Gene expression and brain imaging association study reveals gene signatures in major depressive disorder.

Major depressive disorder is often characterized by changes in the structure and function of the brain, which are influenced by modifications in gene expression profiles. How the depression-related genes work together within the scope of time and space to cause pathological changes remains unclear. By integrating the brain-wide gene expression data and imaging data in major depressive disorder, we identified gene signatures of major depressive disorder and explored their temporal-spatial expression specificity, network properties, function annotations and sex differences systematically. Based on correlation analysis with permutation testing, we found 345 depression-related genes significantly correlated with functional and structural alteration of brain images in major depressive disorder and separated them by directional effects. The genes with negative effect for grey matter density and positive effect for functional indices are enriched in downregulated genes in the post-mortem brain samples of patients with depression and risk genes identified by genome-wide association studies than genes with positive effect for grey matter density and negative effect for functional indices and control genes, confirming their potential association with major depressive disorder. By introducing a parameter of dispersion measure on the gene expression data of developing human brains, we revealed higher spatial specificity and lower temporal specificity of depression-related genes than control genes. Meanwhile, we found depression-related genes tend to be more highly expressed in females than males, which may contribute to the difference in incidence rate between male and female patients. In general, we found the genes with negative effect have lower network degree, more specialized function, higher spatial specificity, lower temporal specificity and more sex differences than genes with positive effect, indicating they may play different roles in the occurrence and development of major depressive disorder. These findings can enhance the understanding of molecular mechanisms underlying major depressive disorder and help develop tailored diagnostic and treatment strategies for patients of depression of different sex.

[A functional MRI study in ADHD children with impulsivity].

OBJECTIVE: Impulsivity is one of the core symptoms of children with attention deficit hyperactivity disorder (ADHD). In order to understand the neuromechanism of the impulsive behaviors in ADHD children, this study investigated the specific functional areas of the brain by functional MRI. METHODS: The subjects consisted of 10 ADHD children with impulsivity, 7 ADHD children without impulsivity and 9 normal children. A functional MRI examination was performed when the subjects were instructed to finish GO and STOP tasks with the GO-STOP impulsivity paradigm. The MRI data during the two tasks of GO and STOP were averaged and the corresponding activation regions between groups were compared. RESULTS: The data from the GO task revealed that the main activation regions of the normal children included frontal pole (superior frontal gyrus, middle frontal gyrus and medial frontal gyrus); the main activation regions of ADHD children without impulsivity were cerebellum (posterior lobe and anterior lobe bouton) and cingulated gyrus; those of ADHD children with impulsivity were medial globus pallidus and insula. The data from the STOP task showed that the main activation regions of normal children included superior frontal gyrus and middle frontal gyrus; those of ADHD children without impulsivity were middle frontal gyrus and cingulate gyrus; those of ADHD children with impulsivity were uncus and putamen. The activation regions of ADHD children with impulsivity were much fewer than the other two groups. CONCLUSIONS: The behavior of impulsivity-control involves a number of specific functional areas in the cerebral cortex. Compared with normal children, ADHD children without impulsivity have weaker brain function and brain activation, and ADHD children with impulsivity demonstrate much fewer brain activation regions, worse brain function and little awareness of the cerebral cortex.

A brain network model for depression: From symptom understanding to disease intervention.

Understanding the neural substrates of depression is crucial for diagnosis and treatment. Here, we review recent studies of functional and effective connectivity in depression, in terms of functional integration in the brain. Findings from these studies, including our own, point to the involvement of at least four networks in patients with depression. Elevated connectivity of a ventral limbic affective network appears to be associated with excessive negative mood (dysphoria) in the patients; decreased connectivity of a frontal-striatal reward network has been suggested to account for loss of interest, motivation, and pleasure (anhedonia); enhanced default mode network connectivity seems to be associated with depressive rumination; and diminished connectivity of a dorsal cognitive control network is thought to underlie cognitive deficits especially ineffective top-down control of negative thoughts and emotions in depressed patients. Moreover, the restoration of connectivity of these networks-and corresponding symptom improvement-following antidepressant treatment (including medication, psychotherapy, and brain stimulation techniques) serves as evidence for the crucial role of these networks in the pathophysiology of depression.

Network asymmetry of motor areas revealed by resting-state functional magnetic resonance imaging.

There are ample functional magnetic resonance imaging (fMRI) studies on functional brain asymmetries, and the asymmetry of cerebral network in the resting state may be crucial to brain function organization. In this paper, a unified schema of voxel-wise functional connectivity and asymmetry analysis was presented and the network asymmetry of motor areas was studied. Twelve healthy male subjects with mean age 29.8 ± 6.4 were studied. Functional network in the resting state was described by using functional connectivity magnetic resonance imaging (fcMRI) analysis. Motor areas were selected as regions of interest (ROIs). Network asymmetry, including intra- and inter-network asymmetries, was formulated and analyzed. The intra-network asymmetry was defined as the difference between the left and right part of a particular functional network. The inter-network asymmetry was defined as the difference between the networks for a specific ROI in the left hemisphere and its homotopic ROI in the right hemisphere. Primary motor area (M1), primary sensory area (S1) and premotor area (PMA) exhibited higher functional correlation with the right parietal-temporal-occipital circuit and the middle frontal gyrus than they did with the left hemisphere. Right S1 and right PMA exhibited higher functional correlation with the ipsilateral precentral and supramarginal areas. There exist the large-scale hierarchical network asymmetries of the motor areas in the resting state. These asymmetries imply the right hemisphere dominance for predictive motor coding based on spatial attention and higher sensory processing load for the motor performance of non-dominant hemisphere.