Computational system to predict novel genetic disease associations

预测新型遗传疾病关联的计算系统

基本信息

批准号：
7921370
负责人：
MARTIN G REESE
金额：
$ 26.29万
依托单位：
FABRIC GENOMICS INC.
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-05-03 至 2012-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7921370
关键词：
Address Agreement Algorithms Alleles Amino Acid Sequence Amino Acid Substitution Area Base Sequence Bioinformatics Biological Biological Markers Biological Process Biotechnology Businesses Candidate Disease Gene Cardiovascular Diseases Cardiovascular system Caring Clinical Clinical Research Code Collection Complement Computer Simulation Computer software Custom DNA Data Databases Diagnostic Disease Disease Association Effectiveness Etiology Evaluation Exons Future Genes Genetic Genetic Markers Genetic Polymorphism Genetic Research Genetic Variation Genome Genomics Genotype Goals Hereditary Disease Homologous Gene Human Human Gene Mapping In Vitro Individual Informatics Intellectual Property Knowledge Lead Legal patent Licensing Link MeSH Thesaurus Medical Medicine Methodology Methods Mining Molecular Diagnostic Testing Myocardial Infarction Natural Language Processing Neighborhoods Odds Ratio Online Mendelian Inheritance In Man Ontology Organism Outcome Paper Pathway interactions Patients Peptide Sequence Determination Performance Phase Phenotype Play Positioning Attribute Prevalence Preventive Procedures Process Proteins Public Health Research Research Infrastructure Research Personnel Risk Role Running Science Sequence Homology Shapes Slice Small Business Innovation Research Grant Staging Symptoms System Techniques Technology Testing Text Validation Variant Work abstracting base case control clinically relevant computerized tools data mining database of Genotypes and Phenotypes design expectation genetic association genome-wide high risk human disease improved information processing insight knowledge base member novel novel marker paralogous gene phase 2 study prototype public health relevance research clinical testing research study technology development therapeutic development tool validation studies

项目摘要

DESCRIPTION (provided by applicant): High-throughput genotyping, expression, and sequencing technologies and the development of increasingly sophisticated methods for predicting gene-disease interactions have given the new field of genomic-based personalized medicine a wealth of data: more, in fact, than can easily be processed and interpreted. Omicia is in the business of developing computational tools and diagnostics in the field of personalized medicine for cardiovascular disease (CVD). As part of that effort we are developing a software infrastructure that uses these abundant data to identify and prioritize candidate genes and their sequence variations for clinical evaluation. The research proposed in this application has three aims. In Phase II, we will enhance and optimize Omicia's Gene Inference System (GIS), prototyped during the SBIR Phase I project. In Phase II we will add additional capabilities to its candidate gene identification methods. This will build upon the Omicia Disease Genes (ODG) ontology built in Phase I, and add pathway and protein-interaction data and include "top" candidates from external publicaly-available clinical studies. In Aim 2, we will enhance the ability of GIS to prioritize sequence variations by improving our novel paralogous-gene variation identification algorithm (iDIP) and by integrating existing amino-acid substitution (AAS) methods. By running these algorithms over all known human genes via dbSNP, we expect to identify a list of candidate variations that will be evaluated in Aim 3 including an in vitro experiment. The goal of Aim 3 is to test the gene- and variant-predictive power of GIS and to compare it to other selection methods. The clinical study will be a single-stage case control design to test the "top" variant candidates from Aims 1 & 2 and compare the potential association to well-established genetic markers for the risk of myocardial infarction (MI). With approximately 700 cases and 700 matched controls, our association study will be well powered to test our predicted functional markers for MI. The GIS infrastructure is an integral part of the commercial workflow of Omicia, and will form the basis of the product pipeline. As such, it will serve as licensable commercial technology for the company by helping other biotechnology companies to develop their genetic biomarkers for diagnostic and therapeutic developments (theranostics). In addition, any novel variants drawn from this Phase II study will be licensable and exploitable intellectual property, useful both as the basis for future products in our internal pipeline, as well as potentially valuable additions to our patent portfolio. The Phase II goals of enhancing and clinically validating GIS serve three purposes: proving our methodology as applied to CVD and opening the door to applications in other disease areas; showcasing GIS as a key technology for managing complexity in the post-genomic era and providing clinically-relevant insights; and finally, potentially identifying valuable IP in the form of novel genetic markers for MI. PUBLIC HEALTH RELEVANCE: The outcome of this project will be an evaluated gene inference system (GIS) for identifying gene-disease interactions, with a focus in the area of cardiovascular disease (CVD). This system will be used as part of the Omicia product pipeline, and can also be licensed to third parties. In addition, any novel genetic markers identified as part of the validation study will themselves be valuable additions to the Omicia product and IP portfolio. Omicia's goal is to provide content and analysis tools for molecular diagnostic tests for cardiovascular conditions, with the promise of identifying patients at high risk to enable them to begin preventive care before symptoms appear. Given the prevalence of CVD in the developed world, these products are potentially a great boon to public health, as well as being significant commercial opportunities.

