Braff David L
University of California San Diego, Department of Psychiatry, 9500 Gilman Drive, La Jolla, CA 92093-0804, United States.
Schizophr Res. 2015 Apr;163(1-3):1-8. doi: 10.1016/j.schres.2015.02.007. Epub 2015 Mar 18.
Endophenotypes provide a powerful neurobiological platform from which we can understand the genomic and neural substrates of schizophrenia and other common complex neuropsychiatric disorders. The Consortium on the Genetics of Schizophrenia (COGS) has conducted multisite studies on carefully selected key neurocognitive and neurophysiological endophenotypes in 300 families (COGS-1) and then in a follow up multisite case-control study of 2471 subjects (COGS-2). Endophenotypes are neurobiologically informed quantitative measures that show deficits in probands and their first degree relatives. They are more amenable to statistical analysis than are "fuzzy" qualitative clinical traits or confoundingly heterogeneous diagnostic categories. Endophenotypes are also viewed as uniquely informative in traditional diagnosis-based as well as emerging NIMH Research Domain (RDoC) contexts, offering a bridge between the two approaches to psychopathology classification and research. Endo- or intermediate phenotypes are heritable, and in the COGS-1 cohort their level of heritability is in the same range as is the heritability of schizophrenia itself, using the same statistical methods and subjects to assess both. Because we can demonstrate endophenotypes link to both gene networks and neural circuits on the one hand and also to real-life function, endophenotypes provide a critically important bridge for "connecting the dots" between genes, cells, circuits, information processing, neurocognition and functional impairment and personalized treatment selection in schizophrenia patients. By connecting schizophrenia risk genes with neurobiologically informed endophenotypes, and via the use of association, linkage, sequencing, stem cell and other strategies, we can provide our field with new neurobiologically informed information in our efforts to understand and treat schizophrenia. Evolving views, data and new analytic strategies about schizophrenia risk, pathology and treatment are described in this Viewpoint and in the accompanying Special Issue reports.
内表型提供了一个强大的神经生物学平台，借此我们能够理解精神分裂症及其他常见复杂神经精神疾病的基因组和神经学基础。精神分裂症遗传学联盟（COGS）对300个家庭中精心挑选的关键神经认知和神经生理学内表型进行了多中心研究（COGS-1），随后又对2471名受试者进行了多中心病例对照随访研究（COGS-2）。内表型是基于神经生物学的定量测量指标，在先证者及其一级亲属中表现出缺陷。相较于“模糊”的定性临床特征或混杂的异质性诊断类别，它们更易于进行统计分析。在内表型在传统的基于诊断的以及新兴的美国国立精神卫生研究所研究领域标准（RDoC）背景下也被视为具有独特的信息价值，为精神病理学分类和研究的两种方法之间搭建了一座桥梁。内表型或中间表型具有遗传性，在COGS-1队列中，使用相同的统计方法和受试者来评估，其内表型的遗传度与精神分裂症本身的遗传度处于同一范围。由于我们能够证明内表型一方面与基因网络和神经回路相关，另一方面也与现实生活功能相关，因此内表型为精神分裂症患者在基因、细胞、回路、信息处理、神经认知和功能损害以及个性化治疗选择之间“连点成线”提供了至关重要的桥梁。通过将精神分裂症风险基因与基于神经生物学的内表型联系起来，并运用关联、连锁、测序、干细胞及其他策略，我们能够在努力理解和治疗精神分裂症的过程中为该领域提供基于神经生物学的新信息。本观点文章以及随附的特刊报告中描述了关于精神分裂症风险、病理和治疗的不断演变的观点、数据和新的分析策略。
