822 LETTERS TO THE EDITOR
J ALLERGY CLIN IMMUNOL MARCH 2015
subjects both crudely and after adjustment for TLC percent pre_ .01). dicted (P < Our results demonstrate greater albuterol response on small airways parameters in obese compared to non-obese individuals, in the absence of history or symptoms of asthma. These data support our hypothesis that peripheral airways dysfunction in obesity reflects exaggerated bronchomotor tone. Our adjusted analysis showed that these findings cannot be attributed to reduced TLC in the obese. It is possible that with a larger sample size we would have been able to detect large airways parameters differences between obese and non-obese subjects, but the important finding is that, even with our modest sample size, small airways parameters were affected by obesity. The presence of asymptomatic airways hyperresponsiveness in one-third of obese subjects does not drive our findings, because re-analysis excluding their data did not alter the outcome. Airways hyperresponsiveness is not a surprising finding considering the known abnormal response to deep inspiration in obesity.4 Notably, we found concordance between hyperresponsiveness and atopy, in that 3 of 4 subjects with hyperresponsiveness had positive skin tests, and these 3 subjects represented 3 of the 4 with positive skin tests. This raises the possibility that, despite the lack of upper or lower airway symptoms, this subgroup of obese individuals may represent a distinct phenotype with increased diathesis for development of asthma. The mechanism for increased bronchomotor tone in obesity is unknown, but several hypotheses are possible. Obese subjects may have decreased breathing amplitude leading to stiffer small airways, which, in turn, would reduce the bronchodilatory effects of sighing and lead to increased bronchomotor tone. However, we did not measure tidal volumes in this study to support this explanation. It is also possible that adipokines (ie, leptin), which are increased in obesity,5 may have direct effects on bronchial diameter, independent of airway inflammation.7 Leptin dysfunction in obesity may increase parasympathetic signaling, leading to increased bronchomotor tone.7 More recent evidence suggests that this may be modulated by insulin.8 Our findings suggest that the frequent co-existence of obesity and asthma may be partially explained by peripheral airways dysfunction in obesity that could synergize with asthma-related abnormalities. We believe that further investigation will offer major insight into the relationship of asthma and obesity, but it may also benefit individuals with obesity alone, whose increased small airways resistance may influence their functionality. Alpa G. Desai, MDa Alkis Togias, MDb Clyde Schechter, MDc Beth Fisher, MDd Aimee Parow, MDd Gwen Skloot, MDd From athe Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, State University of New York at Stony Brook, Stony Brook, NY; bthe National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Md; cthe Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, NY; and dthe Division of Pulmonary, Critical Care, Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. E-mail: [email protected]. Disclaimer: The opinions expressed in this article are the authors’ own and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government.
This research was funded by the Vivian Richenthal Research Institute of Pulmonary/ Critical Care Medicine. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest. REFERENCES 1. Dixon A, Holguin F, Sood A, Salome C, Pratley R, Beuther D, et al. An official American Thoracic Society workshop report: obesity and asthma. Proc Am Thorac Soc 2010;7:325-35. 2. Newson RB, Jones M, Forsberg B, Janson C, Bossios A, Dahlens E, et al. The association of asthma, nasal allergies, and positive skin prick tests with obesity, leptin, and adiponectin. Clin Exp Allergy 2014;44:250-60. 3. Beuther D, Sutherland ER. Overweight, obesity, and incident asthma: a metaanalysis of prospective epidemiologic studies. Am J Respir Crit Care Med 2007; 175:661-6. 4. Skloot G, Schechter C, Desai A, Togias A. Impaired response to deep inspiration in obesity. J Appl Physiol 2011;111:726-34. 5. Sideleva O, Suratt BT, Black KE, Tharp WG, Pratley RE, Forgione P, et al. Obesity and asthma: an inflammatory disease of adipose tissue not the airway. Am J Respir Crit Care Med 2012;186:598-605. 6. Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung function tests. Eur Respir J 2005;26: 948-68. 7. Arteaga-Solis E, Zee T, Emala CW, Vinson C, Wess J, Karsenty G. Inhibition of leptin regulation of parasympathetic signaling as a cause of extreme body weight-associated asthma. Cell Metab 2013;17:35-48. 8. Nie Z, Jacoby DB, Fryer AD. Hyperinsulinemia potentiates airway responsiveness to parasympathetic nerve stimulation in obese rats. Am J Respir Cell Mol Biol 2014;51:251-61. Available online October 31, 2014. http://dx.doi.org/10.1016/j.jaci.2014.09.016
