Atypical Antipsychotic Exposure May Not Differentiate Metabolic Phenotypes of Patients with Schizophrenia. Issue 6 (21st June 2018)

• Record Type: Journal Article
• Authors: Ward, Kristen M.; Yeoman, Larisa; McHugh, Cora; Kraal, A. Zarina; Flowers, Stephanie A.; Rothberg, Amy E.; Karnovsky, Alla; Das, Arun K.; Ellingrod, Vicki L.; Stringer, Kathleen A.
• Is Part Of: Pharmacotherapy. Volume 38:Issue 6(2018)
• Page Start: 638
• Page End: 650
• Publication Date: 2018-06-21
• Subjects: adverse drug reactions -- Insulin -- antipsychotics; Chemotherapy -- Periodicals; Pharmacology -- Periodicals; Drug Therapy -- Periodicals; Pharmacology -- Periodicals; 615.1
• DOI: 10.1002/phar.2119
• Languages: English
• ISSNs: 0277-0008

Abstract

Abstract : Study Objective: Patients 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. Design: Metabolomics analysis Participants: Ninety‐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 Results: Existing 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). Conclusion: Our 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.