Associations of age, body mass index and biochemical parameters with brain morphology in patients with anorexia nervosa.

OBJECTIVE: Accumulating evidence shows that patients with anorexia nervosa (AN) have globally reduced brain mass, including lower cortical volume and thickness, which largely normalizes following weight restoration. The underlying mechanisms for these processes are unknown, and how age and severity of emaciation are associated with brain morphology in AN is poorly understood. We investigated associations of age, body mass index (BMI) and biochemical parameters with brain morphology among patients in treatment. METHOD: We included 85 patients (94% female) aged 12-48 (mean = 23) years with quality controlled magnetic resonance imaging (MRI) data. T1-weighted MRI images, clinical characteristics and biochemical parameters were retrospectively collected from hospital records. Brain morphology was measured using FreeSurfer, and associations investigated using regression models and correlations. RESULTS: Controlling for BMI, age showed significant associations with brain morphology generally concordant with typical brain developmental patterns. Controlling for age, BMI showed significant positive associations with cortical volume and thickness. There were no significant interaction effects between age and BMI. None of the biochemical parameters correlated significantly with brain morphology. CONCLUSION: Our findings suggest the presence of typical neurodevelopmental patterns in AN. Importantly, we showed that severity of emaciation is related to brain morphology reductions, underscoring the importance of weight restoration.

Cerebellar Gray Matter Volume Is Associated With Cognitive Function and Psychopathology in Adolescence.

BACKGROUND: 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 (Philadelphia Neurodevelopmental Cohort, n = 1401, age 8-23 years). 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 < .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. 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.