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Aim: Bipolar disorder (BD) is a common psychiatric disorder characterized by alterations between manic/hypomanic and depressive states. Rare pathogenic copy number variations (CNVs) that overlap with exons of synaptic genes have been associated with BD. However, no study has comprehensively explored CNVs in synaptic genes associated with BD. Here, we evaluated the relationship between BD and rare CNVs that overlap with synaptic genes, not limited to exons, in the Japanese population., Methods: Using array comparative genome hybridization, we detected CNVs in 1839 patients with BD and 2760 controls. We used the Synaptic Gene Ontology database to identify rare CNVs that overlap with synaptic genes. Using gene-based analysis, we compared their frequencies between the BD and control groups. We also searched for synaptic gene sets related to BD. The significance level was set to a false discovery rate of 10%., Results: The RNF216 gene was significantly associated with BD (odds ratio, 4.51 [95% confidence interval, 1.66-14.89], false discovery rate < 10%). The BD-associated CNV that corresponded with RNF216 also partially overlapped with the minimal critical region of the 7p22.1 microduplication syndrome. The integral component of the postsynaptic membrane (Gene Ontology:0099055) was significantly associated with BD. The CNV overlapping with the intron region of GRM5 in this gene set showed a nominal significant association between cases and controls (P < 0.05)., Conclusion: We provide evidence that CNVs in RNF216 and postsynaptic membrane-related genes confer a risk of BD, contributing to a better understanding of the pathogenesis of BD., (© 2024 The Author(s). Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

Dietary habits may impact the prevention and management of schizophrenia (SCZ) and bipolar disorder (BD), and genetic and environmental factors can influence both these habits and these disorders. This study investigated the effects of genetic predispositions to SCZ and BD on current dietary habits among older adults with lifestyle-related diseases, potentially offering insights for preventive mental health strategies. A cohort of 730 older patients who were diagnosed with or suspected of having lifestyle-related diseases was assessed for eight current dietary categories: miso soup, Japanese tea, green and yellow vegetables, light-colored vegetables, fruits, pickles, meats, and soybeans. Polygenic risk scores (PRSs) for the risk of SCZ and BD, including BD types I and II, the shared risk of SCZ and BD, and the differentiation of SCZ from BD, were calculated utilizing data from large-scale genome-wide association studies (GWASs). Our findings revealed that PRSs for SCZ and BD risk significantly influenced specific dietary habits, particularly decreased consumption of nutrient-rich foods such as light-colored vegetables (SCZ, R 2  = 0.0096, p = 3.54 × 10 -3 ; BD, R 2  = 0.0074, p = 9.09 × 10 -3 ) and soybeans (SCZ, R 2  = 0.0061, p = 0.019; BD, R 2  = 0.014, p = 8.38 × 10 -4 ). Notable differences in dietary effects were observed between PRSs for BD I and BD II, with a more pronounced impact associated with BD I (e.g., light-colored vegetables, BD I, R 2  = 0.015, p = 3.11 × 10 -4 ; BD II, p > 0.05). Moreover, shared genetic factors for SCZ and BD were correlated with lower intakes of miso soup (R 2  = 0.013, p = 1.21 × 10 -3 ), Japanese tea (R 2  = 0.0092, p = 5.59 × 10 -3 ), light-colored vegetables (R 2  = 0.010, p = 2.92 × 10 -3 ), and soybeans (R 2  = 0.014, p = 3.13 × 10 -4 ). No significant correlations were found between PRSs for differentiating SCZ from BD and any dietary patterns (p > 6.25 × 10 -3 ). Genetic risks shared by individuals with SCZ and BD may influence dietary choices in older adults, emphasizing the potential for dietary modifications as part of comprehensive strategies for the prevention of the SCZ and BD onset, as well as for the treatment of individuals at risk of or diagnosed with SCZ and BD., (© 2024. The Author(s).)

