Search

Subcortical brain structures are the hubs for various psycho-behavioral functions. There is no mega-analysis to simultaneously investigate subcortical volumetric alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder. Nor are there any neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. We conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in these disorders using T1-weighted images of 5,604 subjects (3,078 controls and 2,526 patients). We found schizophrenia-specific and cross-disorder shared alterations. Moreover, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely and moderately smaller limbic regions, larger basal ganglia, and normal volumes, for predicting cognitive/social functioning. Our results will contribute to the future creation of novel biological data-driven psychiatry diagnostic criteria, expected to support appropriate treatment selection.

The heterogeneity of major depressive disorder (MDD) is attributed to the fact that diagnostic criteria (e.g., DSM-5) are only based on clinical symptoms. The discovery of blood biomarkers has the potential to change the diagnosis of MDD. The purpose of this study was to identify blood biomarkers of DNA methylation by strategically subtyping patients with MDD by onset age. We analyzed genome-wide DNA methylation of patients with adult-onset depression (AOD; age ≥ 50 years, age at depression onset

The prevalence of depression in later life is higher in women than in men. However, the sex difference in the pathophysiology of depression in elderly patients is not fully understood. Here, we performed gene expression profiling in leukocytes of middle-aged and elderly patients with major depressive disorder, termed later-life depression (LLD) in this context, and we characterized the sex-dependent pathophysiology of LLD. A microarray dataset obtained from leukocytes of patients (aged ≥ 50 years) with LLD (32 males and 39 females) and age-matched healthy individuals (20 males and 24 females) was used. Differentially expressed probes were determined by comparing the expression levels between patients and healthy individuals, and then functional annotation analyses (Ingenuity Pathway Analysis, Reactome pathway analysis, and cell-type enrichment analysis) were performed. A total of 1,656 probes were differentially expressed in LLD females, but only 3 genes were differentially expressed in LLD males. The differentially expressed genes in LLD females were relevant to leukocyte extravasation signaling, Tec kinase signaling and the innate immune response. The upregulated genes were relevant to myeloid lineage cells such as CD14+ monocytes. In contrast, the downregulated genes were relevant to CD4+ and CD8+ T cells. Remarkable innate immune signatures are present in the leukocytes of LLD females but not males. Because inflammation is involved in the pathophysiology of depression, the altered inflammatory activity may be involved in the pathophysiology of LLD in women. In contrast, abnormal inflammation may be an uncommon feature in LLD males.

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability., Biomarkers for psychiatric disorders based on neuroimaging data have yet to be put to practical use. This study overcomes the problems of inter-site differences in fMRI data by using a novel harmonization method, thereby successfully constructing a generalizable brain network marker of major depressive disorder across multiple imaging sites.

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable major depressive disorder (MDD) brain network markers which would distinguish patients from healthy controls (a classifier) or would predict symptom severity (a prediction model) based on resting state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD brain network markers. The classifier achieved 70% generalization accuracy, and the prediction model moderately well predicted symptom severity for an independent validation dataset with 449 participants from 4 different imaging sites. Finally, we found common 2 functional connections between those related to MDD diagnosis and those related to depression symptoms. The successful generalization to the perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

No neuroanatomical substrates for distinguishing between depression of bipolar disorder (dBD) and major depressive disorder (dMDD) are currently known. The aim of the current multicenter study was to identify neuroanatomical patterns distinct to depressed patients with the two disorders. Further analysis was conducted on an independent sample to enable generalization of results. We directly compared MR images of these subjects using voxel-based morphometry (VBM) and a support vector machine (SVM) algorithm using 1531 participants. The VBM analysis showed significantly reduced gray matter volumes in the bilateral dorsolateral prefrontal (DLPFC) and anterior cingulate cortices (ACC) in patients with dBD compared with those with dMDD. Patients with the two disorders shared small gray matter volumes for the right ACC and left inferior frontal gyrus when compared with healthy subjects. Voxel signals in these regions during SVM analysis contributed to an accurate classification of the two diagnoses. The VBM and SVM results in the second cohort also supported these results. The current findings provide new evidence that gray matter volumes in the DLPFC and ACC are core regions in displaying shared and distinct neuroanatomical substrates and can shed light on elucidation of neural mechanism for depression within the bipolar/major depressive disorder continuum.

