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Cureus Jan 2024Antipsychotics are considered a gold standard treatment for schizophrenia. However, there is considerable variation in antipsychotic medication choice. Factors...
Antipsychotics are considered a gold standard treatment for schizophrenia. However, there is considerable variation in antipsychotic medication choice. Factors considered involved include symptomatology, prior response, and adverse reactions. This case report presents a 38-year-old male patient with schizophrenia in acute psychosis refractory to several antipsychotics. Hypotheses for the mechanism of action of antipsychotics and psychopharmacology are discussed, and treatment resistance is defined. The patient's psychiatric, medical, and social history and past antipsychotic medications are reviewed. Afterward, the rationale for initiating perphenazine is discussed, and the patient's improvement with this medication is examined. Current literature on perphenazine's efficacy is also reviewed and discussed alongside its limitations.
PubMed: 38313962
DOI: 10.7759/cureus.51593 -
Frontiers in Psychiatry 2023Our objective was to conduct a systematic review and meta-analysis of adverse effects on sleep in patients with schizophrenia receiving antipsychotic treatment.
INTRODUCTION
Our objective was to conduct a systematic review and meta-analysis of adverse effects on sleep in patients with schizophrenia receiving antipsychotic treatment.
METHODS
A systematic search was performed in PubMed, Cochrane Central, Embase, Toxline, Ebsco, Virtual Health Library, Web of Science, SpringerLink, and in Database of abstracts of Reviews of Effects of Randomized Clinical Trials to identify eligible studies published from January 1990 to October 2021. The methodological quality of the studies was evaluated using the CONSORT list, and the Cochrane bias tool. Network meta-analysis was performed using the Bayesian random-effects model, with multivariate meta-regression to assess the association of interest.
RESULTS
87 randomized clinical trials were identified that met the inclusion criteria, and 70 articles were included in the network meta-analysis. Regarding the methodological quality of the studies, 47 had a low or moderate bias risk. The most common adverse effects on sleep reported in the studies were insomnia, somnolence, and sedation. The results of the network meta-analysis showed that ziprasidone was associated with an increased risk of insomnia (OR, 1.56; 95% credible interval CrI, 1.18-2.06). Several of the included antipsychotics were associated with a significantly increased risk of somnolence; haloperidol (OR, 1.90; 95% CrI, 1.12-3.22), lurasidone (OR, 2.25; 95% CrI, 1.28-3.97) and ziprasidone (OR, 1.79; 95% CrI, 1.06-3.02) had the narrowest confidence intervals. In addition, perphenazine (OR, 5.33; 95% CrI, 1.92-14.83), haloperidol (OR, 2.61; 95% CrI, 1.14-5.99), and risperidone (OR, 2.41; 95% CrI, 1.21-4.80) were associated with an increased risk of sedation compared with placebo, and other antipsychotics did not differ. According to the SUCRAs for insomnia, chlorpromazine was ranked as the lowest risk of insomnia (57%), followed by clozapine (20%), while flupentixol (26 %) and perospirone (22.5%) were associated with a lower risk of somnolence. On the other hand, amisulpride (89.9%) was the safest option to reduce the risk of sedation.
DISCUSSION
Insomnia, sedation, and somnolence were the most frequent adverse effects on sleep among the different antipsychotics administered. The evidence shows that chlorpromazine, clozapine, flupentixol, perospirone, and amisulpride had favorable safety profiles. In contrast, ziprasidone, perphenazine, haloperidol, and risperidone were the least safe for sleep.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42017078052, identifier: PROSPERO 2017 CRD42017078052.
PubMed: 37441144
DOI: 10.3389/fpsyt.2023.1189768 -
Frontiers in Psychiatry 2023Depression is widespread global problem that not only severely impacts individuals' physical and mental health but also imposes a heavy disease burden on nations and...
BACKGROUND
Depression is widespread global problem that not only severely impacts individuals' physical and mental health but also imposes a heavy disease burden on nations and societies. The role of inflammation in the pathogenesis and pathophysiology of depression has received much attention, but the precise relationship between the two remains unclear. This study aims to investigate the correlation between depression and inflammation using a network medicine approach.
METHODS
We utilized a degree-preserving approach to identify the large connected component (LCC) of all depression-related proteins in the human interactome. The LCC was deemed as the disease module for depression. To measure the association between depression and other diseases, we calculated the overlap between these disease protein modules using the Sab algorithm. A smaller Sab value indicates a stronger association between diseases. Building on the results of this analysis, we further explored the correlation between inflammation and depression by conducting enrichment and pathway analyses of critical targets. Finally, we used a network proximity approach to calculate drug-disease proximity to predict the efficacy of drugs for the treatment of depression. We calculated and ranked the distances between depression disease modules and 6,100 drugs. The top-ranked drugs were selected to explore their potential for treating depression based on the hypothesis that their antidepressant effects are related to reducing inflammation.
