Genomic Circuitry Underlying Immunological Response to Pediatric Acute Respiratory Infection

Integrated Drivers of Basal and Acute Immunity in Diverse Human Populations

Prior studies have identified genetic, infectious, and biological associations with immune competence and disease severity; however, there have been few integrative analyses of these factors and study populations are often limited in demographic diversity. Utilizing samples from 1,705 individuals in 5 countries, we examined putative determinants of immunity, including: single nucleotide polymorphisms, ancestry informative markers, herpesvirus status, age, and sex. In healthy subjects, we found significant differences in cytokine levels, leukocyte phenotypes, and gene expression. Transcriptional responses also varied by cohort, and the most significant determinant was ancestry. In influenza infected subjects, we found two disease severity immunophenotypes, largely driven by age. Additionally, cytokine regression models show each determinant differentially contributes to acute immune variation, with unique and interactive, location-specific herpesvirus effects. These results provide novel insight into the scope of immune heterogeneity across diverse populations, the integrative effects of factors which drive it, and the consequences for illness outcomes.

Metatranscriptome Reveals Specific Immune and Microbial Signatures of Respiratory Syncytial Virus Infection in Children

Respiratory syncytial virus (RSV) is the most frequently detected respiratory virus in children with acute lower respiratory tract infection. Previous transcriptome studies have focused on systemic transcriptional profiles in blood and have not compared the expression of multiple viral transcriptomes. Here, we sought to compare transcriptome responses to infection with four common respiratory viruses for children (respiratory syncytial virus, adenovirus, influenza virus, and human metapneumovirus) in respiratory samples. Transcriptomic analysis showed that cilium organization and assembly were common pathways related to viral infection. Compared with other virus infections, collagen generation pathways were distinctively enriched in RSV infection. We identified two interferon-stimulated genes (ISGs), CXCL11 and IDO1, which were upregulated to a greater extent in the RSV group. In addition, a deconvolution algorithm was used to analyze the composition of immune cells in respiratory tract samples. The proportions of dendritic cells and neutrophils in the RSV group were significantly higher than those in the other virus groups. The RSV group exhibited a higher richness of Streptococcus than the other virus groups. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of the host response to RSV. Last, according to host-microbe network interference, RSV may disrupt respiratory microbial composition by changing the immune microenvironment. IMPORTANCE In the present study, we demonstrated the comparative results of host responses to infection between RSV and other three common respiratory viruses for children. The comparative transcriptomics study of respiratory samples sheds light on the significant roles that ciliary organization and assembly, extracellular matrix changes, and microbial interactions play in the pathogenesis of RSV infection. Additionally, it was demonstrated that the recruitment of neutrophils and dendritic cells (DCs) in the respiratory tract is more substantial in RSV infection than in other viral infections. Finally, we discovered that RSV infection dramatically increased the expression of two ISGs (CXCL11 and IDO1) and the abundance of Streptococcus.

Age-Related Increase of Collagen/Fibrin Deposition and High PAI-1 Production in Human Nasal Polyps

Objective: Our previous studies showed an age-related increased prevalence of nasal polyps (NP) and reduced production of S100A8/9 in elderly patients with chronic rhinosinusitis with NP (CRSwNP). In this study, we investigated an unbiased age-related gene expression profile in CRSwNP subjects and healthy controls, and further identified the differences in their tissue remodeling. Methods: Microarrays using NP and uncinate tissues from health controls (elderly, age ≥65 vs. non-elderly, age 18-49) were performed, and differentially regulated genes were analyzed. Quantitative real-time PCR (qPCR), Immunostaining, Periodic acid-Schiff (PAS), trichrome staining, Western blot, and ELISA were performed for further investigation. Results: Microarrays identified differentially expressed genes according to disease and age; 278 in NP vs. controls, 75 in non-elderly NP vs. non-elderly controls, and 32 in elderly NP vs. elderly controls. qPCR confirmed that the PLAT gene was downregulated and the SERPINB2 gene upregulated in NP vs. controls. The serous glandular cell-derived antimicrobial protein/peptide-related genes such as BPIFB3, BPIFB2, LPO, and MUC7 were remarkably reduced in NP, regardless of age. SERPINE1 gene (plasminogen activator inhibitor-1, PAI-1) expression was significantly increased in elderly NP versus elderly controls. IHC and western blot confirmed significantly decreased production of MUC7 and LPO in NP versus controls. There was a trend of age-related reduction of submucosal gland cells in normal controls. Trichrome and immunofluorescence staining demonstrated an age-related increase of collagen and fibrin deposition in NP, consistent with increased PAI-1 production. Conclusion: This study demonstrated age-related differential glandular remodeling patterns and fibrosis in NP and normal controls. PAI-1 expression was significantly increased in elderly NP versus elderly controls, suggesting PAI-1 as a potential treatment target in elderly NP.

