PDF(Pubmed)
Abstract：
BACKGROUND: Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project.
METHODS: The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain.
CONCLUSIONS: Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.
METHODS: The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain.
CONCLUSIONS: Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.
摘要：
背景：通过1）对具有不同潜在神经生物学缺陷的临床相似患者进行分层，以及2）客观跟踪疾病轨迹和治疗反应，客观和可量化标记对于开发精神障碍的新疗法至关重要。精神分裂症通常与其他精神疾病混淆，尤其是双相情感障碍,如果基于横断面症状。清醒和睡眠脑电图在识别神经生理学差异作为精神分裂症的生物标志物方面显示出希望。然而,大多数以前的研究，虽然有用，在欧洲和美国人群中进行，样本量小，并利用不同的分析方法，限制了对不同人群的全面分析或普遍性。此外，清醒和睡眠神经生理学指标相互关联以及与症状严重程度或认知障碍相关的程度仍未解决。此外，这些神经生理标志物在不同的精神病状况之间的比较并没有得到很好的表征。生物标志物在临床试验和实践中的应用将通过强大的跨诊断研究得到显著推进。精神分裂症神经生理学全球研究倡议(GRINS)项目旨在通过一个大的,涉及东亚人群的多中心队列研究。为了提高透明度和可重复性，我们描述了GRINS项目的协议。
方法：研究程序包括最初的筛选访谈，然后是三个随后的会议：介绍性访谈，评估访问，和通宵神经生理记录。来自多个域的数据，包括人口统计学和临床特征，行为表现(认知任务，电机序列任务)，和神经生理指标（清醒和睡眠脑电图），由专门从事每个领域的研究小组收集。
结论：GRINS项目的试验结果证明了本研究方案的可行性，并强调了此类研究的重要性。以及它在研究更广泛的精神病患者方面的潜力。通过GRINS,我们正在生成一个跨多个领域的有价值的数据集，以单独和组合识别精神分裂症的神经生理学标志物。通过将该协议应用于通常相互混淆的相关精神障碍，我们可以收集信息，深入了解这些严重疾病的神经生理学特征和潜在机制，告知客观诊断，临床研究的分层，最终,在临床上开发更好的针对性治疗匹配。
方法：研究程序包括最初的筛选访谈，然后是三个随后的会议：介绍性访谈，评估访问，和通宵神经生理记录。来自多个域的数据，包括人口统计学和临床特征，行为表现(认知任务，电机序列任务)，和神经生理指标（清醒和睡眠脑电图），由专门从事每个领域的研究小组收集。
结论：GRINS项目的试验结果证明了本研究方案的可行性，并强调了此类研究的重要性。以及它在研究更广泛的精神病患者方面的潜力。通过GRINS,我们正在生成一个跨多个领域的有价值的数据集，以单独和组合识别精神分裂症的神经生理学标志物。通过将该协议应用于通常相互混淆的相关精神障碍，我们可以收集信息，深入了解这些严重疾病的神经生理学特征和潜在机制，告知客观诊断，临床研究的分层，最终,在临床上开发更好的针对性治疗匹配。
