Are type-2 biomarkers of any help in asthma diagnosis?

Nekoee, Haleh; Graulich, Emmanuel; Schleich, Florence; Guissard, Françoise; Paulus, Virginie; Henket, Monique; Donneau, Anne Françoise; Louis, Renaud

doi:10.1183/23120541.00169-2020

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…Although it is lower than that recommended in the ERS guidelines, this cutoff was calculated to optimize the sensitivity and specificity, whereas the guideline’s higher cutoff was fitted to yield a high specificity to confidently rule in the diagnosis of asthma in symptomatic participants. Our F ENO results and the calculated cutoff are in line with a series of previous studies (46–49). Nevertheless, designing prospective studies to assess other cutoff values of F ENO for diagnosing asthma in elite swimmers may be of interest.…”

Section: Discussionsupporting

confidence: 92%

Exhaled and Systemic Biomarkers to Aid the Diagnosis of Bronchial Asthma in Elite Water Sports Athletes

CSOMA,

SYDÓ,

SZŰcs

et al. 2024

Medicine &Amp; Science in Sports &Amp; Exercise

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Purpose Our aim was to evaluate the accuracy of a combined airway inflammatory biomarker assessment in diagnosing asthma in elite water sports athletes. Methods Members of the Hungarian Olympic and Junior Swim Team and elite athletes from other aquatic disciplines were assessed for asthma by objective lung function measurements, and blood eosinophil count (BEC), serum total IgE, FENO measurements, and skin prick testing were performed. A scoring system from BEC, FENO, serum IgE, and skin test positivity was constructed by dichotomising the variables and assigning a score of 1 if the variable is elevated. These scores were summed to produce a final composite score ranging from 0 to 4. Results A total of 48 participants were enrolled (age 21 ± 4 years, 42% male), of which 22 were diagnosed with asthma. Serum total IgE and FENO levels were higher in asthmatic individuals (68 [27-176] vs. 24 ([1-44], p = 0.01; 20 [17-26] vs. 15 [11-22], p = 0.02), and positive prick test was also more frequent (55% vs. 8%, p < 0.01). Asthmatic participants had higher composite variable scores (2 ([1-3] vs. 1 [0-1], p = 0.02). ROC analysis showed that total IgE, FENO, and the composite variable were suitable for identifying asthmatic participants (AUC 0.72, p = 0.01; 0.70, p = 0.02, and 0.69, p = 0.03). A composite score of >2 reached a specificity of 96.2%, sensitivity of 36.4%, and likelihood ratio of 9.5. Logistic regression model revealed a strong association between the composite variable and the asthma diagnosis (OR 2.71 (95% CI 1.17-6.23), p = 0.02). Conclusions Our data highlight the diagnostic value of combined assessment of Th2-type inflammation in elite water sports athletes. The proposed scoring system may be helpful in ruling in asthma in this population upon clinical suspicion.

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Section: Discussionsupporting

confidence: 92%

Exhaled and Systemic Biomarkers to Aid the Diagnosis of Bronchial Asthma in Elite Water Sports Athletes

CSOMA,

SYDÓ,

SZŰcs

et al. 2024

Medicine &Amp; Science in Sports &Amp; Exercise

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“…This is in line with the value of low FEV 1 (% pred) and low FEV 1 /FVC (%) as predictors of a significant bronchodilator response [ 22 , 28 ]. However, spirometric indices performed better than measuring F ENO (AUC 0.56) in that regard, which is in keeping with previous studies conducted in other cohorts [ 15 , 29 ]. If F ENO was found to be a component of the predictive model that proved to be the best when applied on the validation cohort, its contribution in the predictive models was, however, clearly less than that of spirometric indices.…”

Section: Discussionsupporting

confidence: 90%

“…There has been much emphasis on the need for clinically objective parameters to help the clinician to make an asthma diagnosis [ 13 – 15 ]. Our data show that baseline spirometric indices provided a moderate accuracy (FEV 1 (% pred): AUC 0.68; FEV 1 /FVC (%): AUC 0.69) to make a correct asthma diagnosis in patients complaining with chronic respiratory symptoms.…”