Background Glycosylation is a common posttranslational modification in protein biosynthesis that is implicated in several disease states. It has been reported that specific protein glycan structures are useful as biomarkers for cancer and some neuropsychiatric diseases; however, the relationship between plasma protein glycosylation and major depressive disorder (MDD) has not been investigated to date. The aim of this study was to determine whether plasma protein glycan structures are altered in depression using a stress-based mouse model and samples from patients with MDD. Methods We used chronic ultra-mildly stressed mice that were untreated or treated with imipramine as mouse models of depression and remission, respectively. We also made comparisons between samples from depressed and remitted patients with MDD. Protein glycosylation was analyzed using a lectin microarray that included 45 lectins with binding affinities for various glycan structures. Results Sia-alpha2-6Gal/GalNAc was a commonly altered glycan structure in both depression model mice and patients with MDD. Moreover, the expression of ST6GALNAC2 was decreased in leukocytes from patients with MDD. Limitations Our study samples were small and we did not identify specific alpha2-6Gal/GalNAc-sialylated proteins. Conclusions The glycan structure Sia-alpha2-6GalNAc in plasma protein and ST6GALNAC2 expression in peripheral leukocytes may have utility as candidate biomarkers for the clinical diagnosis and monitoring of MDD.

Although literature evidence suggests deficits in social and non-social cognition in patients with autistic spectrum disorder (ASD) and schizophrenia (SCZ), the difference in neural correlates of the impairments between the two disorders has not been elucidated. We examined brain function in response to a non-social cognition and a social cognition task using functional near-infrared spectroscopy (fNIRS) in 13 patients with ASD, 15 patients with SCZ, and 18 healthy subjects. We assessed the brain function of participants using a verbal fluency task and an emotional facial recognition task. The patients with ASD showed significantly reduced brain activation in the left frontotemporal area during both tasks compared to healthy subjects. The patients with ASD with larger score in ‘attention to detail’ in the autism spectrum quotient showed lower activation of the left frontotemporal area during the two tasks. The patients with SCZ showed significantly reduced activation, compared to healthy subjects, and greater activation, compared to patients with ASD, in the area during the verbal fluency task. The patients with SCZ with more severe symptoms had lower brain activation during the task in this area. Our results suggest that two distinct areas are involved in the distinctive brain pathophysiology relevant to cognitive processing in patients with ASD and SCZ.

Data collected during a phonemic fluency task (or 'FAS test'), a standard component of neuropsychological batteries for assessment of cognitive deficits, may be language-dependent and may differ depending on second-language proficiency. The unique orthographic/phonological system of the task language, and the reported cognitive advantages inherent to bilinguals, may each influence the task's neural correlates. However, language background is not currently assessed in most studies testing phonemic fluency. Here, we used 52-channel functional near-infrared spectroscopy in college-aged native-Japanese subjects to examine functional changes in oxygenated hemoglobin elicited during a phonemic fluency task performed in Japanese and in English. We found activity differences that were related to task language and second-language proficiency. Besides loci activated in the Japanese test, bilateral precentral channels were specifically recruited in the English test. Furthermore, the higher-proficiency group showed almost no increase in oxygenated hemoglobin in either language context, whereas participants with lower proficiency showed widespread increases for both contexts. We interpret precentral increases as the consequence of additional articulatory resource recruitment in a second-language context. As for the lack of such variation in the higher-proficiency group, it may reflect an advantage in nonverbal executive control in this group. Together, our results point to language background and proficiency as confounding variables in neuroimaging studies of phonemic fluency and that the adequacy of such measures in populations with varying language backgrounds needs to be considered in future studies.

Although major depressive disorder (MDD) is a leading cause of disability worldwide, its pathophysiology is poorly understood. Increasing evidence suggests that aberrant regulation of transcription plays a key role in the pathophysiology of MDD. Recently, long noncoding RNAs (lncRNAs) have been recognized for their important functions in chromatin structure, gene expression, and the subsequent manifestation of various biological processes in the central nervous system. However, it is unclear whether the aberrant expression and function of lncRNAs are associated with the pathophysiology of MDD. In this study, we sought to evaluate the expression of lncRNAs in peripheral blood leukocytes as potential biomarkers for MDD. We measured the expression levels of 83 lncRNAs in the peripheral blood leukocytes of 29 MDD patients and 29 age- and gender-matched healthy controls using quantitative reverse transcription PCR (RT-qPCR) analysis. We found that MDD patients exhibited distinct expression signatures. Specifically, the expression level of one lncRNA (RMRP) was lower while the levels of four (Y5, MER11C, PCAT1, and PCAT29) were higher in MDD patients compared to healthy controls. The expression level of RMRP was correlated with depression severity as measured by the Hamilton Depression Rating Scale (HAM-D). Moreover, RMRP expression was lower in a mouse model of depression, corroborating the observation from MDD patients. Taken together, our data suggest that lower RMRP levels may serve as a potential biomarker for MDD.

