Host Transcription Profile in Nasal Epithelium and Whole Blood of Hospitalized Children Under 2 Years of Age With Respiratory Syncytial Virus Infection

Development of innate and adaptive immunity to RSV in young children

Infection of the respiratory tract with respiratory syncytial virus (RSV) is common and occurs repeatedly throughout life with most severe disease occurring at the extremes of age: in young infants and the elderly. Effective anti-viral therapeutics are not available and therefore prevention has been the primary strategy for reducing the disease burden. Our current understanding of respiratory mucosal cell biology and the immune response within the respiratory tract is inadequate to prevent infection caused by a pathogen like RSV that does not disseminate outside of this environment. Gaps in our understanding of the activation of innate and adaptive immunity in response to RSV and the role of age upon infection also limit improvements in the design of therapeutics and vaccines for young infants. However, advancements in structural biology have improved our ability to characterize antibodies against viral proteins and in 2023 the first vaccines for those over 60 years and pregnant women became available, potentially reducing the burden of disease. This review will examine our current understanding of the critical facets of anti-RSV immune responses in infants and young children as well as highlight areas where more research is needed.

A machine learning classifier using 33 host immune response mRNAs accurately distinguishes viral and non-viral acute respiratory illnesses in nasal swab samples

BACKGROUND

Viral acute respiratory illnesses (viral ARIs) contribute significantly to human morbidity and mortality worldwide, but their successful treatment requires timely diagnosis of viral etiology, which is complicated by overlap in clinical presentation with the non-viral ARIs. Multiple pandemics in the twenty-first century to date have further highlighted the unmet need for effective monitoring of clinically relevant emerging viruses. Recent studies have identified conserved host response to viral infections in the blood.

METHODS

We hypothesize that a similarly conserved host response in nasal samples can be utilized for diagnosis and to rule out viral infection in symptomatic patients when current diagnostic tests are negative. Using a multi-cohort analysis framework, we analyzed 1555 nasal samples across 10 independent cohorts dividing them into training and validation.

RESULTS

Using six of the datasets for training, we identified 119 genes that are consistently differentially expressed in viral ARI patients (N = 236) compared to healthy controls (N = 146) and further down-selected 33 genes for classifier development. The resulting locked logistic regression-based classifier using the 33-mRNAs had AUC of 0.94 and 0.89 in the six training and four validation datasets, respectively. Furthermore, we found that although trained on healthy controls only, in the four validation datasets, the 33-mRNA classifier distinguished viral ARI from both healthy or non-viral ARI samples with > 80% specificity and sensitivity, irrespective of age, viral type, and viral load. Single-cell RNA-sequencing data showed that the 33-mRNA signature is dominated by macrophages and neutrophils in nasal samples.

CONCLUSION

This proof-of-concept signature has potential to be adapted as a clinical point-of-care test ('RespVerity') to improve the diagnosis of viral ARIs.

Severe bronchiolitis profiling as the first step towards prevention of asthma

Bronchiolitis is the most common respiratory infection leading to hospitalization and constitutes a significant healthcare burden. The two main viral agents causing bronchiolitis, respiratory syncytial virus (RSV) and rhinovirus (RV), have distinct cytopathic, immune response, and clinical characteristics. Different approaches have been suggested for subtyping bronchiolitis based on viral etiology, atopic status, transcriptome profiles in blood, airway metabolome, lipidomic data, and airway microbiota. The highest risk of asthma at school age has been in a subgroup of bronchiolitis characterized by older age, high prevalence of RV infection, previous breathing problems, and/or eczema. Regarding solely viral etiology, RV-bronchiolitis in infancy has been linked to a nearly three times higher risk of developing asthma than RSV-bronchiolitis. Although treatment with betamimetics and systemic corticosteroids has been found ineffective in bronchiolitis overall, it can be beneficial for infants with severe RV bronchiolitis. Thus, there is a need to develop a more individualized therapeutic approach for bronchiolitis and follow-up strategies for infants at higher risk of asthma in the future perspective.

Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection

INTRODUCTION

Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early.

OBJECTIVE

The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells.

METHODS

Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis.

RESULTS

Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1).

CONCLUSIONS

The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.

