250 words | Article body: 3999 words, 0 tables, and 5 figures.Supplementary Information: 1 word document, 9 tables and 17 figures.
AbstractBackground: 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.
Methods: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 (the Philadelphia Neurodevelopmental Cohort, N=1401, age-range: 8 -23).Results: 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-values < .0009). Analyses of specific symptom domains revealed significant associations with rates of norm-violating behavior (r = .17; p < .0009), as well as psychosis (r = .12; p < .0009) and anxiety (r = .09; p =.0117) symptoms. In contrast, we observed no associations with attention deficits, depressive, manic or obsessivecompulsive 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.
Conclusions: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.