Knowledge of amygdalar and hippocampal development as they pertain to sex differences and laterality would help to understand not only brain development but also the relationship between brain volume and brain functions. However, few studies investigated development of these two regions, especially during infancy. The purpose of this study was to examine typical volumetric trajectories of amygdala and hippocampus from infancy to early adulthood by predicting sexual dimorphism and laterality. We performed a cross-sectional morphometric MRI study of amygdalar and hippocampal growth from 1 month to 25 years old, using 109 healthy individuals. The findings indicated significant non-linear age-related volume changes, especially during the first few years of life, in both the amygdala and hippocampus regardless of sex. The peak ages of amygdalar and hippocampal volumes came at the timing of preadolescence (9–11 years old). The female amygdala reached its peak age about one year and a half earlier than the male amygdala did. In addition, its rate of growth change decreased earlier in the females. Furthermore, both females and males displayed rightward laterality in the hippocampus, but only the males in the amygdala. The robust growth of the amygdala and hippocampus during infancy highlight the importance of this period for neural and functional development. The sex differences and laterality during development of these two regions suggest that sex-related factors such as sex hormones and functional laterality might affect brain development.

A progressive process in the superior temporal gyrus precedes the first expression of florid psychosis. These findings have important implications for underlying neurobiologic features of emerging psychotic disorders and emphasize the importance of early intervention during or before the first episode of psychosis.

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar crossdisorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

Compelling evidence in Caucasian populations suggests a role for copy-number variations (CNVs) in autism spectrum disorder (ASD) and schizophrenia (SCZ). We analyzed 1,108 ASD cases, 2,458 SCZ cases, and 2,095 controls in a Japanese population and confirmed an increased burden of rare exonic CNVs in both disorders. Clinically significant (or pathogenic) CNVs, including those at 29 loci common to both disorders, were found in about 8% of ASD and SCZ cases, which was significantly higher than in controls. Phenotypic analysis revealed an association between clinically significant CNVs and intellectual disability. Gene set analysis showed significant overlap of biological pathways in both disorders including oxidative stress response, lipid metabolism/modification, and genomic integrity. Finally, based on bioinformatics analysis, we identified multiple disease-relevant genes in eight well-known ASD/SCZ-associated CNV loci (e.g., 22q11.2, 3q29). Our findings suggest an etiological overlap of ASD and SCZ and provide biological insights into these disorders.

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