Biomarkers and Cytokines Associated with Asthma, Allergic Rhinitis, and Atopic Eczema

Educational Objectives

The goal of this program is to improve use of biomarkers in the management of asthma, allergic rhinitis, and atopic dermatitis. After hearing and assimilating this program, the clinician will be better able to:

1. Adhere to guidelines regarding recommended use of fractional exhaled nitric oxide levels in management of asthma.
2. Select the most accurate biomarkers for monitoring of various allergic conditions.
3. Diagnose psoriasis and atopic dermatitis through biomarker levels.

Summary

Asthma

Fractional exhaled nitric oxide (FeNO): benefits — FeNO level correlates with eosinophilic inflammation and follows a standardized, non-invasive methodology with established reference ranges; disadvantages — nonspecific for asthma (ie, individuals with allergic rhinitis [AR] may exhibit elevated FeNO); costly; has unclear associations with asthma phenotypes, endotypes, and airway remodeling; some patients may have difficulty using the machinery; smoking can artificially reduce FeNO levels

National Asthma Education and Prevention Program (NAEPP) expert panel (Cloutier et al [2020]): use FeNO as an adjunct evaluation for patients ≥5 yr with an unclear asthma diagnosis, and for monitoring and managing strategies in patients with persistent allergic asthma; use of FeNO alone is strongly discouraged in patients ≥5 yr old with persistent allergic asthma to assess asthma control, predict exacerbations, or evaluate condition severity; do not use FeNO to predict future asthma development in patients <5 yr old

Caveats: the data do not concern biologics; monitoring is recommended every 2 to 3 mo; the primary impact of FeNO is on exacerbations rather than adherence to inhaled corticosteroids (for which FeNO is historically known)

Clinical efficacy: studies by Syk et al (2013) and Calhoun et al (2012) support FeNO in reducing asthma exacerbation rates and being slightly more effective than physician assessment for assessing disease activity, respectively

Responses to biologic agents: compared with placebo, Castro et al (2018) determined that FeNO ≥50 ppb was the most robust predictor of a significant response to dupilumab, leading to a reduction in exacerbations; compared with placebo, use of dupilumab produced a greater decrease in mean FeNO; the same phenomenon is not observed with agents which block interleukin (IL)-5; omalizumab decreases FeNO, and FeNO predicts responses to omalizumab; the use of biomarkers, including FeNO, for treatment responses has not been incorporated into the most recent guidelines

Peripheral blood eosinophil count: a relatively accessible, cost-effective, and widely employed biomarker for selecting existing asthma biologics; while peripheral blood eosinophils somewhat correlate with sputum eosinophilia (which are more reflective of airway inflammation), Fowler et al (2015) highlight the low sensitivity of peripheral blood eosinophil count in predicting ≥2% sputum eosinophilia; peripheral blood eosinophil count lacks specificity for asthma and is influenced by, eg, atopy, autoimmune disease, parasitic infections (specifically worms), drug reactions, hematologic disease; Price et al (2015) discovered that patients with asthma and peripheral blood eosinophil count >400 cells/μL experience more severe exacerbations and poorer asthma control, compared with patients with ≤400 cells/μL; Tran et al (2021) determined that patients with intermittently or persistently elevated peripheral blood eosinophil counts had increased risk of severe asthma exacerbations; Kraft et al (2021) underscored peripheral blood eosinophil count as one of the strongest predictors of exacerbations; Couillard et al (2022) proposed combining peripheral blood eosinophil count and exhaled FeNO as a method to predict asthma attacks

Eosinophil-derived neurotoxin (EDN): signifies eosinophilic activation and is theorized to better predict type 2-driven inflammation and responses to anti-type 2 biologics, compared with peripheral blood eosinophil count alone, including inactive eosinophils; the reference range is established in healthy adults 18 to 75 yr of age, with no variations based on sex, smoking status, circadian rhythm, storage material, or temperature; EDN is not routinely measured in clinical laboratories

Evidence: Granger et al (2022) found an association between high EDN and persistent asthma, but the speaker suggests this information can be gathered through patient communication; An et al (2020) discovered that EDN is only predictive of uncontrolled asthma (readily obtainable through the Asthma Control Test [ACT] or Asthma Control Questionnaire [ACQ] scores); Mogensen et al (2018) found a positive correlation between urinary EDN and persistent airflow obstruction, though its utility remains questionable; Howarth et al (2020) indicated that baseline peripheral blood eosinophil count offers greater precision as a predictive biomarker for mepolizumab (an IL-5 antagonist) treatment response than EDN

