Biology subjects

Mariani, T. J.

Publications and source records attributed to Mariani, T. J..

14 recordsLinked to original sources

bioRxiv2026

Transcriptional regulation of the main olfactory epithelium by environmental olfactory exposures

The nasal epithelium is a complex tissue composed of both respiratory and olfactory tissue, and is constantly exposed to environmental insults, including toxins and pathogens. The main olfactory epithelium (MOE) serves as the critical site for olfaction, or sense of smell. Dysfunction at this critical barrier tissue can result in partial or total loss of olfactory function, resulting in significant impact to quality of life. The MOE is heterogeneous, comprised of many cell types including olfactory sensory neurons, support cells, and immune cells. It is not well understood how these diverse cell types in the MOE interact to regulate this tissue during homeostasis, and during times of injury and inflammation. We investigated how environmental olfactory exposures impact cell type specific transcriptional responses in the mouse MOE. We performed single-cell RNA sequencing (scRNA-seq) of the MOE following controlled environmental exposure to both well-known odorants and allergens. We identified major cell types and subtypes within the MOE, and identified transcriptional changes in response to the olfactory exposures. We identified transcriptional changes in OSNs, sustentacular cells, and resident immune cells to each condition. This indicated that environmental olfactory exposures drive changes to multiple cell types in the MOE. To our knowledge, this is the first study to identify effects of environmental olfactory exposures on cell-type specific transcription at homeostasis. These findings highlight the potential importance of multi-cellular interactions and communication in regulation of the olfactory epithelium.

neuroscience↗

bioRxiv2026

SARS-CoV-2 Defective Viral Genomes from Distinct Genomic Regions Drive Divergent Interferon Responses

Defective viral genomes (DVGs) are naturally generated during genomic replication of many RNA viruses. When produced early in infection or supplemented at the onset of infection, DVGs can attenuate viral pathogenesis by stimulating IFN responses and antagonizing wild type (WT) virus replication, highlighting their potential as antiviral therapeutics. However, during natural infection DVGs can exert both antiviral and proviral effects depending on their generation kinetics, species, and abundance, underscoring the need to better understand their roles in viral pathogenesis. Coronaviruses (CoVs) remain a major global health threat and ubiquitously generate DVGs, yet DVGs roles during CoV infection are largely unknown. Using SARS-CoV-2 as a model, we previously identified DVGs in vitro and in patient samples and discovered two major genomic hotspots (A and B) for their generation. Here, we first showed that overall DVG abundance tended to positively correlate with COVID-19 severity, with approximately 40% of DVGs originating from a specific genomic region designated hotspot B. Analysis of a publicly available single-cell RNA-seq datasets revealed that DVGs from hotspot B, but not hotspot A, were associated with elevated IFN responses, suggesting that DVGs derived from different genomic regions vary in their ability to stimulate innate immunity. To test this directly, we constructed two representative DVGs corresponding to hotspots A and B. Both DVGs suppressed the replication of co-infecting WT virus; however, only DVG-B induced robust IFN responses, exceeding those triggered by WT virus alone. This was further confirmed in human precision-cut lung slices. Mechanistically, DVG-B-derived dsRNA exhibited a distinct subcellular distribution compared with WT virus. Complementation with the nucleocapsid (N) partially restored dsRNA organization but did not alter the IFN response. Together, our findings demonstrate that DVGs arising from distinct genomic hotspots differentially regulate IFN responses, potentially contributing to varied pathogenic outcomes during SARS-CoV-2 infection. Author summaryDefective viral genomes (DVGs) are naturally produced during RNA virus infection and can suppress viral pathogenesis by stimulating innate immune responses. However, their roles in coronavirus infection, particularly SARS-CoV-2, remain poorly understood. This study investigated the species-specific function of DVGs generated during SARS-CoV-2 infection and their impact on disease outcomes. Cohort analysis revealed that overall DVG abundance tended to positively correlate with COVID-19 severity, with approximately 40% of DVGs originating from a specific genomic region designated hotspot B. Single-cell RNA sequencing showed that DVGs from hotspot B, but not hotspot A, were associated with elevated IFN responses, suggesting that DVGs from different genomic regions vary in their immunostimulatory capacity. To directly test this, we constructed representative DVGs from both hotspots. While both suppressed wild-type virus replication, only DVG-B induced robust IFN responses both in vitro and ex vivo. Mechanistically, DVG-B produced dsRNA with distinct subcellular distribution compared to wild-type virus. Interestingly, complementation with the viral nucleocapsid protein partially restored dsRNA organization but did not alter IFN responses. These findings demonstrate that SARS-CoV-2 DVGs arising from different genomic hotspots differentially regulate innate immunity, potentially contributing to varied pathogenic outcomes during infection.