Background: Genetic and environmental factors contribute to the pathogenesis of schizophrenia (SZ) and bipolar disorder (BD). Among genetic risk groups stratified by combinations of Polygenic Risk Score (PRS) deciles for SZ, BD and SZ versus BD, genetic SZ risk groups had high SZ risk and prominent cognitive impairments. Furthermore, epigenetic alterations are implicated in these disorders. However, it was unclear whether DNA Methylation Risk Scores (MRSs) for SZ risk derived from blood and brain tissues were associated with SZ risk, particularly the PRS-stratified genetic SZ risk group., Methods: Epigenome-wide association studies (EWASs) of SZ risk in whole blood were preliminarily conducted between 66 SZ patients and 30 healthy controls (HCs) and among genetic risk groups (individuals with low genetic risk for SZ and BD in HCs (n=30) and in SZ patients (n=11), genetic BD risk in SZ patients (n=25) and genetic SZ risk in SZ patients (n=30)) stratified by combinations of PRSs for SZ, BD and SZ versus BD. Next, differences in MRSs based on independent EWASs of SZ risk in whole blood, postmortem frontal cortex (FC) and superior temporal gyrus (STG) were investigated among our case‒control and PRS-stratified genetic risk status groups., Results: Among case‒control and genetic risk status groups, 33 and 351 genome-wide significant differentially methylated positions (DMPs) associated with SZ were identified, respectively, many of which were hypermethylated. Compared with the low genetic risk in HCs group, the genetic SZ risk in SZ group had 39 genome-wide significant DMPs, while the genetic BD risk in SZ group had only six genome-wide significant DMPs. The MRSs for SZ risk derived from whole blood, FC and STG were higher in our SZ patients than in HCs in whole blood and were particularly higher in the genetic SZ risk in SZ group than in the low genetic risk in HCs and genetic BD risk in SZ groups. Conversely, the MRSs for SZ risk based on our whole-blood EWASs among genetic risk groups were also associated with SZ in the FC and STG. There were no correlations between the MRSs and PRSs., Conclusions: These findings suggest that the MRS is a potential genetic marker in understanding SZ, particularly in patients with a genetic SZ risk., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. Published by BMJ.)

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, 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 (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection., (© 2023. The Author(s).)

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms., (© 2023. The Author(s).)

Background: Individuals with schizophrenia (SCZ) and bipolar disorder (BD) display cognitive impairments, but the impairments in those with SCZ are more prominent, supported by genetic overlap between SCZ and cognitive impairments. However, it remains unclear whether cognitive performances differ between individuals at high and low genetic risks for SCZ or BD., Methods: Using the latest Psychiatric Genomics Consortium (PGC) data, we calculated PGC3 SCZ-, PGC3 BD-, and SCZ v. BD polygenic risk scores (PRSs) in 173 SCZ patients, 70 unaffected first-degree relatives (FRs) and 196 healthy controls (HCs). Based on combinations of three PRS deciles, individuals in the genetic SCZ, genetic BD and low genetic risk groups were extracted. Cognitive performance was assessed by the Brief Assessment of Cognition in Schizophrenia., Results: SCZ-, BD-, SCZ v. BD-PRSs were associated with case-control status ( R 2 = 0.020-0.061), and SCZ-PRS was associated with relative-control status ( R 2 = 0.023). Furthermore, individuals in the highest decile for SCZ PRSs had elevated BD-PRSs [odds ratio (OR) = 6.33] and SCZ v. BD-PRSs (OR = 1.86) compared with those in the lowest decile. Of the three genetic risk groups, the low genetic risk group contained more HCs, whereas the genetic BD and SCZ groups contained more SCZ patients ( p < 0.05). SCZ patients had widespread cognitive impairments, and FRs had cognitive impairments that were between those of SCZ patients and HCs ( p < 0.05). Cognitive differences between HCs in the low genetic risk group and SCZ patients in the genetic BD or genetic SCZ groups were more prominent (Cohen's d > -0.20) than those between HCs and SCZ patients in the no genetic risk group. Furthermore, SCZ patients in the genetic SCZ group displayed lower scores in verbal fluency and attention than those in the genetic BD group ( d > -0.20)., Conclusions: Our findings suggest that cognitive impairments in SCZ are partially mediated through genetic loadings for SCZ but not BD.

