Janssen Joost, Gallego Ana Guil, Díaz-Caneja Covadonga M, Lois Noemi González, Janssen Niels, González-Peñas Javier, Gordaliza Pedro M, Buimer Elizabeth E L, van Haren Neeltje E M, Arango Celso, Kahn René S, Hulshoff Pol Hilleke E, Schnack Hugo G
Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain.
Ciber del Área de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
bioRxiv. 2024 Jun 18:2024.03.26.586768. doi: 10.1101/2024.03.26.586768.
Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia.
Morphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score ≧ than 1.96 was considered supra-normal and a z-score ≦ -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant.
At baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences.
In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.
形态计量相似性是一种最近开发的神经影像学表型，用于通过基于多个MRI参数量化一个区域与其他区域的相似性来反映区域间的连接性。在精神病性障碍的群体水平上，已报道平均形态计量相似性发生改变，个体间存在相当大的异质性。我们使用规范建模来解决健康人群和精神分裂症患者中形态计量相似性的横断面和纵向个体间异质性问题。
从健康个体和慢性精神分裂症患者的基线和随访T1加权扫描中获取62个皮质区域的形态计量相似性。皮质区域被分类为七个预定义的脑功能网络。使用贝叶斯线性回归，并考虑年龄、性别、图像质量和扫描仪，我们在来自11个数据集（n = 4310）的健康对照中训练和验证了规范模型。在两个时间点，为每个参与者的每个网络和区域计算形态计量相似性与规范值的个体偏差（z分数）。z分数≧1.96被认为是超正常范围（高于正常值），z分数≦ -1.96被认为是低于正常范围（低于正常值）。作为纵向指标，我们计算了每个参与者低于或高于正常范围区域总数随时间的变化。
在基线时，与健康对照相比，精神分裂症患者默认模式网络的形态计量相似性降低，躯体运动网络的形态计量相似性增加。在基线和随访时，任何区域低于或高于正常范围值的患者百分比都很低（<6%），与健康对照无差异。在精神分裂症组和健康对照组中，低于或高于正常范围区域总数随时间的组内平均变化很小（<1），且组间无显著差异。
在病例对照研究中，默认模式网络内形态计量相似性的降低可能是精神分裂症的一个有力发现。然而，规范建模表明，区域形态计量相似性的显著降低和随时间的变化仅在少数患者中明显。
