Gene expression signatures diagnose influenza and other symptomatic respiratory viral infections in humans

Investigating Pneumonia Etiology Among Refugees and the Lebanese population (PEARL): A study protocol

Background: Community-acquired pneumonia (CAP), a leading cause of mortality, mainly affects children in developing countries. The harsh circumstances experienced by refugees include various factors associated with respiratory pathogen transmission, and clinical progression of CAP. Consequently, the etiology of CAP in humanitarian crisis situations may differ to that of settled populations, which would impact appropriate case management. Therefore, the Pneumonia Etiology Among Refugees and the Lebanese population (PEARL) study was initiated with the objective of identifying the causal pathogenic microorganisms in the respiratory tract of children and adults from both the refugee and host country population presenting with signs of CAP during a humanitarian crisis.

Methods: PEARL, a prospective, multicentric, case-control study, will be conducted at four primary healthcare facilities in Tripoli and the Bekaa valley over 15 months (including two high-transmission seasons/winters). Sociodemographic and medical data, and biological samples will be collected from at least 600 CAP cases and 600 controls. Nasopharyngeal swabs, sputum, urine and blood samples will be analyzed at five clinical pathology laboratories in Lebanon to identify the bacterial and viral etiological agents of CAP. Transcriptomic profiling of host leukocytes will be performed.

Conclusions: PEARL is an original observational study that will provide important new information on the etiology of pneumonia among refugees, which may improve case management, help design antimicrobial stewardship interventions, and reduce morbidity and mortality due to CAP in a humanitarian crisis.

Personalizing the Management of Pneumonia

Pneumonia is a highly prevalent disease with considerable morbidity and mortality. However, diagnosis and therapy still rely on antiquated methods, leading to the vast overuse of antimicrobials, which carries risks for both society and the individual. Furthermore, outcomes in severe pneumonia remain poor. Genomic techniques have the potential to transform the management of pneumonia through deep characterization of pathogens as well as the host response to infection. This characterization will enable the delivery of selective antimicrobials and immunomodulatory therapy that will help to offset the disorder associated with overexuberant immune responses.

Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network

Infection and disease progression is the outcome of protein interactions between pathogen and host. Pathogen, the role player of Infection, is becoming a severe threat to life as because of its adaptability toward drugs and evolutionary dynamism in nature. Identifying protein targets by analyzing protein interactions between host and pathogen is the key point. Proteins with higher degree and possessing some topologically significant graph theoretical measures are found to be drug targets. On the other hand, exceptional nodes may be involved in infection mechanism because of some pathway process and biologically unknown factors. In this article, we attempt to investigate characteristics of host-pathogen protein interactions by presenting a comprehensive review of computational approaches applied on different infectious diseases. As an illustration, we have analyzed a case study on infectious disease malaria, with its causative agent Plasmodium falciparum acting as 'Bait' and host, Homo sapiens/human acting as 'Prey'. In this pathogen-host interaction network based on some interconnectivity and centrality properties, proteins are viewed as central, peripheral, hub and non-hub nodes and their significance on infection process. Besides, it is observed that because of sparseness of the pathogen and host interaction network, there may be some topologically unimportant but biologically significant proteins, which can also act as Bait/Prey. So, functional similarity or gene ontology mapping can help us in this case to identify these proteins.

Clinical metagenomics

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.

Antibodies to a Conserved Influenza Head Interface Epitope Protect by an IgG Subtype-Dependent Mechanism

Vaccines to generate durable humoral immunity against antigenically evolving pathogens such as the influenza virus must elicit antibodies that recognize conserved epitopes. Analysis of single memory B cells from immunized human donors has led us to characterize a previously unrecognized epitope of influenza hemagglutinin (HA) that is immunogenic in humans and conserved among influenza subtypes. Structures show that an unrelated antibody from a participant in an experimental infection protocol recognized the epitope as well. IgGs specific for this antigenic determinant do not block viral infection in vitro, but passive administration to mice affords robust IgG subtype-dependent protection against influenza infection. The epitope, occluded in the pre-fusion form of HA, is at the contact surface between HA head domains; reversible molecular "breathing" of the HA trimer can expose the interface to antibody and B cells. Antigens that present this broadly immunogenic HA epitope may be good candidates for inclusion in "universal" flu vaccines.

Differential Effects of Influenza Virus NA, HA Head, and HA Stalk Antibodies on Peripheral Blood Leukocyte Gene Expression during Human Infection

In this study, we examined the relationships between anti-influenza virus serum antibody titers, clinical disease, and peripheral blood leukocyte (PBL) global gene expression during presymptomatic, acute, and convalescent illness in 83 participants infected with 2009 pandemic H1N1 virus in a human influenza challenge model. Using traditional statistical and logistic regression modeling approaches, profiles of differentially expressed genes that correlated with active viral shedding, predicted length of viral shedding, and predicted illness severity were identified. These analyses further demonstrated that challenge participants fell into three peripheral blood leukocyte gene expression phenotypes that significantly correlated with different clinical outcomes and prechallenge serum titers of antibodies specific for the viral neuraminidase, hemagglutinin head, and hemagglutinin stalk. Higher prechallenge serum antibody titers were inversely correlated with leukocyte responsiveness in participants with active disease and could mask expression of peripheral blood markers of clinical disease in some participants, including viral shedding and symptom severity. Consequently, preexisting anti-influenza antibodies may modulate PBL gene expression, and this must be taken into consideration in the development and interpretation of peripheral blood diagnostic and prognostic assays of influenza infection.IMPORTANCE Influenza A viruses are significant human pathogens that caused 83,000 deaths in the United States during 2017 to 2018, and there is need to understand the molecular correlates of illness and to identify prognostic markers of viral infection, symptom severity, and disease course. Preexisting antibodies against viral neuraminidase (NA) and hemagglutinin (HA) proteins play a critical role in lessening disease severity. We performed global gene expression profiling of peripheral blood leukocytes collected during acute and convalescent phases from a large cohort of people infected with A/H1N1pdm virus. Using statistical and machine-learning approaches, populations of genes were identified early in infection that correlated with active viral shedding, predicted length of shedding, or disease severity. Finally, these gene expression responses were differentially affected by increased levels of preexisting influenza antibodies, which could mask detection of these markers of contagiousness and disease severity in people with active clinical disease.

