Laboratory of Complex Genetics, Department of Human Genetics, KU Leuven, Herestraat 49 - box 610, 3000 Leuven, Belgium.
Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea.
Cells. 2019 Jun 4;8(6):535. doi: 10.3390/cells8060535.
Inflammatory bowel disease (IBD) is a heterogeneous disorder in terms of age at onset, clinical phenotypes, severity, disease course, and response to therapy. This underlines the need for predictive and precision medicine that can optimize diagnosis and disease management, provide more cost-effective strategies, and minimize the risk of adverse events. Ideally, we can leverage molecular profiling to predict the risk to develop IBD and disease progression. Despite substantial successes of genome-wide association studies in the identification of genetic variants affecting IBD susceptibility, molecular profiling of disease onset and progression as well as of treatment responses has lagged behind. Still, thanks to technological advances and good study designs, predicting phenotypes using genomics and transcriptomics in IBD has been rapidly evolving. In this review, we summarize the current status of prediction of disease risk, clinical course, and response to therapy based on clinical case presentations. We also discuss the potential and limitations of the currently used approaches.
炎症性肠病（IBD）在发病年龄、临床表型、严重程度、疾病过程和治疗反应等方面存在异质性。这凸显了需要预测性和精准医学，以优化诊断和疾病管理，提供更具成本效益的策略，并最大限度地降低不良事件的风险。理想情况下，我们可以利用分子谱分析来预测发生 IBD 和疾病进展的风险。尽管全基因组关联研究在确定影响 IBD 易感性的遗传变异方面取得了巨大成功，但疾病发病和进展以及治疗反应的分子谱分析却落后了。尽管如此，由于技术进步和良好的研究设计，使用基因组学和转录组学预测 IBD 的表型已经迅速发展。在这篇综述中，我们总结了基于临床病例介绍预测疾病风险、临床病程和治疗反应的现状。我们还讨论了目前使用的方法的潜力和局限性。