Cilia-related gene signature in the nasal mucosa correlates with disease severity and outcomes in critical respiratory syncytial virus bronchiolitis

Background

Respiratory syncytial virus (RSV) can cause life-threatening respiratory failure in infants. We sought to characterize the local host response to RSV infection in the nasal mucosa of infants with critical bronchiolitis and to identify early admission gene signatures associated with clinical outcomes.

Methods

Nasal scrape biopsies were obtained from 33 infants admitted to the pediatric intensive care unit (PICU) with critical RSV bronchiolitis requiring non-invasive respiratory support (NIS) or invasive mechanical ventilation (IMV), and RNA sequencing (RNA-seq) was performed. Gene expression in participants who required shortened NIS (</= 3 days), prolonged NIS (> 3 days), and IMV was compared.

Findings

Increased expression of ciliated cell genes and estimated ciliated cell abundance, but not immune cell abundance, positively correlated with duration of hospitalization in infants with critical bronchiolitis. A ciliated cell signature characterized infants who required NIS for > 3 days while a basal cell signature was present in infants who required NIS for </= 3 days, despite both groups requiring an equal degree of respiratory support at the time of sampling. Infants who required invasive mechanical ventilation had increased expression of genes involved in neutrophil activation and cell death.

Interpretation

Increased expression of cilia-related genes in clinically indistinguishable infants with critical RSV may differentiate between infants who will require prolonged hospitalization and infants who will recover quickly. Validation of these findings in a larger cohort is needed to determine whether a cilia-related gene signature can predict duration of illness in infants with critical bronchiolitis. The ability to identify which infants with critical RSV bronchiolitis may require prolonged hospitalization using non-invasive nasal samples would provide invaluable prognostic information to parents and medical providers.

Age-related Differences in the Nasal Mucosal Immune Response to SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 180 million people since the onset of the pandemic. Despite similar viral load and infectivity rates between children and adults, children rarely develop severe illness. Differences in the host response to the virus at the primary infection site are among the mechanisms proposed to account for this disparity. Our objective was to investigate the host response to SARS-CoV-2 in the nasal mucosa in children and adults and compare it with the host response to respiratory syncytial virus (RSV) and influenza virus. We analyzed clinical outcomes and gene expression in the nasal mucosa of 36 children with SARS-CoV-2, 24 children with RSV, 9 children with influenza virus, 16 adults with SARS-CoV-2, and 7 healthy pediatric and 13 healthy adult controls. In both children and adults, infection with SARS-CoV-2 led to an IFN response in the nasal mucosa. The magnitude of the IFN response correlated with the abundance of viral reads, not the severity of illness, and was comparable between children and adults infected with SARS-CoV-2 and children with severe RSV infection. Expression of ACE2 and TMPRSS2 did not correlate with age or presence of viral infection. SARS-CoV-2–infected adults had increased expression of genes involved in neutrophil activation and T-cell receptor signaling pathways compared with SARS-CoV-2–infected children, despite similar severity of illness and viral reads. Age-related differences in the immune response to SARS-CoV-2 may place adults at increased risk of developing severe illness.

Host transcriptional signatures as predictive markers of infection in children

PURPOSE OF REVIEW

Analyses of the host transcriptional response to infection has proved to be an alternative diagnostic strategy to standard direct pathogen detection. This review summarizes the value of applying blood and mucosal transcriptome analyses for the diagnosis and management of children with viral and bacterial infections.

RECENT FINDINGS

Over the years, studies have validated the concept that RNA transcriptional profiles derived from children with infectious diseases carry a pathogen-specific biosignature that can be qualitatively and quantitively measured. These biosignatures can be translated into a biologically meaningful context to improve patient diagnosis, as seen in children with tuberculosis, rhinovirus infections, febrile infants and children with pneumonia; understand disease pathogenesis (i.e. congenital CMV) and objectively classify patients according to clinical severity (i.e. respiratory syncytial virus).

SUMMARY

The global assessment of host RNA transcriptional immune responses has improved our understanding of the host-pathogen interactions in the clinical setting. It has shown the potential to be used in clinical situations wherein our current diagnostic tools are inadequate, guiding the diagnosis and classification of children with infectious diseases.