A curated transcriptome dataset collection to investigate the blood transcriptional response to viral respiratory tract infection and vaccination

The human immune defense mechanisms and factors associated with good versus poor health outcomes following viral respiratory tract infections (VRTI), as well as correlates of protection following vaccination against respiratory viruses, remain incompletely understood. To shed further light into these mechanisms, a number of systems-scale studies have been conducted to measure transcriptional changes in blood leukocytes of either naturally or experimentally infected individuals, or in individual’s post-vaccination. Here we are making available a public repository, for research investigators for interpretation, a collection of transcriptome datasets obtained from human whole blood and peripheral blood mononuclear cells (PBMC) to investigate the transcriptional responses following viral respiratory tract infection or vaccination against respiratory viruses. In total, Thirty one31 datasets, associated to viral respiratory tract infections and their related vaccination studies, were identified and retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application designed for interactive query and visualization of integrated large-scale data. Quality control checks, using relevant biological markers, were performed. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation. Via this interface, users can generate web links to customized graphical views, which may be subsequently inserted into manuscripts to report novel findings. The GXB tool enables browsing of a single gene across projects, providing new perspectives on the role of a given molecule across biological systems in the diagnostic and prognostic following VRTI but also in identifying new correlates of protection. This dataset collection is available at: http://vri1.gxbsidra.org/dm3/geneBrowser/list.

Distinct transcriptional modules in the peripheral blood mononuclear cells response to human respiratory syncytial virus or to human rhinovirus in hospitalized infants with bronchiolitis

Human respiratory syncytial virus (HRSV) is the main cause of bronchiolitis during the first year of life, when infections by other viruses, such as rhinovirus, also occur and are clinically indistinguishable from those caused by HRSV. In hospitalized infants with bronchiolitis, the analysis of gene expression profiles from peripheral blood mononuclear cells (PBMC) may be useful for the rapid identification of etiological factors, as well as for developing diagnostic tests, and elucidating pathogenic mechanisms triggered by different viral agents. In this study we conducted a comparative global gene expression analysis of PBMC obtained from two groups of infants with acute viral bronchiolitis who were infected by HRSV (HRSV group) or by HRV (HRV group). We employed a weighted gene co-expression network analysis (WGCNA) which allows the identification of transcriptional modules and their correlations with HRSV or HRV groups. This approach permitted the identification of distinct transcription modules for the HRSV and HRV groups. According to these data, the immune response to HRSV infection—comparatively to HRV infection—was more associated to the activation of the interferon gamma signaling pathways and less related to neutrophil activation mechanisms. Moreover, we also identified host-response molecular markers that could be used for etiopathogenic diagnosis. These results may contribute to the development of new tests for respiratory virus identification. The finding that distinct transcriptional profiles are associated to specific host responses to HRSV or to HRV may also contribute to the elucidation of the pathogenic mechanisms triggered by different respiratory viruses, paving the way for new therapeutic strategies.

The role of systems biology approaches in determining molecular signatures for the development of more effective vaccines

INTRODUCTION

Emerging infectious diseases are a major threat to public health, and while vaccines have proven to be one of the most effective preventive measures for infectious diseases, we still do not have safe and effective vaccines against many human pathogens, and emerging diseases continually pose new threats. The purpose of this review is to discuss how the creation of vaccines for these new threats has been hindered by limitations in the current approach to vaccine development. Recent advances in high-throughput technologies have enabled scientists to apply systems biology approaches to collect and integrate increasingly large datasets that capture comprehensive biological changes induced by vaccines, and then decipher the complex immune response to those vaccines.

AREAS COVERED

This review covers advances in these technologies and recent publications that describe systems biology approaches to understanding vaccine immune responses and to understanding the rational design of new vaccine candidates.

EXPERT OPINION

Systems biology approaches to vaccine development provide novel information regarding both the immune response and the underlying mechanisms and can inform vaccine development.

Multiplexed enrichment and genomic profiling of peripheral blood cells reveal subset-specific immune signatures

Specialized immune cell subsets are involved in autoimmune disease, cancer immunity, and infectious disease through a diverse range of functions mediated by overlapping pathways and signals. However, subset-specific responses may not be detectable in analyses of whole blood samples, and no efficient approach for profiling cell subsets at high throughput from small samples is available. We present a low-input microfluidic system for sorting immune cells into subsets and profiling their gene expression. We validate the system's technical performance against standard subset isolation and library construction protocols and demonstrate the importance of subset-specific profiling through in vitro stimulation experiments. We show the ability of this integrated platform to identify subset-specific disease signatures by profiling four immune cell subsets in blood from patients with systemic lupus erythematosus (SLE) and matched control subjects. The platform has the potential to make multiplexed subset-specific analysis routine in many research laboratories and clinical settings.

A miRNA Host Response Signature Accurately Discriminates Acute Respiratory Infection Etiologies

Background: Acute respiratory infections (ARIs) are the leading indication for antibacterial prescriptions despite a viral etiology in the majority of cases. The lack of available diagnostics to discriminate viral and bacterial etiologies contributes to this discordance. Recent efforts have focused on the host response as a source for novel diagnostic targets although none have explored the ability of host-derived microRNAs (miRNA) to discriminate between these etiologies. Methods: In this study, we compared host-derived miRNAs and mRNAs from human H3N2 influenza challenge subjects to those from patients with Streptococcus pneumoniae pneumonia. Sparse logistic regression models were used to generate miRNA signatures diagnostic of ARI etiologies. Generalized linear modeling of mRNAs to identify differentially expressed (DE) genes allowed analysis of potential miRNA:mRNA relationships. High likelihood miRNA:mRNA interactions were examined using binding target prediction and negative correlation to further explore potential changes in pathway regulation in response to infection. Results: The resultant miRNA signatures were highly accurate in discriminating ARI etiologies. Mean accuracy was 100% [88.8-100; 95% Confidence Interval (CI)] in discriminating the healthy state from S. pneumoniae pneumonia and 91.3% (72.0-98.9; 95% CI) in discriminating S. pneumoniae pneumonia from influenza infection. Subsequent differential mRNA gene expression analysis revealed alterations in regulatory networks consistent with known biology including immune cell activation and host response to viral infection. Negative correlation network analysis of miRNA:mRNA interactions revealed connections to pathways with known immunobiology such as interferon regulation and MAP kinase signaling. Conclusion: We have developed novel human host-response miRNA signatures for bacterial and viral ARI etiologies. miRNA host response signatures reveal accurate discrimination between S. pneumoniae pneumonia and influenza etiologies for ARI and integrated analyses of the host-pathogen interface are consistent with expected biology. These results highlight the differential miRNA host response to bacterial and viral etiologies of ARI, offering new opportunities to distinguish these entities.