Cigarette smoking is highly prevalent among patients with bipolar disorder (BD). Structural brain abnormalities related to smoking behavior and BD risk are indicated by magnetic resonance imaging (MRI) studies. However, cortical alterations common to smoking behavior and BD remain unclear. Our purpose was to identify common cortical alterations between smoking behavior and BD. 3T MRI-based indices of cortical thickness and surface area using FreeSurfer were acquired from 166 healthy control (HC) nonsmokers, 39 HC smokers, 33 BD nonsmokers, and 18 BD smokers. A stepwise discriminant-function analysis (DFA) with cortical structures as predictors was performed to classify BD patients into nonsmokers and smokers. Next, DFAs with the selected structures as predictors were performed to discriminate smoking status or diagnostic status. Differences in the selected features among the four groups were examined. The first DFA showed that six brain features discriminated between nonsmokers and smokers among BD patients. The six brain features related to BD smoking status also discriminated between HCs and BD patients and HC nonsmokers and BD smokers. Among the six features, left insular thickness showed a negative additive effect of smoking status and BD diagnosis. Our findings suggest the common neurobiological involvement of insular thickness in smoking behavior and BDrisk., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD)., Methods: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD., Results: In genic CNVs, we found an increased burden of smaller (<100 kb) exonic deletions in BD, which contrasted with the highest burden of larger (>500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25-0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue., Conclusions: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Patients with schizophrenia and bipolar disorder have an overlapping polygenic architecture and clinical similarities, although the 2 disorders are distinct diagnoses with clinical dissimilarities. It remains unclear whether there are specific differences in subcortical volumes between schizophrenia and bipolar disorder, and whether the subcortical differences are affected by any clinical characteristics. We investigated differences in subcortical volumes bilaterally among patients with schizophrenia, patients with bipolar disorder and healthy controls. We also investigated the influences of clinical characteristics on specific subcortical volumes in these patient groups., Methods: We collected 3 T T -weighted MRI brain scans from 413 participants (157 with schizophrenia, 51 with bipolar disorder and 205 controls) with a single scanner at a single institute. We used FreeSurfer version 6.0 for processing the 1 -weighted MRI brain scans from 413 participants (157 with schizophrenia, 51 with bipolar disorder and 205 controls) with a single scanner at a single institute. We used FreeSurfer version 6.0 for processing the T 1 -weighted images to segment the following subcortical brain volumes: thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens. Differences in the 7 subcortical volumes were investigated among the groups. We also evaluated correlations between subcortical volumes and clinical variables in these patient groups., Results: Of 7 subcortical regions, patients with schizophrenia had significantly smaller volumes in the left thalamus (Cohen d = -0.29, p = 5.83 × 10 -3 ), bilateral hippocampi (left, d = -0.36, p = 8.85 × 10 -4 ; right, d = -0.41, p = 1.15 × 10 -4 ) and left amygdala ( d = -0.31, p = 4.02 × 10 -3 ) than controls. Compared with controls, patients with bipolar disorder had bilateral reductions only in the hippocampal volumes (left, d = -0.52, p = 1.12 × 10 -3 ; right, d = -0.58, p = 0.30 × 10 -4 ). We also found that patients with schizophrenia had significantly smaller volumes in the bilateral amygdalae (left, d = -0.43, p = 4.22 × 10 -3 ; right, d = -0.45, p = 4.56 × 10 -3 ) than patients with bipolar disorder. We did not find any significant volumetric differences in the other 6 subcortical structures between patient groups ( p > 0.05). Smaller left amygdalar volumes were significantly correlated with younger onset age only in patients with schizophrenia ( r = 0.22, p = 5.78 × 10 -3 )., Limitations: We did not evaluate the differences in subcortical volumes between patients stratified based on clinical bipolar disorder subtype and a history of psychotic episodes because our sample size of patients with bipolar disorder was limited., Conclusion: Our findings suggest that volumetric differences in the amygdala between patients with schizophrenia and those with bipolar disorder may be a putative biomarker for distinguishing 2 clinically similar diagnoses., Competing Interests: Competing interests: None declared., (© 2022 CMA Impact Inc. or its licensors.)