A blood RNA transcriptome signature for COVID-19

Background

COVID-19 is a respiratory viral infection with unique features including a more chronic course and systemic disease manifestations including multiple organ involvement; and there are differences in disease severity between ethnic groups. The immunological basis for disease has not been fully characterised. Analysis of whole-blood RNA expression may provide valuable information on disease pathogenesis.

Methods

We studied 45 patients with confirmed COVID-19 infection within 10 days from onset of illness and a control group of 19 asymptomatic healthy volunteers with no known exposure to COVID-19 in the previous 14 days. Relevant demographic and clinical information was collected and a blood sample was drawn from all participants for whole-blood RNA sequencing. We evaluated differentially-expressed genes in COVID-19 patients (log2 fold change ≥ 1 versus healthy controls; false-discovery rate < 0.05) and associated protein pathways and compared these to published whole-blood signatures for respiratory syncytial virus (RSV) and influenza. We developed a disease score reflecting the overall magnitude of expression of internally-validated genes and assessed the relationship between the disease score and clinical disease parameters.

Results

We found 135 differentially-expressed genes in the patients with COVID-19 (median age 35 years; 82% male; 36% Chinese, 53% South Asian ethnicity). Of the 117 induced genes, 14 were found in datasets from RSV and 40 from influenza; 95 genes were unique to COVID-19. Protein pathways were mostly generic responses to viral infections, including apoptosis by P53-associated pathway, but also included some unique pathways such as viral carcinogenesis. There were no major qualitative differences in pathways between ethnic groups. The composite gene-expression score was correlated with the time from onset of symptoms and nasal swab qPCR CT values (both p < 0.01) but was not related to participant age, gender, ethnicity or the presence or absence of chest X-ray abnormalities (all p > 0.05).

Conclusions

The whole-blood transcriptome of COVID-19 has overall similarity with other respiratory infections but there are some unique pathways that merit further exploration to determine clinical relevance. The approach to a disease score may be of value, but needs further validation in a population with a greater range of disease severity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01006-w.

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

BACKGROUND

Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. The causes and correlates of severe illness in the majority of infants are poorly defined.

METHODS

We recruited a cohort of RSV-infected infants and simultaneously assayed the molecular status of their airways and the presence of airway microbiota. We used rigorous statistical approaches to identify gene expression patterns associated with disease severity and microbiota composition, separately and in combination.

RESULTS

We measured comprehensive airway gene expression patterns in 106 infants with primary RSV infection. We identified an airway gene expression signature of severe illness dominated by excessive chemokine expression. We also found an association between Haemophilus influenzae, disease severity, and airway lymphocyte accumulation. Exploring the time of onset of clinical symptoms revealed acute activation of interferon signaling following RSV infection in infants with mild or moderate illness, which was absent in subjects with severe illness.

CONCLUSIONS

Our data reveal that airway gene expression patterns distinguish mild/moderate from severe illness. Furthermore, our data identify biomarkers that may be therapeutic targets or useful for measuring efficacy of intervention responses.

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants

BACKGROUND

A substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness.

METHOD

We 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).

RESULTS

NGSS1 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%.

CONCLUSION

Airway 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.

Immune response to SARS-CoV-2 in the nasal mucosa in children and adults

Rationale:

Despite similar viral load and infectivity rates between children and adults infected with SARS-CoV-2, children rarely develop severe illness. Differences in the host response to the virus at the primary infection site are among the proposed mechanisms.

Objectives:

To investigate the host response to SARS-CoV-2, respiratory syncytial virus (RSV), and influenza virus (IV) in the nasal mucosa in children and adults.

Methods:

Clinical outcomes and gene expression in the nasal mucosa were analyzed in 36 children hospitalized with SARS-CoV-2 infection, 24 children with RSV infection, 9 children with IV infection, 16 adults with mild to moderate SARS-CoV-2 infection, and 7 healthy pediatric and 13 healthy adult controls.

Results:

In both children and adults, infection with SARS-CoV-2 leads to an interferon response in the nasal mucosa. The magnitude of the interferon response correlated with the abundance of viral reads and was comparable between symptomatic children and adults infected with SARS-CoV-2 and symptomatic children infected with RSV and IV. Cell type deconvolution identified an increased abundance of immune cells in the samples from children and adults with a viral infection. Expression of ACE2 and TMPRSS2 - key entry factors for SARS-CoV-2 - did not correlate with age or presence or absence of viral infection.

