Mauricio Henriques Serpa

Bipolar disorder (BD) is a prevalent psychiatric condition characterized by marked clinical and neuroanatomical heterogeneity. Prior neuroimaging studies have used case-control comparisons yielding small to moderate effect sizes for group differences. Large and diverse samples are needed to map heterogeneity within BD. Here, we used individualized brain morphometry deviations derived from normative modeling for three MRI-based measures (regional cortical thickness, regional surface area, and subcortical volumes). We applied this approach to a large international sample of 4 660 individuals (1 145 with bipolar I disorder and 3 515 healthy controls) from the ENIGMA Bipolar Disorder Working Group consortium (age range = 8–80, female = 53.15%) and examined the distribution of deviations within the bipolar disorder group, differences between healthy controls and individuals with bipolar disorder, and associations between neuroanatomical deviations and clinical variables. We found that individuals with bipolar disorder showed a higher proportion of localized extreme deviations, notably negative cortical thickness deviations in regions consistently reported as thinner in prior studies (the left superior frontal gyrus, bilateral inferior frontal gyrus (pars opercularis), left precuneus) and subcortical volume negative deviations in the left hippocampus. In addition, ROI-level deviations in the left middle temporal gyrus and the left inferior temporal gyrus were associated with longer illness duration. This is the largest study to date exploring individualized deviations as neuroanatomical features associated with bipolar disorder. Our findings suggest that neuroanatomical heterogeneity is a core feature of bipolar disorder, with preferential left-lateralized cortical-hippocampal involvement pointing to spatially structured heterogeneity.

Background: The macro-social and environmental conditions in which people live, such as the level of a country’s development or inequality, are associated with brain-related disorders. However, the relationship between these systemic environmental factors and the brain remains unclear. We aimed to determine the association between the level of development and inequality of a country and the brain structure of healthy adults. Methods: We conducted a cross-sectional study pooling brain imaging (T1-based) data from 145 magnetic resonance imaging (MRI) studies in 7,962 healthy adults (4,110 women) in 29 different countries. We used a meta-regression approach to relate the brain structure to the country’s level of development and inequality. Results: Higher human development was consistently associated with larger hippocampi and more expanded global cortical surface area, particularly in frontal areas. Increased inequality was most consistently associated with smaller hippocampal volume and thinner cortical thickness across the brain. Conclusions: Our results suggest that the macro-economic conditions of a country are reflected in its inhabitants’ brains and may explain the different incidence of brain disorders across the world. The observed variability of brain structure in health across countries should be considered when developing tools in the field of personalized or precision medicine that are intended to be used across the world.

The Brazilian Journal of Psychiatry is the official publication of Brazilian Psychiatric Association (Associação Brasileira de Psiquiatria - ABP)

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.