Asian journal of psychiatry最新文献

As of August 2024, (US) FDA has granted approval for a number of psychotropic drugs on market that might usher an innovative sparkle in psychopharmacotherapy. This is a recap to update busy clinicians.

Psychedelic drug therapy has gained prominence for its potential in treating various mental health conditions, including depression, post-traumatic stress disorder (PTSD), and anxiety. Psychedelic treatment differs from conventional psychiatric approaches in mode of action, legal status, and treatment approach. This work delves into the therapeutic potential, mechanisms, and regulatory approvals of key psychedelic substances like psilocybin, 3,4-Methyl enedioxy methamphetamine (MDMA), mescaline, ketamine, and Lysergic acid diethylamide (LSD). It also provides an overview of legal aspects, and regulations surrounding psychedelics in the US & Europe, emphasizing their Schedule I classification due to potential misuse. The United States Food & Drug Administration (USFDA) closely monitors psychedelics, employing expedited pathways for evaluation. Further, recent guidance from the FDA on considerations for clinical Investigations supports the safe development of psychedelics for human welfare. European Medicines Agency (EMA) regulators focus on atypical psychedelics, addressing challenges in safety and efficacy. Marketed products, such as Spravato nasal spray, face limited distribution due to safety concerns. The call for careful regulation and legislation is essential for harnessing psychedelics' potential for therapeutic benefits and human welfare.

Background

Background

Chronic ketamine use leads to cognitive impairments, however, the neural mechanisms underpinning these impairments are still unclear.

Aims

Many studies showed Anterior cingulate cortex (ACC)is strongly involved in cognition and drug addiction, as supported by our previous studies. The objective of this study was to assess the variations in resting-state functional connectivity (FC) changes in the right anterior cingulate cortex (ACC) of chronic ketamine users (CKUs) and their relationship with cognitive performance.

Methods

The study enrolled 28 chronic ketamine users (CKUs) and 30 healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) data were gathered from both groups. Cognitive functions were evaluated using the MATRICS Consensus Cognitive Battery (MCCB).

Results

CKUs demonstrated significantly poorer cognitive performance than HCs in various cognitive domains, including Visual Learning, Speed of Processing, Working Memory, and the composite score of MCCB. Group-level comparisons revealed that CKUs exhibited enhanced functional connectivity between the right ACC and the right postcentral gyrus (PCG) compared to HCs. There was a positive relationship between the connectivity of right ACC-PCG and reasoning and problem-solving score, but there was no significant association with the characteristics of ketamine use.

Conclusion

CKUs showed enhanced connectivity between the right ACC and the right PCG. This enhanced functional connectivity may indicate functional compensation for cognitive deficits in CKUs, especially for reasoning and problem-solving impairments in CKUs.

Objectives

Second-generation antipsychotics (SGAs) are often prescribed for patients with schizophrenia; however, SGAs are associated with the risk of metabolic syndrome (MetS). This study aimed to investigate the clinical and biochemical determinants of SGA-related MetS.

Methods

Patients with schizophrenia, aged between 20 and 65 years, and under clozapine or olanzapine treatment for at least 9 months, were recruited from a mental hospital. Demographic, comorbidity, clinical status, laboratory, and drug regimen data were collected through chart review. Circulating levels of adiponectin, thyroid hormone responsive protein, and fatty acid binding protein 4 (FABP4) were assayed. Multiple logistic regression was used to identify risk predictors of MetS.

Results

A total of 176 participants were enrolled, including 138 (78.4 %) clozapine users and 38 (21.6 %) olanzapine users. Forty-five (25.6 %) patients were classified as having MetS. The duration of clozapine or olanzapine usage was significantly shorter in those with MetS (p=0.026) than those without MetS. Patients with MetS had a significantly higher serum FABP4 concentration than their counterparts (22.5 ± 8.8 ng/mL vs. 15.7 ± 6.7 ng/mL, p<0.001), and also a significantly lower adiponectin level (6.9 ±4.0 mg/mL vs. 11.6 ± 6.6 mg/mL, p<0.001). A FABP4 level ≥ 16.98 ng/mL (OR: 24.16, 95 % CI: 7.47–78.09, p<0.001) was positively correlated with MetS, whereas serum adiponectin level was inversely correlated with MetS (OR: 0.7980, 95 % CI: 0.70–0.90, p<0.001).