Background: Intelligence is inversely associated with schizophrenia (SCZ) and bipolar disorder (BD); it remains unclear whether low intelligence is a cause or consequence. We investigated causal associations of intelligence with SCZ or BD risk and a shared risk between SCZ and BD and SCZ-specific risk., Methods: To estimate putative causal associations, we performed multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) using generalized summary-data-based MR (GSMR). Summary-level datasets from five GWASs (intelligence, SCZ vs. control [CON], BD vs. CON, SCZ + BD vs. CON, and SCZ vs. BD; sample sizes of up to 269,867) were utilized., Results: A strong bidirectional association between risks for SCZ and BD was observed (odds ratio; ORSCZ → BD = 1.47, p = 2.89 × 10-41, ORBD → SCZ = 1.44, p = 1.85 × 10-52). Low intelligence was bidirectionally associated with a high risk for SCZ, with a stronger effect of intelligence on SCZ risk (ORlower intelligence → SCZ = 1.62, p = 3.23 × 10-14) than the reverse (ORSCZ → lower intelligence = 1.06, p = 3.70 × 10-23). Furthermore, low intelligence affected a shared risk between SCZ and BD (OR lower intelligence → SCZ + BD = 1.23, p = 3.41 × 10-5) and SCZ-specific risk (ORlower intelligence → SCZvsBD = 1.64, p = 9.72 × 10-10); the shared risk (ORSCZ + BD → lower intelligence = 1.04, p = 3.09 × 10-14) but not SCZ-specific risk (ORSCZvsBD → lower intelligence = 1.00, p = 0.88) weakly affected low intelligence. Conversely, there was no significant causal association between intelligence and BD risk (p > 0.05)., Conclusions: These findings support observational studies showing that patients with SCZ display impairment in premorbid intelligence and intelligence decline. Moreover, a shared factor between SCZ and BD might contribute to impairment in premorbid intelligence and intelligence decline but SCZ-specific factors might be affected by impairment in premorbid intelligence. We suggest that patients with these genetic factors should be categorized as having a cognitive disorder SCZ or BD subtype.

Background: Impairments in intelligence are more severe in patients with schizophrenia (SCZ) than in patients with bipolar disorder (BD) despite clinical and genetic similarities between the disorders. Genetic loci differentiating SCZ from BD, that is, SCZ-specific risk, have been identified. Polygenetic [risk] scores (PGSs) for SCZ-specific risk are higher in SCZ patients than in healthy controls (HCs). However, the influence of genetic risk on impaired intelligence is poorly understood. Here, we investigated whether SCZ-specific risk could predict impairments in intelligence in SCZ patients and HCs., Methods: Large-scale genome-wide association study datasets related to SCZ vs BD, childhood intelligence (CHI), and adulthood intelligence (n = 12 441-282 014) were utilized to compute PGSs. PGSs derived from the genome-wide association studies were calculated for 130 patients with SCZ and 146 HCs. Premorbid and current intelligence and the decline were measured in SCZ patients and HCs. Correlations between PGSs and intelligence functions were investigated., Results: High PGSs for SCZ-specific risk were correlated with low premorbid intelligence in SCZ patients and HCs (β = -0.17, P = 4.12 × 10-3). The correlation was still significant after adjusting for diagnostic status (β = -0.13, P = .024). There were no significant correlations between PGSs for SCZ-specific risk and current intelligence or intelligence decline (P > .05). PGSs for CHI were lower in SCZ patients than in HCs (R2 = 0.025, P = .025), while the PGSs for CHI were not significantly correlated with premorbid and current intelligence, the decline, or the PGSs for SCZ-specific risk (P > .05)., Conclusions: These findings suggest that genetic factors differentiating SCZ from BD might affect the pathogenesis of SCZ and/or pathological differences between SCZ and BD via the impairment of premorbid intelligence, that is, crystallized intelligence, while genetic factors for CHI might affect the pathogenesis of SCZ but not via impairments in intelligence., (© The Author(s) 2021. Published by Oxford University Press on behalf of CINP.)

