Atypical Antipsychotic Exposure May Not Differentiate Metabolic Phenotypes of Patients with Schizophrenia.
Atypical Antipsychotic Exposure May Not Differentiate Metabolic Phenotypes of Patients with Schizophrenia.
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DOI：
10.1002/phar.2119
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发表时间：
2018-06
期刊：
影响因子：
4.1
通讯作者：
Stringer KA
中科院分区：
文献类型：
--
作者：
Ward KM;Yeoman L;McHugh C;Kraal AZ;Flowers SA;Rothberg AE;Karnovsky A;Das AK;Ellingrod VL;Stringer KA
众所周知，精神分裂症患者的代谢疾病发生率高于一般人群。影响因素可能包括生活方式和非典型抗精神病药（AAP）的使用，但其潜在机制尚不清楚。本研究的目的是确定正在服用AAP的成年精神分裂症患者的代谢组学变异性，并按空腹胰岛素浓度（我们的代谢风险替代标志物）分组。代谢组学分析。94名成年精神分裂症患者服用AAP至少6个月，过去8周抗精神病药物治疗方案没有变化，并且不需要胰岛素治疗。20名年龄和性别匹配的非肥胖（10名受试者）和肥胖（10名受试者）对照，无心血管疾病或精神健康诊断，用于匹配精神分裂症患者的体重指数范围，以解释归因于体重指数的代谢物浓度差异。使用现有血清样本分别采用定量核磁共振（NMR）和气相色谱（GC）方法鉴定水性代谢物（以区分空腹胰岛素浓度四分位数）和脂肪酸。为了从我们的途径图谱分析中排除由于体重变化引起的代谢物，我们还对来自非肥胖和肥胖对照的血清样品进行了相同的分析。精神分裂症患者的中位年龄为47.0岁（四分位距41.0-52.0）。使用<25%的错误发现率阈值，10种代谢物，不归因于体重，区分精神分裂症患者的胰岛素浓度四分位数，并确定组间一碳代谢的变异性。与空腹胰岛素浓度较低的患者（四分位数1和2）相比，空腹胰岛素浓度较高的患者（四分位数3和4）也倾向于具有较高水平的饱和脂肪酸。这些结果说明了代谢组学的效用，以确定潜在的变量空腹胰岛素浓度在精神分裂症患者的途径。重要的是，各组间AAP暴露量无显著差异，表明目前抗精神病药物的使用可能不是通过空腹胰岛素浓度区分中年精神分裂症患者的主要因素。
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. Metabolomics analysis. 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. 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). 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.
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