Approach to Neonates and Young Infants with Fever without a Source Who Are at Risk for Severe Bacterial Infection

INTRODUCTION

Among neonates and infants <3 months of age with fever without a source (FWS), 5% to 15% of cases are patients with fever caused by a serious bacterial infection (SBI). To favour the differentiation between low- and high-risk infants, several algorithms based on analytical and clinical parameters have been developed. The aim of this review is to describe the management of young infants with FWS and to discuss the impact of recent knowledge regarding FWS management on clinical practice.

MATERIALS AND METHODS

PubMed was used to search for all of the studies published over the last 35 years using the keywords: "fever without source" or "fever of unknown origin" or "meningitis" or "sepsis" or "urinary tract infection" and "neonate" or "newborn" or "infant <90 days of life" or "infant <3 months".

RESULTS AND DISCUSSION

The selection of neonates and young infants who are <3 months old with FWS who are at risk for SBI remains a problem without a definitive solution. The old Rochester criteria remain effective for identifying young infants between 29 and 60 days old who do not have severe bacterial infections (SBIs). However, the addition of laboratory tests such as C-reactive protein (CRP) and procalcitonin (PCT) can significantly improve the identification of children with SBI. The approach in evaluating neonates is significantly more complicated, as their risk of SBIs, including bacteremia and meningitis, remains relevant and none of the suggested approaches can reduce the risk of dramatic mistakes. In both groups, the best antibiotic must be carefully selected considering the clinical findings, the laboratory data, the changing epidemiology, and increasing antibiotic resistance of the most common infectious bacteria.

Animal Models for Influenza A Virus Infection Incorporating the Involvement of Innate Host Defenses: Enhanced Translational Value of the Porcine Model

Influenza is a viral respiratory disease having a major impact on public health. Influenza A virus (IAV) usually causes mild transitory disease in humans. However, in specific groups of individuals such as severely obese, the elderly, and individuals with underlying inflammatory conditions, IAV can cause severe illness or death. In this review, relevant small and large animal models for human IAV infection, including the pig, ferret, and mouse, are discussed. The focus is on the pig as a large animal model for human IAV infection as well as on the associated innate immune response. Pigs are natural hosts for the same IAV subtypes as humans, they develop clinical disease mirroring human symptoms, they have similar lung anatomy, and their respiratory physiology and immune responses to IAV infection are remarkably similar to what is observed in humans. The pig model shows high face and target validity for human IAV infection, making it suitable for modeling many aspects of influenza, including increased risk of severe disease and impaired vaccine response due to underlying pathologies such as low-grade inflammation. Comparative analysis of proteins involved in viral pattern recognition, interferon responses, and regulation of interferon-stimulated genes reveals a significantly higher degree of similarity between pig, ferret, and human compared with mice. It is concluded that the pig is a promising animal model displaying substantial human translational value with the ability to provide essential insights into IAV infection, pathogenesis, and immunity.

Evaluating the Value of Defensins for Diagnosing Secondary Bacterial Infections in Influenza-Infected Patients

Acute respiratory infections by influenza viruses are commonly causes of severe pneumonia, which can further deteriorate if secondary bacterial infections occur. Although the viral and bacterial agents are quite diverse, defensins, a set of antimicrobial peptides expressed by the host, may provide promising biomarkers that would greatly improve the diagnosis and treatment. We examined the correlations between the gene expression levels of defensins and the viral and bacterial loads in the blood on a longitudinal, precision-medical study of a severe pneumonia patient infected by influenza A H7N9 virus. We found that DEFA5 is positively correlated to the blood load of influenza A H7N9 virus (r = 0.735, p < 0.05, Spearman correlation). DEFB116 and DEFB127 are positively and DEFB108B and DEFB114 are negatively correlated to the bacterial load. Then the diagnostic potential of defensins to discriminate bacterial and viral infections was evaluated on an independent dataset with 61 bacterial pneumonia patients and 39 viral pneumonia patients infected by influenza A viruses and reached 93% accuracy. Expression levels of defensins in the blood may be of important diagnostic values in clinic to indicate viral and bacterial infections.

Transcriptomics in lung tissue upon respiratory syncytial virus infection reveals aging as important modulator of immune activation and matrix maintenance

Aging poses an increased risk of severe infection by respiratory syncytial virus (RSV). The many different biological pathways comprising the response to infection in lungs that are influenced by aging are complex and remain to be defined more thoroughly. Towards finding new directions in research on aging, we aimed to define biological pathways in the acute response to RSV that are affected in the lungs by aging. We therefore profiled the full transcriptome of lung tissue of mice prior to and during RSV infection both at young and old age. In the absence of RSV, we found aging to downregulate genes that are involved in constitution of the extracellular matrix. Moreover, uninfected old mice showed elevated expression of pathways that resemble injury, metabolic aberrations, and disorders mediated by functions of the immune system that were induced at young age only by an exogenous trigger like RSV. Furthermore, infection by RSV mounted stronger activation of anti-viral type-I interferon pathways at old age. Despite such exaggerated anti-viral responses, old mice showed reduced control of virus. Altogether, our findings emphasize important roles in aging-related susceptibility to respiratory disease for extracellular matrix dysfunctions and dysregulated immune activation in lungs.

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses.

Viral Sepsis in Children

Sepsis in children is typically presumed to be bacterial in origin until proven otherwise, but frequently bacterial cultures ultimately return negative. Although viruses may be important causative agents of culture-negative sepsis worldwide, the incidence, disease burden and mortality of viral-induced sepsis is poorly elucidated. Consideration of viral sepsis is critical as its recognition carries implications on appropriate use of antibacterial agents, infection control measures, and, in some cases, specific, time-sensitive antiviral therapies. This review outlines our current understanding of viral sepsis in children and addresses its epidemiology and pathophysiology, including pathogen-host interaction during active infection. Clinical manifestation, diagnostic testing, and management options unique to viral infections will be outlined.

The manufacturing of human viral challenge agents for use in clinical studies to accelerate the drug development process

OBJECTIVE

This manuscript aims to provide an overview of the unique considerations and best practice principles associated with the manufacture of human viral challenge agents.

RESULTS

Considerations are discussed on the entire process from strain and viral source selection through manufacturing, safety and efficacy testing. The human viral challenge (HVC) model is an important tool to help accelerate the drug development process but producing viruses suitable for use in the model presents a unique set of challenges. There are many case by case decisions and risk assessments to consider and no clear international standard to produce viruses for this purpose. The authors present challenge virus manufacturing considerations from the current literature, regulatory guidance and their own direct experience in producing challenge viruses. The use of these viral stocks in clinical studies, as published in peer-reviewed journals, is also briefly described.

