Plethysmography Phenotype QTL in Mice Before and After Allergen Sensitization and Challenge

Allergic asthma is common airway disease that is characterized in part by enhanced airway constriction in response to nonspecific stimuli. Genome-wide association studies have identified multiple loci associated with asthma risk in humans, but these studies have not accounted for gene–environment interactions, which are thought to be important factors in asthma. To identify quantitative trait loci (QTL) that regulate responses to a common human allergen, we applied a house dust mite mouse (HDM) model of allergic airway disease (AAD) to 146 incipient lines of the Collaborative Cross (CC) and the CC founder strains. We employed a longitudinal study design in which mice were phenotyped for response to the bronchoconstrictor methacholine both before and after HDM sensitization and challenge using whole body plethysmography (WBP). There was significant variation in methacholine responsiveness due to both strain and HDM treatment, as reflected by changes in the WBP parameter enhanced pause. We also found that distinct QTL regulate baseline [chromosome (Chr) 18] and post-HDM (Chr 19) methacholine responsiveness and that post-HDM airway responsiveness was correlated with other features of AAD. Finally, using invasive measurements of airway mechanics, we tested whether the Chr 19 QTL affects lung resistance per se using C57BL/6J mice and a consomic strain but found that QTL haplotype did not affect lung resistance. We conclude that aspects of baseline and allergen-induced methacholine responsiveness are associated with genetic variation, and that robust detection of airway resistance QTL in genetically diverse mice will be facilitated by direct measurement of airway mechanics

Regional Differences in Mucociliary Clearance in the Upper and Lower Airways

As the nasal cavity is the portal of entry for inspired air in mammals, this region is exposed to the highest concentration of inhaled particulate matter and pathogens, which must be removed to keep the lower airways sterile. Thus, one might expect vigorous removal of these substances via mucociliary clearance (MCC) in this region. We have investigated the rate of MCC in the murine nasal cavity compared to the more distal airways (trachea). The rate of MCC in the nasal cavity (posterior nasopharynx, PNP) was ∼3–4× greater than on the tracheal wall. This appeared to be due to a more abundant population of ciliated cells in the nasal cavity (∼80%) compared to the more sparsely ciliated trachea (∼40%). Interestingly, the tracheal ventral wall exhibited a significantly lower rate of MCC than the tracheal posterior membrane. The trachealis muscle underlying the ciliated epithelium on the posterior membrane appeared to control the surface architecture and likely in part the rate of MCC in this tracheal region. In one of our mouse models (Bpifb1 KO) exhibiting a 3-fold increase in MUC5B protein in lavage fluid, MCC particle transport on the tracheal walls was severely compromised, yet normal MCC occurred on the tracheal posterior membrane. While a blanket of mucus covered the surface of both the PNP and trachea, this mucus appeared to be transported as a blanket by MCC only in the PNP. In contrast, particles appeared to be transported as discrete patches or streams of mucus in the trachea. In addition, particle transport in the PNP was fairly linear, in contrast transport of particles in the trachea often followed a more non-linear route. The thick, viscoelastic mucus blanket that covered the PNP, which exhibited ∼10-fold greater mass of mucus than did the blanket covering the surface of the trachea, could be transported over large areas completely devoid of cells (made by a breach in the epithelial layer). In contrast, particles could not be transported over even a small epithelial breach in the trachea. The thick mucus blanket in the PNP likely aids in particle transport over the non-ciliated olfactory cells in the nasal cavity and likely contributes to humidification and more efficient particle trapping in this upper airway region

Genetic Analysis of Hematological Parameters in Incipient Lines of the Collaborative Cross

Hematological parameters, including red and white blood cell counts and hemoglobin concentration, are widely used clinical indicators of health and disease. These traits are tightly regulated in healthy individuals and are under genetic control. Mutations in key genes that affect hematological parameters have important phenotypic consequences, including multiple variants that affect susceptibility to malarial disease. However, most variation in hematological traits is continuous and is presumably influenced by multiple loci and variants with small phenotypic effects. We used a newly developed mouse resource population, the Collaborative Cross (CC), to identify genetic determinants of hematological parameters. We surveyed the eight founder strains of the CC and performed a mapping study using 131 incipient lines of the CC. Genome scans identified quantitative trait loci for several hematological parameters, including mean red cell volume (Chr 7 and Chr 14), white blood cell count (Chr 18), percent neutrophils/lymphocytes (Chr 11), and monocyte number (Chr 1). We used evolutionary principles and unique bioinformatics resources to reduce the size of candidate intervals and to view functional variation in the context of phylogeny. Many quantitative trait loci regions could be narrowed sufficiently to identify a small number of promising candidate genes. This approach not only expands our knowledge about hematological traits but also demonstrates the unique ability of the CC to elucidate the genetic architecture of complex traits

Integrative Genetic Analysis of Allergic Inflammation in the Murine Lung

Airway allergen exposure induces inflammation among individuals with atopy that is characterized by altered airway gene expression, elevated levels of T helper type 2 cytokines, mucus hypersecretion, and airflow obstruction. To identify the genetic determinants of the airway allergen response, we employed a systems genetics approach. We applied a house dust mite mouse model of allergic airway disease to 151 incipient lines of the Collaborative Cross, a new mouse genetic reference population, and measured serum IgE, airway eosinophilia, and gene expression in the lung. Allergen-induced serum IgE and airway eosinophilia were not correlated. We detected quantitative trait loci (QTL) for airway eosinophilia on chromosome (Chr) 11 (71.802–87.098 megabases [Mb]) and allergen-induced IgE on Chr 4 (13.950–31.660 Mb). More than 4,500 genes expressed in the lung had gene expression QTL (eQTL), the majority of which were located near the gene itself. However, we also detected approximately 1,700 trans-eQTL, and many of these trans-eQTL clustered into two regions on Chr 2. We show that one of these loci (at 147.6 Mb) is associated with the expression of more than 100 genes, and, using bioinformatics resources, fine-map this locus to a 53 kb-long interval. We also use the gene expression and eQTL data to identify a candidate gene, Tlcd2, for the eosinophil QTL. Our results demonstrate that hallmark allergic airway disease phenotypes are associated with distinct genetic loci on Chrs 4 and 11, and that gene expression in the allergically inflamed lung is controlled by both cis and trans regulatory factors

