1 Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; and.
Ann Am Thorac Soc. 2013 Dec;10 Suppl:S197-205. doi: 10.1513/AnnalsATS.201302-035AW.
The complex biology of respiratory diseases such as asthma is feeding the discovery of various disease phenotypes. Although the clinical management of asthma phenotypes by using a single biomarker (e.g., sputum eosinophils) is successful, emerging evidence shows the requirement of multiscale, high-dimensional biological and clinical measurements to capture the complexity of various asthma phenotypes. High-throughput "omics" technologies, including transcriptomics, proteomics, lipidomics, and metabolomics, are increasingly standardized for biomarker discovery in asthma. The leading principle is obeying available guidelines on omics analysis, thereby strictly limiting false discovery. In this review we address the concept of transcriptomics using microarrays or next-generation RNA sequencing and their applications in asthma, highlighting the strengths and limitations of both techniques, and review metabolomics in exhaled air (breathomics) as a noninvasive alternative for sampling the airways directly. These developments will inevitably lead to the integration of molecular signatures in the phenotyping of asthma and other diseases.
哮喘等呼吸道疾病的复杂生物学正在促进各种疾病表型的发现。虽然使用单一生物标志物（例如痰嗜酸性粒细胞）来对哮喘表型进行临床管理是成功的，但新出现的证据表明，需要多尺度、高维的生物和临床测量来捕捉各种哮喘表型的复杂性。高通量“组学”技术，包括转录组学、蛋白质组学、脂质组学和代谢组学，越来越多地用于哮喘的生物标志物发现。主要原则是遵守有关组学分析的现有指南，从而严格限制假阳性发现。在这篇综述中，我们使用微阵列或下一代 RNA 测序来讨论转录组学的概念及其在哮喘中的应用，突出了这两种技术的优势和局限性，并回顾了呼出气（呼吸组学）中的代谢组学作为直接采样气道的非侵入性替代方法。这些发展将不可避免地导致分子特征在哮喘和其他疾病的表型分析中的整合。