Aminoacyl-tRNA synthetases, therapeutic targets for infectious diseases

Despite remarkable advances in medical science, infection-associated diseases remain among the leading causes of death worldwide. There is a great deal of interest and concern at the rate at which new pathogens are emerging and causing significant human health problems. Expanding our understanding of how cells regulate signaling networks to defend against invaders and retain cell homeostasis will reveal promising strategies against infection. It has taken scientists decades to appreciate that eukaryotic aminoacyl-tRNA synthetases (ARSs) play a role as global cell signaling mediators to regulate cell homeostasis, beyond their intrinsic function as protein synthesis enzymes. Recent discoveries revealed that ubiquitously expressed standby cytoplasmic ARSs sense and respond to danger signals and regulate immunity against infections, indicating their potential as therapeutic targets for infectious diseases. In this review, we discuss ARS-mediated anti-infectious signaling and the emerging role of ARSs in antimicrobial immunity. In contrast to their ability to defend against infection, host ARSs are inevitably co-opted by viruses for survival and propagation. We therefore provide a brief overview of the communication between viruses and the ARS system. Finally, we discuss encouraging new approaches to develop ARSs as therapeutics for infectious diseases.

Nasal microbiota clusters associate with inflammatory response, viral load, and symptom severity in experimental rhinovirus challenge

The role of nasal and fecal microbiota in viral respiratory infections has not been established. We collected nasal swabs and washes, and fecal samples in a clinical study assessing the effect of probiotic Bifidobacterium animalis subsp. lactis Bl-04 on experimental rhinovirus infection. The nasal and fecal microbiota were characterized by 16S rRNA gene sequencing. The resulting data were compared with nasal inflammatory marker concentrations, viral load, and clinical symptoms. By using unsupervised clustering, the nasal microbiota divided into six clusters. The clusters predominant of Staphylococcus, Corynebacterium/Alloiococcus, Moraxella, and Pseudomonadaceae/Mixed had characteristic inflammatory marker and viral load profiles in nasal washes. The nasal microbiota clusters of subjects before the infection associated with the severity of clinical cold symptoms during rhinovirus infection. Rhinovirus infection and probiotic intervention did not significantly alter the composition of nasal or fecal microbiota. Our results suggest that nasal microbiota may influence the virus load, host innate immune response, and clinical symptoms during rhinovirus infection, however, further studies are needed.

Whole-Genome mRNA Gene Expression Differs Between Patients With and Without Delirium

OBJECTIVE

To identify differences in gene expression between patients with in-hospital delirium from a known etiology (urinary tract infection [UTI]) and patients with delirium from an unknown etiology, as well as from nondelirious patients.

METHODS

Thirty patients with delirium (8 with UTI) and 21 nondelirious patients (11 with UTI) were included in this prospective case-control study. Transcriptomic profiles from messenger RNA sequencing of peripheral blood were analyzed for gene expression and disease-specific pathway enrichment patterns, correcting for systemic inflammatory response syndrome. Genes and pathways with significant differential activity based on Fisher exact test ( P < .05, |Z score| >2) are reported.

RESULTS

Patients with delirium with UTI, compared to patients with delirium without UTI, exhibited significant activation of interferon signaling, upstream cytokines, and transcription regulators, as well as significant inhibition of actin cytoskeleton, integrin, paxillin, glioma invasiveness signaling, and upstream growth factors. All patients with delirium, compared to nondelirious patients, had significant complement system activation. Among patients with delirium without UTI, compared to nondelirious patients without UTI, there was significant activation of elF4 and p7056 K signaling.

CONCLUSIONS

Differences exist in gene expression between delirious patients due to UTI presence, as well as due to the presence of delirium alone. Transcriptional profiling may help develop etiology-specific biomarkers for patients with delirium.

Of mice and men: the host response to influenza virus infection

Influenza virus (IV) infections represent a very serious public health problem. At present, no established biomarkers exist to support diagnosis for respiratory viral infections and more importantly for severe IV disease. Studies in animal models are extremely important to understand the biological, genetic, and environmental factors that contribute to severe IV disease and to validate biomarker candidates from human studies. However, mouse human cross-species comparisons are often compromised by the fact that animal studies concentrate on the infected lungs, whereas in humans almost all studies use peripheral blood from patients. In addition, human studies do not consider genetic background as variable although human populations are genetically very diverse. Therefore, in this study, we performed a cross-species gene expression study of the peripheral blood from human patients and from the highly genetically diverse Collaborative Cross (CC) mouse population after IV infection. Our results demonstrate that changes of gene expression in individual genes are highly similar in mice and humans. The top-regulated genes in humans were also differentially regulated in mice. We conclude that the mouse is a highly valuable in vivo model system to validate and to discover gene candidates which can be used as biomarkers in humans. Furthermore, mouse studies allow confirmation of findings in humans in a well-controlled experimental system adding enormous value to the understanding of expression and function of human candidate genes.

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.

Diagnostics for Lassa Fever: Detecting Host Antibody Responses

There are two types of viral diagnostics: (1) those that detect components of the pathogen (like viral RNA or proteins) and (2) those that detect host molecules that rise or fall as a consequence of pathogen infection (like anti-viral antibodies or virus-induced inflammatory cytokines). Quantitative PCR to detect Lassa RNA, and clinical chemistry to detect high liver enzymes (AST/ALT) are commonly used to diagnose Lassa fever. Here, we discuss the various types of diagnostics for Lassa fever and the urgent need for early diagnosis. We also describe a protocol for using the attenuated Lassa vaccine candidate, ML29 , as an antigen for detecting Lassa-specific antibodies. Since antibodies are developed late in the progression of Lassa fever disease, this is not an early diagnostic, but is more useful in surveillance of the population to determine the sero-prevalence of antibodies to Lassa virus (LASV ), and to define treatment options for people in close contact with a Lassa-infected person.

Progression of whole-blood transcriptional signatures from interferon-induced to neutrophil-associated patterns in severe influenza

Transcriptional profiles and host-response biomarkers are used increasingly to investigate the severity, subtype and pathogenesis of disease. We now describe whole-blood mRNA signatures and concentrations of local and systemic immunological mediators in 131 adults hospitalized with influenza, from whom extensive clinical and investigational data were obtained by MOSAIC investigators. Signatures reflective of interferon-related antiviral pathways were common up to day 4 of symptoms in patients who did not require mechanical ventilator support; in those who needed mechanical ventilation, an inflammatory, activated-neutrophil and cell-stress or death ('bacterial') pattern was seen, even early in disease. Identifiable bacterial co-infection was not necessary for this 'bacterial' signature but was able to enhance its development while attenuating the early 'viral' signature. Our findings emphasize the importance of timing and severity in the interpretation of host responses to acute viral infection and identify specific patterns of immune-system activation that might enable the development of novel diagnostic and therapeutic tools for severe influenza.

Investigating Pneumonia Etiology Among Refugees and the Lebanese population (PEARL): A study protocol

Background: Community-acquired pneumonia (CAP), a leading cause of mortality, mainly affects children in developing countries. The harsh circumstances experienced by refugees include various factors associated with respiratory pathogen transmission, and clinical progression of CAP. Consequently, the etiology of CAP in humanitarian crisis situations may differ to that of settled populations, which would impact appropriate case management. Therefore, the Pneumonia Etiology Among Refugees and the Lebanese population (PEARL) study was initiated with the objective of identifying the causal pathogenic microorganisms in the respiratory tract of children and adults from both the refugee and host country population presenting with signs of CAP during a humanitarian crisis. Methods: PEARL, a prospective, multicentric, case-control study, will be conducted at four primary healthcare facilities in Tripoli and the Bekaa valley over 15 months (including two high-transmission seasons/winters). Sociodemographic and medical data, and biological samples will be collected from at least 600 CAP cases and 600 controls. Nasopharyngeal swabs, sputum, urine and blood samples will be analyzed at five clinical pathology laboratories in Lebanon to identify the bacterial and viral etiological agents of CAP. Transcriptomic profiling of host leukocytes will be performed. Conclusions: PEARL is an original observational study that will provide important new information on the etiology of pneumonia among refugees, which may improve case management, help design antimicrobial stewardship interventions, and reduce morbidity and mortality due to CAP in a humanitarian crisis.

Patterns in Bacterial- and Viral-Induced Immunosuppression and Secondary Infections in the ICU

Immunosuppression renders the host increased susceptible for secondary infections. It is becoming increasingly clear that not only bacterial sepsis, but also respiratory viruses with both severe and mild disease courses such as influenza, respiratory syncytial virus, and the human rhinovirus may induce immunosuppression. In this review, the current knowledge on (mechanisms of) bacterial- and virus-induced immunosuppression and the accompanying susceptibility toward various secondary infections is described. In addition, the frequently encountered secondary pathogens and their preferred localizations are presented. Finally, future perspectives in the context of the development of diagnostic markers and possibilities for personalized therapy to improve the diagnosis and treatment of immunocompromised patients are discussed.

Rhinovirus respiratory tract infection in hospitalized adult patients is associated with TH2 response irrespective of asthma

OBJECTIVES

We assessed the immunological response of hospitalized adult patients with rhinovirus infection, including critically-ill patients.

METHODS

The differential white blood cell (WBC) count and the levels of 29 plasma cytokines/chemokines were compared between 50 adult hospitalized patients with rhinovirus infection and 100 age-matched controls with influenza virus infection.

RESULTS

The demographics and comorbidities were similar between rhinovirus and influenza patients, but severe disease was more common for the rhinovirus cohort. Rhinovirus patients had significantly higher WBC counts than influenza patients, especially for eosinophil (P = 3.1 × 10^-8). The level of the T_H2 cytokine IL-5 was significantly higher among rhinovirus patients, while the levels of 9 other cytokines/chemokines were significantly lower among rhinovirus patients. The levels of CXCL-10 (IP-10), CCL-2 (MCP-1), IFN-α2, IFN-γ, IL-10, and IL-15 remained significantly lower among rhinovirus patients after correction for multiple comparisons. Notably, CXCL-10 had the highest area under the receiver operating characteristic curve (AUC) in differentiating rhinovirus from influenza patients (AUC, 0.918). In the patient subgroup without asthma, the difference in the WBC count and cytokine/chemokine levels between rhinovirus and influenza patients remained statistically significant.

CONCLUSIONS

Rhinovirus infection was characterized by a prominent T_H2 response, even in patients without asthma. CXCL-10 (IP-10) is a potential biomarker in differentiating rhinovirus from influenza infection.

Transcriptomic profiling reveals gene expression kinetics in patients with hypoxia and high altitude pulmonary edema

OBJECTIVE

High altitude pulmonary edema (HAPE) is a life threatening condition occurring in otherwise healthy individuals who rapidly ascend to high altitude. However, the molecular mechanisms of its pathophysiology are not well understood. The objective of this study is to evaluate differential gene expression in patients with HAPE during acute illness and subsequent recovery.

METHODS

Twenty-one individuals who ascended to an altitude of 3780 m were studied, including 12 patients who developed HAPE and 9 matched controls without HAPE. Whole-blood samples were collected during acute illness and subsequent recovery for analysis of the expression of hypoxia-related genes, and physiologic and laboratory parameters, including mean pulmonary arterial pressure (mPAP), heart rate, blood pressure, and arterial oxygen saturation (SpO₂), were also measured.

RESULTS

Compared with control subjects, numerous hypoxia-related genes were up-regulated in patients with acute HAPE. Gene network analyses suggested that HIF-1α played a central role in acute HAPE by affecting a variety of hypoxia-related genes, including BNIP3L, VEGFA, ANGPTL4 and EGLN1. Transcriptomic profiling revealed the expression of most HAPE-induced genes was restored to a normal level during the recovery phase except some key hypoxia response factors, such asBNIP3L, EGR1, MMP9 and VEGF, which remained persistently elevated.

CONCLUSIONS

Differential expression analysis of hypoxia-related genes revealed distinct molecular signatures of HAPE during acute and recovery phases. This study may help us to better understand HAPE pathogenesis and putative targets for further investigation and therapeutic intervention.

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

Background

Most insights into the cascade of immune events after acute respiratory syncytial virus (RSV) infection have been obtained from animal experiments or in vitro models.

Methods

In this study, we investigated host gene expression profiles in nasopharyngeal (NP) swabs and whole blood samples during natural RSV and rhinovirus (hRV) infection (acute versus early recovery phase) in 83 hospitalized patients <2 years old with lower respiratory tract infections.

Results

Respiratory syncytial virus infection induced strong and persistent innate immune responses including interferon signaling and pathways related to chemokine/cytokine signaling in both compartments. Interferon-α/β, NOTCH1 signaling pathways and potential biomarkers HIST1H4E, IL7R, ISG15 in NP samples, or BCL6, HIST2H2AC, CCNA1 in blood are leading pathways and hub genes that were associated with both RSV load and severity. The observed RSV-induced gene expression patterns did not differ significantly in NP swab and blood specimens. In contrast, hRV infection did not as strongly induce expression of innate immunity pathways, and significant differences were observed between NP swab and blood specimens.