Conclusions:

Our findings support the hypothesis that differences in the immune response to SARS-CoV-2 determine disease severity, independent of viral load and interferon response at the primary infection primary site.

Gene signature of children with severe respiratory syncytial virus infection

BACKGROUND

The limited treatment options for children with severe respiratory syncytial virus (RSV) infection highlights the need for a comprehensive understanding of the host cellular response during infection. We aimed to identify host genes that are associated with severe RSV disease and to identify drugs that can be repurposed for the treatment of severe RSV infection.

METHODS

We examined clinical data and blood samples from 37 hospitalized children (29 mild and 8 severe) with RSV infection. We tested RNA from blood samples using next-generation sequencing to profile global mRNA expression and identify cellular processes.

RESULTS

Retractions, decreased breath sounds, and tachypnea were associated with disease severity. We observed upregulation of genes related to neutrophil, inflammatory response, blood coagulation, and downregulation of genes related to T cell response in children with severe RSV. Using network-based approach, 43 drugs were identified that are predicted to interact with the gene products of these differentially expressed genes.

CONCLUSIONS

These results suggest that the changes in the expression pattern in the innate and adaptive immune responses may be associated with RSV clinical severity. Compounds that target these cellular processes can be repositioned as candidate drugs in the treatment of severe RSV.

IMPACT

Neutrophil, inflammation, and blood coagulation genes are upregulated in children with severe RSV infection. Expression of T cell response genes are suppressed in cases of severe RSV. Genes identified in this study can contribute in understanding the pathogenesis of RSV disease severity. Drugs that target cellular processes associated with severe RSV can be repositioned as potential therapeutic options.

Definition of erythroid cell-positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection

Biomarkers to assess the risk of developing severe respiratory syncytial virus (RSV) infection are needed. We conducted a meta-analysis of 490 unique profiles from six public RSV blood transcriptome datasets. A repertoire of 382 well-characterized transcriptional modules was used to define dominant host responses to RSV infection. The consolidated RSV cohort was stratified according to four traits: "interferon response" (IFN), "neutrophil-driven inflammation" (Infl), "cell cycle" (CC), and "erythrocytes" (Ery). We identified eight prevalent blood transcriptome phenotypes, of which three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. This finding confirms on a larger scale data from one of our earlier reports describing an association between an erythrocyte signature and RSV disease severity. Further contextual interpretation made it possible to associate this signature with immunosuppressive states (late stage cancer, pharmacological immunosuppression), and with a population of fetal glycophorin A+ erythroid precursors. Furthermore, we posit that this erythrocyte cell signature may be linked to a population of immunosuppressive erythroid cells previously described in the literature, and that overabundance of this cell population in RSV patients may underlie progression to severe disease. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that we developed and employed here should also permit to delineate prevalent blood transcriptome phenotypes in other settings.

Transcriptome of airway neutrophils reveals an interferon response in life-threatening respiratory syncytial virus infection

BACKGROUND

Neutrophils are the most abundant cell type infiltrating the airways during severe respiratory syncytial virus (RSV) infection. Their exact role in disease pathophysiology remains enigmatic. Therefore, we determined genome-wide RNA expression profiles of local and systemic neutrophils in RSV bronchiolitis to provide further insight into local neutrophil biology.

METHODS

We performed a single-center analysis, in 16 infants, admitted to the pediatric intensive care unit with severe RSV bronchiolitis. Neutrophils were isolated from blood and tracheobronchial aspirates (sputum). After low input RNA sequencing, differential expression of genes was determined followed by gene set analysis.

RESULTS

Paired transcriptomic analysis of airway versus blood neutrophils showed an inflammatory phenotype, characterized by NF-kB signaling and upregulated expression of IL-6 and interferon pathways. We observed distinct expression of neutrophil activation genes (TNFSF13B, FCER1G).

DISCUSSION

Our data indicate that airway neutrophils regulate their function at the transcriptional level in response to viral infection. It also suggests that local interferon drives the neutrophil response of severe RSV bronchiolitis.

