Bilder Robert M, Sabb Fred W, Parker D Stott, Kalar Donald, Chu Wesley W, Fox Jared, Freimer Nelson B, Poldrack Russell A
Jane & Terry Semel Institute for Neuroscience & Human Behavior at UCLA, Los Angeles, CA 90095, USA.
Cogn Neuropsychiatry. 2009;14(4-5):419-50. doi: 10.1080/13546800902787180.
Now that genome-wide association studies (GWAS) are dominating the landscape of genetic research on neuropsychiatric syndromes, investigators are being faced with complexity on an unprecedented scale. It is now clear that phenomics, the systematic study of phenotypes on a genome-wide scale, comprises a rate-limiting step on the road to genomic discovery. To gain traction on the myriad paths leading from genomic variation to syndromal manifestations, informatics strategies must be deployed to navigate increasingly broad domains of knowledge and help researchers find the most important signals. The success of the Gene Ontology project suggests the potential benefits of developing schemata to represent higher levels of phenotypic expression. Challenges in cognitive ontology development include the lack of formal definitions of key concepts and relations among entities, the inconsistent use of terminology across investigators and time, and the fact that relations among cognitive concepts are not likely to be well represented by simple hierarchical "tree" structures. Because cognitive concept labels are labile, there is a need to represent empirical findings at the cognitive test indicator level. This level of description has greater consistency, and benefits from operational definitions of its concepts and relations to quantitative data. Considering cognitive test indicators as the foundation of cognitive ontologies carries several implications, including the likely utility of cognitive task taxonomies. The concept of cognitive "test speciation" is introduced to mark the evolution of paradigms sufficiently unique that their results cannot be "mated" productively with others in meta-analysis. Several projects have been initiated to develop cognitive ontologies at the Consortium for Neuropsychiatric Phenomics (www.phenomics.ucla.edu), in the hope that these ultimately will enable more effective collaboration, and facilitate connections of information about cognitive phenotypes to other levels of biological knowledge. Several free web applications are available already to support examination and visualisation of cognitive concepts in the literature (PubGraph, PubAtlas, PubBrain) and to aid collaborative development of cognitive ontologies (Phenowiki and the Cognitive Atlas). It is hoped that these tools will help formalise inference about cognitive concepts in behavioural and neuroimaging studies, and facilitate discovery of the genetic bases of both healthy cognition and cognitive disorders.
鉴于全基因组关联研究（GWAS）在神经精神综合征的遗传学研究领域占据主导地位，研究人员正面临着前所未有的复杂性。现在很清楚，表型组学，即在全基因组范围内对表型进行的系统研究，是基因组发现道路上的一个限速步骤。为了在从基因组变异到综合征表现的众多路径上取得进展，必须部署信息学策略，以驾驭日益广泛的知识领域，并帮助研究人员找到最重要的信号。基因本体论项目的成功表明了开发模式以表示更高层次表型表达的潜在益处。认知本体论发展中的挑战包括关键概念和实体间关系缺乏形式化定义、研究人员在不同时间对术语的使用不一致，以及认知概念之间的关系不太可能通过简单的层次“树”结构得到很好的表示。由于认知概念标签不稳定，有必要在认知测试指标层面来表示实证研究结果。这种描述层面具有更高的一致性，并受益于其概念和与定量数据关系的操作定义。将认知测试指标视为认知本体论的基础有几个含义，包括认知任务分类法可能具有的效用。引入认知“测试物种形成”的概念，以标记那些范式的演变，这些范式足够独特，以至于其结果无法在荟萃分析中与其他结果有效“匹配”。神经精神表型组学联盟（www.phenomics.ucla.edu）已经启动了几个项目来开发认知本体论，希望这些最终将实现更有效的合作，并促进关于认知表型的信息与其他生物知识层面的联系。已经有几个免费的网络应用程序可用于支持对文献中认知概念的检查和可视化（PubGraph、PubAtlas、PubBrain），并协助认知本体论的合作开发（Phenowiki和认知图谱）。希望这些工具将有助于使行为和神经影像学研究中关于认知概念的推理形式化，并促进发现健康认知和认知障碍的遗传基础。
