Individualized risk prediction in persons at clinical high-risk for psychosis using neuromelanin-sensitive MRI.

摘要 精神障碍是严重的、使人衰弱的疾病，治疗选择有限。鉴定 患有精神障碍的高风险个体是关键的第一步， 预防先前的研究已经确定，那些临床高风险的人（HRD）， 发展成一个全面的精神障碍（转换器），作为一个群体，往往表现出过量的多巴胺 在黑质-纹状体通路中，如PET测量的。但这一发现不太可能有助于识别 考虑到其预测值较低以及PET相关的实际局限性， (e.g.,辐射暴露）。以前的研究也已经确定，广泛的 可用的临床变量-NAPLS 2计算器-可以预测中度转换的风险 预测值在这里，我们建议使用神经黑色素敏感的MRI（NM-MRI），一种新的，易于 获得非侵入性MRI技术，可安全用于儿科个体，并提供 精神病相关的黑质-纹状体多巴胺过量的替代物，作为 个人的转变。此外，我们的目标是联合收割机结合这种客观的生物标志物， NAPLS 2计算器中的临床（主观）信息，以测试该生物标志物是否可以改善 个体风险预测的准确性超出了仅通过临床信息实现的准确性， 一种生物标志物的潜在临床效用的测试， 在很大程度上被忽视了。因此，我们的目标是结合联合收割机的优势，易于获取，客观的MRI 生物标志物挖掘精神病的病理生理学和已建立的风险算法 基于临床数据，更准确地识别有发展为全面精神病风险的个体， 并预测转换时间。具体而言，根据我们的初步数据，我们 第一个目的是确定黑质，峡部（SNc）的基线NM-MRI是否可以 显示异常增加的信号，特别是在那些有更严重的衰减 精神病症状第二，我们的目标是确定基线NM-MRI SNc信号是否是 特别是与非转换者和社会人口统计学相比， 匹配的健康对照。第三，我们的目标是评估NM-MRI SNc信号是否可以改善 风险预测的准确性高于NAPLS 2计算器得出的准确性。如果成功， 因此，这一提议将建立一种新的MRI生物标志物的潜在临床应用， 在儿科和非儿科人群中广泛采用并安全使用，以增强风险预测 用于精神病的发展，并有可能监测治疗和帮助个性化 治疗选择

ABSTRACT Psychotic disorders are severe, debilitating illnesses with limited treatment options. Identification of individuals who are at elevated risk for developing psychotic disorders is a critical first step for prevention. Prior research has established that those individuals at clinical high risk (CHR) who go on to develop a full-blown psychotic disorder (converters), as a group, tend to exhibit excess dopamine in the nigro-striatal pathway, as measured by PET. But this finding is unlikely to help identify individual subjects given its low predictive value and the practical limitations associated with PET (e.g., radiation exposure). Previous research has also established that a combination of widely available clinical variables –the NAPLS2 calculator– can predict risk of conversion with moderate predictive value. Here, we propose to use neuromelanin-sensitive MRI (NM-MRI), a novel, easy-to- acquire, non-invasive MRI technique that can be safely used in pediatric individuals and that provides a proxy for psychosis-related nigro-striatal dopamine excess, as a predictive biomarker for risk of conversion in CHR individuals. Furthermore, we aim to combine this objective biomarker with the clinical (subjective) information in the NAPLS2 calculator to test whether this biomarker can improve the accuracy of individual risk prediction beyond that achieved by clinical information alone, a critical test of the potential clinical utility of a biomarker that previous imaging studies in CHR populations have largely ignored. Thus, we aim to combine the strengths of an easy-to-acquire, objective MRI biomarker tapping into the pathophysiology of psychosis and those of an established risk algorithm based on clinical data to more accurately identify individuals at risk for developing full-blown psychotic disorders and predict time to conversion. Specifically, and as supported by our preliminary data, we first aim to determine whether baseline NM-MRI of the substantia nigra, pars compacta (SNc) can reveal abnormally increased signal specifically in those CHR individuals with more severe attenuated psychotic symptoms. Second, we aim to determine whether baseline NM-MRI SNc signal is particularly elevated in CHR converters compared to non-converters and to sociodemographically matched healthy controls. Third, we aim to assess whether NM-MRI SNc signal can improve the accuracy of risk predictions over and above those derived from the NAPLS2 calculator. If successful, this proposal will thus establish the potential clinical utility of a novel MRI biomarker that can be adopted widely and used safely in pediatric and non-pediatric populations to enhance risk predictions for the development of psychosis and potentially to monitor treatment and aid in personalized treatment selection.