Background: The genetic etiology of schizophrenia (SCZ) overlaps with that of other major psychiatric disorders in samples of European ancestry. The present study investigated transethnic polygenetic features shared between Japanese SCZ or their unaffected first-degree relatives and European patients with major psychiatric disorders by conducting polygenic risk score (PRS) analyses., Methods: To calculate PRSs for 5 psychiatric disorders (SCZ, bipolar disorder [BIP], major depressive disorder, autism spectrum disorder, and attention-deficit/hyperactivity disorder) and PRSs differentiating SCZ from BIP, we utilized large-scale European genome-wide association study (GWAS) datasets as discovery samples. PRSs derived from these GWASs were calculated for 335 Japanese target participants [SCZ patients, FRs, and healthy controls (HCs)]. We took these PRSs based on GWASs of European psychiatric disorders and investigated their effect on risk in Japanese SCZ patients and unaffected first-degree relatives., Results: The PRSs obtained from European SCZ and BIP patients were higher in Japanese SCZ patients than in HCs. Furthermore, PRSs differentiating SCZ patients from European BIP patients were higher in Japanese SCZ patients than in HCs. Interestingly, PRSs related to European autism spectrum disorder were lower in Japanese first-degree relatives than in HCs or SCZ patients. The PRSs of autism spectrum disorder were positively correlated with a young onset age of SCZ., Conclusions: These findings suggest that polygenic factors related to European SCZ and BIP and the polygenic components differentiating SCZ from BIP can transethnically contribute to SCZ risk in Japanese people. Furthermore, we suggest that reduced levels of an ASD-related genetic factor in unaffected first-degree relatives may help protect against SCZ development., (© The Author(s) 2020. Published by Oxford University Press on behalf of CINP.)

Family history (FH) is predictive of the development of major psychiatric disorders (PSY). Familial psychiatric disorders are largely a consequence of genetic factors and typically exhibit more severe impairments. Decreased prefrontal activity during verbal fluency testing (VFT) may constitute an intermediate phenotype for PSY. We investigated whether familial PSY were associated with a greater severity of prefrontal dysfunction in accordance with genetic loading. We measured prefrontal activity during VFT using near-infrared spectroscopy (NIRS) in patients with schizophrenia (SCZ, n = 45), major depressive disorder (MDD, n = 26) or bipolar disorder (BIP, n = 22) and healthy controls (HC, n = 51). We compared prefrontal activity among patients with or without FH and HC. Patients in the SCZ, MDD and BIP patient groups had lower prefrontal activity than HC subjects. Patients with and without FH in all diagnostic groups had lower prefrontal activity than HC subjects. Moreover, SCZ patients with FH had lower prefrontal activity than SCZ patients without FH. When we included patients with SCZ, MDD or BIP in the group of patients with PSY, the effects of psychiatric FH on prefrontal activity were enhanced. These findings demonstrate the association of substantially more severe prefrontal dysfunction with higher genetic loading in major psychiatric disorders.

Impaired social functioning is a hallmark of major psychiatric disorders. The purpose of this study was to detect a disorder-specific factor of social dysfunction among patients with major psychiatric disorders (PSY), including schizophrenia (SCZ), bipolar disorder (BIP) and major depressive disorder (MDD). Social functioning was assessed in patients with SCZ (n=80), BIP (n=27) or MDD (n=29) and healthy controls (HC, n=68) using the Social Functioning Scale (SFS). Compared to HC, the SCZ, BIP and MDD patient groups showed lower total SFS scores. No differences in the total scores for social functioning were observed between patient groups. We next investigated seven subscales of the SFS among PSY and observed significant diagnostic effects on all subscales of the SFS. Notably, patients with SCZ have poorer interpersonal communication than patients with MDD. Furthermore, the poorer interpersonal communication score was significantly correlated with an increase in schizotypal personality traits, as assessed by the Schizotypal Personality Questionnaire (SPQ) in HC. Although there were no differences in overall social functioning among PSY, disorder-specific factors, such as interpersonal communication, were evident in SCZ. The correlation between poor interpersonal communication and the increase in schizotypal traits suggests that poor interpersonal communication may be an intermediate phenotype of SCZ., (Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.)

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 cross-disorder 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.

