Combination of UGT1A1 polymorphism and baseline plasma bilirubin levels in predicting the risk of antipsychotic-induced dyslipidemia in schizophrenia patients.

IF 3 Q2 PSYCHIATRY
Chenquan Lin, Shuangyang Zhang, Ping Yang, Bikui Zhang, Wenbin Guo, Renrong Wu, Yong Liu, Jianjian Wang, Haishan Wu, Hualin Cai
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Abstract

The prolonged usage of atypical antipsychotic drugs (AAPD) among individuals with schizophrenia often leads to metabolic side effects such as dyslipidemia. These effects not only limit one's selection of AAPD but also significantly reduce compliance and quality of life of patients. Recent studies suggest that bilirubin plays a crucial role in maintaining lipid homeostasis and may be a potential pre-treatment biomarker for individuals with dyslipidemia. The present study included 644 schizophrenia patients from two centers. Demographic and clinical characteristics were collected at baseline and 4 weeks after admission to investigate the correlation between metabolites, episodes, usage of AAPDs, and occurrence of dyslipidemia. Besides, we explored the combined predictive value of genotypes and baseline bilirubin for dyslipidemia by employing multiple PCR targeted capture techniques to sequence two pathways: bilirubin metabolism-related genes and lipid metabolism-related genes. Our results indicated that there existed a negative correlation between the changes in bilirubin levels and triglyceride (TG) levels in patients with schizophrenia. Among three types of bilirubin, direct bilirubin in the baseline (DBIL-bl) proved to be the most effective in predicting dyslipidemia in the ROC analysis (AUC = 0.627, p < 0.001). Furthermore, the odds ratio from multinomial logistic regression analysis showed that UGT1A1*6 was a protective factor for dyslipidemia (ß = -12.868, p < 0.001). The combination of baseline DBIL and UGT1A1*6 significantly improved the performance in predicting dyslipidemia (AUC = 0.939, p < 0.001). Schizophrenia patients with UGT1A1*6 mutation and a certain level of baseline bilirubin may be more resistant to dyslipidemia and have more selections for AAPD than other patients.

Abstract Image

结合 UGT1A1 多态性和血浆胆红素基线水平预测精神分裂症患者因抗精神病药引起血脂异常的风险。
精神分裂症患者长期服用非典型抗精神病药物(AAPD)往往会导致血脂异常等代谢副作用。这些副作用不仅限制了患者对非典型抗精神病药物的选择,还大大降低了患者的依从性和生活质量。最近的研究表明,胆红素在维持血脂平衡方面起着至关重要的作用,可能成为血脂异常患者治疗前的潜在生物标志物。本研究纳入了来自两个中心的 644 名精神分裂症患者。我们收集了基线和入院 4 周后的人口统计学和临床特征,以研究代谢物、发作、AAPDs 的使用和血脂异常发生之间的相关性。此外,我们还采用多种 PCR 靶向捕获技术,对胆红素代谢相关基因和脂质代谢相关基因两条通路进行测序,探讨了基因型和基线胆红素对血脂异常的综合预测价值。结果表明,精神分裂症患者胆红素水平的变化与甘油三酯(TG)水平之间存在负相关。在三种胆红素中,基线直接胆红素(DBIL-bl)在 ROC 分析中被证明是预测血脂异常最有效的指标(AUC = 0.627,p<0.05)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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