Identifying Methylation Signatures and Rules for COVID-19 With Machine Learning Methods

The occurrence of coronavirus disease 2019 (COVID-19) has become a serious challenge to global public health. Definitive and effective treatments for COVID-19 are still lacking, and targeted antiviral drugs are not available. In addition, viruses can regulate host innate immunity and antiviral processes through the epigenome to promote viral self-replication and disease progression. In this study, we first analyzed the methylation dataset of COVID-19 using the Monte Carlo feature selection method to obtain a feature list. This feature list was subjected to the incremental feature selection method combined with a decision tree algorithm to extract key biomarkers, build effective classification models and classification rules that can remarkably distinguish patients with or without COVID-19. EPSTI1, NACAP1, SHROOM3, C19ORF35, and MX1 as the essential features play important roles in the infection and immune response to novel coronavirus. The six significant rules extracted from the optimal classifier quantitatively explained the expression pattern of COVID-19. Therefore, these findings validated that our method can distinguish COVID-19 at the methylation level and provide guidance for the diagnosis and treatment of COVID-19.

Genome-Wide Interaction Study of Late-Onset Asthma With Seven Environmental Factors Using a Structured Linear Mixed Model in Europeans

Asthma is among the most common chronic diseases worldwide, creating a substantial healthcare burden. In late-onset asthma, there are wide global differences in asthma prevalence and low genetic heritability. It has been suggested as evidence for genetic susceptibility to asthma triggered by exposure to multiple environmental factors. Very few genome-wide interaction studies have identified gene-environment (G×E) interaction loci for asthma in adults. We evaluated genetic loci for late-onset asthma showing G×E interactions with multiple environmental factors, including alcohol intake, body mass index, insomnia, physical activity, mental status, sedentary behavior, and socioeconomic status. In gene-by-single environment interactions, we found no genome-wide significant single-nucleotide polymorphisms. However, in the gene-by-multi-environment interaction study, we identified three novel and genome-wide significant single-nucleotide polymorphisms: rs117996675, rs345749, and rs17704680. Bayes factor analysis suggested that for rs117996675 and rs17704680, body mass index is the most relevant environmental factor; for rs345749, insomnia and alcohol intake frequency are the most relevant factors in the G×E interactions of late-onset asthma. Functional annotations implicate the role of these three novel loci in regulating the immune system. In addition, the annotation for rs117996675 supports the body mass index as the most relevant environmental factor, as evidenced by the Bayes factor value. Our findings help to understand the role of the immune system in asthma and the role of environmental factors in late-onset asthma through G×E interactions. Ultimately, the enhanced understanding of asthma would contribute to better precision treatment depending on personal genetic and environmental information.

A comparison of host response strategies to distinguish bacterial and viral infection

OBJECTIVES

Compare three host response strategies to distinguish bacterial and viral etiologies of acute respiratory illness (ARI).

METHODS

In this observational cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene expression mRNA panel were measured in 286 subjects with ARI from four emergency departments. Multinomial logistic regression and leave-one-out cross validation were used to evaluate the protein and mRNA tests.

RESULTS

The mRNA panel performed better than alternative strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel, and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93 for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein panel, respectively.

CONCLUSIONS

A gene expression signature was the most accurate host response strategy for classifying subjects with bacterial, viral, or non-infectious ARI.

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection: a nested, case-control diagnostic accuracy study

BACKGROUND

We hypothesised that host-response biomarkers of viral infections might contribute to early identification of individuals infected with SARS-CoV-2, which is critical to breaking the chains of transmission. We aimed to evaluate the diagnostic accuracy of existing candidate whole-blood transcriptomic signatures for viral infection to predict positivity of nasopharyngeal SARS-CoV-2 PCR testing.

METHODS

We did a nested case-control diagnostic accuracy study among a prospective cohort of health-care workers (aged ≥18 years) at St Bartholomew's Hospital (London, UK) undergoing weekly blood and nasopharyngeal swab sampling for whole-blood RNA sequencing and SARS-CoV-2 PCR testing, when fit to attend work. We identified candidate blood transcriptomic signatures for viral infection through a systematic literature search. We searched MEDLINE for articles published between database inception and Oct 12, 2020, using comprehensive MeSH and keyword terms for "viral infection", "transcriptome", "biomarker", and "blood". We reconstructed signature scores in blood RNA sequencing data and evaluated their diagnostic accuracy for contemporaneous SARS-CoV-2 infection, compared with the gold standard of SARS-CoV-2 PCR testing, by quantifying the area under the receiver operating characteristic curve (AUROC), sensitivities, and specificities at a standardised Z score of at least 2 based on the distribution of signature scores in test-negative controls. We used pairwise DeLong tests compared with the most discriminating signature to identify the subset of best performing biomarkers. We evaluated associations between signature expression, viral load (using PCR cycle thresholds), and symptom status visually and using Spearman rank correlation. The primary outcome was the AUROC for discriminating between samples from participants who tested negative throughout the study (test-negative controls) and samples from participants with PCR-confirmed SARS-CoV-2 infection (test-positive participants) during their first week of PCR positivity.

