Relationship of Small Airway Chymase-Positive Mast Cells and Lung Function in Severe. Asthma

Transcription

1 Relationship of Small Airway Chymase-Positive Mast Cells and Lung Function in Severe Asthma Silvana Balzar, M.D., Hong Wei Chu, M.D., Matthew Strand, Ph.D, Sally Wenzel, M.D. Online Data Supplement

2 METHODS Tissue Acquisition As a part of differential diagnostic procedures, twenty subjects referred to the National Jewish Medical and Research Center for evaluation/treatment of severe, steroid dependent asthma underwent bronchoscopic biopsy or, in two subjects, thoracoscopic/open lung biopsy. In each subject tissue samples of proximal airway (by endobronchial biopsy, EBBX ) and distal lung (by transbronchial or surgical biopsy) were obtained concurrently. All studies were done for clinical reasons. The patients understood that additional biopsies were obtained for research purposes. Tissue Processing and Immunostaining All tissue samples were acetone-fixed and embedded in glycol methacrylate. Serial 2µm sections were immunostained for markers of T-lymphocytes (CD3), monocyte/macrophage (CD68), neutrophil elastase, mast cell tryptase (all from Dako, Carpinteria, CA), mast cell chymase (Chemicon International, Temecula, CA) and eosinophil cationic protein (EG2, Pharmacia, Uppsala, Sweden), using Vectastain Elite ABC Kits (Vector Laboratories, Burlingame, CA), as previously described (E1). Morphometric Analysis Alveolar attachments was the region of alveolar tissue structurally connected to small airway. It was analyzed in TBBX that contained small airway tissue and in surgical

3 tissue samples. In TBBX with small airway tissue present, all of the small amount of alveolar tissue was considered to be alveolar attachments region. In large tissue samples (surgical tissue and transplant tissue) alveolar attachments region was selected within the tissue area visible at 100x magnification, including small airway. A picture of that area was taken and area of alveolar tissue extending from the small airway outer wall toward periphery up to two visual fields at 400x magnification, devoid of bleeding, blood vessels or damage, was outlined for analysis. Positively-stained nucleated cells were counted in the previously defined areas of each lung compartment, excluding blood vessels, mucous glands and areas of damage or bleeding. The tissue area was measured using computerized imaging system and Scion Image software (National Institute of Health, Bethesda, MD). Tissue analysis could not (overall) be conducted in a blinded manner due to the differing morphological features (endobronchial vs. transbronchial biopsies from severe asthmatics) and size (biopsies from severe asthmatics vs. whole lung tissue samples from normal controls) of the tissue. However, the observer (SB) was blinded to all lung function measurements. The coefficient of variation in cell counts by the same observer or two different observers for the same sections was 7%. Lung Function Testing Lung physiology parameters analyzed included forced expiratory volume in one second (FEV 1 ), forced vital capacity (FVC), FEV 1 /FVC, FVC/slow vital capacity (FVC/SVC), residual volume measured by plethysmography (RV) and forced expiratory flow at 25-

4 75% of FVC (FEF 25-75% ). All values, except the FEV1/FVC and the FVC/SVC, were expressed as a percent of predicted value. All physiologic tests were performed in the National Jewish Center s pulmonary physiology unit within one week preceding biopsy using standard operating procedures. Statistical Analysis The inflammatory cell counts and percentages were compared between the five lung regions using repeated measures analyses, since each subject had as many as five repeated measures of each specific marker, one for each region. The analyses were carried out with SAS, Proc Mixed (E2). To facilitate the analysis of data that were not normally distributed, the values were transformed to the natural log scale. When an overall significant difference was found between regions for a particular variable, interregion comparisons were made using the Tukey-Kramer procedure. After analysis, means and mean±se s were transformed from the log scale back to the original scale for presentation. Consequently, standard errors from the estimated mean values are somewhat larger on the positive side than the negative side. Unless otherwise stated, values in the text are reported as [mean (mean±se)]. It should be noted that the tests comparing regions involve standard errors that are based on within-subject differences between regions. However, reported (and graphed) standard errors are for individual regions. Thus, the reported p-values cannot be directly obtained from the means and standard errors given in the text. Spearman s correlations between lung function variables and inflammatory cell counts and percentages were determined for each lung region separately. Due to the large

5 number of correlations performed (78 per region), correlations that remained significant after applying the false discovery rate (FDR) procedure were determined (E3). The FDR procedure controls the expected fraction of null hypothesis rejections that are mistaken. The false discovery rate was fixed at 0.10 within each region. Correlations that were significant before applying the FDR procedure (unadjusted) were distinguished from those that remained significant after applying the procedure. All reported p-values are based on 2-sided tests. Subject Characteristics Subjects with severe asthma had FEV 1 of < 70% predicted on more than one occasion over the previous year; used 10mg/d of prednisone or equivalent for at least 50% of the previous year while taking other standard asthma medications and required > 2 urgent care interventions for asthma in the previous year (E1). REFERENCES E1 Wenzel SE, Schwartz LB, Langmack EL, et al. Evidence that severe asthma can be divided pathologically into two inflammatory subtypes with distinct physiologic and clinical characteristics. Am J Respir Crit Care Med 1999;160: E2 SAS/STAT User's Guide, Version 8. Cary, NC: SAS Institute, E3 Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995;57: