The effect of education regarding treatment guidelines for schizophrenia and major depressive disorders on psychiatrists' hypnotic medication prescribing behavior: a multicenter study.

BACKGROUND: To examine whether the "Effectiveness of Guideline for Dissemination and Education in psychiatric treatment (EGIUDE)" project affects the rate of prescriptions of hypnotic medication and the type of hypnotic medications prescribed among psychiatrists, for schizophrenia and major depressive disorder in Japan. METHODS: The EGUIDE project is a nationwide prospective study of evidence-based clinical guidelines for schizophrenia and major depressive disorder in Japan. From 2016 to 2021, clinical and prescribing data from patients discharged from hospitals participating in the EGUIDE project were used to examine hypnotic medication prescriptions The prescribing rate of hypnotics and the prescribing rate of each type of hypnotic (benzodiazepine receptor agonist, nonbenzodiazepine receptor agonist, melatonin receptor agonist, and orexin receptor antagonist) were compared among patients who had been prescribed medication by psychiatrists participating in the EGUIDE project and patients who had been prescribed medication by nonparticipating psychiatrists. Multivariate logistic regression analysis was performed to examine the effect of the EGUIDE project on the prescription of hypnotic medications. RESULTS: A total of 12,161 patients with schizophrenia and 6,167 patients with major depressive disorder were included. Psychiatrists participating in the EGUIDE project significantly reduced the rate of prescribing hypnotic medication and benzodiazepine receptor agonists for both schizophrenia (P < 0.001) and major depressive disorder (P < 0.001) patients. CONCLUSION: This is the first study to investigate the educational effects of guidelines for the treatment of psychiatric disorders on psychiatrists in terms of prescribing hypnotic medications to patients. The EGUIDE project may play an important role in reducing hypnotic medication prescription rates, particularly with respect to benzodiazepine receptor agonists. The results suggest that the EGUIDE project may result in improved therapeutic behavior.

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.

Associations of polygenic risk scores differentiating attention-deficit hyperactivity disorder from autism spectrum disorder with cognitive and cortical alterations in Schizophrenia patients.

Schizophrenia (SCZ) is a clinically and genetically heterogeneous disorder that shares genetic factors with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). A genome-wide association study (GWAS) differentiating ADHD from ASD was performed recently. In this study, we investigated whether polygenic risk scores (PRSs) differentiating ASD from ADHD are associated with cognitive impairments and alterations in cortical structures in SCZ patients. Based on the GWAS data (9,315 ASD and 11,964 ADHD patients), PRSs differentiating ADHD from ASD (indicating a greater risk of ADHD and a lower risk of ASD) were calculated for SCZ patients (n = 168). Cognitive performance, including verbal comprehension (VC), perceptual organization (PO), working memory (WM), and processing speed (PS), was assessed using the WAIS-III (n = 145). The surface areas and cortical thicknesses of 34 bilateral brain regions were extracted using FreeSurfer (n = 126). We examined the associations of these PRSs with cognitive performance and cortical structures in SCZ patients. Among the four cognitive domains, a higher PRS, indicating a greater risk of ADHD, was associated with impaired WM in SCZ patients (beta=-0.21, p = 0.012). A lower PRS, indicating a greater risk of ASD, was associated with decreased surface areas of the left medial orbitofrontal (beta = 0.21, p = 8.29 × 10- 4), left entorhinal (beta = 0.21, p = 0.025), left postcentral (beta = 0.18, p = 7.52 × 10- 3), right fusiform (beta = 0.17, p = 6.64 × 10- 3), and left fusiform cortices (beta = 0.17, p = 7.77 × 10- 3) in SCZ patients. A higher PRS, indicating a greater risk of ADHD, was associated with decreased cortical thickness in the bilateral transverse temporal regions (left, beta=-0.17, p = 0.039; right, beta=-0.17, p = 0.045). Our study revealed a relationship between genetic factors that differentiate ADHD patients from ASD patients and both cortical structure and cognitive performance in SCZ patients. These findings suggest that the heterogeneity of SCZ might be partly derived from genetic factors related to neurodevelopmental and psychiatric disorders other than SCZ.

The influence of novelty detection on the 40-Hz auditory steady-state response in schizophrenia: A novel hypothesis from meta-analysis.