Conclusions

We conclude that RSV induced strong and persistent innate immune responses and that RSV severity may be related to development of T follicular helper cells and antiviral inflammatory sequelae derived from high activation of BCL6.

Advancing Diagnostics to Address Antibacterial Resistance: The Diagnostics and Devices Committee of the Antibacterial Resistance Leadership Group

Diagnostics are a cornerstone of the practice of infectious diseases. However, various limitations frequently lead to unmet clinical needs. In most other domains, diagnostics focus on narrowly defined questions, provide readily interpretable answers, and use true gold standards for development. In contrast, infectious diseases diagnostics must contend with scores of potential pathogens, dozens of clinical syndromes, emerging pathogens, rapid evolution of existing pathogens and their associated resistance mechanisms, and the absence of gold standards in many situations. In spite of these challenges, the importance and value of diagnostics cannot be underestimated. Therefore, the Antibacterial Resistance Leadership Group has identified diagnostics as 1 of 4 major areas of emphasis. Herein, we provide an overview of that development, highlighting several examples where innovation in study design, content, and execution is advancing the field of infectious diseases diagnostics.

Transcriptomics in Human Challenge Models

Human challenge models, in which volunteers are experimentally infected with a pathogen of interest, provide the opportunity to directly identify both natural and vaccine-induced correlates of protection. In this review, we highlight how the application of transcriptomics to human challenge studies allows for the identification of novel correlates and gives insight into the immunological pathways required to develop functional immunity. In malaria challenge trials for example, innate immune pathways appear to play a previously underappreciated role in conferring protective immunity. Transcriptomic analyses of samples obtained in human challenge studies can also deepen our understanding of the immune responses preceding symptom onset, allowing characterization of innate immunity and early gene signatures, which may influence disease outcome. Influenza challenge studies demonstrate that these gene signatures have diagnostic potential in the context of pandemics, in which presymptomatic diagnosis of at-risk individuals could allow early initiation of antiviral treatment and help limit transmission. Furthermore, gene expression analysis facilitates the identification of host factors contributing to disease susceptibility, such as C4BPA expression in enterotoxigenic Escherichia coli infection. Overall, these studies highlight the exceptional value of transcriptional data generated in human challenge trials and illustrate the broad impact molecular data analysis may have on global health through rational vaccine design and biomarker discovery.

Robust classification of bacterial and viral infections via integrated host gene expression diagnostics

Improved diagnostics for acute infections could decrease morbidity and mortality by increasing early antibiotics for patients with bacterial infections and reducing unnecessary antibiotics for patients without bacterial infections. Several groups have used gene expression microarrays to build classifiers for acute infections, but these have been hampered by the size of the gene sets, use of overfit models, or lack of independent validation. We used multicohort analysis to derive a set of seven genes for robust discrimination of bacterial and viral infections, which we then validated in 30 independent cohorts. We next used our previously published 11-gene Sepsis MetaScore together with the new bacterial/viral classifier to build an integrated antibiotics decision model. In a pooled analysis of 1057 samples from 20 cohorts (excluding infants), the integrated antibiotics decision model had a sensitivity and specificity for bacterial infections of 94.0 and 59.8%, respectively (negative likelihood ratio, 0.10). Prospective clinical validation will be needed before these findings are implemented for patient care.

A novel host-protein assay outperforms routine parameters for distinguishing between bacterial and viral lower respiratory tract infections

Bacterial and viral lower respiratory tract infections (LRTIs) are often clinically indistinguishable, leading to antibiotic overuse. We compared the diagnostic accuracy of a new assay that combines 3 host-biomarkers (TRAIL, IP-10, CRP) with parameters in routine use to distinguish bacterial from viral LRTIs. Study cohort included 184 potentially eligible pediatric and adult patients. Reference standard diagnosis was based on adjudication by an expert panel following comprehensive clinical and laboratory investigation (including respiratory PCRs). Experts were blinded to assay results and assay performers were blinded to reference standard outcomes. Evaluated cohort included 88 bacterial and 36 viral patients (23 did not fulfill inclusion criteria; 37 had indeterminate reference standard outcome). Assay distinguished bacterial from viral LRTI patients with sensitivity of 0.93±0.06 and specificity of 0.91±0.09, outperforming routine parameters, including WBC, CRP and chest x-ray signs. These findings support the assay's potential to help clinicians avoid missing bacterial LRTIs or overusing antibiotics.

A genome-by-environment interaction classifier for precision medicine: personal transcriptome response to rhinovirus identifies children prone to asthma exacerbations

OBJECTIVE

To introduce a disease prognosis framework enabled by a robust classification scheme derived from patient-specific transcriptomic response to stimulation.

MATERIALS AND METHODS

Within an illustrative case study to predict asthma exacerbation, we designed a stimulation assay that reveals individualized transcriptomic response to human rhinovirus. Gene expression from peripheral blood mononuclear cells was quantified from 23 pediatric asthmatic patients and stimulated in vitro with human rhinovirus. Responses were obtained via the single-subject gene set testing methodology "N-of-1-pathways." The classifier was trained on a related independent training dataset (n = 19). Novel visualizations of personal transcriptomic responses are provided.

RESULTS

Of the 23 pediatric asthmatic patients, 12 experienced recurrent exacerbations. Our classifier, using individualized responses and trained on an independent dataset, obtained 74% accuracy (area under the receiver operating curve of 71%; 2-sided P = .039). Conventional classifiers using messenger RNA (mRNA) expression within the viral-exposed samples were unsuccessful (all patients predicted to have recurrent exacerbations; accuracy of 52%).

DISCUSSION

Prognosis based on single time point, static mRNA expression alone neglects the importance of dynamic genome-by-environment interplay in phenotypic presentation. Individualized transcriptomic response quantified at the pathway (gene sets) level reveals interpretable signals related to clinical outcomes.

CONCLUSION

The proposed framework provides an innovative approach to precision medicine. We show that quantifying personal pathway-level transcriptomic response to a disease-relevant environmental challenge predicts disease progression. This genome-by-environment interaction assay offers a noninvasive opportunity to translate omics data to clinical practice by improving the ability to predict disease exacerbation and increasing the potential to produce more effective treatment decisions.

Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is "mediation" by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "cis-mediators" of trans-eQTLs, including those "cis-hubs" involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types.

Genome-wide host RNA signatures of infectious diseases: discovery and clinical translation

The use of whole blood gene expression to derive diagnostic biomarkers capable of distinguishing between phenotypically similar diseases holds great promise but remains a challenge. Differential gene expression analysis is used to identify the key genes that undergo changes in expression relative to healthy individuals, as well as to patients with other diseases. These key genes can act as diagnostic, prognostic and predictive markers of disease. Gene expression ‘signatures’ in the blood hold the potential to be used for the diagnosis of infectious diseases, where current diagnostics are unreliable, ineffective or of limited potential. For diagnostic tests based on RNA signatures to be useful clinically, the first step is to identify the minimum set of gene transcripts that accurately identify the disease in question. The second requirement is rapid and cost‐effective detection of the gene expression levels. Signatures have been described for a number of infectious diseases, but ‘clinic‐ready’ technologies for RNA detection from clinical samples are limited, though existing methods such as RT‐PCR are likely to be superseded by a number of emerging technologies, which may form the basis of the translation of gene expression signatures into routine diagnostic tests for a range of disease states.

Neonatal immune response to rhinovirus A16 has diminished dendritic cell function and increased B cell activation

Background

Rhinovirus infections during infancy account for the majority of respiratory illness health care utilization and are an associated risk factor for subsequent development of allergic asthma. Neonatal type I interferon production is diminished compared to adults after stimulation with TLR agonists. However, broad profiling of immune cell responses to infectious rhinovirus has not been undertaken and we hypothesized that additional immune differences can be identified in neonates. In this study, we undertook a comparative analysis of neonatal and adult blood immune cell responses after in vitro incubation with infectious RV-A16 for 6 and 24 hours.

Methods

Intracellular proinflammatory and type I interferon cytokines along with expression of surface co-stimulatory and maturation markers were measured using multi-parameter flow cytometry.

Results

Both circulating myeloid dendritic cell (mDC) and plasmacytoid dendritic cell (pDC) frequency were lower in cord blood. Qualitative and quantitative plasmacytoid dendritic cell IFN-alpha + TNF- alpha responses to rhinovirus were significantly lower in cord pDCs. In cord blood samples, the majority of responsive pDCs were single-positive TNF-alpha producing cells, whereas in adult samples rhinovirus increased double-positive TNF-alpha+IFN-alpha+ pDCs. Rhinovirus upregulated activation and maturation markers on monocytes, mDCs, pDCs, and B cells, but CD40+CD86+ monocytes, mDCs, and pDCs cells were significantly higher in adult samples compared to cord samples. Surprisingly, rhinovirus increased CD40+CD86+ B cells to a significantly greater extent in cord samples compared to adults.

Conclusions

These findings define a number of cell-specific differences in neonatal responses to rhinovirus. This differential age-related immune response to RV may have implications for the immune correlates of protection to viral respiratory illness burden and determination of potential biomarkers for asthma risk.

Host Transcriptional Response to Ebola Virus Infection

Ebola virus disease (EVD) is a serious illness that causes severe disease in humans and non-human primates (NHPs) and has mortality rates up to 90%. EVD is caused by the Ebolavirus and currently there are no licensed therapeutics or vaccines to treat EVD. Due to its high mortality rates and potential as a bioterrorist weapon, a better understanding of the disease is of high priority. Multiparametric analysis techniques allow for a more complete understanding of a disease and the host response. Analysis of RNA species present in a sample can lead to a greater understanding of activation or suppression of different states of the immune response. Transcriptomic analyses such as microarrays and RNA-Sequencing (RNA-Seq) have been important tools to better understand the global gene expression response to EVD. In this review, we outline the current knowledge gained by transcriptomic analysis of EVD.

Transcriptomic Biomarkers to Discriminate Bacterial from Nonbacterial Infection in Adults Hospitalized with Respiratory Illness

Lower respiratory tract infection (LRTI) commonly causes hospitalization in adults. Because bacterial diagnostic tests are not accurate, antibiotics are frequently prescribed. Peripheral blood gene expression to identify subjects with bacterial infection is a promising strategy. We evaluated whole blood profiling using RNASeq to discriminate infectious agents in adults with microbiologically defined LRTI. Hospitalized adults with LRTI symptoms were recruited. Clinical data and blood was collected, and comprehensive microbiologic testing performed. Gene expression was measured using RNASeq and qPCR. Genes discriminatory for bacterial infection were identified using the Bonferroni-corrected Wilcoxon test. Constrained logistic models to predict bacterial infection were fit using screened LASSO. We enrolled 94 subjects who were microbiologically classified; 53 as “non-bacterial” and 41 as “bacterial”. RNAseq and qPCR confirmed significant differences in mean expression for 10 genes previously identified as discriminatory for bacterial LRTI. A novel dimension reduction strategy selected three pathways (lymphocyte, α-linoleic acid metabolism, IGF regulation) including eleven genes as optimal markers for discriminating bacterial infection (naïve AUC = 0.94; nested CV-AUC = 0.86). Using these genes, we constructed a classifier for bacterial LRTI with 90% (79% CV) sensitivity and 83% (76% CV) specificity. This novel, pathway-based gene set displays promise as a method to distinguish bacterial from nonbacterial LRTI.

Type I interferon as a biomarker in autoimmunity and viral infection: a leukocyte subset-specific analysis unveils hidden diagnostic options

Interferon alpha and its surrogates, including IP-10 and SIGLEC1, paralleled changes of disease activity in systemic lupus erythematosus (SLE). However, the whole blood interferon signature (WBIFNS)-the current standard for type I IFN assessment in SLE-does not correlate with SLE disease activity in individual patients over time. The underlying causes for this apparent contradiction have not been convincingly demonstrated. Using a multicenter dataset of gene expression data from leukocyte subsets in SLE, we identify distinctive subset-specific contributions to the WBIFNS. In a subsequent analysis, the effects of type I interferon on cellular blood composition in patients with SLE and hepatitis B were also studied over time. We found that type I interferon mediates significant alterations in whole blood composition, including a neutropenia and relative lymphocytosis. Given different effects of type 1 interferon on different leukocyte subsets, these shifts confound measurement of a type 1 interferon signature in whole blood. To minimize and overcome these limitations of the WBIFNS, we suggest to measure IFN-induced transcripts or proteins in a specific leukocyte subset to improve clinical impact of interferon biomarkers.

