van Erp T G M, Hibar D P, Rasmussen J M, Glahn D C, Pearlson G D, Andreassen O A, Agartz I, Westlye L T, Haukvik U K, Dale A M, Melle I, Hartberg C B, Gruber O, Kraemer B, Zilles D, Donohoe G, Kelly S, McDonald C, Morris D W, Cannon D M, Corvin A, Machielsen M W J, Koenders L, de Haan L, Veltman D J, Satterthwaite T D, Wolf D H, Gur R C, Gur R E, Potkin S G, Mathalon D H, Mueller B A, Preda A, Macciardi F, Ehrlich S, Walton E, Hass J, Calhoun V D, Bockholt H J, Sponheim S R, Shoemaker J M, van Haren N E M, Hulshoff Pol H E, Ophoff R A, Kahn R S, Roiz-Santiañez R, Crespo-Facorro B, Wang L, Alpert K I, Jönsson E G, Dimitrova R, Bois C, Whalley H C, McIntosh A M, Lawrie S M, Hashimoto R, Thompson P M, Turner J A
Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA.
Imaging Genetics Center, University of Southern California, Los Angeles, CA, USA.
Mol Psychiatry. 2016 Apr;21(4):547-53. doi: 10.1038/mp.2015.63. Epub 2015 Jun 2.
The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.
尽管使用脑部扫描进行了数十年的研究,但精神分裂症患者脑部结构异常的情况仍未完全了解。为了验证一种用于分析多中心神经影像数据的前瞻性荟萃分析方法,我们分析了来自2028名精神分裂症患者和2540名健康对照者的脑部MRI扫描数据,这些数据在全球15个中心采用标准化方法进行评估。我们确定了能区分患者与对照者的皮层下脑容量,并根据效应大小对它们进行排名。与健康对照者相比,精神分裂症患者的海马体(科恩d值=-0.46)、杏仁核(d=-0.31)、丘脑(d=-0.31)、伏隔核(d=-0.25)和颅内体积(d=-0.12)较小,而苍白球(d=0.21)和侧脑室体积(d=0.37)较大。壳核和苍白球体积增大与病程呈正相关,海马体缺陷与未用药患者的比例成正比。对脑成像数据进行的全球合作分析支持精神分裂症患者存在皮层下异常的情况,这与基于传统荟萃分析方法得出的结果一致。这项由ENIGMA精神分裂症工作组开展的首项研究证实,协作数据分析可轻松应用于各种脑表型和疾病,并鼓励开展分析和数据共享工作,以加深我们对严重精神疾病的理解。