The 40-Hz auditory steady-state response (ASSR) is influenced not only by parameters such as attention, stimulus type, and analysis level but also by stimulus duration and inter-stimulus interval (ISI). In this meta-analysis, we examined these parameters in 33 studies that investigated 40-Hz ASSRs in patients with schizophrenia. The average Hedges' g random effect sizes were - 0.47 and - 0.43 for spectral power and phase-locking, respectively. We also found differences in ASSR measures based on stimulus duration and ISI. In particular, ISI was shown to significantly influence differences in the 40-Hz ASSR between healthy controls and patients with schizophrenia. We proposed a novel hypothesis focusing on the role of novelty detection, dependent on stimulus duration and ISI, as a critical factor in determining these differences. Specifically, longer stimulus durations and shorter ISIs under random presentation, or shorter stimulus durations and longer ISIs under repetitive presentation, decrease the 40-Hz ASSR in healthy controls. Patients with schizophrenia show minimal changes in response to stimulus duration and ISI, thus reducing the difference between controls and patients. This hypothesis can consistently explain most of the studies that have failed to show a reduction in 40-Hz ASSR in patients with schizophrenia. Increased novelty-related activity, reflected as an increase in auditory evoked potential components at stimulus onset, such as the N1, could suppress the 40-Hz ASSR, potentially reducing the peak measures of spectral power and phase-locking. To establish the 40-Hz ASSR as a truly valuable biomarker for schizophrenia, further systematic research using paradigms with various stimulus durations and ISIs is needed.

Epigenetic signatures of social anxiety, panic disorders and stress experiences: Insights from genome-wide DNA methylation risk scores.

Social anxiety disorder (SAD) and panic disorder (PD) are prevalent anxiety disorders characterized by a complex interplay of genetic and environmental factors. Both disorders share overlapping features and often coexist, despite displaying distinct characteristics. Childhood life adversity, overall stressful life events, and genetic factors contribute to the development of these disorders. DNA methylation, an epigenetic modification, has been implicated in the pathogenesis of these diseases. In this study, we investigated whether whole-genome DNA methylation risk scores (MRSs) for SAD risk, severity of social anxiety, childhood life adversity, PD risk, and overall stressful life events were associated with SAD or PD case‒control status. Preliminary epigenome-wide association studies (EWASs) for SAD risk, severity of social anxiety, and childhood life adversity were conducted in 66 SAD individuals and 77 healthy controls (HCs). Similarly, EWASs for PD risk and overall stressful life events were performed in 182 PD individuals and 81 HCs. MRSs were calculated from these EWASs. MRSs derived from the EWASs of SAD risk and severity of social anxiety were greater in PD patients than in HCs. Additionally, MRSs derived from the EWASs of overall stressful life events, particularly in PD individuals, were lower in SAD individuals than in HCs. In contrast, MRSs for childhood life adversity or PD risk were not significantly associated with PD or SAD case‒control status. These findings highlight the epigenetic features shared in both disorders and the distinctive epigenetic features related to social avoidance in SAD patients, helping to elucidate the epigenetic basis of these disorders.

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.

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.

Tablet-Based Cognitive and Eye Movement Measures as Accessible Tools for Schizophrenia Assessment: Multisite Usability Study.

BACKGROUND: Schizophrenia is a complex mental disorder characterized by significant cognitive and neurobiological alterations. Impairments in cognitive function and eye movement have been known to be promising biomarkers for schizophrenia. However, cognitive assessment methods require specialized expertise. To date, data on simplified measurement tools for assessing both cognitive function and eye movement in patients with schizophrenia are lacking. OBJECTIVE: This study aims to assess the efficacy of a novel tablet-based platform combining cognitive and eye movement measures for classifying schizophrenia. METHODS: Forty-four patients with schizophrenia, 67 healthy controls, and 41 patients with other psychiatric diagnoses participated in this study from 10 sites across Japan. A free-viewing eye movement task and 2 cognitive assessment tools (Codebreaker task from the THINC-integrated tool and the CognitiveFunctionTest app) were used for conducting assessments in a 12.9-inch iPad Pro. We performed comparative group and logistic regression analyses for evaluating the diagnostic efficacy of the 3 measures of interest. RESULTS: Cognitive and eye movement measures differed significantly between patients with schizophrenia and healthy controls (all 3 measures; P<.001). The Codebreaker task showed the highest classification effectiveness in distinguishing schizophrenia with an area under the receiver operating characteristic curve of 0.90. Combining cognitive and eye movement measures further improved accuracy with a maximum area under the receiver operating characteristic curve of 0.94. Cognitive measures were more effective in differentiating patients with schizophrenia from healthy controls, whereas eye movement measures better differentiated schizophrenia from other psychiatric conditions. CONCLUSIONS: This multisite study demonstrates the feasibility and effectiveness of a tablet-based app for assessing cognitive functioning and eye movements in patients with schizophrenia. Our results suggest the potential of tablet-based assessments of cognitive function and eye movement as simple and accessible evaluation tools, which may be useful for future clinical implementation.