How cytokines co-occur across asthma patients

From bipartite network analysis to a molecular-based classification

Suresh Bhavnani, Sundar Victor, William Calhoun, William W. Busse, Eugene Bleecker, Mario Castro, Hyunsu Ju, Regina Pillai, Numan Oezguen, Gowtham Bellala, Allan R. Brasier

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
JournalJournal of Biomedical Informatics
Volume44
Issue numberSUPPL. 1
DOIs
StatePublished - Dec 2011

Fingerprint

Electric network analysis
Asthma
Cytokines
Visualization
Bronchoalveolar Lavage
Therapeutics
Respiratory System
Glucocorticoids
Lung

Keywords

  • Co-occurrence of cytokines
  • Molecular-based classification of asthma patients
  • Network analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

Cite this

How cytokines co-occur across asthma patients : From bipartite network analysis to a molecular-based classification. / Bhavnani, Suresh; Victor, Sundar; Calhoun, William; Busse, William W.; Bleecker, Eugene; Castro, Mario; Ju, Hyunsu; Pillai, Regina; Oezguen, Numan; Bellala, Gowtham; Brasier, Allan R.

In: Journal of Biomedical Informatics, Vol. 44, No. SUPPL. 1, 12.2011.

Research output: Contribution to journalArticle

Bhavnani, Suresh ; Victor, Sundar ; Calhoun, William ; Busse, William W. ; Bleecker, Eugene ; Castro, Mario ; Ju, Hyunsu ; Pillai, Regina ; Oezguen, Numan ; Bellala, Gowtham ; Brasier, Allan R. / How cytokines co-occur across asthma patients : From bipartite network analysis to a molecular-based classification. In: Journal of Biomedical Informatics. 2011 ; Vol. 44, No. SUPPL. 1.
@article{f927322c45ac4dd3b0654ec457583c0f,
title = "How cytokines co-occur across asthma patients: From bipartite network analysis to a molecular-based classification",
abstract = "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.",
keywords = "Co-occurrence of cytokines, Molecular-based classification of asthma patients, Network analysis",
author = "Suresh Bhavnani and Sundar Victor and William Calhoun and Busse, {William W.} and Eugene Bleecker and Mario Castro and Hyunsu Ju and Regina Pillai and Numan Oezguen and Gowtham Bellala and Brasier, {Allan R.}",
year = "2011",
month = "12",
doi = "10.1016/j.jbi.2011.09.006",
language = "English (US)",
volume = "44",
journal = "Journal of Biomedical Informatics",
issn = "1532-0464",
publisher = "Academic Press Inc.",
number = "SUPPL. 1",

}

TY - JOUR

T1 - How cytokines co-occur across asthma patients

T2 - From bipartite network analysis to a molecular-based classification

AU - Bhavnani, Suresh

AU - Victor, Sundar

AU - Calhoun, William

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.

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 - http://www.scopus.com/inward/record.url?scp=83755218841&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=83755218841&partnerID=8YFLogxK

U2 - 10.1016/j.jbi.2011.09.006

DO - 10.1016/j.jbi.2011.09.006

M3 - Article

VL - 44

JO - Journal of Biomedical Informatics

JF - Journal of Biomedical Informatics

SN - 1532-0464

IS - SUPPL. 1

ER -