Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental 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.

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning.

OBJECTIVE: Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques. METHODS: Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556-1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated. RESULTS: All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks. CONCLUSIONS: These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.

Cognitive performances across individuals at high genetic risk for schizophrenia, high genetic risk for bipolar disorder, and low genetic risks: a combined polygenic risk score approach.

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 (R2 = 0.020-0.061), and SCZ-PRS was associated with relative-control status (R2 = 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.

Shared genetic basis between reproductive behaviors and anxiety-related disorders.

Reproductive behaviors are associated with risks for psychiatric disorders. Reproductive phenotypes are moderately heritable and have genetic overlaps with risks for psychiatric disorders. However, the genetic and causal relationships between anxiety-related disorders or specific anxiety disorders and reproductive phenotypes remain unknown. We utilized large-scale genome-wide association study (GWAS) results (n = 9537-542,901) for five reproductive phenotypes [age at menarche, age at first sexual intercourse (AFS), age at first birth (AFB), number of children ever born (NEB), and age at menopause] and five anxiety-related disorders [panic disorder, anxiety disorders from the ANGST and the UK biobank (UKBB), posttraumatic stress disorder (PTSD) and obsessive-compulsive disorder (OCD)]. To assess genetic correlations and causal associations, linkage disequilibrium score regression and Mendelian randomization analyses, respectively, were performed. We found that AFS and AFB were negatively correlated with anxiety disorders ANGST (AFS: rg ± SE = -0.28 ± 0.08, p = 6.00 × 10-4; AFB: -0.45 ± 0.11, p = 3.26 × 10-5), anxiety disorders UKBB (AFS: -0.18 ± 0.03, p = 9.64 × 10-9; AFB; -0.25 ± 0.03, p = 2.90 × 10-13) and PTSD (AFS: -0.42 ± 0.12, p = 4.00 × 10-4; AFB: -0.44 ± 0.12, p = 2.00 × 10-4) and positively correlated with OCD (AFS: 0.25 ± 0.05, p = 2.46 × 10-6; AFB: 0.25 ± 0.05, p = 3.92 × 10-7). Conversely, NEB was negatively correlated with OCD (-0.28 ± 0.08, p = 6.00 × 10-4). We revealed bidirectional effects between earlier AFS and AFB and anxiety disorders (odds ratios: ORearlier AFS→Anxiety = 1.64, p = 2.27 × 10-8; ORearlier AFB→Anxiety = 1.15, p = 2.28 × 10-3; ORAnxiety→earlier AFS = 1.02, p = 6.62 × 10-8; ORAnxiety→earlier AFB = 1.08, p = 1.60 × 10-4). In contrast, we observed unidirectional effects of later AFS and AFB on OCD (ORlater AFS→OCD = 2.18, p = 2.16 × 10-6; ORlater AFB→OCD = 1.22, p = 0.016). We suggest that those who have earlier sexual debut and childbirth are prone to risk for anxiety disorders and vice versa, while those who have later sexual debut and childbirth are genetically prone to risk for OCD. Our findings further support revising the diagnostic criteria (DSM-5) such that OCD is independent from anxiety disorders.

Common brain cortical abnormality in smoking behavior and bipolar disorder: discriminant analysis using cortical thickness and surface area.

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.

Suppression of Low-Frequency Gamma Oscillations by Activation of 40-Hz Oscillation.

Gamma oscillations have received considerable attention owing to their association with cognitive function and various neuropsychiatric disorders. However, interactions of gamma oscillations at different frequency bands in humans remain unclear. In the present magnetoencephalographic study, brain oscillations in a wide frequency range were examined using a time-frequency analysis during the 20-, 30-, 40-, and 50-Hz auditory stimuli in 21 healthy subjects. First, dipoles for auditory steady-state response (ASSR) were estimated and interaction among oscillations at 10-60 Hz was examined using the source strength waveforms. Results showed the suppression of ongoing low-gamma oscillations at approximately 30 Hz during stimulation at 40 Hz. Second, multi-dipole analyses suggested that the main dipole for ASSR and dipoles for suppressed low-frequency gamma oscillations were distinct. Third, an all-sensor analysis was performed to clarify the distribution of the 40-Hz ASSR and suppression of low-frequency gamma oscillations. Notably, the area of suppression surrounded the center of the 40-Hz ASSR and showed a trend of extending to the vertex, indicating that different groups of neurons were responsible for these two gamma oscillations and that the 40-Hz oscillation circuit have specific inhibitory innervation to the low-gamma circuit.

Olfactory identification ability among schizophrenia patients, their first-degree relatives and healthy subjects.