FINDINGS

We identified 20 candidate blood transcriptomic signatures of viral infection from 18 studies and evaluated their accuracy among 169 blood RNA samples from 96 participants over 24 weeks. Participants were recruited between March 23 and March 31, 2020. 114 samples were from 41 participants with SARS-CoV-2 infection, and 55 samples were from 55 test-negative controls. The median age of participants was 36 years (IQR 27-47) and 69 (72%) of 96 were women. Signatures had little overlap of component genes, but were mostly correlated as components of type I interferon responses. A single blood transcript for IFI27 provided the highest accuracy for discriminating between test-negative controls and test-positive individuals at the time of their first positive SARS-CoV-2 PCR result, with AUROC of 0·95 (95% CI 0·91-0·99), sensitivity 0·84 (0·70-0·93), and specificity 0·95 (0·85-0·98) at a predefined threshold (Z score >2). The transcript performed equally well in individuals with and without symptoms. Three other candidate signatures (including two to 48 transcripts) had statistically equivalent discrimination to IFI27 (AUROCs 0·91-0·95).

INTERPRETATION

Our findings support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection for screening individuals at high risk of infection, such as contacts of index cases, to facilitate early case isolation and early use of antiviral treatments as they emerge.

FUNDING

Barts Charity, Wellcome Trust, and National Institute of Health Research.

Mycoplasma pneumoniae P1 Genotype Indicates Severity of Lower Respiratory Tract Infections in Children

Mycoplasma pneumoniae strains can be classified into two major genetic groups, P1 type 1 (P1-1) and P1 type 2 (P1-2). It remains unknown if clinical manifestations of lower respiratory tract infections (LRTI) in children differ between the two genotypes. We aimed to determine if the M. pneumoniae P1 genotype is associated with severity of LRTI in children. Medical charts of 420 children (≤15 years old) with signs of acute LRTI who were PCR positive for M. pneumoniae from pharyngeal swabs in a recent M. pneumoniae epidemic were analyzed. We used a culture and pyrosequencing approach for genotyping PCR-positive samples. We compared epidemiological and clinical data of children with either P1-1 or P1-2 LRTI. P1-2-infected children presented with a significantly higher median baseline C-reactive protein level and were admitted to the hospital more often. The P1 genotype had a significant predictive value in a multiple linear regression model predicting C-reactive protein levels in our study sample. Moreover, the P1 genotype significantly affected the likelihood of hospital admission in a logistic regression model. Our modeling results were also confirmed on an additional independent sample of children with M. pneumoniae LRTI. Results from our large patient group indicate that the two M. pneumoniae P1 genotypes may have different pathogenic potential and that LRTI with P1-2 strains may have a more severe disease course than those with P1-1 strains in children. P1 genotyping is not routinely performed but could be used as a predictor of M. pneumoniae LRTI severity, enabling patient-tailored treatments.

Age-Dependent Differences in T-Cell Responses to Influenza A Virus

Respiratory infections from influenza A virus (IAV) cause substantial morbidity and mortality in children relative to adults. T cells play a critical role in the host response to IAV by supporting the innate and humoral responses, mediating cytotoxic activity, and promoting recovery. There are age-dependent differences in the number, subsets, and localization of T cells, which impact the host response to pathogens. In this article, we first review how T cells recognize IAV and examine differences in the resting T-cell populations between juveniles and adults. Next, we describe how the juvenile CD4⁺, CD8⁺, and regulatory T-cell responses compare with those in adults and discuss the potential physiologic and clinical consequences of the differences. Finally, we explore the roles of two unconventional T-cell types in the juvenile response to influenza, natural-killer T cells and γδ T cells. A clear understanding of age-dependent differences in the T-cell response is essential to developing therapies to prevent or reverse the deleterious effects of IAV in children.

Clinical characteristics of infections caused by Mycoplasma pneumoniae P1 genotypes in children

Mycoplasma pneumoniae (M. pneumoniae) isolates can be classified into two major genetic groups, P1 type 1 (MP1) and P1 type 2 (MP2), based on the DNA sequence of the P1 adhesion protein gene. The aim of our study was to determine if M. pneumoniae P1 genotype is associated with disease manifestation and severity of acute M. pneumoniae infection. We compared epidemiological and clinical data of children infected with either MP1 or MP2. In addition, we separately analysed data of patients presenting with individual manifestations of M. pneumoniae infection. Data of 356 patients infected with MP1 were compared with those of 126 patients infected with MP2. MP2-infected children presented with higher median baseline C-reactive protein levels and were admitted to the hospital more often. The distribution of P1 genotype varied among groups of patients with different manifestations of M. pneumoniae infection. MP2 was more common than MP1 among patients with neurological and cardiovascular manifestations, whereas MP1 was more prevalent in other manifestations. The results from our large cohort indicate that the two P1 subtypes may have different pathogenic potential and that infections with MP2 strains could be more virulent than those with MP1 strains.