1 Department of Animal Science, Biotechnical Faculty, University of Ljubljana , Domzale, Slovenia .
2 Laboratory for Clinical Immunology and Molecular Genetics, University Clinic of Respiratory and Allergic Diseases , Golnik, Slovenia .
OMICS. 2018 Jun;22(6):392-409. doi: 10.1089/omi.2018.0036.
Asthma is a common complex disorder and has been subject to intensive omics research for disease susceptibility and therapeutic innovation. Candidate biomarkers of asthma and its precision treatment demand that they stand the test of multiomics data triangulation before they can be prioritized for clinical applications. We classified the biomarkers of asthma after a search of the literature and based on whether or not a given biomarker candidate is reported in multiple omics platforms and methodologies, using PubMed and Web of Science, we identified omics studies of asthma conducted on diverse platforms using keywords, such as asthma, genomics, metabolomics, and epigenomics. We extracted data about asthma candidate biomarkers from 73 articles and developed a catalog of 190 potential asthma biomarkers (167 human, 23 animal data), comprising DNA loci, transcripts, proteins, metabolites, epimutations, and noncoding RNAs. The data were sorted according to 13 omics types: genomics, epigenomics, transcriptomics, proteomics, interactomics, metabolomics, ncRNAomics, glycomics, lipidomics, environmental omics, pharmacogenomics, phenomics, and integrative omics. Importantly, we found that 10 candidate biomarkers were apparent in at least two or more omics levels, thus promising potential for further biomarker research and development and precision medicine applications. This multiomics catalog reported herein for the first time contributes to future decision-making on prioritization of biomarkers and validation efforts for precision medicine in asthma. The findings may also facilitate meta-analyses and integrative omics studies in the future.
哮喘是一种常见的复杂疾病,一直是疾病易感性和治疗创新的组学研究的重点。哮喘及其精准治疗的候选生物标志物需要经过多组学数据三角测量的检验,才能优先考虑用于临床应用。我们在文献检索的基础上对哮喘的生物标志物进行了分类,并根据给定的生物标志物候选者是否在多个组学平台和方法中报告,使用 PubMed 和 Web of Science 来确定使用哮喘、基因组学、代谢组学和表观基因组学等关键词在不同平台上进行的哮喘组学研究。我们从 73 篇文章中提取了哮喘候选生物标志物的数据,并开发了一个包含 190 个潜在哮喘生物标志物的目录(167 个人类,23 个动物数据),包括 DNA 基因座、转录本、蛋白质、代谢物、表观突变和非编码 RNA。这些数据根据 13 种组学类型进行了分类:基因组学、表观基因组学、转录组学、蛋白质组学、相互作用组学、代谢组学、ncRNA 组学、糖组学、脂质组学、环境组学、药物基因组学、表型组学和综合组学。重要的是,我们发现有 10 个候选生物标志物至少在两种或更多的组学水平上显现出来,因此有进一步进行生物标志物研究和开发以及精准医学应用的潜力。本文首次报道的这个多组学目录有助于未来在哮喘精准医学中对生物标志物进行优先级排序和验证工作的决策。这些发现也可能为未来的荟萃分析和综合组学研究提供便利。