microbiology↗

bioRxiv2025

A Respiratory Syncytial Virus trailer sequence modulates viral replication and copy-back defective viral genome generation and propagation kinetics

Copy-back defective viral genomes (cbDVGs) are key inducers of antiviral responses during negative-sense RNA virus infection. Once considered byproducts of in vitro viral replication, cbDVGs have since been detected in clinical specimens and implicated in affecting infection outcomes. The molecular mechanism of cbDVG generation remains unclear, thereby hindering our ability to manipulate cbDVG production during infection for therapeutic gain. Previous work showed that respiratory syncytial virus (RSV) cbDVG re-initiation sites cluster in trailer-end hotspots R1, R2, and R3, and that a poly-U mutation in R1 selectively reduced cbDVG formation at the mutated region. Here, we reported that a 10U mutation in R2 drastically reduced cbDVGs in this region in both minigenome and recombinant virus systems. Furthermore, during high-MOI passaging of the R2-10U virus, we observed delayed detection of cbDVGs with re-initiation sites in R1-R3 (trailer cbDVGs) compared to WT, while no differences in virus titers were observed. Interestingly, we observed the rapid emergence and accumulation of a viral variant bearing a 2-ribonucleotide deletion (R2-8U) within the R2-10U mutation sequence as early as P0. Compared to R2-10U, the R2-8U virus was stable, displayed faster generation and accumulation of trailer cbDVGs, restored cbDVGs with R2 re-initiation sites, and exhibited enhanced genomic replication. Overall, our data identify a sequence in the RSV trailer whose mutation critically modulates both viral replication and the generation/propagation of trailer cbDVGs. Our data also suggest that cbDVG generation, particularly near the trailer, may be an evolutionary tradeoff for more rapid virus genomic replication.

microbiology↗

bioRxiv2024

Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cells

The ability of SARS-CoV-2 to evade antiviral immune signaling in the airway contributes to the severity of COVID-19 disease. Additionally, COVID-19 is influenced by age and has more severe presentations in older individuals. This raises questions about innate immune signaling as a function of lung development and age. Therefore, we investigated the transcriptome of different cell populations of the airway epithelium using pediatric and adult lung tissue samples from the LungMAP Human Tissue Core Biorepository. Specifically, lung lobes were digested and cultured into a biomimetic model of the airway epithelium on an air-liquid interface. Cells were then infected with SARS-CoV-2 and subjected to single-cell RNA sequencing. Transcriptional profiling and differential expression analysis were carried out using Seurat. The clustering analysis identified several cell populations: club cells, proliferating epithelial cells, multiciliated precursor cells, ionocytes, and two biologically distinct clusters of ciliated cells (FOXJ1high and FOXJ1low). Interestingly, the two ciliated cell clusters showed different infection rates and enrichment of processes involved in ciliary biogenesis and function; we observed a cell-type-specific suppression of innate immunity in infected cells from the FOXJ1low subset. We also identified a significant number of genes that were differentially expressed in lung cells derived from children as compared to adults, suggesting the differential pathogenesis of SARS-CoV-2 infection in children versus adults. We discuss how this work can be used to identify drug targets to modulate molecular signaling cascades that mediate an innate immune response and begin to understand differences in COVID-19 outcomes for pediatric vs. adult populations. ImportanceViral innate immune evasion leads to uncontrolled viral spread in infected tissues and increased pathogenicity in COVID-19. Understanding the dynamic of the antiviral signaling in lung tissues may help us to understand which molecular signals lead to more severe disease in different populations, particularly considering the enhanced vulnerability of older populations. This study provides foundational insight into the age-related differences in innate immune responses to SARS-CoV-2, identifying distinct patterns of infection and molecular signaling in different cell populations of airway epithelial cells from pediatric and adult lung tissues. The findings provide a deeper understanding of age-related differences in COVID-19 pathology and pave the way for developing targeted therapies.

