Norwegian Centre for Mental Disorders Research, K.G. Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Norwegian Centre for Mental Disorders Research, K.G. Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Biol Psychiatry. 2019 Jul 1;86(1):65-75. doi: 10.1016/j.biopsych.2019.01.019. Epub 2019 Jan 30.
Accumulating evidence supports cerebellar involvement in mental disorders, such as schizophrenia, bipolar disorder, depression, anxiety disorders, and attention-deficit/hyperactivity disorder. However, little is known about the cerebellum in developmental stages of these disorders. In particular, whether cerebellar morphology is associated with early expression of specific symptom domains remains unclear.
We used machine learning to test whether cerebellar morphometric features could robustly predict general cognitive function and psychiatric symptoms in a large and well-characterized developmental community sample centered on adolescence (Philadelphia Neurodevelopmental Cohort, n = 1401, age 8-23 years).
Cerebellar morphology was associated with both general cognitive function and general psychopathology (mean correlations between predicted and observed values: r = .20 and r = .13; p < .001). Analyses of specific symptom domains revealed significant associations with rates of norm-violating behavior (r = .17; p < .001) as well as psychosis (r = .12; p < .001) and anxiety (r = .09; p = .012) symptoms. In contrast, we observed no associations with attention deficits or depressive, manic, or obsessive-compulsive symptoms. Crucially, across 52 brain-wide anatomical features, cerebellar features emerged as the most important for prediction of general psychopathology, psychotic symptoms, and norm-violating behavior. Moreover, the association between cerebellar volume and psychotic symptoms and, to a lesser extent, norm-violating behavior remained significant when adjusting for several potentially confounding factors.
The robust associations with psychiatric symptoms in the age range when these typically emerge highlight the cerebellum as a key brain structure in the development of severe mental disorders.
越来越多的证据表明小脑参与了精神疾病，如精神分裂症、双相情感障碍、抑郁症、焦虑症和注意缺陷多动障碍。然而，人们对这些疾病的发育阶段的小脑知之甚少。特别是，小脑形态是否与特定症状领域的早期表达有关尚不清楚。
我们使用机器学习来测试小脑形态特征是否可以在以青春期为中心的大型、特征良好的发育性社区样本（费城神经发育队列，n=1401，年龄 8-23 岁）中稳健地预测一般认知功能和精神症状。
小脑形态与一般认知功能和一般精神病理学都有关（预测值与观察值之间的平均相关性：r=0.20 和 r=0.13；p<0.001）。对特定症状领域的分析显示与违规行为发生率（r=0.17；p<0.001）以及精神病（r=0.12；p<0.001）和焦虑症（r=0.09；p=0.012）症状有显著关联。相比之下，我们没有观察到与注意力缺陷或抑郁、躁狂或强迫症症状有关联。至关重要的是，在 52 个大脑广泛的解剖特征中，小脑特征是预测一般精神病理学、精神病症状和违规行为的最重要特征。此外，当调整几个潜在的混杂因素时，小脑体积与精神病症状的关联，以及在较小程度上与违规行为的关联仍然显著。
在这些疾病通常出现的年龄范围内与精神症状的稳健关联突显了小脑在严重精神障碍发展中的关键脑结构作用。
