Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue.
Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue.
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DOI：
10.1186/s12890-023-02389-5
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发表时间：
2023-04-11
影响因子：
3.1
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中科院分区：
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慢性阻塞性肺疾病（COPD）是一种高度病态和异质性的疾病。虽然COPD是由肺活量测定来定义的，但在肺活量测定正常的吸烟者中可以看到许多COPD特征。COPD和COPD异质性在肺组织组学中被捕获的程度尚不清楚。我们聚集了78个肺功能正常或严重COPD的前吸烟者肺组织样本的基因表达和甲基化数据。我们采用了两种整合组学聚类方法：(1)相似网络融合（SNF）和(2)基于熵的共识聚类（ECC）。SNF聚类在COPD病例中所占的百分比上无显著差异（48.8%比68.6%,p = 0.13），但在预测的1秒内强制呼气量（FEV1）中位数上有差异（82比31，p = 0.017）。相比之下，ECC聚类显示出更强的COPD病例状态分离证据（48.2%对81.8%,p = 0.013），并且预测中位数FEV1%的分层相似（82对30.5,p = 0.0059）。同时使用基因表达和甲基化的ECC聚类与仅使用甲基化数据生成的ECC聚类解决方案相同。这两种方法都选择了具有白细胞介素信号和淋巴细胞与非淋巴细胞之间免疫调节相互作用富集差异表达转录物的簇。从肺组织中整合的基因表达和甲基化数据进行的无监督聚类分析显示，尽管在可能导致COPD相关病理和异质性的途径中富集，但聚类与COPD有适度的一致性。在线版本包含补充材料，可在10.1186/s12890-023-02389-5获得。
Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known. We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC). SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells. Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity. The online version contains supplementary material available at 10.1186/s12890-023-02389-5.