Yale University, School of Medicine, New Haven, CT, USA.
Adv Neurobiol. 2024;40:237-283. doi: 10.1007/978-3-031-69491-2_10.
Schizophrenia is a debilitating neuropsychiatric disorder that affects approximately 1% of the population and poses a major public health problem. Despite over 100 years of study, the treatment for schizophrenia remains limited, partially due to the lack of knowledge about the neural mechanisms of the illness and how they relate to symptoms. The US Food and Drug Administration (FDA) and the National Institute of Health (NIH) have provided seven biomarker categories that indicate causes, risks, and treatment responses. However, no FDA-approved biomarkers exist for psychiatric conditions, including schizophrenia, highlighting the need for biomarker development. Over three decades, magnetic resonance imaging (MRI)-based studies have identified patterns of abnormal brain function in schizophrenia. By using functional connectivity (FC) data, which gauges how brain regions interact over time, these studies have differentiated patient subgroups, predicted responses to antipsychotic medication, and correlated neural changes with symptoms. This suggests FC metrics could serve as promising biomarkers. Here, we present a selective review of studies leveraging MRI-derived FC to study neural alterations in schizophrenia, discuss how they align with FDA-NIH biomarkers, and outline the challenges and goals for developing FC biomarkers in schizophrenia.
精神分裂症是一种使人衰弱的神经精神疾病,影响大约 1%的人口,是一个主要的公共卫生问题。尽管经过 100 多年的研究,精神分裂症的治疗仍然有限,部分原因是缺乏对疾病的神经机制及其与症状的关系的了解。美国食品和药物管理局(FDA)和美国国立卫生研究院(NIH)已经提供了七个生物标志物类别,表明病因、风险和治疗反应。然而,没有 FDA 批准的生物标志物用于精神疾病,包括精神分裂症,这突出了生物标志物开发的必要性。三十多年来,基于磁共振成像(MRI)的研究已经确定了精神分裂症中大脑功能异常的模式。通过使用功能连接(FC)数据,即衡量大脑区域随时间相互作用的程度,这些研究区分了患者亚组,预测了抗精神病药物的反应,并将神经变化与症状相关联。这表明 FC 指标可以作为有前途的生物标志物。在这里,我们对利用 MRI 衍生的 FC 研究精神分裂症中神经改变的研究进行了选择性综述,讨论了它们如何与 FDA-NIH 生物标志物一致,并概述了开发精神分裂症 FC 生物标志物的挑战和目标。