Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers
Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers
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DOI：
10.1093/brain/awv111
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发表时间：
2015-07-01
期刊：
影响因子：
14.5
通讯作者：
Davatzikos, Christos
中科院分区：
文献类型：
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作者：
Koutsouleris, Nikolaos;Meisenzahl, Eva M.;Davatzikos, Christos
基于磁共振成像的精神分裂症标志物已被反复证明可以在单一受试者水平上将患者与健康对照区分开，但尚不清楚这些标志物是否可靠地将精神分裂症与情绪障碍区分开来，并推广到新患者以及这些疾病的早期阶段。目前的研究使用基于结构mri的多变量模式分类来(i)识别和交叉验证区分首发和复发阶段精神分裂症患者（n = 158）和重度抑郁症患者（n = 104）的鉴别诊断特征；（ii）量化主要临床变量的影响，包括疾病阶段、发病年龄和大脑加速老化对签名分类性能的影响。该诊断性磁共振成像特征随后在来自两个不同中心的独立患者队列中进行评估，以测试其对双相情感障碍（n = 35）、首发精神病（n = 23）和临床定义的精神病高危精神状态（n = 89）患者的普遍性。神经解剖学诊断分别在80%和72%的重度抑郁症和精神分裂症患者中是正确的，并且涉及精神分裂症与重度抑郁症相比前额叶-颞叶-边缘体积减少和前运动、体感和皮质下体积增加的模式。精神分裂症患者是否存在抑郁症状或重性抑郁症患者是否存在精神病性症状并不影响诊断表现，但由于这些患者在神经解剖学上与精神分裂症的相似性增加，疾病发病早和脑老化加速促进了重性抑郁症的错误分类。此外，疾病分期显著调节神经解剖学诊断，因为复发患者的误诊率（重度抑郁症：23%；精神分裂症：29%）高于首发患者（重度抑郁症：15%；精神分裂症：12%）。最后，经过训练的生物标志物将74%的双相患者划分为重度抑郁症组，而83%的首发精神病患者以及77%和61%的超高风险和低风险状态的个体分别被标记为精神分裂症。我们的研究结果表明，神经解剖学信息可能提供一种通用的诊断工具，在精神病病程的早期区分精神分裂症和情绪障碍。疾病病程相关变量，如发病年龄和疾病阶段以及脑结构成熟的改变，可能对重度抑郁症和精神分裂症的神经解剖学可分离性产生强烈影响。
Magnetic resonance imaging-based markers of schizophrenia have been repeatedly shown to separate patients from healthy controls at the single-subject level, but it remains unclear whether these markers reliably distinguish schizophrenia from mood disorders across the life span and generalize to new patients as well as to early stages of these illnesses. The current study used structural MRI-based multivariate pattern classification to (i) identify and cross-validate a differential diagnostic signature separating patients with first-episode and recurrent stages of schizophrenia (n = 158) from patients with major depression (n = 104); and (ii) quantify the impact of major clinical variables, including disease stage, age of disease onset and accelerated brain ageing on the signature's classification performance. This diagnostic magnetic resonance imaging signature was then evaluated in an independent patient cohort from two different centres to test its generalizability to individuals with bipolar disorder (n = 35), first-episode psychosis (n = 23) and clinically defined at-risk mental states for psychosis (n = 89). Neuroanatomical diagnosis was correct in 80% and 72% of patients with major depression and schizophrenia, respectively, and involved a pattern of prefronto-temporo-limbic volume reductions and premotor, somatosensory and subcortical increments in schizophrenia versus major depression. Diagnostic performance was not influenced by the presence of depressive symptoms in schizophrenia or psychotic symptoms in major depression, but earlier disease onset and accelerated brain ageing promoted misclassification in major depression due to an increased neuroanatomical schizophrenia likeness of these patients. Furthermore, disease stage significantly moderated neuroanatomical diagnosis as recurrently-ill patients had higher misclassification rates (major depression: 23%; schizophrenia: 29%) than first-episode patients (major depression: 15%; schizophrenia: 12%). Finally, the trained biomarker assigned 74% of the bipolar patients to the major depression group, while 83% of the first-episode psychosis patients and 77% and 61% of the individuals with an ultra-high risk and low-risk state, respectively, were labelled with schizophrenia. Our findings suggest that neuroanatomical information may provide generalizable diagnostic tools distinguishing schizophrenia from mood disorders early in the course of psychosis. Disease course-related variables such as age of disease onset and disease stage as well alterations of structural brain maturation may strongly impact on the neuroanatomical separability of major depression and schizophrenia.