High blood eosinophil counts predict sputum eosinophilia in patients with severe asthma To the Editor: In asthmatic patients sputum eosinophilia predicts steroid response1 and identifies an inflammatory phenotype that responds to anti-TH2 biologic agents, such as mepolizumab.2 However, sputum induction is not without risk in patients with severe asthma nor is it always successful, and processing requires expertise and is time consuming. A recent study from the Severe Asthma Research Program analyzed same-day blood and sputum eosinophil counts, concluding that the former cannot be reliably used to predict the latter.3 Cutoffs to define sputum eosinophilia of 2% or greater and blood eosinophilia of 0.3 3 109 cells/L or greater were chosen. The upper limit of the normal range for sputum eosinophil counts in the healthy (nonasthmatic) population is 1.9% or less,4 and therefore 2% seems appropriate, especially where most patients are already treated with eosinophil-suppressing corticosteroids. For blood eosinophil counts, however, a higher cutoff of normality of greater than 0.45 3 109 cells/L is more commonly used, both in our hospital and in the literature, although this is by no means universal.5 Visual inspection of the graphic data provided in the article by Hastie et al3 suggests that this higher cutoff might have a higher positive predictive value for sputum eosinophilia and potentially could be used to classify the airway inflammatory phenotype in a subgroup of patients with severe asthma and hence remove the requirement for sputum induction and processing in some patients. We run a tertiary severe asthma service and routinely analyze sputum cell counts to help characterize the airway status of newly referred patients and to facilitate management decisions in returning patients. Blood is often collected on the same visit, and therefore we investigated whether in our cohort blood
LETTERS TO THE EDITOR 823
J ALLERGY CLIN IMMUNOL VOLUME 135, NUMBER 3
FIG 1. Scatter plot of blood eosinophils (3 109 cells/L) against sputum eosinophils (as a percentage), with cutoffs shown for sputum eosinophilia of 2% or greater (dashed line) and blood eosinophil counts of 0.15 3 109 cells/L or greater (dotted line), 0.3 3 109 cells/L or greater (dashed line), and greater than 0.45 3 109 cells/L (solid line). Open circles represent samples from patients receiving moderate-dose steroids, and solid circles _10 mg/d prednisolone, 80 mg of intramuscular represent samples from those receiving high-dose steroids (> _2000 mg/d beclomethasone or equivalent). triamcinolone within the previous month, or >
TABLE I. Performance characteristics (percentages) for prediction of at least 2% sputum eosinophilia in patients with moderate and severe asthma by using blood eosinophil count cutoffs of 0.15, 0.3, and 0.45 3 109 cells/L Blood eosinophil cutoff (3 109 cells/L)
Sensitivity Specificity Positive predictive value Negative predictive value
_0.15 >
_0.30 >
>0.45
77.6 53.3 45.2 82.8
59.7 84.4 65.6 80.9
49.3 97.0 89.2 79.4
eosinophilia could predict sputum eosinophilia and whether a higher cutoff could increase the clinical utility of the test. We collected data from our clinical database of patients attending the Manchester Severe Asthma Service between 2006 and 2013. All patients were receiving at least 1000 mg/d inhaled beclomethasone or equivalent with or without 5 mg of oral prednisone and with or without intramuscular triamcinolone. Sputum was collected either as a spontaneous sample or induced by using hypertonic saline and processed, as previously described.6 A venous blood sample was collected and analyzed during the same episode. For practical reasons, blood samples were sometimes collected up to 2 days on either side of the sputum visit.
Data presented are descriptive, with performance characteristics also reported for the ability of blood eosinophil counts of 0.15 3 109 cells/L or greater, 0.3 3 109 cells/L or greater, and greater than 0.45 3 109 cells/L to predict sputum eosinophilia of 2% or more. Data were analyzed with SPSS software (version 20; SPSS, Chicago, Ill). Complete data sets were available from 163 patients providing samples on 202 sample days. Blood samples were collected on the same day as the sputum sample on all but 15 occasions. Demographic details (at the index visits where patients provided multiple samples) were mean age of 46.6 years (SD, 12.2 years), 56% female sex, 63% receiving systemic corticosteroids, 9% receiving second-line systemic immunosuppressants, and mean inhaled beclomethasone dipropionate dose equivalent of 2293 mg/d (SD, 1158 mg/d). Blood and sputum eosinophil counts correlated (Spearman correlation 5 0.493, P < .001). Values for each of the 202 bloodsputum pairs are plotted in Fig 1, and a receiver operating characteristic curve with coordinates is presented in Fig E1 and Table E1 in this article’s Online Repository at www.jacionline.org. Changing the threshold from 0.3 to 0.45 3 109 cells/L improved the positive predictive value for sputum eosinophilia from 65.6% to 89.2% and the specificity from 84.4% to 97%. There was a marginal loss of sensitivity/negative predictive value (Table I). A blood eosinophil cutoff of 0.15 3 109 cells/L had a positive predictive value of less than 50%.
