Discriminatory Molecular Biomarkers of Allergic and Nonallergic Asthma and Its Severity

Selene Baos, David Calzada, Lucía Cremades-Jimeno, MªÁngeles de Pedro, Joaquín Sastre, César Picado, Joaquín Quiralte, Fernando Florido, Carlos Lahoz, Blanca Cárdaba, Selene Baos, David Calzada, Lucía Cremades-Jimeno, MªÁngeles de Pedro, Joaquín Sastre, César Picado, Joaquín Quiralte, Fernando Florido, Carlos Lahoz, Blanca Cárdaba

Abstract

Asthma is a complex disease comprising various phenotypes and endotypes, all of which still need solid biomarkers for accurate classification. In a previous study, we defined specific genes related to asthma and respiratory allergy by studying the expression of 94 genes in a population composed of 4 groups of subjects: healthy control, nonallergic asthmatic, asthmatic allergic, and nonasthmatic allergic patients. An analysis of differential gene expression between controls and patients revealed a set of statistically relevant genes mainly associated with disease severity, i.e., CHI3L1, IL-8, IL-10, MSR1, PHLDA1, PI3, and SERPINB2. Here, we analyzed whether these genes and their proteins could be potential asthma biomarkers to distinguish between nonallergic asthmatic and asthmatic allergic subjects. Protein quantification was determined by ELISA (in serum) or Western blot (in protein extracted from peripheral blood mononuclear cells or PBMCs). Statistical analyses were performed by unpaired t-test using the Graph-Pad program. The sensitivity and specificity of the gene and protein expression of several candidate biomarkers in differentiating the two groups (and the severity subgroups) was performed by receiver operating characteristic (ROC) curve analysis using the R program. The ROC curve analysis determined single genes with good sensitivity and specificity for discriminating some of the phenotypes. However, interesting combinations of two or three protein biomarkers were found to distinguish the asthma disease and disease severity between the different phenotypes of this pathology using reproducible techniques in easy-to-obtain samples. Gene and protein panels formed by single biomarkers and biomarker combinations have been defined in easily obtainable samples and by standardized techniques. These panels could be useful for characterizing phenotypes of asthma, specifically when differentiating asthma severity.

Keywords: allergy; asthma; biomarkers; gene expression; protein expression.

Figures

Figure 1
Figure 1
Mean levels of protein expression. (A) Mean levels of PHLDA1. (B) Mean levels of SERPINB2. (C) Mean levels of CHI3L1. (D) Mean levels of IL-8. (E) Mean levels of IL-10. (F) Mean levels of PI3. (G) Mean levels of POSTN. *Statistically significant comparison (P < 0.05) between the indicated groups. Protein levels of PHLDA1 and SERPINB2 were measured by Western blot in 5 NA and 6 AA subjects, and 11 NA and 11 AA, respectively. Densitometric analysis was done in individual blots (see “Materials and Methods”) using the β-actin protein for normalization. CHI3L1, IL-8, IL-10, PI3, and POSTN were quantified by ELISA in all patients included in the study population. The levels and relative expression of the proteins studied were compared among groups by unpaired t-test, using the Graph-Pad InStat 3 program. The error bars indicate the standard deviation. NA, total nonallergic asthma group; AA, total allergic asthma group.
Figure 2
Figure 2
Mean levels of protein expression by asthma severity subgroup. (A) Mean levels of PHLDA1. (B) Mean levels of SERPINB2. (C) Mean levels of CHI3L1. (D) Mean levels of IL-8. (E) Mean levels of IL-10. (F) Mean levels of PI3. (G) Mean levels of POSTN. *Statistically significant comparison (p < 0.05) between the indicated groups. **Statistically significant comparison (p < 0.005) between the indicated groups. Protein levels of PHLDA1 were measured by Western blot in 3 severe NA and 2 moderate-mild NA patients, 3 patients with severe AA, and 3 with moderate-mild AA. Protein levels of SERPINB2 were measured by Western blot in 6 severe NA and AA subjects and in 5 moderate-mild NA and AA patients. Densitometric analysis was done in individual blots (see “Materials and Methods”) using the β-actin protein for normalization. CHI3L1, IL-8, IL-10, PI3, and POSTN were quantified by ELISA in all patients studied. The levels and relative expression of the proteins studied were compared among groups by unpaired t-test, using the Graph-Pad InStat 3 program. The error bars indicate the standard deviation. S, group of subjects with severe asthma; MM, group of subjects with moderate-mild asthma.

