# Living systematic review and meta-analysis of plasma-concentrations of antipsychotic drugs in carriers and non-carriers of variant CYP450 genotypes: Living systematic review protocol

**Authors:** Filip Milosavljević, Stefan Leucht, Pierre Baumann, Filip Milosavljević, Jhohann Richard de Lima Benzi, Filip Milosavljević

PMC · DOI: 10.12688/f1000research.147794.1 · F1000Research · 2024-05-07

## TL;DR

This paper outlines a living systematic review and meta-analysis to study how genetic variations affect plasma levels of antipsychotic drugs, aiming to improve personalized treatment.

## Contribution

The study introduces a continuously updated living systematic review and meta-analysis framework for pharmacogenomic drug-gene interactions in antipsychotics.

## Key findings

- A baseline systematic review and meta-analysis will compare plasma drug levels between genotype carriers and non-carriers.
- The project will use random-effect ratio-of-means meta-analysis to assess drug-gene interactions.
- Results will be updated every six months and made publicly accessible online.

## Abstract

Carriers of variant alleles of genes that encode liver CYP450 and UGT enzymes may experience abnormal plasma levels of antipsychotics and, consequently, worse efficacy or tolerability. Although pharmacogenomics is a rapidly developing field, current guidelines often rely on limited, underpowered evidence. We have previously demonstrated that meta-analysis is a viable strategy for overcoming this problem. Here, we propose a project that will expand our previous work and create a living systematic review and meta-analysis of drug plasma level differences between carriers and non-carriers of variant genotype-predicted phenotypes for every pharmacokinetic drug-gene interaction relevant to commonly used antipsychotic drugs.

First, a baseline systematic review and meta-analysis will be conducted by searching for observational pharmacogenomics-pharmacokinetic studies. Data on dose-adjusted drug plasma levels will be extracted, and participants will be grouped based on their genotype for each drug-gene pair separately. Differences in plasma drug levels between different phenotypes will be compared using a random-effect ratio-of-means meta-analysis. The risk of bias will be assessed using ROBINS-I, and the certainty of evidence will be assessed using GRADE. Following the establishment of baseline results, the literature search will be re-run at least once every six months, and the baseline data will be updated and re-evaluated as new evidence is published. A freely available website will be designated to present up-to-date results and conclusions.

This systematic review will provide evidence-based results that are continuously updated with evidence as it emerges in the rapidly developing field of pharmacogenomics. These results may help psychiatrists in their decision-making, as clinicians are becoming increasingly aware of the patients’ genetic data as testing becomes more widespread and cheaper. In addition, the results may serve as a scientific basis for the development of evidence-based pharmacogenomics algorithms for personalized dosing of antipsychotics to mitigate potentially harmful drug-gene interactions.

## Linked entities

- **Genes:** LOC107927610 (alkane hydroxylase MAH1-like) [NCBI Gene 107927610]

## Full-text entities

- **Genes:** UGT1A (UDP glucuronosyltransferase family 1 member A complex locus) [NCBI Gene 7361] {aka GNT1, UGT, UGT1, UGT1A@}
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC11292185/full.md

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Source: https://tomesphere.com/paper/PMC11292185