824 LETTERS TO THE EDITOR
J ALLERGY CLIN IMMUNOL MARCH 2015
In our cohort of patients with severe asthma, the majority receiving very high doses of inhaled or systemic corticosteroids, a blood eosinophil count of greater than 0.45 3 109 cells/L can correctly predict sputum eosinophilia in 9 of 10 cases. We have included only patients with severe asthma in our study, and therefore we believe our results are important because these are the patients who will be considered for novel TH2-targeting biologic agents. The search for biomarkers of airway inflammation has been made more urgent by the advance of novel therapies that act specifically by targeting this inflammation. To this end, recent studies that aimed to investigate the potential benefit of mepolizumab in patients with eosinophilic asthma identified patients by using blood eosinophil cutoffs as low as 0.15 3 109 cells/L.7,8 As demonstrated both here and in the article from the Severe Asthma Research Program group,4 this cutoff would include many patients who in fact do not have contemporaneous sputum eosinophilia (more than half in this study) and therefore potentially would not be in the group of patients who could benefit from treatment. The consequence of this in a trial of a biologic agent is that the magnitude of benefit could be underestimated or even missed, as happened previously when mepolizumab was trialed in unselected patients.9 The other potential consequence of using blood eosinophil counts as a surrogate for sputum is the very high risk of false-negative results; from our data, approximately 1 in 5 patients without blood eosinophilia had airway eosinophilia and hence could be missed by using this selection method. Choosing a simple and universally available biomarker (blood eosinophil counts) is attractive, but in this case does not lead to a personalized medicine approach. In conclusion, we have shown that using a cutoff of 0.45 3 109 cells/L for blood eosinophilia can usefully predict airway eosinophilia in patients with severe asthma receiving high levels of treatment. However, we agree with Hastie et al3 that lower cutoffs are not useful. We would propose that study design for novel antieosinophil therapies could use this higher cutoff to investigate the effect of these therapies but that patients should also be included with airway but not blood eosinophilia, as previously described.8 In the meantime, more work needs to be done to develop useful minimally invasive and accurate surrogate markers for airway inflammation, including composite biomarkers comprising, for example, exhaled nitric oxide and serum periostin levels together with blood eosinophil counts. Stephen J. Fowler, MDa,b Ga€ el Tavernier, PhDa Robert Niven, MDa From athe University of Manchester, Manchester Academic Health Science Centre, and NIHR Translational Research Facility in Respiratory Medicine, University Hospital of South Manchester, Manchester, United Kingdom, and bLancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom. E-mail: stephen. [email protected]. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest. REFERENCES 1. Green RH, Brightling CE, McKenna S, Hargadon B, Parker D, Bradding P, et al. Asthma exacerbations and sputum eosinophil counts: a randomised controlled trial. Lancet 2002;360:1715-21. 2. Nair P, Pizzichini MM, Kjarsgaard M, Inman MD, Efthimiadis A, Pizzichini E, et al. Mepolizumab for prednisone-dependent asthma with sputum eosinophilia. N Engl J Med 2009;360:985-93.
3. Hastie AT, Moore WC, Li H, Rector BM, Ortega VE, Pascual RM, et al. Biomarker surrogates do not accurately predict sputum eosinophil and neutrophil percentages in asthmatic subjects. J Allergy Clin Immunol 2013;132:72-80. 4. Reddel HK, Taylor DR, Bateman ED, Boulet LP, Boushey HA, Busse WW, et al. An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice. Am J Respir Crit Care Med 2009;180:59-99. 5. Fulkerson PC, Rothenberg ME. Targeting eosinophils in allergy, inflammation and beyond. Nat Rev Drug Discov 2013;12:117-29. 6. Pizzichini E, Pizzichini MM, Efthimiadis A, Hargreave FE, Dolovich J. Measurement of inflammatory indices in induced sputum: effects of selection of sputum to minimize salivary contamination. Eur Respir J 1996;9:1174-80. 7. Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl R, Keene ON, et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial. Lancet 2012;380:651-9. 8. Ortega HG, Liu MC, Pavord ID, Brusselle GG, FitzGerald JM, Chetta A, et al. Mepolizumab treatment in patients with severe eosinophilic asthma. N Engl J Med 2014;371:1198-207. 9. Flood-Page P, Swenson C, Faiferman I, Matthews J, Williams M, Brannick L, et al. A study to evaluate safety and efficacy of mepolizumab in patients with moderate persistent asthma. Am J Respir Crit Care Med 2007;176:1062-71. Available online October 30, 2014. http://dx.doi.org/10.1016/j.jaci.2014.09.034