RESULTS
In the human interactome, all depression-related proteins are clustered into a large connected component (LCC) consisting of 202 proteins and multiple small subgraphs. This indicates that depression-related proteins tend to form clusters within the same network. We used the 202 LCC proteins as the key disease module for depression. Next, we investigated the potential relationships between depression and 299 other diseases. Our analysis identified over 18 diseases that exhibited significant overlap with the depression module. Where S = -0.075 for the vascular disease and depressive disorders module, S = -0.070 for the gastrointestinal disease and depressive disorders module, and S = -0.062 for the endocrine system disease and depressive disorders module. The distance between them S < 0 implies that the pathogenesis of depression is likely to be related to the pathogenesis of its co-morbidities of depression and that potential therapeutic approaches may be derived from the disease treatment libraries of these co-morbidities. Further, considering that the inflammation is ubiquitous in some disease, we calculate the overlap between the collected inflammation module (236 proteins) and the depression module (202 proteins), finding that they are closely related (S = -0.358) in the human protein interaction network. After enrichment and pathway analysis of key genes, we identified the HIF-1 signaling pathway, PI3K-Akt signaling pathway, Th17 cell differentiation, hepatitis B, and inflammatory bowel disease as key to the inflammatory response in depression. Finally, we calculated the -score to determine the proximity of 6,100 drugs to the depression disease module. Among the top three drugs identified by drug-disease proximity analysis were Perphenazine, Clomipramine, and Amitriptyline, all of which had a greater number of targets in the network associated with the depression disease module. Notably, these drugs have been shown to exert both anti-inflammatory and antidepressant effects, suggesting that they may modulate depression through an anti-inflammatory mechanism. These findings demonstrate a correlation between depression and inflammation at the network medicine level, which has important implications for future elucidation of the etiology of depression and improved treatment outcomes.
CONCLUSION
Neuroimmune signaling pathways play an important role in the pathogenesis of depression, and many classes of antidepressants exhibiting anti-inflammatory properties. The pathogenesis of depression is closely related to inflammation.
PubMed: 37492068
DOI: 10.3389/fpsyt.2023.1184188 -
Heliyon Nov 2023Adverse events (AEs) of antipsychotic drugs include neuroleptic malignant syndrome (NMS), which presents complex clinical symptoms, resulting in a fatal outcome. In this...
Adverse events (AEs) of antipsychotic drugs include neuroleptic malignant syndrome (NMS), which presents complex clinical symptoms, resulting in a fatal outcome. In this study, the association between antipsychotic drugs and NMS was comprehensively evaluated by cluster and association analyses using the Japanese Adverse Drug Event Report (JADER) database. The analyses were performed using 20 typical antipsychotics (TAPs) alongside 9 atypical antipsychotics (AAPs). The Standardised MedDRA Queries (SMQ) database was used to analyze NMS (SMQ code: 20000044). Reporting odds ratios (RORs) were used for AE signal detection. The relationship between antipsychotic drugs and AEs for NMS was investigated by performing hierarchical cluster analysis using Ward's method. Between April 2004 and September 2021, the total number of JADER reports was 705,294. RORs (95 % confidence interval) of NMS for haloperidol, chlorpromazine, risperidone, and aripiprazole were 12.1 (11.1-13.3), 6.3 (5.7-7.0), 6.2 (5.8-6.6), and 4.7 (4.4-5.1), respectively. Three clusters were formed, with characteristics as follows: Cluster 1 consisted of only TAPs, such as bromperidol and fluphenazine, whilst having a high reporting rate of hypotension, tachycardia, dyskinesia, and dystonia. Cluster 2 consisted of all AAPs alongside several TAPs, such as haloperidol and chlorpromazine, with higher reporting rates of disturbance of consciousness, extrapyramidal disorders (excluding dyskinesia and dystonia), and serotonin syndrome. Cluster 3 consisted of only perphenazine, whilst having a higher reporting rate of coma, leukocytosis, and Parkinsonism. The results of this study may therefore aid in the management of NMS using antipsychotic drugs.
PubMed: 38034668
DOI: 10.1016/j.heliyon.2023.e21891 -
EBioMedicine Jun 2024Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations...
BACKGROUND
Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia.
METHODS
A total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed.
FINDINGS
Higher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33-7.19) and risk CNVs was 8.47 (95% CI: 1.92-37.43). CNV interacted with genetic risk score on APD efficacy (Beta = -1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%-82.82%).
INTERPRETATION
Copy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted.
FUNDING
National Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.
PubMed: 38870545
DOI: 10.1016/j.ebiom.2024.105195 -
Immunity, Inflammation and Disease May 2024Esophageal cancer (ESCA) is a highly invasive malignant tumor with poor prognosis. This study aimed to discover a generalized and high-sensitivity immune prognostic...
