TY - JOUR
T1 - How cytokines co-occur across asthma patients
T2 - From bipartite network analysis to a molecular-based classification
AU - Bhavnani, Suresh K.
AU - Victor, Sundar
AU - Calhoun, William J.
AU - Busse, William W.
AU - Bleecker, Eugene
AU - Castro, Mario
AU - Ju, Hyunsu
AU - Pillai, Regina
AU - Oezguen, Numan
AU - Bellala, Gowtham
AU - Brasier, Allan R.
N1 - Funding Information:
This work was supported in part by NIH Grants 1U54RR02614 UTMB CTSA (ARB), AI062885 (ARB), NHLBI contract BAA-HL-02-04 (ARB), HL69130 US SARP (WJC), and HL69149 (MC), and CDC/NIOSH Grant R21OH 0094441-01A2. We thank H. Spratt, M. Sinha, A. Ganesan, and D. Bostick for their suggestions.
PY - 2011/12
Y1 - 2011/12
N2 - Asthmatic patients are currently classified as either severe or non-severe based primarily on their response to glucocorticoids. However, because this classification is based on a post-hoc assessment of treatment response, it does not inform the rational staging of disease or therapy. Recent studies in other diseases suggest that a classification which includes molecular information could lead to more accurate diagnoses and prediction of treatment response. We therefore measured cytokine values in bronchoalveolar lavage (BAL) samples of the lower respiratory tract obtained from 83 asthma patients, and used bipartite network visualizations with associated quantitative measures to conduct an exploratory analysis of the co-occurrence of cytokines across patients. The analysis helped to identify three clusters of patients which had a complex but understandable interaction with three clusters of cytokines, leading to insights for a state-based classification of asthma patients. Furthermore, while the patient clusters were significantly different based on key pulmonary functions, they appeared to have no significant relationship to the current classification of asthma patients. These results suggest the need to define a molecular-based classification of asthma patients, which could improve the diagnosis and treatment of this disease.
AB - Asthmatic patients are currently classified as either severe or non-severe based primarily on their response to glucocorticoids. However, because this classification is based on a post-hoc assessment of treatment response, it does not inform the rational staging of disease or therapy. Recent studies in other diseases suggest that a classification which includes molecular information could lead to more accurate diagnoses and prediction of treatment response. We therefore measured cytokine values in bronchoalveolar lavage (BAL) samples of the lower respiratory tract obtained from 83 asthma patients, and used bipartite network visualizations with associated quantitative measures to conduct an exploratory analysis of the co-occurrence of cytokines across patients. The analysis helped to identify three clusters of patients which had a complex but understandable interaction with three clusters of cytokines, leading to insights for a state-based classification of asthma patients. Furthermore, while the patient clusters were significantly different based on key pulmonary functions, they appeared to have no significant relationship to the current classification of asthma patients. These results suggest the need to define a molecular-based classification of asthma patients, which could improve the diagnosis and treatment of this disease.
KW - Co-occurrence of cytokines
KW - Molecular-based classification of asthma patients
KW - Network analysis
UR - https://www.scopus.com/pages/publications/83755218841
U2 - 10.1016/j.jbi.2011.09.006
DO - 10.1016/j.jbi.2011.09.006
M3 - Article
C2 - 21986291
AN - SCOPUS:83755218841
SN - 1532-0464
VL - 44
SP - S24-S30
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
IS - SUPPL. 1
ER -