Tissue-specific gene expression of genome-wide significant loci associated with major depressive disorder subtypes.

Major depressive disorder (MDD) is a clinically and genetically heterogeneous disorder. To reduce heterogeneity, large-scale genome-wide association studies have recently identified genome-wide significant loci associated with seven MDD subtypes. However, it was unclear in which tissues the genes near those loci are specifically expressed. We investigated whether genes related to specific MDD subtypes would be preferably expressed in a specific tissue. At 14 novel subtype-specific loci related to seven MDD subtypes-(1) non-atypical-like features MDD, (2) early-onset MDD, (3) recurrent MDD, (4) MDD with suicidal thoughts, (5) MDD without suicidal thoughts, (6) MDD with moderate impairment, and (7) postpartum depression, we investigated whether 22 genome-wide significant genetic variant-mapped genes were tissue-specifically expressed in brain, female reproductive, male specific, cardiovascular, gastrointestinal, or urinary tissues in the Genotype-Tissue Expression (GTEx) subjects (n ≤ 948). To confirm the tissue-specific expression in the GTEx, we used independent Human Protein Atlas (HPA) RNA-seq subjects (n ≤ 95). Of 22 genes, nine and five genes were tissue-specifically expressed in brain and female reproductive tissues, respectively (p < 2.27 × 10-3). RTN1, ERBB4, and AMIGO1 related to early-onset MDD, recurrent MDD, or MDD with suicidal thoughts were highly expressed in brain tissues (d = 1.19-2.71), while OAS1, LRRC9, DHRS7, PSMA5, SYPL2, and GULP1 related to non-atypical-like features MDD, early-onset MDD, MDD with suicidal thoughts, or postpartum depression were expressed at low levels in brain tissues (d = -0.17--1.48). DFNA5, CTBP2, PCNX4, SDCCAG8, and GULP1, which are related to early-onset MDD, MDD with moderate impairment, or postpartum depression, were highly expressed in female reproductive tissues (d = 0.80-2.08). Brain and female reproductive tissue-specific expression was confirmed in the HPA RNA-seq subjects. Our findings suggest that brain and female reproductive tissue-specific expression might contribute to the pathogenesis of MDD subtypes.

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.

Genome-wide DNA methylation risk scores for schizophrenia derived from blood and brain tissues further explain the genetic risk in patients stratified by polygenic risk scores for schizophrenia and bipolar disorder.

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.

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.

Is adjustment disorder genetically correlated with depression, anxiety, or risk-tolerant personality trait?

Adjustment disorder has three main subtypes: adjustment disorder with depressed mood, adjustment disorder with anxiety, and adjustment disorder with disturbance of conduct. The disorder is moderately heritable and has lifetime comorbidities with major depressive disorder (MDD), anxiety disorders, or risk-tolerant personality. However, it remains unclear whether the degrees of genetic correlations between adjustment disorder and other psychiatric disorders and intermediate phenotypes are similar or different to those between MDD, anxiety disorders or risk-tolerant personality and these other psychiatric disorders and intermediate phenotypes. To compare patterns of genetic correlations, we utilized large-scale genome-wide association study summary statistics for adjustment disorder-related disorders and personality trait, eleven other psychiatric disorders and fifteen intermediate phenotypes. Adjustment disorder had highly positive genetic correlations with MDD, anxiety disorders, and risk-tolerant personality. Among other psychiatric disorders, adjustment disorder, MDD, anxiety disorders and risk-tolerant personality were positively correlated with risks for schizophrenia (SCZ), bipolar disorder (BD), SCZ + BD, attention-deficit/hyperactivity disorder, and cross disorders. In contrast, adjustment disorder was not significantly correlated with risks for obsessive-compulsive disorder, Tourette syndrome, or posttraumatic stress disorder despite significant genetic correlations of MDD or anxiety disorders with these disorders. Among intermediate phenotypes, adjustment disorder, MDD, anxiety disorders, and risk-tolerant personality commonly had a younger age at first sexual intercourse, first birth, and menopause, lower cognitive ability, and higher rate of smoking initiation. Adjustment disorder was not genetically correlated with extraversion, although the related disorder and personality were correlated with extraversion. Only adjustment disorder was correlated with a higher smoking quantity. These findings suggest that adjustment disorder could share a genetic etiology with MDD, anxiety disorders and risk-tolerant personality trait, as well as have a disorder-specific genetic etiology.

