Department of Surgery, The University of Auckland, Auckland, New Zealand.
School of Biological Science, Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand.
mSphere. 2019 Feb 6;4(1):e00679-18. doi: 10.1128/mSphere.00679-18.
Chronic rhinosinusitis (CRS) is a heterogeneous condition characterized by persistent sinus inflammation and microbial dysbiosis. This study aimed to identify clinically relevant subgroups of CRS patients based on distinct microbial signatures, with a comparison to the commonly used phenotypic subgrouping approach. The underlying drivers of these distinct microbial clusters were also investigated, together with associations with epithelial barrier integrity. Sinus biopsy specimens were collected from CRS patients ( = 23) and disease controls ( = 8). The expression of 42 tight junction genes was evaluated using quantitative PCR together with microbiota analysis and immunohistochemistry for measuring mucosal integrity and inflammation. CRS patients clustered into two distinct microbial subgroups using probabilistic modelling Dirichlet (DC) multinomial mixtures. DC1 exhibited significantly reduced bacterial diversity and increased dispersion and was dominated by , , and DC2 had significantly elevated B cells and incidences of nasal polyps and higher numbers of , , , , and In addition, each DC exhibited distinct tight junction gene and protein expression profiles compared with those of controls. Stratifying CRS patients based on clinical phenotypic subtypes (absence or presence of nasal polyps [CRSsNP or CRSwNP, respectively] or with cystic fibrosis [CRSwCF]) accounted for a larger proportion of the variation in the microbial data set than with DC groupings. However, no significant differences between CRSsNP and CRSwNP cohorts were observed for inflammatory markers, beta-dispersion, and alpha-diversity measures. In conclusion, both approaches used for stratifying CRS patients had benefits and pitfalls, but DC clustering provided greater resolution when studying tight junction impairment. Future studies in CRS should give careful consideration to the patient subtyping approach used. Chronic rhinosinusitis (CRS) is a major human health problem that significantly reduces quality of life. While various microbes have been implicated, there is no clear understanding of the role they play in CRS pathogenesis. Another equally important observation made for CRS patients is that the epithelial barrier in the sinonasal cavity is defective. Finding a robust approach to subtype CRS patients would be the first step toward unravelling the pathogenesis of this heterogeneous condition. Previous work has explored stratification based on the clinical presentation of the disease (with or without polyps), inflammatory markers, pathology, or microbial composition. Comparisons between the different stratification approaches used in these studies have not been possible due to the different cohorts, analytical methods, or sample sites used. In this study, two approaches for subtyping CRS patients were compared, and the underlying drivers of the heterogeneity in CRS were also explored.
慢性鼻-鼻窦炎(CRS)是一种以持续性鼻窦炎症和微生物失调为特征的异质性疾病。本研究旨在根据不同的微生物特征,为 CRS 患者确定具有临床意义的亚群,并与常用的表型亚群划分方法进行比较。还研究了这些不同微生物群的潜在驱动因素,以及与上皮屏障完整性的关联。从 CRS 患者( = 23)和疾病对照( = 8)中采集鼻窦活检标本。使用定量 PCR 评估 42 个紧密连接基因的表达,同时进行微生物分析和免疫组织化学检测,以测量黏膜完整性和炎症。使用概率模型 Dirichlet(DC)多项分布混合物对 CRS 患者进行聚类分析,将其分为两个不同的微生物亚群。DC1 表现出显著降低的细菌多样性和增加的分散性,并且以 、 和 为主。DC2 具有显著升高的 B 细胞和鼻息肉的发生率,并且具有更高数量的 、 、 、 和 。此外,与对照组相比,每个 DC 都表现出不同的紧密连接基因和蛋白表达谱。基于临床表型亚型(是否存在鼻息肉[CRSsNP 或 CRSwNP 分别]或囊性纤维化[CRSwCF])对 CRS 患者进行分层,比基于 DC 分组可以解释更多的微生物数据集的变异性。然而,CRSsNP 和 CRSwNP 队列之间在炎症标志物、β-分散和 α-多样性测量方面没有观察到显著差异。总之,用于 CRS 患者分层的两种方法都有优点和缺点,但 DC 聚类在研究紧密连接损伤时提供了更高的分辨率。未来的 CRS 研究应仔细考虑所使用的患者亚群划分方法。慢性鼻-鼻窦炎(CRS)是一个重大的人类健康问题,显著降低了生活质量。尽管已经涉及到各种微生物,但它们在 CRS 发病机制中的作用仍不清楚。另一个同样重要的观察结果是,鼻窦腔内的上皮屏障存在缺陷。找到一种稳健的方法来对 CRS 患者进行亚群划分将是揭示这种异质性疾病发病机制的第一步。以前的工作已经探索了基于疾病的临床表现(有或无息肉)、炎症标志物、病理学或微生物组成的分层方法。由于使用的队列、分析方法或样本部位不同,这些研究中使用的不同分层方法之间的比较是不可能的。在这项研究中,比较了两种用于 CRS 患者分类的方法,并探索了 CRS 异质性的潜在驱动因素。