Meta-analysis of differential expression of sex-biased and common drug metabolism enzymes and transporters genes in blood transcriptomics of mental disorders: An in silico study
Year: 2023
Type: review
Study design: Systematic Review
Abstract: Background: There are reports that pharmacogenomics, pharmacodynamics, and pharmacotherapeutics of psychiatric drugs differ significantly with sex. There is a dearth of literature on this aspect. The aim of this study is to identify sex-biased genes among common mental disorders and the influence of sex on the common drug metabolism enzymes and transporters (DMET) genes in blood transcriptomics data. Methodology: Data for this meta-analytic, in silico study, are from Gene Expression Omnibus repository with restrictions of human blood samples that measured the mRNA expression of genes of any mental disorder patients without any date limitations. The identified datasets were then entered into the online Exatlas software. Quality check of the dataset was performed and only those datasets that fulfilled were used further in this meta-analysis. DMET genes were identified from literature, and the differential expression (DE) was identified and presented. Results: In all, 239 patient samples with five common mental disorders formed the study group. Of them, there were 21139 genes, of which the number of significant genes (FDR <0.05) was 16989. In this meta-analysis of mental illness among either sex, 32 genes were identified as DE. Of these 32 genes, 23 (72%) belonged to sex chromosomes and the remaining mapped to autosomes. We identified 48 DEMT genes from literature and their DE reported. Conclusion: Within the limitation of this study, it is established that among the mentally ill, there is a measurable difference between males and females, in terms of gene expression, particularly of DMET genes. Such DE of genes can potentially alter the pharmacogenomics, pharmacodynamics, and pharmacotherapeutics of psychiatric drugs.
Language: English
Subfield: Pharmacology
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4402098103