ArticlePharmacotherapy2018
Atypical Antipsychotic Exposure May Not Differentiate Metabolic Phenotypes of Patients with Schizophrenia.
Article in Pharmacotherapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Discovery of biological markers for schizophrenia based on metabolomics: a systematic review.Frontiers in psychiatry · 2025Pooled it
- Metabolomics, Lipidomics, and Antipsychotics: A Systematic Review.Biomedicines · 2023Review
- Sex differences in the prevalence and clinical correlates of diabetes in Chinese patients with chronic schizophrenia.Heliyon · 2023Article
- Effects of Psychostimulants and Antipsychotics on Serum Lipids in an Animal Model for Schizophrenia.Biomedicines · 2021Article
- Genetic and Metabolite Variability in One-Carbon Metabolism Applied to an Insulin Resistance Model in Patients With Schizophrenia Receiving Atypical Antipsychotics.Frontiers in psychiatry · 2021Article
- Metabolomic profiles associated with a mouse model of antipsychotic-induced food intake and weight gain.Scientific reports · 2020Article
- Atypical Antipsychotics and the Human Skeletal Muscle Lipidome.Metabolites · 2018Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
STUDY
objectivePatients with schizophrenia are known to have higher rates of metabolic disease than the general population. Contributing factors likely include lifestyle and atypical antipsychotic (AAP) use, but the underlying mechanisms are unknown. The objective of this study was to identify metabolomic variability in adult patients with schizophrenia who were taking AAPs and grouped by fasting insulin concentration, our surrogate marker for metabolic risk.
designMetabolomics analysis
participantsNinety-four adult patients with schizophrenia who were taking an AAP for at least 6 months, with no changes in their antipsychotic regimen for the previous 8 weeks, and who did not require treatment with insulin, participated in the study. Twenty age- and sex-matched nonobese (10 subjects) and obese (10 subjects) controls without cardiovascular disease or mental health diagnoses were used to match the body mass index (BMI) range of the patients with schizophrenia to account for metabolite concentration differences attributable to BMI. MEASUREMENTS AND MAIN
resultsExisting serum samples were used to identify aqueous metabolites (to differentiate fasting insulin concentration quartiles) and fatty acids with quantitative nuclear magnetic resonance and gas chromatography methods, respectively. To exclude metabolites from our pathway mapping analysis that were due to variability in weight, we also subjected serum samples from the nonobese and obese controls to the same analyses. Patients with schizophrenia had a median age of 47.0 years (interquartile range 41.0-52.0 years). Using a false discovery rate threshold of less than 25%, 10 metabolites, not attributable to weight, differentiated insulin concentration quartiles in patients with schizophrenia and identified variability in one-carbon metabolism between groups. Patients with higher fasting insulin concentrations (quartiles 3 and 4) also trended toward higher levels of saturated fatty acids compared with patients with lower fasting insulin concentrations (quartiles 1 and 2).
conclusionOur results illustrate the utility of metabolomics to identify pathways underlying variable fasting insulin concentration in patients with schizophrenia. Importantly, no significant difference in AAP exposure was observed among groups, suggesting that current antipsychotic use may not be a primary factor that differentiates middle-aged adult patients with schizophrenia by fasting insulin concentration.
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