Vitamin D enhances production of soluble ST2, inhibiting the action of IL-33 To the Editor: Vitamin D insufficiency is an environmental factor that has been strongly associated with asthma and its severity.1 The genes IL33 and IL1RL1 have been repeatedly identified as predisposing to asthma risk in genome-wide association studies.2 IL-33 is an alarmin cytokine that acts on multiple pulmonary cell types, including TH2 lymphocytes, mast cells, and innate lymphoid cells, to promote TH2-type cytokine secretion and airway inflammatory responses of the kind observed in asthmatic patients.3,4 The receptor for IL-33 is encoded by IL1RL1; differential splicing of the gene can produce a functional membrane-bound receptor (ST2L) or a soluble decoy receptor (sST2).5 Therefore we investigated whether IL1RL1 is regulated by vitamin D in cells relevant to asthma. We did this first by measuring gene expression by means of quantitative real-time PCR with 2 different TaqMan probe sets: Hs01073300, which detects mRNA splice variants encoding both the membrane-bound and soluble receptors (the total mRNA for IL1RL1), and Hs00249389, which detects mRNA only for the splice variant encoding the membrane-bound receptor ST2L (Fig 1, A). Methods are provided in this article’s Online Repository at www.jacionline.org. Both probe sets display similar efficiency of amplification (data not shown). Human primary bronchial epithelial cells (HBECs), CD4 lymphocytes, CD8 lymphocytes, eosinophils, and LUVA mast cells were cultured in the presence or absence of 1a,25dihydroxyvitamin D3 (1,25[OH]D3), the active form of vitamin D (Fig 1, B-D, and see Fig E1, A and B, in this article’s Online Repository at www.jacionline.org). Addition of 1,25(OH)D3 significantly increased the total number of IL1RL1 mRNA transcripts expressed by HBECs and CD4 and CD8 lymphocytes, as measured by using the Hs01073300 probe set. However, 1,25(OH)D3 did not significantly increase expression of IL1RL1 mRNA transcripts by primary eosinophils and LUVA mast cells, despite it significantly increasing expression of the Ó 2014 The Authors. Published by Elsevier, Inc. on behalf of the Academy of Allergy, Asthma & Immunology. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/3.0/).
824.e1 LETTERS TO THE EDITOR
J ALLERGY CLIN IMMUNOL MARCH 2015
1.0
1 - Specificity
0.8
0.6
0.4
0.2
0.0 0.0
0.2
0.4
0.6
0.8
1.0
Sensitivity FIG E1. Receiver operating characteristic curve for use of blood eosinophil counts to predict sputum eosinophil values of at least 2%. The area under the receiver operating characteristic curve was 0.79 (95% CI, 0.72-0.86; P < .001).
LETTERS TO THE EDITOR 824.e2
J ALLERGY CLIN IMMUNOL VOLUME 135, NUMBER 3
TABLE E1. Coordinates of the receiver operating characteristics curve in Fig E1 showing sensitivity and 1 2 specificity for blood eosinophil counts to predict sputum eosinophils of at least 2% (eg, blood eosinophil counts of at least 0.46 3 109 cells/L has a sensitivity of 49.3% and a specificity of 97.0% for sputum eosinophilia) Blood eosinophil cutoff (3 109 cells/L)
0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.29 0.31 0.33 0.34 0.35 0.36 0.38 0.39 0.40 0.42 0.43 0.44 0.46 0.47 0.49 0.51 0.52 0.53 0.54 0.56 0.59 0.62 0.64 0.66 0.67 0.70 0.74 0.78
Sensitivity
1 2 Specificity
1.000 0.970 0.955 0.955 0.940 0.940 0.925 0.910 0.866 0.836 0.836 0.821 0.806 0.791 0.776 0.776 0.776 0.776 0.761 0.746 0.746 0.716 0.716 0.672 0.672 0.642 0.627 0.612 0.597 0.597 0.582 0.582 0.582 0.567 0.552 0.552 0.522 0.522 0.507 0.493 0.493 0.478 0.463 0.448 0.433 0.433 0.403 0.373 0.358 0.343 0.313 0.299 0.284 0.254 0.239 0.224
1.000 0.933 0.911 0.881 0.793 0.756 0.696 0.667 0.644 0.622 0.600 0.541 0.511 0.504 0.489 0.467 0.430 0.363 0.341 0.296 0.267 0.267 0.244 0.230 0.215 0.200 0.178 0.178 0.163 0.156 0.133 0.111 0.089 0.081 0.074 0.059 0.059 0.052 0.044 0.044 0.030 0.030 0.030 0.030 0.030 0.022 0.022 0.022 0.015 0.015 0.015 0.007 0.007 0.007 0.007 0.007 (Continued)
TABLE E1. (Continued ) Blood eosinophil cutoff (3 109 cells/L)
0.81 0.86 0.89 0.92 0.96 0.99 1.01 1.04 1.08 1.15 1.21 1.31 1.80 3.22
Sensitivity
1 2 Specificity
0.209 0.209 0.194 0.164 0.149 0.134 0.119 0.104 0.090 0.060 0.045 0.030 0.015 0.000
0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
J ALLERGY CLIN IMMUNOL MARCH 2015