The preventive strategy for pandemics in the elderly is to collect in advance samples & data to counteract chronic inflammation (inflammaging)

Fighting the current COVID-19 pandemic, we must not forget to prepare for the next. Since elderly and frail people are at high risk, we wish to predict their vulnerability, and intervene if possible. For example, it would take little effort to take additional swabs or dried blood spots. Such minimally-invasive sampling, exemplified here during screening for potential COVID-19 infection, can yield the data to discover biomarkers to better handle this and the next respiratory disease pandemic. Longitudinal outcome data can then be combined with other epidemics and old-age health data, to discover the best biomarkers to predict (i) coping with infection & inflammation and thus hospitalization or intensive care, (ii) long-term health challenges, e.g. deterioration of lung function after intensive care, and (iii) treatment & vaccination response. Further, there are universal triggers of old-age morbidity & mortality, and the elimination of senescent cells improved health in pilot studies in idiopathic lung fibrosis & osteoarthritis patients alike. Biomarker studies are needed to test the hypothesis that resilience of the elderly during a pandemic can be improved by countering chronic inflammation and/or removing senescent cells. Our review suggests that more samples should be taken and saved systematically, following minimum standards, and data be made available, to maximize healthspan & minimize frailty, leading to savings in health care, gains in quality of life, and preparing us better for the next pandemic, all at the same time.

Human Respiratory Syncytial Virus-Induced Immune Signature of Infection Revealed by Transcriptome Analysis of Clinical Pediatric Nasopharyngeal Swab Samples

Human respiratory syncytial virus (HRSV) constitutes one the main causes of respiratory infection in neonates and infants worldwide. Transcriptome analysis of clinical samples using high-throughput technologies remains an important tool to better understand virus-host complex interactions in the real-life setting but also to identify new diagnosis/prognosis markers or therapeutics targets. A major challenge when exploiting clinical samples such as nasal swabs, washes, or bronchoalveolar lavages is the poor quantity and integrity of nucleic acids. In this study, we applied a tailored transcriptomics workflow to exploit nasal wash samples from children who tested positive for HRSV. Our analysis revealed a characteristic immune signature as a direct reflection of HRSV pathogenesis and highlighted putative biomarkers of interest such as IP-10, TMEM190, MCEMP1, and TIMM23.

A blood RNA transcript signature for TB exposure in household contacts

Background

Current tools for diagnosing latent TB infection (LTBI) detect immunological memory of past exposure but are unable to determine whether exposure is recent. We sought to identify a whole-blood transcriptome signature of recent TB exposure.

Methods

We studied household contacts of TB patients; healthy volunteers without recent history of TB exposure; and patients with active TB. We performed whole-blood RNA sequencing (in all), an interferon gamma release assay (IGRA; in contacts and healthy controls) and PET/MRI lung scans (in contacts only). We evaluated differentially-expressed genes in household contacts (log2 fold change ≥1 versus healthy controls; false-discovery rate < 0.05); compared these to differentially-expressed genes seen in the active TB group; and assessed the association of a composite gene expression score to independent exposure/treatment/immunological variables.

Results

There were 186 differentially-expressed genes in household contacts (n = 26, age 22–66, 46% male) compared with healthy controls (n = 5, age 29–38, 100% male). Of these genes, 141 (76%) were also differentially expressed in active TB (n = 14, age 27–69, 71% male). The exposure signature included genes from inflammatory response, type I interferon signalling and neutrophil-mediated immunity pathways; and genes such as BATF2 and SCARF1 known to be associated with incipient TB. The composite gene-expression score was higher in IGRA-positive contacts (P = 0.04) but not related to time from exposure, isoniazid prophylaxis, or abnormalities on PET/MRI (all P > 0.19).

Conclusions

Transcriptomics can detect TB exposure and, with further development, may be an approach of value for epidemiological research and targeting public health interventions.

