title: Unsupervised network mapping of commercially available immunoassay yields three distinct chronic rhinosinusitis endotypes.
abstract: 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.
  
  
  
  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.
  
  
  
  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).
  
  
  
  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.
authors.affiliation: Division of Allergy, Asthma, and Clinical Immunology, Mayo Clinic in Rochester, Rochester, MN.
authors.forename: Rohit
authors.initials: R
authors.lastname: Divekar
authors.affiliation: Division of Allergy, Asthma, and Clinical Immunology, Mayo Clinic in Arizona, Scottsdale, AZ.
authors.forename: Matthew
authors.initials: M
authors.lastname: Rank
authors.affiliation: Allergic Diseases Research Laboratory, Mayo Clinic, Rochester, MN.
authors.forename: Diane
authors.initials: D
authors.lastname: Squillace
authors.affiliation: Division of Allergy, Asthma, and Clinical Immunology, Mayo Clinic in Rochester, Rochester, MN.|Allergic Diseases Research Laboratory, Mayo Clinic, Rochester, MN.
authors.forename: Hirohito
authors.initials: H
authors.lastname: Kita
authors.affiliation: Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic in Arizona, Phoenix, AZ.
authors.forename: Devyani
authors.initials: D
authors.lastname: Lal
mesh_terms: D000328:Adult; D002908:Chronic Disease; D016207:Cytokines / Q000276:immunology*; D005260:Female; D006801:Humans; D007118:Immunoassay; D008297:Male; D010256:Paranasal Sinuses / Q000276:immunology; D012220:Rhinitis / Q000145:classification / Q000276:immunology*; D012852:Sinusitis / Q000145:classification / Q000276:immunology*
chemical_list: D016207:Cytokines
keywords: CRS; chronic rhinosinusitis endotypes; immunoassay; network analysis