subjects both crudely and after adjustment for TLC percent pre_ .01). dicted (P < Our results demonstrate greater albuterol response on small airways parameters in obese compared to non-obese individuals, in the absence of history or symptoms of asthma. These data support our hypothesis that peripheral airways dysfunction in obesity reflects exaggerated bronchomotor tone. Our adjusted analysis showed that these findings cannot be attributed to reduced TLC in the obese. It is possible that with a larger sample size we would have been able to detect large airways parameters differences between obese and non-obese subjects, but the important finding is that, even with our modest sample size, small airways parameters were affected by obesity. The presence of asymptomatic airways hyperresponsiveness in one-third of obese subjects does not drive our findings, because re-analysis excluding their data did not alter the outcome. Airways hyperresponsiveness is not a surprising finding considering the known abnormal response to deep inspiration in obesity.4 Notably, we found concordance between hyperresponsiveness and atopy, in that 3 of 4 subjects with hyperresponsiveness had positive skin tests, and these 3 subjects represented 3 of the 4 with positive skin tests. This raises the possibility that, despite the lack of upper or lower airway symptoms, this subgroup of obese individuals may represent a distinct phenotype with increased diathesis for development of asthma. The mechanism for increased bronchomotor tone in obesity is unknown, but several hypotheses are possible. Obese subjects may have decreased breathing amplitude leading to stiffer small airways, which, in turn, would reduce the bronchodilatory effects of sighing and lead to increased bronchomotor tone. However, we did not measure tidal volumes in this study to support this explanation. It is also possible that adipokines (ie, leptin), which are increased in obesity,5 may have direct effects on bronchial diameter, independent of airway inflammation.7 Leptin dysfunction in obesity may increase parasympathetic signaling, leading to increased bronchomotor tone.7 More recent evidence suggests that this may be modulated by insulin.8 Our findings suggest that the frequent co-existence of obesity and asthma may be partially explained by peripheral airways dysfunction in obesity that could synergize with asthma-related abnormalities. We believe that further investigation will offer major insight into the relationship of asthma and obesity, but it may also benefit individuals with obesity alone, whose increased small airways resistance may influence their functionality. Alpa G. Desai, MDa Alkis Togias, MDb Clyde Schechter, MDc Beth Fisher, MDd Aimee Parow, MDd Gwen Skloot, MDd From athe Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, State University of New York at Stony Brook, Stony Brook, NY; bthe National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Md; cthe Department of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, NY; and dthe Division of Pulmonary, Critical Care, Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. E-mail: [email protected]. Disclaimer: The opinions expressed in this article are the authors’ own and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government.
This research was funded by the Vivian Richenthal Research Institute of Pulmonary/ Critical Care Medicine. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest. REFERENCES 1. Dixon A, Holguin F, Sood A, Salome C, Pratley R, Beuther D, et al. An official American Thoracic Society workshop report: obesity and asthma. Proc Am Thorac Soc 2010;7:325-35. 2. Newson RB, Jones M, Forsberg B, Janson C, Bossios A, Dahlens E, et al. The association of asthma, nasal allergies, and positive skin prick tests with obesity, leptin, and adiponectin. Clin Exp Allergy 2014;44:250-60. 3. Beuther D, Sutherland ER. Overweight, obesity, and incident asthma: a metaanalysis of prospective epidemiologic studies. Am J Respir Crit Care Med 2007; 175:661-6. 4. Skloot G, Schechter C, Desai A, Togias A. Impaired response to deep inspiration in obesity. J Appl Physiol 2011;111:726-34. 5. Sideleva O, Suratt BT, Black KE, Tharp WG, Pratley RE, Forgione P, et al. Obesity and asthma: an inflammatory disease of adipose tissue not the airway. Am J Respir Crit Care Med 2012;186:598-605. 6. Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung function tests. Eur Respir J 2005;26: 948-68. 7. Arteaga-Solis E, Zee T, Emala CW, Vinson C, Wess J, Karsenty G. Inhibition of leptin regulation of parasympathetic signaling as a cause of extreme body weight-associated asthma. Cell Metab 2013;17:35-48. 8. Nie Z, Jacoby DB, Fryer AD. Hyperinsulinemia potentiates airway responsiveness to parasympathetic nerve stimulation in obese rats. Am J Respir Cell Mol Biol 2014;51:251-61. Available online October 31, 2014. http://dx.doi.org/10.1016/j.jaci.2014.09.016
