolitis profiles (profiles A-D). Profile A (n = 388; 13%) was characterized by a history of breathing problems/eczema and non-respiratory syncytial virus (non-RSV) infection. In contrast, profile B (n = 1064; 34%) resembled classic RSV-induced bronchiolitis. Profile C (n = 993; 32%) was comprised of the most severely ill group. Profile D (n = 636; 21%) was the least-ill group. Profile A infants had a significantly higher risk for asthma, compared to profile B infants (38% vs. 23%, adjusted odds ratio [adjOR] 2⋅57, 95%confidence interval [CI] 1⋅63-4⋅06). The derived 4-predictor (RSV infection, history of breathing problems, history of eczema, and parental history of asthma) decision rule strongly predicted profile A-e.g., area under the curve [AUC] of 0⋅98 (95%CI 0⋅97-0⋅99), sensitivity of 1⋅00 (95%CI 0⋅96-1⋅00), and specificity of 0⋅90 (95%CI 0⋅89-0⋅93) in a validation cohort.

INTERPRETATION

In three prospective cohorts of infants with bronchiolitis, we identified clinically distinct profiles and their longitudinal relationship with asthma risk. We also derived and validated an accurate prediction rule to determine the profile at highest risk. The current results should advance research into the development of profile-specific preventive strategies for asthma.

Metabolic Reprogramming of Nasal Airway Epithelial Cells Following Infant Respiratory Syncytial Virus Infection

Respiratory syncytial virus (RSV) is a seasonal mucosal pathogen that infects the ciliated respiratory epithelium and results in the most severe morbidity in the first six months of life. RSV is a common cause of acute respiratory infection during infancy and is an important early-life risk factor strongly associated with asthma development. While this association has been repeatedly demonstrated, limited progress has been made on the mechanistic understanding in humans of the contribution of infant RSV infection to airway epithelial dysfunction. An active infection of epithelial cells with RSV in vitro results in heightened central metabolism and overall hypermetabolic state; however, little is known about whether natural infection with RSV in vivo results in lasting metabolic reprogramming of the airway epithelium in infancy. To address this gap, we performed functional metabolomics, 13C glucose metabolic flux analysis, and RNA-seq gene expression analysis of nasal airway epithelial cells (NAECs) sampled from infants between 2-3 years of age, with RSV infection or not during the first year of life. We found that RSV infection in infancy was associated with lasting epithelial metabolic reprogramming, which was characterized by (1) significant increase in glucose uptake and differential utilization of glucose by epithelium; (2) altered preferences for metabolism of several carbon and energy sources; and (3) significant sexual dimorphism in metabolic parameters, with RSV-induced metabolic changes most pronounced in male epithelium. In summary, our study supports the proposed phenomenon of metabolic reprogramming of epithelial cells associated with RSV infection in infancy and opens exciting new venues for pursuing mechanisms of RSV-induced epithelial barrier dysfunction in early life.

Big Data, Data Science, and Causal Inference: A Primer for Clinicians

Clinicians handle a growing amount of clinical, biometric, and biomarker data. In this “big data” era, there is an emerging faith that the answer to all clinical and scientific questions reside in “big data” and that data will transform medicine into precision medicine. However, data by themselves are useless. It is the algorithms encoding causal reasoning and domain (e.g., clinical and biological) knowledge that prove transformative. The recent introduction of (health) data science presents an opportunity to re-think this data-centric view. For example, while precision medicine seeks to provide the right prevention and treatment strategy to the right patients at the right time, its realization cannot be achieved by algorithms that operate exclusively in data-driven prediction modes, as do most machine learning algorithms. Better understanding of data science and its tasks is vital to interpret findings and translate new discoveries into clinical practice. In this review, we first discuss the principles and major tasks of data science by organizing it into three defining tasks: (1) association and prediction, (2) intervention, and (3) counterfactual causal inference. Second, we review commonly-used data science tools with examples in the medical literature. Lastly, we outline current challenges and future directions in the fields of medicine, elaborating on how data science can enhance clinical effectiveness and inform medical practice. As machine learning algorithms become ubiquitous tools to handle quantitatively “big data,” their integration with causal reasoning and domain knowledge is instrumental to qualitatively transform medicine, which will, in turn, improve health outcomes of patients.

Integrated associations of nasopharyngeal and serum metabolome with bronchiolitis severity and asthma: A multicenter prospective cohort study

BACKGROUND

While infant bronchiolitis contributes to substantial acute (eg, severity) and chronic (eg, asthma development) morbidities, its pathobiology remains uncertain. We examined the integrated relationships of local (nasopharyngeal) and systemic (serum) responses with bronchiolitis morbidities.

METHODS

In a multicenter prospective cohort study of infants hospitalized for bronchiolitis, we applied a network analysis approach to identify distinct networks (modules)-clusters of densely interconnected metabolites-of the nasopharyngeal and serum metabolome. We examined their individual and integrated relationships with acute severity (defined by positive pressure ventilation [PPV] use) and asthma development by age 5 years.

RESULTS

In 140 infants, we identified 285 nasopharyngeal and 639 serum metabolites. Network analysis revealed 7 nasopharyngeal and 8 serum modules. At the individual module level, nasopharyngeal-amino acid, tricarboxylic acid (TCA) cycle, and carnitine modules were associated with higher risk of PPV use (r > .20; P < .001), while serum-carnitine, amino acid, and glycerophosphorylcholine (GPC)/glycerophosphorylethanolamine (GPE) modules were associated with lower risk (all r < -.20; P < .05). The integrated analysis for PPV use revealed consistent findings-for example, nasopharyngeal-TCA (adjOR: 2.87, 95% CI: 1.68-12.2) and serum-GPC/GPE (adjOR: 0.54, 95% CI: 0.38-0.80) modules-and an additional module-serum-glucose-alanine cycle module (adjOR: 0.69, 95% CI: 0.56-0.86). With asthma risk, there were no individual associations, but there were integrated associations (eg, nasopharyngeal-carnitine module; adjOR: 1.48, 95% CI: 1.11-1.99).