systems biology↗

bioRxiv2022

Generation and functional analysis of defective viral genomes during SARS-CoV-2 infection

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from RNA-seq datasets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hotspots were identified for DVG recombination and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single cell RNA-seq analysis indicated the IFN stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the NGS dataset from a published cohort study and observed significantly higher DVG amount and frequency in symptomatic patients than that in asymptomatic patients. Finally, we observed unusually high DVG frequency in one immunosuppressive patient up to 140 days after admitted to hospital due to COVID-19, first-time suggesting an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. ImportanceDefective viral genomes (DVGs) are ubiquitously generated in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide them the potential for novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex and the recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hotspots for non-homologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide the evidence to harness DVGs immunostimulatory potential in the development of vaccine and antivirals for SARS-CoV-2.

microbiology↗

bioRxiv2022

Genetic Variation and Disease Severity of Respiratory Syncytial Viruses

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

microbiology↗

bioRxiv2021

Gene Expression Risk Scores for COVID-19 Illness Severity

BackgroundThe correlates of COVID-19 illness severity following infection with SARS-Coronavirus 2 (SARS-CoV-2) are incompletely understood. MethodsWe assessed peripheral blood gene expression in 53 adults with confirmed SARS-CoV-2-infection clinically adjudicated as having mild, moderate or severe disease. Supervised principal components analysis was used to build a weighted gene expression risk score (WGERS) to discriminate between severe and non-severe COVID. ResultsGene expression patterns in participants with mild and moderate illness were similar, but significantly different from severe illness. When comparing severe versus non-severe illness, we identified >4000 genes differentially expressed (FDR<0.05). Biological pathways increased in severe COVID-19 were associated with platelet activation and coagulation, and those significantly decreased with T cell signaling and differentiation. A WGERS based on 18 genes distinguished severe illness in our training cohort (cross-validated ROC-AUC=0.98), and need for intensive care in an independent cohort (ROC-AUC=0.85). Dichotomizing the WGERS yielded 100% sensitivity and 85% specificity for classifying severe illness in our training cohort, and 84% sensitivity and 74% specificity for defining the need for intensive care in the validation cohort. ConclusionThese data suggest that gene expression classifiers may provide clinical utility as predictors of COVID-19 illness severity.

genomics↗

bioRxiv2020

A systems genomics approach uncovers molecular associates of RSV severity

Globally, RSV infection results in millions of hospitalizations and thousands of deaths each year. Specific factors that contribute to disease severity, such as premature birth and certain comorbidities, are well established. Additionally, genetic variants resulting in alterations in the adaptive and innate immune response appear to be associated with RSV severity. While previous studies focused on a single aspect of the disease, we jointly modeled the association of disparate data modalities with RSV severity. To investigate the host response to respiratory syncytial virus (RSV) infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. Specifically, we developed and employed a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation. Our novel approach enabled us to identify cell type specific and shared cellular pathways associated with RSV severity. Of particular interest was the association between RSV severity, activation of pathways controlling Th17 and acute phase response signaling, and inhibition of B cell receptor signaling, which were present in both airway and immune cells. These data identify specific aspects of dysregulation between the humoral and mucosal response to RSV that may play a critical role in determining illness severity.

genomics↗

bioRxiv2020

Lymphocyte-Specific Biomarkers Associated with Preterm Birth and Bronchopulmonary Dysplasia