Section: Discussionmentioning

confidence: 99%

“…The reason is that lung function tests are often not performed and consequently diagnosis is reduced to the clinical history and signs at the physical examination [ 12 ]. There has been much emphasis on the utility of discovering and using biomarkers to help in the diagnosis [ 13 – 15 ]. In contrast, the respective value of symptoms as reported directly by patients has been somewhat neglected [ 5 , 11 ] and the recent ERS guidelines acknowledge the importance of new research focusing on detailed symptoms history [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis

et al. 2022

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INTRODUCTIONAlthough asthma is a common disease, its diagnosis remains a challenge in clinical practice with both over/under-diagnosis. Here, we performed a prospective observational study investigating the value of symptom intensity scales alone or combined with spirometry and FeNO to aid in asthma diagnosis.METHODSWe recruited, over a 38-month period, 303 untreated patients complaining with symptoms suggestive of asthma (cough, chest tightness, dyspnea, airway secretion and wheezing). The whole cohort was split in a training cohort (n=166) for patients recruited in odd months and a validation cohort (n=137) for the patients recruited in even months. Asthma was diagnosed either by a positive reversibility test (≥12% and 200 ml) and/or a positive bronchial challenge test (PC20M≤8 mg·ml−1). In order to assess the diagnostic performance of symptoms, spirometric indices and FeNO, we performed ROC curve analysis and multivariable logistic regression to identify the independent factors associated with asthma in the training cohort. Then, the derived predictive models were applied to the validation cohort.RESULTS63% of patients in the derivation cohort and 58% in the validation cohort were diagnosed as being asthmatics. After logistic regression wheezing was the only symptom to be significantly associated with asthma. Similarly, FEV1% predicted, FEV1/FVC% and FeNO were significantly associated with asthma. A predictive model combining these four parameters yielded an AUC of 0.76 (95%CI: 0.66–0.84) in the training cohort and 0.73 (95%CI: 0.65–0.82) when applied to the validation cohort.CONCLUSIONCombining wheezing intensity scale with spirometry and FeNO may help in improving asthma diagnosis accuracy in clinical practice.

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“…This question will likely be of interest for future studies, although in the meantime it is noteworthy that the expression of miR-144-3p in the serum of asthmatic patients can be used as a biomarker for asthma subphenotyping, as seen in the ROC curve analysis, where the expression of this miRNA in serum had an AUC of 0.63 for differentiating severe asthmatics form mild to moderate asthmatics (being a mildly poor biomarker), and an AUC of 0.74 when distinguishing asthmatics who are in treatment with corticosteroids and bronchodilators from those with on-demand bronchodilator therapy (being a good biomarker for asthma treatment). The importance of biomarkers for asthma diagnosis has been previously shown, as lung function tests are not always good, and therefore combinatorial biomarkers seem to be the most promising diagnostic tool in asthma (40).…”

Section: Discussionmentioning

confidence: 99%

miR-144-3p Is a Biomarker Related to Severe Corticosteroid-Dependent Asthma

et al. 2022

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MicroRNAs are non-coding molecules that act both as regulators of the epigenetic landscape and as biomarkers for diseases, including asthma. In the era of personalized medicine, there is a need for novel disease-associated biomarkers that can help in classifying diseases into phenotypes for treatment selection. Currently, severe eosinophilic asthma is one of the most widely studied phenotypes in clinical practice, as many patients require higher and higher doses of corticosteroids, which in some cases fail to achieve the desired outcome. Such patients may only benefit from alternative drugs such as biologics, for which novel biomarkers are necessary. The objective of the study was to study the expression of miR-144-3p in order to discover its possible use as a diagnostic biomarker for severe asthma. For this purpose, miR-144-3p was evaluated in airway biopsies and serum from asthmatics and healthy individuals. mRNA was studied in asthmatic biopsies and smooth muscle cells transfected with miR-144-3p mimic. An in silico regulation of miR-144-3p was performed using miRSystem, miRDB, STRING, and ShinyGO for pathway analysis. From our experimental procedures, we found that miR-144-3p is a biomarker associated with asthma severity and corticosteroid treatment. MiR-144-3p is increased in asthmatic lungs, and its presence correlates directly with blood eosinophilia and with the expression of genes involved in asthma pathophysiology in the airways. When studied in serum, this miRNA was increased in severe asthmatics and associated with higher doses of corticosteroids, thereby making it a potential biomarker for severe asthma previously treated with higher doses of corticosteroids. Thus, we can conclude that miR-144-3p is associated with severe diseases in both the airways and serum of asthmatics, and this association is related to corticosteroid treatment.

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Are type-2 biomarkers of any help in asthma diagnosis?

Cited by 7 publications

References 13 publications

Exhaled and Systemic Biomarkers to Aid the Diagnosis of Bronchial Asthma in Elite Water Sports Athletes

Exhaled and Systemic Biomarkers to Aid the Diagnosis of Bronchial Asthma in Elite Water Sports Athletes

Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis

miR-144-3p Is a Biomarker Related to Severe Corticosteroid-Dependent Asthma

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