Background Depression in old age is an increasing contributor to poor health and accompanying health care costs. Although there is an abundance of literature on later-life depression (LLD), the neural correlates have not been clarified. The aim of this study was to determine whether patients with LLD show abnormal gray matter volume (GMV) and white matter integrity by using multiple image analysis methods. Methods The study included 45 patients with LLD and 61 healthy participants who were matched for age, sex, years of education, and vascular risk factors. GMV was examined using voxel-based morphometry, while the white matter integrity was determined by tract-based spatial statistics and tract-specific analysis, which were obtained from high-resolution magnetic resonance images. Results Patients with LLD showed significantly less GMV in the orbitofrontal cortex, anterior cingulate, insula, amygdala, and temporal regions, as well as higher fractional anisotropy in the uncinate fasciculus, compared with healthy participants. Patients with LLD who had reduced orbitofrontal and insular GMV had more severe clinical variables. The reduced orbitofrontal GMV was associated with higher fractional anisotropy in the uncinate fasciculus. Limitation The effects of medication should also be considered when interpreting the results of this study. Conclusion Our results suggest that regional GMV is linked to white matter integrity of the uncinate fasciculus in the orbitomedial prefrontal limbic network, and the disruption of this network may be involved in the pathophysiology of LLD.

Although patients with schizophrenia demonstrate abnormal processing of emotional face recognition, the neural substrates underlying this process remain unclear. We previously showed abnormal fronto-temporal function during facial expression of emotions, and cognitive inhibition in patients with schizophrenia using functional near-infrared spectroscopy (fNIRS). The aim of the current study was to use fNIRS to identify which brain regions involved in recognizing emotional faces are impaired in patients with schizophrenia, and to determine the neural substrates underlying the response to emotional facial expressions per se, and to facial expressions with cognitive inhibition. We recruited 19 patients with schizophrenia and 19 healthy controls, statistically matched on age, sex, and premorbid IQ. Brain function was measured by fNIRS during emotional face assessment and face identification tasks. Patients with schizophrenia showed lower activation of the right precentral and inferior frontal areas during the emotional face task compared to controls. Further, patients with schizophrenia were slower and less accurate in completing tasks compared to healthy participants. Decreasing performance was associated with increasing severity of the disease. Our present and prior studies suggest that the impaired behavioral performance in schizophrenia is associated with different mechanisms for processing emotional facial expressions versus facial expressions combined with cognitive inhibition.

Introduction Patients with schizophrenia (SZ) have deficits of facial emotion processing and cognitive inhibition, but the brain pathophysiology underlying these deficits and their interaction are not clearly understood. We tested brain activity during an emotional face go/no-go task that requires rapid executive control affected by emotional stimuli in patients with SZ using functional near-infrared spectroscopy (fNIRS). Methods Twenty-five patients with SZ and 28 healthy control subjects were studied. We evaluated behavioral performance and used fNIRS to measure oxygenated hemoglobin concentration changes in fronto-temporal areas during the emotional go/no-go task with emotional and non-emotional blocks. Results Patients with SZ made more errors and had longer reaction times in both test blocks compared with healthy subjects. Significantly greater activation in the inferior, superior, middle, and orbital frontal regions were observed in healthy subjects during the emotional go/no-go block compared to the non-emotional go/no-go block, but this difference was not observed in patients with SZ. Relative to healthy subjects, patients with SZ showed less activation in the superior and orbital frontal and middle temporal regions during the emotional go/no-go block. Discussion Our results suggest that fronto-temporal dysfunction in patients with SZ is due to an interaction between abnormal processing of emotional facial expressions with negative valence and cognitive inhibition, especially during the rapid selection of rule-based associations that override automatic emotional response tendencies. They indicate that fronto-temporal dysfunction is involved in the pathophysiology of emotional–cognitive deficits in patients with SZ.

