Genome Wide Study of Tardive Dyskinesia in Schizophrenia

Lam, Max; Lim, Keane; Tay, Jenny; Karlsson, Nina; Deshpande, Smita N.; Thelma, B. K.; Ozaki, Norio; Inada, Toshiya; Sim, Kang; Chong, Siow‐Ann; Li, Jianjun; Lee, Jimmy

doi:10.1101/386227

Cited by 2 publications

(2 citation statements)

References 69 publications

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“…Indeed, the link between AP use and increased PRL has been well-established, and high PRL has been associated with hypertension ( 56 ). Although we did not find studies linking TNFRSF1B to AP use per se , a previous GWAS study linked TNFRSF1B to tardive dyskinesia, a known side effect of APs ( 57 ). In addition, olanzapine use has also been associated with CD36 overexpression ( 58 ).…”

Section: Discussioncontrasting

confidence: 81%

Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls

et al. 2022

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BackgroundSchizophrenia (SZ) and bipolar disorder (BD) share many features: overlap in mood and psychotic symptoms, common genetic predisposition, treatment with antipsychotics (APs), and similar metabolic comorbidities. The pathophysiology of both is still not well defined, and no biomarkers can be used clinically for diagnosis and management. This study aimed to assess the plasma proteomics profile of patients with SZ and BD maintained on APs compared to those who had been off APs for 6 months and to healthy controls (HCs).MethodsWe analyzed the data using functional enrichment, random forest modeling to identify potential biomarkers, and multivariate regression for the associations with metabolic abnormalities.ResultsWe identified several proteins known to play roles in the differentiation of the nervous system like NTRK2, CNTN1, ROBO2, and PLXNC1, which were downregulated in AP-free SZ and BD patients but were “normalized” in those on APs. Other proteins (like NCAM1 and TNFRSF17) were “normal” in AP-free patients but downregulated in patients on APs, suggesting that these changes are related to medication's effects. We found significant enrichment of proteins involved in neuronal plasticity, mainly in SZ patients on APs. Most of the proteins associated with metabolic abnormalities were more related to APs use than having SZ or BD. The biomarkers identification showed specific and sensitive results for schizophrenia, where two proteins (PRL and MRC2) produced adequate results.ConclusionsOur results confirmed the utility of blood samples to identify protein signatures and mechanisms involved in the pathophysiology and treatment of SZ and BD.

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Section: Discussioncontrasting

confidence: 81%

Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls

et al. 2022

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“…Two STCRP schizophrenia cohorts were of Asian descent and were recruited between 2005 to 2008 (N = H44) 20,36 and 2008 to 2011 (N = 921). 23,35 The third cohort were individuals (N = 168) deemed as Ultra-High Risk (UHR) of psychosis recruited between 2008 to 2011.…”

Section: Methodsmentioning

confidence: 99%

Large-Scale Evaluation of the Positive and Negative Syndrome Scale (PANSS) Symptom Architecture in Schizophrenia

Lim

Peh

Yang

et al. 2020

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Although the Positive and Negative Syndrome Scale (PANSS) is widely utilized in schizophrenia research, variability in specific item loading exist, hindering reproducibility and generalizability of findings across schizophrenia samples. We aim to establish a common metric PANSS factor structure from a large multi-ethnic sample and validate it against a meta-analysis of existing PANSS models. Schizophrenia participants (N = 3511) included in the current study were part of the Singapore Translational and Clinical Research Program (STCRP) and the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE). Exploratory Factor Analysis (EFA) was conducted to identify the factor structure of PANSS and validated with a meta-analysis (N = 16,171) of existing PANSS models. Temporal stability of the PANSS model and generalizability to individuals at ultra-high risk (UHR) of psychosis were evaluated. A five-factor solution best fit the PANSS data. These were the i) Positive, ii) Negative, iii) Cognitive/disorganization, iv) Depression/anxiety and v) Hostility factors. Convergence of PANSS symptom architecture between EFA model and meta-analysis was observed. Modest longitudinal reliability was observed. The schizophrenia derived PANSS factor model fit the UHR population, but not vice versa. We found that two other domains, Social Amotivation (SA) and Diminished Expression (DE), were nested within the negative symptoms factor. Here, we report one of the largest transethnic factorial structures of PANSS symptom domains (N = 19,682). Evidence reported here serves as crucial consolidation of a common metric PANSS that could aid in furthering our understanding of schizophrenia.

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Genome Wide Study of Tardive Dyskinesia in Schizophrenia

Cited by 2 publications

References 69 publications

Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls

Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics: Comparison to Patients Off Antipsychotics and Normal Controls

Large-Scale Evaluation of the Positive and Negative Syndrome Scale (PANSS) Symptom Architecture in Schizophrenia

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