Unsupervised network mapping of commercially available immunoassay yields three distinct chronic rhinosinusitis endotypes

Rohit Divekar, Matthew A Rank, Diane Squillace, Hirohito Kita, Devyani Lal

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Background: Endotyping chronic rhinosinusitis (CRS) through simplified cytokine assays may help direct individualized therapy such as corticosteroids, antibiotics, or biologics. We performed an unsupervised network analysis to endotype CRS and control subjects using a commercially available cytokine-chemokine immunoassay. Methods: A 41-plex cytokine-chemokine array along with major basic protein (MBP) assay was performed on sinonasal surgical tissue of 32 adults. Subjects were defined as non-CRS controls (n = 6), CRS with nasal polyps (CRSwNP; n = 13), and CRS without nasal polyps (CRSsNP; n = 13). Unsupervised network modeling was performed to reveal association cytokine-chemokine ("analyte") clusters and "subject" groups. Results: Network mapping and unsupervised clustering revealed 3 analyte clusters and 3 subject groups. Analyte cluster-1 was composed of T helper 1 (Th1)/Th17 type markers, analyte cluster-2 Th2 markers, and analyte cluster-3 chemokines (CC) and growth factors (GF). Subject group-1 was devoid of CRSwNP, had fewer asthmatics, and was associated most strongly with analyte cluster-3 (CC/GF) (p < 0.001). Subject group-2 was characterized with the most asthmatics (86%) and CRSwNP (100%) patients, and was associated with analyte cluster-2 (Th2; p < 0.001). Subject group-3 was associated with both analyte cluster-1 (Th1/Th17) and analyte cluster-3 (CC/GF) (p < 0.001), and had the highest proportion of CRSsNP patients (62.5%). Tissue levels of MBP, eosinophilia, and computed tomography (CT) scores were significantly higher in subject group-2 vs other groups (p ≤ 0.05). Conclusion: An unbiased network-mapping approach using a commercially available immunoassay kit reveals 3 distinct tissue cytokine-chemokine signatures that endotype CRS patients and controls. These signatures are prominent even in a limited number of patients, and may help formulate individualized therapy and optimize outcomes.

Original languageEnglish (US)
JournalInternational Forum of Allergy and Rhinology
DOIs
StateAccepted/In press - 2016

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Chemokines
Immunoassay
Cytokines
Nasal Polyps
Intercellular Signaling Peptides and Proteins
Eosinophilia
Biological Products
Cluster Analysis
Adrenal Cortex Hormones
Proteins
Tomography
Anti-Bacterial Agents
Therapeutics

Keywords

  • Chronic rhinosinusitis endotypes
  • CRS
  • Immunoassay
  • Network analysis

ASJC Scopus subject areas

  • Immunology and Allergy
  • Otorhinolaryngology

Cite this

@article{8a3b572f98d24b838a0ea2e6e4bc309b,
title = "Unsupervised network mapping of commercially available immunoassay yields three distinct chronic rhinosinusitis endotypes",
abstract = "Background: Endotyping chronic rhinosinusitis (CRS) through simplified cytokine assays may help direct individualized therapy such as corticosteroids, antibiotics, or biologics. We performed an unsupervised network analysis to endotype CRS and control subjects using a commercially available cytokine-chemokine immunoassay. Methods: A 41-plex cytokine-chemokine array along with major basic protein (MBP) assay was performed on sinonasal surgical tissue of 32 adults. Subjects were defined as non-CRS controls (n = 6), CRS with nasal polyps (CRSwNP; n = 13), and CRS without nasal polyps (CRSsNP; n = 13). Unsupervised network modeling was performed to reveal association cytokine-chemokine ({"}analyte{"}) clusters and {"}subject{"} groups. Results: Network mapping and unsupervised clustering revealed 3 analyte clusters and 3 subject groups. Analyte cluster-1 was composed of T helper 1 (Th1)/Th17 type markers, analyte cluster-2 Th2 markers, and analyte cluster-3 chemokines (CC) and growth factors (GF). Subject group-1 was devoid of CRSwNP, had fewer asthmatics, and was associated most strongly with analyte cluster-3 (CC/GF) (p < 0.001). Subject group-2 was characterized with the most asthmatics (86{\%}) and CRSwNP (100{\%}) patients, and was associated with analyte cluster-2 (Th2; p < 0.001). Subject group-3 was associated with both analyte cluster-1 (Th1/Th17) and analyte cluster-3 (CC/GF) (p < 0.001), and had the highest proportion of CRSsNP patients (62.5{\%}). Tissue levels of MBP, eosinophilia, and computed tomography (CT) scores were significantly higher in subject group-2 vs other groups (p ≤ 0.05). Conclusion: An unbiased network-mapping approach using a commercially available immunoassay kit reveals 3 distinct tissue cytokine-chemokine signatures that endotype CRS patients and controls. These signatures are prominent even in a limited number of patients, and may help formulate individualized therapy and optimize outcomes.",
keywords = "Chronic rhinosinusitis endotypes, CRS, Immunoassay, Network analysis",
author = "Rohit Divekar and Rank, {Matthew A} and Diane Squillace and Hirohito Kita and Devyani Lal",
year = "2016",
doi = "10.1002/alr.21904",
language = "English (US)",
journal = "International Forum of Allergy and Rhinology",
issn = "2042-6976",
publisher = "Wiley-Blackwell",