Background: Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders. Methods: To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes. Results: Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased. Conclusions: These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders. [ABSTRACT FROM AUTHOR]

Sensory processing is disrupted in several psychiatric disorders, including schizophrenia, bipolar disorder, and autism spectrum disorder. In this review, we focus on the electrophysiological auditory steady-state response (ASSR) driven by high-frequency stimulus trains as an index for disease-associated sensory processing deficits. The ASSR amplitude is suppressed within the gamma band (≥30 Hz) among these patients, suggesting an imbalance between GABAergic and N-methyl-D-aspartate (NMDA) receptor-mediated neurotransmission. The reduced power and synchronization of the 40-Hz ASSR are robust in patients with schizophrenia. In recent years, similar ASSR deficits at gamma frequencies have also been reported in patients with bipolar disorder and autism spectrum disorder. We summarize ASSR abnormalities in each of these psychiatric disorders and suggest that the observed commonalities reflect shared pathophysiological mechanisms. We reviewed studies on phase resetting in which a salient sensory stimulus affects ASSR. Phase resetting induces the reduction of both the amplitude and phase of ASSR. Moreover, phase resetting is also affected by rare auditory stimulus patterns or superimposed stimuli of other modalities. Thus, sensory memory and multisensory integration can be investigated using phase resetting of ASSR. Here, we propose that ASSR amplitude, phase, and resetting responses are sensitive indices for investigating sensory processing dysfunction in psychiatric disorders. [ABSTRACT FROM AUTHOR]

Psychiatric disorders as well as subcortical brain volumes are highly heritable. Large-scale genome-wide association studies (GWASs) for these traits have been performed. We investigated the genetic correlations between five psychiatric disorders and the seven subcortical brain volumes and the intracranial volume from large-scale GWASs by linkage disequilibrium score regression. We revealed weak overlaps between the genetic variants associated with psychiatric disorders and subcortical brain and intracranial volumes, such as in schizophrenia and the hippocampus and bipolar disorder and the accumbens. We confirmed shared aetiology and polygenic architecture across the psychiatric disorders and the specific subcortical brain and intracranial volume. [ABSTRACT FROM AUTHOR]

The single nucleotide polymorphism (SNP) rs13438494 in intron 24 of PCLO was significantly associated with bipolar disorder in a meta-analysis of genome-wide association studies. In this study, we performed functional minigene analysis and bioinformatics prediction of splicing regulatory sequences to characterize the deep intronic SNP rs13438494. We constructed minigenes with A and C alleles containing exon 24, intron 24, and exon 25 of PCLO to assess the genetic effect of rs13438494 on splicing. We found that the C allele of rs13438494 reduces the splicing efficiency of the PCLO minigene. In addition, prediction analysis of enhancer/silencer motifs using the Human Splice Finder web tool indicated that rs13438494 induces the abrogation or creation of such binding sites. Our results indicate that rs13438494 alters splicing efficiency by creating or disrupting a splicing motif, which functions by binding of splicing regulatory proteins, and may ultimately result in bipolar disorder in affected people. [ABSTRACT FROM AUTHOR]

The current diagnostic tests for mood disorders, including major depressive disorder (MDD) and bipolar disorder (BD), have limitations. Inflammatory markers, growth factors, and oxidative stress markers are involved in the pathophysiology of mood disorders. A multi-assay biological diagnostic test combining these biomarkers might improve diagnostic efficiency. The plasma levels of soluble tumor necrosis factor receptor 2 (sTNFR2), epidermal growth factor (EGF), and myeloperoxidase were measured in 40 MDD patients, 40 BD patients and 40 controls in a Japanese population. We also investigated the plasma levels of these markers in 40 patients with schizophrenia to determine the utility of these markers in differential diagnosis. The plasma levels of sTNFR2 were significantly higher in BD and schizophrenia patients than in controls. The plasma levels of EGF and myeloperoxidase were significantly higher in patients with BD than in controls. The correct classification rate obtained from discriminant analysis with sTNFR2 and EGF between controls and mood disorders was 69.2%, with a sensitivity and specificity of 62.5% and 82.5%, respectively. The correct classification rate obtained from discriminant analysis with sTNFR2 and EGF between controls and BD was 85.0%, with a sensitivity and specificity of 77.6% and 92.5%, respectively. Our results suggest that sTNFR2 and EGF could be biological markers of BD. Further studies are needed to determine the utility of these markers in diagnostic tests for mood disorders. [ABSTRACT FROM AUTHOR]