Clinical characteristics of subjects who participated in the microarray and RT-qPCR study.

<p>Clinical characteristics of subjects who participated in the microarray and RT-qPCR study.</p

Severe asthma versus health, in central airways and in peripheral airways.

<p><b>A.</b><i>Greater expression</i>, genes with a greater expression in severe asthmatics when compared to healthy volunteers; <i>Lesser expression</i>, genes with a lesser expression in severe asthmatics when compared to healthy controls. <b>B.</b> Fold changes for IL-13 disease signature and steroid response obtained by differential gene expression analysis. <b>C.</b> RT-qPCR validation of microarray findings. Changes in gene expression (mean and standard error of mean) are shown relative to <i>GAPDH</i>. <i>HC</i>, central airways in health; <i>HP</i>, peripheral airways in health; <i>SC</i>, central airways in severe asthma; <i>SP</i>, peripheral airways in severe asthma; <i>*</i>, p-value < 0.05.</p

Interaction analysis to evaluate the effects of disease and lung airway region on gene expression.

<p>Log₂ intensities are plotted and significance of interaction is depicted by: <i>DR</i>, interaction between disease and lung airway region; <i>D</i>, main effect of disease; <i>R</i>, main effect of region; p-values <i>*</i> < 0.05, <i>**</i> < 0.01, *** <0.001, **** <0.0001; <i>ns</i>, not significant.</p

Schematic depicting the conclusions from the study.

<p>The main findings along with the numbers of differentially expressed genes are listed for each comparison. <i>PA</i>, peripheral airways; <i>ns</i>, not significant.</p

Altered Epithelial Gene Expression in Peripheral Airways of Severe Asthma

<div><p>Management of severe asthma remains a challenge despite treatment with glucocorticosteroid therapy. The majority of studies investigating disease mechanisms in treatment-resistant severe asthma have previously focused on the large central airways, with very few utilizing transcriptomic approaches. The small peripheral airways, which comprise the majority of the airway surface area, remain an unexplored area in severe asthma and were targeted for global epithelial gene expression profiling in this study. Differences between central and peripheral airways were evaluated using transcriptomic analysis (Affymetrix HG U133 plus 2.0 GeneChips) of epithelial brushings obtained from severe asthma patients (N = 17) and healthy volunteers (N = 23). Results were validated in an independent cohort (N = 10) by real-time quantitative PCR. The IL-13 disease signature that is associated with an asthmatic phenotype was upregulated in severe asthmatics compared to healthy controls but was predominantly evident within the peripheral airways, as were genes related to mast cell presence. The gene expression response associated with glucocorticosteroid therapy (i.e. <i>FKBP5</i>) was also upregulated in severe asthmatics compared to healthy controls but, in contrast, was more pronounced in central airways. Moreover, an altered epithelial repair response (e.g. <i>FGFBP1</i>) was evident across both airway sites reflecting a significant aspect of disease in severe asthma unadressed by current therapies. A transcriptomic approach to understand epithelial activation in severe asthma has thus highlighted the need for better-targeted therapy to the peripheral airways in severe asthma, where the IL-13 disease signature persists despite treatment with currently available therapy.</p></div

Peripheral airways versus central airways, in healthy volunteers and in severe asthmatics.

<p><b>A.</b><i>Greater expression</i>, genes with a greater expression in peripheral airways compared to central airways; <i>Lesser expression</i>, genes with a lesser expression in peripheral airways compared to central airways. <b>B.</b> Heatmap depicting unsupervised hierarchical clustering (Pearson complete) of modules identified using SSIM. Expression values of genes within each module were averaged and scaled to indicate the number of standard deviations above (red) or below (blue) the mean, denoted as row Z-score. <i>PA</i>, peripheral airways; <i>SA</i>, severe asthmatics; <i>ns</i>, not significant. <b>C.</b> Fold changes for mast cell proteases obtained by differential gene expression analysis. <b>D.</b> RT-qPCR validation of differential gene expression analysis of mast cell proteases. Changes in gene expression (mean and standard error of mean) are shown relative to <i>GAPDH</i>. <i>HC</i>, central airways in health; <i>HP</i>, peripheral airways in health; <i>SC</i>, central airways in severe asthma; <i>SP</i>, peripheral airways in severe asthma; <i>*</i>, p-value < 0.05.</p

Heatmap depicting heterogeneity in severe asthma samples.

<p>Unsupervised hierarchical clustering (Euclidean complete) was performed on log₂ fold change values for severe asthmatics with paired samples from both central and peripheral airways (N = 11 pairs). Red and blue represent greater and lower expression in the peripheral airways compared to the central airways, respectively. Severe asthma patients have been assigned a letter from A through K, arbitrarily.</p

Values measured by digital PCR do not vary with cycle number.

<p>Plasmid templates were emulsified into droplets and thermally cycled for 30 to 50 cycles before analysis. No significant differences in measured <i>pol</i> (<b>A</b>) or 2-LTR (<b>B</b>) copy numbers were observed over this range of cycling times. No positive events were observed after 20 cycles (not shown). Similar results were obtained using dilutions of infected CD4+ T cells into uninfected PBMC (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055943#pone.0055943.s001" target="_blank">Fig. S.1</a>). Error bars indicate the observed standard deviation between wells.</p

Effect of sequence variation.

<p>Patient isolates with previously determined <i>pol</i> sequences that differ from the consensus primer/probe set in at least two positions were analyzed by ddPCR and by qPCR. Both assays were conducted in parallel using the mismatched consensus primer/probe set and a patient-specific matched primer/probe set. Use of consensus primers and probe resulted in an underestimate of copy number by one to two log₁₀ by qPCR, with complete loss of detection in the extreme case of 5 total mismatched bases. The underestimate was largely mitigated (mean 57% reduction in log₁₀ copy number change) by ddPCR in all cases. These 4 cases reflect the most extreme mismatches observed in 84 patients, suggesting that sequence variation is unlikely to significantly impact ddPCR assay results in clinical studies. All samples analyzed were HIV-1 subtype B.</p

Correlation of ddPCR and qPCR measurements.

<p>(<b>a</b>) Pol copy numbers measured by ddPCR and qPCR were significantly correlated (Pearson R² = 0.64, slope = 0.98±0.08). The correlation weakened at low copy numbers, primarily due to a rapid increase in the variance of the qPCR assay (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055943#pone.0055943.s003" target="_blank">Fig. S3</a> (a)). For copy numbers measured in the bottom tertile (<230 HIV DNA copies/10⁶ cells) by ddPCR, the correlation was not significant (R² = 0.08, P = 0.12). In the central tertile, the correlation was weak but significant (R² = 0.15, P = 0.03). In the top tertile, the correlation was strong (R² = 0.53, P<0.0001). (<b>b</b>) 2-LTR copy numbers measured by both methods were significantly but weakly (R² = 0.14, P = 0.002) correlated.</p