High blood eosinophil counts predict sputum eosinophilia in patients with severe asthma To the Editor: In asthmatic patients sputum eosinophilia predicts steroid response1 and identifies an inflammatory phenotype that responds to anti-TH2 biologic agents, such as mepolizumab.2 However, sputum induction is not without risk in patients with severe asthma nor is it always successful, and processing requires expertise and is time consuming. A recent study from the Severe Asthma Research Program analyzed same-day blood and sputum eosinophil counts, concluding that the former cannot be reliably used to predict the latter.3 Cutoffs to define sputum eosinophilia of 2% or greater and blood eosinophilia of 0.3 3 109 cells/L or greater were chosen. The upper limit of the normal range for sputum eosinophil counts in the healthy (nonasthmatic) population is 1.9% or less,4 and therefore 2% seems appropriate, especially where most patients are already treated with eosinophil-suppressing corticosteroids. For blood eosinophil counts, however, a higher cutoff of normality of greater than 0.45 3 109 cells/L is more commonly used, both in our hospital and in the literature, although this is by no means universal.5 Visual inspection of the graphic data provided in the article by Hastie et al3 suggests that this higher cutoff might have a higher positive predictive value for sputum eosinophilia and potentially could be used to classify the airway inflammatory phenotype in a subgroup of patients with severe asthma and hence remove the requirement for sputum induction and processing in some patients. We run a tertiary severe asthma service and routinely analyze sputum cell counts to help characterize the airway status of newly referred patients and to facilitate management decisions in returning patients. Blood is often collected on the same visit, and therefore we investigated whether in our cohort blood
LETTERS TO THE EDITOR 823
J ALLERGY CLIN IMMUNOL VOLUME 135, NUMBER 3
FIG 1. Scatter plot of blood eosinophils (3 109 cells/L) against sputum eosinophils (as a percentage), with cutoffs shown for sputum eosinophilia of 2% or greater (dashed line) and blood eosinophil counts of 0.15 3 109 cells/L or greater (dotted line), 0.3 3 109 cells/L or greater (dashed line), and greater than 0.45 3 109 cells/L (solid line). Open circles represent samples from patients receiving moderate-dose steroids, and solid circles _10 mg/d prednisolone, 80 mg of intramuscular represent samples from those receiving high-dose steroids (> _2000 mg/d beclomethasone or equivalent). triamcinolone within the previous month, or >
TABLE I. Performance characteristics (percentages) for prediction of at least 2% sputum eosinophilia in patients with moderate and severe asthma by using blood eosinophil count cutoffs of 0.15, 0.3, and 0.45 3 109 cells/L Blood eosinophil cutoff (3 109 cells/L)
Sensitivity Specificity Positive predictive value Negative predictive value
_0.15 >
_0.30 >
>0.45
77.6 53.3 45.2 82.8
59.7 84.4 65.6 80.9
49.3 97.0 89.2 79.4
eosinophilia could predict sputum eosinophilia and whether a higher cutoff could increase the clinical utility of the test. We collected data from our clinical database of patients attending the Manchester Severe Asthma Service between 2006 and 2013. All patients were receiving at least 1000 mg/d inhaled beclomethasone or equivalent with or without 5 mg of oral prednisone and with or without intramuscular triamcinolone. Sputum was collected either as a spontaneous sample or induced by using hypertonic saline and processed, as previously described.6 A venous blood sample was collected and analyzed during the same episode. For practical reasons, blood samples were sometimes collected up to 2 days on either side of the sputum visit.
Data presented are descriptive, with performance characteristics also reported for the ability of blood eosinophil counts of 0.15 3 109 cells/L or greater, 0.3 3 109 cells/L or greater, and greater than 0.45 3 109 cells/L to predict sputum eosinophilia of 2% or more. Data were analyzed with SPSS software (version 20; SPSS, Chicago, Ill). Complete data sets were available from 163 patients providing samples on 202 sample days. Blood samples were collected on the same day as the sputum sample on all but 15 occasions. Demographic details (at the index visits where patients provided multiple samples) were mean age of 46.6 years (SD, 12.2 years), 56% female sex, 63% receiving systemic corticosteroids, 9% receiving second-line systemic immunosuppressants, and mean inhaled beclomethasone dipropionate dose equivalent of 2293 mg/d (SD, 1158 mg/d). Blood and sputum eosinophil counts correlated (Spearman correlation 5 0.493, P < .001). Values for each of the 202 bloodsputum pairs are plotted in Fig 1, and a receiver operating characteristic curve with coordinates is presented in Fig E1 and Table E1 in this article’s Online Repository at www.jacionline.org. Changing the threshold from 0.3 to 0.45 3 109 cells/L improved the positive predictive value for sputum eosinophilia from 65.6% to 89.2% and the specificity from 84.4% to 97%. There was a marginal loss of sensitivity/negative predictive value (Table I). A blood eosinophil cutoff of 0.15 3 109 cells/L had a positive predictive value of less than 50%.
