Tools for Normalizing and Interpreting the Clinical Actionability of Genomic Variants

项目摘要/摘要 高通量、低成本测序的出现改变了生物医学研究的格局 通过极大地扩展我们审问人类基因组序列的能力。因此，在那里 描述特定基因组变异的作用及其影响的生物医学文献激增 关于人类疾病的。这些进展正在将测序引入临床，以塑造临床实践 患者的基因组内容，一种俗称为基因组或精确医学的范例。留下来的 在精准医学时代，充分发挥我们的潜力有许多障碍。其中有一位公认的 需要强大的、精心设计的系统来提供关于基因组变异及其在 疾病。理想情况下，这样的系统将提供与 患者独特的基因组内容。 实现精确医学的早期瓶颈是，尽管有大量的文献和几个 已经建立了定义药物和基因之间相互作用的知识库，跨它们的查询是 极具挑战性。为满足这一需要，药物-基因相互作用数据库(DGIdb，dgidb.org) 发展起来的。通过自动处理和人工管理的组合，药物与基因的相互作用 信息是从这些不同的数据来源收集、组织和连接(标准化)的 通过用户友好的搜索界面和应用程序编程接口(API)输入数据库。 然而，将跨资源的药物和药物-基因相互作用的概念联系起来仍然是一个极具挑战性的问题 任务，以及聚集的药物-基因相互作用也很难用一种突出效用的方式来表示 收集到的精准医学方面的知识。这项建议旨在提高我们实现正常化的能力 并解释与患者基因组变异相对应的药物-基因相互作用。 我们将通过两个具体目标实现这一目标。首先，将改进DGIdb归一化例程 通过纳入新的内容和功能。其中，DGIdb将支持药物收集， 包括联合疗法和药物课程。此外，DGIdb将有新的社区提交和 管理功能，允许用户将新知识合并到数据库中。第二，变种 将创建解释聚合器数据库(VIAdb)，以标准化几个不同的 资料来源主要集中在基因组变异的临床解释上。VIAdb将作为一个独立的网络运行 工具和API，并将作为对DGIdb的相关解释的来源。最后，我们将开发技术 用于自动识别药物-基因相互作用和变体解释共识，以协助社区 策展工作。如果成功，这项研究将提高各种解释的广度和一致性，并 精准医学努力的药物-基因相互作用。

PROJECT SUMMARY/ABSTRACT The availability of high-throughput, low-cost sequencing has transformed the landscape of biomedical research by dramatically expanding our capacity to interrogate the sequence of the human genome. Consequently, there has been an explosion of biomedical literature describing the role of specific genomic variants and their impact on human diseases. These advances are bringing sequencing into the clinic to shape clinical practice from the patient’s genomic content, a paradigm colloquially referred to as genomic or precision medicine. There remain many obstacles to fully realizing our potential in the era of precision medicine. Among them is a recognized need for robust, well-engineered systems that provide knowledge about genomic variants and their role in disease. Ideally, such systems would provide a comprehensive summary of all knowledge that is relevant to the patient’s unique genomic content. An early bottleneck to realizing precision medicine was that, despite the substantial literature and several established knowledgebases that define interactions between drugs and genes, querying across them was extremely challenging. In response to this need, the Drug-Gene Interaction database (DGIdb, dgidb.org) was developed. Through a combination of automated processing and manual curation, drug-gene interaction information was collected, structured, and connected (normalized) from these diverse sources of data and entered into a database with a user-friendly search interface and an application programming interface (API). However, linking drug and drug-gene interaction concepts across resources remains an extremely challenging task, and aggregated drug-gene interactions are also challenging to represent in a way that highlights the utility of the collected knowledge for precision medicine efforts. This proposal seeks to improve our ability to normalize and interpret drug-gene interactions corresponding to patient genomic variants. We will achieve this goal through two specific aims. First, the DGIdb normalization routines will be improved through incorporation of new content and features. Among these, the DGIdb will support collections of drugs, including combination therapies and drug classes. Also, the DGIdb will have new community submission and curation features, allowing users to incorporate new knowledge into the database. Second, the Variant Interpretation Aggregator database (VIAdb) will be created to normalize knowledge across several disparate sources focused on the clinical interpretations of genomic variants. The VIAdb will operate as a stand-alone web tool and API and will behave as a source of relevant interpretations to DGIdb. Finally, we will develop techniques for automated identification of drug-gene interactions and variant interpretation consensus to assist community curation efforts. If successful, this research will improve breadth and consistency of variant interpretations and drug-gene interactions for precision medicine efforts.