Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas schizophrenia (SCZ) risk associated with DNMs has thus far been shown to be modest. ...We analyzed DNMs from 1,695 SCZ-affected trios and 1,077 published SCZ-affected trios to better understand the contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remained modest. Gene set analyses revealed that SCZ DNMs were significantly concentrated in genes that were highly expressed in the brain, that were under strong evolutionary constraint and/or overlapped with genes identified in other neurodevelopmental disorders. No single gene surpassed exome-wide significance; however, 16 genes were recurrently hit by protein-truncating DNMs, corresponding to a 3.15-fold higher rate than the mutation model expectation (permuted 95% confidence interval: 1-10 genes; permuted P = 3 × 10
). Overall, DNMs explain a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confers risk for SCZ in the population.
People with schizophrenia are enriched for rare coding variants in genes associated with neurodevelopmental disorders, particularly autism spectrum disorders and intellectual disability. However, it ...is unclear if the same changes to gene function that increase risk to neurodevelopmental disorders also do so for schizophrenia. Using data from 3444 schizophrenia trios and 37,488 neurodevelopmental disorder trios, we show that within shared risk genes, de novo variants in schizophrenia and neurodevelopmental disorders are generally of the same functional category, and that specific de novo variants observed in neurodevelopmental disorders are enriched in schizophrenia (P = 5.0 × 10
). The latter includes variants known to be pathogenic for syndromic disorders, suggesting that schizophrenia be included as a characteristic of those syndromes. Our findings imply that, in part, neurodevelopmental disorders and schizophrenia have shared molecular aetiology, and therefore likely overlapping pathophysiology, and support the hypothesis that at least some forms of schizophrenia lie on a continuum of neurodevelopmental disorders.
Patients with remitted psychosis face a dilemma between the wish to discontinue antipsychotics and the risk of relapse. We test if an operationalized guided-dose-reduction algorithm can help reach a ...lower effective dose without increased risks of relapse.
A 2-year open-label randomized prospective comparative cohort trial from Aug 2017 to Sep 2022. Patients with a history of schizophrenia-related psychotic disorders under stable medications and symptoms were eligible, randomized 2:1 into guided dose reduction group (GDR)
maintenance treatment group (MT1), together with a group of naturalistic maintenance controls (MT2). We observed if the relapse rates would be different between 3 groups, to what extent the dose could be reduced, and if GDR patients could have improved functioning and quality of life.
A total of 96 patients, comprised 51, 24, and 21 patients in GDR, MT1, and MT2 groups, respectively. During follow-up, 14 patients (14.6%) relapsed, including 6, 4, and 4 from GDR, MT1, and MT2, statistically no difference between groups. In total, 74.5% of GDR patients could stay well under a lower dose, including 18 patients (35.3%) conducting 4 consecutive dose-tapering and staying well after reducing 58.5% of their baseline dose. The GDR group exhibited improved clinical outcomes and endorsed better quality of life.
GDR is a feasible approach as the majority of patients had a chance to taper antipsychotics to certain extents. Still, 25.5% of GDR patients could not successfully decrease any dose, including 11.8% experienced relapse, a risk comparable to their maintenance counterparts.
