Division of Allergy, Asthma, and Clinical Immunology, Mayo Clinic in Rochester, Rochester, MN.
Division of Allergy, Asthma, and Clinical Immunology, Mayo Clinic in Arizona, Scottsdale, AZ.
Int Forum Allergy Rhinol. 2017 Apr;7(4):373-379. doi: 10.1002/alr.21904. Epub 2017 Jan 2.
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.
通过简化的细胞因子检测对慢性鼻-鼻窦炎(CRS)进行表型分型可能有助于指导皮质类固醇、抗生素或生物制剂等个体化治疗。我们使用市售的细胞因子-趋化因子免疫分析试剂盒,通过无监督网络分析对 CRS 和对照受试者进行表型分型。
对 32 例成人鼻-鼻窦手术组织进行了 41 重细胞因子-趋化因子数组和主要碱性蛋白(MBP)检测。受试者定义为非 CRS 对照(n = 6)、伴有鼻息肉的 CRS(CRSwNP;n = 13)和不伴鼻息肉的 CRS(CRSsNP;n = 13)。进行无监督网络建模以揭示关联细胞因子-趋化因子(“分析物”)簇和“受试者”组。
网络映射和无监督聚类显示 3 个分析物簇和 3 个受试者组。分析物簇 1 由辅助性 T 细胞 1(Th1)/Th17 型标志物组成,分析物簇 2 为 Th2 标志物,分析物簇 3 为趋化因子(CC)和生长因子(GF)。受试者组 1 无 CRSwNP,哮喘患者较少,与分析物簇 3(CC/GF)关系最密切(p < 0.001)。受试者组 2 的特点是哮喘患者(86%)和 CRSwNP 患者(100%)最多,与分析物簇 2(Th2;p < 0.001)关系最密切。受试者组 3 与分析物簇 1(Th1/Th17)和分析物簇 3(CC/GF)均有关联(p < 0.001),并且 CRSsNP 患者比例最高(62.5%)。与其他组相比,受试者组 2 的 MBP、嗜酸性粒细胞和计算机断层扫描(CT)评分明显更高(p ≤ 0.05)。
使用市售免疫分析试剂盒进行无偏倚网络映射方法可揭示 3 种不同的组织细胞因子-趋化因子特征,可对 CRS 患者和对照进行表型分型。即使在数量有限的患者中,这些特征也很明显,可能有助于制定个体化治疗方案并优化结果。