Greenwood Tiffany A, Shutes-David Andrew, Tsuang Debby W
Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.
Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA 98108, USA.
J Psychiatr Brain Sci. 2019;4(2). doi: 10.20900/jpbs.20190005. Epub 2019 Mar 13.
Schizophrenia (SZ) is a severe psychotic disorder that is highly heritable and common in the general population. The genetic heterogeneity of SZ is substantial, with contributions from common, rare, and variants, in addition to environmental factors. Large genome-wide association studies have detected many variants that are associated with SZ, yet the pathways by which these variants influence risk remain largely unknown. SZ is also clinically heterogeneous, with patients exhibiting a broad range of deficits and symptom severity that vary over the course of illness and treatment, which has complicated efforts to identify risk variants. However, the underlying brain dysfunction forms a more stable trait marker that quantitative neurocognitive and neurophysiological endophenotypes may be able to objectively measure. These endophenotypes are less likely to be heterogeneous than the disorder and provide a neurobiological context to detect risk variants and underlying pathways among genes associated with SZ diagnosis. Furthermore, many endophenotypes are translational into animal model systems, allowing for direct evaluation of the neural circuit dysfunctions and neurobiological substrates. We review a selection of the most promising SZ endophenotypes, including prepulse inhibition, mismatch negativity, oculomotor antisaccade, letter-number sequencing, and continuous performance tests. We also highlight recent findings from large consortia that suggest the potential role of genes, particularly in the neuregulin and glutamate pathways, in several of these endophenotypes. Although endophenotypes require additional time and effort to assess, the insight into the underlying neurobiology that they provide may ultimately reveal the underlying genetic architecture for SZ and suggest novel treatment targets.
精神分裂症(SZ)是一种严重的精神障碍,具有高度遗传性且在普通人群中较为常见。SZ的遗传异质性很大,除环境因素外,还受到常见、罕见和变异因素的影响。大规模全基因组关联研究已经检测到许多与SZ相关的变异,但这些变异影响风险的途径在很大程度上仍不清楚。SZ在临床上也具有异质性,患者表现出广泛的缺陷和症状严重程度,且在疾病过程和治疗过程中会有所变化,这使得识别风险变异的工作变得复杂。然而,潜在的脑功能障碍形成了一种更稳定的特征标记,定量神经认知和神经生理内表型可能能够客观地测量。这些内表型比该疾病更不容易出现异质性,并为检测与SZ诊断相关的基因中的风险变异和潜在途径提供了神经生物学背景。此外,许多内表型可以转化到动物模型系统中,从而可以直接评估神经回路功能障碍和神经生物学底物。我们回顾了一些最有前景的SZ内表型,包括前脉冲抑制、失配负波、动眼反扫视、字母数字排序和持续操作测试。我们还强调了大型联盟最近的研究结果,这些结果表明基因,特别是在神经调节蛋白和谷氨酸途径中的基因,在其中几种内表型中具有潜在作用。尽管评估内表型需要额外的时间和精力,但它们所提供的对潜在神经生物学的深入了解最终可能揭示SZ的潜在遗传结构,并提出新的治疗靶点。