OBJECTIVE: Olfactory impairments, including identification, have been reported in patients with schizophrenia, while few studies have examined the olfactory function of unaffected first-degree relatives of patients with schizophrenia, and the sample sizes of first-degree relatives were relatively small. Here, we investigated olfactory identification ability among patients with schizophrenia, first-degree relatives and healthy controls (HCs) using relatively large sample sizes at a single institute. METHODS: To assess olfactory identification ability, the open essence odorant identification test was administered to 172 schizophrenia patients, 75 first-degree relatives and 158 healthy controls. Differences in olfactory identification and correlations between olfactory ability and clinical variables were examined among these participants. RESULTS: We found a significant difference in olfactory identification ability among the diagnostic groups (p = 7.65 × 10-16). Schizophrenia patients displayed lower olfactory identification ability than first-degree relatives (Cohen's d = -0.57, p = 3.13 × 10-6) and healthy controls (d = -1.00, p = 2.19 × 10-16). Furthermore, first-degree relatives had lower olfactory identification ability than healthy controls (d = -0.29, p = 0.039). Olfactory identification ability moderately and negatively correlated with the duration of illness (r = -0.41, p = 1.88 × 10-8) and negative symptoms (r = -0.28, p = 1.99 × 10-4) in schizophrenia patients, although the correlation with the duration of illness was affected by aging (r = -0.24). CONCLUSIONS: Our results demonstrated that schizophrenia patients have impaired olfactory identification ability compared with first-degree relatives and healthy controls, and the impaired olfactory identification ability of first-degree relatives was intermediate between those in schizophrenia patients and healthy controls. Olfactory identification ability was relatively independent of clinical variables. Therefore, olfactory identification ability might be an intermediate phenotype for schizophrenia.

Differences in subcortical brain volumes among patients with schizophrenia and bipolar disorder and healthy controls.

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 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.

Gray matter volume differences between transgender men and cisgender women: A voxel-based morphometry study.

OBJECTIVE: Gender dysphoria (GD) is characterized by distress due to inconsistency between gender identity and biological sex. Individuals with GD often desire to be the other gender, which is called transgender. Although altered brain volumes in transgender people, particularly transgender women, have been reported, the particular brain regions have been inconsistent among studies. This study aimed to investigate neuroanatomical differences in transgender men without physical interventions. METHOD: T1-weighted magnetic resonance images (MRIs) were acquired in 21 transgender men and 21 cisgender women matched for biological sex and age. Whole-brain comparisons using voxel-based morphometry (VBM) were performed to identify gray matter volume (GMV) differences between transgender men and cisgender women. RESULTS: Transgender men showed greater GMV in the right posterior cingulate gyrus (PFWE-corr = 3.06×10-6) and the left occipital pole (PFWE-corr = 0.017) and lower GMV in the left middle temporal gyrus (PFWE-corr = 0.017) than cisgender women. Even after including serum sex hormone levels as covariates, the posterior cingulate gyrus was still significant (PFWE-corr < 0.05). In contrast, the occipital pole and the middle temporal gyrus were not significant after controlling for the sex hormone levels (PFWE-corr > 0.05), especially affected by testosterone but not estradiol. CONCLUSION: These findings suggest that transgender men have altered brain structure. We suggest that larger posterior midline structures may contribute to sensitivity to self-referential processing through altered visual perception in transgender people.

Polygenic Risk Scores Differentiating Schizophrenia From Bipolar Disorder Are Associated With Premorbid Intelligence in Schizophrenia Patients and Healthy Subjects.

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 (ß = -0.17, P = 4.12 × 10-3). The correlation was still significant after adjusting for diagnostic status (ß = -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.

Intelligence decline across major depressive disorder, bipolar disorder, and schizophrenia.

BACKGROUND: Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with impaired intelligence that predicts poor functional outcomes. However, little is known regarding the extent and severity of intelligence decline, that is, decreased present intelligence quotient (IQ) relative to premorbid levels, across psychiatric disorders and which clinical characteristics affect the decline. METHODS: Premorbid IQ, present IQ, and intelligence decline were compared across patients with MDD (n = 45), BD (n = 30), and SCZ (n = 139), and healthy controls (HCs; n = 135). Furthermore, we investigated which factors contribute to the intelligence decline in each diagnostic group. RESULTS: Significant differences were observed in premorbid IQ, present IQ, and intelligence decline across the diagnostic groups. Patients with each psychiatric disorder displayed lower premorbid and present IQ and more intelligence decline than HCs. Patients with SCZ displayed lower premorbid and present IQ and more intelligence decline than patients with MDD and BD, while there were no significant differences between patients with MDD and BD. When patients with BD were divided based on bipolar I disorder (BD-I) and bipolar II disorder (BD-II), degrees of intelligence decline were similar between MDD and BD-II and between BD-I and SCZ. Lower educational attainment was correlated with a greater degree of intelligence decline in patients with SCZ and BD but not MDD. CONCLUSIONS: These findings confirm that although all psychiatric disorders display intelligence decline, the severity of intelligence decline differs across psychiatric disorders (SCZ, BD-I > BD-II, MDD > HCs). Higher educational attainment as cognitive reserve contributes to protection against intelligence decline in BD and SCZ.