References

    1. Hershey GKK. Is it all in our genes? The “mite-y” truth. J Allergy Clin Immunol. (2004) 113:392–4. 10.1016/j.jaci.2004.01.564
    1. Cárdaba B. Aspectos genéticos, ambientales y epigenéticos de las enfermedades alérgicas. In: Dávila González IJ, Jauregui Presa I, Olaguibel Rivera JM, Zubeldía Ortuño JM. editors. Tratado de Alergología. Madrid: Ergon; (2015). p. 81–100.
    1. Braido F, Holgate S, Canonica GW. From “blockbusters” to “biosimilars”: an opportunity for patients, medical specialists and healthcare providers. Pulm Pharmacol Ther. (2012) 25:483–6. 10.1016/j.pupt.2012.09.005
    1. Wenzel SE. Asthma phenotypes: the evolution from clinical to molecular approaches. Nat Med. (2012) 18:716–25. 10.1038/nm.2678
    1. Lötvall J, Akdis CA, Bacharier LB, Bjermer L, Casale TB, Custovic A, et al. . Asthma endotypes: a new approach to classification of disease entities within the asthma syndrome. J Allergy Clin Immunol. (2011) 127:355–60. 10.1016/j.jaci.2010.11.037
    1. Vijverberg SJ, Hilvering B, Raaijmakers JA, Lammers JW, Maitland-van der Zee AH, Koenderman L. Clinical utility of asthma biomarkers: from bench to bedside. Biologics. (2013) 7:199–210. 10.2147/BTT.S29976
    1. Peters SP. Asthma phenotypes: nonallergic (intrinsic) asthma. J Allergy Clin Immunol Pract. (2014) 2:650–2. 10.1016/j.jaip.2014.09.006
    1. Peters MC, Mekonnen ZK, Yuan S, Bhakta NR, Woodruff PG, Fahy JV. Measures of gene expression in sputum cells can identify TH2-high and TH2-low subtypes of asthma. J Allergy Clin Immunol. (2014) 133:388–94. 10.1016/j.jaci.2013.07.036
    1. Green RH, Brightling CE, Woltmann G, Parker D, Wardlaw AJ, Pavord ID. Analysis of induced sputum in adults with asthma: identification of subgroup with isolated sputum neutrophilia and poor response to inhaled corticosteroids. Thorax. (2002) 57:875–9. 10.1136/thorax.57.10.875
    1. Bullens DM, Truyen E, Coteur L, Dilissen E, Hellings PW, Dupont LJ, et al. . IL-17 mRNA in sputum of asthmatic patients: linking T cell driven inflammation and granulocytic influx? Respir Res. (2006) 7:135. 10.1186/1465-9921-7-135
    1. Simpson JL, Gibson PG, Yang IA, Upham J, James A, Reynolds PN, et al. AMAZES study research group. impaired macrophage phagocytosis in non-eosinophilic asthma. Clin Exp Allergy. (2013) 43:29–35. 10.1111/j.1365-2222.2012.04075.x
    1. Raedler D, Ballenberger N, Klucker E, Böck A, Otto R, Prazeres da Costa O, et al. . Identification of novel immune phenotypes for allergic and nonallergic childhood asthma. J Allergy Clin Immunol. (2015) 135:81–91. 10.1016/j.jaci.2014.07.046
    1. Muraro A, Lemanske RF, Hellings PW, Akdis CA, Bieber T, Casale TB, et al. . Precision medicine in patients with allergic diseases: airway diseases and atopic dermatitis-PRACTALL document of the European Academy of Allergy and Clinical Immunology and the American Academy of Allergy, Asthma & Immunology. J Allergy Clin Immunol. (2016) 137:1347–58. 10.1016/j.jaci.2016.03.010