824 LETTERS TO THE EDITOR
J ALLERGY CLIN IMMUNOL MARCH 2015
In our cohort of patients with severe asthma, the majority receiving very high doses of inhaled or systemic corticosteroids, a blood eosinophil count of greater than 0.45 3 109 cells/L can correctly predict sputum eosinophilia in 9 of 10 cases. We have included only patients with severe asthma in our study, and therefore we believe our results are important because these are the patients who will be considered for novel TH2-targeting biologic agents. The search for biomarkers of airway inflammation has been made more urgent by the advance of novel therapies that act specifically by targeting this inflammation. To this end, recent studies that aimed to investigate the potential benefit of mepolizumab in patients with eosinophilic asthma identified patients by using blood eosinophil cutoffs as low as 0.15 3 109 cells/L.7,8 As demonstrated both here and in the article from the Severe Asthma Research Program group,4 this cutoff would include many patients who in fact do not have contemporaneous sputum eosinophilia (more than half in this study) and therefore potentially would not be in the group of patients who could benefit from treatment. The consequence of this in a trial of a biologic agent is that the magnitude of benefit could be underestimated or even missed, as happened previously when mepolizumab was trialed in unselected patients.9 The other potential consequence of using blood eosinophil counts as a surrogate for sputum is the very high risk of false-negative results; from our data, approximately 1 in 5 patients without blood eosinophilia had airway eosinophilia and hence could be missed by using this selection method. Choosing a simple and universally available biomarker (blood eosinophil counts) is attractive, but in this case does not lead to a personalized medicine approach. In conclusion, we have shown that using a cutoff of 0.45 3 109 cells/L for blood eosinophilia can usefully predict airway eosinophilia in patients with severe asthma receiving high levels of treatment. However, we agree with Hastie et al3 that lower cutoffs are not useful. We would propose that study design for novel antieosinophil therapies could use this higher cutoff to investigate the effect of these therapies but that patients should also be included with airway but not blood eosinophilia, as previously described.8 In the meantime, more work needs to be done to develop useful minimally invasive and accurate surrogate markers for airway inflammation, including composite biomarkers comprising, for example, exhaled nitric oxide and serum periostin levels together with blood eosinophil counts. Stephen J. Fowler, MDa,b Ga€ el Tavernier, PhDa Robert Niven, MDa From athe University of Manchester, Manchester Academic Health Science Centre, and NIHR Translational Research Facility in Respiratory Medicine, University Hospital of South Manchester, Manchester, United Kingdom, and bLancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom. E-mail: stephen. [email protected]. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest. REFERENCES 1. Green RH, Brightling CE, McKenna S, Hargadon B, Parker D, Bradding P, et al. Asthma exacerbations and sputum eosinophil counts: a randomised controlled trial. Lancet 2002;360:1715-21. 2. Nair P, Pizzichini MM, Kjarsgaard M, Inman MD, Efthimiadis A, Pizzichini E, et al. Mepolizumab for prednisone-dependent asthma with sputum eosinophilia. N Engl J Med 2009;360:985-93.
3. Hastie AT, Moore WC, Li H, Rector BM, Ortega VE, Pascual RM, et al. Biomarker surrogates do not accurately predict sputum eosinophil and neutrophil percentages in asthmatic subjects. J Allergy Clin Immunol 2013;132:72-80. 4. Reddel HK, Taylor DR, Bateman ED, Boulet LP, Boushey HA, Busse WW, et al. An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice. Am J Respir Crit Care Med 2009;180:59-99. 5. Fulkerson PC, Rothenberg ME. Targeting eosinophils in allergy, inflammation and beyond. Nat Rev Drug Discov 2013;12:117-29. 6. Pizzichini E, Pizzichini MM, Efthimiadis A, Hargreave FE, Dolovich J. Measurement of inflammatory indices in induced sputum: effects of selection of sputum to minimize salivary contamination. Eur Respir J 1996;9:1174-80. 7. Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl R, Keene ON, et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial. Lancet 2012;380:651-9. 8. Ortega HG, Liu MC, Pavord ID, Brusselle GG, FitzGerald JM, Chetta A, et al. Mepolizumab treatment in patients with severe eosinophilic asthma. N Engl J Med 2014;371:1198-207. 9. Flood-Page P, Swenson C, Faiferman I, Matthews J, Williams M, Brannick L, et al. A study to evaluate safety and efficacy of mepolizumab in patients with moderate persistent asthma. Am J Respir Crit Care Med 2007;176:1062-71. Available online October 30, 2014. http://dx.doi.org/10.1016/j.jaci.2014.09.034