Assessment of haptic memory using somatosensory change-related cortical responses.

Haptic memory briefly retains somatosensory information for later use; however, how and which cortical areas are affected by haptic memory remain unclear. We used change-related cortical responses to investigate the relationship between the somatosensory cortex and haptic memory objectively. Electrical pulses, at 50 Hz with a duration of 500 ms, were randomly applied to the second, third, and fourth fingers of the right and left hands at an even probability every 800 ms. Each stimulus was labeled as D (preceded by a different side) or S (preceded by the same side). The D stimuli were further classified into 1D, 2D, and 3D, according to the number of different preceding stimuli. The S stimuli were similarly divided into 1S and 2S. The somatosensory-evoked magnetic fields obtained were divided into four components via a dipole analysis, and each component's amplitudes were measured using the source strength waveform. The results showed that the preceding event did not affect the amplitude of the earliest 20-30 ms response in the primary somatosensory cortex. However, in the subsequent three components, the cortical activity amplitude was largest in 3D, followed by 2D, 1D, and S. These results indicate that such modulatory effects occurred somewhere in the somatosensory processing pathway higher than Brodmann's area 3b. To the best of our knowledge, this is the first study to demonstrate the existence of haptic memory for somatosensory laterality and its impact on the somatosensory cortex using change-related cortical responses without contamination from peripheral effects.

Differences in executive function among patients with schizophrenia, their unaffected first-degree relatives and healthy participants.

BACKGROUND: Patients with schizophrenia (SCZ) display impaired executive functions compared with healthy controls (HCs). Furthermore, unaffected first-degree relatives (FRs) of patients with SCZ independently perform worse executive functions than do HCs. However, few studies have investigated the differences in executive functions assessed among patients with SCZ, FRs, and HCs, and the findings are inconsistent. METHODS: We investigated diagnostic differences in executive functions, namely, (i) numbers of categories achieved (CA), (ii) total errors (TE) and (iii) %perseverative errors of Nelson types (%PEN), using the Wisconsin card sorting test (WCST) among patients with SCZ (n=116), unaffected FRs (n=62) and HCs (n=146) at a single institute. Correlations between these executive functions and clinical variables were investigated. RESULTS: Significant differences existed in all executive functions among diagnostic groups (CA, F2,319=15.5, p=3.71×10-7; TE, F2,319=16.2, p=2.06×10-7; and %PEN, F2,319=21.3, p=2.15×10-9). Patients with SCZ had fewer CA and more TE and %PEN than those of HCs (CA, Cohen's d=-0.70, p=5.49×10-8; TE, d=0.70, p=5.62×10-8; and %PEN, d=0.82, p=2.85×10-10) and FRs (TE, d=0.46, p=3.73×10-3 and %PEN, d=0.38, p=0.017). Of the three executive functions, CA and %PEN of FRs were intermediately impaired between patients with SCZ and HCs (CA, d=-0.41, p=0.011 and %PEN, d=0.41, p=0.012). In contrast, no significant difference in TE existed between FRs and HCs (d=0.22, p=0.18). Although CA and TE were affected by the duration of illness (p<0.017), %PEN was not affected by any clinical variable in patients with SCZ (p>0.017). CONCLUSIONS: Executive function, particularly %PEN, could be a useful intermediate phenotype for understanding the genetic mechanisms implicated in SCZ pathophysiology.

Polygenetic Risk Scores for Major Psychiatric Disorders Among Schizophrenia Patients, Their First-Degree Relatives, and Healthy Participants.

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.

Genetic correlations between subcortical brain volumes and psychiatric disorders.

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.

Identifying and supporting students at risk of failing the National Medical Licensure Examination in Japan using a predictive pass rate.

BACKGROUND: Students who fail to pass the National Medical Licensure Examination (NMLE) pose a huge problem from the educational standpoint of healthcare professionals. In the present study, we developed a formula of predictive pass rate (PPR)" which reliably predicts medical students who will fail the NMLE in Japan, and provides an adequate academic support for them. METHODS: Six consecutive cohorts of 531 medical students between 2012 and 2017, Gifu University Graduate School of Medicine, were investigated. Using 7 variables before the admission to medical school and 10 variables after admission, we developed a prediction formula to obtain the PPR for the NMLE using logistic regression analysis. In a new cohort of 106 medical students in 2018, we applied the formula for PPR to them to confirm the capability of the PPR and predicted students who will have a strong likelihood of failing the NMLE. RESULTS: Medical students who passed the NMLE had the following characteristics: younger age at admission, graduates of high schools located in the surrounding area, high scores in the graduation examination and in the comprehensive computer-based test provided by the Common Achievement Test Organization in Japan. However, total score of examination in pre-clinical medical sciences and Pre-CC OSCE score in the 4th year were not correlated with the PPR. Ninety-one out of 531 students had a strong likelihood of failing the NMLE between 2012 and 2017 and 33 of these 91 students failed NMLE. Using the PPR, we predicted 12 out of 106 students will have a strong likelihood of failing the NMLE. Actually, five of these 12 students failed NMLE. CONCLUSIONS: The PPR can be used to predict medical students who have a higher probability of failing the NMLE. This prediction would enable focused support and guidance by faculty members. Prospective and longitudinal studies for larger and different cohorts would be necessary.

