CRCNS: Ontology-Based Multi-Scale Integration of the Autism Phenome

CRCNS:基于本体论的自闭症现象多尺度整合

基本信息

  • 批准号:
    8067171
  • 负责人:
  • 金额:
    $ 32.39万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-09-04 至 2012-04-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Intellectual Merits of Proposed Activities With completion of the sequencing of the human genome, finding genetic variants that predispose and regulate brain-related disorders has increasingly become a significant area of collective neuroscience research. With advancements in genotyping technologies and analytic methodologies, investigators are making progress towards finding biological determinants of neuropathology. These efforts, however, have not been as rapid or as successful as those for non-mental disorders, and much still remains unknown about causal pathways between genes and complex traits in common mental disorders, such as schizophrenia, major depression, bipolar disorder and autism. An oft-cited reason for this lack of progress is the under use of intermediate phenotypes, or endophenotypes, which arguably provide higher genetic signal-to-noise ratios than the use of disease categories themselves. When researchers have incorporated endophenotypes into genetic analyses, the categories have not been based on a shared, well-defined and standardized set of definitions, making comparisons across studies and replication of prior findings problematic. Furthermore, it is unclear how categories of endophenotype measurements can be coherently integrated into multi-scale models of neuropathology. Phenomics - the systematic cataloging of phenotypes on a genome-wide scale - has emerged as a scientific endeavor within psychiatric genetics to address this challenge. A critical limitation to its advancement, and thus to its ability to support genomics studies of brain-related disease, is the lack of available methods and tools for modeling, managing, and reasoning about endophenotypes. We propose to overcome this major impediment through the development of the Phenologue, a novel knowledge-based technology that can support collaborative efforts to acquire, manage, and reason about a disease phenome given experimental data and published findings. The project's research objectives are to (1) develop an ontology of endophenotypes that maps brain connectivity, neural deficits, and genetic markers into a subject domain theory; (2) develop logic-based methods to encode and classify endophenotypes based on multi-scale measurements; (3) create tools to acquire new endophenotypes and annotate phenotype-genotype findings in online resources such as published literature; and (4) develop query-elicitation methods that can evaluate hypotheses about the subject domain theory of endophenotypes using deductive inference. These efforts will be undertaken through a close collaboration of researchers in psychiatric genetics, Semantic Web technologies, and first-order reasoning. Broader Impacts of Proposed Activities The research team will use the Phenologue to integrate data and knowledge from multiple lines of research on autism spectrum disorder. Thus, a broader objective of the activities proposed in this collaborative neuroscience project is to help investigators develop a coherent and formal understanding of the genetic underpinnings of this heterogeneous condition. The proposed project will build upon current NIH-funded efforts to create an autism ontology for the National Database for Autism Research (http://ndar.nih.gov), and the methods can be made accessible to users of this resource. The Principal Investigator will incorporate work from the proposed research on the use of ontologies and logic in scientific resource development into the teaching material of a graduate-level biomedical informatics course he offers at Stanford University. In addition, the investigative team will make software tools developed through the proposed project directly available to the other psychiatric genetics research communities, and will disseminate the proposed methods to similar informatics collaborations on brain-related disorders.
随着人类基因组测序的完成,发现易患和调节大脑相关疾病的遗传变异已日益成为集体神经科学研究的一个重要领域。随着基因分型技术和分析方法的进步,研究人员正在努力寻找神经病理学的生物学决定因素。然而,这些努力并不像在非精神障碍方面那样迅速或成功,而且在精神分裂症、重度抑郁症、双相情感障碍和自闭症等常见精神障碍中,基因和复杂特征之间的因果关系仍有很多未知之处。这种缺乏进展的一个经常被引用的原因是中间表型或内表型的使用不足,这可以说比使用疾病类别本身提供更高的遗传信噪比。当研究人员将内表型纳入遗传分析时,这些分类并没有基于一个共享的、定义明确的和标准化的定义集,这使得研究间的比较和先前发现的复制存在问题。此外,目前尚不清楚如何将内表型测量的类别连贯地整合到神经病理学的多尺度模型中。表型组学——在全基因组范围内对表型进行系统编目——已经成为精神病学遗传学中应对这一挑战的一项科学努力。对其发展的一个关键限制,从而对其支持脑相关疾病基因组学研究的能力的限制,是缺乏可用的方法和工具来建模,管理和推理内表型。我们建议通过开发物候学来克服这一主要障碍,物候学是一种基于知识的新技术,可以支持协作努力,根据实验数据和已发表的发现来获取、管理和推断疾病现象。该项目的研究目标是:(1)开发一个内表型本体论,将大脑连接、神经缺陷和遗传标记映射到一个主题领域理论中;(2)发展基于逻辑的方法,基于多尺度测量对内表型进行编码和分类;(3)创建工具以获取新的内表型,并对在线资源(如已发表的文献)中的表型-基因型发现进行注释;(4)发展查询-启发方法,利用演绎推理来评估关于内生表型主体领域理论的假设。这些努力将通过精神病学遗传学、语义网技术和一阶推理方面的研究人员的密切合作来进行。研究小组将使用物候仪来整合来自自闭症谱系障碍多个研究领域的数据和知识。因此,在这个神经科学合作项目中提出的活动的一个更广泛的目标是帮助研究人员对这种异质条件的遗传基础有一个连贯和正式的理解。提议的项目将建立在目前美国国立卫生研究院资助的为国家自闭症研究数据库(http://ndar.nih.gov)创建自闭症本体的努力基础上,该方法可以向该资源的用户开放。首席研究员将把本体论和逻辑在科学资源开发中的应用研究纳入他在斯坦福大学提供的研究生生物医学信息学课程的教材中。此外,调查小组将使通过拟议项目开发的软件工具直接提供给其他精神病学遗传学研究团体,并将拟议的方法传播给类似的脑相关疾病信息学合作。

项目成果

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AMARENDRA K. DAS其他文献

AMARENDRA K. DAS的其他文献

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{{ truncateString('AMARENDRA K. DAS', 18)}}的其他基金

CRCNS: Ontology-Based Multi-Scale Integration of the Autism Phenome
CRCNS:基于本体论的自闭症现象多尺度整合
  • 批准号:
    7778021
  • 财政年份:
    2009
  • 资助金额:
    $ 32.39万
  • 项目类别:
Open-Source Toolkit for Knowledge-Based Querying of Time-Oriented Data
用于基于知识的时间数据查询的开源工具包
  • 批准号:
    7849699
  • 财政年份:
    2009
  • 资助金额:
    $ 32.39万
  • 项目类别:
Open-Source Toolkit for Knowledge-Based Querying of Time-Oriented Data
用于基于知识的时间数据查询的开源工具包
  • 批准号:
    7654754
  • 财政年份:
    2009
  • 资助金额:
    $ 32.39万
  • 项目类别:
CRCNS: Ontology-Based Multi-Scale Integration of the Autism Phenome
CRCNS:基于本体论的自闭症现象多尺度整合
  • 批准号:
    7927177
  • 财政年份:
    2009
  • 资助金额:
    $ 32.39万
  • 项目类别:

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