Pharmacometabolomics of Psychotropic Drugs: Treatment Response, Adverse Effects, and Precision Psychiatry—A Narrative Review
Abstract
<h4>Background: </h4> /Objectives: Response to psychotropic medications is highly variable: approximately 40% of patients with major depressive disorder fail to respond to initial antidepressant treatment, and antipsychotics and mood stabilizers show comparably wide inter-individual variability in efficacy and tolerability. Genetic studies explain only a fraction of this variation, and the absence of valid biomarkers forces trial-and-error prescribing. Pharmacometabolomics — the application of global metabolite profiling to drug response — has emerged as a complementary “omics” strategy capturing the integrated effects of genome, environment, gut microbiome, and disease state on efficacy and toxicity. This review synthesizes evidence that pharmacometabolomics can predict psychotropic treatment response, characterize adverse metabolic effects, and contribute to precision psychiatry, focusing on antidepressants, antipsychotics, and mood stabilizers. <h4>Methods:</h4> This narrative review synthesized seminal conceptual and methodological literature, proof-of-concept and replication pharmacometabolomic studies in depressed, psychotic, and bipolar populations, lipidomic and metabolomic investigations of antipsychotic-induced metabolic adversity, ketamine/esketamine translational studies, and pharmacometabolomics-informed pharmacogenomic investigations, prioritizing highly cited primary literature. <h4>Results:</h4> Pretreatment metabolic profiles (“metabotypes”) distinguish responders from non-responders to sertraline and placebo, and baseline glycine, sphingolipid, and tryptophan-pathway metabolites predict citalopram/escitalopram outcomes, with a glycine dehydrogenase polymorphism identified through pharmacometabolomics-informed pharmacogenomics. Ketamine and esketamine produce detectable changes in glutamate, tryptophan, and urea-cycle metabolites within two hours that correlate with antidepressant response days later. Risperidone normalizes partially disturbed energy, neurotransmitter, and phospholipid pathways in schizophrenia, and lipidomic signatures track antipsychotic-associated weight gain, free-fatty-acid surges, and diabetes risk. Gut microbial metabolism of psychotropics contributes additional, individually variable layers of drug activation and toxicity visible in the metabolome, and regulatory frameworks for biomarker qualification are emerging. <h4>Conclusions:</h4> Pharmacometabolomics provides mechanism-based, dynamically measurable biomarkers of psychotropic treatment response and adverse effects, and its integration with pharmacogenomics and systems pharmacology offers a credible route to precision psychiatry. Prospective validation, standardized analytical platforms, and multi-omics integration remain the principal barriers to clinical translation.
Topics & conditions
Detected automatically by Psychedelic Commons from the title and abstract, not labels from the source. They may be incomplete.
Psychedelic Commons aggregates metadata from open sources and links back to the original. Rights remain with the authors and publishers. Something wrong with this record? Report a problem.