Cognitive Phenotypes and Endophenotypes: Concepts and Criteria

内表型 表型 认知 心理学 遗传力 人口 神经科学 生物 计算生物学 进化生物学 医学 遗传学 环境卫生 基因
作者
Carrie E. Bearden,Anderson M. Winkler,Katherine H. Karlsgodt,Robert M. Bilder
出处
期刊:Innovations in cognitive neuroscience 卷期号:: 61-80 被引量:4
标识
DOI:10.1007/978-1-4614-3846-5_4
摘要

Despite major advances in neuroscience, existing treatments for neuropsychiatric syndromes have only limited effectiveness. Because existing diagnoses rely on heterogeneous clusters of symptoms that are not closely associated with direct drug targets, discovery of new treatments almost always occurs by chance. Conventional diagnostic phenotypes are marked by significant heterogeneity and overlap, calling into question the biological validity of these diagnostic categories. In this chapter, the authors review the value of quantitative traits for unraveling complex disease and discuss phenotypes, endophenotypes, biomarkers, and cognitive phenotypes in particular. They then explore the necessary and sufficient criteria for viable cognitive phenotypes, including reproducibility and heritability. Next, they explore the utility of endophenotypes for genetic mapping studies, before moving on to discuss the specificity of cognitive phenotypes and their association with categorical disease phenotypes, their relevance to biological mechanisms, cognitive and neuroanatomic phenotypes in population samples, successful utilization of endophenotypes in the study of non-psychiatric complex traits, feasibility of animal models, multivariate phenotype approaches, and end with a description of the endophenotype ranking value (ERV). The authors conclude that defining new phenotypes at a neural systems level, with links to specific molecular targets, could yield dramatic advances in neuropsychiatric therapeutics. To achieve this, the current characterization of neuropsychiatric disorders must be dramatically revised by focusing on discrete, continuously distributed phenotypes, indexed by quantitative assays, that can help bridge molecular and behavioral constructs.
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