Wu Chen-Hao, Hwang Tzung-Jeng, Chen Yu-Jen, Hsu Yun-Chin, Lo Yu-Chun, Liu Chih-Min, Hwu Hai-Gwo, Liu Chen-Chung, Hsieh Ming H, Chien Yi Ling, Chen Chung-Ming, Tseng Wen-Yih Isaac
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; Center for Optoelectronic Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.
Hum Brain Mapp. 2015 Mar;36(3):1065-76. doi: 10.1002/hbm.22686. Epub 2014 Nov 4.
Trait markers of schizophrenia aid the dissection of the heterogeneous phenotypes into distinct subtypes and facilitate the genetic underpinning of the disease. The microstructural integrity of the white matter tracts could serve as a trait marker of schizophrenia, and tractography-based analysis (TBA) is the current method of choice. Manual tractography is time-consuming and limits the analysis to preselected fiber tracts. Here, we sought to identify a trait marker of schizophrenia from among 74 fiber tracts across the whole brain using a novel automatic TBA method. Thirty-one patients with schizophrenia, 31 unaffected siblings and 31 healthy controls were recruited to undergo diffusion spectrum magnetic resonance imaging at 3T. Generalized fractional anisotropy (GFA), an index reflecting tract integrity, was computed for each tract and compared among the three groups. Ten tracts were found to exhibit significant differences between the groups with a linear, stepwise order from controls to siblings to patients; they included the right arcuate fasciculus, bilateral fornices, bilateral auditory tracts, left optic radiation, the genu of the corpus callosum, and the corpus callosum to the bilateral dorsolateral prefrontal cortices, bilateral temporal poles, and bilateral hippocampi. Posthoc between-group analyses revealed that the GFA of the right arcuate fasciculus was significantly decreased in both the patients and unaffected siblings compared to the controls. Furthermore, the GFA of the right arcuate fasciculus exhibited a trend toward positive symptom scores. In conclusion, the right arcuate fasciculus may be a candidate trait marker and deserves further study to verify any genetic association.
精神分裂症的特质标记有助于将异质性表型分解为不同亚型,并促进该疾病的遗传基础研究。白质束的微观结构完整性可作为精神分裂症的特质标记,基于纤维束成像的分析(TBA)是目前的首选方法。手动纤维束成像耗时且将分析局限于预先选定的纤维束。在此,我们试图使用一种新型自动TBA方法,从全脑的74条纤维束中识别出精神分裂症的特质标记。招募了31名精神分裂症患者、31名未受影响的同胞和31名健康对照,在3T条件下接受扩散谱磁共振成像检查。计算每条纤维束的广义分数各向异性(GFA),这是一个反映纤维束完整性的指标,并在三组之间进行比较。发现有10条纤维束在三组之间呈现出从对照到同胞再到患者的线性、逐步变化的显著差异;它们包括右侧弓状束、双侧穹窿、双侧听觉纤维束、左侧视辐射、胼胝体膝部,以及从胼胝体到双侧背外侧前额叶皮质、双侧颞极和双侧海马体的纤维束。事后组间分析显示,与对照组相比,患者和未受影响的同胞的右侧弓状束GFA均显著降低。此外,右侧弓状束的GFA与阳性症状评分呈正相关趋势。总之,右侧弓状束可能是一个候选特质标记,值得进一步研究以验证其与遗传的关联。