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Metabolomics of Metabolic Risk in Patients Taking Atypical Antipsychotics (part II)

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 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.

ORGANISM(S): Human Homo Sapiens

TISSUE(S): Blood

DISEASE(S): Schizophrenia

SUBMITTER: Kathleen Stringer

PROVIDER: ST001098 | MetabolomicsWorkbench | Thu Nov 15 00:00:00 GMT 2018

REPOSITORIES: MetabolomicsWorkbench

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Project description: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. 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.

Project description:In this study, we compared the expression profiles of miRNAs in blood samples from Impaired Fasting Glucose (IFG) and T2D male patients. Healthy adult males with no past history of T2D (n=158) and with desirable cholesterol and blood pressure profiles were enrolled in this study. They were then classified according to fasting glucose levels to have T2D, IFG or as healthy controls (CTL), for comparison of miRNA expression profiles. Employing miRNA microarray, we identified ‘signature miRNAs’ in peripheral blood samples that distinguished IFG and T2D. Eight selected miRNAs were further validated using stem-loop real-time RT-PCR. miR-144 expression was found to be dysregulated in Type 2 Diabetes, wherein its expression was significantly higher than in healthy controls. Insulin receptor substrate 1 (IRS1) has been predicted to be a potential target of miR-144. Consistent with this observation, IRS1 mRNA and protein levels, verified by quantitative real-time PCR and western blotting respectively, were found to be down-regulated. Dysregulation in expression of microRNAs (miRNAs) in various tissues has been linked to a wide spectrum of diseases, including Type 2 Diabetes mellitus (T2D). In this study, we compared the expression profiles of miRNAs in blood samples from Impaired Fasting Glucose (IFG) and T2D male patients. Healthy adult males with no past history of T2D (n=158) and with desirable cholesterol and blood pressure profiles were enrolled in this study. They were then classified according to fasting glucose levels to have T2D, IFG or as healthy controls (CTL), for comparison of miRNA expression profiles. Employing miRNA microarray, we identified ‘signature miRNAs’ in peripheral blood samples that distinguished IFG and T2D. Eight selected miRNAs were further validated using stem-loop real-time RT-PCR. miR-144 expression was found to be dysregulated in Type 2 Diabetes, wherein its expression was significantly higher than in healthy controls. Insulin receptor substrate 1 (IRS1) has been predicted to be a potential target of miR-144. Consistent with this observation, IRS1 mRNA and protein levels, verified by quantitative real-time PCR and western blotting respectively, were found to be down-regulated. Using luciferase assay, we further demonstrated that miR-144 directly targets IRS1 and showed its effects on protein expression via immunocytochemistry. From this cross-sectional study in humans, we have identified signature miRNAs which could explain the pathogenesis of T2D. Whether miRNAs like miR-144 could be potential therapeutic targets for management of T2D will need to be explored by further mechanistic and functional studies. Total RNA (plus miRNAs) was isolated using a modification of the RiboPure™-Blood kit from Ambion (Austin,TX) according to the manufacturer’s protocol. The concentration of total RNA and integrity were determined by using Nano-Drop ND-1000 Spectrophotometry (NanoDrop Tech, Rockland, Del) and gel electrophoresis respectively.

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Metabolomics of Metabolic Risk in Patients Taking Atypical Antipsychotics (part II)

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