Many premature babies who are born with neonatal respiratory distress syndrome (RDS) go on to develop Bronchopulmonary Dysplasia (BPD) and later Post-Prematurity Respiratory Disease (PRD) at one year corrected age, characterized by persistent or recurrent lower respiratory tract symptoms frequently related to inflammation and viral infection. Transcriptomic profiles were generated from sorted peripheral blood CD8+ T cells of preterm and full-term infants enrolled with consent in the NHLBI Prematurity and Respiratory Outcomes Program (PROP) at the University of Rochester and the University at Buffalo. We identified outcome-related gene expression patterns following standard methods to identify markers for oxygen utilization and BPD as outcomes in extremely premature infants. We further identified predictor gene sets for BPD based on transcriptomic data adjusted for gestational age at birth (GAB). RNA-Seq analysis was completed for CD8+ T cells from 145 subjects. Among the subjects with highest risk for BPD (born at <29 weeks gestational age (GA); n=72), 501 genes were associated with oxygen utilization. In the same set of subjects, 571 genes were differentially expressed in subjects with a diagnosis of BPD and 105 genes were different in BPD subjects as defined by physiologic challenge. A set of 92 genes could predict BPD with a moderately high degree of accuracy. We consistently observed dysregulation of NRF2, HIPPO and CD40-associated pathways in BPD. Using gene expression data from both premature and full-term subjects (n=116), we identified a 28 gene set that predicted the PRD status with a moderately high level of accuracy. Transcriptomic data from sort-purified peripheral blood CD8+ T cells from 145 preterm and full-term infants identified sets of molecular markers associated with independent development of BPD in extremely premature infants at high risk for the disease and of PRD among the preterm and full-term subjects.

genomics↗

bioRxiv2020

CX3CR1 Engagement by Respiratory Syncytial Virus Leads to Induction of Nucleolin and Dysregulation of Cilia-related Genes

Respiratory syncytial virus (RSV) contains a conserved CX3C motif on the ectodomain of the G-protein. The motif has been indicated as facilitating attachment of the virus to the host initiating infection via the human CX3CR1 receptor. The natural CX3CR1 ligand, CX3CL1, has been shown to induce signaling pathways resulting in transcriptional changes in the host cells. We hypothesize that binding of RSV to CX3CR1 via CX3C leads to transcriptional changes in host epithelial cells. Using transcriptomic analysis, the effect of CX3CR1 engagement by RSV was investigated. Normal human bronchial epithelial (NHBE) cells were infected with RSV virus containing either wildtype G-protein, or a mutant virus containing a CX4C mutation in the G-protein. RNA sequencing was performed on mock and 4-days-post-infected cultures. NHBE cultures were also treated with purified recombinant wild-type A2 G-protein. Here we report that RSV infection resulted in significant changes in the levels 766 transcripts. Many nuclear associated proteins were upregulated in the WT group, including Nucleolin. Alternatively, cilia-associated genes, including CC2D2A and CFAP221 (PCDP1), were downregulated. The addition of recombinant G-protein to the culture lead to the suppression of cilia-related genes while also inducing Nucleolin. Mutation of the CX3C motif (CX4C) reversed these effects on transcription decreasing nucleolin induction and lessening the suppression of cilia-related transcripts in culture. Furthermore, immunohistochemical staining demonstrated decreases in in ciliated cells and altered morphology. Therefore, it appears that engagement of CX3CR1 leads to induction of genes necessary for RSV entry as well as dysregulation of genes associated with cilia function. ImportanceRespiratory Syncytial Virus (RSV) has an enormous impact on infants and the elderly including increased fatality rates and potential for causing lifelong lung problems. Humans become infected with RSV through the inhalation of viral particles exhaled from an infected individual. These virus particles contain specific proteins that the virus uses to attach to human ciliated lung epithelial cells, initiating infection. Two viral proteins, G-protein and F-protein, have been shown to bind to human CX3CR1and Nucleolin, respectively. Here we show that the G-protein induces Nucleolin and suppresses gene transcripts specific to ciliated cells. Furthermore, we show that mutation of the CX3C-motif on the G-protein, CX4C, reverses these transcriptional changes.

microbiology↗

bioRxiv2020

Single cell transcriptomic profiling identifies molecular phenotypes of newborn human lung cells