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TY - JOUR

T1 - Unsupervised network mapping of commercially available immunoassay yields three distinct chronic rhinosinusitis endotypes

AU - Divekar, Rohit

AU - Rank, Matthew A

AU - Squillace, Diane

AU - Kita, Hirohito

AU - Lal, Devyani

PY - 2016

Y1 - 2016

N2 - Background: Endotyping chronic rhinosinusitis (CRS) through simplified cytokine assays may help direct individualized therapy such as corticosteroids, antibiotics, or biologics. We performed an unsupervised network analysis to endotype CRS and control subjects using a commercially available cytokine-chemokine immunoassay. Methods: A 41-plex cytokine-chemokine array along with major basic protein (MBP) assay was performed on sinonasal surgical tissue of 32 adults. Subjects were defined as non-CRS controls (n = 6), CRS with nasal polyps (CRSwNP; n = 13), and CRS without nasal polyps (CRSsNP; n = 13). Unsupervised network modeling was performed to reveal association cytokine-chemokine ("analyte") clusters and "subject" groups. Results: Network mapping and unsupervised clustering revealed 3 analyte clusters and 3 subject groups. Analyte cluster-1 was composed of T helper 1 (Th1)/Th17 type markers, analyte cluster-2 Th2 markers, and analyte cluster-3 chemokines (CC) and growth factors (GF). Subject group-1 was devoid of CRSwNP, had fewer asthmatics, and was associated most strongly with analyte cluster-3 (CC/GF) (p < 0.001). Subject group-2 was characterized with the most asthmatics (86%) and CRSwNP (100%) patients, and was associated with analyte cluster-2 (Th2; p < 0.001). Subject group-3 was associated with both analyte cluster-1 (Th1/Th17) and analyte cluster-3 (CC/GF) (p < 0.001), and had the highest proportion of CRSsNP patients (62.5%). Tissue levels of MBP, eosinophilia, and computed tomography (CT) scores were significantly higher in subject group-2 vs other groups (p ≤ 0.05). Conclusion: An unbiased network-mapping approach using a commercially available immunoassay kit reveals 3 distinct tissue cytokine-chemokine signatures that endotype CRS patients and controls. These signatures are prominent even in a limited number of patients, and may help formulate individualized therapy and optimize outcomes.

AB - Background: Endotyping chronic rhinosinusitis (CRS) through simplified cytokine assays may help direct individualized therapy such as corticosteroids, antibiotics, or biologics. We performed an unsupervised network analysis to endotype CRS and control subjects using a commercially available cytokine-chemokine immunoassay. Methods: A 41-plex cytokine-chemokine array along with major basic protein (MBP) assay was performed on sinonasal surgical tissue of 32 adults. Subjects were defined as non-CRS controls (n = 6), CRS with nasal polyps (CRSwNP; n = 13), and CRS without nasal polyps (CRSsNP; n = 13). Unsupervised network modeling was performed to reveal association cytokine-chemokine ("analyte") clusters and "subject" groups. Results: Network mapping and unsupervised clustering revealed 3 analyte clusters and 3 subject groups. Analyte cluster-1 was composed of T helper 1 (Th1)/Th17 type markers, analyte cluster-2 Th2 markers, and analyte cluster-3 chemokines (CC) and growth factors (GF). Subject group-1 was devoid of CRSwNP, had fewer asthmatics, and was associated most strongly with analyte cluster-3 (CC/GF) (p < 0.001). Subject group-2 was characterized with the most asthmatics (86%) and CRSwNP (100%) patients, and was associated with analyte cluster-2 (Th2; p < 0.001). Subject group-3 was associated with both analyte cluster-1 (Th1/Th17) and analyte cluster-3 (CC/GF) (p < 0.001), and had the highest proportion of CRSsNP patients (62.5%). Tissue levels of MBP, eosinophilia, and computed tomography (CT) scores were significantly higher in subject group-2 vs other groups (p ≤ 0.05). Conclusion: An unbiased network-mapping approach using a commercially available immunoassay kit reveals 3 distinct tissue cytokine-chemokine signatures that endotype CRS patients and controls. These signatures are prominent even in a limited number of patients, and may help formulate individualized therapy and optimize outcomes.

KW - Chronic rhinosinusitis endotypes

KW - CRS

KW - Immunoassay

KW - Network analysis

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