Impact of Respiratory Syncytial Virus Infection on Host Functions: Implications for Antiviral Strategies

Respiratory syncytial virus (RSV) is one of the leading causes of viral respiratory tract infection in infants, the elderly, and the immunocompromised worldwide, causing more deaths each year than influenza. Years of research into RSV since its discovery over 60 yr ago have elucidated detailed mechanisms of the host-pathogen interface. RSV infection elicits widespread transcriptomic and proteomic changes, which both mediate the host innate and adaptive immune responses to infection, and reflect RSV's ability to circumvent the host stress responses, including stress granule formation, endoplasmic reticulum stress, oxidative stress, and programmed cell death. The combination of these events can severely impact on human lungs, resulting in airway remodeling and pathophysiology. The RSV membrane envelope glycoproteins (fusion F and attachment G), matrix (M) and nonstructural (NS) 1 and 2 proteins play key roles in modulating host cell functions to promote the infectious cycle. This review presents a comprehensive overview of how RSV impacts the host response to infection and how detailed knowledge of the mechanisms thereof can inform the development of new approaches to develop RSV vaccines and therapeutics.

Host Gene Expression in Nose and Blood for the Diagnosis of Viral Respiratory Infection

BACKGROUND

Recently there has been a growing interest in the potential for host transcriptomic analysis to augment the diagnosis of infectious diseases.

METHODS

We compared nasal and blood samples for evaluation of the host transcriptomic response in children with acute respiratory syncytial virus (RSV) infection, symptomatic non-RSV respiratory virus infection, asymptomatic rhinovirus infection, and virus-negative asymptomatic controls. We used nested leave-one-pair-out cross-validation and supervised principal components analysis to define small sets of genes whose expression patterns accurately classified subjects. We validated gene classification scores using an external data set.

RESULTS

Despite lower quality of nasal RNA, the number of genes detected by microarray in each sample type was equivalent. Nasal gene expression signal derived mainly from epithelial cells but also included a variable leukocyte contribution. The number of genes with increased expression in virus-infected children was comparable in nasal and blood samples, while nasal samples also had decreased expression of many genes associated with ciliary function and assembly. Nasal gene expression signatures were as good or better for discriminating between symptomatic, asymptomatic, and uninfected children.

CONCLSUSIONS

Our results support the use of nasal samples to augment pathogen-based tests to diagnose viral respiratory infection.

Host-Based Diagnostics for Acute Respiratory Infections

PURPOSE

The inappropriate use of antimicrobials, especially in acute respiratory infections (ARIs), is largely driven by difficulty distinguishing bacterial, viral, and noninfectious etiologies of illness. A new frontier in infectious disease diagnostics looks to the host response for disease classification. This article examines how host response-based diagnostics for ARIs are being used in clinical practice, as well as new developments in the research pipeline.

METHODS

A limited search was conducted of the relevant literature, with emphasis placed on literature published in the last 5 years (2014-2019).

FINDINGS

Advances are being made in all areas of host response-based diagnostics for ARIs. Specifically, there has been significant progress made in single protein biomarkers, as well as in various "omics" fields (including proteomics, metabolomics, and transcriptomics) and wearable technologies. There are many potential applications of a host response-based approach; a few key examples include the ability to discriminate bacterial and viral disease, presymptomatic diagnosis of infection, and pathogen-specific host response diagnostics, including modeling disease progression.

IMPLICATIONS

As biomarker measurement technologies continue to improve, host response-based diagnostics will increasingly be translated to clinically available platforms that can generate a holistic characterization of an individual's health. This knowledge, in the hands of both patient and provider, can improve care for the individual patient and help fight rising rates of antibiotic resistance.

Cytokines in the Respiratory Airway as Biomarkers of Severity and Prognosis for Respiratory Syncytial Virus Infection: An Update

The human respiratory syncytial virus (hRSV) is one of the most important causes of upper and lower respiratory tract infections in children and the main cause of bronchiolitis worldwide. Disease manifestations caused by hRSV may vary from mild to severe, occasionally requiring admission and hospitalization in intensive care units. Despite the high morbidity rates associated to bronchiolitis, treatment options against hRSV are limited and there are no current vaccination strategies to prevent infection. Importantly, the early identification of high-risk patients can help improve disease management and prevent complications associated with hRSV infection. Recently, the characterization of pro- and anti-inflammatory cytokine patterns produced during hRSV-related inflammatory processes has allowed the identification of potential prognosis biomarkers. A suitable biomarker should allow predicting the severity of the infection in a simple and opportune manner and should ideally be obtained from non-invasive samples. Among the cytokines associated with hRSV disease severity, IL-8, interferon-alpha (IFN-alpha), and IL-6, as well as the Th2-type cytokines thymic stromal lymphopoietin (TSLP), IL-3, and IL-33 have been highlighted as molecules with prognostic value in hRSV infections. In this review, we discuss current studies that describe molecules produced by patients during hRSV infection and their potential as biomarkers to anticipate the severity of the disease caused by this virus.