The heterogeneity of depression (due to factors such as varying age of onset) may explain why biological markers of major depressive disorder (MDD) remain uncertain. We aimed to identify gene expression markers of MDD in leukocytes using microarray analysis. We analyzed gene expression profiles of patients with MDD (age ≥50, age of depression onset

Little is known about disorder-specific biomarkers of bipolar disorder (BD) and major depressive disorder (MDD). Our aim was to determine a neural substrate that could be used to distinguish BD from MDD. Our study included a BD group (10 patients with BD, 10 first-degree relatives (FDRs) of individuals with BD), MDD group (17 patients with MDD, 17 FDRs of individuals with MDD), and 27 healthy individuals. Structural and functional brain abnormalities were evaluated by voxel-based morphometry and a trail making test (TMT), respectively. The BD group showed a significant main effect of diagnosis in the gray matter (GM) volume of the anterior cingulate cortex (ACC; p = 0.01) and left insula (p < 0.01). FDRs of individuals with BD showed significantly smaller left ACC GM volume than healthy subjects (p < 0.01), and patients with BD showed significantly smaller ACC (p < 0.01) and left insular GM volume (p < 0.01) than healthy subjects. The MDD group showed a tendency toward a main effect of diagnosis in the right and left insular GM volume. The BD group showed a significantly inverse correlation between the left insular GM volume and TMT-A scores (p < 0.05). Our results suggest that the ACC volume could be a distinct endophenotype of BD, while the insular volume could be a shared BD and MDD endophenotype. Moreover, the insula could be associated with cognitive decline and poor outcome in BD.

Background Reduced motivation and blunted decision-making are key features of major depressive disorder (MDD). Patients with MDD show abnormal decision-making when given negative feedback regarding a reward. The brain mechanisms underpinning this behavior remain unclear. In the present study, we examined the association between rapid decision-making with negative feedback and brain volume in MDD. Methods Thirty-six patients with MDD and 54 age-, sex- and IQ-matched healthy subjects were studied. Subjects performed a rapid decision-making monetary task in which participants could make high- or low-risk choices. We compared between the 2 groups the probability that a high-risk choice followed negative feedback. In addition, we used voxel-based morphometry (VBM) to compare between group differences in gray matter volume, and the correlation between the probability for high-risk choices and brain volume. Results Compared to the healthy group, the MDD group showed significantly lower probabilities for high-risk choices following negative feedback. VBM analysis revealed that the MDD group had less gray matter volume in the right medial prefrontal cortex and orbitofrontal cortex (OFC) compared to the healthy group. The right OFC volume was negatively correlated with the probability that a high-risk choice followed negative feedback in patients with MDD. We did not observe these trends in healthy subjects. Conclusions Patients with MDD show reduced motivation for monetary incentives when they were required to make rapid decisions following negative feedback. We observed a correlation between this reduced motivation and gray matter volume in the medial and ventral prefrontal cortex, which suggests that these brain regions are likely involved in the pathophysiology of aberrant decision-making in MDD.

Abnormal emotional processing is involved in the pathophysiology of bipolar disorder (BD) and major depressive disorder (MDD). However, whether the neural mechanism underlying this deficit is a trait characteristic of BD and MDD is unclear. The aim of this study was to elucidate the similarities and differences in processing of emotional stimuli between patients with BD and MDD in remission, using functional near-infrared spectroscopy (fNIRS). Thirty-two patients (16 with BD and 16 with MDD) and 20 healthy control subjects matched for age, sex, handedness, and years of education were included. An emotional Stroop task, including happy, sad, and threat words, was used. The relative oxygenated and deoxygenated hemoglobin concentration ([oxy-Hb] and [deoxy-Hb]) changes in the frontal region were measured using 52-channels of NIRS. During the threat task, compared to healthy control subjects, patients with BD showed significantly increased [oxy-Hb] in the left inferior frontal region whereas patients with MDD showed significantly increased [oxy-Hb] in the left middle frontal region. During the happy task, compared to healthy control subjects, patients with BD showed significantly decreased [oxy-Hb] in the middle frontal region in both hemispheres. Moreover, patients with BD exhibited decreased [oxy-Hb] and increased [deoxy-Hb] in the superior frontal and middle frontal regions compared to MDD in response to the happy stimulus. No significant differences in [oxy-Hb] or [deoxy-Hb] were seen between the groups during the sad task. These results suggest that abnormal neural responses to emotional stimuli in patients with mood disorders in remission may be a trait characteristic, that negative emotional stimuli are associated with similar prefrontal responses, and that positive emotional stimuli are associated with different prefrontal responses in patients with BD and MDD. These findings indicate that different neural circuits play a role in emotional processing in BD and MDD; this may aid the elucidation of the pathophysiology of these two disorders.

This paper deals with the unique aspects and surgical indication of "dish face" deformity, including "flat face" deformity, due to cleft lip and palate. The importance of deformities of the nose and lip caused by cleft lip and palate and the role of their reconstruction in the treatment of "dish face" deformity are described in detail. For the protruding chin and pseudoprognathism, vertical osteotomy of the ramus of the mandible is recommended over advancement osteotomy of the hypoplastic maxilla.