Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders.

AIM: Increasing evidence suggests that psychiatric disorders are linked to alterations in the mesocorticolimbic dopamine-related circuits. However, the common and disease-specific alterations remain to be examined in schizophrenia (SCZ), major depressive disorder (MDD), and autism spectrum disorder (ASD). Thus, this study aimed to examine common and disease-specific features related to mesocorticolimbic circuits. METHODS: This study included 555 participants from four institutes with five scanners: 140 individuals with SCZ (45.0% female), 127 individuals with MDD (44.9%), 119 individuals with ASD (15.1%), and 169 healthy controls (HC) (34.9%). All participants underwent resting-state functional magnetic resonance imaging. A parametric empirical Bayes approach was adopted to compare estimated effective connectivity among groups. Intrinsic effective connectivity focusing on the mesocorticolimbic dopamine-related circuits including the ventral tegmental area (VTA), shell and core parts of the nucleus accumbens (NAc), and medial prefrontal cortex (mPFC) were examined using a dynamic causal modeling analysis across these psychiatric disorders. RESULTS: The excitatory shell-to-core connectivity was greater in all patients than in the HC group. The inhibitory shell-to-VTA and shell-to-mPFC connectivities were greater in the ASD group than in the HC, MDD, and SCZ groups. Furthermore, the VTA-to-core and VTA-to-shell connectivities were excitatory in the ASD group, while those connections were inhibitory in the HC, MDD, and SCZ groups. CONCLUSION: Impaired signaling in the mesocorticolimbic dopamine-related circuits could be an underlying neuropathogenesis of various psychiatric disorders. These findings will improve the understanding of unique neural alternations of each disorder and will facilitate identification of effective therapeutic targets.

The association between clinical symptoms and later subjective quality of life in individuals with ultra-high risk for psychosis and recent-onset psychotic disorder: A longitudinal investigation.

AIM: Subjective quality of life is a clinically relevant outcome that is strongly associated with the severity of clinical symptoms in individuals with ultra-high risk for psychosis and patients with recent-onset psychotic disorder. Our objective was to examine whether longitudinal changes in clinical symptoms are associated with quality of life in ultra-high risk individuals and patients with recent-onset psychotic disorder. METHODS: Individuals with ultra-high risk and patients with recent-onset psychosis disorder were recruited in the same clinical settings at baseline and were followed up with more than 6 months and less than 5 years later. We assessed five factors of clinical symptoms using the positive and negative syndrome scale, and quality of life using the World Health Organization quality of life questionnaire-short form. We used multiple regression to examine the relationships between clinical symptoms and quality of life while controlling for diagnosis, follow-up period, age, and sex. RESULTS: Data were collected from 22 individuals with ultra-high risk and 27 patients with recent-onset psychosis disorder. The multiple regression analysis results indicated that the more severe anxiety/depression was at baseline, the poorer the quality of life at follow-up. Further, improvement of anxiety/depression and disorganized thoughts were associated with improvement in quality of life. The difference in diagnosis did not affect the association between clinical symptoms and quality of life. CONCLUSION: These findings suggest that the improvement of anxiety/depression and disorganized thoughts is important in the early stages of psychosis before it becomes severe, affecting the quality of life.

Association between duration of breastfeeding based on maternal reports and dorsal and ventral striatum and medial orbital gyrus volumes in early adolescence.

Maternal breastfeeding has an impact on motor and emotional development in children of the next generation. Elucidating how breastfeeding during infancy affects brain regional structural development in early adolescence will be helpful for promoting healthy development. However, previous studies that have shown relationships between breastfeeding during infancy and cortical brain regions in adolescence are usually based on maternal retrospective recall of breastfeeding, and the accuracy of the data is unclear. In this study, we investigated the association between breastfeeding duration and brain regional volume in a population-neuroimaging study of early adolescents in Japan (N â€‹= â€‹207; 10.5-13.4 years) using voxel-based morphometry, which enabled us to analyze the whole brain. We evaluated breastfeeding duration as indexed by maternal and child health handbook records during infancy. The results showed a significant positive correlation between the duration of breastfeeding and gray matter volume in the dorsal and ventral striatum and the medial orbital gyrus. Post hoc exploratory analyses revealed that the duration of breastfeeding was significantly correlated with emotional behavior. Additionally, the volume in the medial orbital gyrus mediated an association between breastfeeding duration and emotional behavior. This is the first study to evaluate the effect of breastfeeding during infancy on regional brain volumes in early adolescence based on maternal and child health handbook records. Our findings shed light upon the importance of maternal breastfeeding for brain development related to emotional and motivational processing in early adolescence.

Cortical white matter microstructural alterations underlying the impaired gamma-band auditory steady-state response in schizophrenia.

The gamma-band auditory steady-state response (ASSR), primarily generated from the auditory cortex, has received substantial attention as a potential brain marker indicating the pathophysiology of schizophrenia. Previous studies have shown reduced gamma-band ASSR in patients with schizophrenia and demonstrated correlations with impaired neurocognition and psychosocial functioning. Recent studies in clinical and healthy populations have suggested that the neural substrates of reduced gamma-band ASSR may be distributed throughout the cortices surrounding the auditory cortex, especially in the right hemisphere. This study aimed to investigate associations between the gamma-band ASSR and white matter alterations in the bundles broadly connecting the right frontal, parietal and occipital cortices to clarify the networks underlying reduced gamma-band ASSR in patients with schizophrenia. We measured the 40 Hz ASSR using electroencephalography and diffusion tensor imaging in 42 patients with schizophrenia and 22 healthy comparison subjects. The results showed that the gamma-band ASSR was positively correlated with fractional anisotropy (an index of white matter integrity) in the regions connecting the right frontal, parietal and occipital cortices in healthy subjects (ß = 0.41, corrected p = 0.075, uncorrected p = 0.038) but not in patients with schizophrenia (ß = 0.17, corrected p = 0.46, uncorrected p = 0.23). These findings support our hypothesis that the generation of gamma-band ASSR is supported by white matter bundles that broadly connect the cortices and that these relationships may be disrupted in schizophrenia. Our study may help characterize and interpret reduced gamma-band ASSR as a useful brain marker of schizophrenia.

Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets.

BACKGROUND AND HYPOTHESIS: Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders. STUDY DESIGN: We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network. STUDY RESULTS: DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively. CONCLUSIONS: DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders.

Intergenerational transmission of the patterns of functional and structural brain networks.

There is clear evidence of intergenerational transmission of life values, cognitive traits, psychiatric disorders, and even aspects of daily decision making. To investigate biological substrates of this phenomenon, the brain has received increasing attention as a measurable biomarker and potential target for intervention. However, no previous study has quantitatively and comprehensively investigated the effects of intergenerational transmission on functional and structural brain networks. Here, by employing an unusually large cohort dataset (N = 84 parent-child dyads; 45 sons, 39 daughters, 81 mothers, and 3 fathers), we show that patterns of functional and structural brain networks are preserved over a generation. We also demonstrate that several demographic factors and behavioral/physiological phenotypes have a relationship with brain similarity. Collectively, our results provide a comprehensive picture of neurobiological substrates of intergenerational transmission and demonstrate the usability of our dataset for investigating the neurobiological substrates of intergenerational transmission.

Mismatch Negativity Predicts Remission and Neurocognitive Function in Individuals at Ultra-High Risk for Psychosis.

BACKGROUND: In the early intervention in psychosis, ultra-high risk (UHR) criteria have been used to identify individuals who are prone to develop psychosis. Although the transition rate to psychosis in individuals at UHR is 10% to 30% within several years, some individuals at UHR present with poor prognoses even without transition occurring. Therefore, it is important to identify biomarkers for predicting the prognosis of individuals at UHR, regardless of transition. We investigated whether mismatch negativity (MMN) in response to both duration deviant stimuli (dMMN) and frequency deviant stimuli (fMMN) could predict prognosis, including remission and neurocognitive function in individuals at UHR. MATERIALS AND METHODS: Individuals at UHR (n = 24) and healthy controls (HC; n = 18) participated in this study. In an auditory oddball paradigm, both dMMN and fMMN were measured at baseline. Remission and neurocognitive function after > 180 days were examined in the UHR group. Remission from UHR was defined as functional and symptomatic improvement using the Global Assessment of Functioning (GAF) score and Scale of Prodromal Symptoms (SOPS) positive subscales. Neurocognitive function was measured using the Brief Assessment of Cognition in Schizophrenia (BACS). We examined differences in MMN amplitude at baseline between those who achieved remission (remitters) and those who did not (non-remitters). Multiple regression analyses were performed to identify predictors for functioning, positive symptoms, and neurocognitive function. RESULTS: Compared with the HC group, the UHR group had a significantly attenuated dMMN amplitude (p = 0.003). In the UHR group, GAF scores significantly improved during the follow-up period (mean value 47.1 to 55.5, p = 0.004). The dMMN amplitude at baseline was significantly larger in the remitter (n = 6) than in the non-remitter group (n = 18) (p = 0.039). The total SOPS positive subscale scores and fMMN amplitude at baseline could predict BACS attention subscore at the follow-up point (SOPS positive subscales, p = 0.030; fMMN, p = 0.041). CONCLUSION: Our findings indicate that dMMN and fMMN predicted remission and neurocognitive function, respectively, in individuals at UHR, which suggests that there are both promising biomarker candidates for predicting prognosis in individuals at UHR.

Resting-state EEG beta band power predicts quality of life outcomes in patients with depressive disorders: A longitudinal investigation.

BACKGROUND: Quality of life is severely impaired in patients with depressive disorders. Previous studies have focused on biomarkers predicting depressive symptomatology; however, studies investigating biomarkers predicting quality of life outcomes are limited. Improving quality of life is important because it is related not only to mental health but also to physical health. We need to develop a biomarker related to quality of life as a therapeutic target for patients with depressive disorders. Resting-state electroencephalography (EEG) is easy to record in clinical settings. The index of bandwidth spectral power predicts treatment response in depressive disorders and thus may be a candidate biomarker. However, no longitudinal studies have investigated whether EEG-recorded power could predict quality of life outcomes in patients with depressive disorders. METHODS: The resting-state EEG-recorded bandwidth spectral power at baseline and the World Health Organization Quality of Life (QOL)-26 scores at 3-year follow-up were measured in 44 patients with depressive disorders. RESULTS: The high beta band power (20-30 Hz) at baseline significantly predicted QOL at the 3-year follow-up after considering depressive symptoms and medication effects in a longitudinal investigation in patients with depressive disorders (ß = 0.38, p = 0.01). LIMITATIONS: We did not have healthy subjects as a comparison group in this study. CONCLUSIONS: Our findings suggest that resting-state beta activity has the potential to be a useful biomarker for predicting future quality of life outcomes in patients with depressive disorders.