Damien C Croteau-Chonka1, Weiliang Qiu1, Fernando D Martinez2, Robert C Strunk3, Robert F Lemanske4, Andrew H Liu5, Frank D Gilliland6, Joshua Millstein7, W James Gauderman7, Carole Ober8, Jerry A Krishnan9, Steven R White10, Edward T Naureckas10, Dan L Nicolae8,11,12, Kathleen C Barnes13, Stephanie J London14, Albino Barraza-Villarreal15, Vincent J Carey1, Scott T Weiss1,16, Benjamin A Raby1,17. 1. 1 Channing Division of Network Medicine and. 2. 2 Arizona Respiratory Center and BIO5 Institute, University of Arizona, Tucson, Arizona. 3. 3 Division of Allergy, Immunology and Pulmonary Medicine, Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri. 4. 4 University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. 5. 5 Division of Allergy and Clinical Immunology, Department of Pediatrics, National Jewish Health and University of Colorado School of Medicine, Denver, Colorado. 6. 6 Division of Environmental Health and. 7. 7 Division of Biostatistics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California. 8. 8 Department of Human Genetics. 9. 9 Division of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois. 10. 10 Section of Pulmonary and Critical Care Medicine, Department of Medicine. 11. 11 Section of Genetic Medicine, Department of Medicine, and. 12. 12 Department of Statistics, University of Chicago, Chicago, Illinois. 13. 13 Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland. 14. 14 Division of Intramural Research, Department of Health and Human Services, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina. 15. 15 National Institute of Public Health, Cuernavaca, Morelos, México; and. 16. 16 Partners HealthCare Personalized Medicine, Partners Health Care, Boston, Massachusetts. 17. 17 Pulmonary Genetics Center and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Abstract
RATIONALE: Maintaining optimal symptom control remains the primary objective of asthma treatment. Better understanding of the biologic underpinnings of asthma control may lead to the development of improved clinical and pharmaceutical approaches. OBJECTIVES: To identify molecular pathways and interrelated genes whose differential expression was associated with asthma control. METHODS: We performed gene set enrichment analyses of asthma control in 1,170 adults with asthma, each with gene expression data derived from either whole blood (WB) or unstimulated CD4+ T lymphocytes (CD4), and a self-reported asthma control score representing either the preceding 6 months (chronic) or 7 days (acute). Our study comprised a discovery WB cohort (n = 245, chronic) and three independent, nonoverlapping replication cohorts: a second WB set (n = 448, acute) and two CD4 sets (n = 300, chronic; n = 77, acute). MEASUREMENTS AND MAIN RESULTS: In the WB discovery cohort, we found significant overrepresentation of genes associated with asthma control in 1,106 gene sets from the Molecular Signatures Database (false discovery rate, <5%). Of these, 583 (53%) replicated in at least one replication cohort (false discovery rate, <25%). Suboptimal control was associated with signatures of eosinophilic and granulocytic inflammatory signals, whereas optimal control signatures were enriched for immature lymphocytic patterns. These signatures included two related biologic processes related to activation by TREM-1 (triggering receptor expressed on myeloid cells 1) and lipopolysaccharide. CONCLUSIONS: Together, these results demonstrate the existence of specific, reproducible transcriptomic components in blood that vary with degree of asthma control and implicate a novel biologic target (TREM-1).
RATIONALE: Maintaining optimal symptom control remains the primary objective of asthma treatment. Better understanding of the biologic underpinnings of asthma control may lead to the development of improved clinical and pharmaceutical approaches. OBJECTIVES: To identify molecular pathways and interrelated genes whose differential expression was associated with asthma control. METHODS: We performed gene set enrichment analyses of asthma control in 1,170 adults with asthma, each with gene expression data derived from either whole blood (WB) or unstimulated CD4+ T lymphocytes (CD4), and a self-reported asthma control score representing either the preceding 6 months (chronic) or 7 days (acute). Our study comprised a discovery WB cohort (n = 245, chronic) and three independent, nonoverlapping replication cohorts: a second WB set (n = 448, acute) and two CD4 sets (n = 300, chronic; n = 77, acute). MEASUREMENTS AND MAIN RESULTS: In the WB discovery cohort, we found significant overrepresentation of genes associated with asthma control in 1,106 gene sets from the Molecular Signatures Database (false discovery rate, <5%). Of these, 583 (53%) replicated in at least one replication cohort (false discovery rate, <25%). Suboptimal control was associated with signatures of eosinophilic and granulocytic inflammatory signals, whereas optimal control signatures were enriched for immature lymphocytic patterns. These signatures included two related biologic processes related to activation by TREM-1 (triggering receptor expressed on myeloid cells 1) and lipopolysaccharide. CONCLUSIONS: Together, these results demonstrate the existence of specific, reproducible transcriptomic components in blood that vary with degree of asthma control and implicate a novel biologic target (TREM-1).
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