BACKGROUND
Esophageal cancer (ESCA) is a highly invasive malignant tumor with poor prognosis. This study aimed to discover a generalized and high-sensitivity immune prognostic signature that could stratify ESCA patients and predict their overall survival, and to discover potential therapeutic drugs by the connectivity map.
METHODS
The key gene modules significantly related to clinical traits (survival time and state) of ESCA patients were selected by weighted gene coexpression network analysis (WCGNA), then the univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a 15-immune-related gene prognostic signature.
RESULTS
The immune-related risk model was related to clinical and pathologic factors and remained an effective independent prognostic factor. Enrichment analyses revealed that the differentially expressed genes (DEGs) of the high- and low-risk groups were associated with tumor cell proliferation and immune mechanisms. Based on the gathered data, a small molecule drug named perphenazine (PPZ) was elected. The pharmacological analysis indicates that PPZ could help in adjuvant therapy of ESCA through regulation of metabolic process and cellular proliferation, enhancement of immunologic functions, and inhibition of inflammatory reactions. Furthermore, molecular docking was performed to explore and verify the PPZ-core target interactions.
CONCLUSION
We succeed in structuring the immune-related prognostic model, which could be used to distinguish and predict patients' survival outcome, and screening a small molecule drug named PPZ. Prospective studies also are needed to further validate its analytical accuracy for estimating prognoses and confirm the potential use of PPZ for treating ESCA.
Topics: Esophageal Neoplasms; Humans; Network Pharmacology; Prognosis; Computational Biology; Gene Regulatory Networks; Gene Expression Regulation, Neoplastic; Gene Expression Profiling; Biomarkers, Tumor; Molecular Docking Simulation; Antineoplastic Agents; Male; Female
PubMed: 38804848
DOI: 10.1002/iid3.1266 -
International Journal of Molecular... May 2024In the area of drug research, several computational drug repurposing studies have highlighted candidate repurposed drugs, as well as clinical trial studies that have...
In the area of drug research, several computational drug repurposing studies have highlighted candidate repurposed drugs, as well as clinical trial studies that have tested/are testing drugs in different phases. To the best of our knowledge, the aggregation of the proposed lists of drugs by previous studies has not been extensively exploited towards generating a dynamic reference matrix with enhanced resolution. To fill this knowledge gap, we performed weight-modulated majority voting of the modes of action, initial indications and targeted pathways of the drugs in a well-known repository, namely the Drug Repurposing Hub. Our method, Democracy, exploits this pile of information and creates frequency tables and, finally, a disease suitability score for each drug from the selected library. As a testbed, we applied this method to a group of neurodegenerative diseases (Alzheimer's, Parkinson's, Huntington's disease and Multiple Sclerosis). A super-reference table with drug suitability scores has been created for all four neurodegenerative diseases and can be queried for any drug candidate against them. Top-scored drugs for Alzheimer's Disease include agomelatine, mirtazapine and vortioxetine; for Parkinson's Disease, they include apomorphine, pramipexole and lisuride; for Huntington's, they include chlorpromazine, fluphenazine and perphenazine; and for Multiple Sclerosis, they include zonisamide, disopyramide and priralfimide. Overall, Democracy is a methodology that focuses on leveraging the existing drug-related experimental and/or computational knowledge rather than a predictive model for drug repurposing, offering a quantified aggregation of existing drug discovery results to (1) reveal trends in selected tracks of drug discovery research with increased resolution that includes modes of action, targeted pathways and initial indications for the investigated drugs and (2) score new candidate drugs for repurposing against a selected disease.
Topics: Drug Repositioning; Humans; Drug Discovery; Neurodegenerative Diseases
PubMed: 38791356
DOI: 10.3390/ijms25105319 -
Clinical Case Reports Aug 2023In some patients, neuroleptic malignant syndrome is accompanied significant high levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP).
KEY CLINICAL MESSAGE
In some patients, neuroleptic malignant syndrome is accompanied significant high levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP).
ABSTRACT
Neuroleptic malignant syndrome (NMS) is an idiosyncratic life-threatening adverse reaction and usually triggered in response to antipsychotic drugs. In addition, leukocytosis and increased muscle enzymes levels (especially creatine phosphokinase) are observed in NMS. In addition, a transient increase in different types of acute phase reactants in NMS has been mentioned. This article describes a woman treated with haloperidol, perphenazine, escitalopram, and alprazolam because she developed catatonic symptoms after psychological stress. She suffered from NMS symptoms and had elevated CRP and ESR levels, among other signs and symptoms. Given the COVID-19 pandemic and reports of co-occurrence of catatonia and NMS and COVID-19 and elevated erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), this patient was a diagnostic dilemma. After consultation with the consultation-liaison psychiatry units, she was managed adequately with electroconvulsive therapy and lorazepam.
PubMed: 37546158
DOI: 10.1002/ccr3.7734