    1. Korevaar DA, Westerhof GA, Wang J, Cohen JF, Spijker R, Sterk PJ, et al. . Diagnostic accuracy of minimally invasive markers for detection of airway eosinophilia in asthma: a systematic review and meta-analysis. Lancet Respir Med. (2015) 3:290–300. 10.1016/S2213-2600(15)00050-8
    1. Moore WC, Hastie AT, Li X, Li H, Busse WW, Jarjour NN, et al. National Heart, Lung, and Blood Institute's Severe Asthma Research Program. Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis. J Allergy Clin Immunol. (2014) 133:1557–63.e5. 10.1016/j.jaci.2013.10.011
    1. Mukherjee M, Svenningsen S, Nair P. Glucocortiosteroid subsensitivity and asthma severity. Curr Opin Pulm Med. (2017) 23:78–88. 10.1097/MCP.0000000000000337
    1. Nadif R, Siroux V, Boudier A, le Moual N, Just J, Gormand F, et al. . Blood granulocyte patterns as predictors of asthma phenotypes in adults from the EGEA study. Eur Respir J. (2016) 48:1040–51. 10.1183/13993003.00336-2016
    1. Wood LG, Baines KJ, Fu J, Scott HA, Gibson PG. The neutrophilic inflammatory phenotype is associated with systemic inflammation in asthma. Chest. (2012) 142:86–93. 10.1378/chest.11-1838
    1. Cowan DC, Cowan JO, Palmay R, Williamson A, Taylor DR. Effects of steroid therapy on inflammatory cell subtypes in asthma. Thorax. (2010) 65:384–90. 10.1136/thx.2009.126722
    1. Baos S, Calzada D, Cremades-Jimeno L, Sastre J, Picado C, Quiralte J, et al. . Nonallergic asthma and its severity: biomarkers for its discrimination in peripheral samples. Front Immunol. (2018) 9:1416. 10.3389/fimmu.2018.01416
    1. Baos S, Calzada D, Cremades L, Sastre J, Quiralte J, Florido F, et al. . Biomarkers associated with disease severity in allergic and nonallergic asthma. Mol Immunol. (2017) 82:34–45. 10.1016/j.molimm.2016.12.012
    1. Lim HF, Nair P. Airway inflammation and inflammatory biomarkers. Semin Respir Crit Care Med. (2018) 39:56–63. 10.1055/s-0037-1606217
    1. Richards LB, Neerincx AH, van Bragt JJMH, Sterk PJ, Bel EHD, Maitland-van der Zee AH. Biomarkers and asthma management: analysis and potential applications. Curr Opin Allergy Clin Immunol. (2018) 18:96–108. 10.1097/ACI.0000000000000426
    1. Baos S, Calzada D, Cremades L, Sastre J, Quiralte J, Florido F, et al. . Data set on a study of gene expression in peripheral simples to identify biomarkers of severity of allergic and nonallergic asthma. Data Brief. (2016) 10:505–10. 10.1016/j.dib.2016.12.035
    1. Plaza Moral V. Comité Ejecutivo de GEMA. [GEMA (4.0) Guidelines for asthma management]. Arch Bronconeumol. (2015) 51(Suppl. 1):2–54. 10.1016/S0300-2896(15)32812-X
    1. Jia G, Erickson RW, Choy DF, Mosesova S, Wu LC, Solberg OD, et al. Bronchoscopic exploratory research study of biomarkers in corticosteroidrefractory asthma (BOBCAT) study group. Periostin is a systemic biomarker of eosinophilic airway inflammation in asthmatic patients. J Allergy Clin Immunol. (2012) 130:647–54.e10. 10.1016/j.jaci.2012.06.025
    1. Parulekar AD, Atik MA, Hanania NA. Periostin, a novel biomarker of TH2- driven asthma. Curr Opin Pulm Med. (2014) 20:60–5. 10.1097/MCP.0000000000000005
