Ultra-high field GluCEST MRI and MRS in youth at risk for psychosis

摘要：精神病通常发生在青春期或成年早期。故障 神经递质系统，如谷氨酸，与精神病的疾病进展有关。变化 在大脑中，谷氨酸在精神病中可能有几个来源，因此，许多一线抗精神病药物 间接靶向谷氨酸系统，缓解临床症状。不幸的是，体内监测 大脑内谷氨酸系统的改变在空间上受到传统磁共振的限制 技巧。但是，最近一项新的7T磁共振技术(GluCEST)表明，大脑中的谷氨酸水平 与精神分裂症患者相比，青少年和精神分裂症患者的大脑水平更低 通常是发展中的年轻人。在这里，我们建议将这项新工作扩展到直接测量体内的谷氨酸 有发展成精神病风险的患者的大脑。因此，这项提议的动机是需要更好地 了解大脑神经化学、结构和功能在正常发育和正常发育中的关系 在精神错乱的早期。在这项研究中，我们试图1)比较不同地区谷氨酸能发育的指标 对典型发育(TD)青年、临床精神病高危人群(CHR)和 患有坦率精神病(PSY)的人；2)大脑谷氨酸的变化与年龄和诊断- 精神疾病高危人群的相关结构网络变化；以及3)建立比较 7T MRI上谷氨酸测定数据(1HMRS与GluCEST)。我们将招聘并跟踪35名TD、CHR和PSY 在5年的资助期内。成像数据将在7T时获得，分析将利用最近的进展 在网络科学和机器学习方面。我们相信这种创新的方法可以极大地推动我们的 了解精神病谷氨酸功能减退的病因并提供精确的进展 精神病学的医学。通过拟议的多层次分析，这项创新研究将提供 我们对精神病的神经发育基础的理解有了实质性的进展。

ABSTRACT: Psychosis commonly develops in adolescence or early adulthood. Malfunctioning neurotransmitter systems, such as glutamate, are implicated in the disease progression of psychosis. Changes in brain glutamate in psychosis likely have several sources, as such, many frontline antipsychotic medications indirectly target the glutamate system and alleviate clinical symptoms. Unfortunately, monitoring in vivo alterations of the glutamate system within the brain are spatially limited by traditional magnetic resonance techniques. But, recently a novel 7T MRI technique (GluCEST) has shown that brain glutamate levels are lower across the brain in youth on the psychosis spectrum and patients with schizophrenia as compared to typically developing youth. Here, we propose to extend this novel work to directly measure glutamate within the brain of patients at risk for developing psychosis. Thus, this proposal is motivated by the need to better understand associations of brain neurochemistry, structure and function in both normal development and during early psychosis. In this study, we seek to 1) compare measures of glutamatergic development across the cortex in a cohort of typically developing (TD) youth, those at-clinical high-risk for psychosis (CHR) and individuals with frank psychosis (PSY); 2) associate changes in brain glutamate with age- and diagnosis- related structural network changes in those at risk for developing psychosis; and 3) to establish comparison data of glutamate measures at 7T MRI (1HMRS vs. GluCEST). We will recruit and follow 35 TD, CHR and PSY over the 5-year funding period. Imaging data will be acquired at 7T and analyses will leverage recent advances in network science and machine learning. We believe this innovative approach can significantly advance our understanding of the etiology of glutamate hypofunction in psychosis and provide advances to precision medicine in psychiatry. Through the proposed multi-level analysis, this innovative research will provide a substantial advance in our understanding of the neurodevelopmental substrates of psychosis.