Ota Mineto, Fujio Keishi
Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Inflamm Regen. 2021 Aug 1;41(1):23. doi: 10.1186/s41232-021-00173-8.
Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.
高通量测序技术的最新创新极大地推动了科学研究。因此，现在能够同时在多个层面捕获样本的全面概况，包括基因组、表观基因组和转录组。将这类丰富信息应用于临床具有重大的社会意义。对于某些性状，如心血管疾病，尝试将组学数据集应用于临床实践以预测疾病风险已经取得了有希望的结果，尽管在免疫介导疾病方面仍在进行中。多项研究试图利用基因组、转录组或临床信息预测免疫介导疾病的治疗反应，显示出各种可能的指标。为了更好地预测免疫介导疾病的治疗反应或疾病结局，将多层信息结合在一起可能会增强预测能力。此外，为了从海量数据中高效提取有意义的信息，基因组功能的高质量注释也至关重要。在这篇综述中，我们讨论了到目前为止多组学方法在免疫介导疾病方面取得的成果以及未来的方向。