Genetic regulators of sputum mucin concentration and their associations with COPD phenotypes

Hyper-secretion and/or hyper-concentration of mucus is a defining feature of multiple obstructive lung diseases, including chronic obstructive pulmonary disease (COPD). Mucus itself is composed of a mixture of water, ions, salt and proteins, of which the gel-forming mucins, MUC5AC and MUC5B, are the most abundant. Recent studies have linked the concentrations of these proteins in sputum to COPD phenotypes, including chronic bronchitis (CB) and acute exacerbations (AE). We sought to determine whether common genetic variants influence sputum mucin concentrations and whether these variants are also associated with COPD phenotypes, specifically CB and AE. We performed a GWAS to identify quantitative trait loci for sputum mucin protein concentration (pQTL) in the Sub-Populations and InteRmediate Outcome Measures in COPD Study (SPIROMICS, n = 708 for total mucin, n = 215 for MUC5AC, MUC5B). Subsequently, we tested for associations of mucin pQTL with CB and AE using regression modeling (n = 822–1300). Replication analysis was conducted using data from COPDGene (n = 5740) and by examining results from the UK Biobank. We identified one genome-wide significant pQTL for MUC5AC (rs75401036) and two for MUC5B (rs140324259, rs10001928). The strongest association for MUC5B, with rs140324259 on chromosome 11, explained 14% of variation in sputum MUC5B. Despite being associated with lower MUC5B, the C allele of rs140324259 conferred increased risk of CB (odds ratio (OR) = 1.42; 95% confidence interval (CI): 1.10–1.80) as well as AE ascertained over three years of follow up (OR = 1.41; 95% CI: 1.02–1.94). Associations between rs140324259 and CB or AE did not replicate in COPDGene. However, in the UK Biobank, rs140324259 was associated with phenotypes that define CB, namely chronic mucus production and cough, again with the C allele conferring increased risk. We conclude that sputum MUC5AC and MUC5B concentrations are associated with common genetic variants, and the top locus for MUC5B may influence COPD phenotypes, in particular CB

Plethysmography Phenotype QTL in Mice Before and After Allergen Sensitization and Challenge

Allergic asthma is common airway disease that is characterized in part by enhanced airway constriction in response to nonspecific stimuli. Genome-wide association studies have identified multiple loci associated with asthma risk in humans, but these studies have not accounted for gene–environment interactions, which are thought to be important factors in asthma. To identify quantitative trait loci (QTL) that regulate responses to a common human allergen, we applied a house dust mite mouse (HDM) model of allergic airway disease (AAD) to 146 incipient lines of the Collaborative Cross (CC) and the CC founder strains. We employed a longitudinal study design in which mice were phenotyped for response to the bronchoconstrictor methacholine both before and after HDM sensitization and challenge using whole body plethysmography (WBP). There was significant variation in methacholine responsiveness due to both strain and HDM treatment, as reflected by changes in the WBP parameter enhanced pause. We also found that distinct QTL regulate baseline [chromosome (Chr) 18] and post-HDM (Chr 19) methacholine responsiveness and that post-HDM airway responsiveness was correlated with other features of AAD. Finally, using invasive measurements of airway mechanics, we tested whether the Chr 19 QTL affects lung resistance per se using C57BL/6J mice and a consomic strain but found that QTL haplotype did not affect lung resistance. We conclude that aspects of baseline and allergen-induced methacholine responsiveness are associated with genetic variation, and that robust detection of airway resistance QTL in genetically diverse mice will be facilitated by direct measurement of airway mechanics

Determinants of QTL Mapping Power in the Realized Collaborative Cross

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments

Predicted effects of observed changes in the mRNA and microRNA transcriptome of lung neutrophils during S. pneumoniae pneumonia in mice

Abstract The complex role of neutrophils in modulating the inflammatory response is increasingly appreciated. Our studies profiled the expression of mRNAs and microRNAs (miRs) in lung neutrophils in mice during S. pneumoniae pneumonia and performed in depth in silico analyses. Lung neutrophils were isolated 24 hours after intratracheal instillation of PBS or S. pneumoniae, and differentially expressed (DE) mRNAs and miRs were identified. Lung neutrophils from mice with S. pneumoniae pneumonia contained 4127 DE mRNAs, 36% of which were upregulated at least 2-fold. During pneumonia, lung neutrophils increase expression of pattern recognition receptors, receptors for inflammatory mediators, transcription factors including NF-κB and AP-1, Nrf2 targets, cytokines, chemokines and other inflammatory mediators. Interestingly, neutrophils responded to Type I interferons, whereas they both produced and responded to Type II interferon. Expression of regulators of the inflammatory and immune response was verified at the mRNA and protein level. Of approximately 1100 miRs queried, 31 increased and 67 decreased more than 2-fold in neutrophils from S. pneumoniae pneumonia. Network analyses of potential DE miR-target DE mRNA interactions revealed candidate key regulatory miRs. Thus, S. pneumoniae modulates mRNA and miR expression by lung neutrophils, increasing their ability to respond and facilitating host defense