Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif., and Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque (Tohen); Department of Psychiatry, University of Texas Dell Medical School, Austin (Nemeroff).
Am J Psychiatry. 2021 Jun;178(6):509-521. doi: 10.1176/appi.ajp.2020.20030340. Epub 2021 Jan 5.
Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, -methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.
精神分裂症是一种复杂的神经精神综合征,具有异质的遗传、神经生物学和表型特征。目前,尚无客观的生物学指标(即生物标志物)可用于告知诊断或治疗决策。神经影像学非常适合开发精神分裂症的生物标志物,因为它可以捕捉到分子和细胞疾病靶点或脑回路中的表型变化。这些基于机制的生物标志物可能代表疾病过程病理生理基础的直接衡量标准,因此可以作为真正的中间或替代终点。有效的生物标志物可以验证新的治疗靶点或途径,预测反应,帮助选择治疗的患者,确定治疗方案,并为个性化治疗提供依据。在这篇综述中,作者讨论了一系列在机制上合理的神经影像学生物标志物候选物,包括多巴胺过度活跃、-甲基-d-天冬氨酸受体功能低下、海马体过度活跃、免疫失调、连通性障碍和皮质灰质体积减少。然后,他们重点介绍了精神分裂症中用于疾病风险、诊断、靶点结合和治疗反应的假定神经影像学生物标志物。最后,他们强调了未满足的需求领域,并讨论了推进生物标志物开发的策略。