Conclusions

Adiponectin, FABP4, and certain clinical covariates and comedications were highly correlated with SGA-related MetS. Further studies are required to investigate the underlying mechanisms.

Aim

This retrospective study aimed to evaluate the long-term effectiveness of switching to clozapine in the management of tardive syndromes (TS).

Methodology

The treatment records of patients who had TS at the time of starting clozapine, were reviewed and demographic and clinical data was extracted on a predesigned performa.

Results

About three-fourth (74.2 %) of the study subjects had tardive dystonias and two-third (69.7 %) had tardive dyskinesia at the time of starting clozapine. About half (48.5 %) of the patients had both tardive dystonia and dyskinesia. A small proportion (13.6 %) also had tardive akathisia at the time of starting clozapine. About three-fourth (72.2 %) of the patients had >50 % reduction, and about two-third (66.6 %) of the patients had >75 % reduction and nearly half (54.5 %) of the patients had complete resolution of dyskinesia at the last follow-up. Similar trends were seen in reduction in dystonia, i.e., >50 % reduction in 74.3 %, >75 % reduction in 62.2 % and complete resolution was seen in 56.1 %.

Conclusions

The present study suggest that clozapine is useful in the management of drug induced tardive dyskinesia and tardive dystonia.

Although large-scale genome-wide association studies (GWASs) have revealed the genetic architecture of schizophrenia, these studies have mainly focused on populations of European ancestry. This study aimed to identify common genetic variants associated with schizophrenia in the Korean population and evaluate the performance of polygenic risk scores (PRSs) derived from large-scale GWASs across ancestries. In the Korean psychiatric GWAS project (KPGP), seven academic institutes and their affiliated hospitals across South Korea recruited a cohort of 1670 patients with DSM-IV-defined schizophrenia and 2271 healthy controls. A total of 6690,822 SNPs were tested for association with schizophrenia. We identified one previously unreported genome-wide significant locus rs2423464 (P = 2.83 × 10⁻¹¹; odds ratio = 1.65; 95 % confidence interval = 1.43–1.91, minor allele frequency = 0.126). This variant was also associated with increased lysosomal-associated membrane protein family member 5 (LAMP5) gene expression. The PRS derived from the meta-analysis results of East Asian and European GWASs explained a larger proportion of the phenotypic variance in the Korean schizophrenia sample than the PRS of an East Asian or European GWAS. (R² = 0.073 for meta-analysis; 0.028 for East Asian GWAS; 0.037 for European GWAS). GWASs involving diverse ethnic groups will expand our understanding of the genetic architecture of schizophrenia.

The integration of artificial intelligence (AI) into the diagnosis and treatment of autism spectrum disorder (ASD) represents a promising frontier in healthcare. This review explores the current landscape and future prospects of AI technologies in ASD diagnostics and interventions. AI enables early detection and personalized assessment of ASD through the analysis of diverse data sources such as behavioural patterns, neuroimaging, genetics, and electronic health records. Machine learning algorithms exhibit high accuracy in distinguishing ASD from neurotypical development and other developmental disorders, facilitating timely interventions. Furthermore, AI-driven therapeutic interventions, including augmentative communication systems, virtual reality-based training, and robot-assisted therapies, show potential in improving social interactions and communication skills in individuals with ASD. Despite challenges such as data privacy and interpretability, the future of AI in ASD holds promise for refining diagnostic accuracy, deploying telehealth platforms, and tailoring treatment plans. By harnessing AI, clinicians can enhance ASD care delivery, empower patients, and advance our understanding of this complex condition.