KEY MESSAGES

Myeloid cells contribute more to the WBIFNS in SLE than their lymphocytic counterpart. Very similar leukocyte subsets reveal distinctive IFN signatures. IFN alpha mixes up composition of blood and leads to a preferential neutropenia, yielding relative lymphocytosis.

Development of an objective gene expression panel as an alternative to self-reported symptom scores in human influenza challenge trials

Background

Influenza challenge trials are important for vaccine efficacy testing. Currently, disease severity is determined by self-reported scores to a list of symptoms which can be highly subjective. A more objective measure would allow for improved data analysis.

Methods

Twenty-one volunteers participated in an influenza challenge trial. We calculated the daily sum of scores (DSS) for a list of 16 influenza symptoms. Whole blood collected at baseline and 24, 48, 72 and 96 h post challenge was profiled on Illumina HT12v4 microarrays. Changes in gene expression most strongly correlated with DSS were selected to train a Random Forest model and tested on two independent test sets consisting of 41 individuals profiled on a different microarray platform and 33 volunteers assayed by qRT-PCR.

Results

1456 probes are significantly associated with DSS at 1% false discovery rate. We selected 19 genes with the largest fold change to train a random forest model. We observed good concordance between predicted and actual scores in the first test set (r = 0.57; RMSE = −16.1%) with the greatest agreement achieved on samples collected approximately 72 h post challenge. Therefore, we assayed samples collected at baseline and 72 h post challenge in the second test set by qRT-PCR and observed good concordance (r = 0.81; RMSE = −36.1%).

Conclusions

We developed a 19-gene qRT-PCR panel to predict DSS, validated on two independent datasets. A transcriptomics based panel could provide a more objective measure of symptom scoring in future influenza challenge studies.

Trial registration Samples were obtained from a clinical trial with the ClinicalTrials.gov Identifier: NCT02014870, first registered on December 5, 2013

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-017-1235-3) contains supplementary material, which is available to authorized users.

A Four-Biomarker Blood Signature Discriminates Systemic Inflammation Due to Viral Infection Versus Other Etiologies

The innate immune system of humans and other mammals responds to pathogen-associated molecular patterns (PAMPs) that are conserved across broad classes of infectious agents such as bacteria and viruses. We hypothesized that a blood-based transcriptional signature could be discovered indicating a host systemic response to viral infection. Previous work identified host transcriptional signatures to individual viruses including influenza, respiratory syncytial virus and dengue, but the generality of these signatures across all viral infection types has not been established. Based on 44 publicly available datasets and two clinical studies of our own design, we discovered and validated a four-gene expression signature in whole blood, indicative of a general host systemic response to many types of viral infection. The signature’s genes are: Interferon Stimulated Gene 15 (ISG15), Interleukin 16 (IL16), 2′,5′-Oligoadenylate Synthetase Like (OASL), and Adhesion G Protein Coupled Receptor E5 (ADGRE5). In each of 13 validation datasets encompassing human, macaque, chimpanzee, pig, mouse, rat and all seven Baltimore virus classification groups, the signature provides statistically significant (p < 0.05) discrimination between viral and non-viral conditions. The signature may have clinical utility for differentiating host systemic inflammation (SI) due to viral versus bacterial or non-infectious causes.

Benchmarking Sepsis Gene Expression Diagnostics Using Public Data

OBJECTIVE

In response to a need for better sepsis diagnostics, several new gene expression classifiers have been recently published, including the 11-gene "Sepsis MetaScore," the "FAIM3-to-PLAC8" ratio, and the Septicyte Lab. We performed a systematic search for publicly available gene expression data in sepsis and tested each gene expression classifier in all included datasets. We also created a public repository of sepsis gene expression data to encourage their future reuse.

DATA SOURCES

We searched National Institutes of Health Gene Expression Omnibus and EBI ArrayExpress for human gene expression microarray datasets. We also included the Glue Grant trauma gene expression cohorts.

STUDY SELECTION

We selected clinical, time-matched, whole blood studies of sepsis and acute infections as compared to healthy and/or noninfectious inflammation patients. We identified 39 datasets composed of 3,241 samples from 2,604 patients.

DATA EXTRACTION

All data were renormalized from raw data, when available, using consistent methods.

DATA SYNTHESIS

Mean validation areas under the receiver operating characteristic curve for discriminating septic patients from patients with noninfectious inflammation for the Sepsis MetaScore, the FAIM3-to-PLAC8 ratio, and the Septicyte Lab were 0.82 (range, 0.73-0.89), 0.78 (range, 0.49-0.96), and 0.73 (range, 0.44-0.90), respectively. Paired-sample t tests of validation datasets showed no significant differences in area under the receiver operating characteristic curves. Mean validation area under the receiver operating characteristic curves for discriminating infected patients from healthy controls for the Sepsis MetaScore, FAIM3-to-PLAC8 ratio, and Septicyte Lab were 0.97 (range, 0.85-1.0), 0.94 (range, 0.65-1.0), and 0.71 (range, 0.24-1.0), respectively. There were few significant differences in any diagnostics due to pathogen type.

CONCLUSIONS

The three diagnostics do not show significant differences in overall ability to distinguish noninfectious systemic inflammatory response syndrome from sepsis, though the performance in some datasets was low (area under the receiver operating characteristic curve, < 0.7) for the FAIM3-to-PLAC8 ratio and Septicyte Lab. The Septicyte Lab also demonstrated significantly worse performance in discriminating infections as compared to healthy controls. Overall, public gene expression data are a useful tool for benchmarking gene expression diagnostics.

Rhinovirus - From bench to bedside

Rhinovirus has been neglected in the past because it was generally perceived as a respiratory virus only capable of causing mild common cold. Contemporary epidemiological studies using molecular assays have shown that rhinovirus is frequently detected in adult and pediatric patients with upper or lower respiratory tract infections. Severe pulmonary and extrapulmonary complications are increasingly recognized. Contrary to popular belief, some rhinoviruses can actually replicate well at 37 °C and infect the lower airway in humans. The increasing availability of multiplex PCR panels allows rapid detection of rhinovirus and provides the opportunity for timely treatment and early recognition of outbreaks. Recent advances in the understanding of host factors for viral attachment and replication, and the host immunological response in both asthmatic and non-asthmatic individuals, have provided important insights into rhinovirus infection which are crucial in the development of antiviral treatment. The identification of novel drugs has been accelerated by repurposing clinically-approved drugs. As humoral antibodies induced by past exposure and vaccine antigen of a particular serotype cannot provide full coverage for all rhinovirus serotypes, novel vaccination strategies are required for inducing protective response against all rhinoviruses.

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.