Background

Given the plethora of pathophysiologic mechanisms described in idiopathic pulmonary fibrosis (IPF), we hypothesize that the mechanisms driving fibrosis in IPF may be different from one patient to another.

Research Question

Do IPF endotypes exist and are they associated with outcome?

Study Design and Methods

Using a publicly available gene expression dataset retrieved from BAL samples of patients with IPF and control participants (GSE70867), we clustered IPF samples based on a dimension reduction algorithm specifically designed for -omics data, called DDR Tree. After clustering, gene set enrichment analysis was performed for functional annotation, associations with clinical variables and prognosis were investigated, and differences in transcriptional regulation were determined using motif enrichment analysis. The findings were validated in three independent publicly available gene expression datasets retrieved from IPF blood samples.

Results

One hundred seventy-six IPF samples from three centers were clustered in six IPF clusters, with distinct functional enrichment. Although clinical characteristics did not differ between the clusters, one cluster conferred worse sex-age-physiology score-corrected survival, whereas another showed a numeric trend toward worse survival (P = .08). The first was enriched for increased epithelial and innate and adaptive immunity signatures, whereas the other showed important telomere and mitochondrial dysfunction, loss of proteostasis, and increased myofibroblast signatures. The existence of these two endotypes, including the impact on survival of the immune endotype, was validated in three independent validation cohorts. Finally, we identified transcription factors regulating the expression of endotype-specific survival-associated genes.

Interpretation

Gene expression-based endotyping in IPF is feasible and can inform clinical evolution. As endotype-specific pathways and survival-associated transcription factors are identified, endotyping may open up the possibility of endotype-tailored therapy.

中文翻译：

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BAL 转录组表征具有预后影响的特发性肺纤维化内型

背景

鉴于特发性肺纤维化 (IPF) 中描述的过多病理生理机制，我们假设 IPF 中驱动纤维化的机制可能因患者而异。

研究问题

IPF 内型是否存在，它们与结果相关吗？

研究设计和方法

使用从 IPF 患者和对照参与者 (GSE70867) 的 BAL 样本中检索到的公开可用基因表达数据集，我们根据专门为组学数据设计的降维算法（称为 DDR 树）对 IPF 样本进行聚类。聚类后​​，对功能注释进行基因集富集分析，研究与临床变量和预后的关联，并使用基序富集分析确定转录调控的差异。这些发现在从 IPF 血液样本中检索到的三个独立的公开基因表达数据集中得到了验证。

结果

来自三个中心的 176 个 IPF 样本聚集在六个 IPF 簇中，具有明显的功能富集。尽管集群之间的临床特征没有差异，但一个集群的性别-年龄-生理评分校正生存率较差，而另一个集群则显示出生存率较差的数字趋势（P =.08）。第一个因增加的上皮和先天性和适应性免疫特征而丰富，而另一个则显示出重要的端粒和线粒体功能障碍、蛋白质稳态丧失和肌成纤维细胞特征增加。这两种内型的存在，包括对免疫内型存活的影响，在三个独立的验证队列中得到验证。最后，我们确定了调节内型特异性生存相关基因表达的转录因子。

解释

IPF 中基于基因表达的内分型是可行的，可以为临床进展提供信息。随着内型特异性途径和生存相关转录因子的确定，内型分析可能会开启内型定制治疗的可能性。