Infant Immune Response to Respiratory Viral Infections

Of all respiratory viruses that affect infants, respiratory syncytial virus (RSV) and rhinovirus (RV) represent the leading pathogens causing acute disease (bronchiolitis) and are associated with the development of recurrent wheezing and asthma. The immune system in infants is still developing, and several factors contribute to their increased susceptibility to viral infections. These factors include differences in pathogen detection, weaker interferon responses, lack of immunologic memory toward the invading pathogen, and T-cell responses that are balanced to promote tolerance and restrain inflammation. These aspects are reviewed here with a focus on RSV and RV infections.

Respiratory syncytial virus

Respiratory syncytial virus (RSV) is the most common cause of infant hospitalization and causes a high burden of disease in the elderly, too. This enveloped negative-stranded RNA virus has been recently reclassified in the Pneumoviridae family. Infections of the respiratory cells happens when the two major surface glycoproteins, G and F, take contact with the cell receptor CX3CR1 and mediate entry by fusion, respectively. Viral mRNA transcription, genomic RNA synthesis and nucleocapsid formation occur in large cytoplasmic inclusion bodies to avoid recognition by the host innate immune response. Most progeny virions remain associated to the infected cell surface; fusion of infected with adjacent cells results in the formation of large multinucleated syncytia that eventually undergo apoptosis. Desquamated epithelial cells form the plugs that with mucus and fibrin may cause lower airway obstructions. Pathogenetic mechanism of severe RSV disease likely involve both the extent of viral replication and the host immune response. Regarding the latter, single nucleotide polymorphism analysis and genome-wide association studies showed that genetic susceptibility to severe RSV infection is likely a complex trait, in which many different host genetic variants contribute. Recent studies pointed to the fact that bronchiolitis severity depends more on the specific infecting RSV genotypes than on the amount of viral loads. A population-based surveillance system to better define RSV burden of disease would be of valuable help for implementing future vaccination programs.

KLRD1-expressing natural killer cells predict influenza susceptibility

BACKGROUND

Influenza infects tens of millions of people every year in the USA. Other than notable risk groups, such as children and the elderly, it is difficult to predict what subpopulations are at higher risk of infection. Viral challenge studies, where healthy human volunteers are inoculated with live influenza virus, provide a unique opportunity to study infection susceptibility. Biomarkers predicting influenza susceptibility would be useful for identifying risk groups and designing vaccines.

METHODS

We applied cell mixture deconvolution to estimate immune cell proportions from whole blood transcriptome data in four independent influenza challenge studies. We compared immune cell proportions in the blood between symptomatic shedders and asymptomatic nonshedders across three discovery cohorts prior to influenza inoculation and tested results in a held-out validation challenge cohort.

RESULTS

Natural killer (NK) cells were significantly lower in symptomatic shedders at baseline in both discovery and validation cohorts. Hematopoietic stem and progenitor cells (HSPCs) were higher in symptomatic shedders at baseline in discovery cohorts. Although the HSPCs were higher in symptomatic shedders in the validation cohort, the increase was statistically nonsignificant. We observed that a gene associated with NK cells, KLRD1, which encodes CD94, was expressed at lower levels in symptomatic shedders at baseline in discovery and validation cohorts. KLRD1 expression in the blood at baseline negatively correlated with influenza infection symptom severity. KLRD1 expression 8 h post-infection in the nasal epithelium from a rhinovirus challenge study also negatively correlated with symptom severity.

CONCLUSIONS

We identified KLRD1-expressing NK cells as a potential biomarker for influenza susceptibility. Expression of KLRD1 was inversely correlated with symptom severity. Our results support a model where an early response by KLRD1-expressing NK cells may control influenza infection.