Micropublications for Automating Genome Sequence Variant Interpretation from Medical Literature

项目总结 对临床决策的基因组变异的准确和有效的解释是基于Ready的 从医学文献中获取和提取信息。潜在相关的绝对数量 在这一过程中必须审查的物品对确保准确性和 临床解释的重复性，因为它耗时，容易出错，并高度依赖于用户。对这件事 最后，我们开发了大师基因组搜索引擎-一个商业数据库，自动 通过系统地为数百万人编制索引来组织来自医学文献的疾病、基因和变异信息 科学文章。来自100多个不同国家的9100多名变种科学家使用MASHING来 更快地在临床环境中解释基因变异。在该项目的第一阶段，我们开发并测试了 MasterMind内的微出版平台，集合了文学精选和人口频率 数据，致病性的计算预测，以及自动ACMG/AMP分类，改善了 变异解释的速度提高了70%以上，并将这些结果的灵敏度提高了2-20倍。这个 本提案寻求在第一阶段成功的基础上，通过1)将微出版平台整合到 负责迁移协作功能，以社区为基础对不同解释进行评估；2) 优化和改进条款的自动变体口译/优先排序，并实施严格的 质量保证过程；以及3)使用这些改进来精选所有基因中所有变种的所有证据 组成整个人类基因组，从临床外显子组开始。预先管理的基因组的整合 微出版平台中的数据将导致MasterMind Enterprise，允许立即和准确 全基因组变异解释，在与来源的互动点实时协作管理 材料(即单个参考文献)。这项工作将缓解困扰其他大型项目的可重复性挑战 众包项目，包括由NIH的ClinVar和QIAGEN的HGMD等组织承担的项目。在……里面 此外，我们的新方法不会受到较差的敏感性，因为它依赖于全面的医疗来源 基于遗传内容的预先注释的文献。这项工作将使不同解释的戏剧性扩展成为可能 活动，并允许在两年内完整和准确地管理整个人类基因组-这是一项壮举 无法利用目前的人工方法进行变式解释。策划者进取号将成为 基因组学行业的革命性成果，并将代表着自然的下一步，以取得的成就为基础 由人类基因组计划提供，并降低了下一代测序的成本。它将极大地 提高临床诊断率和准确率，特别是在缺乏遗传证据的罕见疾病中 通常会导致严重延迟和不准确的诊断。此外，它还将允许制药业 开发更成功的靶向治疗，设计更具包容性的临床试验，以及更多 可靠地确定将从治疗干预中受益的患者。 [字数-468；行数-30]

PROJECT SUMMARY Accurate and efficient interpretation of genomic variants for clinical decision making is predicated on ready access to and extraction of information from the medical literature. The sheer number of potentially relevant articles that must be examined during this process poses a significant challenge in ensuring the accuracy and reproducibility of clinical interpretation as it is time-consuming, error-prone, and highly user-dependent. To this end, we have developed the Mastermind Genomic Search Engine - a commercial database that automatically organizes disease, gene and variant information from the medical literature by systematically indexing millions of scientific articles. Mastermind is used by over 9,100 variant scientists in more than 100 different countries to more quickly interpret genetic variants in clinical settings. In Phase I of this project, we developed and tested a micropublication platform within Mastermind that assembles literature curation along with population frequency data, computational predictions of pathogenicity, and automated ACMG/AMP classifications that improves the speed of variant interpretation by more than 70% and increases the sensitivity of these results by 2-20x. The present proposal seeks to build on the success of Phase I by 1) integrating the micropublication platform into Mastermind with migration of collaborative features for community-based evaluation of variant interpretations; 2) optimizing and improving automated variant interpretation/prioritization of articles and implementing a rigorous quality assurance process; and 3) using these improvements to curate all evidence in all variants in all genes comprising the entire human genome, beginning with the clinical exome. Integration of the pre-curated genome data in the micropublication platform will result in Mastermind Enterprise, allowing for immediate and accurate genome-wide variant interpretations with collaborative curation in real-time at the point of interaction with source material (i.e. individual references). This work will mitigate reproducibility challenges plaguing other large-scale crowd-sourced projects, including those undertaken by groups like NIH’s ClinVar and QIAGEN’s HGMD. In addition, our novel approach will not suffer from poor sensitivity as it relies on a comprehensive source of medical literature pre-annotated based on genetic content. This work will permit dramatic scaling of variant interpretation activities and allow for complete and accurate curation of the entire human genome within 2 years – a feat that could not be completed utilizing current manual methods for variant interpretation. Mastermind Enterprise will be revolutionary in the genomics industry and will represent a natural next step to build on the achievements provided by the Human Genome Project and the reduced cost of next-generation sequencing. It will substantially improve diagnostic rates and accuracy in the clinic, especially in rare disease, where a lack of genetic evidence often results in severely delayed and inaccurate diagnoses. Additionally, it will allow the pharmaceutical industry to develop more successful targeted therapies and to design more inclusive clinical trials as well as to more reliably identify patients who would benefit from therapeutic intervention. [Word count – 468; Line count – 30]