    1. Zervas E, Samitas K, Papaioannou AI, Bakakos P, Loukides S, Gaga M. An algorithmic approach for the treatment of severe uncontrolled asthma. ERJ Open Res. (2018) 4: 125–2017. 10.1183/23120541.00125-2017
    1. Berry A, Busse WW. Biomarkers in asthmatic patients: has their time come to direct treatment? J Allergy Clin Immunol. (2016) 137:1317–24. 10.1016/j.jaci.2016.03.009
    1. Parulekar AD, Diamant Z, Hanania NA. Role of biologics targeting type 2 airway inflammation in asthma: what have we learned so far? Curr Opin Pulm Med. (2017) 23:3–11. 10.1097/MCP.0000000000000343
    1. Hanania NA, Diamant Z. The road to precision medicine in asthma: challenges and opportunities. Curr Opin Pulm Med. (2018) 24:1–3. 10.1097/MCP.0000000000000444
    1. Peters MC, Ringel L, Dyjack N, Herrin R, Woodruff PG, Rios C, et al. . A transcriptomic method to determine airway immunedysfunction in T2-High and T2-Low asthma. Am J Respir Crit Care Med. (2018) 10.1164/rccm.201807-1291OC
    1. Bérubé JC, Bossé Y. Future clinical implications emerging from recent genomewide expression studies in asthma. Expert Rev Clin Immunol. (2014) 10:985–1004. 10.1586/1744666X.2014.932249
    1. Wagener AH, Yick CY, Brinkman P, van der Schee MP, Fens N, Sterk PJ. Toward composite molecular signatures in the phenotyping of asthma. Ann Am Thorac Soc. (2013) 10(Suppl.):S197–205. 10.1513/AnnalsATS.201302-035AW
    1. Tong X, Wang D, Liu S, Ma Y, Fan H. Can YKL-40 be used as a biomarker and therapeutic target for adult asthma? Eur Resp J. (2018). 51:1702194. 10.1183/13993003.02194-2017
    1. Nair P, Gaga M, Zervas E, Alagha K, Hargreave FE, O'Byrne PM, et al. . Safety and efficacy of a CXCR2 antagonist in patients with severe asthma and sputum neutrophils: a randomized, placebo-controlled clinical trial. Clin Exp Allergy. (2012) 42:1097–103. 10.1111/j.1365-2222.2012.04014.x
    1. O'Byrne PM, Metev H, Puu M, Richter K, Keen C, Uddin M, et al. . Efficacy and safety of a CXCR2 antagonist, AZD5069, in patients with uncontrolled persistent asthma: a randomised, double-blind, placebo-controlled trial. Lancet Respir Med. (2016) 4:797–806. 10.1016/S2213-2600(16)30227-2
    1. Calzada D, Baos S, Cremades-Jimeno L, Cárdaba B. Immunological mechanisms in allergic diseases and allergen tolerance: the role of treg cells. J Immunol Res. (2018) 14:6012053 10.1155/2018/6012053
    1. Palomares O, Martín-Fontecha M, Lauener R, Traidl-Hoffmann C, Cavkaytar O, Akdis M, et al. . Regulatory T cells and immune regulation of allergic diseases: roles of IL-10 and TGF-β. Genes Immun. (2014) 15:511–20. 10.1038/gene.2014.45
    1. Tsai YS, Tseng YT, Chen PS, Lin MC, Wu CC, Huang MS, et al. . Protective effects of elafin against adult asthma. Allergy Asthma Proc. (2016) 37:15–24. 10.2500/aap.2016.37.3932
    1. Woodruff PG, Modrek B, Choy DF, Jia G, Abbas AR, Ellwanger A, et al. . T-helper Type 2-driven inflammation defines major subphenotypes of asthma. Am J Respir Crit Care Med. (2009) 180:388–95. 10.1164/rccm.200903-0392OC

Source: PubMed

3
Subscribe