Vitamin D enhances production of soluble ST2, inhibiting the action of IL-33 To the Editor: Vitamin D insufficiency is an environmental factor that has been strongly associated with asthma and its severity.1 The genes IL33 and IL1RL1 have been repeatedly identified as predisposing to asthma risk in genome-wide association studies.2 IL-33 is an alarmin cytokine that acts on multiple pulmonary cell types, including TH2 lymphocytes, mast cells, and innate lymphoid cells, to promote TH2-type cytokine secretion and airway inflammatory responses of the kind observed in asthmatic patients.3,4 The receptor for IL-33 is encoded by IL1RL1; differential splicing of the gene can produce a functional membrane-bound receptor (ST2L) or a soluble decoy receptor (sST2).5 Therefore we investigated whether IL1RL1 is regulated by vitamin D in cells relevant to asthma. We did this first by measuring gene expression by means of quantitative real-time PCR with 2 different TaqMan probe sets: Hs01073300, which detects mRNA splice variants encoding both the membrane-bound and soluble receptors (the total mRNA for IL1RL1), and Hs00249389, which detects mRNA only for the splice variant encoding the membrane-bound receptor ST2L (Fig 1, A). Methods are provided in this article’s Online Repository at www.jacionline.org. Both probe sets display similar efficiency of amplification (data not shown). Human primary bronchial epithelial cells (HBECs), CD4 lymphocytes, CD8 lymphocytes, eosinophils, and LUVA mast cells were cultured in the presence or absence of 1a,25dihydroxyvitamin D3 (1,25[OH]D3), the active form of vitamin D (Fig 1, B-D, and see Fig E1, A and B, in this article’s Online Repository at www.jacionline.org). Addition of 1,25(OH)D3 significantly increased the total number of IL1RL1 mRNA transcripts expressed by HBECs and CD4 and CD8 lymphocytes, as measured by using the Hs01073300 probe set. However, 1,25(OH)D3 did not significantly increase expression of IL1RL1 mRNA transcripts by primary eosinophils and LUVA mast cells, despite it significantly increasing expression of the Ó 2014 The Authors. Published by Elsevier, Inc. on behalf of the Academy of Allergy, Asthma & Immunology. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/3.0/).
824.e1 LETTERS TO THE EDITOR
J ALLERGY CLIN IMMUNOL MARCH 2015
1.0
1 - Specificity
0.8
0.6
0.4
0.2
0.0 0.0
0.2
0.4
0.6
0.8
1.0
Sensitivity FIG E1. Receiver operating characteristic curve for use of blood eosinophil counts to predict sputum eosinophil values of at least 2%. The area under the receiver operating characteristic curve was 0.79 (95% CI, 0.72-0.86; P < .001).
LETTERS TO THE EDITOR 824.e2
J ALLERGY CLIN IMMUNOL VOLUME 135, NUMBER 3
TABLE E1. Coordinates of the receiver operating characteristics curve in Fig E1 showing sensitivity and 1 2 specificity for blood eosinophil counts to predict sputum eosinophils of at least 2% (eg, blood eosinophil counts of at least 0.46 3 109 cells/L has a sensitivity of 49.3% and a specificity of 97.0% for sputum eosinophilia) Blood eosinophil cutoff (3 109 cells/L)
0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.29 0.31 0.33 0.34 0.35 0.36 0.38 0.39 0.40 0.42 0.43 0.44 0.46 0.47 0.49 0.51 0.52 0.53 0.54 0.56 0.59 0.62 0.64 0.66 0.67 0.70 0.74 0.78
Sensitivity
1 2 Specificity
1.000 0.970 0.955 0.955 0.940 0.940 0.925 0.910 0.866 0.836 0.836 0.821 0.806 0.791 0.776 0.776 0.776 0.776 0.761 0.746 0.746 0.716 0.716 0.672 0.672 0.642 0.627 0.612 0.597 0.597 0.582 0.582 0.582 0.567 0.552 0.552 0.522 0.522 0.507 0.493 0.493 0.478 0.463 0.448 0.433 0.433 0.403 0.373 0.358 0.343 0.313 0.299 0.284 0.254 0.239 0.224
1.000 0.933 0.911 0.881 0.793 0.756 0.696 0.667 0.644 0.622 0.600 0.541 0.511 0.504 0.489 0.467 0.430 0.363 0.341 0.296 0.267 0.267 0.244 0.230 0.215 0.200 0.178 0.178 0.163 0.156 0.133 0.111 0.089 0.081 0.074 0.059 0.059 0.052 0.044 0.044 0.030 0.030 0.030 0.030 0.030 0.022 0.022 0.022 0.015 0.015 0.015 0.007 0.007 0.007 0.007 0.007 (Continued)
TABLE E1. (Continued ) Blood eosinophil cutoff (3 109 cells/L)
0.81 0.86 0.89 0.92 0.96 0.99 1.01 1.04 1.08 1.15 1.21 1.31 1.80 3.22
Sensitivity
1 2 Specificity
0.209 0.209 0.194 0.164 0.149 0.134 0.119 0.104 0.090 0.060 0.045 0.030 0.015 0.000
0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