Cysteinyl leukotriene E4 (CystLTE₄): Bochenek et al (2018) comprehensively examined various diagnostic criteria for aspirin-exacerbated respiratory disease (AERD) and found that urinary LTE4 concentration (uLTE₄) alone is not highly predictive of AERD (negative predictive value of 61%), and the addition of uLTE₄ concentration did not add significant predictive diagnostic value; Jerschow et al (2019) demonstrated that polypectomy decreases aspirin sensitivity and uLTE₄ level in patients with AERD

IL-6: Peters et al (2016) noted an association of elevated IL-6 levels with metabolic syndrome, obesity, and severe asthma, and also observed a higher representation of severe asthma in individuals with elevated IL-6; the Severe Asthma Research Program (SARP) revealed a correlation between asthma severity and higher mean IL-6 levels, which also aligns with exacerbation history; Peters et al (2020) discovered that a one-time measurement of IL-6 longitudinally predicts asthma exacerbation rates, introducing a new endotype

Allergic Rhinitis (AR)

Type 2 cytokines and CystLT: Steelant et al (2018) demonstrated that transepithelial electrical resistance is partially mediated by T2 cytokines; Qin et al (2020) found a higher proportion of CystLTE receptor expression on the lymphoid cells of patients with AR, compared with patients without AR, and they found that montelukast and budesonide decrease IL-5 and IL-13 production by these cells

Microbiome: Yuan et al (2022) determined a high predictive accuracy for diagnosis of AR based on the nasal microbiota; however, the observed microbiota changes were linked to use of steroids; the clinical adoption of this information remains uncertain, as the traditional diagnostic approach, relying on patient-reported signs and symptoms, remains the preferred method; diagnosis is primarily determined through patient assessment and response to treatment; currently, there is no reliable method to predict a patient's optimal response in AR, a crucial aspect for personalized care

Atopic Dermatitis (AD)

Distinguishing biomarkers for AD vs psoriasis: Renert-Yuval et al (2021) determined that iNOS2 expression is upregulated in psoriasis and downregulated in AD, while C-C motif chemokine ligand 27 (CCL27) is upregulated in AD and downregulated in psoriasis; robust literature supporting these distinctions in patients is lacking, making it unclear whether incorporating these markers into clinical practice is warranted

Monitoring serum biomarkers for disease severity: high or very high overall evidence is sought for biomarker generalizability; specifically, the focus is on biomarkers with a real correlation coefficient ≥0.4, a p-value <0.05, and with >5 publications supporting their relevance; disease severity — immunoglobulin E (IgE) and lactate dehydrogenase are accessible, hence practical options for monitoring disease severity; therapeutic response — CCL17 and CCL22 are under consideration

Biomarkers for AD: Ahrens et al (2015) — noted high CCL17 and positive IgE (for food allergens) in the presence of AD; conversely, low or absent CCL17 correlated with the absence of AD, suggesting its potential as a biomarker; higher levels of CCL17 were associated with more severe AD; Zedan et al (2015) — while total IgE was shown to be a distinguishing biomarker for the presence or absence of AD, its utility in routine clinical use might be limited, given the straightforward clinical diagnosis of AD; a dose-response relationship was identified in terms of disease severity determined by the SCORing Atopic Dermatitis (SCORAD) index, indicating that higher SCORAD severity was associated with elevated total IgE