RationaleWhile animal model studies have extensively defined mechanisms controlling cell diversity in the developing mammalian lung, the limited data available from late stage human lung development represents a significant knowledge gap. The NHLBI Molecular Atlas of Lung Development Program (LungMAP) seeks to fill this gap by creating a structural, cellular and molecular atlas of the human and mouse lung. MethodsSingle cell RNA sequencing generated transcriptional profiles of 5500 cells obtained from two one-day old human lungs (born at gestational ages of 39 and 31 weeks) from the LungMAP Human Tissue Core Biorepository at the University of Rochester. Frozen single cell isolates were captured, and library preparation was completed on the Chromium 10X system. Data was analyzed in Seurat, and cellular annotation was performed using the ToppGene functional analysis tool. Single cell sequence data from 32000 postnatal day 1, 3, 7 and 10 mouse lung (n = 2 at each time point) cells generated by the LungMAP Research Center at Cincinnati Childrens Hospital and Medical Center, using Dropseq platform, was integrated with the human data. In situ hybridization was used to confirm the spatial location of cellular phenotypes. ResultsTranscriptional interrogation of donor newborn human lung cells identified distinct clusters representing multiple populations of epithelial, endothelial, fibroblasts, pericytes, smooth muscle, and immune cells and signature genes for each of these populations were identified. Computational integration of newborn human and postnatal mouse lung development cellular transcriptomes facilitated the identification of distinct cellular lineages among all the major cell types. Integration of the human and mouse cellular transcriptomes also demonstrated cell type-specific differences in developmental states of the newborn human lung cells. In particular, matrix fibroblasts could be separated into those representative of younger cells (n=393), or older cells (n=158). This is the first comprehensive molecular map of the cellular landscape of neonatal human lung, including biomarkers for cells at distinct states of development. Our results indicate that integrated single cell RNA profiling of human and mouse lung will help identify common and species-specific mechanisms of lung development and respiratory disease.

genomics↗

bioRxiv2020

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection

RationaleRespiratory Syncytial Virus (RSV) infection is a leading cause of infant respiratory disease and hospitalization. Infant airway microbiota occupying the nasopharynx have been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease severity and infection susceptibility, are not well understood. ObjectivesTo characterize associations between the nasal microbiota and RSV infection before, during, and after infants first respiratory illness. MethodsNasal 16S rRNA microbial community profiling of two cohorts of infants in the first year of life: 1) a cross-sectional cohort of 89 RSV infected infants sampled during illness and 102 population matched healthy controls, and 2) an individually matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled at time points before, during, and after infection. Measurements and Main ResultsWe identified 12 taxa significantly associated with RSV infection. All 12 were differentially abundant during infection, with seven differentially abundant prior to infection, and eight differentially abundant after infection. Eight of these taxa were associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs. infected than of disease severity. ConclusionsOur findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with first-time RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and the impact of RSV infection on microbiota composition. Identified taxa represent appealing targets for additional translationally-oriented research.

microbiology↗

bioRxiv2019

Insufficiency in airway interferon activation defines clinical severity to infant RSV infection

Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. Other than age at the time of infection, the causes and correlates of severe illness in infants lacking known risk factors are poorly defined. We recruited a cohort of confirmed RSV-infected infants and simultaneously assayed the presence of resident airway microbiota and the molecular status of their airways using a novel method. Rigorous statistical analyses identified a molecular airway gene expression signature of severe illness dominated by excessive chemokine expression. Global 16S rRNA sequencing confirmed an association between H. influenzae and clinical severity. Interestingly, adjusting for H. influenzae in our gene expression analysis revealed an association between severity and airway lymphocyte accumulation. Exploring the relationship between airway gene expression and the time of onset of clinical symptoms revealed a robust, acute activation of interferon (IFN) signaling, which was absent in subjects with severe illness. Finally, we explored the relationship between IFN activity, airway gene expression and productive RSV infection using a novel in vitro model of bona fide pediatric human airway epithelial cells. Interestingly, blocking IFN signaling, but not IFN ligand production, in these cells leads to increased viral infection. Our data reveal that acute airway interferon responses are physiologically relevant in the context of infant RSV infection and may be a target for therapeutic intervention. Additionally, the airway gene expression signature we define may be useful as a biomarker for efficacy of intervention responses.

genomics↗

bioRxiv2019

Airway Gene-Expression Classifiers for Respiratory Syncytial Virus (RSV) Disease Severity in Infants

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

immunology↗