Breath profile clusters predict response to biologic treatment in severe asthma
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Key takeaways:
- The SpiroNose can measure the volatome of exhaled breath.
- Clusters emerged at baseline based on TH2 features, BMI, GERD and Asthma Quality of Life Questionnaire scores.
SAN DIEGO — Breath profile clusters can predict positive response to anti-IL5 or anti-IL5R alpha asthma treatment 1 month after initiation, according to an abstract presented at the American Thoracic Society International Conference.
Also, the volatomes of patients with severe asthma treated with these biologics come to resemble those of patients with mild to moderate asthma after 12 months, Piers Dixey, MBBCh, MRCP(UK), clinical research fellow, National Heart and Lung Institute, Imperial College London, and colleagues wrote.
“We have this new era of precision medicine, dominated by monoclonal antibodies, or biologics, and we know that they target various pathways,” Dixey said during his presentation.
For example, mepolizumab (Nucala, GSK) is an anti-IL5 treatment, and benralizumab (Fasenra, AstraZeneca) targets IL5 receptor alpha (IL5Ra).
Dixey also noted that some patients can be classified as biological responders, defined by a 50% or greater reduction in annual exacerbation rates or oral corticosteroid use at 12 months after beginning therapy.
“But what we don’t currently have are biomarkers to identify the subjects who respond to these biologics,” he said. “Exhaled breath volatome is a noninvasive, easily accessible compartment that might have the answers.”
The SpiroNose (Breathomix) point-of-care tool can be used to measure the volatome, Dixey said, which is a mixture of exhaled volatile organic compounds (VOCs). Patients breathe into this “electronic nose” or e-nose through a mouthpiece, and sensors provide 13 outputs.
The volatome then represents a “breathprint” of each patient that is unique to the time it is taken, Dixey continued, although it does not provide individual volatile organic compound concentrations.
Dixey and his colleagues hypothesized that e-nose breath profile clusters can phenotype severe asthma and predict response to anti-IL5 and anti-IL5Ra biologic treatment.
The observational and longitudinal PRISM study included 44 patients (median age, 65 years; 68% female) with severe asthma, including 49% with nasal polyps.
Also, the cohort had a mean of five exacerbations in the previous 12 months, a mean FeNO of 47 ppb, and 19% sputum eosinophils. With 55% on benralizumab and 45% on mepolizumab, 65% of the cohort were classified as biologic responders.
The researchers took e-nose measurements at baseline and then at 1, 6 and 12 months after the initiation of biologic therapy.
Using a Gaussian mixture model and unsupervised clustering, analysis at baseline revealed two clusters differentiated by serum IgE that were independent of oral steroid use with no other clinical, physiological or questionnaire parameters differentiating them.
At baseline, there were 28 patients in the first cluster (median age, 63 years; 61% female) and 16 patients in the second cluster (median age, 66 years; 81% female).
“In cluster one, there were high, high levels of TH2 markers,” Dixey said.
The first cluster had higher blood eosinophil counts (0.5*109/L vs. 0.1*109/L; P < .001), FeNO (55 ppb vs. 35 ppb; P = .032), total IgE (294 IU/mL vs. 96 IU/mL; P = .04) and Asthma Quality of Life Questionnaire delta changes over 12 months (1.47 vs. 0.34; P = .038).
The second cluster had higher BMI (33.8 kg/m2 vs. 25.8 kg/m2; P = .013) and more GERD (93% vs. 50%; P = .004).
After a month, the second cluster (n = 19; median age, 65 years; 79% female) had higher Asthma Control Questionnaire (ACQ6) scores (2 vs. 1.25; P = .048). It also had more biologic responders (87% vs. 53%) than the first cluster (n = 22; median age, 66 years; 50% female).
“Although not significant, there’s certainly a trend,” Dixey said.
The first cluster had more total IgE (209 IU/mL vs. 61 IU/mL; P = .022), more biologic non-responders (47% vs. 13%) and higher ACQ6 delta change after 12 months (–0.34 vs. –1.51; P = .022).
“One month after therapy, the two clusters were delineated by 12-month responder status,” Dixey said. “Although it wasn’t significant, cluster two had a higher percentage of responders to biologics than cluster one.”
Predictive modeling of response to biologic treatment based on these breath profile clusters after at 1 month yielded an area under the curve of 0.71 (95% CI, 0.71-0.73), accuracy of 0.74 (95% CI, 0.74-0.76), sensitivity of 0.78 (95% CI, 0.78-0.83) and specificity of 0.64 (95% CI, 0.64-0.64).
“The predictive modeling was done on just the e-nose sensor outputs,” Dixey said. “There wasn’t any clinical data.”
Additionally, the researchers compared these breath profiles with another cohort of patients with mild to moderate asthma who also used the e-nose in addition to mepolizumab and benralizumab treatment.
Based on four sensor outputs, the volatomes of the patients with severe asthma were comparable with the volatomes of those with mild to moderate asthma after 12 months of treatment.
These findings indicate that breath profile clusters from an e-nose system can phenotype severe asthma according to TH2 markers and BMI, Dixey said, as well as predict response to anti-IL5 and anti-IL5Ra biologics at 12 months.
The researchers plan on continuing their analysis, Dixey continued.
“We’re looking at a time series probability analysis of all the e-nose sensor changes plus the variables that change over 12 months, such as ACQ scores and FEV1, and see if we can use those data to get a higher area under the curve into the modeling system,” he said.
Dixey also cited the value of the e-nose system.
“One of the strengths of the e-nose is it looks at the whole volatome. It doesn’t just look at TH2,” he said, adding that severe asthma is heterogenous.
Also, Dixey said, TH2 pathways play a huge role for many patients, but they do not represent the whole picture of their disease.
“That’s why I think it’s a powerful tool, because we’re looking at the whole volatome and not just isolating that specific pathway,” he said. “You can hone your e-nose to asthma using VOC signatures. I think that’s probably the next step.”