Readings

An J, Lee JH, Sim JH, et al. Serum eosinophil-derived neurotoxin better reflect asthma control status than blood eosinophil counts. J Allergy Clin Immunol Pract. 2020;8(8):2681-2688.e1. doi:10.1016/j.jaip.2020.03.035; Ahrens B, Schulz G, Bellach J, et al. Chemokine levels in serum of children with atopic dermatitis with regard to severity and sensitization status. Pediatr Allergy Immunol. 2015;26(7):634-640. doi:10.1111/pai.12431; Bochenek G, Stachura T, Szafraniec K, et al. Diagnostic accuracy of urinary LTE4 measurement to predict aspirin-exacerbated respiratory disease in patients with asthma. J Allergy Clin Immunol Pract. 2018;6(2):528-535. doi:10.1016/j.jaip.2017.07.001; Castro M, Corren J, Pavord ID, et al. Dupilumab efficacy and safety in moderate-to-severe uncontrolled asthma. N Engl J Med. 2018;378(26):2486-2496. doi:10.1056/NEJMoa1804092; Expert Panel Working Group of the National Heart, Lung, and Blood Institute (NHLBI) administered and coordinated National Asthma Education and Prevention Program Coordinating Committee (NAEPPCC), Cloutier MM, Baptist AP, et al. 2020 focused updates to the Asthma Management Guidelines: a report from the National Asthma Education and Prevention Program Coordinating Committee Expert Panel Working Group [published correction appears in J Allergy Clin Immunol. 2021 Apr;147(4):1528-1530]. J Allergy Clin Immunol. 2020;146(6):1217-1270. doi:10.1016/j.jaci.2020.10.003; Fowler SJ, Tavernier G, Niven R. High blood eosinophil counts predict sputum eosinophilia in patients with severe asthma. J Allergy Clin Immunol. 2015;135(3):822-4.e2. doi:10.1016/j.jaci.2014.09.034; Gemicioglu B, Musellim B, Dogan I, et al. Fractional exhaled nitric oxide (FeNo) in different asthma phenotypes. Allergy Rhinol (Providence). 2014;5(3):157-61. doi:10.2500/ar.2014.5.0099; Howarth P, Quirce S, Papi A, et al. Eosinophil-derived neurotoxin and clinical outcomes with mepolizumab in severe eosinophilic asthma. Allergy. 2020;75(8):2085-2088. doi:10.1111/all.14266; Peters MC, Mauger D, Ross KR, et al. Evidence for exacerbation-prone asthma and predictive biomarkers of exacerbation frequency. Am J Respir Crit Care Med. 2020;202(7):973-982. doi:10.1164/rccm.201909-1813OC; Qin ZL, Peng YQ, Fang SB, et al. CysLT1R expression on ILC2s and effects of CysLT1R antagonist on ILC2 activity in patients with allergic rhinitis. Allergy. 2020;75(4):977-981. doi:10.1111/all.14117; Rutten B, Young S, Rhedin M, et al. Eosinophil-derived neurotoxin: a biologically and analytically attractive asthma biomarker. PLoS One. 2021;16(2):e0246627. doi:10.1371/journal.pone.0246627; Tran TN, Kerkhof M, Carter V, et al. Persistence of eosinophilic asthma endotype and clinical outcomes: a real-world observational study. J Asthma Allergy. 2021;14:727-742. doi:10.2147/JAA.S306416; Zedan K, Rasheed Z, Farouk Y, et al. Immunoglobulin e, interleukin-18 and interleukin-12 in patients with atopic dermatitis: correlation with disease activity. J Clin Diagn Res. 2015;9(4):WC01-WC5. doi:10.7860/JCDR/2015/12261.5742.

Disclosures

For this program, the following relevant financial relationships were disclosed and mitigated to ensure that no commercial bias has been inserted into this content: Dr. Cardet has served on the advisory board for AstraZeneca, Genentech, GlaxoSmithKline, and Sanofi-Aventis US. Members of the faculty and planning committee reported nothing relevant to disclose.

Acknowledgements

Dr. Cardet was recorded at the 2023 Symposium Update in Allergy and Immunology, held January 20-21, 2023, in Tampa, FL, and presented by the University of South Florida Health. For information on upcoming CME activities from this presenter, please visit https://health.usf.edu/cpd. Audio Digest thanks the speakers and presenters for their cooperation in the production of this program.

CME/CE INFO

Accreditation:

The Audio- Digest Foundation is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The Audio- Digest Foundation designates this enduring material for a maximum of 0.75 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Audio Digest Foundation is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's (ANCC's) Commission on Accreditation. Audio Digest Foundation designates this activity for 0.75 CE contact hours.

Lecture ID:

IM710802

Expiration:

This CME course qualifies for AMA PRA Category 1 Credits™ for 3 years from the date of publication.

Instructions:

To earn CME/CE credit for this course, you must complete all the following components in the order recommended: (1) Review introductory course content, including Educational Objectives and Faculty/Planner Disclosures; (2) Listen to the audio program and review accompanying learning materials; (3) Complete posttest (only after completing Step 2) and earn a passing score of at least 80%. Taking the course Pretest and completing the Evaluation Survey are strongly recommended (but not mandatory) components of completing this CME/CE course.

Estimated time to complete this CME/CE course:

Approximately 2x the length of the recorded lecture to account for time spent studying accompanying learning materials and completing tests.