Unexpected interaction between quetiapine and valproate in patients with bipolar disorder

Effect of antipsychotics and mood stabilisers on metabolism in bipolar disorder: a network meta-analysis of randomised-controlled trials

Background

Antipsychotics and mood stabilisers are gathering attention for the disturbance of metabolism. This network meta-analysis aims to evaluate and rank the metabolic effects of the commonly used antipsychotics and mood stabilisers in treating bipolar disorder (BD).

Methods

Registries including PubMed, Embase, Cochrane Library, Web of Science, Ovid, and Google Scholar were searched before February 15th, 2024, for randomised controlled trials (RCTs) applying antipsychotics or mood stabilisers for BD treatment. The observed outcomes were twelve metabolic indicators. The data were extracted by two reviewers independently, and confirmed by another four reviewers and a corresponding author. The above six reviewers all participated in data analyses. Data extraction was based on PRISMA guidelines, and quality assessment was conducted according to the Cochrane Handbook. Use a random effects model for data pooling. The PROSPERO registration number is CRD42023466669.

Findings

Together, 5421 records were identified, and 41 publications with 11,678 complete-trial participants were confirmed eligible. After eliminating possible sensitivity, risperidone ranked 1st in elevating fasting serum glucose (SUCRA = 90.7%) and serum insulin (SUCRA = 96.6%). Lurasidone was most likely to elevate HbA1c (SUCRA = 82.1%). Olanzapine ranked 1st in elevating serum TC (SUCRA = 93.3%), TG (SUCRA = 89.6%), and LDL (SUCRA = 94.7%). Lamotrigine ranked 1st in reducing HDL (SUCRA = 82.6%). Amisulpride ranked 1st in elevating body weight (SUCRA = 100.0%). For subgroup analyses, quetiapine is more likely to affect indicators of glucose metabolism among male adult patients with bipolar mania, while long-term lurasidone tended to affect glucose metabolism among female patients with bipolar depression. Among patients under 18, divalproex tended to affect glucose metabolism, with lithium affecting lipid metabolism. In addition, most observed antipsychotics performed higher response and remission rates than placebo, and displayed a similar dropout rate with placebo, while no between-group significance of rate was observed among mood stabilisers.

Interpretation

Our findings suggest that overall, antipsychotics are effective in treating BD, while they are also more likely to disturb metabolism than mood stabilisers. Attention should be paid to individual applicability in clinical practice. The results put forward evidence-based information and clinical inspiration for drug compatibility and further research of the BD mechanism.

Funding

The National Key Research and Development Program of China (2023YFC2506200), and the Research Project of Jinan Microecological Biomedicine Shandong Laboratory (No. JNL-2023001B).

Delirium Induced by Quetiapine and the Potential Role of Norquetiapine

Quetiapine in an atypical antipsychotic drug that is frequently used for delirium and behavioral and psychological symptoms in dementia. However, its potential anticholinergic effects, mediated primarily through its metabolite norquetiapine, could present as counterproductive adverse effects in these situations. There is little data published discussing this potential negative impact on quetiapine’s safety and tolerability, especially in the elderly. Here, we present what is, to our knowledge, the first published case report of delirium apparently induced by low-dose quetiapine, in a 95-year-old patient with no prior history of mental illness, and the potential role of its metabolite norquetiapine.

Drug voyager: a computational platform for exploring unintended drug action

BACKGROUND

The dominant paradigm in understanding drug action focuses on the intended therapeutic effects and frequent adverse reactions. However, this approach may limit opportunities to grasp unintended drug actions, which can open up channels to repurpose existing drugs and identify rare adverse drug reactions. Advances in systems biology can be exploited to comprehensively understand pharmacodynamic actions, although proper frameworks to represent drug actions are still lacking.

RESULTS

We suggest a novel platform to construct a drug-specific pathway in which a molecular-level mechanism of action is formulated based on pharmacologic, pharmacogenomic, transcriptomic, and phenotypic data related to drug response ( http://databio.gachon.ac.kr/tools/ ). In this platform, an adoption of three conceptual levels imitating drug perturbation allows these pathways to be realistically rendered in comparison to those of other models. Furthermore, we propose a new method that exploits functional features of the drug-specific pathways to predict new indications as well as adverse reactions. For therapeutic uses, our predictions significantly overlapped with clinical trials and an up-to-date drug-disease association database. Also, our method outperforms existing methods with regard to classification of active compounds for cancers. For adverse reactions, our predictions were significantly enriched in an independent database derived from the Food and Drug Administration (FDA) Adverse Event Reporting System and meaningfully cover an Adverse Reaction Database provided by Health Canada. Lastly, we discuss several predictions for both therapeutic indications and side-effects through the published literature.

CONCLUSIONS

Our study addresses how we can computationally represent drug-signaling pathways to understand unintended drug actions and to facilitate drug discovery and screening.

Interactions between valproic acid and quetiapine/olanzapine in the treatment of bipolar disorder and the role of therapeutic drug monitoring

OBJECTIVES

The anticonvulsant valproic acid and the atypical antipsychotics olanzapine and quetiapine provide synergistic mood-stabilising, antidepressant and antipsychotic activities in the treatment of bipolar and schizoaffective disorders. Existing literature shows that pharmacokinetic and pharmacodynamics drug-drug interactions (DDIs) possibly occur with the use of such a combination. Clinical reports of a possible interaction between the drugs leading to an increased risk of adverse drug reactions have also emerged. The main objective of this paper is to review the incidence of DDIs between the anticonvulsant and the antipsychotics, to postulate the possible mechanisms of the interaction and to establish whether certain target populations are at an increased susceptibility to such interactions. The usefulness of therapeutic drug monitoring (TDM) of the antipsychotics to monitor for an interaction was also assessed. A systematic database search was carried out using the search engine provided by PubMed using the following key words: olanzapine, quetiapine, valproic acid, pharmacokinetic drug-drug interaction, bipolar disorder, therapeutic drug monitoring.

KEY FINDINGS

Evidence of a possible clinically relevant DDI between valproic acid and both antipsychotics has been uncovered. A possible mechanism for the interactions has been postulated, and the importance of TDM has been discussed.

SUMMARY

Further research is required to determine whether DDIs occur with the concurrent use of valproic acid and olanzapine or quetiapine, and to investigate the potential of TDM as a clinical tool in improving pharmacotherapy and preventing toxicity.

Adverse drug reactions induced by valproic acid

Valproic acid is a widely-used first-generation antiepileptic drug, prescribed predominantly in epilepsy and psychiatric disorders. VPA has good efficacy and pharmacoeconomic profiles, as well as a relatively favorable safety profile. However, adverse drug reactions have been reported in relation with valproic acid use, either as monotherapy or polytherapy with other antiepileptic drugs or antipsychotic drugs. This systematic review discusses valproic acid adverse drug reactions, in terms of hepatotoxicity, mitochondrial toxicity, hyperammonemic encephalopathy, hypersensitivity syndrome reactions, neurological toxicity, metabolic and endocrine adverse events, and teratogenicity.