Mitochondrial genetic variants associated with bipolar disorder and Schizophrenia in a Japanese population.

BACKGROUND: Bipolar disorder (BD) and schizophrenia (SZ) are complex psychotic disorders (PSY), with both environmental and genetic factors including possible maternal inheritance playing a role. Some studies have investigated whether genetic variants in the mitochondrial chromosome are associated with BD and SZ. However, the genetic variants identified as being associated are not identical among studies, and the participants were limited to individuals of European ancestry. Here, we investigate associations of genome-wide genetic variants in the mitochondrial chromosome with BD, SZ, and PSY in a Japanese population. METHODS: After performing quality control for individuals and genetic variants, we investigated whether mitochondrial genetic variants [minor allele frequency (MAF) > 0.01, n = 45 variants) are associated with BD, SZ, and PSY in 420 Japanese individuals consisting of patients with BD (n = 51), patients with SZ (n = 172), and healthy controls (HCs, n = 197). RESULTS: Of mitochondrial genetic variants, three (rs200478835, rs200044200 and rs28359178 on or near NADH dehydrogenase) and one (rs200478835) were significantly associated with BD and PSY, respectively, even after correcting for multiple comparisons (PGC=0.045-4.9 × 10- 3). In particular, individuals with the minor G-allele of rs200044200, a missense variant, were only observed among patients with BD (MAF = 0.059) but not HCs (MAF = 0) (odds ratio=∞). Three patients commonly had neuropsychiatric family histories. CONCLUSIONS: We suggest that mitochondrial genetic variants in NADH dehydrogenase-related genes may contribute to the pathogenesis of BD and PSY in the Japanese population through dysfunction of energy production.

The 40-Hz auditory steady-state response enhanced by beta-band subharmonics.

The 40-Hz auditory steady-state response (ASSR) has received special attention as an index of gamma oscillations owing to its association with various neuropsychiatric disorders including schizophrenia. When a periodic stimulus is presented, oscillatory responses are often elicited not only at the stimulus frequency, but also at its harmonic frequencies. However, little is known about the effect of 40-Hz subharmonic stimuli on the activity of the 40-Hz ASSR. In the present magnetoencephalography study, we focused on the nature of oscillation harmonics and examined oscillations in a wide frequency range using a time-frequency analysis during the 6.67-, 8-, 10-, 13.3-, 20-, and 40-Hz auditory stimuli in 23 healthy subjects. The results suggested that the 40-Hz ASSR represents activation of a specific circuit tuned to this frequency. Particularly, oscillations elicited by 13.3- and 20-Hz stimuli exhibited significant enhancement at 40 Hz without changing those at the stimulus frequency. In addition, it was found that there was a non-linear response to stimulation in the beta band. We also demonstrated that the inhibition of beta to low-gamma oscillations by the 40-Hz circuit contributed to the violation of the rule that harmonic oscillations gradually decrease at higher frequencies. These findings can advance our understanding of oscillatory abnormalities in patients with schizophrenia in the future.

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.

Sex differences in brainstem structure volumes in patients with schizophrenia.

Patients with schizophrenia (SZ) display moderate reductions in brainstem volumes, including the midbrain, pons, superior cerebellar peduncle, and medulla oblongata. Here, we investigated alterations in brainstem volumes between SZ patients and healthy controls (HCs) stratified by sex. T1-weighted MRI brain scans were processed with FreeSurfer v6.0 in 156 SZ patients (61 males/95 females) and 205 HCs (133/72). Of the brainstem structures, pons volumes were significantly reduced, particularly in male SZ patients. The decreased pons volumes were correlated with lower levels of education but not duration of illness in male patients. These findings suggest that the reduction in pons volume in male patients might be occurred before or around the onset of the disorder.

Efficacy of sofpironium bromide gel on clozapine-induced hypersalivation in patients with treatment-resistant schizophrenia: double-blind, controlled crossover study.

