Department of Psychology, University of Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, University of Oslo, & Oslo University Hospital, Oslo, Norway.
Department of Psychology, University of Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, University of Oslo, & Oslo University Hospital, Oslo, Norway; Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.
Dev Cogn Neurosci. 2022 Dec;58:101173. doi: 10.1016/j.dcn.2022.101173. Epub 2022 Nov 1.
Combining imaging modalities and metrics that are sensitive to various aspects of brain structure and maturation may help identify individuals that show deviations in relation to same-aged peers, and thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal brain imaging, cognitive, and questionnaire data from 1280 eight- to twenty-one-year-olds from the Philadelphia Neurodevelopmental Cohort. We estimated age-related gray and white matter properties and estimated individual deviation scores using normative modeling. Next, we tested for associations between the estimated deviation scores, and with psychopathology domain scores and cognition. More negative deviations in DTI-based fractional anisotropy (FA) and the first principal eigenvalue of the diffusion tensor (L1) were associated with higher scores on psychosis positive and prodromal symptoms and general psychopathology. A more negative deviation in cortical thickness (CT) was associated with a higher general psychopathology score. Negative deviations in global FA, surface area, L1 and CT were also associated with poorer cognitive performance. No robust associations were found between the deviation scores based on CT and DTI. The low correlations between the different multimodal magnetic resonance imaging-based deviation scores suggest that psychopathological burden in adolescence can be mapped onto partly distinct neurobiological features.
结合对大脑结构和成熟度各个方面敏感的成像方式和指标，可能有助于识别出与同龄个体存在偏差的个体，从而有助于对精神障碍进行早期风险评估。我们使用了来自费城神经发育队列的 1280 名 8 至 21 岁个体的单次多模态脑成像、认知和问卷调查数据。我们使用规范建模来估计与年龄相关的灰质和白质特性，并估计个体偏差得分。接下来，我们测试了估计的偏差得分与精神病理学领域得分和认知之间的关联。基于弥散张量成像（DTI）的分数各向异性（FA）和扩散张量的第一主特征值（L1）的负偏差越大，精神病阳性和前驱症状以及一般精神病理学的得分越高。皮质厚度（CT）的负偏差越大，一般精神病理学得分越高。全脑 FA、表面积、L1 和 CT 的负偏差也与较差的认知表现相关。基于 CT 和 DTI 的偏差得分之间没有发现稳健的关联。不同多模态磁共振成像偏差得分之间的低相关性表明，青少年时期的精神病理学负担可以映射到部分不同的神经生物学特征上。
