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肺纤维化中细胞状态变化与外周蛋白生物标志物的综合分析。

Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers.

机构信息

Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum München, Member of the German Center for Lung Research (DZL), Munich, Germany.

Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany.

出版信息

EMBO Mol Med. 2021 Apr 9;13(4):e12871. doi: 10.15252/emmm.202012871. Epub 2021 Mar 2.

DOI:10.15252/emmm.202012871
PMID:33650774
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8033531/
Abstract

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type-2 epithelial cell health status in lavage fluid and plasma. Using cross-modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.

摘要

目前尚不清楚病变器官中细胞状态变化与外周蛋白特征之间的对应关系。在这里,我们生成并整合了来自多个大型肺纤维化患者队列的单细胞转录组学和蛋白质组学数据。整合了三个独立队列的 233638 个单细胞转录组(n=61),使我们能够得出细胞类型比例的变化和肺纤维化中 45 种细胞类型中改变的稳健核心基因集。对肺灌洗液(n=124)和血浆(n=141)蛋白质组的质谱分析确定了与诊断、肺功能和损伤状态相关的独特蛋白质特征。一种新型的 SSTR2+周细胞状态与疾病严重程度相关,并在灌洗液中通过补体调节因子 CFHR1 的水平升高来反映。我们进一步发现 CRTAC1 是灌洗液和血浆中肺泡型 2 上皮细胞健康状况的生物标志物。使用跨模态分析和机器学习,我们确定了生物标志物的细胞来源,并证明了模态之间的信息传递可以正确预测疾病状态,这表明通过对体液蛋白质组进行纵向采样进行临床细胞状态监测是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7032/8033531/9af27649f334/EMMM-13-e12871-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7032/8033531/c5e93d2b8ff8/EMMM-13-e12871-g010.jpg
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