BACKGROUND: Hypersalivation is a major side-effect of clozapine in patients with treatment-resistant schizophrenia. AIMS: We investigated the efficacy of topical anticholinergic formulation sofpironium bromide gel for improving hypersalivation in patients with treatment-resistant schizophrenia receiving clozapine. METHOD: A double-blind, controlled crossover study was conducted with sofpironium bromide gel and a placebo gel to treat clozapine-induced hypersalivation in 16 patients with treatment-resistant schizophrenia. Patients were randomly divided between groups A and B (each n = 8). Group A was treated with sofpironium bromide gel for 6 weeks, followed by a 2-week washout period and 6 weeks of placebo gel, after which they were observed for another 2 weeks. In contrast, group B was treated with placebo gel for 6 weeks, followed by a 2-week washout period, 6 weeks of sofpironium bromide gel and a 2-week observation period. One-minute saliva volume, objective salivation ratings (Drooling Severity and Frequency Scale and Nocturnal Hypersalivation Rating Scale) and subjective salivation ratings (Visual Analogue Scale) were assessed every 2 weeks. RESULTS: All patients completed the trials. Three patients reported mild, spontaneously resolved skin itching. Compared with baseline values, the 1-min saliva volumes of both groups were significantly decreased by approximately 30% at the second week of sofpironium bromide gel treatment (P < 0.001), and significantly decreased by >40% at the fourth and sixth weeks of treatment (P < 0.001). The effects were maintained for over 2 weeks even after the treatment was discontinued. CONCLUSIONS: We suggest that sofpironium bromide gel is effective in treating clozapine-induced hypersalivation in patients with treatment-resistant schizophrenia.

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.

Higher polygenic risk scores for anxiety disorders are associated with reduced area in the anterior cingulate gyrus.

Anxiety disorders are heterogeneous, show a moderate genetic contribution and are associated with inconsistent cortical structure alterations. Here, we investigated whether genetic factors for anxiety disorders contribute to cortical alterations by conducting polygenic risk score (PRS) analyses. We calculated PRSs for anxiety disorders at several P value thresholds (from PT ≤ 5.0 × 10-8 to PT ≤ 1.0) based on the latest large-scale genome-wide association study of anxiety disorders from the UK biobank (25,453 cases; 58,113 controls) in an independent sample of psychiatrically and physically healthy subjects (n = 174). Using regression after adjusting for confounding factors, we tested whether these PRSs were associated with the surface area and cortical thickness in 34 bilateral brain regions extracted using FreeSurfer. A higher PRS for anxiety disorders at PT ≤ 1.0 was significantly associated with a reduced right caudal anterior cingulate area (beta = -0.25, puncorrected = 9.51 × 10-4, pcorrected = 0.032). PRSs based on more common SNPs, especially from PT ≤ 0.01 to PT ≤ 1.0, were associated with the right caudal anterior cingulate area (a maximum at PT ≤ 0.5: R2 = 0.066, beta = -0.27, puncorr = 3.81 × 10-4, pcorr = 0.013). Furthermore, individuals in the highest quartile for anxiety disorder PRS had lower surface area and volume in the right anterior cingulate gyrus than those in the lowest quartile. We suggest a shared genetic etiology between anxiety disorders and structural features of the anterior cingulate gyrus, possibly contributing to the pathogenesis of anxiety disorders via emotional dysregulations. Our findings suggest the potential usefulness of PRS to reduce pathological heterogeneity among anxiety disorders.

Cross-Disorder Analysis of Genic and Regulatory Copy Number Variations in Bipolar Disorder, Schizophrenia, and Autism Spectrum Disorder.

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.

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.

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.

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.

Investigating genetic overlaps of the genetic factor differentiating schizophrenia from bipolar disorder with cognitive function and hippocampal volume.

Schizophrenia and bipolar disorder display clinical similarities and dissimilarities. We investigated whether the genetic factor differentiating schizophrenia from bipolar disorder is genetically associated with cognitive phenotypes and hippocampal volumes. We revealed genetic overlaps of the genetic differentiating factor with low general cognitive ability, low childhood IQ, low educational attainment and reduced hippocampal volumes. The genetic correlations with low general cognitive ability and reduced hippocampal volumes were associated with risk of schizophrenia, whereas the genetic correlations with high childhood IQ and educational attainment were associated with risks of bipolar disorder. These findings suggest these disorders have disorder-specific genetic factors related to clinical phenotypes.

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.