描述（由申请人提供）：高通量基因分型，表达和测序技术以及越来越复杂的方法来预测基因 - 疾病相互作用的越来越复杂的方法，使基于基因组的个性化医学的新领域具有大量的数据：实际上，更多，实际上，可以处理和解释更多。 Omicia从事个性化医学领域的计算工具和诊断性心血管疾病（CVD）的业务。作为这项工作的一部分，我们正在开发一种软件基础架构，该软件基础架构使用这些丰富的数据来识别和优先考虑候选基因及其序列变化以进行临床评估。本应用程序中提出的研究具有三个目标。在第二阶段，我们将增强和优化Omicia的基因推理系统（GIS），该系统在SBIR I期项目期间进行了原型。在第二阶段，我们将在其候选基因识别方法中添加其他功能。这将建立在第I阶段建立的Omicia疾病基因（ODG）本体论的基础上，并添加途径和蛋白质相互作用数据，并包括来自外部公开可用的临床研究的“顶级”候选者。在AIM 2中，我们将通过改善我们新颖的寄生虫变化识别算法（IDIP）以及整合现有的氨基酸替代（AAS）方法来增强GIS优先级序列变化的能力。通过通过DBSNP在所有已知的人类基因上运行这些算法，我们希望确定将在AIM 3中评估的候选变化列表，包括体外实验。目标3的目的是测试GIS的基因和变体预测能力，并将其与其他选择方法进行比较。临床研究将是一种单级病例控制设计，可测试AIMS 1和2的“顶部”候选者，并将潜在的关联与已建立的遗传标记物进行比较，以使心肌梗塞（MI）的风险。在大约700例病例和700个匹配的对照中，我们的协会研究将有能力测试我们预测的MI功能标记。 GIS基础架构是Omicia商业工作流程的组成部分，并将构成产品管道的基础。因此，它将通过帮助其他生物技术公司开发其遗传生物标志物来作为诊断和治疗发展（TheranoStics）来充当公司的可授权商业技术。此外，从这一第二阶段研究中汲取的任何新型变体都将是有许可和可利用的知识产权，这既可以作为我们内部管道中未来产品的基础，也是对我们的专利组合的潜在有价值的补充。增强和临床验证GIS的II期目标具有三个目的：证明我们适用于CVD的方法，并在其他疾病地区开放了应用；将GIS展示为在后总部时期管理复杂性并提供与临床上相关的见解的关键技术；最后，有可能以新型MI遗传标记的形式识别有价值的IP。公共卫生相关性：该项目的结果将是评估的基因推理系统（GIS），用于识别基因 - 疾病相互作用，重点是心血管疾病（CVD）。该系统将被用作Omicia产品管道的一部分，也可以将其许可给第三方。此外，任何确定为验证研究一部分的新型遗传标记本身将是Omicia产品和IP组合的宝贵补充。 Omicia的目标是为心血管疾病的分子诊断测试提供内容和分析工具，并有望识别有高风险的患者，使他们能够在症状出现之前开始预防性护理。鉴于发达国家中CVD的流行率，这些产品可能对公共卫生也是一个巨大的恩惠，并且是巨大的商业机会。