Michael C Peters1, David Mauger2, Kristie R Ross3, Brenda Phillips2, Benjamin Gaston3, Juan Carlos Cardet4, Elliot Israel5, Bruce D Levy5, Wanda Phipatanakul6, Nizar N Jarjour7, Mario Castro8, Sally E Wenzel9,10, Annette Hastie11, Wendy Moore11, Eugene Bleecker12, John V Fahy1,13, Loren C Denlinger7. 1. Division of Pulmonary and Critical Care Medicine, Department of Medicine, and. 2. Division of Statistics and Bioinformatics, Department of Public Health Sciences, Pennsylvania State University, Hershey, Pennsylvania. 3. University Hospitals Rainbow Babies and Children's Hospital/Case Western Reserve University School of Medicine, Cleveland, Ohio. 4. Division of Allergy and Immunology, Department of Internal Medicine, University of South Florida Morsani College of Medicine, Tampa, Florida. 5. Division of Allergy and Immunology Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. 6. Division of Allergy and Immunology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts. 7. Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin School of Medicine, Madison, Wisconsin. 8. Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kansas School of Medicine, Kansas City, Kansas. 9. Department of Environmental and Occupational Health, Graduate School of Public Health University of Pittsburgh, Pittsburgh, Pennsylvania. 10. Pulmonary, Allergy and Critical Care Medicine Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. 11. Section on Pulmonary, Critical Care, Allergy & Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, North Carolina; and. 12. Asthma and Airway Disease Research Center and Division of Genetics, Genomics and Precision Medicine, Department of Medicine, The University of Arizona Health Sciences, Tucson, Arizona. 13. Cardiovascular Research Institute, University of California San Francisco, San Francisco, California.
Abstract
Rationale: Cross-sectional studies suggest an exacerbation-prone asthma (EPA) phenotype and the utility of blood eosinophils and plasma IL-6 as predictive biomarkers. Objectives: To prospectively test for EPA phenotype and utility of baseline blood measures of eosinophils and IL-6 as predictive biomarkers. Methods: Three-year asthma exacerbation data were analyzed in 406 adults in the Severe Asthma Research Program-3. Transition models were used to assess uninformed and informed probabilities of exacerbation in year 3. Binomial regression models were used to assess eosinophils and IL-6 as predictive biomarkers.Measurements and Main Results: Eighty-three participants (21%) had ≥1 exacerbation in each year (EPA) and 168 participants (41%) had no exacerbation in any year (exacerbation-resistant asthma). The uninformed probability of an exacerbation in Year 3 was 40%, but the informed probability increased to 63% with an exacerbation in Year 2 and 82% with an exacerbation in Years 1 and 2. The probability of a Year 3 exacerbation with no Year 1 or 2 exacerbations was 13%. Compared with exacerbation-resistant asthma, EPA was characterized by lower FEV1 and a higher prevalence of obesity, hypertension, and diabetes. High-plasma IL-6 occurred in EPA, and the incident rate ratio for exacerbation increased 10% for each 1-pg/μl increase in baseline IL-6 level. Although high blood eosinophils did not occur in EPA, the incident rate ratio for exacerbations increased 9% for each 100-cell/μl increase in baseline eosinophil number.Conclusions: Longitudinal analysis confirms an EPA phenotype characterized by features of metabolic dysfunction. Blood measures of IL-6, but not eosinophils, were significantly associated with EPA, and IL-6 and eosinophils predicted exacerbations in the sample as a whole.
Rationale: Cross-sectional studies suggest an exacerbation-prone asthma (EPA) phenotype and the utility of blood eosinophils and plasma IL-6 as predictive biomarkers. Objectives: To prospectively test for EPA phenotype and utility of baseline blood measures of eosinophils and IL-6 as predictive biomarkers. Methods: Three-year asthma exacerbation data were analyzed in 406 adults in the Severe Asthma Research Program-3. Transition models were used to assess uninformed and informed probabilities of exacerbation in year 3. Binomial regression models were used to assess eosinophils and IL-6 as predictive biomarkers.Measurements and Main Results: Eighty-three participants (21%) had ≥1 exacerbation in each year (EPA) and 168 participants (41%) had no exacerbation in any year (exacerbation-resistant asthma). The uninformed probability of an exacerbation in Year 3 was 40%, but the informed probability increased to 63% with an exacerbation in Year 2 and 82% with an exacerbation in Years 1 and 2. The probability of a Year 3 exacerbation with no Year 1 or 2 exacerbations was 13%. Compared with exacerbation-resistant asthma, EPA was characterized by lower FEV1 and a higher prevalence of obesity, hypertension, and diabetes. High-plasma IL-6 occurred in EPA, and the incident rate ratio for exacerbation increased 10% for each 1-pg/μl increase in baseline IL-6 level. Although high blood eosinophils did not occur in EPA, the incident rate ratio for exacerbations increased 9% for each 100-cell/μl increase in baseline eosinophil number.Conclusions: Longitudinal analysis confirms an EPA phenotype characterized by features of metabolic dysfunction. Blood measures of IL-6, but not eosinophils, were significantly associated with EPA, and IL-6 and eosinophils predicted exacerbations in the sample as a whole.
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