Brain age prediction models using diffusion magnetic resonance imaging (dMRI) and machine learning techniques enable individual assessment of brain aging status in healthy people and patients with ...brain disorders. However, dMRI data are notorious for high intersite variability, prohibiting direct application of a model to the datasets obtained from other sites. In this study, we generalized the dMRI-based brain age model to different dMRI datasets acquired under different imaging conditions. Specifically, we adopted a transfer learning approach to achieve domain adaptation. To evaluate the performance of transferred models, brain age prediction models were constructed using a large dMRI dataset as the source domain, and the models were transferred to three target domains with distinct acquisition scenarios. The experiments were performed to investigate (1) the tuning data size needed to achieve satisfactory performance for brain age prediction, (2) the feature types suitable for different dMRI acquisition scenarios, and (3) performance of the transfer learning approach compared with the statistical covariate approach. By tuning the models with relatively small data size and certain feature types, optimal transferred models were obtained with significantly improved prediction performance in all three target cohorts (p < 0.001). The mean absolute error of the predicted age was reduced from 13.89 to 4.78 years in Cohort 1, 8.34 to 5.35 years in Cohort 2, and 8.74 to 5.64 years in Cohort 3. The test–retest reliability of the transferred model was verified using dMRI data acquired at two timepoints (intraclass correlation coefficient = 0.950). Clinical sensitivity of the brain age prediction model was investigated by estimating the brain age in patients with schizophrenia. The prediction made by the transferred model was not significantly different from that made by the reference model. Both models predicted significant brain aging in patients with schizophrenia as compared with healthy controls (p < 0.001); the predicted age difference of the transferred model was 4.63 and 0.26 years for patients and controls, respectively, and that of the reference model was 4.39 and −0.09 years, respectively. In conclusion, transfer learning approach is an efficient way to generalize the dMRI-based brain age prediction model. Appropriate transfer learning approach and suitable tuning data size should be chosen according to different dMRI acquisition scenarios.
Disrupted‐in‐Schizophrenia 1 (DISC1) is a susceptibility gene for several psychiatric illnesses. To study the pathogenesis of these disorders, we generated Disc1 mutant mice by introducing the ...129S6/SvEv 25‐bp deletion Disc1 variants into the C57BL/6J strain. In this study, we used heterozygous Disc1 mutant (Het) mice to evaluate the DISC1 haploinsufficiency model of schizophrenia. No changes in locomotor behaviors were observed in Het mice; however, after amphetamine injection, greater locomotor activity was observed in Het mice compared with wild‐type (WT) mice. Moreover, amphetamine‐induced elevations of c‐Fos expression and dopamine level in the striatum were greater in Het mice than in WT controls, suggesting an altered dopaminergic regulation in the striatum of Het mice. Compared with those in WTs, the striatal protein levels of dopamine transporter and D2 dopamine receptor were increased in Het mice, while D1 dopamine receptor level was decreased. DISC1 interacting proteins, GSK3α and GSK3β, were downregulated in Het mice, whereas the levels of PDE4B and CREB were not altered. Morphologically, the complexities of striatal median spiny neurons (MSNs), parvalbumin‐positive interneurons and Iba1‐positive microglia were all decreased in Het mice. The density and head diameter of dendritic spines in the MSNs of Het mice were also reduced. Our results indicate that mice lacking one WT Disc1 allele are more sensitive to psychostimulant amphetamine challenge, which might be attributed to the altered structure and function of the striatal dopaminergic system. Here, we demonstrated striatal phenotypes in heterozygous Disc1 mutant mice, which could be a promising model of DISC1 haploinsufficiency.
In the striatum of Het Disc1 mutant mice, the protein levels of DAT and D2R are increased while D1R and GSK3 α/β are decreased, the complexities of MSNs, PVNs and microglia as well as the densities of MSN spine and PVN are reduced.
「Abstract」Prevalence and Determinants of Workplace Violence of Health Care Workers in a Psychiatric Hospital in Taiwan:Wen-Ching CHEN, et al. Yu-Li Hospital, Department of Health, Executive Yuan, ...Taiwan―Workplace violence, a possible cause of job stress, has recently become an important concern in occupational health. This study determined the prevalence of workplace violence and its risk factors for employees at a psychiatric hospital in Taiwan. A questionnaire developed by ILO/ICN/WHO/PSI was first translated and validated. It was then used to survey the prevalence of workplace violence in the last 12 months experienced by all nursing aides, nurses, and clerks at the hospital. Multiple logistic regression models were constructed to discover the determinants of violence. A total of 222 out of 231 surveyed workers completed a valid questionnaire. The one-year prevalence rates of physical violence (PV), verbal abuse, bullying/mobbing, sexual harassment, and racial harassment were 35.1, 50.9, 15.8, 9.5, and 4.5%, respectively. The prevalence of PV at this hospital was higher than that reported by other countries for the health sector. A high anxiety level was associated with the occurrence of PV. These results need to be corroborated by future investigation. A training program may be required for high risk groups to reduce workplace violence.
Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which ...regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sensory gating describes neurological processes of filtering out redundant or unnecessary stimuli during information processing, and sensory gating deficits may contribute to the symptoms of ...schizophrenia. Among the three components of auditory event-related potentials reflecting sensory gating, P50 implies pre-attentional filtering of sensory information and N100/P200 reflects attention triggering and allocation processes. Although diminished P50 gating has been extensively documented in patients with schizophrenia, previous studies on N100 were inconclusive, and P200 has been rarely examined. This study aimed to investigate whether patients with schizophrenia have P50, N100, and P200 gating deficits compared with control subjects.
Control subjects and clinically stable schizophrenia patients were recruited. The mid-latency auditory evoked responses, comprising P50, N100, and P200, were measured using the auditory-paired click paradigm without manipulation of attention. Sensory gating parameters included S1 amplitude, S2 amplitude, amplitude difference (S1-S2), and gating ratio (S2/S1). We also evaluated schizophrenia patients with PANSS to be correlated with sensory gating indices.
One hundred four patients and 102 control subjects were examined. Compared to the control group, schizophrenia patients had significant sensory gating deficits in P50, N100, and P200, reflected by larger gating ratios and smaller amplitude differences. Further analysis revealed that the S2 amplitude of P50 was larger, while the S1 amplitude of N100/P200 was smaller, in schizophrenia patients than in the controls. We found no correlations between sensory gating indices and schizophrenia positive or negative symptom clusters. However, we found a negative correlation between the P200 S2 amplitude and Bell's emotional discomfort factor/Wallwork's depressed factor.
Till date, this study has the largest sample size to analyze P50, N100, and P200 collectively by adopting the passive auditory paired-click paradigm without distractors. With covariates controlled for possible confounds, such as age, education, smoking amount and retained pairs, we found that schizophrenia patients had significant sensory gating deficits in P50-N100-P200. The schizophrenia patients had demonstrated a unique pattern of sensory gating deficits, including repetition suppression deficits in P50 and stimulus registration deficits in N100/200. These results suggest that sensory gating is a pervasive cognitive abnormality in schizophrenia patients that is not limited to the pre-attentive phase of information processing. Since P200 exhibited a large effect size and did not require additional time during recruitment, future studies of P50-N100-P200 collectively are highly recommended.
Aims
Patients with psychosis intend to discontinue antipsychotic treatment for various reasons. As antipsychotic discontinuation involves a high risk of relapse, maintenance treatment is recommended ...by mainstream opinion even when remission is attained. To optimize the risk‐to‐benefit ratio of long‐term antipsychotic treatment, we proposed an operationalized guided dose‐reduction algorithm to serve as an intermediate approach as to achieve the lowest effective antipsychotic dose and better functioning for patients with remitted psychosis.
Methods
Outpatients with a history of schizophrenia‐related psychotic disorders currently under stable medications and symptoms are eligible to register in this protocol. Patients intending for dose reduction are randomized into 2:1, guided dose reduction group (GDR) versus maintenance treatment group (MTG1). Eligible patients who do not intend to reduce antipsychotics serve as naturalistic maintenance controls (MTG2). The GDR patients reduce no more than 25% of their baseline antipsychotic dose, with at least a 6‐month stabilization period before reducing another 25% of their last dose. The timing of the next dose reduction will be determined by shared decision‐making with the patient. Following a dose reduction, the patients will receive three consecutive monthly monitoring; otherwise, they receive treatment as usual.
Discussion
By employing this pragmatic‐based protocol, patients are empowered to evaluate their readiness for next dose reduction attempt. We would like to test in real‐world situations if stable patients can reduce antipsychotics not at the expense of an increased risk of relapse, so as to optimize the balance between risk‐to‐benefit ratios of long‐term antipsychotic treatment.
PDF