Prevalence of mental illness, intellectual disability, and developmental disability among homeless people in Nagoya, Japan: A case series study.

AIM: While it has been reported that the prevalence of mental illness is higher in homeless people than in the national population, few studies have investigated the prevalence of intellectual and developmental disability among the homeless. In this study, we conducted a survey to comprehensively assess these mental problems among homeless people in Nagoya, Japan. METHODS: The subjects were 18 homeless men. Mental illness was diagnosed with semi-structured interviews conducted by psychiatrists. We used the Wechsler Adult Intelligence Scale III to diagnose intellectual disability. Discrepancies between Wechsler Adult Intelligence Scale III subtest scores were used as criteria for developmental disability. RESULTS: Eleven of the 18 participants were diagnosed with mental illness: six with mood disorder, two with psychotic disorder, and six with alcohol problems. The mean IQ of all subjects was 83.4 ± 27.4. The 95% confidence interval (CI) was 96.2-69.1. Seven participants were found to have intellectual disability. Three men showed discrepancies of more than 10 between subtest scores, and all of them were diagnosed with a mental illness. We divided the participants into four groups: those with mental illness only; those with intellectual disability only; those with both problems; and those without diagnosis. The men with intellectual disability only were significantly younger and had been homeless since a younger age than the other groups. Participants diagnosed with a mental illness had been homeless for longer than those without mental health problems. CONCLUSION: Although the sample size was limited, this study revealed the high prevalence of mental illness and intellectual disability, 61% (95%CI, 35-83%) and 39% (95%CI, 17-64%), respectively, in homeless people in Nagoya, Japan.

[Impact of DSM-5: Application and Problems Based on Clinical and Research Viewpoints on Anxiety Disorders].

In Japan, the impact of DSM-5 has been greater than we had imagined. The Japanese Society of Psychiatry and Neurology organized a group for translation and the members spent many hours in this volunteer effort over a 2-year period. This highlights the significance of and expectations for DSM-5 in clinical practice in Japan. Regarding anxiety disorders, the highlights of changes from DSM-IV-TR to DSM-5 are as follows. Firstly, the DSM-5 chapter on anxiety disorder no longer includes obsessive-compulsive disorder (which is included with obsessive-compulsive and related disorders) or posttraumatic stress disorder and acute stress disorder(which are included with trauma- and stressor-related disorders). However, the sequential order of these chapters in DSM-5 reflects the close relationships among them. Secondly, in DSM-IV, selective mutism and separation anxiety disorder were classified in the section "Disorders Usually First Diagnosed in Infancy, Childhood, or Adolescence." They are now classified as an anxiety disorder. Through these two changes, at the beginning of the chapter, it can be clearly noted that anxiety disorders include disorders that share features of excessive fear and anxiety and related behavioral disturbances. Thirdly, panic disorder and agoraphobia are not associated in DSM-5. Thus, the former DSM-IV diagnoses of panic disorder with agoraphobia, panic disorder without agoraphobia, and agoraphobia without a history of panic disorder are now replaced by two diagnoses, panic disorder and agoraphobia, each with separate criteria. The co-occurrence of panic disorder and agoraphobia is now coded with two diagnoses. This change recognizes that a marked number of individuals with agoraphobia do not experience panic symptoms. For the present, this change ends the. controversy over the hierarchy between panic disorder and agoraphobia. The diagnostic criteria for agoraphobia are derived from the DSM-IV descriptors for agoraphobia, although the clarification of fears from two or more agoraphobia-related situations is now required, because this is a robust means for distinguishing agoraphobia from specific phobias. Also, the criteria for agoraphobia are now extended to be consistent with criteria sets for other anxiety disorders (e.g., a clinician's judgment of the fears as being out of proportion to the actual danger in the situation, with a typical duration of 6 months or more). From the above, these changes from DSM-IV-TR to DSM-5 in anxiety disorders make our judgments faster and more efficient in clinical practice, and DSM-5 is more useful to elucidate the pathology. In this manuscript, we discuss the application and problems based on clinical and research viewpoints regarding anxiety disorders in DSM-5.