CONCLUSION

In infants with bronchiolitis, we found integrated relationships of local and systemic metabolome networks with acute and chronic morbidity. Our findings advance research into the complex interplay among respiratory viruses, local and systemic response, and disease pathobiology in infants with bronchiolitis.

Which Current and Novel Diagnostic Avenues for Bacterial Respiratory Diseases?

Bacterial acute pneumonia is responsible for an extremely large burden of death worldwide and diagnosis is paramount in the management of patients. While multidrug-resistant bacteria is one of the biggest health threats in the coming decades, clinicians urgently need access to novel diagnostic technologies. In this review, we will first present the already existing and largely used techniques that allow identifying pathogen-associated pneumonia. Then, we will discuss the latest and most promising technological advances that are based on connected technologies (artificial intelligence-based and Omics-based) or rapid tests, to improve the management of lung infections caused by pathogenic bacteria. We also aim to highlight the mutual benefits of fundamental and clinical studies for a better understanding of lung infections and their more efficient diagnostic management.

Respiratory viruses are associated with serum metabolome among infants hospitalized for bronchiolitis: A multicenter study

BACKGROUND

Bronchiolitis is the leading cause of infant hospitalizations in the United States. Growing evidence supports the heterogeneity of bronchiolitis. However, little is known about the interrelationships between major respiratory viruses (and their species), host systemic metabolism, and disease pathobiology.

METHODS

In an ongoing multicenter prospective cohort study, we profiled the serum metabolome in 113 infants (63 RSV-only, 21 RV-A, and 29 RV-C) hospitalized with bronchiolitis. We identified serum metabolites that are most discriminatory in the RSV-RV-A and RSV-RV-C comparisons using sparse partial least squares discriminant analysis. We then investigated the association between discriminatory metabolites with acute and chronic outcomes.

RESULTS

In 113 infants with bronchiolitis, we measured 639 metabolites. Serum metabolomic profiles differed in both comparisons (Ppermutation  < 0.05). In the RSV-RV-A comparison, we identified 30 discriminatory metabolites, predominantly in lipid metabolism pathways (eg, sphingolipids and carnitines). In multivariable models, these metabolites were significantly associated with the risk of clinical outcomes (eg, tricosanoyl sphingomyelin, OR for recurrent wheezing at age of 3 years = 1.50; 95% CI: 1.05-2.15). In the RSV-RV-C comparison, the discriminatory metabolites were also primarily involved in lipid metabolism (eg, glycerophosphocholines [GPCs], 12,13-diHome). These metabolites were also significantly associated with the risk of outcomes (eg, 1-stearoyl-2-linoleoyl-GPC, OR for positive pressure ventilation use during hospitalization = 0.47; 95% CI: 0.28-0.78).

CONCLUSION

Respiratory viruses and their species had distinct serum metabolomic signatures that are associated with differential risks of acute and chronic morbidities of bronchiolitis. Our findings advance research into the complex interrelations between viruses, host systemic response, and bronchiolitis pathobiology.

Detection of Respiratory Syncytial Virus or Rhinovirus Weeks After Hospitalization for Bronchiolitis and the Risk of Recurrent Wheezing

BACKGROUND

In severe bronchiolitis, it is unclear if delayed clearance or sequential infection of respiratory syncytial virus (RSV) or rhinovirus (RV) is associated with recurrent wheezing.

METHODS

In a 17-center severe bronchiolitis cohort, we tested nasopharyngeal aspirates (NPA) upon hospitalization and 3 weeks later (clearance swab) for respiratory viruses using PCR. The same RSV subtype or RV genotype in NPA and clearance swab defined delayed clearance (DC); a new RSV subtype or RV genotype at clearance defined sequential infection (SI). Recurrent wheezing by age 3 years was defined per national asthma guidelines.

RESULTS

Among 673 infants, RSV DC and RV DC were not associated with recurrent wheezing, and RSV SI was rare. The 128 infants with RV SI (19%) had nonsignificantly higher risk of recurrent wheezing (hazard ratio [HR], 1.31; 95% confidence interval [CI], .95-1.80; P = .10) versus infants without RV SI. Among infants with RV at hospitalization, those with RV SI had a higher risk of recurrent wheezing compared to children without RV SI (HR, 2.49; 95% CI, 1.22-5.06; P = .01).

CONCLUSIONS

Among infants with severe bronchiolitis, those with RV at hospitalization followed by a new RV infection had the highest risk of recurrent wheezing.

Metabolic changes during respiratory syncytial virus infection of epithelial cells

Viral infections induce substantial metabolic changes in infected cells to optimize viral production while cells develop countermeasures to restrict that infection. Human respiratory syncytial virus (HRSV) is an infectious pathogen that causes severe lower respiratory tract infections (LRTI) in infants, the elderly, and immunocompromised adults for which no effective treatment or vaccine is currently available. In this study, variations in metabolite levels at different time points post-HRSV infection of epithelial cells were studied by untargeted metabolomics using liquid chromatography/mass spectrometry analysis of methanol cell extracts. Numerous metabolites were significantly upregulated after 18 hours post-infection, including nucleotides, amino acids, amino and nucleotide sugars, and metabolites of the central carbon pathway. In contrast, most lipid classes were downregulated. Additionally, increased levels of oxidized glutathione and polyamines were associated with oxidative stress in infected cells. These results show how HRSV infection influences cell metabolism to produce the energy and building blocks necessary for virus reproduction, suggesting potential therapeutic interventions against this virus.