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

使用神经黑色素敏感 MRI 对临床精神病高危人群进行个体化风险预测。

• 批准号: 10412110
• 负责人: Guillermo Horga
• 金额: $ 60.53万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10412110
• 关键词: Adolescent and Young Adult; Adopted; Age; Algorithms; Antipsychotic Agents; Attenuated; Biological; Biological Markers; Cell Nucleus; Childhood; Clinic; Clinical; Clinical Data; Clinical assessments; Data; Development; Disease; Dopamine; Early identification; Early treatment; Exhibits; Functional disorder; Future; Individual; Intake; Longevity; Magnetic Resonance Imaging; Measures; Midbrain structure; Modeling; Monitor; Neurons; Noise; Onset of illness; Pathway interactions; Persons; Phenotype; Population; Populations at Risk; Positron-Emission Tomography; Predictive Value; Prevention; Prevention strategy; Prognosis; Proxy; Psychoses; Psychotic Disorders; Public Health; Radiation; Radiation exposure; Research; Risk; Sample Size; Sampling; Schizophrenia; Selection for Treatments; Severities; Signal Transduction; Staging; Substantia nigra structure; Symptoms; Techniques; Testing; Time; Tissues; Validation; Work; base; candidate marker; clinical high risk for psychosis; clinical risk; cost; disability; follow-up; high risk; high risk population; high-risk adolescents; imaging study; improved; neuroimaging marker; neuromelanin; nigrostriatal pathway; novel; pars compacta; personalized medicine; personalized risk prediction; prediction algorithm; predictive marker; prevent; psychotic symptoms; risk prediction; sociodemographic variables; sociodemographics; therapeutic development; tool; transmission process; white matter

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.

抽象的 精神病性疾病严重，使疾病具有有限的治疗选择。识别 患有精神疾病风险较高的人是关键的第一步 预防。先前的研究已经确定，那些处于临床高风险（CHR）的人继续 为了发展成熟的精神病（转换器），往往存在超过多巴胺 在通过PET测量的Nigro - 纹状体途径中。但是这一发现不太可能有助于识别 个人受试者的预测价值低和与PET相关的实际限制 （例如，辐射暴露）。先前的研究还确定了广泛的结合 可用的临床变量 - NAPLS2计算器 - 可以预测现代转化的风险 预测价值。在这里，我们建议使用神经素敏感的MRI（NM-MRI），这是一种新颖，易于 - 获取可安全用于儿科个体的无创MRI技术，并提供 与精神病相关的分子纹状体多巴胺的代理，作为一种预测性生物标志物 CHR个人的转换。此外，我们旨在将这个目标生物标志物与 NAPLS2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 仅通过临床信息实现的个人风险预测的准确性，这是一个关键 测试生物标志物的潜在临床实用性，即先前的成像研究 在很大程度上被忽略了。这是我们的目标 生物标志物挖掘精神病的病理生理学和既定风险算法的生物标志物 基于临床数据，以更准确地识别有发展全面精神病风险的人 疾病并预测转换时间。特别是，在我们的初步数据的支持下，我们 首先要确定底底nigra的基线NM-MRI是否可以 在那些更严重衰减的CHR个体中，明显增加信号明显增加 精神病符号。第二，我们旨在确定基线NM-MRI SNC信号是否为 与非转换器相比，CHR转换器的升高尤其高于社会人口统计学 匹配的健康对照。第三，我们旨在评估NM-MRI SNC信号是否可以改善 风险预测的准确性超过了NAPLS2计算器的准确性。如果成功， 因此，该建议将确定可以是新型MRI生物标志物的潜在临床实用性 广泛采用并安全地用于小儿和非培养质人群中，以增强风险预测 为了发展精神病，并有可能监测治疗和帮助个性化 治疗选择。