Summary of Study ST001098

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR000734. The data can be accessed directly via it's Project DOI: 10.21228/M8SX1Q This work is supported by NIH grant, U2C- DK119886.


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Study IDST001098
Study TitleMetabolomics of Metabolic Risk in Patients Taking Atypical Antipsychotics (part II)
Study SummarySTUDY 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 metabolomics 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. 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 range of the patients with schizophrenia to account for metabolite concentration differences attributable to body mass index. 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 (NMR) and gas chromatography (GC) 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 (interquartile range 41.0-52.0) years. Using a false discovery rate threshold of <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 having higher levels of saturated fatty acids compared with patients with lower fasting insulin concentrations (quartiles 1 and 2). CONCLUSION These 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. This article is protected by copyright. All rights reserved. As published in Pharmacotherapy. 2018 Jun;38(6):638-650.
University of Michigan
Last NameStringer
First NameKathleen
Address428 Church St
Submit Date2018-11-15
Analysis Type DetailGC-MS
Release Date2019-01-22
Release Version1
Kathleen Stringer Kathleen Stringer application/zip

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Subject ID:SU001142
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:30-60 years old
Weight Or Weight Range:52.3-176.6 kg
Gender:Male and female
Human Medications:To be included in the study all participants had to be taking an atypical (second-generation) antipsychotic
Human Inclusion Criteria:DSM IV diagnosis of a schizophrenia spectrum diagnosis who had been taking an atypical antipsychotic for at least 6 months, with no changes in antipsychotic regimen for 8 weeks preceding the baseline visit. Twenty age and sex matched obese and nonobese participants without mental health diagnoses were included to match the BMI range of the patients with schizophrenia as BMI controls.
Human Exclusion Criteria:Current use of insulin, diagnosis of diabetes mellitus type 2 prior to antipsychotic exposure, active substance abuse diagnosis